Next Article in Journal
The Tomato Feruloyl Transferase FHT Promoter Is an Accurate Identifier of Early Development and Stress-Induced Suberization
Next Article in Special Issue
Plant Tolerance to Drought Stress with Emphasis on Wheat
Previous Article in Journal
Theoretical Analyses of Turgor Pressure during Stress Relaxation and Water Uptake, and after Changes in Expansive Growth Rate When Water Uptake Is Normal and Reduced
Previous Article in Special Issue
Genome and Transcriptome Identification of a Rice Germplasm with High Cadmium Uptake and Translocation
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

The Potential of CRISPR/Cas Technology to Enhance Crop Performance on Adverse Soil Conditions

by
Humberto A. Gajardo
1,†,
Olman Gómez-Espinoza
1,2,†,
Pedro Boscariol Ferreira
3,
Helaine Carrer
3 and
León A. Bravo
1,*
1
Laboratorio de Fisiología y Biología Molecular Vegetal, Instituto de Agroindustria, Departamento de Ciencias Agronómicas y Recursos Naturales, Facultad de Ciencias Agropecuarias y Medioambiente & Center of Plant, Soil Interaction and Natural Resources Biotechnology, Scientific and Technological Bioresource Nucleus, Universidad de La Frontera, Temuco 1145, Chile
2
Centro de Investigación en Biotecnología, Escuela de Biología, Instituto Tecnológico de Costa Rica, Cartago 30101, Costa Rica
3
Department of Biological Sciences, Luiz de Queiroz College of Agriculture (ESALQ), University of São Paulo, Piracicaba 13418-900, Brazil
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Plants 2023, 12(9), 1892; https://doi.org/10.3390/plants12091892
Submission received: 31 March 2023 / Revised: 22 April 2023 / Accepted: 24 April 2023 / Published: 5 May 2023
(This article belongs to the Special Issue Abiotic Stress of Crops: Molecular Genetics and Genomics)

Abstract

:
Worldwide food security is under threat in the actual scenery of global climate change because the major staple food crops are not adapted to hostile climatic and soil conditions. Significant efforts have been performed to maintain the actual yield of crops, using traditional breeding and innovative molecular techniques to assist them. However, additional strategies are necessary to achieve the future food demand. Clustered regularly interspaced short palindromic repeat/CRISPR-associated protein (CRISPR/Cas) technology, as well as its variants, have emerged as alternatives to transgenic plant breeding. This novelty has helped to accelerate the necessary modifications in major crops to confront the impact of abiotic stress on agriculture systems. This review summarizes the current advances in CRISPR/Cas applications in crops to deal with the main hostile soil conditions, such as drought, flooding and waterlogging, salinity, heavy metals, and nutrient deficiencies. In addition, the potential of extremophytes as a reservoir of new molecular mechanisms for abiotic stress tolerance, as well as their orthologue identification and edition in crops, is shown. Moreover, the future challenges and prospects related to CRISPR/Cas technology issues, legal regulations, and customer acceptance will be discussed.

1. Introduction

Humans have depended on plants throughout their existence. Since the beginning of agriculture and the domestication of plants, agronomic management and traditional breeding have provided humanity with the modern varieties that feed the world today [1]. In contrast to the primary evolution of land plants, which occurred under unfavorable conditions (e.g., drought, fluctuating light, and temperature) [2], domestication occurred under relatively stress-free, managed conditions [3,4]. Later, during the green revolution of the mid-twentieth century, agricultural breeding radically modified plant architecture to achieve high yields [5]. As a result, the current world situation is that crop plants are much more used as food and feed than wild species [6].
Unfortunately, improvement of yield-related traits can compromise resource allocation to other traits, impairing biotic and abiotic stress tolerance [4]. This trade-off between traits hinders the capacity of crop species to mitigate the effect of changing environmental conditions [7]. Therefore, crop domestication increased the likelihood of these species being more sensitive to stresses than their wild relatives [8,9]. Within this framework, some crops can only achieve high yields with management-intense modern agricultural practices [10].
Indeed, crop production is already being affected across several regions worldwide due to climate change. The rising frequency of extreme climate events threatens further damage to food and feed production [11]. Many species are and will be affected by combinations of elevated atmospheric CO2 concentration, increased temperatures, and changing seasonal rainfall patterns [12]. Between 2013 and 2016, for example, all Caribbean islands experienced an extensive drought that pushed more than two million people into food insecurity [13], and over 50% of the crops were lost in some of these regions [14]. Additionally, drought cost the United States of America (USA) USD $250 billion in damages, one of the costliest natural disasters [15]. Aside from natural causes, agricultural practices, such as artificial fertilization, burning agricultural residues, trading, long-distance transportation, and pesticides, are responsible for significant carbon and methane emissions and environmental pollution [16]. These factors, combined, are believed to have accelerated climate change, and there is an urgent need to adopt practices to reduce the future impacts of extreme climate events [17].
Currently, abiotic stresses, such as drought, salinity, and flooding, already limit food production severely, resulting in yearly global losses of over USD $100 billion to the agricultural sector [18,19]. Coupled with the abovementioned stresses, heavy metal accumulation and nutrient deficiencies promote hostile soils for food, feed, and fuel production [18,20]. While healthy soils are pivotal to sustainable crop yield, one-third of global soils face progressive degradation [21,22]. Therefore, effective adaptation strategies are needed to mitigate the negative impacts of these soils on crop production. As such, technology-based approaches are a faster alternative to traditional techniques and management strategies [23].
Current and developing technologies that might aid in creating or enhancing stress resilience in crops include molecular-assisted plant breeding [24], genetic manipulation of traits by transgenesis or gene editing [25,26], plant-microbe engineering [27,28], de novo domestication of wild species [29], and artificial apomixis [30]. In most of these approaches, natural genetic variability and gene orthology are sources of targets for genetic manipulation to enhance crops. Natural variation in the gene, in its cis-regulatory elements, protein-coding sequence, transcription start and termination sites, and splice sites, can explain intra-species variability regarding stress tolerance, for example [31]. In addition, since the genome-wide functional characterization is unavailable for any single species, researchers use the orthology-function conjecture, wherein orthologous genes might perform similar functions in different species [32]. In both cases, genetic information from intra- or interspecies variation guides the strategies to engineer desirable traits. In this context, an under-utilized genetic resource resides in crop wild relatives and extremophytes that can be naturally tolerant to extreme conditions [33]. A broader knowledge of extremophytes’ genetics could provide even more information to the plant biotechnology toolbox.
Given this background, this review will focus on recent advances in the applications of gene editing by Clustered Regularly Interspaced Short Palindromic Repeat (CRISPR)/CRISPR-associated protein (Cas) systems in crops to cope with hostile soil conditions, such as drought, flooding, salinity, accumulation of heavy metals or toxic elements, and nutrient deficiency. Since CRISPR/Cas technologies enable the targeted and accurate genetic modification of crops without the incorporation of foreign DNA, they increase the speed of crop improvement [34] and are gaining popularity instead of classic transgenesis [35]. The use of extremophytes as reservoirs of natural variants and orthologue targets for CRISPR/Cas applications, as well as future challenges and prospects of this technology, are also discussed.

2. A Broad Overview of CRISPR/Cas Technologies in Plants

Precise genome editing techniques and applications have radically changed after the development of CRISPR/Cas technologies. The CRISPR defense systems were first noticed in bacterial genomes in 1987 [36], as part of the natural adaptive immunity in bacteria and Archaea [37,38]. In general, CRISPR/Cas-mediated immunity occurs in three steps: (1) the CRISPR-containing organism acquires deoxyribonucleic acid (DNA) or ribonucleic acid (RNA) fragments from invading bacteriophages or plasmids, then (2) it uses the stored nucleic acid to generate CRISPR RNAs (crRNAs) to (3) guide the RNA (gRNA) toward the Cas-mediated inactivation-by-cleavage of future invading viruses (Figure 1) [39].
In 2012, Jinek et al. [37] showed that the Type II CRISPR/Cas9 system of Streptococcus pyogenes could be mimicked using a single chimeric gRNA instead of the natural trans-activating crRNA (tracrRNA):crRNA duplex. Similar work was concurrently published by Gasiunas et al. (2012) [40], utilizing the CRISPR/Cas9 system from the bacterium Streptococcus thermophilus. Both publications proposed using the artificial CRISPR/Cas9 system to induce double strand breaks (DSB) at target locations in a genome of interest and to take advantage of the error-prone DSB repair pathways to generate genetic variability. Since then, CRISPR/Cas technologies have become synonymous with a relatively cheap, global gene-editing tool, and several modifications and enhancements have been made in this first decade of use [39]. In addition, since the CRISPR/Cas system is diverse, and different combinations of Cas proteins participate in the immune process depending on the host species [41], more systems and variations can be discovered.
In plants, the first five reports of CRISPR/Cas9-based genome editing were published in August 2013 and focused on demonstrating the vast versatility of the technology in the area of plant biology (proof of concept) in the model species Arabidopsis thaliana, Nicotiana benthamiana, and Oryza sativa [42,43,44,45,46]. Shortly after, the CRISPR/Cas9 system became a helpful tool for the functional annotation of plant genes [47], and the first reports of its use in model crops showed successful results in sorghum [48], wheat [49], maize [50], and soybean [51,52]. Since 2012, the number of publications related to genome editing in plants using this technology has grown exponentially (Figure 2), and 925 Research Articles were published in 2022 alone.
In the majority of these publications, the general protocol needed to achieve a CRISPR gene-edited line in plants is comprised of four main steps: (1) guide RNA design and optional design validation, (2) gene editing by expression of Cas and gRNA plant cells, (3) tissue culture for plant regeneration, and (4) evaluation of mutations by sequencing and selection of transgene-free mutated lines (Figure 3). For successful gene editing, 20 nucleotides specific to the target DNA sequence must be provided in the gRNA, applying standard RNA–DNA complementary base-pairing rules [53]. The target sites must be contiguous to a Protospacer Adjacent Motif (PAM) sequence, which varies depending on the Cas nuclease chosen [54]. In the case of the Cas9 nuclease, activity is directed to any DNA region preceding a 5′-NGG-3′ PAM sequence [55]. Several bioinformatics tools have been developed to help design gRNAs and predict their off-target potential [56]. An optional validation of the gRNA can be performed by transiently expressing the Cas/gRNA in plant protoplasts. In this stage, genomic DNA from the protoplast culture is submitted to sequencing to evaluate the presence of mutations in the desired region [48]. After proper gRNA design, a Cas/gRNA transgene is used for the genetic transformation of a target plant, using the appropriate explants and tissue culture protocols (Figure 3b). Then, the last step is to assess whether independent lines carry mutations in the target site by conventional PCR, followed by Sanger sequencing or Illumina deep sequencing. An additional step is usually added to eliminate the Cas/gRNA cassette to prevent off-target mutations induced by the nuclease’s constant expression and to reduce concerns about ‘genome-editing’ plants. Thus, one of the most used strategies to obtain mutant lines without the Cas/gRNA-expressing transgene is selection by Mendelian segregation, facilitated by visual markers, such as fluorescent proteins (Figure 3c) [57]. However, other transgene-free methods are desired, since traditional methods are laborious and time-consuming. These methods include technologies for self-elimination of transgenes, direct delivery of the Cas/gRNA ribonucleoprotein (RNP), or expression of Cas/gRNA by viral vectors [58].
Following the success of CRISPR/Cas technologies in single gene editing, several modifications were developed to enhance and diversify their use [39,59]. The multiplex CRISPR approach is a strategy that enables the editing of multiple genes in a single transformation event and uses multiple gRNAs delivered at once to achieve this goal [60,61,62,63]. Abdallah et al. [60] used three distinct gRNAs to knockout five TaSal1 genes in wheat, resulting in drought-tolerant seedlings. In another example, Lorenzo et al. [64] used 12 gRNAs, in combination, to target the knockout of 12 different growth-related genes, producing lines with enhanced yield in maize. Another approach is to produce point mutations using CRISPR base editing, which does not create breaks in the DNA. This technique uses a catalytically defective Cas enzyme, with nickase activity in a single DNA strand (nCas). Then, nCas is fused with enzymes with deaminase activity that modify the bases in the window targeted by the gRNA [54]. A different technology, Prime Editing CRISPR (CRISPR-PE), allows the insertion of sequences at the target location by providing a RNA template in the gRNA (then called pegRNA) when nCas produces a single strand break. In this technique, nCas is fused with a Reverse Transcriptase that uses the template pegRNA to insert the modification on the generated single strand [54]. Other systems, such as CRISPR-Combo [65], combine gene editing capabilities with CRISPR/Cas-based gene expression activation to boost plant genome engineering. In this case, gRNAs with different protospacer lengths determine whether the target is cleaved by the Cas9 (20 nt protospacer) or activated by the MS2-SunTag activator (15 nucleotides protospacer). The authors tested several applications of the system, and one example is the concurrent activation of AtFT, accelerating flowering time and inactivation of herbicide target genes AtALS and AtACC2. By selecting only early flowering plants, transgene-free herbicide-resistant mutants were easily detected [65]. The different CRISPR/Cas technologies can be used in genome-wide screens, which provide a targeted approach in generating a large number of mutants that can be selected by their phenotype in a desired condition [66]. The identification of causal genes is then easily performed by using the gRNAs as barcodes in deep sequencing [67]. Gaillochet et al. [66] and Pan et al. [68] review CRISPR screening in plants in more detail, demonstrating its potential to identify genes and generate varieties tolerant to multiple stresses, since mutants can be selected by phenotype after they are established. The toolbox of CRISPR/Cas technologies is still expanding, and this plethora of strategies to manipulate plant genomes shows promise to generate transgene-free stress-resilient crops.
From this perspective, genome manipulation techniques have always supported basic and applied crop research and are crucial for modern agricultural production [69]. Although these techniques require prior physiology and molecular genetics knowledge of the plant species under study, at least 42 plant species have been successfully edited by CRISPR/Cas technologies [70]. An attractive characteristic of CRISPR/Cas systems is their success in genome editing polyploid species, which is the case for most crop and biofuel species [71]. With the theoretical knowledge and the know-how of gene-editing techniques, custom modifications can be targeted to specific genes to improve desired traits in a highly predictive manner. The following sections summarize stress-related genetic discoveries in crops achieved by CRISPR/Cas and discuss the potential of these technologies for engineering crops with higher tolerance to extreme conditions affecting the soil–plant interface.

3. Advances in Engineering Commercial Crop Genomes to Cope with Different Hostile Soil Conditions

The decline in soil quality poses a significant challenge to agriculture [72], and CRISPR/Cas systems can be valuable tools to address abiotic stress-related traits in plants. These traits are often controlled by regulatory genes, which can be knocked out or down to improve tolerance [73]. However, natural environments typically present a combination of different stresses simultaneously, and while most progress has been made in studying individual stresses, genome-wide association studies and transcriptomic information have identified numerous candidate genes involved in stress tolerance regulation that are potential targets for CRISPR/Cas applications [74]. Cross-species analysis of stress responses shows a conserved core genetic response to stresses [75,76,77], which may help develop genotype-independent strategies to cope with a changing climate. CRISPR-edited single genes that confer tolerance to individual stresses can be used as a starting point for a multiplexed approach, where combinations of mutations can confer combined stress tolerance.

3.1. Drought Stress Tolerance

Water deficiency is a chronic abiotic crop stress that impacts plant growth and development, constituting about 70% of potential crop yield and productivity losses globally [78]. Drought exists either due to significantly less rainfall or a significant decrease in the quantity of moisture, and it is considered a substantial abiotic stress, hindering agriculture and forestry [78]. Indeed, modeled climate change projections show an even worse scenario for drought, independent of the decrease or increase in greenhouse emissions in most of the world [79,80]. Soil drought can have significant negative impacts on crops by reducing plant growth, altering plant architecture, delaying or inhibiting plant development, reducing reproductive success, and increasing susceptibility to diseases and pests [78].
Plant responses to drought might be classified in five critical processes: sensing, avoidance, tolerance, scape, and recovery. After drought sensing, two pathways can be activated: an abscisic acid (ABA)-dependent pathway or an ABA-independent pathway, triggering the activation of transcription factors and specific drought responsive genes [81,82]. Drought avoidance involves morpho-physiological changes, such as stomatal closure, leaf area or leaf number reduction, wax synthesis, and increased root systems [82]. On the other hand, drought tolerance involves mechanisms to cope with severe drought at different phenological stages, such as changes in stomatal density, gene expression of drought responsive genes, and synthesis of osmoprotectans. In addition, the reduction of photosynthesis rate under drought leads to an imbalance in energy, inducing the production of Reactive Oxygen Species (ROS), which are signaling molecules of stress that can damage the plant cellular machinery [83]. An additional tolerance mechanism is the biosynthesis of antioxidant molecules and expression of the enzymatic antioxidant system to ameliorate the oxidative cellular stress triggered by drought conditions [83]. Short life cycles or early flowering, on the other hand, are examples of escape mechanism to drought, and they could be interesting targets for gene editing. Finally, recovery, the capacity of the plant to survive a severe drought event, involves processes of cellular protection, repair, and stress priming to promote photosynthesis recovery, and it has been extensively studied in resurrection plants [84]. These cellular processes are all targets for genetic manipulation, and several elements have already been studied by CRISPR/Cas technologies. A comprehensive summary of research that employed CRISPR/Cas-directed mutagenesis strategies to study drought stress tolerance in crops is presented in Table 1. All of the studies have proven to either enhance or reduce performance of the mutant plants in comparison to the wild type by experiments in growth chambers, greenhouses, or in the field. Proof-of-concept studies and cross-species gene validation studies were excluded from Table 1 for brevity.
Most studies employing CRISPR/Cas genome editing to study drought resistance so far have occurred in rice varieties (Table 1). An in-frame deletion of a DROUGHT AND SALT TOLERANCE (DST) gene using CRISPR/Cas9 in O. sativa subsp. indica caused deletion of the C-terminal EAR motif in the protein product, which produced plants with broader leaves and reduced stomatal density in comparison with the wild type, resulting in enhanced water retention under dehydration stress [102]. The rice CONSTANS-like transcription factor, Ghd2, regulates drought-induced leaf senescence, and its knockout (KO) by CRISPR/Cas9 enhances drought tolerance by delaying the senescence process [98]. While these examples are of mutations that increased tolerance to drought, several CRISPR studies revealed genes whose KO impairs tolerance. The KO of gene OsNPF8.1, a nitrate transporter, reduced tolerance to drought and salt stress, as well as lower grain yield with less N accumulation in comparison with the control genotype [125].
Another important characteristic of CRISPR/Cas technologies is their ability to KO microRNAs, previously difficult to achieve by classic transgenesis due to their short sequence [161]. Um et al. (2022) [113] used CRISPR/Cas9 to generate KO rice lines for osa-MIR171, which showed sensitivity to drought in comparison to the wild type. With additional experiments, the authors show that osa-MIR171 regulates the expression of flavonoid biosynthesis genes, which are known participants of stress response pathways [162]. Contrastingly, the CRISPR/Cas9 KO of osa-miR535 in rice enhances the tolerance of plants to dehydration and PEG stresses in comparison to unedited plants [100]. Interestingly, osa-mir535 is a highly conserved miRNA present in more than 50 plant species [163], which makes it an interesting target to engineer drought tolerance in crops.
In Solanum lycopersicum (tomato), pipecolic acid (Pip) biosynthetic gene, SlALD1, CRISPR-generated mutants show elevated drought resistance compared with the wild-type, a phenotype associated with CO2 assimilation, photosystems activities, and antioxidant enzyme activities [136]. Still, in tomatoes, the KO of the jasmonic acid-responsive transcription factor SlLBD40 by CRISPR/Cas9 enhanced drought tolerance in comparison to unedited plants [140]. Similarly, in maize, CRISPR/Cas9 KO mutants of another LBD transcription factor, ZmLDB5, have higher grain yield under drought stress compared to the wild type and do not exhibit differences in well-watered conditions [151]. In soybean, a quadruple KO of circadian rhythm transcription factors GmLHY1a, GmLHY1b, GmLHY2a, and GmLHY2b produced plants with enhanced drought tolerance and delayed maturity in comparison to the unedited genotype [89]. It is important to note that, although most CRISPR/Cas research so far has focused on model crops, such as rice and maize, other species are being explored, including oilseed rape [85], cucumber [86], strawberry [87], alfalfa [94], tobacco [95,96,97], poplar [133,134,135], potato [144], wheat [145,146,147,148], and grape [149] (Table 1). Collectively, these studies provide a growing database of mutant alleles that modulate responses to drought in crops, which could be used to breed stress-resilient cultivars. Furthermore, based on orthology principles, similar mutations could be effective across different species.

3.2. Flooding and Waterlogging Tolerance

Although drought and flood are viewed as opposing stresses and are usually studied separately, they share molecular pathways of tolerance, and both stresses reduce energy-consuming processes, facilitating the allocation of energetic resources to stress adaptation [164,165]. Similar to plants in drought stress, shoots need to adapt to dehydration caused by impaired root hydraulics and leaf water loss after a flood event [165]. Due to climate change, there is evidence suggesting that compound extremes, such as the co-occurrence of droughts and floods, are increasing in many parts of the world, including the United States, Europe, and Asia [166]. When the El-Niño South Oscillation perseveres, for example, it leads to prolonged flooding in some areas [80], and drought–flood abrupt alternation is becoming more unpredictable [167]. The co-occurrence of droughts and floods can amplify their impacts and create complex challenges for ecosystems, agriculture, water resources, and human settlements.
In addition to flooding, characterized by the presence of standing water above the soil surface, another phenomenon of excess water in the soil is waterlogging, which is the lack of drainage [168]. Both flooding and waterlogging can cause significant damage to crops and soil, but they have different impacts on plant growth and development [169]. While some plants may be adapted to tolerate occasional flooding, most plants are highly sensitive to waterlogging and can suffer from reduced growth, root damage, and even death [170]. Unfortunately, until the publication of this review, no studies involving CRISPR/Cas have tackled waterlogging, and only two examples of specific flood-related CRISPR studies were found (Table 2). In both cases, the evaluated gene KOs present reduced tolerance to floods. The OsGF14h gene encodes a 14-3-3 protein in weedy O. sativa subsp. japonica cultivar WR04-6, and its KO mutant in this background is sensitive to anaerobic conditions imposed by flooding stress. Interestingly, already sensitive modern cultivars SN9816 and Nipponbare show six polymorphic sites in the coding sequence of OsGF14h, which produce an incomplete isoform of the 14-3-3 protein [171]. The second study knocked out the ethylene-response factor-like gene SUB1A in a flooding-tolerant cultivar of O. sativa subsp. indica, Chiherang-Sub1, resulting in sensitivity to the flooding experiment, similar to the wild-type cultivar Chiherang [172]. Another interesting study by Ye et al. [173] verified that CRISPR-mediated KO of gene OsCBL10 is embryo-lethal, but natural variations in the gene’s promoter were associated with flooding tolerance.
In summary, since drought and flood may coexist and possibly share regulatory mechanisms in plants, it is urgent to revisit already characterized mutants tolerant to drought concerning flood tolerance. This would be an effective strategy to accelerate the discovery of genes conferring this trait. Furthermore, genetic resources for flood tolerance might be found in crop wild relatives. All major crop families possess members that show adaptation to seasonal wetlands, including members of genera Oryza and Zea (Poaceae), Lotus (Fabaceae), Solanum (Solanaceae), and Rorippa (Brassicaceae), which can provide insight into plastic survival strategies lost during crop domestication or selection for production agriculture [174].

