Next Article in Journal
Optimizing Embryo Collection for Application of CRISPR/Cas9 System and Generation of Fukutin Knockout Rat Using This Method
Next Article in Special Issue
Functional Validation of Different Alternative Splicing Variants of the Chrysanthemum lavandulifolium ClNUM1 Gene in Tobacco
Previous Article in Journal
Phospho-Chitooligosaccharides below 1 kDa Inhibit HIV-1 Entry In Vitro
Previous Article in Special Issue
Biochemical and Molecular Basis of Chemically Induced Defense Activation in Maize against Banded Leaf and Sheath Blight Disease
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
CIMB
Volume 46
Issue 4
10.3390/cimb46040233
cimb-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Enhancing Yield and Improving Grain Quality in Japonica Rice: Targeted EHD1 Editing via CRISPR-Cas9 in Low-Latitude Adaptation

by
Jian Song
1,†,
Liqun Tang
1,†,
Honghuan Fan
1,
Xiaozheng Xu
2,
Xinlu Peng
2,
Yongtao Cui
1 and
Jianjun Wang
1,*
1
Institute of Crops and Nuclear Technology Utilization, Zhejiang Academy of Agricultural Sciences, Hangzhou 310021, China
2
College of Advanced Agriculture Sciences, Zhejiang A&F University, Hangzhou 311300, China
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Curr. Issues Mol. Biol. 2024, 46(4), 3741-3751; https://doi.org/10.3390/cimb46040233
Submission received: 25 March 2024 / Revised: 15 April 2024 / Accepted: 19 April 2024 / Published: 22 April 2024
(This article belongs to the Special Issue Molecular Breeding and Genetics Research in Plants)
Browse Figures
Review Reports Versions Notes

Abstract

:
The “Indica to Japonica” initiative in China focuses on adapting Japonica rice varieties from the northeast to the unique photoperiod and temperature conditions of lower latitudes. While breeders can select varieties for their adaptability, the sensitivity to light and temperature often complicates and prolongs the process. Addressing the challenge of cultivating high-yield, superior-quality Japonica rice over expanded latitudinal ranges swiftly, in the face of these sensitivities, is critical. Our approach harnesses the CRISPR-Cas9 technology to edit the EHD1 gene in the premium northeastern Japonica cultivars Jiyuanxiang 1 and Yinongxiang 12, which are distinguished by their exceptional grain quality—increased head rice rates, gel consistency, and reduced chalkiness and amylose content. Field trials showed that these new ehd1 mutants not only surpass the wild types in yield when grown at low latitudes but also retain the desirable traits of their progenitors. Additionally, we found that disabling Ehd1 boosts the activity of Hd3a and RFT1, postponing flowering by approximately one month in the ehd1 mutants. This research presents a viable strategy for the accelerated breeding of elite northeastern Japonica rice by integrating genomic insights with gene-editing techniques suitable for low-latitude cultivation.

1. Introduction

The cultivation of high-yield crop varieties has significantly enhanced agricultural performance, particularly in adapting to diverse latitudes [1]. The photoperiod is a critical factor in this adaptation, as it significantly influences crop yields. In China, Oryza sativa L., predominantly a short-day (SD) crop, has evolved into two main subspecies: indica and japonica [2]. Traditionally, indica is cultivated in southern China’s lower-latitude areas, while Japonica is grown in the mid-latitude regions of the northeastern plain and along the Yangtze River [3]. Northeastern japonica rice is increasingly preferred for its superior grain quality. However, attempts to breed northeastern Japonica-like rice at lower latitudes have faced challenges due to photosensitivity or temperature sensitivity [4,5,6]. Selecting the optimal flowering time for southern China’s lower-latitude areas could enable the expansion of Japonica rice from north to south. However, traditional breeding methods are time-consuming [7]. Recent molecular genetic research has uncovered beneficial photoperiod-associated alleles in elite cultivars [8,9], paving the way for advanced gene-editing techniques, such as the clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated 9 (Cas9) system [10,11].
Photoperiod conditions significantly promote rice heading [8]. Rice has evolved two distinct flowering pathways: a long-day (LD) flowering suppression pathway and a flowering-promotion pathway [8,12]. Under both LD and SD conditions, Ehd1, a B-type response regulator, plays a crucial role in integrating these signals. Ehd1 enhances heading by elevating the expression of Hd3a and RFT1 under SD conditions [13,14]. Various genes modulate the expression of Ehd1. For instance, RID1/Ehd2/OsID1, SE5, OsMADS51, and others positively influence Ehd1 [15,16], while Heading Date 1 (Hd1), Ghd7, COL4, and DTH8/Ghd8/Hd5 have a negative impact [8,17,18,19,20]. Hd1 is unique, suppressing heading under LD and promoting it under SD [17]. The roles of other key regulatory genes, like Ghd7, Hd2, and DTH8, are necessary for Hd1 to reduce heading under LD [9,21]. SE5 is involved in phytochrome chromophore biosynthesis [16]. Mutations in se5 result in early heading under both SD and LD conditions. The AP2 genes, containing the miR172 target site, act as repressors of Ehd1 [22]. Loss of Ehd1 function leads to extended flowering times and exhibits elite agronomic traits at low latitudes, as demonstrated in the Longdao16 and Longdao24 rice varieties [3]. Therefore, Ehd1 presents a potential target for genome editing to facilitate the adaptation of Japonica rice from north to south.
Addressing the pressing need to rapidly breed a diverse array of modern varieties, our study introduces a method using the CRISPR-Cas9 technique. We applied this technique to edit the EHD1 gene in elite northeastern Japonica varieties, including Jiyuanxiang 1 and Yinongxiang 12, which are known for their superior grain quality (higher head rice rates; gel consistency; and lower chalky rice rates, chalkiness degree, and amylose content). The objectives include achieving suitable flowering times and elite plant architecture for modern rice production at low latitudes while preserving the superior grain quality traits of the progenitors. This endeavor represents an integration of gene editing with existing Japonica rice landraces and breeding strategies in northeastern China, aiming to enhance the adaptation of Japonica rice and breed new, modern varieties suitable for low-latitude regions.

2. Materials and Methods

2.1. Plant Materials and Growth Conditions

The transgenic plants used in this study were of the Yinongxiang and Jiyuanxiang varieties. All rice plants were cultivated in paddy fields under natural conditions at locations in Hangzhou and LingShui, managed by the Zhejiang Academy of Agricultural Sciences, China.

2.2. Agronomic Trait Measurements

Upon reaching maturity, primary agronomic traits such as plant height, tiller count, leaf length, leaf breadth, spikelet length, number of primary and secondary branches, and seed-setting rate were evaluated. For each trait, data were collected from three biological replicates.

2.3. Plasmid Construction

The CRISPR/Cas9 system was utilized to target the EHD1 gene, with two specific target sites designed. gRNA1EHD1 and gRNA2EHD1 were initially digested and then assembled into an intermediate vector [23]. This intermediate vector was subsequently incorporated into the pC1300-Cas9 binary vector. Details of the target sequences can be found in Supplementary Table S3. The binary vector loaded with two sgRNAs was employed for genetic transformation using the Agrobacterium-mediated transformation method (strain EHA105), as outlined in previous studies [24].

2.4. Detection of Mutations

Genomic DNA was extracted from approximately 100 mg of leaf tissue from the transgenic rice plants by using the CTAB method. PCR amplification of the fragments surrounding the target sites was performed by using KOD FX DNA polymerase (Toyobo Co., Ltd., Osaka, Japan). The amplified DNA fragments were then sequenced using the Sanger method (Applied Biosystems, Foster City, CA, USA) and analyzed by the degenerate sequence decoding method [25,26]. To identify transgene-free plants, PCR amplification was conducted by using specific primers for the hygromycin phosphotransferase gene.

2.5. RNA Extraction and RT-PCR

Total RNA was extracted from leaf tissues by using TRIzol reagent (Thermo Fisher Scientific, Waltham, MA, USA). First-strand cDNA synthesis was performed by using 1 μg of RNA and the ReverTra Ace qPCR RT Master Mix with gDNA Remover (Toyobo Co., Ltd., Osaka, Japan). Real-time PCR was conducted on each cDNA sample in duplicate. The quantitative real-time PCR experiments were performed by using the Power SYBR Green PCR Master Mix kit (Applied Biosystems, Foster City, CA, USA) under specified conditions. The rice UBIQUITIN gene served as an internal control, and relative expression ratios were calculated by using the 2−ΔΔCT method. Gene-specific primers are listed in Table S3.

2.6. Photoperiod and Temperature Treatments

ycas-1, jcas-2, and WT plants were sown on 15 June 2022 at the Institute of Crops and Nuclear Technology Utilization, Zhejiang Academy of Agricultural Sciences. Fifty-eight-day-old plants underwent photoperiod and temperature treatments in growth chambers. Plants were treated for 7 days and sampled randomly every 3 days over a 10-day period, with each sampling involving three biological replicates.

2.7. Measurement of Amylose, Gel Consistency, and Alkali Spreading Value

Amylose content and gel consistency in mature grains of WT, ycas-1, and jcas-2 plants were measured by using the concanavalin A-based method (Sigma-Aldrich, St. Louis, MO, USA). Gel consistency was determined by the alkali digestion test (Sigma-Aldrich, St. Louis, MO, USA), which involved evaluating starchy endosperm by using a standard seven-point numerical spreading scale. The alkali spreading value (ASV) classified the gelatinization temperature (GT) of rice grains into four groups: high (1–2), high–intermediate (3), intermediate (4–5), and low (6–7)

2.8. Statistical Analysis

Data were expressed as mean values ± standard deviations (SDs) based on three biological replicates. Statistical significance was determined by using Student’s unpaired t-test and Duncan’s multiple range test. Significance levels were set at 5% (indicated by a single asterisk, *) and 1% (indicated by a double asterisk, **) for the t-test. For Duncan’s multiple range test, significance levels were also set at 5% and 1%, and these are indicated in the respective figures and tables with different letters to denote statistically significant differences among the groups.

3. Results

3.1. Early Flowering of Northeastern Japonica Rice at Low Latitudes

A study involving 119 high-grain-quality northeastern Japonica rice varieties in Hangzhou, a low-latitude region, revealed that these varieties flower 30–50 days earlier than the local cultivars, Zhe 08A and Zhejing 99 (Figure S1, Table S1). This early flowering, however, limits their direct application in low-latitude regions. The findings suggest the need for improvement in genes associated with the long-day flowering suppression pathway.