3.3. Salinity Stress Tolerance

Another global problem in agriculture, affecting over 400 million ha worldwide, with direct implications on crop yield and food security, is soil salinity [72]. This phenomenon can be caused by irrigation with saline water or over-irrigation [175], excessive fertilization [176], conversion of natural habitats to agricultural land [177,178], geological factors [179], climate effects, sea level increase, flooding, or tsunamis [180,181]. The effects of salinity on crops have been extensively studied at the physiological and molecular levels, including osmotic and toxic consequences on different phenological stages [182,183,184].
Physiological consequences of salinity stress include ion toxicity, which impairs the uptake and transport of essential nutrients [185], osmotic stress, which reduces water potential in cells [186], oxidative stress [187], changes in the expression of genes involved in growth and development [188], and alteration of hormones impacting growth and stress responses [189]. At the early phase of perception, sodium/hydrogen exchangers (NHXs) and high-affinity potassium transporters (HKTs) import Na+ ions and activate a Na+ sensing module [190]. Then, early signaling is activated, involving K+, Ca2+, cGMP, phospholipids, ROS, and protein kinases that can activate hormones and gene responses downstream [191].
This signal cascade allows the expression of different adaptive mechanisms, such as growth and developmental response, ion exclusion and sequestration, and the synthesis of compatible solutes to cope with osmotic stress [183]. Some tolerant plant species have developed specific mechanisms to excrete salt ions through specialized structures [192]. Other species can induce the synthesis of osmoprotectant metabolites, such as proline, glycine betaine, γ-GABA, spermidine, spermine, putrescine, mannitol, sucrose, trehalose, and enzymatic and non-enzymatic antioxidant molecules [193,194,195,196].
Salinity stress is the second most common abiotic stress with available CRISPR/Cas data, with many of the same genes also implicated in drought tolerance (Table 3, Figure 4). There are five genes with CRISPR mutants that enhance both drought and salinity tolerance: OsPPR035 and OsPPR406 [109], OsDST [102], osa-MIR535 [100], and OsIPK1 [105], all in rice. There are also four genes with mutants having reduced stress tolerance: OsNPF8.1 [125] and OsDIP1 [119], in rice, as well as GmMYB118 [91] and GmCOL1a [90], in soybean. This overlap is largely explained by the shared genetic networks involved in the ABA-dependent and ABA-independent pathways of the abiotic stress response [197]. The CRISPR/Cas9-generated in-frame deletion of 33 bp in gene OsIPK1 controlled the synthesis of phytic acid and conferred salt and drought tolerance without apparent penalties in yield [105]. The expression of ABA-independent TF OsDREB1A is upregulated in both stresses in osipk1_1 mutants, corroborating the overlap between shared stress regulation.
In addition to the shared genes, 16 other studies are summarized in Table 3. One of these studies in rice generated 14 CRISPR-mediated mutations in gene OsRR22, a B-type response regulator TF involved in cytokinin signal transduction and metabolism [198]. These mutations confer salt tolerance at the seedling and mature stages compared with wild-type plants, without effects on other agronomic traits [199]. In soybean, CRISPR/Cas9 was used to validate the participation of TF GmNAC06 in salt stress, since KO mutants display poor performance under experimental conditions in comparison to the wild-type and overexpression lines [200]. Contrastingly, enhanced performance in laboratory and field salinity stress experiments was found for double and quadruple KO soybean mutants gmaitr36 and gmaitr23456, respectively [201]. This was achieved by a multiplexed approach of CRISPR/Cas9-mediated KO of GmAITR genes, which are ABA-induced transcription repressors involved in regulating ABA signaling [202].
Table 3. Studies employing CRISPR/Cas on genes related to salinity stress. TF: Transcription Factor; ABA: Abscisic Acid; KO = Knockout; KD = Knockdown; I.N.F. = Information Not Found.
Table 3. Studies employing CRISPR/Cas on genes related to salinity stress. TF: Transcription Factor; ABA: Abscisic Acid; KO = Knockout; KD = Knockdown; I.N.F. = Information Not Found.
SpeciesTarget LocusPathway/FunctionEffect on ToleranceResultReference
Cucurbita moschataCmoPIP1-4Plasma membrane intrinsic proteinReducedKO[203]
Glycine maxGmAITR2
GmAITR3
GmAITR4
GmAITR5
GmAITR6
ABA-induced transcription repressorEnhancedKO[201]
E2Photoperiodic floweringEnhancedKO[204]
GmCOL1aCONSTANS-like TFReducedKO[90]
GmMYB118MYB TFReducedAmino acid change[91]
GmNAC06NAC TFReducedI.N.F.[200]
Hordeum vulgareHVP10Vacuolar H+-pyrophosphataseReducedKO[205]
Oryza sativaosa-MIR535Drought-induced miRNAEnhancedKO[100]
OsbHLH024bHLH TFEnhancedKO[206]
OsDSTZn Finger TFEnhancedDomain deletion[102]
OsIPK1Inositol 1,3,4,5,6-pentakisphosphate 2-kinaseEnhanced11-amino acid deletion[105]
OsPPR035Chloroplast RNA editingEnhancedKO[109]
OsPPR406Chloroplast RNA editingEnhancedKO[109]
OsRR22B-type RR TFEnhancedKO[199]
OsVDEXanthophyll cycle/Violaxanthin deoxidaseEnhancedKD[207]
BEAR1bHLH TFReducedKD[208]
OsDIP1TF-interacting proteinReducedKO[119]
OsGLYI3glyoxalaseReducedKO[209]
OsNPF8.1Peptide transporterReducedKO[125]
OsWRKY28WRKY TFReducedKO[210]
OsWRKY54WRKY TFReducedKO[211]
Solanum lycopersicumAIT1.1ABA transporterEnhancedKO[212]
SlABIG1HD-ZIP II TFEnhancedKO[213]
SlHyPRP1Hybrid Proline-rich proteinEnhancedDomain deletion[214]
Put2Polyamine uptake transporterReducedKO[215]

3.4. Heavy Metals or Toxic Element Tolerance

Heavy metals occur naturally in the Earth’s crust, and the release of these metals into the soil can occur due to natural or anthropogenic processes. Some of the natural causes of heavy metals in soils are the weathering of parent rock, releasing trace amounts of metals, transport of heavy metals from one location to another during floods, landslides or wind erosion, and atmospheric deposition from volcanic emissions, among others [216]. The biological activity of microorganisms, plants, and animals can also concentrate heavy metals in the soil through biological processes, such as uptake and bioaccumulation [217]. Anthropogenic heavy metal accumulation in soils is far more significant than natural sources, and the use of agrochemicals is the most impactful [217]. Fertilizers, pesticides, and herbicides can contain these harmful molecules, as well as cause soil acidity and erosion, which intensifies their accumulation in soils and possibly contaminates the water table [218,219].
The accumulation of heavy metals and toxic elements in plant tissues can affect their nutritional quality, making them unsuitable for consumption or even harmful to human health. This is a significant concern in the food industry and public health because of the reported diseases associated with the consumption of heavy metal-contaminated foods and exposure to contaminated environments [220,221]. In mining countries, such as Chile, the accumulation of heavy metals derived from the copper industry, for example, has generated the contamination of soils and groundwater in localities considered nowadays as "sacrifice zones", such as Puchuncaví and Quintero-Ventanas Bay [222]. Besides, other mining-associated activities or agricultural practices, such as smelting, industrial exhaust, irrigation with mining wastewater, natural presence in some agricultural soils, and applying fertilizers and pesticides with heavy metal traces, have generated a similar problem worldwide [223]. The primary heavy metals and metalloids found in contaminated soils are copper (Cu), zinc (Zn), lead (Pb), cadmium (Cd), mercury (Hg), and arsenic (As). In southern China, for instance, the analysis of rice samples from contaminated or very industrialized areas showed a high percentage (56 to 87%) of samples contaminated with Cd [224]. Additionally, since rice is the second-most produced staple food worldwide, its contamination generates concern and health risks in different countries [223].
Since heavy metals and toxic elements can have negative impacts on crop growth and development, they can accumulate in plant tissues and lead to reduced yield, quality, and even plant death [225]. These contaminants can also affect nutrient uptake and interfere with photosynthesis, respiration, and transpiration [226]. Physiological and molecular impacts on plants may lead to growth inhibition, chlorosis, necrosis, reduced photosynthesis, and decreased crop yield. These elements can also affect the uptake and transport of essential nutrients, leading to nutrient imbalances and deficiencies. At the molecular level, heavy metals and toxic elements can induce oxidative stress, disrupt cellular homeostasis, alter gene expression, and impair enzymatic activities [227]. Additionally, heavy metals and toxic elements can alter the composition and diversity of the plant-associated microbial communities, affecting plant–microbe interactions and nutrient cycling in the soil [228].
Some metal elements are essential micronutrients for the enzymatic cellular machinery to function. However, under an unbalance of heavy metal homeostasis, some plant species have developed mechanisms to deal with the rise of their concentrations in different cellular compartments [229]. Among the mechanisms involved, we can mention the expression of Heavy Metal ATPases (HMA) proteins [230], Zn and Fe-regulated Membrane Transporter (ZIP) proteins [231], Cation Diffusion Facilitator (CDF) proteins [232], Cation/hydrogen Exchangers (CAX) proteins [233], High-affinity Copper Transport (COPT) proteins [234], Natural Resistant Associated Macrophage (NRAMPS) proteins [235], the bHLH TFs [236], and low molecular weight chelators and subcellular sequesters, such as metallothioneins, phytochelatins, amino acids, nicotinamides, glutathione, and defensins [237,238].
Most of the genes encoding the expression of the aforementioned proteins are potential targets for CRISPR/Cas9 modification to modulate heavy metal tolerance. Although major efforts have been performed using the advances in omics tools, to identify molecular targets controlling heavy metal tolerance in plants [239], few studies show heavy metal tolerance modification for major crops (Table 4). The modulation of a plant’s response to this stress depends on its application. For phytoremediation, the goal is to increase the uptake of heavy metals from highly contaminated lands, while avoiding accumulation in final food products requires a decrease in the uptake of these molecules. In rice, for instance, the KO of Cd/Mn transporter OsNRAMP5 confers Cd tolerance to a wide range of external Cd concentrations, producing shoots with sufficient nutrients and grains with lower Cd accumulation [240]. The KO of OsNRAMP5 in two O. sativa subsp. japonica varieties generated lines with decreased accumulation of Cd in aerial organs, but reduced yield in comparison to unedited plants in both hydroponic and field experiments [241]. Similarly, KO of the rice Low Cadmium (OsLCD) gene also diminished Cd accumulation in the shoot, but maintained yield under high Cd concentrations in comparison to the wild genotype [242]. Another Cd-related gene, Sl1, was knocked out in tomatoes, and edited plants displayed increased Cd accumulation in plant tissues, as well as increased ROS activity in comparison to the wild-type and overexpression lines [243].
The R2R3 MYB transcription factor OsARM1 regulates arsenic(As)-associated transporter genes, and KO lines generated by CRISPR/Cas9 improve the tolerance of rice to As in comparison to the wild-type [244]. A similar proof of concept used the KO of Antioxidant Protein 1 (OsATX1) gene, a Cu chaperone in rice, which induced an increase in Cu concentration in roots, thereby decreasing the root-to-shoot translocation of Cu [245]. The CRISPR/Cas technology has also been used to deal with other toxic element contamination in soils, such as radioactive Cs+. The inactivation of Cs+ transporter OsHAK1 in rice by CRISPR/Cas9 dramatically reduced the uptake of Cs+ in highly Cs+ contaminated lands from Fukushima, Japan [246].
Table 4. Studies employing CRISPR/Cas on genes related to flooding heavy metal and toxic element stresses. TF: Transcription Factor; KO = Knockout.
Table 4. Studies employing CRISPR/Cas on genes related to flooding heavy metal and toxic element stresses. TF: Transcription Factor; KO = Knockout.
SpeciesTarget LocusPathway/FunctionEffect on ToleranceCRISPR ResultReference
Oryza sativaOsHAK1Cs+-permeable transporterCesium resistantKO[246]
OsATX1Cu chaperoneDosage-dependent tolerantKO[245]
osa-MIR535Drought-induced miRNAsEnhancedKO[247]
OsARM1R2R3 MYB TF regulator of As-associated transporters genesEnhancedKO[244]
OsLCDUnknown, Cd relatedEnhancedKO[242]
OsLCT1Low affinity cation transporterEnhancedKO[248]
OsNRAMP1Cd and Mn transporterEnhancedKO[249]
OsNRAMP5Cd and Mn transporterEnhancedKO[240,248]
OsPMEI12Pectin MethylesteraseEnhancedKO[250]
Solanum lycopersicumSl1E3 Ubiquitin ligaseReducedKO[243]

3.5. Tolerance to Barrenness

Nutrient deficiencies in soils can be triggered by a variety of factors, such as soil pH and soil organic matter, which influence the types and the abundance of essential nutrients, respectively [251]. Other factors, such as soil texture, can affect nutrient availability. Soil compaction can affect the nutrient and water access by the root system, and excessive plant uptake causes nutrient depletion in soils that are heavily cropped or in which fertilization is inadequate [252]. Agricultural practices that can lead to soil barrenness or degradation include the overuse of chemical fertilizers, leading to nutrient imbalances and soil acidification [253], as well as monocultures, which can deplete soil nutrients, leading to reduced yields and increased susceptibility to pests and diseases [254]. Moreover, soil erosion results in a loss of soil organic matter, nutrients, and soil structure, leading to reduced productivity and increased vulnerability to drought and flooding [255]. In addition, pesticide use can harm beneficial microorganisms and disrupt soil food webs, leading to reduced soil fertility and productivity over time [256]. Additionally, the use of fertilizers to boost the yield of crops has allowed for maintaining the requirements for global food security during the years past the green revolution. However, this practice is under the threat of actual climate change and geopolitical sceneries [257,258]. However, the environmental pollution and ecological degradation generated by the indiscriminate use of fertilizers [259], as well as the fertilizers’ price increment generated by recent events, such as the Russian-Ukraine conflict [258], will raise the cost of the farmer’s production, making this practice unsustainable over time, as we know today. Finally, natural disasters, such as floods, droughts, and wildfires, can also contribute to soil barrenness by altering soil properties and reducing nutrient availability [260].
Nutrient use efficiency (NUE) is the capability of a crop to take up the nutrients from soil, transport them, assimilate them, and use them to maximize its yield. NUE is a very complex trait, involving several plant functions and metabolic pathways. The polyploidy nature of major crops makes their manipulation a big challenge for plant researchers. Nevertheless, some studies have been performed to improve NUE using transgenic [261], siRNA [262], and gene over-expression approaches [263,264], which have shown impressive advances focused on NUE. Nowadays, physiological and genomic information can be used to select targets for CRISPR/Cas NUE improvement, showing promising results. Recent thorough reviews were published on potential targets for nutrient use efficiency [265,266,267], and more CRISPR-based studies might benefit from this knowledge. In total, eight studies are summarized in Table 5, including one in barley, five in rice, one in Populus, and one in wheat.
For example, a CRISPR cytosine base editing system (CBE) was used to generate a C-T point mutation in gene OsNRT1.1B of Japonica rice cv. Nipponbare, causing amino acid conversion T327M [268]. This mutation corresponds to an allele difference between rice varieties Nipponbare (T327) and IR24 (M327) [269], and the base editing conversion of the Nipponbare allele results in better NUE in comparison to the wild type [268,269]. Interestingly, the mutated DST protein in the Indica rice cv. MT1010 dst mutant shows enhanced drought and salinity tolerance [102], while its CRISPR KO in Japonica rice cv. ZH11 impairs NUE in comparison with the wild type, showing reduced growth in nitrogen-poor substrates [108].
In another major staple food crop, wheat, lines with mutant alleles of Abnormal Cytokinin Response 1 Repressor 1 Protein (TaARE1) were generated by CRISPR/Cas9, showing increased NUE, delayed senescence, and higher grain yield than the wild-type [270]. The same orthologous gene in barley, HvARE1, was mutated by CRISPR/Cas9, generating improved NUE in mutant lines 1are1-E-7-6 (amino acid substitution E78G) and 2are1-K-4 (substitution N205D) [271]. Recently, the overexpression of the PdGNC transcription factor in poplar was found to increase nitrate uptake, remobilization, and assimilation, improving overall NUE in this species, which was validated using CRISPR/Cas9 mutants [272].
Table 5. Studies employing CRISPR/Cas on genes related to nutrient deficiency stress. TF: Transcription Factor; KO = Knockout.
Table 5. Studies employing CRISPR/Cas on genes related to nutrient deficiency stress. TF: Transcription Factor; KO = Knockout.
SpeciesTarget LocusPathway/FunctionEffect on ToleranceResultReference
Hordeum vulgareHvARE1Abnormal cytokinin response 1 repressor 1 proteinEnhancedAmino acid change[271]
Oryza sativaNRT1.1BNitrogen transporter geneEnhancedBase editing[268]
OsDSTZinc finger TFReducedDomain deletion[108]
OsNPF3.1Nitrate/Peptide transporterReducedKO[273]
OsNPF8.1Nitrate/Peptide transporterReducedKO[125]
OsNR1.2Nitrate/Peptide transporterReducedKO[108]
Populus clone 717-1B4 (Populus tremula × Populus alba)PdGNCNitrate uptakeReducedKO[133]
Triticum aestivumTaARE1-A
TaARE1-B
TaARE1-D
Abnormal cytokinin response 1 repressor 1 proteinEnhancedKO[270]

4. Extremophytes: Genetic Reservoirs for CRISPR/Cas Applications

Although evolutionarily distant species may exhibit different transcriptional responses to stress, they share core genetic regulatory elements [75]. In this context, studying extremophytes’ genetics poses a great opportunity to find potential targets for genetic manipulation, leading to enhanced stress-related traits. Extremophiles can be defined as organisms capable of dealing with extreme conditions of pH, temperature, pressure, salinity, high concentrations of gasses (such as CO2), metals, and ionizing radiation, for example [274,275]. The first well-studied extremophiles are microorganisms, which have already been extensively used in the bioprospection of potentially valuable enzymes, mainly in the biofuel industry [276]. A classic example is the DNA polymerase isolated from the thermophilic bacterium Thermus aquaticus [277], an essential enzyme in molecular biology research. Another example is the use of extremophile microbiota that induce drought/salinity resistance in plants, which have been isolated from deserts [278] and Antarctica [279]. Although there is high interest in extremozymes, bioactive compounds, and cultured extremophiles for direct use in the industry [280], little has been explored in plant genetic engineering.
Extremophyte species grow in harsh conditions, which are limiting to unadapted species. For instance, propagules of sub-Antarctic species may arrive in more extreme Antarctic regions, but few can establish new individuals that survive more than one season, and none can establish populations without human intervention [281]. This unique feature of extremophytes defies the trade-off between growth and stress resilience, since they can properly balance their resources, obtained from photosynthesis, to adapt to the extreme climatic factors to complete their life cycles [282]. In this context, deserts (warm and cold), salt pans, geothermal springs, and high mountains, common niches of extremophytes, serve as excellent model conditions to study plant performance on hostile soils [283].
Unfortunately, studies on the molecular and physiological determinants of the trade-off between growth and stress tolerance are scarce, particularly in non-model species. This gap leaves a significant source of variation for photosynthetic functioning and stress tolerance unexplored. Therefore, the unique opportunity provided by extremophytes to investigate how they differentially invest their photosynthetic resources to adapt their life cycles under extreme climatic factors can be leveraged to understand the mechanistic bases of the trade-off between productivity and stress tolerance [282,284]. Moreover, extremophytes offer a promising source of valuable traits for the biotechnology industry to improve crop productivity, as well as at least to maintain it in agricultural regions affected by climate change scenarios [280,285]. As the climate changes, extremophytes can provide insights into the future. Discovering the molecular and biochemical adaptations employed by these plants can enhance our understanding of how plants, in general, will respond to climate change [286].
Interestingly, even though molecular mechanisms controlling plant physiology during abiotic stress have been amply reviewed in model plants and crops [287,288], our knowledge of the molecular mechanisms that support extremophytes success is more limited [275]. Some of the best-studied extremophytes are the resurrection plants, for their potential as ideal models to engineer crops with enhanced drought tolerance [289,290]. Similarly, many studies have been performed on halophyte plants, including highly salt-tolerant close relatives of A. thaliana, allowing for direct comparisons of stress tolerance mechanisms [3]. Since established protocols for greenhouse cultivation, in vitro culture, and transformation or gene editing of extremophytes are scarce, functional genetic studies have mostly focused on the heterologous expression of extremophile proteins in model plants [31]. For instance, HIGH-AFFINITY POTASSIUM TRANSPORTER (HKT) genes from the halophytes Thellungiella salsuginea [291], Eutrema parvula [292], and Suaeda salsa [293] have been expressed ectopically in Arabidopsis plants, and they confer salt tolerance in comparison to the wild-type protein.
Transcriptome sequencing is another strategy to study the reprogrammed metabolism observed in some extremophytes, enabling target trait selection in close relative crops. All major crop families possess members that show adaptation to hostile soils, including members of genera Oryza and Zea (Poaceae), Lotus (Fabaceae), Solanum (Solanaceae), and Arabidopsis, Rorippa (Brassicaceae) [174,294,295]. These species can provide insights into plastic survival strategies to hostile conditions, which were lost during crop domestication or selection for intensive agriculture. The identification of the genetic factors controlling stress tolerance traits in extremophytes can guide the search for orthologs in closely related crops, which would then be modified by CRISPR/Cas technologies (Figure 5).
For instance, the transcriptomic analysis of Populus euphratica, a desert tree related to the commercial species poplar, showed a reprogrammed metabolism under salt stress, where genes involved in ABA regulation are differentially expressed [296]. Thereby, negative regulators of stress tolerance previously identified in extremophytes could be knocked down using a CRISPR/Cas system. Meanwhile, the sequences of promoters or positively regulatory regions of stress response genes could be modified, as was shown for the generation of HDR-based editing to produce a salt-tolerant SlHKT1;2 alleles in tomato utilizing the CRISPR/Cpf1-geminiviral replicon technique [297]. In another example, CRISPR/Cas9 KO of metallophyte Sedum pumbizincicola Heavy Metal ATPase 1 (SpHMA1) helped to characterize the function of SpHMA1 in protecting PSII from Cd toxicity [298]. Therefore, there is still much to be explored and discovered in these extremophile species that can be used for crops to face the challenges of climate change and hostile soils.

5. Challenges and Prospects

5.1. Combined Stresses

Although great advances have been made in the study of stresses, most of these discoveries assessed plant responses to single stresses. In natural conditions, the combination of stresses is usually the norm, and climate change will also affect the intensity and frequency of these compound stresses [166]. Given these statements, it is possible to assume that combined stresses complicate the equation for stress resilience engineering. However, elegant systems, such as BREEDIT [64], aim to solve this problem by editing a combination of genes with multiplex CRISPR, resulting in additive roles in stress or yield traits. In their proof-of-concept study, a knock-out of 48 different genes involved in plant growth was conducted, combining 12 genes simultaneously, and generating over 1000 different edited lines with potential enhancements in yield [64]. If a similar strategy is used to knock out multiple genes associated with the suppression of stress tolerance, the combinations of such mutations could help establish a multi-tolerant plant line. Furthermore, sophisticated systems, such as CRISPR-Combo [65], couple gene editing with gene activation, allowing for fine-tuned metabolic engineering.

5.2. Technological Limitations and Potential Solutions

CRISPR/Cas systems have been widely acknowledged for their potential to improve crops through gene insertion, removal, point mutation, and gene replacement. However, their use in agricultural research is still in the early stages, with most reports constrained to proof-of-concept findings [299]. Even though CRISPR has been successfully applied in at least 42 plant species [70], there is still a need for a global mechanism that is genotype-independent. Several efforts are underway to improve the limitations of CRISPR/Cas technologies, such as limited PAM sites, off-target mutations, low HDR efficacy, and time consumption due to the Agrobacterium-mediated transformation system [300]. For instance, several mutated Cas enzymes opened the possibility of more diverse PAM sites with lower off-target potential [39], and slightly more efficient HDR could be achieved with CRISPR/Cas12a [301].
Regarding transformation limitations, advances have been achieved in both Agrobacterium-mediated and other methods, such as the use of viral vectors. The latter, although efficient, is limited by the size of the Cas-encoding sequences, which are very large [302]. Recently discovered Cas12f1 is considerably smaller, allowing for the use of viral vectors to produce gene editing without transgene integration [54]. These strategies hold promise for expanding the application of CRISPR/Cas9 in agriculture and addressing some of its current limitations. An important step forward in monocotyledonous and recalcitrant plant transformation, mediated by Agrobacterium, is the use of morphogenetic factors to induce somatic cells into initiating embryogenesis, thus partly circumventing the need for strenuous callus induction and regeneration studies [303,304]. Another important discovery is the newly described “cut-dip-budding” (CDB) system, which enables gene editing in previously recalcitrant species, which is the case for many crops and wild relatives [305]. The CBD system relies on the ability of plants to generate basal shoots from adventitious buds in roots, and it was already applied successfully in species where transformation was either difficult or impossible. An advantage of the CBD system is the absence of in vitro or sterile culture, since all steps can be performed directly in soil [305]. These technologies are promising for the application of CRISPR in wild relatives or extremophyte species to study gene function and to apply these discoveries in crop plants.

5.3. Field Evaluation of CRISPR-Modified Crops

The usefulness of the CRISPR/Cas editing techniques must be demonstrated before the large-scale distribution of any new variety possessing them [306]. However, as shown in Table S1, most studies on hostile soil tolerance in plants modified by CRISPR/Cas systems were only evaluated in the laboratory or greenhouse. Therefore, verifying whether results can be translated to crop plants grown in the field is crucial [307]. In addition, field trials provide a tremendous amount of otherwise unknown information on how plants respond to environmental changes under agricultural systems [308]. Unfortunately, the diverse landscape of legislation regarding gene-edited plants has hindered large-scale field trials, and most such tests have occurred only in China [309]. In 2018, the first field trial of a CRISPR/Cas9 gene-edited crop, Camelina sativa, began in Europe at the Rothamsted Research in the UK and provided a wealth of essential data and enabled the evaluation of the potential of a new trait [310]. During the experiment, the UK Department for Environment, Food & Rural Affairs reclassified gene-edited crops as GMOs, and the next field trial only occurred in 2021 [307]. Later, in 2021, field tests of low-asparagine gene-edited wheat were performed in this same research field and were essential to confirm the results observed in the laboratory [311]. Additionally, in 2021, Lee and Hutton (2021) [306] conducted field trials during three consecutive seasons using CRISPR-driven jointless pedicel, as well as fresh-market tomatoes, without detecting significant differences in fruit size yield between CRISPR-modified tomatoes and WT tomatoes [306]. Despite these studies, further field trials conducted across a broader range of regions are imperative to authenticate the scientific effectiveness of gene-edited plants and instill greater assurance and security for both producers and end consumers.

5.4. Regulation and Customer Acceptance

Important limitations on CRISPR/Cas-modified crops are the legal regulation of plant genome editing and consumer acceptance. Although CRISPR crops are being developed and grown globally, this trend is accompanied by legal, ethical, and policy debates. The technical limitations of CRISPR and whether existing GMO regulations should apply to CRISPR-edited crops are key issues [312]. In the scientific community, there is a belief that mutations generated by CRISPR/Cas9 are no different from those induced by nature or conventional breeding. Thus, plants created through this technology should not undergo the same regulatory processes as conventional GMOs. However, on a global scale, opinions differ, and some countries believe that CRISPR-generated crops should undergo the same regulations as GMOs before entering the market [313,314].
For instance, the United States and the European Union have different approaches to CRISPR-edited crops. The former is more permissive because they do not have to undergo the same regulatory process as GMOs, while in the European Union, they are considered GMOs. However, several countries have already regulated that plants generated through CRISPR with only InDels or homologous inserts can be excluded from GMO regulation [312,314,315,316]. Hence, the international community is considering whether certain CRISPR-edited crops can be excluded from regulatory oversight and what safety data would be required for CRISPR-edited crops to be regulated in specific countries.
The success and adoption of gene-edited foods depend ultimately on consumer acceptance, which has been a problem for GMO foods due to misinformation. Consumers worldwide display limited understanding, misconceptions, and unfamiliarity with GMO food products [317]. Consumer acceptance of gene-edited foods varies across countries. In China, 45% of respondents (n = 835) agreed that gene-edited plant products should be allowed, compared to 36% for transgenic plant products [318]. In Brazil, producers (n = 37) are prone to planting transgenic beans (84%), and consumers (n = 100) are willing to include them in their diets (79%) [319]. In the UK (n = 490) and Switzerland (n = 505), participants expressed higher acceptance levels for genome editing than for transgenic modification. Acceptance depends on perceived benefits, scientific uncertainty, and location [320]. Acceptance levels for these technologies depend mainly on whether the application is believed to be beneficial, how scientific uncertainty is perceived, and where they reside [35,316]. Surveys, such as these, and the amount of safety data required, will affect the overall cost of regulation, an essential factor to consider when bringing new CRISPR plants to market [314,321].

6. Concluding Remarks

The worldwide deterioration of soil quality has emerged as a critical challenge for agriculture, compounded by the escalating impact of climate change. This looming crisis poses a significant risk to food security, particularly as we approach the year 2050. Unfortunately, there is no single solution to address the issue of hostile soils or to ensure food production in the future. Instead, an integrated, multidisciplinary approach is necessary, leveraging specific tools and solutions to mitigate the detrimental effects of hostile soils on agriculture. By combining these solutions from diverse approaches, we can potentially safeguard agriculture and ensure global food security. These tools include CRISPR/Cas technologies, which enable the precise editing of crop genomes to develop plants that are more tolerant to the stresses of hostile soils. In the past decade, this technique has demonstrated its efficacy in accurately editing the genomes of various organisms, including plants.
As reviewed here, several scientific studies have provided concrete evidence of the effectiveness of CRISPR/Cas technologies for developing crops that are tolerant to hostile soils. These studies have demonstrated successful applications of the technology in improving plant tolerance to stressors, such as drought, heavy metals, salinity, and NUE. As a result, CRISPR/Cas systems are increasingly being considered viable solutions to these agricultural challenges. Notably, a significant amount of research on using CRISPR to develop stress-tolerant crops is being conducted in China, suggesting a potential technological advantage in this area due to its legal status on gene editing organisms.
Although CRISPR technologies for genome engineering in plants are not infallible, ongoing technical advancements are addressing its limitations. Meanwhile, the regulatory landscape is becoming more lenient, allowing for greater openness towards CRISPR-mutated crops that are transgene-free and exempt from traditional GMO regulations. Additionally, consumer acceptance of CRISPR-modified products is predicted to increase, and evidence supports the continued use of this technology for plant breeders. To achieve crops tolerant to future challenges, we suggest leveraging CRISPR technology alongside advances in sequencing and the search for new genetic targets in extremophytes. These developments, alongside novel management strategies and biotechnologies, provide promising solutions for ensuring stable food security by 2050.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/plants12091892/s1, Table S1: Studies employing CRISPR/Cas on genes related to drought, flooding and waterlogging, salinity, heavy metal and toxic elements, and barrenness tolerance, extended.

Author Contributions

H.A.G., O.G.-E. and P.B.F. conceived and designed the manuscript, conducted the literature research, compiled tables, drew figures, and drafted the manuscript. L.A.B. and H.C. acquired funding and reviewed and edited the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by the project: Fundação de Amparo à Pesquisa do Estado de São Paulo—Universidad de La Frontera (2020/07578-1). H.A.G. was funded by ANID National Doctorate Scholarship 21181972. O.G.-E. was funded by ANID Fondecyt Postdoctorado N°3230521.

Data Availability Statement

No new data were created or analyzed in this study. Data sharing is not applicable to this article.