3.2. Both ehd1-Ji Yuan Xiang 1 and ehd1-Yi Nong Xiang 12 Display Delayed Heading Date and Good Field Performance

Among the varieties studied, Ji Yuan Xiang 1 and Yi Nong Xiang 12 were selected for modification of their flowering time. We employed the CRISPR/Cas9 system to target the EHD1 gene in these varieties, building upon previous research for the construction of the CRISPR/Cas9 vector. The gRNA1 and gRNA2 targeting sites were strategically designed within the third exon of the EHD1 gene (Figure 1A). Initial steps involved cloning the target sequences into SK-gRNA vectors, followed by assembling these gRNAs into a single intermediate vector to create a combined SK–gRNA1EHD1–gRNA2EHD1 structure. Subsequently, the sgRNAs were incorporated into the pC1300-Cas9 expression vector for genetic transformation. This resulted in 21 and 38 positive transgenic plants for Yinongxiang 12 and Jiyuanxiang 1, respectively, in the T0 generation (Table S2). The sequencing of the target regions in these plants revealed mutation rates of 0% and 47.6% at the gRNA1 and gRNA2 targeting sites in Yinongxiang 12, and 7.9% and 34.2% in Jiyuanxiang 1, respectively. These results demonstrate that the CRISPR/Cas9-mediated editing efficiency significantly varies between the two rice varieties Jiyuanxiang 1 and Yinongxiang 12, highlighting the influence of distinct genetic backgrounds on gene-editing outcomes. This underscores the necessity for tailored gene-editing strategies when targeting specific traits within different agricultural varieties.
To assess the phenotypic consequences of the new ehd1 mutations and eliminate selective marker genes and T-DNA elements, T0 progeny plants underwent DNA sequencing and were self-pollinated to produce T1 progeny. T2 progeny, either homozygous for ehd1/ehd1 or free of T-DNA, were subjected to phenotypic screening and genotyping (Figure S2). The sequencing analysis identified deletions or insertions at the predicted editing sites in ycas-1, ycas-4, ycas-5, ycas-6, jcas-2, jcas-3, jcas-4, and jcas-11, potentially leading to altered protein functions (Figure 1B).
To investigate the impact of these allelic variations on yield, several agronomic traits were measured (Table 1). For instance, the average plant height of the mutants ranged from 102.7 cm to 111.7 cm (Figure 2A,D), showing a noticeable increase compared with the WT. Furthermore, the grain number per panicle in all new ehd1 alleles demonstrated varying degrees of increase relative to the WT (Figure 2C,F). The number of tillers per plant in the mutant lines also saw a significant increase compared with the WT. Notably, the heading date in ehd1 mutants was delayed by about 30 days (Figure 2B,E). In yield tests, the average yield of ycas-1 and jcas-2 across thirty plants each surpassed that of the WT (Yinongxiang 12 and Jiyuan xiang 1) (Table 1). The next phase involves applying these new ehd1 alleles in breeding and fertilizer testing to maximize yield potential.

3.3. Temperature Sensitivity of Modified ehd1 Variants

To investigate the effects of ehd1 mutations on photoperiod and temperature responses, experiments with ycas-1 and jcas-2 mutants were conducted. The results show that variations in photoperiods and temperatures impacted the mutants differently from the WT (Figure 3 and Figure 4A,B). Both ycas-1 and jcas-2, along with the WT, demonstrated temperature sensitivity; notably, ycas-1 and jcas-2 exhibited extended basic vegetative growth periods at 23 °C compared with 38 °C. Similarly, under photoperiod treatments, these mutants showed marginally longer basic vegetative growth periods under 11 h light conditions than under 14 h light conditions (Figure 3 and Figure 4A,B).
Additionally, the mRNA expression levels of Hd3a and RFT1 were monitored in ycas-1 and jcas-2 under various photoperiod and temperature conditions. Initially, the expression levels of these genes in the mutants were akin to those in the WT. However, a significant increase was observed after 3 to 6 days of treatment (Figure 4C–F). This pattern suggests a negative correlation between the heading date and the expression levels of Hd3a and RFT1. This finding supports the hypothesis that the transcriptional activation of these genes largely depends on the presence of functional Ehd1. The observed photoperiod and temperature responses indicate that a loss of Ehd1 function leads to the inactivation of Hd3a and RFT1 expression, thereby resulting in a phenotype characterized by delayed flowering.

3.4. High Grain Yield and Quality of ehd1 Mutants in Low-Latitude Regions

The superior grain quality of japonica rice has significantly boosted its popularity in China. However, extended periods of basic vegetative growth can negatively impact both grain yield and quality. This study evaluated the grain quality of the ycas-1 and jcas-2 variants by analyzing several grain quality characteristics, such as chalkiness degree, chalky rice rate, amylose content, gel consistency, and alkali spreading value. These characteristics were compared across Ji Yuan Xiang 1, Yi Nong Xiang 12, ycas-1, and jcas-2 (Table 2). The results indicate that ycas-1 and jcas-2, cultivated in Hangzhou, showed a lower chalky rice rate and chalkiness degree than Ji Yuan Xiang 1 and Yi Nong Xiang 12, with no significant differences in other traits (t-test, p > 0.1). The reduced chalky rice rate and chalkiness degree in the ehd1 mutant lines, ycas-1 and jcas-2, might be attributed to the lower temperatures experienced during their grain-filling stage. Notably, the ycas-1 and jcas-2 lines demonstrated commendable grain quality when cultivated in Hangzhou.

4. Discussion

4.1. Advancements in Genome Editing for Rice Breeding

This study highlights the pivotal role of genome editing in rice gene research, breeding, and domestication. The CRISPR/Cas9 system, consisting of Cas9 protein and a single-stranded guide RNA (sgRNA), is now foundational in this field [11,27]. This technique, including methods like Prime genome editing and CRISPR/Cas9-based base editing, has seen successful application across diverse crops, like rice, sorghum, wheat, tomato, and maize [11,28,29,30,31,32,33]. Rice, with its small genome size, high transformation efficiency, extensive quality reference sequences, and varied genomic haplotypes, serves as an ideal model for genetic studies and breeding [8]. Numerous genes have been targeted for improvement in rice by using CRISPR/Cas9, including those associated with disease resistance, grain quality, and yield [11,31,34].