Acknowledgments

The authors thank Charles L. Guy for his valuable observations and English edition of the manuscript.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Schaal, B. Plants and People: Our Shared History and Future. Plants People Planet 2019, 1, 14–19. [Google Scholar] [CrossRef]
  2. De Vries, J.; Archibald, J.M. Plant Evolution: Landmarks on the Path to Terrestrial Life. New Phytol. 2018, 217, 1428–1434. [Google Scholar] [CrossRef] [PubMed]
  3. Bechtold, U. Plant Life in Extreme Environments: How Do You Improve Drought Tolerance? Front. Plant Sci. 2018, 9, 543. [Google Scholar] [CrossRef] [PubMed]
  4. Figueroa-Macías, J.P.; García, Y.C.; Núñez, M.; Díaz, K.; Olea, A.F.; Espinoza, L. Plant Growth-Defense Trade-Offs: Molecular Processes Leading to Physiological Changes. Int. J. Mol. Sci. 2021, 22, 693. [Google Scholar] [CrossRef] [PubMed]
  5. Bailey-Serres, J.; Parker, J.E.; Ainsworth, E.A.; Oldroyd, G.E.D.; Schroeder, J.I. Genetic Strategies for Improving Crop Yields. Nature 2019, 575, 109–118. [Google Scholar] [CrossRef] [PubMed]
  6. Perrino, E.V.; Perrino, P. Crop Wild Relatives: Know How Past and Present to Improve Future Research, Conservation and Utilization Strategies, Especially in Italy: A Review. Genet. Resour. Crop Evol. 2020, 67, 1067–1105. [Google Scholar] [CrossRef]
  7. Dwivedi, S.L.; Reynolds, M.P.; Ortiz, R. Mitigating Tradeoffs in Plant Breeding. iScience 2021, 24, 102965. [Google Scholar] [CrossRef]
  8. Koziol, L.; Rieseberg, L.H.; Kane, N.; Bever, J.D. Reduced drought tolerance during domestication and the evolution of weediness results from tolerance–growth trade-offs. Evolution 2012, 66, 3803–3814. [Google Scholar] [CrossRef]
  9. Mayrose, M.; Kane, N.C.; Mayrose, I.; Dlugosch, K.M.; Rieseberg, L.H. Increased Growth in Sunflower Correlates with Reduced Defences and Altered Gene Expression in Response to Biotic and Abiotic Stress. Mol. Ecol. 2011, 20, 4683–4694. [Google Scholar] [CrossRef]
  10. Meyer, R.S.; Duval, A.E.; Jensen, H.R. Patterns and Processes in Crop Domestication: An Historical Review and Quantitative Analysis of 203 Global Food Crops. New Phytol. 2012, 196, 29–48. [Google Scholar] [CrossRef]
  11. Holleman, C.; Rembold, F.; Crespo, O.; Conti, V. The Impact of Climate Variability and Extremes on Agriculture and Food Security—An Analysis of the Evidence and Case Studies. Background Paper for The State of Food Security and Nutrition in the World 2018; Agricultural Development Economics Technical Study N°4; FAO: Rome, Italy, 2020. [Google Scholar] [CrossRef]
  12. Sperry, J.S.; Venturas, M.D.; Todd, H.N.; Trugman, A.T.; Anderegg, W.R.L.; Wang, Y.; Tai, X. The Impact of Rising CO2 and Acclimation on the Response of US Forests to Global Warming. Proc. Natl. Acad. Sci. USA 2019, 116, 25734–25744. [Google Scholar] [CrossRef]
  13. Herrera, D.; Ault, T. Insights from a New High-Resolution Drought Atlas for the Caribbean Spanning 1950–2016. J. Clim. 2017, 30, 7801–7825. [Google Scholar] [CrossRef]
  14. Herrera, D.A.; Ault, T.R.; Fasullo, J.T.; Coats, S.J.; Carrillo, C.M.; Cook, B.I.; Williams, A.P. Exacerbation of the 2013–2016 Pan-Caribbean Drought by Anthropogenic Warming. Geophys. Res. Lett. 2018, 45, 10–619. [Google Scholar] [CrossRef] [PubMed]
  15. Ault, T.R. On the Essentials of Drought in a Changing Climate. Science 2020, 368, 256–260. [Google Scholar] [CrossRef]
  16. Balogh, J.M. The Role of Agriculture in Climate Change: A Global Perspective. Int. J. Energy Econ. Policy 2020, 10, 401–408. [Google Scholar] [CrossRef]
  17. Zurek, M.; Hebinck, A.; Selomane, O. Climate Change and the Urgency to Transform Food Systems. Science 2022, 376, 1416–1421. [Google Scholar] [CrossRef]
  18. Shabala, S.; Bose, J.; Fuglsang, A.T.; Pottosin, I. On a Quest for Stress Tolerance Genes: Membrane Transporters in Sensing and Adapting to Hostile Soils. J. Exp. Bot. 2016, 67, 1015–1031. [Google Scholar] [CrossRef] [PubMed]
  19. FAO. The Impact of Disasters and Crises on Agriculture and Food Security; FAO: Rome, Italy, 2021; ISBN 978-92-5-134071-4. [Google Scholar]
  20. Jiménez-Mejía, R.; Medina-Estrada, R.I.; Carballar-Hernández, S.; del Carmen Orozco-Mosqueda, M.; Santoyo, G.; Loeza-Lara, P.D. Teamwork to Survive in Hostile Soils: Use of Plant Growth-Promoting Bacteria to Ameliorate Soil Salinity Stress in Crops. Microorganisms 2022, 10, 150. [Google Scholar] [CrossRef]
  21. Rojas, R.V.; Achouri, M.; Maroulis, J.; Caon, L. Healthy Soils: A Prerequisite for Sustainable Food Security. Environ. Earth Sci. 2016, 75, 180. [Google Scholar] [CrossRef]
  22. Perri, S.; Molini, A.; Hedin, L.O.; Porporato, A. Contrasting Effects of Aridity and Seasonality on Global Salinization. Nat. Geosci. 2022, 15, 375–381. [Google Scholar] [CrossRef]
  23. Coomes, O.T.; Barham, B.L.; MacDonald, G.K.; Ramankutty, N.; Chavas, J.P. Leveraging Total Factor Productivity Growth for Sustainable and Resilient Farming. Nat. Sustain. 2019, 2, 22–28. [Google Scholar] [CrossRef]
  24. Younis, A.; Ramzan, F.; Ramzan, Y.; Zulfiqar, F.; Ahsan, M.; Lim, K.B. Molecular Markers Improve Abiotic Stress Tolerance in Crops: A Review. Plants 2020, 9, 1374. [Google Scholar] [CrossRef]
  25. Das, D.; Singha, D.L.; Paswan, R.R.; Chowdhury, N.; Sharma, M.; Reddy, P.S.; Chikkaputtaiah, C. Recent Advancements in CRISPR/Cas Technology for Accelerated Crop Improvement. Planta 2022, 255, 109. [Google Scholar] [CrossRef] [PubMed]
  26. Gao, C. Genome Engineering for Crop Improvement and Future Agriculture. Cell 2021, 184, 1621–1635. [Google Scholar] [CrossRef] [PubMed]
  27. Hakim, S.; Naqqash, T.; Nawaz, M.S.; Laraib, I.; Siddique, M.J.; Zia, R.; Mirza, M.S.; Imran, A. Rhizosphere Engineering With Plant Growth-Promoting Microorganisms for Agriculture and Ecological Sustainability. Front. Sustain. Food Syst. 2021, 5, 617157. [Google Scholar] [CrossRef]
  28. Arif, I.; Batool, M.; Schenk, P.M. Plant Microbiome Engineering: Expected Benefits for Improved Crop Growth and Resilience. Trends Biotechnol. 2020, 38, 1385–1396. [Google Scholar] [CrossRef]
  29. Gasparini, K.; dos Reis Moreira, J.; Peres, L.E.P.; Zsögön, A. De Novo Domestication of Wild Species to Create Crops with Increased Resilience and Nutritional Value. Curr. Opin. Plant Biol. 2021, 60, 102006. [Google Scholar] [CrossRef]
  30. Xiong, J.; Hu, F.; Ren, J.; Huang, Y.; Liu, C.; Wang, K. Synthetic Apomixis: The Beginning of a New Era. Curr. Opin. Biotechnol. 2023, 79, 102877. [Google Scholar] [CrossRef]
  31. Yolcu, S.; Alavilli, H.; Lee, B. Natural Genetic Resources from Diverse Plants to Improve Abiotic Stress Tolerance in Plants. Int. J. Mol. Sci. 2020, 21, 8567. [Google Scholar] [CrossRef]
  32. Gabaldón, T.; Koonin, E.V. Functional and Evolutionary Implications of Gene Orthology. Nat. Rev. Genet. 2013, 14, 360–366. [Google Scholar] [CrossRef]
  33. Kapazoglou, A.; Gerakari, M.; Lazaridi, E.; Kleftogianni, K.; Sarri, E.; Tani, E.; Bebeli, P.J. Crop Wild Relatives: A Valuable Source of Tolerance to Various Abiotic Stresses. Plants 2023, 12, 328. [Google Scholar] [CrossRef]
  34. Rasheed, A.; Gill, R.A.; Hassan, M.U.; Mahmood, A.; Qari, S.; Zaman, Q.U.; Ilyas, M.; Aamer, M.; Batool, M.; Li, H.; et al. A Critical Review: Recent Advancements in the Use of CRISPR/Cas9 Technology to Enhance Crops and Alleviate Global Food Crises. Curr. Issues Mol. Biol. 2021, 43, 1950–1976. [Google Scholar] [CrossRef]
  35. Strobbe, S.; Wesana, J.; Van Der Straeten, D.; De Steur, H. Public Acceptance and Stakeholder Views of Gene Edited Foods: A Global Overview. Trends Biotechnol. 2023, in press. [CrossRef]
  36. Jansen, R.; van Embden, J.D.A.; Gaastra, W.; Schouls, L.M. Identification of Genes That Are Associated with DNA Repeats in Prokaryotes. Mol. Microbiol. 2002, 43, 1565–1575. [Google Scholar] [CrossRef]
  37. Jinek, M.; Chylinski, K.; Fonfara, I.; Hauer, M.; Doudna, J.A.; Charpentier, E. A Programmable Dual-RNA–Guided DNA Endonuclease in Adaptive Bacterial Immunity. Science 2012, 337, 816–821. [Google Scholar] [CrossRef]
  38. Wang, H.; La Russa, M.; Qi, L.S. CRISPR/Cas9 in Genome Editing and Beyond. Annu. Rev. Biochem. 2016, 85, 227–264. [Google Scholar] [CrossRef] [PubMed]
  39. Wang, J.Y.; Doudna, J.A. CRISPR Technology: A Decade of Genome Editing Is Only the Beginning. Science 2023, 379, eadd8643. [Google Scholar] [CrossRef] [PubMed]
  40. Gasiunas, G.; Barrangou, R.; Horvath, P.; Siksnys, V. Cas9–CrRNA Ribonucleoprotein Complex Mediates Specific DNA Cleavage for Adaptive Immunity in Bacteria. Proc. Natl. Acad. Sci. USA 2012, 109, E2579–E2586. [Google Scholar] [CrossRef] [PubMed]
  41. Makarova, K.S.; Koonin, E.V. Annotation and Classification of CRISPR-Cas Systems. Methods Mol. Biol. 2015, 1311, 47–75. [Google Scholar] [CrossRef] [PubMed]
  42. Bortesi, L.; Fischer, R. The CRISPR/Cas9 System for Plant Genome Editing and Beyond. Biotechnol. Adv. 2015, 33, 41–52. [Google Scholar] [CrossRef] [PubMed]
  43. Feng, Z.; Zhang, B.; Ding, W.; Liu, X.; Yang, D.-L.; Wei, P.; Cao, F.; Zhu, S.; Zhang, F.; Mao, Y.; et al. Efficient Genome Editing in Plants Using a CRISPR/Cas System. Cell Res. 2013, 23, 1229–1232. [Google Scholar] [CrossRef]
  44. Li, J.-F.; Norville, J.E.; Aach, J.; McCormack, M.; Zhang, D.; Bush, J.; Church, G.M.; Sheen, J. Multiplex and Homologous Recombination–Mediated Genome Editing in Arabidopsis and Nicotiana benthamiana Using Guide RNA and Cas9. Nat. Biotechnol. 2013, 31, 688–691. [Google Scholar] [CrossRef]
  45. Shan, Q.; Wang, Y.; Li, J.; Zhang, Y.; Chen, K.; Liang, Z.; Zhang, K.; Liu, J.; Xi, J.J.; Qiu, J.-L.; et al. Targeted Genome Modification of Crop Plants Using a CRISPR-Cas System. Nat. Biotechnol. 2013, 31, 686–688. [Google Scholar] [CrossRef] [PubMed]
  46. Xie, K.; Yang, Y. RNA-Guided Genome Editing in Plants Using a CRISPR–Cas System. Mol. Plant 2013, 6, 1975–1983. [Google Scholar] [CrossRef]
  47. Hilscher, J.; Bürstmayr, H.; Stoger, E. Targeted Modification of Plant Genomes for Precision Crop Breeding. Biotechnol. J. 2017, 12, 1600173. [Google Scholar] [CrossRef] [PubMed]
  48. Jiang, W.; Zhou, H.; Bi, H.; Fromm, M.; Yang, B.; Weeks, D.P. Demonstration of CRISPR/Cas9/SgRNA-Mediated Targeted Gene Modification in Arabidopsis, Tobacco, Sorghum and Rice. Nucleic Acids Res. 2013, 41, e188. [Google Scholar] [CrossRef]
  49. Upadhyay, S.K.; Kumar, J.; Alok, A.; Tuli, R. RNA-Guided Genome Editing for Target Gene Mutations in Wheat. G3 Genes Genomes Genet. 2013, 3, 2233–2238. [Google Scholar] [CrossRef] [PubMed]
  50. Liang, Z.; Zhang, K.; Chen, K.; Gao, C. Targeted Mutagenesis in Zea mays Using TALENs and the CRISPR/Cas System. J. Genet. Genom. 2014, 41, 63–68. [Google Scholar] [CrossRef]
  51. Jacobs, T.B.; LaFayette, P.R.; Schmitz, R.J.; Parrott, W.A. Targeted Genome Modifications in Soybean with CRISPR/Cas9. BMC Biotechnol. 2015, 15, 16. [Google Scholar] [CrossRef]
  52. Cai, Y.; Chen, L.; Liu, X.; Sun, S.; Wu, C.; Jiang, B.; Han, T.; Hou, W. CRISPR/Cas9-Mediated Genome Editing in Soybean Hairy Roots. PLoS ONE 2015, 10, e0136064. [Google Scholar] [CrossRef]
  53. Hsu, P.D.; Lander, E.S.; Zhang, F. Development and Applications of CRISPR-Cas9 for Genome Engineering. Cell 2014, 157, 1262–1278. [Google Scholar] [CrossRef]
  54. Capdeville, N.; Schindele, P.; Puchta, H. Getting Better All the Time—Recent Progress in the Development of CRISPR/Cas-Based Tools for Plant Genome Engineering. Curr. Opin. Biotechnol. 2023, 79, 102854. [Google Scholar] [CrossRef] [PubMed]
  55. Waddington, S.N.; Privolizzi, R.; Karda, R.; O’Neill, H.C. A Broad Overview and Review of CRISPR-Cas Technology and Stem Cells. Curr. Stem. Cell Rep. 2016, 2, 9–20. [Google Scholar] [CrossRef] [PubMed]
  56. Li, C.; Chu, W.; Gill, R.A.; Sang, S.; Shi, Y.; Hu, X.; Yang, Y.; Zaman, Q.U.; Zhang, B. Computational Tools and Resources for CRISPR/Cas Genome Editing. Genom. Proteom. Bioinform. 2022, in press. [CrossRef]
  57. Gao, X.; Chen, J.; Dai, X.; Zhang, D.; Zhao, Y. An Effective Strategy for Reliably Isolating Heritable and Cas9 -Free Arabidopsis Mutants Generated by CRISPR/Cas9-Mediated Genome Editing. Plant Physiol. 2016, 171, 1794–1800. [Google Scholar] [CrossRef]
  58. He, Y.; Mudgett, M.; Zhao, Y. Advances in Gene Editing without Residual Transgenes in Plants. Plant Physiol. 2022, 188, 1757–1768. [Google Scholar] [CrossRef]
  59. Wada, N.; Osakabe, K.; Osakabe, Y. Expanding the Plant Genome Editing Toolbox with Recently Developed CRISPR–Cas Systems. Plant Physiol. 2022, 188, 1825–1837. [Google Scholar] [CrossRef]
  60. Abdallah, N.A.; Elsharawy, H.; Abulela, H.A.; Thilmony, R.; Abdelhadi, A.A.; Elarabi, N.I. Multiplex CRISPR/Cas9-Mediated Genome Editing to Address Drought Tolerance in Wheat. GM Crops Food 2022. [Google Scholar] [CrossRef] [PubMed]
  61. Yang, N.; Yan, L.; Zheng, Z.; Zhang, Y.; Zhan, H.; Tian, Y.; Zhang, T.; Li, R.; Gong, X.; Xu, M.; et al. Editing Gene Families by CRISPR/Cas9: Accelerating the Isolation of Multiple Transgene-Free Null Mutant Combinations with Much Reduced Labor-Intensive Analysis. Plant Biotechnol. J. 2022, 20, 241–243. [Google Scholar] [CrossRef]
  62. Liu, J.L.; Chen, M.M.; Chen, W.Q.; Liu, C.M.; He, Y.; Song, X.F. A CASE Toolkit for Easy and Efficient Multiplex Transgene-Free Gene Editing. Plant Physiol. 2022, 188, 1843–1847. [Google Scholar] [CrossRef]
  63. Singh, J.; Sharma, D.; Brar, G.S.; Sandhu, K.S.; Wani, S.H.; Kashyap, R.; Kour, A.; Singh, S. CRISPR/Cas Tool Designs for Multiplex Genome Editing and Its Applications in Developing Biotic and Abiotic Stress-Resistant Crop Plants. Mol. Biol. Rep. 2022, 49, 11443–11467. [Google Scholar] [CrossRef]
  64. Lorenzo, C.D.; Debray, K.; Herwegh, D.; Develtere, W.; Impens, L.; Schaumont, D.; Vandeputte, W.; Aesaert, S.; Coussens, G.; De Boe, Y.; et al. BREEDIT: A Multiplex Genome Editing Strategy to Improve Complex Quantitative Traits in Maize. Plant Cell 2023, 35, 218–238. [Google Scholar] [CrossRef]
  65. Pan, C.; Li, G.; Malzahn, A.A.; Cheng, Y.; Leyson, B.; Sretenovic, S.; Gurel, F.; Coleman, G.D.; Qi, Y. Boosting Plant Genome Editing with a Versatile CRISPR-Combo System. Nat. Plants 2022, 8, 513–525. [Google Scholar] [CrossRef]
  66. Gaillochet, C.; Develtere, W.; Jacobs, T.B. CRISPR Screens in Plants: Approaches, Guidelines, and Future Prospects. Plant Cell 2021, 33, 794–813. [Google Scholar] [CrossRef] [PubMed]
  67. Liu, H.-J.; Jian, L.; Xu, J.; Zhang, Q.; Zhang, M.; Jin, M.; Peng, Y.; Yan, J.; Han, B.; Liu, J.; et al. High-Throughput CRISPR/Cas9 Mutagenesis Streamlines Trait Gene Identification in Maize. Plant Cell 2020, 32, 1397–1413. [Google Scholar] [CrossRef]
  68. Pan, C.; Li, G.; Bandyopadhyay, A.; Qi, Y. Guide RNA Library-Based CRISPR Screens in Plants: Opportunities and Challenges. Curr. Opin. Biotechnol. 2023, 79, 102883. [Google Scholar] [CrossRef]
  69. Raman, R. The Impact of Genetically Modified (GM) Crops in Modern Agriculture: A Review. GM Crops Food 2017, 8, 195–208. [Google Scholar] [CrossRef] [PubMed]
  70. Rao, Y.; Yang, X.; Pan, C.; Wang, C.; Wang, K. Advance of Clustered Regularly Interspaced Short Palindromic Repeats-Cas9 System and Its Application in Crop Improvement. Front. Plant Sci. 2022, 13, 839001. [Google Scholar] [CrossRef]
  71. Shan, S.; Mavrodiev, E.V.; Li, R.; Zhang, Z.; Hauser, B.A.; Soltis, P.S.; Soltis, D.E.; Yang, B. Application of CRISPR/Cas9 to Tragopogon (Asteraceae), an Evolutionary Model for the Study of Polyploidy. Mol. Ecol. Resour. 2018, 18, 1427–1443. [Google Scholar] [CrossRef] [PubMed]
  72. FAO; ITPS. Status of the World’s Soil Resources (SWSR)—Main Report; Food and Agriculture Organization of the United Nations; Intergovernmental Technical Panel on Soils: Rome, Italy, 2015. [Google Scholar]
  73. Ma, X.; Zhu, Q.; Chen, Y.; Liu, Y.-G. CRISPR/Cas9 Platforms for Genome Editing in Plants: Developments and Applications. Mol. Plant 2016, 9, 961–974. [Google Scholar] [CrossRef]
  74. Husaini, A.M. High-Value Pleiotropic Genes for Developing Multiple Stress-Tolerant Biofortified Crops for 21st-Century Challenges. Heredity 2022, 128, 460–472. [Google Scholar] [CrossRef]
  75. Hartmann, A.; Berkowitz, O.; Whelan, J.; Narsai, R. Cross-Species Transcriptomic Analyses Reveals Common and Opposite Responses in Arabidopsis, Rice and Barley Following Oxidative Stress and Hormone Treatment. BMC Plant Biol. 2022, 22, 62. [Google Scholar] [CrossRef]
  76. Tan, Q.W.; Lim, P.K.; Chen, Z.; Pasha, A.; Provart, N.; Arend, M.; Nikoloski, Z.; Mutwil, M. Cross-Stress Gene Expression Atlas of Marchantia Polymorpha Reveals the Hierarchy and Regulatory Principles of Abiotic Stress Responses. Nat. Commun. 2023, 14, 986. [Google Scholar] [CrossRef]
  77. Wu, T.Y.; Goh, H.Z.; Azodi, C.B.; Krishnamoorthi, S.; Liu, M.J.; Urano, D. Evolutionarily Conserved Hierarchical Gene Regulatory Networks for Plant Salt Stress Response. Nat. Plants 2021, 7, 787–799. [Google Scholar] [CrossRef]
  78. Bashir, S.S.; Hussain, A.; Hussain, S.J.; Wani, O.A.; Zahid Nabi, S.; Dar, N.A.; Baloch, F.S.; Mansoor, S. Plant Drought Stress Tolerance: Understanding Its Physiological, Biochemical and Molecular Mechanisms. Biotechnol. Biotechnol. Equip. 2021, 35, 1912–1925. [Google Scholar] [CrossRef]
  79. Satoh, Y.; Yoshimura, K.; Pokhrel, Y.; Kim, H.; Shiogama, H.; Yokohata, T.; Hanasaki, N.; Wada, Y.; Burek, P.; Byers, E.; et al. The Timing of Unprecedented Hydrological Drought under Climate Change. Nat. Commun. 2022, 13, 3287. [Google Scholar] [CrossRef]
  80. Ndehedehe, C.E.; Ferreira, V.G.; Adeyeri, O.E.; Correa, F.M.; Usman, M.; Oussou, F.E.; Kalu, I.; Okwuashi, O.; Onojeghuo, A.O.; Getirana, A.; et al. Global Assessment of Drought Characteristics in the Anthropocene. Resour. Environ. Sustain. 2023, 12, 100105. [Google Scholar] [CrossRef]
  81. Oguz, M.C.; Aycan, M.; Oguz, E.; Poyraz, I.; Yildiz, M. Drought Stress Tolerance in Plants: Interplay of Molecular, Biochemical and Physiological Responses in Important Development Stages. Physiologia 2022, 2, 180–197. [Google Scholar] [CrossRef]