4.2. Tailoring Northeastern Japonica Rice for Low-Latitude Cultivation

Photoperiodic gene adaptation in rice is crucial for its suitability across different latitudes and directly impacts grain yield [9]. Single-nucleotide polymorphisms (SNPs) in these genes vary among varieties at different latitudes [35]. Studies have focused on latitude adaptation in rice through enhanced expression or mutations in flowering time genes [27]. For instance, the allele of Heading date 1 (Hd1) in indica varieties has been backcrossed into a Japonica variety, facilitating the integration of indica traits into Japonica rice in southern China. Mutations in the Ehd1 gene, particularly in its third exon, have shown promising results in delaying the heading date and enhancing suitability for low-latitude growth [3,27].
The adaptation of photoperiodic genes is crucial for the suitability of rice cultivation across different latitudes, which directly impacts grain yield. In our study, we focused on the adaptation of rice to low latitudes through modifications in the Ehd1 gene, which is instrumental in delaying flowering time. These genetic modifications are particularly important for northeastern Japonica rice varieties, which, despite their superior grain quality, face challenges in breeding due to their sensitivity to light and temperature.
The transformation of Jiyuanxiang 1 and Yinongxiang 12, varieties known for their high-quality grain, through CRISPR-Cas9-mediated editing demonstrates the potential to overcome these environmental sensitivities. By introducing mutations in the Ehd1 gene, we delayed the flowering period to a time that avoids the peak temperatures of August, which typically range from an average low of 27 °C to a high of 35 °C. Instead, the edited varieties now flower in late August, with grain filling occurring in September, under milder temperature conditions of 22 °C to 29 °C. This strategic delay in the flowering time circumvents the high-temperature stress during the crucial grain-filling period, markedly improving grain quality. This evidence showcases the power of genome editing in mitigating adverse temperature effects on crop yield and quality and underscores the importance of precise genetic modifications for enhancing crop resilience and productivity in response to climate variability.
Furthermore, the observed differences in gene-editing efficiency between gRNA1 and gRNA2 could be attributed to variations in target site accessibility, sgRNA design, or genomic context, which may influence the CRISPR/Cas9 system’s ability to induce precise edits. Understanding these nuances can guide improvements in sgRNA design and editing strategies, enhancing the precision and efficiency of genome editing applications in rice and other crops.
In summary, the modification of the EHD1 gene in northeastern japonica rice varieties has proven effective for producing high-quality Japonica rice adapted to low latitudes. With the flowering times of the ycas-1 and jcas-2 variants closely aligning with local main varieties in Hangzhou, future efforts will focus on the broader application of these genetically edited varieties in rice breeding programs for low-latitude regions, thereby meeting the demands for high-quality rice production. This approach could serve as a blueprint for similar advancements in other crop varieties, highlighting the transformative impact of precision breeding technologies in modern agriculture.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/cimb46040233/s1, Figure S1: Frequency distribution of heading date of the elite northeastern plain japonica varieties and two control japonica varieties. Analysis performed using GraphPad Prism software (GraphPad Software, San Diego, CA, USA); Figure S2: Identification of hygromycin in different edited plants, Hygromycin detection performed using ELISA Kit (Sigma-Aldrich, St. Louis, MO, USA); Table S1: The heading date of elite northeastern plain japonica varieties in the Yangtze River region; Table S2: The number of plants detected in the two Yi Nong Xiang 12 PAM sites and Ji Yuan Xiang 1 PAM sites; Table S3: Primer sequences used in this study, Primers synthesized by Integrated DNA Technologies (IDT, Coralville, IA, USA).

Author Contributions

J.S., Y.C. and J.W. conceived the project and wrote the manuscript. L.T., X.X. and X.P. cloned the CRISPR-Cas9 plasmid, identified mutants, and performed qRT-PCR. H.F. performed phenotype observations. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by National Natural Science Foundation of China, under grant No. 32101791; Zhejiang Provincial Natural Science Foundation, grant number LQ20C130007; and the “14th Five-Year Plan” Major Special Projects for Breeding New Rice Varieties of Zhejiang Province, grant number 2021C02063-1.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The original data of this present study are available from the corresponding authors.

Acknowledgments

The authors thank the National Mid-term Genebank for Rice of China National Rice Research Institute for providing the rice germplasm collection.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Eshed, Y.A.-O.; Lippman, Z.A.-O. Revolutions in agriculture chart a course for targeted breeding of old and new crops. Science 2019, 366, eaax0025. [Google Scholar] [CrossRef] [PubMed]
  2. Huang, X.; Kurata, N.; Wei, X.; Wang, Z.-X.; Wang, A.; Zhao, Q.; Zhao, Y.; Liu, K.; Lu, H.; Li, W. A map of rice genome variation reveals the origin of cultivated rice. Nature 2012, 490, 497–501. [Google Scholar] [CrossRef] [PubMed]
  3. Wu, M.; Liu, H.; Lin, Y.; Chen, J.; Fu, Y.; Luo, J.; Zhang, Z.; Liang, K.; Chen, S.; Wang, F. In-Frame and Frame-Shift Editing of the Ehd1 Gene to Develop Japonica Rice With Prolonged Basic Vegetative Growth Periods. Front. Plant Sci. 2020, 11, 307. [Google Scholar] [CrossRef] [PubMed]
  4. Saito, H.; Yuan, Q.; Okumoto, Y.; Doi, K.; Yoshimura, A.; Inoue, H.; Teraishi, M.; Tsukiyama, T.; Tanisaka, T. Multiple alleles at Early flowering 1 locus making variation in the basic vegetative growth period in rice (Oryza sativa L.). Theor. Appl. Genet. 2009, 119, 315–323. [Google Scholar] [CrossRef] [PubMed]
  5. Wei, X.J.; Jiang, L.; Xu, J.F.; Liu, X.; Liu, S.J.; Zhai, H.Q.; Wan, J.M. The distribution of japonica rice cultivars in the lower region of the Yangtze River valley is determined by its photoperiod-sensitivity and heading date genotypes. J. Integr. Plant Biol. 2009, 51, 922–932. [Google Scholar] [CrossRef] [PubMed]
  6. Yuan, Q.; Saito, H.; Okumoto, Y.; Inoue, H.; Nishida, H.; Tsukiyama, T.; Teraishi, M.; Tanisaka, T. Identification of a novel gene ef7 conferring an extremely long basic vegetative growth phase in rice. Theor. Appl. Genet. 2009, 119, 675–684. [Google Scholar] [CrossRef] [PubMed]
  7. Qiu, L.; Wu, Q.; Wang, X.; Han, J.; Zhuang, G.; Wang, H.; Shang, Z.; Tian, W.; Chen, Z.; Lin, Z. Forecasting rice latitude adaptation through a daylength-sensing-based environment adaptation simulator. Nat. Food 2021, 2, 348–362. [Google Scholar] [CrossRef]
  8. Chen, R.; Deng, Y.; Ding, Y.; Guo, J.; Qiu, J.; Wang, B.; Wang, C.; Xie, Y.; Zhang, Z.; Chen, J.; et al. Rice functional genomics: Decades’ efforts and roads ahead. Sci. China Life Sci. 2022, 65, 33–92. [Google Scholar] [CrossRef] [PubMed]
  9. Zong, W.; Ren, D.; Huang, M.; Sun, K.; Feng, J.; Zhao, J.; Xiao, D.; Xie, W.; Liu, S.; Zhang, H. Strong photoperiod sensitivity is controlled by cooperation and competition among Hd1, Ghd7 and DTH8 in rice heading. New Phytol. 2021, 229, 1635–1649. [Google Scholar] [CrossRef] [PubMed]
  10. Rothan, C.; Diouf, I.; Causse, M. Trait discovery and editing in tomato. Plant J. 2019, 97, 73–90. [Google Scholar] [CrossRef]
  11. Cui, Y.; Hu, X.; Liang, G.; Feng, A.; Wang, F.; Ruan, S.; Dong, G.; Shen, L.; Zhang, B.; Chen, D. Production of novel beneficial alleles of a rice yield-related QTL by CRISPR/Cas9. Plant Biotechnol. J. 2020, 18, 1987. [Google Scholar] [CrossRef]
  12. Cui, Y.; Zhu, M.; Song, J.; Fan, H.; Xu, X.; Wu, J.; Guo, L.; Wang, J. Expression dynamics of phytochrome genes for the shade-avoidance response in densely direct-seeding rice. Front. Plant Sci. 2022, 13, 1105882. [Google Scholar] [CrossRef] [PubMed]
  13. Cho, L.-H.; Yoon, J.; Pasriga, R.; An, G. Homodimerization of Ehd1 is required to induce flowering in rice. Plant Physiol. 2016, 170, 2159–2171. [Google Scholar] [CrossRef] [PubMed]
  14. Zhao, J.; Chen, H.; Ren, D.; Tang, H.; Qiu, R.; Feng, J.; Long, Y.; Niu, B.; Chen, D.; Zhong, T. Genetic interactions between diverged alleles of Early heading date 1 (Ehd1) and Heading date 3a (Hd3a)/RICE FLOWERING LOCUS T1 (RFT 1) control differential heading and contribute to regional adaptation in rice (Oryza sativa). New Phytol. 2015, 208, 936–948. [Google Scholar] [CrossRef] [PubMed]
  15. Kim, S.L.; Lee, S.; Kim, H.J.; Nam, H.G.; An, G. OsMADS51 is a short-day flowering promoter that functions upstream of Ehd1, OsMADS14, and Hd3a. Plant Physiol. 2007, 145, 1484–1494. [Google Scholar] [CrossRef] [PubMed]
  16. Andrés, F.; Galbraith, D.W.; Talón, M.; Domingo, C. Analysis of PHOTOPERIOD SENSITIVITY5 sheds light on the role of phytochromes in photoperiodic flowering in rice. Plant Physiol. 2009, 151, 681–690. [Google Scholar] [CrossRef] [PubMed]
  17. Yano, M.; Katayose, Y.; Ashikari, M.; Yamanouchi, U.; Monna, L.; Fuse, T.; Baba, T.; Yamamoto, K.; Umehara, Y.; Nagamura, Y.; et al. Hd1, a Major Photoperiod Sensitivity Quantitative Trait Locus in Rice, Is Closely Related to the Arabidopsis Flowering Time Gene CONSTANS. Plant Cell 2000, 12, 2473–2483. [Google Scholar] [CrossRef] [PubMed]
  18. Xue, W.; Xing, Y.; Weng, X.; Zhao, Y.; Tang, W.; Wang, L.; Zhou, H.; Yu, S.; Xu, C.; Li, X. Natural variation in Ghd7 is an important regulator of heading date and yield potential in rice. Nat. Genet. 2008, 40, 761–767. [Google Scholar] [CrossRef] [PubMed]
  19. Lee, Y.S.; Jeong, D.H.; Lee, D.Y.; Yi, J.; Ryu, C.H.; Kim, S.L.; Jeong, H.J.; Choi, S.C.; Jin, P.; Yang, J. OsCOL4 is a constitutive flowering repressor upstream of Ehd1 and downstream of OsphyB. Plant J. 2010, 63, 18–30. [Google Scholar] [CrossRef] [PubMed]
  20. Wei, X.; Xu, J.; Guo, H.; Jiang, L.; Chen, S.; Yu, C.; Zhou, Z.; Hu, P.; Zhai, H.; Wan, J. DTH8 suppresses flowering in rice, influencing plant height and yield potential simultaneously. Plant Physiol. 2010, 153, 1747–1758. [Google Scholar] [CrossRef] [PubMed]
  21. Zhang, Z.; Hu, W.; Shen, G.; Liu, H.; Hu, Y.; Zhou, X.; Liu, T.; Xing, Y. Alternative functions of Hd1 in repressing or promoting heading are determined by Ghd7 status under long-day conditions. Sci. Rep. 2017, 7, 5388. [Google Scholar] [CrossRef] [PubMed]
  22. Lee, Y.S.; Lee, D.Y.; Cho, L.H.; An, G. Rice miR172 induces flowering by suppressing OsIDS1 and SNB, two AP2 genes that negatively regulate expression of Ehd1 and florigens. Rice 2014, 7, 31. [Google Scholar] [CrossRef] [PubMed]