  82. Shelake, R.M.; Kadam, U.S.; Kumar, R.; Pramanik, D.; Singh, A.K.; Kim, J.Y. Engineering Drought and Salinity Tolerance Traits in Crops through CRISPR-Mediated Genome Editing: Targets, Tools, Challenges, and Perspectives. Plant Commun. 2022, 3, 100417. [Google Scholar] [CrossRef] [PubMed]
  83. Razi, K.; Muneer, S. Drought Stress-Induced Physiological Mechanisms, Signaling Pathways and Molecular Response of Chloroplasts in Common Vegetable Crops. Crit. Rev. Biotechnol. 2021, 41, 669–691. [Google Scholar] [CrossRef] [PubMed]
  84. VanBuren, R.; Wai, C.M.; Giarola, V.; Župunski, M.; Pardo, J.; Kalinowski, M.; Grossmann, G.; Bartels, D. Core Cellular and Tissue-specific Mechanisms Enable Desiccation Tolerance in Craterostigma. Plant J. 2023, 114, 231–245. [Google Scholar] [CrossRef] [PubMed]
  85. Wu, J.; Yan, G.; Duan, Z.; Wang, Z.; Kang, C.; Guo, L.; Liu, K.; Tu, J.; Shen, J.; Yi, B.; et al. Roles of the Brassica Napus DELLA Protein BnaA6.RGA, in Modulating Drought Tolerance by Interacting With the ABA Signaling Component BnaA10.ABF2. Front. Plant Sci. 2020, 11, 577. [Google Scholar] [CrossRef]
  86. Peng, Y.; Chen, L.; Zhu, L.; Cui, L.; Yang, L.; Wu, H.; Bie, Z. CsAKT1 Is a Key Gene for the CeO 2 Nanoparticle’s Improved Cucumber Salt Tolerance: A Validation from CRISPR-Cas9 Lines. Environ. Sci. Nano 2022, 9, 4367–4381. [Google Scholar] [CrossRef]
  87. Han, J.; Li, X.; Li, W.; Yang, Q.; Li, Z.; Cheng, Z.; Lv, L.; Zhang, L.; Han, D. Isolation and Preliminary Functional Analysis of FvICE1, Involved in Cold and Drought Tolerance in Fragaria Vesca through Overexpression and CRISPR/Cas9 Technologies. Plant Physiol. Biochem. 2023, 196, 270–280. [Google Scholar] [CrossRef] [PubMed]
  88. Zhong, X.; Hong, W.; Shu, Y.; Li, J.; Liu, L.; Chen, X.; Islam, F.; Zhou, W.; Tang, G. CRISPR/Cas9 Mediated Gene-Editing of GmHdz4 Transcription Factor Enhances Drought Tolerance in Soybean (Glycine max [L.] Merr.). Front. Plant Sci. 2022, 13, 988505. [Google Scholar] [CrossRef]
  89. Wang, K.; Bu, T.; Cheng, Q.; Dong, L.; Su, T.; Chen, Z.; Kong, F.; Gong, Z.; Liu, B.; Li, M. Two Homologous LHY Pairs Negatively Control Soybean Drought Tolerance by Repressing the Abscisic Acid Responses. New Phytol. 2021, 229, 2660–2675. [Google Scholar] [CrossRef]
  90. Xu, C.; Shan, J.; Liu, T.; Wang, Q.; Ji, Y.; Zhang, Y.; Wang, M.; Xia, N.; Zhao, L. CONSTANS-LIKE 1a Positively Regulates Salt and Drought Tolerance in Soybean. Plant Physiol. 2022, 191, 2427–2446. [Google Scholar] [CrossRef] [PubMed]
  91. Du, Y.-T.; Zhao, M.-J.; Wang, C.-T.; Gao, Y.; Wang, Y.-X.; Liu, Y.-W.; Chen, M.; Chen, J.; Zhou, Y.-B.; Xu, Z.-S.; et al. Identification and Characterization of GmMYB118 Responses to Drought and Salt Stress. BMC Plant Biol. 2018, 18, 320. [Google Scholar] [CrossRef]
  92. Yang, C.; Huang, Y.; Lv, P.; Antwi-Boasiako, A.; Begum, N.; Zhao, T.; Zhao, J. NAC Transcription Factor GmNAC12 Improved Drought Stress Tolerance in Soybean. Int. J. Mol. Sci. 2022, 23, 12029. [Google Scholar] [CrossRef]
  93. Yang, C.; Huang, Y.; Lv, W.; Zhang, Y.; Bhat, J.A.; Kong, J.; Xing, H.; Zhao, J.; Zhao, T. GmNAC8 Acts as a Positive Regulator in Soybean Drought Stress. Plant Sci. 2020, 293, 110442. [Google Scholar] [CrossRef]
  94. Singer, S.D.; Burton Hughes, K.; Subedi, U.; Dhariwal, G.K.; Kader, K.; Acharya, S.; Chen, G.; Hannoufa, A. The CRISPR/Cas9-Mediated Modulation of Squamosa Promoter-Binding Protein-like 8 in Alfalfa Leads to Distinct Phenotypic Outcomes. Front. Plant Sci. 2022, 12, 3203. [Google Scholar] [CrossRef] [PubMed]
  95. Li, G.; Ma, Y.; Wang, X.; Cheng, N.; Meng, D.; Chen, S.; Wang, W.; Wang, X.; Hu, X.; Yan, L.; et al. CRISPR/Cas9 Gene Editing of NtAITRs, a Family of Transcription Repressor Genes, Leads to Enhanced Drought Tolerance in Tobacco. Int. J. Mol. Sci. 2022, 23, 15268. [Google Scholar] [CrossRef] [PubMed]
  96. Xu, L.; Gao, Q.; Feng, J.; Xu, Y.; Jiang, J.; Deng, L.; Lu, Y.; Zeng, W.; Xing, J.; Xiang, H.; et al. Physiological and Phosphoproteomic Analyses Revealed That the NtPOD63 L Knockout Mutant Enhances Drought Tolerance in Tobacco. Ind. Crops Prod. 2023, 193, 116218. [Google Scholar] [CrossRef]
  97. Gao, Y.; Yang, J.; Duan, W.; Ma, X.; Qu, L.; Xu, Z.; Yang, Y.; Xu, J. NtRAV4 Negatively Regulates Drought Tolerance in Nicotiana Tabacum by Enhancing Antioxidant Capacity and Defence System. Plant Cell Rep. 2022, 41, 1775–1788. [Google Scholar] [CrossRef] [PubMed]
  98. Liu, J.; Shen, J.; Xu, Y.; Li, X.; Xiao, J.; Xiong, L. Ghd2, a CONSTANS -like Gene, Confers Drought Sensitivity through Regulation of Senescence in Rice. J. Exp. Bot. 2016, 67, 5785–5798. [Google Scholar] [CrossRef] [PubMed]
  99. Zhao, W.; Wang, X.; Zhang, Q.; Zheng, Q.; Yao, H.; Gu, X.; Liu, D.; Tian, X.; Wang, X.; Li, Y.; et al. H3K36 Demethylase JMJ710 Negatively Regulates Drought Tolerance by Suppressing MYB48-1 Expression in Rice. Plant Physiol. 2022, 189, 1050–1064. [Google Scholar] [CrossRef]
  100. Yue, E.; Cao, H.; Liu, B. OsmiR535, a Potential Genetic Editing Target for Drought and Salinity Stress Tolerance in Oryza sativa. Plants 2020, 9, 1337. [Google Scholar] [CrossRef] [PubMed]
  101. Zhang, Y.; Wang, X.; Luo, Y.; Zhang, L.; Yao, Y.; Han, L.; Chen, Z.; Wang, L.; Li, Y. OsABA8ox2, an ABA Catabolic Gene, Suppresses Root Elongation of Rice Seedlings and Contributes to Drought Response. Crop J. 2020, 8, 480–491. [Google Scholar] [CrossRef]
  102. Santosh Kumar, V.V.; Verma, R.K.; Yadav, S.K.; Yadav, P.; Watts, A.; Rao, M.V.; Chinnusamy, V. CRISPR-Cas9 Mediated Genome Editing of Drought and Salt Tolerance (OsDST) Gene in Indica Mega Rice Cultivar MTU1010. Physiol. Mol. Biol. Plants 2020, 26, 1099–1110. [Google Scholar] [CrossRef]
  103. Ogata, T.; Ishizaki, T.; Fujita, M.; Fujita, Y. CRISPR/Cas9-Targeted Mutagenesis of OsERA1 Confers Enhanced Responses to Abscisic Acid and Drought Stress and Increased Primary Root Growth under Nonstressed Conditions in Rice. PLoS ONE 2020, 15, e0243376. [Google Scholar] [CrossRef]
  104. Gu, H.; Zhang, K.; Chen, J.; Gull, S.; Chen, C.; Hou, Y.; Li, X.; Miao, J.; Zhou, Y.; Liang, G. OsFTL4, an FT-like Gene, Regulates Flowering Time and Drought Tolerance in Rice (Oryza sativa L.). Rice 2022, 15, 47. [Google Scholar] [CrossRef]
  105. Jiang, M.; Liu, Y.; Li, R.; Li, S.; Tan, Y.; Huang, J.; Shu, Q. An Inositol 1,3,4,5,6-Pentakisphosphate 2-Kinase 1 Mutant with a 33-Nt Deletion Showed Enhanced Tolerance to Salt and Drought Stress in Rice. Plants 2021, 10, 23. [Google Scholar] [CrossRef]
  106. Wu, Q.; Liu, Y.; Xie, Z.; Yu, B.; Sun, Y.; Huang, J. OsNAC016 Regulates Plant Architecture and Drought Tolerance by Interacting with the Kinases GSK2 and SAPK8. Plant Physiol. 2022, 189, 1296–1313. [Google Scholar] [CrossRef] [PubMed]
  107. Wang, B.; Wang, Y.; Yu, W.; Wang, L.; Lan, Q.; Wang, Y.; Chen, C.; Zhang, Y. Knocking Out the Transcription Factor OsNAC092 Promoted Rice Drought Tolerance. Biology 2022, 11, 1830. [Google Scholar] [CrossRef] [PubMed]
  108. Han, M.-L.; Lv, Q.-Y.; Zhang, J.; Wang, T.; Zhang, C.-X.; Tan, R.-J.; Wang, Y.-L.; Zhong, L.-Y.; Gao, Y.-Q.; Chao, Z.-F.; et al. Decreasing Nitrogen Assimilation under Drought Stress by Suppressing DST-Mediated Activation of Nitrate Reductase 1.2 in Rice. Mol. Plant 2022, 15, 167–178. [Google Scholar] [CrossRef] [PubMed]
  109. Luo, Z.; Xiong, J.; Xia, H.; Wang, L.; Hou, G.; Li, Z.; Li, J.; Zhou, H.; Li, T.; Luo, L. Pentatricopeptide Repeat Gene-Mediated Mitochondrial RNA Editing Impacts on Rice Drought Tolerance. Front. Plant Sci. 2022, 13, 926285. [Google Scholar] [CrossRef]
  110. Usman, B.; Nawaz, G.; Zhao, N.; Liao, S.; Liu, Y.; Li, R. Precise Editing of the OsPYL9 Gene by RNA-Guided Cas9 Nuclease Confers Enhanced Drought Tolerance and Grain Yield in Rice (Oryza sativa L.) by Regulating Circadian Rhythm and Abiotic Stress Responsive Proteins. Int. J. Mol. Sci. 2020, 21, 7854. [Google Scholar] [CrossRef] [PubMed]
  111. Lim, C.; Kang, K.; Shim, Y.; Yoo, S.-C.; Paek, N.-C. Inactivating Transcription Factor OsWRKY5 Enhances Drought Tolerance through Abscisic Acid Signaling Pathways. Plant Physiol. 2022, 188, 1900–1916. [Google Scholar] [CrossRef]
  112. Liao, S.; Qin, X.; Luo, L.; Han, Y.; Wang, X.; Usman, B.; Nawaz, G.; Zhao, N.; Liu, Y.; Li, R. CRISPR/Cas9-Induced Mutagenesis of Semi-Rolled Leaf1,2 Confers Curled Leaf Phenotype and Drought Tolerance by Influencing Protein Expression Patterns and ROS Scavenging in Rice (Oryza sativa L.). Agronomy 2019, 9, 728. [Google Scholar] [CrossRef]
  113. Um, T.; Choi, J.; Park, T.; Chung, P.J.; Jung, S.E.; Shim, J.S.; Kim, Y.S.; Choi, I.-Y.; Park, S.C.; Oh, S.-J.; et al. Rice MicroRNA171f/SCL6 Module Enhances Drought Tolerance by Regulation of Flavonoid Biosynthesis Genes. Plant Direct 2022, 6, e374. [Google Scholar] [CrossRef]
  114. Chung, P.J.; Chung, H.; Oh, N.; Choi, J.; Bang, S.W.; Jung, S.E.; Jung, H.; Shim, J.S.; Kim, J.-K. Efficiency of Recombinant CRISPR/RCas9-Mediated MiRNA Gene Editing in Rice. Int. J. Mol. Sci. 2020, 21, 9606. [Google Scholar] [CrossRef]
  115. Li, J.; Zhang, M.; Yang, L.; Mao, X.; Li, J.; Li, L.; Wang, J.; Liu, H.; Zheng, H.; Li, Z.; et al. OsADR3 Increases Drought Stress Tolerance by Inducing Antioxidant Defense Mechanisms and Regulating OsGPX1 in Rice (Oryza sativa L.). Crop J. 2021, 9, 1003–1017. [Google Scholar] [CrossRef]
  116. Du, C.; Cai, W.; Lin, F.; Wang, K.; Li, S.; Chen, C.; Tian, H.; Wang, D.; Zhao, Q. Leucine-Rich Repeat Receptor-like Kinase OsASLRK Regulates Abscisic Acid and Drought Responses via Cooperation with S-like RNase OsRNS4 in Rice. Environ. Exp. Bot. 2022, 201, 104949. [Google Scholar] [CrossRef]
  117. Gao, W.; Li, M.; Yang, S.; Gao, C.; Su, Y.; Zeng, X.; Jiao, Z.; Xu, W.; Zhang, M.; Xia, K. MiR2105 and the Kinase OsSAPK10 Co-Regulate OsbZIP86 to Mediate Drought-Induced ABA Biosynthesis in Rice. Plant Physiol. 2022, 189, 889–905. [Google Scholar] [CrossRef] [PubMed]
  118. Bang, S.W.; Choi, S.; Jin, X.; Jung, S.E.; Choi, J.W.; Seo, J.S.; Kim, J.-K. Transcriptional Activation of Rice CINNAMOYL-CoA REDUCTASE 10 by OsNAC5, Contributes to Drought Tolerance by Modulating Lignin Accumulation in Roots. Plant Biotechnol. J. 2022, 20, 736–747. [Google Scholar] [CrossRef]
  119. Huang, L.; Fu, W.; Ji, E.; Tanveer, M.; Shabala, S.; Yu, M.; Jiang, M. A Novel R3H Protein, OsDIP1, Confers ABA-Mediated Adaptation to Drought and Salinity Stress in Rice. Plant Soil 2022, 477, 501–519. [Google Scholar] [CrossRef]
  120. Yang, L.; Chen, Y.; Xu, L.; Wang, J.; Qi, H.; Guo, J.; Zhang, L.; Shen, J.; Wang, H.; Zhang, F.; et al. The OsFTIP6-OsHB22-OsMYBR57 Module Regulates Drought Response in Rice. Mol. Plant 2022, 15, 1227–1242. [Google Scholar] [CrossRef] [PubMed]
  121. Xu, W.; Dou, Y.; Geng, H.; Fu, J.; Dan, Z.; Liang, T.; Cheng, M.; Zhao, W.; Zeng, Y.; Hu, Z.; et al. OsGRP3 Enhances Drought Resistance by Altering Phenylpropanoid Biosynthesis Pathway in Rice (Oryza sativa L.). Int. J. Mol. Sci. 2022, 23, 7045. [Google Scholar] [CrossRef] [PubMed]
  122. Jian, L.; Kang, K.; Choi, Y.; Suh, M.C.; Paek, N.-C. Mutation of OsMYB60 Reduces Rice Resilience to Drought Stress by Attenuating Cuticular Wax Biosynthesis. Plant J. 2022, 112, 339–351. [Google Scholar] [CrossRef] [PubMed]
  123. Wang, B.; Zhong, Z.; Wang, X.; Han, X.; Yu, D.; Wang, C.; Song, W.; Zheng, X.; Chen, C.; Zhang, Y. Knockout of the OsNAC006 Transcription Factor Causes Drought and Heat Sensitivity in Rice. Int. J. Mol. Sci. 2020, 21, 2288. [Google Scholar] [CrossRef] [PubMed]
  124. Jung, S.E.; Kim, T.H.; Shim, J.S.; Bang, S.W.; Bin Yoon, H.; Oh, S.H.; Kim, Y.S.; Oh, S.-J.; Seo, J.S.; Kim, J.-K. Rice NAC17 Transcription Factor Enhances Drought Tolerance by Modulating Lignin Accumulation. Plant Sci. 2022, 323, 111404. [Google Scholar] [CrossRef]
  125. Diyang, Q.; Rui, H.; Ji, L.; Ying, L.; Jierong, D.; Kuaifei, X.; Xuhua, Z.; Zhongming, F.; Mingyong, Z. Peptide Transporter OsNPF8.1 Contributes to Sustainable Growth under Salt and Drought Stresses, and Grain Yield under Nitrogen Deficiency in Rice. Rice Sci. 2023, 30, 113–126. [Google Scholar] [CrossRef]
  126. Yao, L.; Cheng, X.; Gu, Z.; Huang, W.; Li, S.; Wang, L.; Wang, Y.-F.; Xu, P.; Ma, H.; Ge, X. The AWPM-19 Family Protein OsPM1 Mediates Abscisic Acid Influx and Drought Response in Rice. Plant Cell 2018, 30, 1258–1276. [Google Scholar] [CrossRef]
  127. Qin, Q.; Wang, Y.; Huang, L.; Du, F.; Zhao, X.; Li, Z.; Wang, W.; Fu, B. A U-Box E3 Ubiquitin Ligase OsPUB67 Is Positively Involved in Drought Tolerance in Rice. Plant Mol. Biol. 2020, 102, 89–107. [Google Scholar] [CrossRef] [PubMed]
  128. Chen, S.; Xu, K.; Kong, D.; Wu, L.; Chen, Q.; Ma, X.; Ma, S.; Li, T.; Xie, Q.; Liu, H.; et al. Ubiquitin Ligase OsRINGzf1 Regulates Drought Resistance by Controlling the Turnover of OsPIP2;1. Plant Biotechnol. J. 2022, 20, 1743–1755. [Google Scholar] [CrossRef] [PubMed]
  129. Lou, D.; Wang, H.; Liang, G.; Yu, D. OsSAPK2 Confers Abscisic Acid Sensitivity and Tolerance to Drought Stress in Rice. Front. Plant Sci. 2017, 8, 993. [Google Scholar] [CrossRef]
  130. Lou, D.; Lu, S.; Chen, Z.; Lin, Y.; Yu, D.; Yang, X. Molecular Characterization Reveals That OsSAPK3 Improves Drought Tolerance and Grain Yield in Rice. BMC Plant Biol. 2023, 23, 53. [Google Scholar] [CrossRef]
  131. Chen, F.; Zhang, H.; Li, H.; Lian, L.; Wei, Y.; Lin, Y.; Wang, L.; He, W.; Cai, Q.; Xie, H.; et al. IPA1 Improves Drought Tolerance by Activating SNAC1 in Rice. BMC Plant Biol. 2023, 23, 55. [Google Scholar] [CrossRef]
  132. Shi, X.; Tian, Q.; Deng, P.; Zhang, W.; Jing, W. The Rice Aldehyde Oxidase OsAO3 Gene Regulates Plant Growth, Grain Yield, and Drought Tolerance by Participating in ABA Biosynthesis. Biochem. Biophys. Res. Commun. 2021, 548, 189–195. [Google Scholar] [CrossRef] [PubMed]
  133. Shen, C.; Zhang, Y.; Li, Q.; Liu, S.; He, F.; An, Y.; Zhou, Y.; Liu, C.; Yin, W.; Xia, X. PdGNC Confers Drought Tolerance by Mediating Stomatal Closure Resulting from NO and H2O2 Production via the Direct Regulation of PdHXK1 Expression in Populus. New Phytol. 2021, 230, 1868–1882. [Google Scholar] [CrossRef]
  134. Zhou, Y.; Zhang, Y.; Wang, X.; Han, X.; An, Y.; Lin, S.; Shen, C.; Wen, J.; Liu, C.; Yin, W.; et al. Root-Specific NF-Y Family Transcription Factor, PdNF-YB21, Positively Regulates Root Growth and Drought Resistance by Abscisic Acid-Mediated Indoylacetic Acid Transport in Populus. New Phytol. 2020, 227, 407–426. [Google Scholar] [CrossRef] [PubMed]
  135. Li, S.; Lin, Y.-C.J.; Wang, P.; Zhang, B.; Li, M.; Chen, S.; Shi, R.; Tunlaya-Anukit, S.; Liu, X.; Wang, Z.; et al. The AREB1 Transcription Factor Influences Histone Acetylation to Regulate Drought Responses and Tolerance in Populus Trichocarpa. Plant Cell 2019, 31, 663–686. [Google Scholar] [CrossRef]
  136. Wang, P.; Luo, Q.; Yang, W.; Ahammed, G.J.; Ding, S.; Chen, X.; Wang, J.; Xia, X.; Shi, K. A Novel Role of Pipecolic Acid Biosynthetic Pathway in Drought Tolerance through the Antioxidant System in Tomato. Antioxidants 2021, 10, 1923. [Google Scholar] [CrossRef] [PubMed]
  137. Chen, M.; Zhu, X.; Liu, X.; Wu, C.; Yu, C.; Hu, G.; Chen, L.; Chen, R.; Bouzayen, M.; Zouine, M.; et al. Knockout of Auxin Response Factor SlARF4 Improves Tomato Resistance to Water Deficit. Int. J. Mol. Sci. 2021, 22, 3347. [Google Scholar] [CrossRef]
  138. Zhao, W.; Huang, H.; Wang, J.; Wang, X.; Xu, B.; Yao, X.; Sun, L.; Yang, R.; Wang, J.; Sun, A.; et al. Jasmonic Acid Enhances Osmotic Stress Responses by MYC2-Mediated Inhibition of Protein Phosphatase 2C1 and Response Regulators 26 Transcription Factor in Tomato. Plant J. 2023, 113, 546–561. [Google Scholar] [CrossRef] [PubMed]
  139. Wang, X.; Liu, Y.; Li, H.; Wang, F.; Xia, P.; Li, W.; Zhang, X.; Zhang, N.; Guo, Y.-D. SlSNAT2, a Chloroplast-Localized Acetyltransferase, Is Involved in Rubisco Lysine Acetylation and Negatively Regulates Drought Stress Tolerance in Tomato. Environ. Exp. Bot. 2022, 201, 105003. [Google Scholar] [CrossRef]
  140. Liu, L.; Zhang, J.; Xu, J.; Li, Y.; Guo, L.; Wang, Z.; Zhang, X.; Zhao, B.; Guo, Y.-D.; Zhang, N. CRISPR/Cas9 Targeted Mutagenesis of SlLBD40, a Lateral Organ Boundaries Domain Transcription Factor, Enhances Drought Tolerance in Tomato. Plant Sci. 2020, 301, 110683. [Google Scholar] [CrossRef]
  141. Wang, L.; Chen, L.; Li, R.; Zhao, R.; Yang, M.; Sheng, J.; Shen, L. Reduced Drought Tolerance by CRISPR/Cas9-Mediated SlMAPK3 Mutagenesis in Tomato Plants. J. Agric. Food Chem. 2017, 65, 8674–8682. [Google Scholar] [CrossRef]
  142. Li, R.; Liu, C.; Zhao, R.; Wang, L.; Chen, L.; Yu, W.; Zhang, S.; Sheng, J.; Shen, L. CRISPR/Cas9-Mediated SlNPR1 Mutagenesis Reduces Tomato Plant Drought Tolerance. BMC Plant Biol. 2019, 19, 38. [Google Scholar] [CrossRef]
  143. dos Reis Moreira, J.; Quiñones, A.; Lira, B.S.; Robledo, J.M.; Curtin, S.J.; Vicente, M.H.; Ribeiro, D.M.; Ryngajllo, M.; Jiménez-Gómez, J.M.; Peres, L.E.P.; et al. SELF PRUNING 3C Is a Flowering Repressor That Modulates Seed Germination, Root Architecture, and Drought Responses. J. Exp. Bot. 2022, 73, 6226–6240. [Google Scholar] [CrossRef]
  144. Ramírez Gonzales, L.; Shi, L.; Bergonzi, S.B.; Oortwijn, M.; Franco-Zorrilla, J.M.; Solano-Tavira, R.; Visser, R.G.F.; Abelenda, J.A.; Bachem, C.W.B. Potato cycling Dof factor 1 and Its LncRNA Counterpart StFLORE Link Tuber Development and Drought Response. Plant J. 2021, 105, 855–869. [Google Scholar] [CrossRef] [PubMed]
  145. Mohr, T.; Horstman, J.; Gu, Y.Q.; Elarabi, N.I.; Abdallah, N.A.; Thilmony, R. CRISPR-Cas9 Gene Editing of the Sal1 Gene Family in Wheat. Plants 2022, 11, 2259. [Google Scholar] [CrossRef] [PubMed]
  146. He, J.; Li, C.; Hu, N.; Zhu, Y.; He, Z.; Sun, Y.; Wang, Z.; Wang, Y. ECERIFERUM1-6A Is Required for the Synthesis of Cuticular Wax Alkanes and Promotes Drought Tolerance in Wheat. Plant Physiol. 2022, 190, 1640–1657. [Google Scholar] [CrossRef] [PubMed]