  23. Shen, L.; Hua, Y.; Fu, Y.; Li, J.; Liu, Q.; Jiao, X.; Xin, G.; Wang, J.; Wang, X.; Yan, C.; et al. Erratum to: Rapid generation of genetic diversity by multiplex CRISPR/Cas9 genome editing in rice. Sci. China Life Sci. 2019, 62, 1270. [Google Scholar] [CrossRef] [PubMed]
  24. Hiei, Y.; Komari, T.; Kubo, T. Transformation of rice mediated by Agrobacterium tumefaciens. Plant Mol. Biol. 1997, 35, 205–218. [Google Scholar] [CrossRef] [PubMed]
  25. Liu, W.; Xie, X.; Ma, X.; Li, J.; Chen, J.; Liu, Y.G. DSDecode: A Web-Based Tool for Decoding of Sequencing Chromatograms for Genotyping of Targeted Mutations. Mol. Plant 2015, 8, 1431–1433. [Google Scholar] [CrossRef] [PubMed]
  26. Ma, X.; Chen, L.; Zhu, Q.; Chen, Y.; Liu, Y.G. Rapid Decoding of Sequence-Specific Nuclease-Induced Heterozygous and Biallelic Mutations by Direct Sequencing of PCR Products. Mol. Plant 2015, 8, 1285–1287. [Google Scholar] [CrossRef] [PubMed]
  27. Cui, Y.; Zhu, M.; Xu, Z.; Xu, Q. Assessment of the effect of ten heading time genes on reproductive transition and yield components in rice using a CRISPR/Cas9 system. Theor. Appl. Genet. 2019, 132, 1887–1896. [Google Scholar] [CrossRef] [PubMed]
  28. Anzalone, A.V.; Koblan, L.W.; Liu, D.A.-O. Genome editing with CRISPR-Cas nucleases, base editors, transposases and prime editors. Nat. Biotechnol. 2020, 38, 824–844. [Google Scholar] [CrossRef] [PubMed]
  29. Son, S.; Park, S.R. Challenges Facing CRISPR/Cas9-Based Genome Editing in Plants. Front. Plant Sci. 2022, 13, 902413. [Google Scholar] [CrossRef] [PubMed]
  30. Tomlinson, L.; Yang, Y.; Emenecker, R.; Smoker, M.; Taylor, J.; Perkins, S.; Smith, J.; MacLean, D.; Olszewski, N.E.; Jones, J.D. Using CRISPR/Cas9 genome editing in tomato to create a gibberellin-responsive dominant dwarf DELLA allele. Plant Biotechnol. J. 2019, 17, 132–140. [Google Scholar] [CrossRef] [PubMed]
  31. Macovei, A.; Sevilla, N.R.; Cantos, C.; Jonson, G.B.; Slamet-Loedin, I.; Cermak, T.; Voytas, D.F.; Choi, I.R.; Chadha-Mohanty, P. Novel alleles of rice eIF4G generated by CRISPR/Cas9-targeted mutagenesis confer resistance to Rice tungro spherical virus. Plant Biotechnol. J. 2018, 16, 1918–1927. [Google Scholar] [CrossRef] [PubMed]
  32. Li, A.; Jia, S.; Yobi, A.; Ge, Z.; Sato, S.J.; Zhang, C.; Angelovici, R.; Clemente, T.E.; Holding, D.R. Editing of an alpha-kafirin gene family increases, digestibility and protein quality in sorghum. Plant Physiol. 2018, 177, 1425–1438. [Google Scholar] [CrossRef]
  33. Liu, X.; Wu, S.; Xu, J.; Sui, C.; Wei, J. Application of CRISPR/Cas9 in plant biology. Acta Pharm. Sin. B 2017, 7, 292–302. [Google Scholar] [CrossRef]
  34. Zhang, J.; Zhang, H.; Botella, J.R.; Zhu, J.K. Generation of new glutinous rice by CRISPR/Cas9-targeted mutagenesis of the Waxy gene in elite rice varieties. J. Integr. Plant Biol. 2018, 60, 369. [Google Scholar] [CrossRef] [PubMed]
  35. Leng, Y.; Gao, Y.; Chen, L.; Yang, Y.; Huang, L.; Dai, L.; Ren, D.; Xu, Q.; Zhang, Y.; Ponce, K. Using Heading date 1 preponderant alleles from indica cultivars to breed high-yield, high-quality japonica rice varieties for cultivation in south China. Plant Biotechnol. J. 2020, 18, 119–128. [Google Scholar] [CrossRef] [PubMed]
Cimb 46 00233 g001
Figure 1. Illustration of ehd1 mutant alleles in Jiyuanxiang 1 and Yinongxiang 12 varieties. (A) Targeted EHD1 locus for CRISPR-Cas9 editing; (B) alignment of mutational sequences in the newly created ehd1 alleles within the backgrounds of Jiyuanxiang 1 and Yinongxiang 12, compared with the wild type (WT) sequence. Protospacer Adjacent Motifs (PAMs) are marked in blue for clarity.
Figure 1. Illustration of ehd1 mutant alleles in Jiyuanxiang 1 and Yinongxiang 12 varieties. (A) Targeted EHD1 locus for CRISPR-Cas9 editing; (B) alignment of mutational sequences in the newly created ehd1 alleles within the backgrounds of Jiyuanxiang 1 and Yinongxiang 12, compared with the wild type (WT) sequence. Protospacer Adjacent Motifs (PAMs) are marked in blue for clarity.
Cimb 46 00233 g001
Cimb 46 00233 g002
Figure 2. Characteristics of ehd1 mutants derived from CRISPR-Cas9 editing with Jiyuanxiang 1 and Yinongxiang 12. (A) Physical characteristics of various ehd1 mutants in the Yinongxiang 12 background, developed through gene editing. Scale bar represents 20 cm. (B) Extended basic vegetative growth periods observed in ycas9-1, ycas9-4, and ycas9-5. (C) Comparative analysis of panicle length between the wild type (Jiyuanxiang 1) and jcas9-2, jcas9-3, and jcas9-4. (D) Physical characteristics of different ehd1 mutants with the Jiyuanxiang 1 background, developed through gene editing. Scale bar represents 20 cm. (E) Prolonged basic vegetative growth periods seen in jcas9-2, jcas9-3, and jcas9-4. (F) Panicle length comparison between the wild type (Jiyuanxiang 1) and jcas9-2, jcas9-3, and jcas9-4. Error bars represent means ± SDs (n = 3). Statistical analysis of agronomic trait variations was performed by using Duncan’s multiple range test (p < 0.05). The letters ‘a’ and ‘b’ indicate a highly significant difference.
Figure 2. Characteristics of ehd1 mutants derived from CRISPR-Cas9 editing with Jiyuanxiang 1 and Yinongxiang 12. (A) Physical characteristics of various ehd1 mutants in the Yinongxiang 12 background, developed through gene editing. Scale bar represents 20 cm. (B) Extended basic vegetative growth periods observed in ycas9-1, ycas9-4, and ycas9-5. (C) Comparative analysis of panicle length between the wild type (Jiyuanxiang 1) and jcas9-2, jcas9-3, and jcas9-4. (D) Physical characteristics of different ehd1 mutants with the Jiyuanxiang 1 background, developed through gene editing. Scale bar represents 20 cm. (E) Prolonged basic vegetative growth periods seen in jcas9-2, jcas9-3, and jcas9-4. (F) Panicle length comparison between the wild type (Jiyuanxiang 1) and jcas9-2, jcas9-3, and jcas9-4. Error bars represent means ± SDs (n = 3). Statistical analysis of agronomic trait variations was performed by using Duncan’s multiple range test (p < 0.05). The letters ‘a’ and ‘b’ indicate a highly significant difference.
Cimb 46 00233 g002
Cimb 46 00233 g003
Figure 3. Temperature sensitivity in ehd1 mutants of Jiyuanxiang 1 and Yinongxiang 12. (A) Trait of Yi nongxiang under 38 °C, 14 h treatment. (B) Trait of ycas-1 under 38 °C, 14 h treatment. (C) Trait of Ji yuanxiang under 38 °C, 14 h treatment. (D) Trait of jcas-2 under 38 °C, 14 h treatment. (E) Trait of Yi nongxiang under 38 °C, 11 h treatment. (F) Trait of ycas-1 under 38 °C, 11 h treatment. (G) Trait of Ji yuanxiang under 38 °C, 11 h treatment. (H) Trait of jcas-2 under 38 °C, 11 h treatment. (I) Trait of Yi nongxiang under 23 °C, 14 h treatment. (J) Trait of ycas-1 under 23 °C, 14 h treatment. (K) Trait of Ji yuanxiang under 23 °C, 14 h treatment. (L) Trait of jcas-2 under 23 °C, 14 h treatment. (M) Trait of Yi nongxiang under 23 °C, 11 h treatment. (N) Trait of ycas-1 under 23 °C, 11 h treatment. (O) Trait of Ji yuanxiang under 23 °C, 11 h treatment. (P) Trait of jcas-2 under 23 °C, 11 h treatment. Bar = 20 cm.
Figure 3. Temperature sensitivity in ehd1 mutants of Jiyuanxiang 1 and Yinongxiang 12. (A) Trait of Yi nongxiang under 38 °C, 14 h treatment. (B) Trait of ycas-1 under 38 °C, 14 h treatment. (C) Trait of Ji yuanxiang under 38 °C, 14 h treatment. (D) Trait of jcas-2 under 38 °C, 14 h treatment. (E) Trait of Yi nongxiang under 38 °C, 11 h treatment. (F) Trait of ycas-1 under 38 °C, 11 h treatment. (G) Trait of Ji yuanxiang under 38 °C, 11 h treatment. (H) Trait of jcas-2 under 38 °C, 11 h treatment. (I) Trait of Yi nongxiang under 23 °C, 14 h treatment. (J) Trait of ycas-1 under 23 °C, 14 h treatment. (K) Trait of Ji yuanxiang under 23 °C, 14 h treatment. (L) Trait of jcas-2 under 23 °C, 14 h treatment. (M) Trait of Yi nongxiang under 23 °C, 11 h treatment. (N) Trait of ycas-1 under 23 °C, 11 h treatment. (O) Trait of Ji yuanxiang under 23 °C, 11 h treatment. (P) Trait of jcas-2 under 23 °C, 11 h treatment. Bar = 20 cm.
Cimb 46 00233 g003
Cimb 46 00233 g004
Figure 4. Heading dates and expression patterns of Hd3a and RFT1 in the WT. Analysis of WT and mutant lines under different temperature and photoperiod conditions: artificial high temperature and long day (AHTLD), artificial high temperature and short day (AHTSD), artificial low temperature and long day (ALTLD), and artificial low temperature and short day (ALTSD). The study involved fifty-eight-day-old plants. (A,B) Heading day comparisons between Jiyuanxiang and jcas9-2, and Yinongxiang and ycas9-1, under varied light and temperature treatments (AHTLD, AHTSD, ALTLD, and ALTSD); (C–F) Expression patterns of Hd3a and RFT1 in the presence and absence of Ehd1 (Jiyuanxiang vs. jcas9-2; Yinongxiang vs. ycas9-1). Error bars represent means ± SDs (n = 3). Statistical analysis of agronomic trait variations was performed by using Duncan’s multiple range test (p < 0.05). The letters ‘a’, ‘b’, and ‘c’ indicate a highly significant difference.
Figure 4. Heading dates and expression patterns of Hd3a and RFT1 in the WT. Analysis of WT and mutant lines under different temperature and photoperiod conditions: artificial high temperature and long day (AHTLD), artificial high temperature and short day (AHTSD), artificial low temperature and long day (ALTLD), and artificial low temperature and short day (ALTSD). The study involved fifty-eight-day-old plants. (A,B) Heading day comparisons between Jiyuanxiang and jcas9-2, and Yinongxiang and ycas9-1, under varied light and temperature treatments (AHTLD, AHTSD, ALTLD, and ALTSD); (C–F) Expression patterns of Hd3a and RFT1 in the presence and absence of Ehd1 (Jiyuanxiang vs. jcas9-2; Yinongxiang vs. ycas9-1). Error bars represent means ± SDs (n = 3). Statistical analysis of agronomic trait variations was performed by using Duncan’s multiple range test (p < 0.05). The letters ‘a’, ‘b’, and ‘c’ indicate a highly significant difference.
Cimb 46 00233 g004
Table 1. Major agronomic traits of the ehd1 mutant lines.
Table 1. Major agronomic traits of the ehd1 mutant lines.
Rice LinePH (cm)PNPPPL (cm)PBSB SPPSSR (%)
Yinongxiang 1278.3 ± 2.1 a7.3 ± 0.5 a16.7 ± 0.3 a5 ± 1.7 a20.7 ± 1.5 a76.3 ± 1.5 a88.6 ± 1.9
ycas-1102.7 ± 1.5 b17.3 ± 0.6 b23.2 ± 1.0 b11.3 ± 0.6 b40.3 ± 2.1 b146.3 ± 10.2 b88.3 ± 6.7
ycas-4102.3 ± 1.2 b19.3 ± 1.5 b23.8 ± 0.3 b12 ± 1 b42.6 ± 4.0 b148.7 ± 9.8 b91.6 ± 3.2
ycas-5103.7 ± 1.5 b16.3 ± 1.5 b23.7 ± 0.3 b12 ± 1.7 b44.3 ± 3.1 b145.3 ± 6.0 b87.5 ± 2.1
Jiyuanxiang 183.3 ± 1.2 a10.3 ± 1.5 a17.6 ± 0.3 a10.0 ± 1.7 a9.7 ± 1.2 a99.3 ± 1.5 a83.9 ± 3.5
jcas-2109.3 ± 0.6 b18.7 ± 3.1 b27 ± 0.1 b14.3 ± 1.5 b25.3 ± 2.5 b227.7 ± 14.3 b92.0 ± 1.6
jcas-3110.7 ± 1.5 b16.7 ± 1.5 b27.1 ± 0.3 b14.0 ± 2.6 b26.3 ± 1.2 b229.3 ± 2.5 b89.7 ± 1.7
jcas-4111.7 ± 2.1 b19.3 ± 1.5 b26.6 ± 0.4 b14.6 ± 2.1 b22.6 ± 2.9 b223.3 ± 5.9 b91.2 ± 1.1
Note: The table presents average values for plant height (PH), panicle number per plant (PNPP), panicle length (PL), primary branches (PB), secondary branches (SB), spikelets per panicle (SPP), and seed-setting rate (SSR) with standard deviations (±SDs; n = 10). Statistical analysis of agronomic trait variations was performed by using Duncan’s multiple range test (p < 0.05). The letters ‘a’ and ‘b’ indicate a highly significant difference between the two.
Table 2. Comparative analysis of rice quality characteristics in ehd1 mutant lines.
Table 2. Comparative analysis of rice quality characteristics in ehd1 mutant lines.
Brown Rice Rate (%)Milled Rice Rate (%)Head Rice Rate (%)Grain Length (mm)Chalkiness Grain Rate (%)Chalkiness (%)Amylose (%)Gel Consistency (mm)Alkali Spreading Value
Yi nongxiang81.41 ± 0.4772.78 ± 0.7269.85 ± 1.415.97 ± 0.0552.67 ± 3.51 **12.07 ± 1.66 **17.46 ± 0.24 **55.67 ± 5.136.60 ± 1.10
ycas9-182.99 ± 0.27972.59 ± 0.2967.51 ± 0.756.21 ± 0.0144.00 ± 2.657.70 ± 0.2515.51 ± 0.4458.00 ± 3.606.50 ± 0.00
Ji yuanxiang82.08 ± 0.4474.38 ± 0.6273.77 ± 0.784.63 ± 0.0262.33 ± 7.64 **20.03 ± 2.60 **14.57 ± 0.3162.67 ± 0.586.50 ± 0.00
jcas9-283.46 ± 0.3174.40 ± 0.4173.36 ± 0.434.67 ± 0.0232.67 ± 1.533.70 ± 0.4414.65 ± 0.1662.67 ± 3.066.70 ± 0.17
Data represent the means ± SDs of three biological replicates (Student’s t-test: ** p < 0.01).
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