  147. Wang, N.; Chen, J.; Gao, Y.; Zhou, Y.; Chen, M.; Xu, Z.; Fang, Z.; Ma, Y. Genomic Analysis of Isopentenyltransferase Genes and Functional Characterization of TaIPT8 Indicates Positive Effects of Cytokinins on Drought Tolerance in Wheat. Crop J. 2023, 11, 46–56. [Google Scholar] [CrossRef]
  148. Mao, H.; Jian, C.; Cheng, X.; Chen, B.; Mei, F.; Li, F.; Zhang, Y.; Li, S.; Du, L.; Li, T.; et al. The Wheat ABA Receptor Gene TaPYL1-1B Contributes to Drought Tolerance and Grain Yield by Increasing Water-Use Efficiency. Plant Biotechnol. J. 2022, 20, 846–861. [Google Scholar] [CrossRef]
  149. Clemens, M.; Faralli, M.; Lagreze, J.; Bontempo, L.; Piazza, S.; Varotto, C.; Malnoy, M.; Oechel, W.; Rizzoli, A.; Dalla Costa, L. VvEPFL9-1 Knock-Out via CRISPR/Cas9 Reduces Stomatal Density in Grapevine. Front. Plant Sci. 2022, 13, 878001. [Google Scholar] [CrossRef]
  150. Shi, J.; Gao, H.; Wang, H.; Lafitte, H.R.; Archibald, R.L.; Yang, M.; Hakimi, S.M.; Mo, H.; Habben, J.E. ARGOS8 Variants Generated by CRISPR-Cas9 Improve Maize Grain Yield under Field Drought Stress Conditions. Plant Biotechnol. J. 2017, 15, 207–216. [Google Scholar] [CrossRef]
  151. Feng, X.; Xiong, J.; Zhang, W.; Guan, H.; Zheng, D.; Xiong, H.; Jia, L.; Hu, Y.; Zhou, H.; Wen, Y.; et al. ZmLBD5, a Class-II LBD Gene, Negatively Regulates Drought Tolerance by Impairing Abscisic Acid Synthesis. Plant J. 2022, 112, 1364–1376. [Google Scholar] [CrossRef] [PubMed]
  152. Zhang, M.; Chen, Y.; Xing, H.; Ke, W.; Shi, Y.; Sui, Z.; Xu, R.; Gao, L.; Guo, G.; Li, J.; et al. Positional Cloning and Characterization Reveal the Role of a MiRNA Precursor Gene ZmLRT in the Regulation of Lateral Root Number and Drought Tolerance in Maize. J. Integr. Plant Biol. 2022, 65, 772–790. [Google Scholar] [CrossRef]
  153. Guo, Y.; Shi, Y.; Wang, Y.; Liu, F.; Li, Z.; Qi, J.; Wang, Y.; Zhang, J.; Yang, S.; Wang, Y.; et al. The Clade F PP2C Phosphatase ZmPP84 Negatively Regulates Drought Tolerance by Repressing Stomatal Closure in Maize. New Phytol. 2023, 237, 1728–1744. [Google Scholar] [CrossRef]
  154. Wang, C.; Gao, B.; Chen, N.; Jiao, P.; Jiang, Z.; Zhao, C.; Ma, Y.; Guan, S.; Liu, S. A Novel Senescence-Specific Gene (ZmSAG39) Negatively Regulates Darkness and Drought Responses in Maize. Int. J. Mol. Sci. 2022, 23, 15984. [Google Scholar] [CrossRef] [PubMed]
  155. Jiao, P.; Liu, T.; Zhao, C.; Fei, J.; Guan, S.; Ma, Y. ZmTCP14, a TCP Transcription Factor, Modulates Drought Stress Response in Zea mays L. Environ. Exp. Bot. 2023, 208, 105232. [Google Scholar] [CrossRef]
  156. Jiao, P.; Jiang, Z.; Wei, X.; Liu, S.; Qu, J.; Guan, S.; Ma, Y. Overexpression of the Homeobox-Leucine Zipper Protein ATHB-6 Improves the Drought Tolerance of Maize (Zea mays L.). Plant Sci. 2022, 316, 111159. [Google Scholar] [CrossRef] [PubMed]
  157. Yang, Y.; Shi, J.; Chen, L.; Xiao, W.; Yu, J. ZmEREB46, a Maize Ortholog of Arabidopsis WAX INDUCER1/SHINE1, Is Involved in the Biosynthesis of Leaf Epicuticular Very-Long-Chain Waxes and Drought Tolerance. Plant Sci. 2022, 321, 111256. [Google Scholar] [CrossRef]
  158. Gao, H.; Cui, J.; Liu, S.; Wang, S.; Lian, Y.; Bai, Y.; Zhu, T.; Wu, H.; Wang, Y.; Yang, S.; et al. Natural Variations of ZmSRO1d Modulate the Trade-off between Drought Resistance and Yield by Affecting ZmRBOHC-Mediated Stomatal ROS Production in Maize. Mol. Plant 2022, 15, 1558–1574. [Google Scholar] [CrossRef] [PubMed]
  159. Tian, T.; Wang, S.; Yang, S.; Yang, Z.; Liu, S.; Wang, Y.; Gao, H.; Zhang, S.; Yang, X.; Jiang, C.; et al. Genome Assembly and Genetic Dissection of a Prominent Drought-Resistant Maize Germplasm. Nat. Genet. 2023, 55, 496–506. [Google Scholar] [CrossRef] [PubMed]
  160. Pan, Z.; Liu, M.; Zhao, H.; Tan, Z.; Liang, K.; Sun, Q.; Gong, D.; He, H.; Zhou, W.; Qiu, F. ZmSRL5 Is Involved in Drought Tolerance by Maintaining Cuticular Wax Structure in Maize. J. Integr. Plant Biol. 2020, 62, 1895–1909. [Google Scholar] [CrossRef]
  161. Chang, H.; Yi, B.; Ma, R.; Zhang, X.; Zhao, H.; Xi, Y. CRISPR/Cas9, a Novel Genomic Tool to Knock down MicroRNA in Vitro and in Vivo. Sci. Rep. 2016, 6, 22312. [Google Scholar] [CrossRef]
  162. Shomali, A.; Das, S.; Arif, N.; Sarraf, M.; Zahra, N.; Yadav, V.; Aliniaeifard, S.; Chauhan, D.K.; Hasanuzzaman, M. Diverse Physiological Roles of Flavonoids in Plant Environmental Stress Responses and Tolerance. Plants 2022, 11, 3158. [Google Scholar] [CrossRef]
  163. Guo, Z.; Kuang, Z.; Wang, Y.; Zhao, Y.; Tao, Y.; Cheng, C.; Yang, J.; Lu, X.; Hao, C.; Wang, T.; et al. PmiREN: A Comprehensive Encyclopedia of Plant MiRNAs. Nucleic Acids Res. 2020, 48, D1114–D1121. [Google Scholar] [CrossRef]
  164. Bin Rahman, A.N.M.R.; Zhang, J. Flood and Drought Tolerance in Rice: Opposite but May Coexist. Food Energy Secur. 2016, 5, 76–88. [Google Scholar] [CrossRef]
  165. Tamang, B.G.; Li, S.; Rajasundaram, D.; Lamichhane, S.; Fukao, T. Overlapping and Stress-specific Transcriptomic and Hormonal Responses to Flooding and Drought in Soybean. Plant J. 2021, 107, 100–117. [Google Scholar] [CrossRef] [PubMed]
  166. Zscheischler, J.; Westra, S.; van den Hurk, B.J.J.M.; Seneviratne, S.I.; Ward, P.J.; Pitman, A.; AghaKouchak, A.; Bresch, D.N.; Leonard, M.; Wahl, T.; et al. Future Climate Risk from Compound Events. Nat. Clim. Change 2018, 8, 469–477. [Google Scholar] [CrossRef]
  167. Cui, H.; Jiang, S.; Ren, L.; Xiao, W.; Yuan, F.; Wang, M.; Wei, L. Dynamics and Potential Synchronization of Regional Precipitation Concentration and Drought-Flood Abrupt Alternation under the Influence of Reservoir Climate. J. Hydrol. Reg. Stud. 2022, 42, 101147. [Google Scholar] [CrossRef]
  168. Fukao, T.; Barrera-Figueroa, B.E.; Juntawong, P.; Peña-Castro, J.M. Submergence and Waterlogging Stress in Plants: A Review Highlighting Research Opportunities and Understudied Aspects. Front. Plant Sci. 2019, 10, 340. [Google Scholar] [CrossRef] [PubMed]
  169. Jackson, M.B.; Colmer, T.D. Response and Adaptation by Plants to Flooding Stress. Ann. Bot. 2005, 96, 501–505. [Google Scholar] [CrossRef]
  170. Pan, J.; Sharif, R.; Xu, X.; Chen, X. Mechanisms of Waterlogging Tolerance in Plants: Research Progress and Prospects. Front. Plant Sci. 2021, 11, 627331. [Google Scholar] [CrossRef]
  171. Sun, J.; Zhang, G.; Cui, Z.; Kong, X.; Yu, X.; Gui, R.; Han, Y.; Li, Z.; Lang, H.; Hua, Y.; et al. Regain Flood Adaptation in Rice through a 14-3-3 Protein OsGF14h. Nat. Commun. 2022, 13, 5664. [Google Scholar] [CrossRef]
  172. Liang, Y.; Biswas, S.; Kim, B.; Bailey-Serres, J.; Septiningsih, E.M. Improved Transformation and Regeneration of Indica Rice: Disruption of SUB1A as a Test Case via CRISPR-Cas9. Int. J. Mol. Sci. 2021, 22, 6989. [Google Scholar] [CrossRef]
  173. Ye, N.-H.; Wang, F.-Z.; Shi, L.; Chen, M.-X.; Cao, Y.-Y.; Zhu, F.-Y.; Wu, Y.-Z.; Xie, L.-J.; Liu, T.-Y.; Su, Z.-Z.; et al. Natural Variation in the Promoter of Rice Calcineurin B-like Protein10 (OsCBL10) Affects Flooding Tolerance during Seed Germination among Rice Subspecies. Plant J. 2018, 94, 612–625. [Google Scholar] [CrossRef]
  174. Verslues, P.E.; Bailey-Serres, J.; Brodersen, C.; Buckley, T.N.; Conti, L.; Christmann, A.; Dinneny, J.R.; Grill, E.; Hayes, S.; Heckman, R.W.; et al. Burning Questions for a Warming and Changing World: 15 Unknowns in Plant Abiotic Stress. Plant Cell 2022, 35, 67–108. [Google Scholar] [CrossRef]
  175. Shrivastava, P.; Kumar, R. Soil Salinity: A Serious Environmental Issue and Plant Growth Promoting Bacteria as One of the Tools for Its Alleviation. Saudi J. Biol. Sci. 2015, 22, 123–131. [Google Scholar] [CrossRef] [PubMed]
  176. Litalien, A.; Zeeb, B. Curing the Earth: A Review of Anthropogenic Soil Salinization and Plant-Based Strategies for Sustainable Mitigation. Sci. Total Environ. 2020, 698, 134235. [Google Scholar] [CrossRef]
  177. Qadir, M.; Quillérou, E.; Nangia, V.; Murtaza, G.; Singh, M.; Thomas, R.J.; Drechsel, P.; Noble, A.D. Economics of Salt-Induced Land Degradation and Restoration. Nat. Resour. Forum 2014, 38, 282–295. [Google Scholar] [CrossRef]
  178. Chen, J.; Mueller, V. Coastal Climate Change, Soil Salinity and Human Migration in Bangladesh. Nat. Clim. Change 2018, 8, 981–985. [Google Scholar] [CrossRef]
  179. Li, J.; Pu, L.; Han, M.; Zhu, M.; Zhang, R.; Xiang, Y. Soil Salinization Research in China: Advances and Prospects. J. Geogr. Sci. 2014, 24, 943–960. [Google Scholar] [CrossRef]
  180. Casanova, M.; Salazar, O.; Oyarzún, I.; Tapia, Y.; Fajardo, M. Field Monitoring of 2010-Tsunami Impact on Agricultural Soils and Irrigation Waters: Central Chile. Water Air Soil Pollut. 2016, 227, 411. [Google Scholar] [CrossRef]
  181. Kumar, K.; Kumar, M.; Kim, S.-R.; Ryu, H.; Cho, Y.-G. Insights into Genomics of Salt Stress Response in Rice. Rice 2013, 6, 27. [Google Scholar] [CrossRef] [PubMed]
  182. Moradi, F.; Ismail, A.M. Responses of Photosynthesis, Chlorophyll Fluorescence and ROS-Scavenging Systems to Salt Stress During Seedling and Reproductive Stages in Rice. Ann. Bot. 2007, 99, 1161–1173. [Google Scholar] [CrossRef] [PubMed]
  183. Parihar, P.; Singh, S.; Singh, R.; Singh, V.P.; Prasad, S.M. Effect of Salinity Stress on Plants and Its Tolerance Strategies: A Review. Environ. Sci. Pollut. Res. 2015, 22, 4056–4075. [Google Scholar] [CrossRef]
  184. Razzaq, A.; Ali, A.; Safdar, L.B.; Zafar, M.M.; Rui, Y.; Shakeel, A.; Shaukat, A.; Ashraf, M.; Gong, W.; Yuan, Y. Salt Stress Induces Physiochemical Alterations in Rice Grain Composition and Quality. J. Food Sci. 2020, 85, 14–20. [Google Scholar] [CrossRef]
  185. Munns, R. Comparative Physiology of Salt and Water Stress: Comparative Physiology of Salt and Water Stress. Plant Cell Environ. 2002, 25, 239–250. [Google Scholar] [CrossRef]
  186. Zhu, J.-K. Salt and drought stress signal transduction in plants. Annu. Rev. Plant Biol. 2002, 53, 247–273. [Google Scholar] [CrossRef]
  187. Hasanuzzaman, M.; Bhuyan, M.H.M.B.; Parvin, K.; Bhuiyan, T.F.; Anee, T.I.; Nahar, K.; Hossen, M.S.; Zulfiqar, F.; Alam, M.M.; Fujita, M. Regulation of ROS Metabolism in Plants under Environmental Stress: A Review of Recent Experimental Evidence. IJMS 2020, 21, 8695. [Google Scholar] [CrossRef]
  188. Shavrukov, Y. Salt Stress or Salt Shock: Which Genes Are We Studying? J. Exp. Bot. 2013, 64, 119–127. [Google Scholar] [CrossRef]
  189. Arif, Y.; Singh, P.; Siddiqui, H.; Bajguz, A.; Hayat, S. Salinity Induced Physiological and Biochemical Changes in Plants: An Omic Approach towards Salt Stress Tolerance. Plant Physiol. Biochem. 2020, 156, 64–77. [Google Scholar] [CrossRef]
  190. Deinlein, U.; Stephan, A.B.; Horie, T.; Luo, W.; Xu, G.; Schroeder, J.I. Plant Salt-Tolerance Mechanisms. Trends Plant Sci. 2014, 19, 371–379. [Google Scholar] [CrossRef]
  191. van Zelm, E.; Zhang, Y.; Testerink, C. Salt Tolerance Mechanisms of Plants. Annu. Rev. Plant Biol. 2020, 71, 403–433. [Google Scholar] [CrossRef] [PubMed]
  192. Shabala, S.; Bose, J.; Hedrich, R. Salt Bladders: Do They Matter? Trends Plant Sci. 2014, 19, 687–691. [Google Scholar] [CrossRef] [PubMed]
  193. Gupta, B.; Huang, B. Mechanism of Salinity Tolerance in Plants: Physiological, Biochemical, and Molecular Characterization. Int. J. Genom. 2014, 2014, 701596. [Google Scholar] [CrossRef] [PubMed]
  194. Rathinapriya, P.; Pandian, S.; Rakkammal, K.; Balasangeetha, M.; Alexpandi, R.; Satish, L.; Rameshkumar, R.; Ramesh, M. The Protective Effects of Polyamines on Salinity Stress Tolerance in Foxtail Millet (Setaria italica L.), an Important C4 Model Crop. Physiol. Mol. Biol. Plants 2020, 26, 1815–1829. [Google Scholar] [CrossRef] [PubMed]
  195. Tiburcio, A.F.; Altabella, T.; Bitrián, M.; Alcázar, R. The Roles of Polyamines during the Lifespan of Plants: From Development to Stress. Planta 2014, 240, 1–18. [Google Scholar] [CrossRef]
  196. Wani, S.H.; Kumar, V.; Khare, T.; Guddimalli, R.; Parveda, M.; Solymosi, K.; Suprasanna, P.; Kavi Kishor, P.B. Engineering Salinity Tolerance in Plants: Progress and Prospects. Planta 2020, 251, 76. [Google Scholar] [CrossRef]
  197. Seki, M.; Kamei, A.; Yamaguchi-Shinozaki, K.; Shinozaki, K. Molecular Responses to Drought, Salinity and Frost: Common and Different Paths for Plant Protection. Curr. Opin. Biotechnol. 2003, 14, 194–199. [Google Scholar] [CrossRef] [PubMed]
  198. Takagi, H.; Tamiru, M.; Abe, A.; Yoshida, K.; Uemura, A.; Yaegashi, H.; Obara, T.; Oikawa, K.; Utsushi, H.; Kanzaki, E.; et al. MutMap Accelerates Breeding of a Salt-Tolerant Rice Cultivar. Nat. Biotechnol. 2015, 33, 445–449. [Google Scholar] [CrossRef]
  199. Zhang, A.; Liu, Y.; Wang, F.; Li, T.; Chen, Z.; Kong, D.; Bi, J.; Zhang, F.; Luo, X.; Wang, J.; et al. Enhanced Rice Salinity Tolerance via CRISPR/Cas9-Targeted Mutagenesis of the OsRR22 Gene. Mol Breed. 2019, 39, 47. [Google Scholar] [CrossRef] [PubMed]
  200. Li, M.; Chen, R.; Jiang, Q.; Sun, X.; Zhang, H.; Hu, Z. GmNAC06, a NAC Domain Transcription Factor Enhances Salt Stress Tolerance in Soybean. Plant Mol. Biol. 2021, 105, 333–345. [Google Scholar] [CrossRef] [PubMed]
  201. Wang, T.; Xun, H.; Wang, W.; Ding, X.; Tian, H.; Hussain, S.; Dong, Q.; Li, Y.; Cheng, Y.; Wang, C.; et al. Mutation of GmAITR Genes by CRISPR/Cas9 Genome Editing Results in Enhanced Salinity Stress Tolerance in Soybean. Front. Plant Sci. 2021, 12, 779598. [Google Scholar] [CrossRef]
  202. Tian, H.; Chen, S.; Yang, W.; Wang, T.; Zheng, K.; Wang, Y.; Cheng, Y.; Zhang, N.; Liu, S.; Li, D.; et al. A Novel Family of Transcription Factors Conserved in Angiosperms Is Required for ABA Signalling. Plant Cell Environ. 2017, 40, 2958–2971. [Google Scholar] [CrossRef]
  203. Sohail, H.; Noor, I.; Nawaz, M.A.; Ma, M.; Shireen, F.; Huang, Y.; Yang, L.; Bie, Z. Genome-Wide Identification of Plasma-Membrane Intrinsic Proteins in Pumpkin and Functional Characterization of CmoPIP1-4 under Salinity Stress. Environ. Exp. Bot. 2022, 202, 104995. [Google Scholar] [CrossRef]
  204. Dong, L.; Hou, Z.; Li, H.; Li, Z.; Fang, C.; Kong, L.; Li, Y.; Du, H.; Li, T.; Wang, L.; et al. Agronomical Selection on Loss-of-Function of GIGANTEA Simultaneously Facilitates Soybean Salt Tolerance and Early Maturity. J. Integr. Plant Biol. 2022, 64, 1866–1882. [Google Scholar] [CrossRef]
  205. Fu, L.; Wu, D.; Zhang, X.; Xu, Y.; Kuang, L.; Cai, S.; Zhang, G.; Shen, Q. Vacuolar H+-Pyrophosphatase HVP10 Enhances Salt Tolerance via Promoting Na+ Translocation into Root Vacuoles. Plant Physiol. 2022, 188, 1248–1263. [Google Scholar] [CrossRef] [PubMed]
  206. Alam, M.S.; Kong, J.; Tao, R.; Ahmed, T.; Alamin, M.; Alotaibi, S.S.; Abdelsalam, N.R.; Xu, J.-H. CRISPR/Cas9 Mediated Knockout of the OsbHLH024 Transcription Factor Improves Salt Stress Resistance in Rice (Oryza sativa L.). Plants 2022, 11, 1184. [Google Scholar] [CrossRef] [PubMed]
  207. Wang, X.; Ren, P.; Ji, L.; Zhu, B.; Xie, G. OsVDE, a Xanthophyll Cycle Key Enzyme, Mediates Abscisic Acid Biosynthesis and Negatively Regulates Salinity Tolerance in Rice. Planta 2021, 255, 6. [Google Scholar] [CrossRef] [PubMed]
  208. Teng, Y.; Lv, M.; Zhang, X.; Cai, M.; Chen, T. BEAR1, a BHLH Transcription Factor, Controls Salt Response Genes to Regulate Rice Salt Response. J. Plant Biol. 2022, 65, 217–230. [Google Scholar] [CrossRef]
  209. Liu, S.; Liu, W.; Lai, J.; Liu, Q.; Zhang, W.; Chen, Z.; Gao, J.; Song, S.; Liu, J.; Xiao, Y. OsGLYI3, a Glyoxalase Gene Expressed in Rice Seed, Contributes to Seed Longevity and Salt Stress Tolerance. Plant Physiol. Biochem. 2022, 183, 85–95. [Google Scholar] [CrossRef]
  210. Zhang, M.; Zhao, R.; Wang, H.; Ren, S.; Shi, L.; Huang, S.; Wei, Z.; Guo, B.; Jin, J.; Zhong, Y.; et al. OsWRKY28 Positively Regulates Salinity Tolerance by Directly Activating OsDREB1B Expression in Rice. Plant Cell Rep. 2022, 42, 223–234. [Google Scholar] [CrossRef]
  211. Huang, J.; Liu, F.; Chao, D.; Xin, B.; Liu, K.; Cao, S.; Chen, X.; Peng, L.; Zhang, B.; Fu, S.; et al. The WRKY Transcription Factor OsWRKY54 Is Involved in Salt Tolerance in Rice. Int. J. Mol. Sci. 2022, 23, 11999. [Google Scholar] [CrossRef] [PubMed]
  212. Shohat, H.; Cheriker, H.; Cohen, A.; Weiss, D. Tomato ABA-IMPORTING TRANSPORTER 1.1 Inhibits Seed Germination under High Salinity Conditions. Plant Physiol. 2023, 191, 1404–1415. [Google Scholar] [CrossRef]
  213. Ding, F.; Qiang, X.; Jia, Z.; Li, L.; Hu, J.; Yin, M.; Xia, S.; Chen, B.; Qi, J.; Li, Q.; et al. Knockout of a Novel Salt Responsive Gene SlABIG1 Enhance Salinity Tolerance in Tomato. Environ. Exp. Bot. 2022, 200, 104903. [Google Scholar] [CrossRef]
  214. Tran, M.T.; Doan, D.T.H.; Kim, J.; Song, Y.J.; Sung, Y.W.; Das, S.; Kim, E.; Son, G.H.; Kim, S.H.; Van Vu, T.; et al. CRISPR/Cas9-Based Precise Excision of SlHyPRP1 Domain(s) to Obtain Salt Stress-Tolerant Tomato. Plant Cell Rep. 2021, 40, 999–1011. [Google Scholar] [CrossRef] [PubMed]
  215. Zhong, M.; Yue, L.; Liu, W.; Qin, H.; Lei, B.; Huang, R.; Yang, X.; Kang, Y. Genome-Wide Identification and Characterization of the Polyamine Uptake Transporter (Put) Gene Family in Tomatoes and the Role of Put2 in Response to Salt Stress. Antioxidants 2023, 12, 228. [Google Scholar] [CrossRef] [PubMed]
  216. Bradl, H.B. Chapter 1 Sources and Origins of Heavy Metals. In Interface Science and Technology; Elsevier: Amsterdam, The Netherlands, 2005; Volume 6, pp. 1–27. ISBN 978-0-12-088381-3. [Google Scholar]
  217. Li, C.; Zhou, K.; Qin, W.; Tian, C.; Qi, M.; Yan, X.; Han, W. A Review on Heavy Metals Contamination in Soil: Effects, Sources, and Remediation Techniques. Soil Sediment Contam. Int. J. 2019, 28, 380–394. [Google Scholar] [CrossRef]
  218. Zoffoli, H.J.O.; do Amaral-Sobrinho, N.M.B.; Zonta, E.; Luisi, M.V.; Marcon, G.; Tolón-Becerra, A. Inputs of Heavy Metals Due to Agrochemical Use in Tobacco Fields in Brazil’s Southern Region. Environ. Monit Assess 2013, 185, 2423–2437. [Google Scholar] [CrossRef] [PubMed]