Song, J.; Tang, L.; Fan, H.; Xu, X.; Peng, X.; Cui, Y.; Wang, J. Enhancing Yield and Improving Grain Quality in Japonica Rice: Targeted EHD1 Editing via CRISPR-Cas9 in Low-Latitude Adaptation. Curr. Issues Mol. Biol. 2024, 46, 3741-3751. https://doi.org/10.3390/cimb46040233

AMA Style

Song J, Tang L, Fan H, Xu X, Peng X, Cui Y, Wang J. Enhancing Yield and Improving Grain Quality in Japonica Rice: Targeted EHD1 Editing via CRISPR-Cas9 in Low-Latitude Adaptation. Current Issues in Molecular Biology. 2024; 46(4):3741-3751. https://doi.org/10.3390/cimb46040233

Chicago/Turabian Style

Song, Jian, Liqun Tang, Honghuan Fan, Xiaozheng Xu, Xinlu Peng, Yongtao Cui, and Jianjun Wang. 2024. "Enhancing Yield and Improving Grain Quality in Japonica Rice: Targeted EHD1 Editing via CRISPR-Cas9 in Low-Latitude Adaptation" Current Issues in Molecular Biology 46, no. 4: 3741-3751. https://doi.org/10.3390/cimb46040233

APA Style

Song, J., Tang, L., Fan, H., Xu, X., Peng, X., Cui, Y., & Wang, J. (2024). Enhancing Yield and Improving Grain Quality in Japonica Rice: Targeted EHD1 Editing via CRISPR-Cas9 in Low-Latitude Adaptation. Current Issues in Molecular Biology, 46(4), 3741-3751. https://doi.org/10.3390/cimb46040233

Article Metrics

Back to TopTop