  219. Huang, Y.; Wang, L.; Wang, W.; Li, T.; He, Z.; Yang, X. Current Status of Agricultural Soil Pollution by Heavy Metals in China: A Meta-Analysis. Sci. Total Environ. 2019, 651, 3034–3042. [Google Scholar] [CrossRef]
  220. Chowdhury, R.; Ramond, A.; O’Keeffe, L.M.; Shahzad, S.; Kunutsor, S.K.; Muka, T.; Gregson, J.; Willeit, P.; Warnakula, S.; Khan, H.; et al. Environmental Toxic Metal Contaminants and Risk of Cardiovascular Disease: Systematic Review and Meta-Analysis. BMJ 2018, 362, k3310. [Google Scholar] [CrossRef]
  221. Guo, G.; Zhang, D.; Wang, Y. Probabilistic Human Health Risk Assessment of Heavy Metal Intake via Vegetable Consumption around Pb/Zn Smelters in Southwest China. Int. J. Environ. Res. Public Health 2019, 16, 3267. [Google Scholar] [CrossRef]
  222. Meza-Ramírez, V.; Espinoza-Ortiz, X.; Ramírez-Verdugo, P.; Hernández-Lazcano, P.; Rojas Hermosilla, P. Pb-Contaminated Soil from Quintero-Ventanas, Chile: Remediation Using Sarcocornia Neei. Sci. World J. 2021, 2021, 2974786. [Google Scholar] [CrossRef]
  223. Khanam, R.; Kumar, A.; Nayak, A.K.; Shahid, M.; Tripathi, R.; Vijayakumar, S.; Bhaduri, D.; Kumar, U.; Mohanty, S.; Panneerselvam, P.; et al. Metal(Loid)s (As, Hg, Se, Pb and Cd) in Paddy Soil: Bioavailability and Potential Risk to Human Health. Sci. Total Environ. 2020, 699, 134330. [Google Scholar] [CrossRef]
  224. Wang, P.; Chen, H.; Kopittke, P.M.; Zhao, F.-J. Cadmium Contamination in Agricultural Soils of China and the Impact on Food Safety. Environ. Pollut. 2019, 249, 1038–1048. [Google Scholar] [CrossRef]
  225. DalCorso, G.; Manara, A.; Furini, A. An Overview of Heavy Metal Challenge in Plants: From Roots to Shoots. Metallomics 2013, 5, 1117. [Google Scholar] [CrossRef]
  226. Clemens, S. Toxic Metal Accumulation, Responses to Exposure and Mechanisms of Tolerance in Plants. Biochimie 2006, 88, 1707–1719. [Google Scholar] [CrossRef]
  227. Kumar, J.; Gaur, S.; Srivastava, P.K.; Mishra, R.K.; Prasad, S.M.; Chauhan, D.K. (Eds.) Heavy Metals in Plants: Physiological to Molecular Approach; CRC Press: Boca Raton, FL, USA, 2022; ISBN 978-1-00-311057-6. [Google Scholar]
  228. Ding, Z.; Wu, J.; You, A.; Huang, B.; Cao, C. Effects of Heavy Metals on Soil Microbial Community Structure and Diversity in the Rice (Oryza sativa L. Subsp. Japonica, Food Crops Institute of Jiangsu Academy of Agricultural Sciences) Rhizosphere. Soil Sci. Plant Nutr. 2017, 63, 75–83. [Google Scholar] [CrossRef]
  229. Belykh, E.S.; Maystrenko, T.A.; Velegzhaninov, I.O. Recent Trends in Enhancing the Resistance of Cultivated Plants to Heavy Metal Stress by Transgenesis and Transcriptional Programming. Mol. Biotechnol. 2019, 61, 725–741. [Google Scholar] [CrossRef]
  230. Williams, L.E.; Mills, R.F. P1B-ATPases—An Ancient Family of Transition Metal Pumps with Diverse Functions in Plants. Trends Plant Sci. 2005, 10, 491–502. [Google Scholar] [CrossRef]
  231. Milner, M.J.; Seamon, J.; Craft, E.; Kochian, L.V. Transport Properties of Members of the ZIP Family in Plants and Their Role in Zn and Mn Homeostasis. J. Exp. Bot. 2013, 64, 369–381. [Google Scholar] [CrossRef] [PubMed]
  232. Li, X.; Wu, Y.; Li, B.; He, W.; Yang, Y.; Yang, Y. Genome-Wide Identification and Expression Analysis of the Cation Diffusion Facilitator Gene Family in Turnip Under Diverse Metal Ion Stresses. Front. Genet. 2018, 9, 103. [Google Scholar] [CrossRef] [PubMed]
  233. Pittman, J.K.; Hirschi, K.D. CAX-Ing a Wide Net: Cation/H + Transporters in Metal Remediation and Abiotic Stress Signalling. Plant Biol. J. 2016, 18, 741–749. [Google Scholar] [CrossRef]
  234. Yuan, M.; Li, X.; Xiao, J.; Wang, S. Molecular and Functional Analyses of COPT/Ctr-Type Copper Transporter-like Gene Family in Rice. BMC Plant Biol. 2011, 11, 69. [Google Scholar] [CrossRef] [PubMed]
  235. Chen, S.; Han, X.; Fang, J.; Lu, Z.; Qiu, W.; Liu, M.; Sang, J.; Jiang, J.; Zhuo, R. Sedum alfredii SaNramp6 Metal Transporter Contributes to Cadmium Accumulation in Transgenic Arabidopsis thaliana. Sci. Rep. 2017, 7, 13318. [Google Scholar] [CrossRef] [PubMed]
  236. Yao, X.; Cai, Y.; Yu, D.; Liang, G. BHLH104 Confers Tolerance to Cadmium Stress in Arabidopsis thaliana. J. Integr. Plant Biol. 2018, 60, 691–702. [Google Scholar] [CrossRef]
  237. Luo, J.-S.; Huang, J.; Zeng, D.-L.; Peng, J.-S.; Zhang, G.-B.; Ma, H.-L.; Guan, Y.; Yi, H.-Y.; Fu, Y.-L.; Han, B.; et al. A Defensin-like Protein Drives Cadmium Efflux and Allocation in Rice. Nat. Commun. 2018, 9, 645. [Google Scholar] [CrossRef] [PubMed]
  238. Verbruggen, N.; Hermans, C.; Schat, H. Molecular Mechanisms of Metal Hyperaccumulation in Plants. New Phytol. 2009, 181, 759–776. [Google Scholar] [CrossRef] [PubMed]
  239. Ghuge, S.A.; Nikalje, G.C.; Kadam, U.S.; Suprasanna, P.; Hong, J.C. Comprehensive Mechanisms of Heavy Metal Toxicity in Plants, Detoxification, and Remediation. J. Hazard. Mater. 2023, 450, 131039. [Google Scholar] [CrossRef] [PubMed]
  240. Tang, L.; Dong, J.; Qu, M.; Lv, Q.; Zhang, L.; Peng, C.; Hu, Y.; Li, Y.; Ji, Z.; Mao, B.; et al. Knockout of OsNRAMP5 Enhances Rice Tolerance to Cadmium Toxicity in Response to Varying External Cadmium Concentrations via Distinct Mechanisms. Sci. Total Environ. 2022, 832, 155006. [Google Scholar] [CrossRef] [PubMed]
  241. Yang, C.; Zhang, Y.; Huang, C. Reduction in Cadmium Accumulation in Japonica Rice Grains by CRISPR/Cas9-Mediated Editing of OsNRAMP5. J. Integr. Agric. 2019, 18, 688–697. [Google Scholar] [CrossRef]
  242. Chen, H.; Ye, R.; Liang, Y.; Zhang, S.; Liu, X.; Sun, C.; Li, F.; Yi, J. Generation of Low-Cadmium Rice Germplasms via Knockout of OsLCD Using CRISPR/Cas9. J. Environ. Sci. 2023, 126, 138–152. [Google Scholar] [CrossRef]
  243. Liu, C.-X.; Yang, T.; Zhou, H.; Ahammed, G.J.; Qi, Z.-Y.; Zhou, J. The E3 Ubiquitin Ligase Gene Sl1 Is Critical for Cadmium Tolerance in Solanum lycopersicum L. Antioxidants 2022, 11, 456. [Google Scholar] [CrossRef]
  244. Wang, F.-Z.; Chen, M.-X.; Yu, L.-J.; Xie, L.-J.; Yuan, L.-B.; Qi, H.; Xiao, M.; Guo, W.; Chen, Z.; Yi, K.; et al. OsARM1, an R2R3 MYB Transcription Factor, Is Involved in Regulation of the Response to Arsenic Stress in Rice. Front. Plant Sci. 2017, 8, 1868. [Google Scholar] [CrossRef]
  245. Zhang, Y.; Chen, K.; Zhao, F.-J.; Sun, C.; Jin, C.; Shi, Y.; Sun, Y.; Li, Y.; Yang, M.; Jing, X.; et al. OsATX1 Interacts with Heavy Metal P1B-Type ATPases and Affects Copper Transport and Distribution. Plant Physiol. 2018, 178, 329–344. [Google Scholar] [CrossRef]
  246. Nieves-Cordones, M.; Mohamed, S.; Tanoi, K.; Kobayashi, N.I.; Takagi, K.; Vernet, A.; Guiderdoni, E.; Périn, C.; Sentenac, H.; Véry, A.-A. Production of Low-Cs+ Rice Plants by Inactivation of the K+ Transporter OsHAK1 with the CRISPR-Cas System. Plant J. 2017, 92, 43–56. [Google Scholar] [CrossRef] [PubMed]
  247. Yue, E.; Rong, F.; Liu, Z.; Ruan, S.; Lu, T.; Qian, H. Cadmium Induced a Non-Coding RNA MicroRNA535 Mediates Cd Accumulation in Rice. J. Environ. Sci. 2023, 130, 149–162. [Google Scholar] [CrossRef] [PubMed]
  248. Songmei, L.; Jie, J.; Yang, L.; Jun, M.; Shouling, X.; Yuanyuan, T.; Youfa, L.; Qingyao, S.; Jianzhong, H. Characterization and Evaluation of OsLCT1 and OsNramp5 Mutants Generated Through CRISPR/Cas9-Mediated Mutagenesis for Breeding Low Cd Rice. Rice Sci. 2019, 26, 88–97. [Google Scholar] [CrossRef]
  249. Chu, C.; Huang, R.; Liu, L.; Tang, G.; Xiao, J.; Yoo, H.; Yuan, M. The Rice Heavy-Metal Transporter OsNRAMP1 Regulates Disease Resistance by Modulating ROS Homoeostasis. Plant Cell Environ. 2022, 45, 1109–1126. [Google Scholar] [CrossRef] [PubMed]
  250. Li, Z.; Rao, M.J.; Li, J.; Wang, Y.; Chen, P.; Yu, H.; Ma, C.; Wang, L. CRISPR/Cas9 Mutant Rice Ospmei12 Involved in Growth, Cell Wall Development, and Response to Phytohormone and Heavy Metal Stress. Int. J. Mol. Sci. 2022, 23, 16082. [Google Scholar] [CrossRef] [PubMed]
  251. Lal, R. Soil Carbon Sequestration to Mitigate Climate Change. Geoderma 2004, 123, 1–22. [Google Scholar] [CrossRef]
  252. White, P.J.; Brown, P.H. Plant Nutrition for Sustainable Development and Global Health. Ann. Bot. 2010, 105, 1073–1080. [Google Scholar] [CrossRef]
  253. Lal, R. Crop Residues as Soil Amendments and Feedstock for Bioethanol Production. Waste Manag. 2008, 28, 747–758. [Google Scholar] [CrossRef]
  254. Tilman, D.; Cassman, K.G.; Matson, P.A.; Naylor, R.; Polasky, S. Agricultural Sustainability and Intensive Production Practices. Nature 2002, 418, 671–677. [Google Scholar] [CrossRef]
  255. Montgomery, D.R. Soil Erosion and Agricultural Sustainability. Proc. Natl. Acad. Sci. USA 2007, 104, 13268–13272. [Google Scholar] [CrossRef]
  256. Pretty, J.; Bharucha, Z.P. Sustainable Intensification in Agricultural Systems. Ann. Bot. 2014, 114, 1571–1596. [Google Scholar] [CrossRef]
  257. Wheeler, T.; von Braun, J. Climate Change Impacts on Global Food Security. Science 2013, 341, 508–513. [Google Scholar] [CrossRef]
  258. Pereira, P.; Bašić, F.; Bogunovic, I.; Barcelo, D. Russian-Ukrainian War Impacts the Total Environment. Sci. Total Environ. 2022, 837, 155865. [Google Scholar] [CrossRef]
  259. Pahalvi, H.N.; Rafiya, L.; Rashid, S.; Nisar, B.; Kamili, A.N. Chemical Fertilizers and Their Impact on Soil Health. In Microbiota and Biofertilizers; Dar, G.H., Bhat, R.A., Mehmood, M.A., Hakeem, K.R., Eds.; Springer International Publishing: Cham, Switzerland, 2021; Volume 2, pp. 1–20. ISBN 978-3-030-61009-8. [Google Scholar]
  260. Pimentel, D.; Harvey, C.; Resosudarmo, P.; Sinclair, K.; Kurz, D.; McNair, M.; Crist, S.; Shpritz, L.; Fitton, L.; Saffouri, R.; et al. Environmental and Economic Costs of Soil Erosion and Conservation Benefits. Science 1995, 267, 1117–1123. [Google Scholar] [CrossRef]
  261. Li, S.; Zhang, C.; Li, J.; Yan, L.; Wang, N.; Xia, L. Present and Future Prospects for Wheat Improvement through Genome Editing and Advanced Technologies. Plant Commun. 2021, 2, 100211. [Google Scholar] [CrossRef] [PubMed]
  262. Liang, C.; Wang, Y.; Zhu, Y.; Tang, J.; Hu, B.; Liu, L.; Ou, S.; Wu, H.; Sun, X.; Chu, J.; et al. OsNAP Connects Abscisic Acid and Leaf Senescence by Fine-Tuning Abscisic Acid Biosynthesis and Directly Targeting Senescence-Associated Genes in Rice. Proc. Natl. Acad. Sci. USA 2014, 111, 10013–10018. [Google Scholar] [CrossRef] [PubMed]
  263. Chen, J.; Zhang, Y.; Tan, Y.; Zhang, M.; Zhu, L.; Xu, G.; Fan, X. Agronomic Nitrogen-Use Efficiency of Rice Can Be Increased by Driving OsNRT2.1 Expression with the OsNAR2.1 Promoter. Plant Biotechnol. J. 2016, 14, 1705–1715. [Google Scholar] [CrossRef]
  264. Wang, D.; Xu, T.; Yin, Z.; Wu, W.; Geng, H.; Li, L.; Yang, M.; Cai, H.; Lian, X. Overexpression of OsMYB305 in Rice Enhances the Nitrogen Uptake Under Low-Nitrogen Condition. Front. Plant Sci. 2020, 11, 369. [Google Scholar] [CrossRef] [PubMed]
  265. Liu, Y.; Hu, B.; Chu, C. Toward Improving Nitrogen Use Efficiency in Rice: Utilization, Coordination, and Availability. Curr. Opin. Plant Biol. 2023, 71, 102327. [Google Scholar] [CrossRef] [PubMed]
  266. Sathee, L.; Jagadhesan, B.; Pandesha, P.H.; Barman, D.; Adavi, B.S.; Nagar, S.; Krishna, G.K.; Tripathi, S.; Jha, S.K.; Chinnusamy, V. Genome Editing Targets for Improving Nutrient Use Efficiency and Nutrient Stress Adaptation. Front. Genet. 2022, 13, 1427. [Google Scholar] [CrossRef]
  267. Aluko, O.O.; Kant, S.; Adedire, O.M.; Li, C.; Yuan, G.; Liu, H.; Wang, Q. Unlocking the Potentials of Nitrate Transporters at Improving Plant Nitrogen Use Efficiency. Front. Plant Sci. 2023, 14, 1074839. [Google Scholar] [CrossRef] [PubMed]
  268. Lu, Y.; Zhu, J.-K. Precise Editing of a Target Base in the Rice Genome Using a Modified CRISPR/Cas9 System. Mol. Plant 2017, 10, 523–525. [Google Scholar] [CrossRef]
  269. Hu, B.; Wang, W.; Ou, S.; Tang, J.; Li, H.; Che, R.; Zhang, Z.; Chai, X.; Wang, H.; Wang, Y.; et al. Variation in NRT1.1B Contributes to Nitrate-Use Divergence between Rice Subspecies. Nat. Genet. 2015, 47, 834–838. [Google Scholar] [CrossRef]
  270. Zhang, J.; Zhang, H.; Li, S.; Li, J.; Yan, L.; Xia, L. Increasing Yield Potential through Manipulating of an ARE1 Ortholog Related to Nitrogen Use Efficiency in Wheat by CRISPR/Cas9. J. Integr. Plant Biol. 2021, 63, 1649–1663. [Google Scholar] [CrossRef] [PubMed]
  271. Karunarathne, S.D.; Han, Y.; Zhang, X.-Q.; Li, C. CRISPR/Cas9 Gene Editing and Natural Variation Analysis Demonstrate the Potential for HvARE1 in Improvement of Nitrogen Use Efficiency in Barley. J. Integr. Plant Biol. 2022, 64, 756–770. [Google Scholar] [CrossRef]
  272. Shen, C.; Li, Q.; An, Y.; Zhou, Y.; Zhang, Y.; He, F.; Chen, L.; Liu, C.; Mao, W.; Wang, X.; et al. The Transcription Factor GNC Optimizes Nitrogen Use Efficiency and Growth by Up-Regulating the Expression of Nitrate Uptake and Assimilation Genes in Poplar. J. Exp. Bot. 2022, 73, 4778–4792. [Google Scholar] [CrossRef]
  273. Yang, X.; Nong, B.; Chen, C.; Wang, J.; Xia, X.; Zhang, Z.; Wei, Y.; Zeng, Y.; Feng, R.; Wu, Y.; et al. OsNPF3.1, a Member of the NRT1/PTR Family, Increases Nitrogen Use Efficiency and Biomass Production in Rice. Crop J. 2023, 11, 108–118. [Google Scholar] [CrossRef]
  274. Varshney, P.; Mikulic, P.; Vonshak, A.; Beardall, J.; Wangikar, P.P. Extremophilic Micro-Algae and Their Potential Contribution in Biotechnology. Bioresour. Technol. 2015, 184, 363–372. [Google Scholar] [CrossRef]
  275. Fernández-Marín, B.; Gulías, J.; Figueroa, C.M.; Iñiguez, C.; Clemente-Moreno, M.J.; Nunes-Nesi, A.; Fernie, A.R.; Cavieres, L.A.; Bravo, L.A.; García-Plazaola, J.I.; et al. How Do Vascular Plants Perform Photosynthesis in Extreme Environments? An Integrative Ecophysiological and Biochemical Story. Plant J. 2020, 101, 979–1000. [Google Scholar] [CrossRef]
  276. Barnard, D.; Casanueva, A.; Tuffin, M.; Cowan, D. Extremophiles in Biofuel Synthesis. Environ. Technol. 2010, 31, 871–888. [Google Scholar] [CrossRef]
  277. Chien, A.; Edgar, D.B.; Trela, J.M. Deoxyribonucleic Acid Polymerase from the Extreme Thermophile Thermus Aquaticus. J. Bacteriol. 1976, 127, 1550. [Google Scholar] [CrossRef]
  278. Marasco, R.; Rolli, E.; Ettoumi, B.; Vigani, G.; Mapelli, F.; Borin, S.; Abou-Hadid, A.F.; El-Behairy, U.A.; Sorlini, C.; Cherif, A.; et al. A Drought Resistance-Promoting Microbiome Is Selected by Root System under Desert Farming. PLoS ONE 2012, 7, e48479. [Google Scholar] [CrossRef] [PubMed]
  279. Acuña-Rodríguez, I.S.; Hansen, H.; Gallardo-Cerda, J.; Atala, C.; Molina-Montenegro, M.A. Antarctic Extremophiles: Biotechnological Alternative to Crop Productivity in Saline Soils. Front. Bioeng. Biotechnol. 2019, 7, 22. [Google Scholar] [CrossRef] [PubMed]
  280. Jorquera, M.A.; Graether, S.P.; Maruyama, F. Editorial: Bioprospecting and Biotechnology of Extremophiles. Front. Bioeng. Biotechnol. 2019, 7, 204. [Google Scholar] [CrossRef] [PubMed]
  281. Cavieres, L.A.; Sáez, P.; Sanhueza, C.; Sierra-Almeida, A.; Rabert, C.; Corcuera, L.J.; Alberdi, M.; Bravo, L.A. Ecophysiological Traits of Antarctic Vascular Plants: Their Importance in the Responses to Climate Change. Plant Ecol. 2016, 217, 343–358. [Google Scholar] [CrossRef]
  282. Morales, M.; Munné-Bosch, S. Oxidative Stress: A Master Regulator of Plant Trade-Offs? Trends Plant Sci. 2016, 21, 996–999. [Google Scholar] [CrossRef]
  283. Orellana, R.; Macaya, C.; Bravo, G.; Dorochesi, F.; Cumsille, A.; Valencia, R.; Rojas, C.; Seeger, M. Living at the Frontiers of Life: Extremophiles in Chile and Their Potential for Bioremediation. Front. Microbiol. 2018, 9, 2309. [Google Scholar] [CrossRef]
  284. Oh, D.-H.; Dassanayake, M.; Bohnert, H.J.; Cheeseman, J.M. Life at the Extreme: Lessons from the Genome. Genome Biol. 2013, 13, 241. [Google Scholar] [CrossRef]
  285. Barak, S.; Farrant, J.M. Extremophyte Adaptations to Salt and Water Deficit Stress. Funct. Plant Biol. 2016, 43, v–x. [Google Scholar] [CrossRef]
  286. Lindgren, A.R.; Buckley, B.A.; Eppley, S.M.; Reysenbach, A.L.; Stedman, K.M.; Wagner, J.T. Life on the Edge—The Biology of Organisms Inhabiting Extreme Environments: An Introduction to the Symposium. Integr. Comp. Biol. 2016, 56, 493–499. [Google Scholar] [CrossRef]
  287. Bechtold, U.; Field, B. Molecular Mechanisms Controlling Plant Growth during Abiotic Stress. J. Exp. Bot. 2018, 69, 2753–2758. [Google Scholar] [CrossRef] [PubMed]
  288. Waqas, M.A.; Kaya, C.; Riaz, A.; Farooq, M.; Nawaz, I.; Wilkes, A.; Li, Y. Potential Mechanisms of Abiotic Stress Tolerance in Crop Plants Induced by Thiourea. Front. Plant Sci. 2019, 10, 1336. [Google Scholar] [CrossRef] [PubMed]
  289. Ostria-Gallardo, E.; Larama, G.; Berríos, G.; Fallard, A.; Gutiérrez-Moraga, A.; Ensminger, I.; Bravo, L.A. A Comparative Gene Co-Expression Analysis Using Self-Organizing Maps on Two Congener Filmy Ferns Identifies Specific Desiccation Tolerance Mechanisms Associated to Their Microhabitat Preference. BMC Plant Biol. 2020, 20, 56. [Google Scholar] [CrossRef] [PubMed]
  290. Costa-Silva, J.; Domingues, D.; Lopes, F.M. RNA-Seq Differential Expression Analysis: An Extended Review and a Software Tool. PLoS ONE 2017, 12, e0190152. [Google Scholar] [CrossRef]
  291. Ali, A.; Cheol Park, H.; Aman, R.; Ali, Z.; Yun, D.-J. Role of HKT1 in Thellungiella Salsugine a, a Model Extremophile Plant. Plant Signal. Behav. 2013, 8, e25196. [Google Scholar] [CrossRef] [PubMed]
  292. Ali, A.; Khan, I.U.; Jan, M.; Khan, H.A.; Hussain, S.; Nisar, M.; Chung, W.S.; Yun, D.-J. The High-Affinity Potassium Transporter EpHKT1;2 From the Extremophile Eutrema Parvula Mediates Salt Tolerance. Front. Plant Sci. 2018, 9, 1108. [Google Scholar] [CrossRef] [PubMed]
  293. Wang, W.-Y.; Liu, Y.-Q.; Duan, H.-R.; Yin, X.-X.; Cui, Y.-N.; Chai, W.-W.; Song, X.; Flowers, T.J.; Wang, S.-M. SsHKT1;1 Is Coordinated with SsSOS1 and SsNHX1 to Regulate Na+ Homeostasis in Suaeda Salsa under Saline Conditions. Plant Soil 2020, 449, 117–131. [Google Scholar] [CrossRef]
  294. Boulc’h, P.-N.; Caullireau, E.; Faucher, E.; Gouerou, M.; Guérin, A.; Miray, R.; Couée, I. Abiotic Stress Signalling in Extremophile Land Plants. J. Exp. Bot. 2020, 71, 5771–5785. [Google Scholar] [CrossRef]
  295. Flowers, T.J.; Colmer, T.D. Salinity Tolerance in Halophytes. New Phytol. 2008, 179, 945–963. [Google Scholar] [CrossRef]
  296. Qiu, Q.; Ma, T.; Hu, Q.; Liu, B.; Wu, Y.; Zhou, H.; Wang, Q.; Wang, J.; Liu, J. Genome-Scale Transcriptome Analysis of the Desert Poplar, Populus Euphratica. Tree Physiol. 2011, 31, 452–461. [Google Scholar] [CrossRef] [PubMed]
  297. Vu, T.V.; Sivankalyani, V.; Kim, E.-J.; Doan, D.T.H.; Tran, M.T.; Kim, J.; Sung, Y.W.; Park, M.; Kang, Y.J.; Kim, J.-Y. Highly Efficient Homology-Directed Repair Using CRISPR/Cpf1-Geminiviral Replicon in Tomato. Plant Biotechnol. J. 2020, 18, 2133–2143. [Google Scholar] [CrossRef]
  298. Zhao, H.; Wang, L.; Zhao, F.-J.; Wu, L.; Liu, A.; Xu, W. SpHMA1 Is a Chloroplast Cadmium Exporter Protecting Photochemical Reactions in the Cd Hyperaccumulator Sedum Plumbizincicola. Plant Cell Environ. 2019, 42, 1112–1124. [Google Scholar] [CrossRef]
  299. Biswas, P.; Anand, U.; Ghorai, M.; Pandey, D.K.; Jha, N.K.; Behl, T.; Kumar, M.; Chauhan, R.; Shekhawat, M.S.; Dey, A. Unraveling the Promise and Limitations of CRISPR/Cas System in Natural Product Research: Approaches and Challenges. Biotechnol. J. 2022, 17, 2100507. [Google Scholar] [CrossRef] [PubMed]
  300. Ahmad, S.; Wei, X.; Sheng, Z.; Hu, P.; Tang, S. CRISPR/Cas9 for Development of Disease Resistance in Plants: Recent Progress, Limitations and Future Prospects. Brief. Funct. Genom. 2020, 19, 26–39. [Google Scholar] [CrossRef]
  301. Chen, J.; Li, S.; He, Y.; Li, J.; Xia, L. An Update on Precision Genome Editing by Homology-Directed Repair in Plants. Plant Physiol. 2022, 188, 1780–1794. [Google Scholar] [CrossRef]
  302. Gong, Z.; Cheng, M.; Botella, J.R. Non-GM Genome Editing Approaches in Crops. Front. Genome Ed. 2021, 3, 40. [Google Scholar] [CrossRef] [PubMed]
  303. Chen, Z.; Debernardi, J.M.; Dubcovsky, J.; Gallavotti, A. Recent Advances in Crop Transformation Technologies. Nat. Plants 2022, 8, 1343–1351. [Google Scholar] [CrossRef] [PubMed]
  304. Lowe, K.; Wu, E.; Wang, N.; Hoerster, G.; Hastings, C.; Cho, M.-J.; Scelonge, C.; Lenderts, B.; Chamberlin, M.; Cushatt, J.; et al. Morphogenic Regulators Baby Boom and Wuschel Improve Monocot Transformation. Plant Cell 2016, 28, 1998–2015. [Google Scholar] [CrossRef]
  305. Cao, X.; Xie, H.; Song, M.; Lu, J.; Ma, P.; Huang, B.; Wang, M.; Tian, Y.; Chen, F.; Peng, J.; et al. Cut–Dip–Budding Delivery System Enables Genetic Modifications in Plants without Tissue Culture. Innovation 2023, 4, 100345. [Google Scholar] [CrossRef]
  306. Lee, T.G.; Hutton, S.F. Field Evaluation of CRISPR-Driven Jointless Pedicel Fresh-Market Tomatoes. Agronomy 2021, 11, 1957. [Google Scholar] [CrossRef]
  307. Neequaye, M.; Stavnstrup, S.; Harwood, W.; Lawrenson, T.; Hundleby, P.; Irwin, J.; Troncoso-Rey, P.; Saha, S.; Traka, M.H.; Mithen, R.; et al. CRISPR-Cas9-Mediated Gene Editing of MYB28 Genes Impair Glucoraphanin Accumulation of Brassica Oleracea in the Field. CRISPR J. 2021, 4, 416–426. [Google Scholar] [CrossRef]
  308. Shabbir, R.; Singhal, R.K.; Mishra, U.N.; Chauhan, J.; Javed, T.; Hussain, S.; Kumar, S.; Anuragi, H.; Lal, D.; Chen, P. Combined Abiotic Stresses: Challenges and Potential for Crop Improvement. Agronomy 2022, 12, 2795. [Google Scholar] [CrossRef]
  309. Metje-Sprink, J.; Sprink, T.; Hartung, F. Genome-Edited Plants in the Field. Curr. Opin. Biotechnol. 2020, 61, 1–6. [Google Scholar] [CrossRef]
  310. Faure, J.-D.; Napier, J.A. Europe’s First and Last Field Trial of Gene-Edited Plants? eLife 2018, 7, e42379. [Google Scholar] [CrossRef]
  311. Raffan, S.; Oddy, J.; Mead, A.; Barker, G.; Curtis, T.; Usher, S.; Burt, C.; Halford, N.G. Field Assessment of Genome-edited, Low Asparagine Wheat: Europe’s First CRISPR Wheat Field Trial. Plant Biotechnol. J. 2023. [Google Scholar] [CrossRef] [PubMed]
  312. Medvedieva, M.O.; Blume, Y.B. Legal Regulation of Plant Genome Editing with the CRISPR/Cas9 Technology as an Example. Cytol. Genet. 2018, 52, 204–212. [Google Scholar] [CrossRef]
  313. Kuzma, J. Social Concerns and Regulation of Cisgenic Crops in North America. In Cisgenic Crops: Safety, Legal and Social Issues; Chaurasia, A., Kole, C., Eds.; Concepts and Strategies in Plant Sciences; Springer International Publishing: Cham, Switzerland, 2023; pp. 179–194. ISBN 978-3-031-10721-4. [Google Scholar]
  314. Ahmad, A.; Munawar, N.; Khan, Z.; Qusmani, A.T.; Khan, S.H.; Jamil, A.; Ashraf, S.; Ghouri, M.Z.; Aslam, S.; Mubarik, M.S.; et al. An Outlook on Global Regulatory Landscape for Genome-Edited Crops. Int. J. Mol. Sci. 2021, 22, 11753. [Google Scholar] [CrossRef] [PubMed]
  315. Gatica-Arias, A. The Regulatory Current Status of Plant Breeding Technologies in Some Latin American and the Caribbean Countries. Plant Cell Tiss. Organ Cult. 2020, 141, 229–242. [Google Scholar] [CrossRef]
  316. Sprink, T.; Wilhelm, R.; Hartung, F. Genome Editing around the Globe: An Update on Policies and Perceptions. Plant Physiol. 2022, 190, 1579–1587. [Google Scholar] [CrossRef]
  317. Wunderlich, S.; Gatto, K.A. Consumer Perception of Genetically Modified Organisms and Sources of Information. Adv. Nutr. 2015, 6, 842–851. [Google Scholar] [CrossRef]
  318. Ortega, D.L.; Lin, W.; Ward, P.S. Consumer Acceptance of Gene-Edited Food Products in China. Food Qual. Prefer. 2022, 95, 104374. [Google Scholar] [CrossRef]
  319. da Silva Santos, C.R.; Teixeira, S.M.; Cruz, J.E.; Bron, P.C. Perception of Producers and Consumers on the Adoption of Genetically Modified Food: The Case of the Transgenic Bean BRSFC401 RMD. Rev. Econ. Sociol. Rural 2023, 61, e25027. [Google Scholar] [CrossRef]
  320. Bearth, A.; Kaptan, G.; Kessler, S.H. Genome-Edited versus Genetically-Modified Tomatoes: An Experiment on People’s Perceptions and Acceptance of Food Biotechnology in the UK and Switzerland. Agric. Hum. Values 2022, 39, 1117–1131. [Google Scholar] [CrossRef]
  321. Menz, J.; Modrzejewski, D.; Hartung, F.; Wilhelm, R.; Sprink, T. Genome Edited Crops Touch the Market: A View on the Global Development and Regulatory Environment. Front. Plant Sci. 2020, 11, 586027. [Google Scholar] [CrossRef]
Figure 1. CRISPR/Cas-mediated immunity in bacteria: Three main phases. Image adapted from CRISPR-Cas9 adaptive immune system of Streptococcus pyogenes against bacteriophages template by BioRender.com (2023). Retrieved from https://app.biorender.com/biorender-templates, accessed on 31 March 2023.
Figure 1. CRISPR/Cas-mediated immunity in bacteria: Three main phases. Image adapted from CRISPR-Cas9 adaptive immune system of Streptococcus pyogenes against bacteriophages template by BioRender.com (2023). Retrieved from https://app.biorender.com/biorender-templates, accessed on 31 March 2023.
Plants 12 01892 g001
Figure 2. New original research papers per year in the Web of Science database (webofscience.com) from 2013 to 2021 containing the keywords “plant” and “CRISPR”.
Figure 2. New original research papers per year in the Web of Science database (webofscience.com) from 2013 to 2021 containing the keywords “plant” and “CRISPR”.
Plants 12 01892 g002
Figure 3. Standard protocol for generating transgene-free gene-edited plants using CRISPR/Cas9. (a) The use of protoplasts is the most common technique for validating CRISPR/Cas9 construct designs and generating transient gene expression. (b) Then, Agrobacterium-mediated transformation is the common technique to generate CRISPR/Cas9 mutated plants with a stable gene expression. (c) Finally, elimination of transgenic sequences is performed to generate “null segregants” via Mendelian segregation. Images (a,b) are adapted from Agrobacterium-Mediated Transformation and CRISPR-Cas9 Gene Editing in Trypanosoma cruzi templates by BioRender.com (2022). Retrieved from https://app.biorender.com/biorender-templates, accessed on 31 March 2023.
Figure 3. Standard protocol for generating transgene-free gene-edited plants using CRISPR/Cas9. (a) The use of protoplasts is the most common technique for validating CRISPR/Cas9 construct designs and generating transient gene expression. (b) Then, Agrobacterium-mediated transformation is the common technique to generate CRISPR/Cas9 mutated plants with a stable gene expression. (c) Finally, elimination of transgenic sequences is performed to generate “null segregants” via Mendelian segregation. Images (a,b) are adapted from Agrobacterium-Mediated Transformation and CRISPR-Cas9 Gene Editing in Trypanosoma cruzi templates by BioRender.com (2022). Retrieved from https://app.biorender.com/biorender-templates, accessed on 31 March 2023.
Plants 12 01892 g003
Figure 4. Overlap between genes involved in drought and salinity stresses in CRISPR studies presented in this review. There are a total of 35 studies of gene editing promoting enhanced drought tolerance, of which five overlap with enhanced salinity tolerance. Studies of reduced drought tolerance sum to 47, of which four also show reduced salinity tolerance. For salinity, a total of 13 genes shows enhanced tolerance, while 12 show reduced tolerance.
Figure 4. Overlap between genes involved in drought and salinity stresses in CRISPR studies presented in this review. There are a total of 35 studies of gene editing promoting enhanced drought tolerance, of which five overlap with enhanced salinity tolerance. Studies of reduced drought tolerance sum to 47, of which four also show reduced salinity tolerance. For salinity, a total of 13 genes shows enhanced tolerance, while 12 show reduced tolerance.
Plants 12 01892 g004
Figure 5. Schematic depicting the use of extremophytes and new sequencing technologies to identify new gene targets that can be modified in crops using CRISPR/Cas9. Image created with BioRender.com, accessed on 31 March 2023.
Figure 5. Schematic depicting the use of extremophytes and new sequencing technologies to identify new gene targets that can be modified in crops using CRISPR/Cas9. Image created with BioRender.com, accessed on 31 March 2023.
Plants 12 01892 g005
Table 1. Studies employing CRISPR/Cas on genes related to drought stress. TF: Transcription Factor; GA: Gibberellic acid; ABA: Abscisic acid; BR: Brassinosteroid; SA: Salicylic acid; KO = Knockout; KD = Knockdown; I.N.F. = Information Not Found, KU: Knokup.
Table 1. Studies employing CRISPR/Cas on genes related to drought stress. TF: Transcription Factor; GA: Gibberellic acid; ABA: Abscisic acid; BR: Brassinosteroid; SA: Salicylic acid; KO = Knockout; KD = Knockdown; I.N.F. = Information Not Found, KU: Knokup.
SpeciesTarget LocusPathway/FunctionEffect on ToleranceResultReference
Brassica napusBnaA6.RGAGrowth regulation/DELLA transcription regulatorEnhancedGain-of-function[85]
BnaA6.RGA
BnaC7.RGA
BnaA9.RGA
BnaC9.RGA
Growth regulation/DELLA transcription regulatorReducedKO[85]
Cucumis sativusCsAKT1Osmoregulation/K+ transporterReducedKO[86]
Fragaria vescaFvICE1Cold stress response/TFReducedKO[87]
Glycine maxGmHdz4Drought stress response/HD-ZIP I TFEnhancedKO[88]
GmLHY1a
GmLHY1b
GmLHY2a
GmLHY2b
Regulation of circadian rhythm/TFEnhancedKO[89]
GmCOL1aFlowering time/CONSTANS-like TFReducedKO[90]
GmMYB118Flavonoid biosynthesis/MYB TFReducedAmino acid change[91]
GmNAC12Abiotic stress response/NAC TFReducedKO[92]
GmNAC8Nodulation, abiotic stress response/NAC TFReducedKO[93]
Medicago sativaMsSPL8Nodulation, growth, GA pathway/SPL TFEnhancedKD[94]
Nicotiana tabacumNtAITR1
NtAITR2
NtAITR3
NtAITR5
NtAITR6
ROS homeostasis/ABA-induced transcription repressorsEnhancedI.N.F.[95]
NtPOD63LCell wall integrity/class III peroxidaseEnhancedKO[96]
NtRAV4Growth, development, stress response/RAV TFEnhancedKO[97]
Oryza sativaGhd2Grain development, flowering/CCT TFEnhancedKO[98]
JMJ710Flowering time/Histone demethylaseEnhancedKO[99]
osa-MIR535Phosphate homeostasis, root development/Drought-induced miRNAsEnhancedKO[100]
OsABA8ox2Biosynthesis of ABA/ABA hydroxylaseEnhancedKO[101]
OsDSTABA-dependent stress signaling/Zinc finger TFEnhancedDomain deletion[102]
OsERA1BR signaling/GASA growth regulatorEnhancedI.N.F.[103]
OsFTL4Flowering/PEBP, florigenEnhancedKO[104]
OsIPK1Growth, development, ion homeostasis/KinaseEnhanced11-aminoacid deletion[105]
OsNAC016Growth, development, hormone signaling, abiotic stress response/NAC TFEnhancedKO[106]
OsNAC092Biotic and abiotic stress response/NAC TFEnhancedKO[107]
OsNR1.2Nitrogen metabolism/Nitrate reductaseEnhancedKO[108]
OsPPR035Energy metabolism, stress response/Mitochondrial RNA editingEnhancedKO[109]
OsPPR406Energy metabolism, stress response/Mitochondrial RNA editingEnhancedKO[109]
OsPYL9Stress responses/ABA receptorEnhancedKO[110]
OsWRKY5ABA signaling/WRKY TFEnhancedKO[111]
SRL1,2Root development, stress response/LRR-RLK proteinEnhancedKD[112]
osa-MIR171Flavonoid biosynthesis/microRNAReducedKO[113]
osa-MIR818bStress response/Drought-induced miRNAsReducedKD[114]
OsADR3Spikelet development/MADS-box TFReducedKO[115]
OsASLRKRoot development/Armadillo-like Repeat KinesinReducedKD[116]
OsbZIP86Stress response/bZIP TFReducedKO[117]
OsCCR10Biosynthesis of lignin/cinnamoyl-CoA reductaseReducedKO[118]
OsDIP1Root water uptake/AquaporinReducedKO[119]
OsFTIP6Flowering, leaf senescence, plant architecture/Florigen transporterReducedKO[120]
OsGRP3RNA processing/Glycine-rich RNA-binding proteinReducedKO[121]
OsHB22Growth, development, abiotic stress response/HD-ZIP TFReducedKO[120]
OsMYB60Osmoprotectants and antioxidants biosynthesis/MYB TFReducedKO[122]
OsMYBR57Drought stress response/MYB-Related TFReducedKO[120]
OsNAC006Abiotic stress response/NAC TFReducedKO[123]
OsNAC17Development, stress response/NAC TFReducedKO[124]
OsNPF8.1Nutrient acquisition/Phosphate transporterReducedKO[125]
OsPM1Ion homeostasis/Plasma membrane proteinReducedKO[126]
OsPUB67Protein degradation, root development/U-box E3 ubiquitin ligaseReducedKO[127]
OsRINGzf1Protein degradation/RING zinc finger E3 ligaseReducedKO[128]
OsRNS4Biotic and abiotic stress response/S-like RNAseReducedKD[116]
OsSAPK2Stress/ABA–activated protein kinaseReducedKO[129]
OsSAPK3Stress/ABA–activated protein kinaseReducedKO[130]
IPA1/OsSPL14Growth, development, environmental stimuli response/SPL TFReducedKO[131]
OsAO3ABA biosynthesis/Aldehyde oxidaseReducedKO[132]
Populus clone 717-1B4 (Populus tremula × Populus alba)PdGNCCarbon and nitrogen metabolism/TFReducedKO[133]
Populus clone NE-19 (Populus nigra × (Populus deltoides × P. nigra))PdNF-YB21Flowering, growth, abiotic stress response/NF-Y TFReducedKO[134]
Populus trichocarpaPtrADA2b-3Chromatin modification/Histone acetyltransferase adaptorReducedKO[135]
Solanum lycopersicumSlALD1Stress responses/Pipecolic acidEnhancedKO[136]
SlARF4Auxin signaling/Auxin response factorEnhancedKO[137]
SlRR26Cytokinin pathway/Type-B Response RegulatorEnhancedKO[138]
SlSNAT2Negative regulation of rbcL/RUBISCO lysine acetylaseEnhancedKO[139]
SlLBD40Lateral root development/LBD TFReducedKO[140]
SlMAPK3Biotic and abiotic stress response/Mitogen-Activated Protein KinaseReducedKO[141]
SlNPR1Plant immunity/SA receptorReducedKO[142]
SP3CAnti-florigen/PEBPReducedKO[143]
Solanum tuberosumStFLOREFlowering/long non-coding RNAReducedKD[144]
Triticum aestivumTaSal1
(6 homeologs)
Monophosphate 3′-phosphoadenosine 5′phosphate (PAP) signalingEnhancedKO[145]
TaCER1-6ACuticle biosynthesisReducedKO[146]
TaIPT8Cytokinin biosynthesis/isopentenyltransferaseReducedKO[147]
TaPYL1-1BAbscisic acid receptorReducedKD[148]
Vitis viniferaVvEPFL9-1Stomata formationEnhancedKO[149]
Zea maysARGOS8Negative regulator of ethylene responsesEnhancedKU[150]
ZmLBD5LBD Transcription factorEnhancedKO[151]
ZmLRTlateral root Development/miR166a-encoding geneEnhancedKO[152]
ZmPP84PP2C PhosphataseEnhancedKO[153]
ZmSAG39Papain-like cysteine proteasesEnhancedKO[154]
ZmTCP14TCP Transcription factorEnhancedKO[155]
ZmATHB-6Homeobox Transcription FactorReducedKO[156]
ZmEREB46Ethylene-responsive Transcription factorReducedKO[157]
ZmRBOHCNADPH oxidaseReducedKO[158]
ZmRtn16Reticulon-like proteinReducedKO[159]
ZmSRL5Cuticle biosynthesisReducedKO[160]
ZmSRO1d-SOxidative and abiotic stress responseReducedKO[158]
Table 2. Studies employing CRISPR/Cas on genes related to flooding stress. GA: Gibberellic Acid; ABA: Abscisic Acid; KO = Knockout.
Table 2. Studies employing CRISPR/Cas on genes related to flooding stress. GA: Gibberellic Acid; ABA: Abscisic Acid; KO = Knockout.
SpeciesTarget LocusPathway/FunctionEffect on ToleranceResultReference
Oryza sativaOsGF14hABA and GA signaling/14-3-3 proteinReducedKO[171]
SUB1AEthylene-responsive transcription factorReducedKO[172]
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Gajardo, H.A.; Gómez-Espinoza, O.; Boscariol Ferreira, P.; Carrer, H.; Bravo, L.A. The Potential of CRISPR/Cas Technology to Enhance Crop Performance on Adverse Soil Conditions. Plants 2023, 12, 1892. https://doi.org/10.3390/plants12091892

AMA Style

Gajardo HA, Gómez-Espinoza O, Boscariol Ferreira P, Carrer H, Bravo LA. The Potential of CRISPR/Cas Technology to Enhance Crop Performance on Adverse Soil Conditions. Plants. 2023; 12(9):1892. https://doi.org/10.3390/plants12091892

Chicago/Turabian Style

Gajardo, Humberto A., Olman Gómez-Espinoza, Pedro Boscariol Ferreira, Helaine Carrer, and León A. Bravo. 2023. "The Potential of CRISPR/Cas Technology to Enhance Crop Performance on Adverse Soil Conditions" Plants 12, no. 9: 1892. https://doi.org/10.3390/plants12091892

APA Style

Gajardo, H. A., Gómez-Espinoza, O., Boscariol Ferreira, P., Carrer, H., & Bravo, L. A. (2023). The Potential of CRISPR/Cas Technology to Enhance Crop Performance on Adverse Soil Conditions. Plants, 12(9), 1892. https://doi.org/10.3390/plants12091892

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop