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Quantitative Genetics and Genomics to Accelerate Plant Breeding Research
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Quantitative Genetics and Genomics to Accelerate Plant Breeding Research

A special issue of Genes (ISSN 2073-4425). This special issue belongs to the section "Plant Genetics and Genomics".

Deadline for manuscript submissions: closed (31 March 2021) | Viewed by 22389

Special Issue Editor

Dr. Sandip Kale

E-Mail Website
Guest Editor
Leibniz Inst Plant Genet & Crop Plant Res IPK, Corrensstr 3, D-06466 Gatersleben, Germany
Interests: plant; breeding; QTL; genetic; genomics

Special Issue Information

Dear Colleagues,

Development of high-yielding, stress-tolerant varieties is needed today to meet the food demand of a burgeoning human population. This can be achieved by understanding the genetic nature of traits, screening the germplasm and utilizing traditional/sophisticated plant breeding techniques to transfer the trait in an elite background.

Since their discovery, molecular markers have been used at various stages viz. to understand genetic diversity; quantitative trait locus (QTL) mapping; marker assisted selection (MAS); genomic selection; etc. in crop improvement programs. Further, advancements in sequencing technology have made it possible to effectively develop several thousand markers within a limited time. As a result, the quantitative genetics principles can now be effectively utilized in current crop improvement programs. 

This Special Issue calls for original articles, reviews, and perspectives that utilize Genetics and Genomics approaches for genetic dissection of agronomically important traits and their utilization in crop improvement programs.

Dr. Sandip Kale
Guest Editor

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Molecular markers
  • Next-generation sequencing (NGS)
  • Diversity study
  • Quantitative trait locus (QTL) mapping
  • Fine mapping
  • Marker-assisted selection
  • Genome-wide association study
  • Genomic selection

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Published Papers (6 papers)

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Research

11 pages, 1242 KiB  
Article
Improvement of a Yairipok Chujak Maize Landrace from North Eastern Himalayan Region for β-Carotene Content through Molecular Marker-Assisted Backcross Breeding
by Maqbool Qutub, Sarankumar Chandran, Krishnakumar Rathinavel, Vellaikumar Sampathrajan, Ravikesavan Rajasekaran, Sudha Manickam, Karthikeyan Adhimoolam, Samuel Jeberson Muniyandi and Senthil Natesan
Genes 2021, 12(5), 762; https://doi.org/10.3390/genes12050762 - 18 May 2021
Cited by 8 | Viewed by 2774
Abstract
In the North Eastern Himalayan region (NEHR) of India, maize is an important food crop. The local people cultivate the maize landraces and consume them as food. However, these landraces are deficient in β-carotene content. Thus, we aimed to incorporate the crtRB1 gene [...] Read more.
In the North Eastern Himalayan region (NEHR) of India, maize is an important food crop. The local people cultivate the maize landraces and consume them as food. However, these landraces are deficient in β-carotene content. Thus, we aimed to incorporate the crtRB1 gene from UMI285β+ into the genetic background of the NEHR maize landrace, Yairipok Chujak (CAUM66), and thereby enhance the β-carotene content through marker-assisted backcrossing (MABC). In this regard, we backcrossed and screened BC1F1 and BC2F1 plants possessing the heterozygous allele for crtRB1 and then screened with 106 polymorphic simple sequence repeat (SSR) markers. The plants having maximum recurrent parent genome recovery (RPGR) were selected in each generation and selfed to produce BC2F2 seeds. In the BC2F2 generation, four plants (CAUM66-54-9-12-2, CAUM66-54-9-12-11, CAUM66-54-9-12-13, and CAUM66-54-9-12-24) having homozygous crtRB1-favorable allele with maximum RPGR (86.74–90.16%) were selected and advanced to BC2F3. The four selected plants were selfed to produce BC2F3 and then evaluated for agronomic traits and β-carotene content. The agronomic performance of the four lines was similar (78.83–99.44%) to that of the recurrent parent, and β-carotene content (7.541–8.711 μg/g) was on par with the donor parent. Our study is the first to improve the β-carotene content in NEHR maize landrace through MABC. The newly developed lines could serve as potential resources to further develop nutrition-rich maize lines and could provide genetic stock for use in breeding programs. Full article
(This article belongs to the Special Issue Quantitative Genetics and Genomics to Accelerate Plant Breeding Research)
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13 pages, 1975 KiB  
Article
Genome-Wide Association Studies and Prediction of Tan Spot (Pyrenophora tritici-repentis) Infection in European Winter Wheat via Different Marker Platforms
by Quddoos H. Muqaddasi, Roop Kamal, Vilson Mirdita, Bernd Rodemann, Martin W. Ganal, Jochen C. Reif and Marion S. Röder
Genes 2021, 12(4), 490; https://doi.org/10.3390/genes12040490 - 27 Mar 2021
Cited by 15 | Viewed by 2646
Abstract
Tan spot, caused by the fungus Pyrenophoratritici-repentis (Ptr), is a severe foliar disease of wheat (Triticumaestivum L.). Improving genetic resistance is a durable strategy to reduce Ptr-related losses. Here, we dissected Ptr-infection’s genetic basis in 372 [...] Read more.
Tan spot, caused by the fungus Pyrenophoratritici-repentis (Ptr), is a severe foliar disease of wheat (Triticumaestivum L.). Improving genetic resistance is a durable strategy to reduce Ptr-related losses. Here, we dissected Ptr-infection’s genetic basis in 372 European wheat varieties via simple sequence repeats (SSRs) plus 35k and 90k single nucleotide polymorphism (SNP) marker platforms. In our phenotypic data analyses, Ptr infection showed a significant genotypic variance and a significant negative correlation with plant height. Genome-wide association studies revealed a highly quantitative nature of Ptr infection and identified two quantitative trait loci (QTL), viz., QTs.ipk-7A and QTs.ipk-7B, which imparted 21.23 and 5.84% of the genotypic variance, respectively. Besides, the Rht-D1 gene showed a strong allelic influence on the infection scores. Due to the complex genetic nature of the Ptr infection, the potential of genome-wide prediction (GP) was assessed via three different genetic models on individual and combined marker platforms. The GP results indicated that the marker density and marker platforms do not considerably impact prediction accuracy (~40–42%) and that higher-order epistatic interactions may not be highly pervasive. Our results provide a further understanding of Ptr-infection’s genetic nature, serve as a resource for marker-assisted breeding, and highlight the potential of genome-wide selection for improved Ptr resistance. Full article
(This article belongs to the Special Issue Quantitative Genetics and Genomics to Accelerate Plant Breeding Research)
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17 pages, 3899 KiB  
Article
Application of Genomics to Understand Salt Tolerance in Lentil
by Ruwani Dissanayake, Noel O.I. Cogan, Kevin F. Smith and Sukhjiwan Kaur
Genes 2021, 12(3), 332; https://doi.org/10.3390/genes12030332 - 25 Feb 2021
Cited by 18 | Viewed by 3936
Abstract
Soil salinity is a major abiotic stress, limiting lentil productivity worldwide. Understanding the genetic basis of salt tolerance is vital to develop tolerant varieties. A diversity panel consisting of 276 lentil accessions was screened in a previous study through traditional and image-based approaches [...] Read more.
Soil salinity is a major abiotic stress, limiting lentil productivity worldwide. Understanding the genetic basis of salt tolerance is vital to develop tolerant varieties. A diversity panel consisting of 276 lentil accessions was screened in a previous study through traditional and image-based approaches to quantify growth under salt stress. Genotyping was performed using two contrasting methods, targeted (tGBS) and transcriptome (GBS-t) genotyping-by-sequencing, to evaluate the most appropriate methodology. tGBS revealed the highest number of single-base variants (SNPs) (c. 56,349), and markers were more evenly distributed across the genome compared to GBS-t. A genome-wide association study (GWAS) was conducted using a mixed linear model. Significant marker-trait associations were observed on Chromosome 2 as well as Chromosome 4, and a range of candidate genes was identified from the reference genome, the most plausible being potassium transporters, which are known to be involved in salt tolerance in related species. Detailed mineral composition performed on salt-treated and control plant tissues revealed the salt tolerance mechanism in lentil, in which tolerant accessions do not transport Na+ ions around the plant instead localize within the root tissues. The pedigree analysis identified two parental accessions that could have been the key sources of tolerance in this dataset. Full article
(This article belongs to the Special Issue Quantitative Genetics and Genomics to Accelerate Plant Breeding Research)
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14 pages, 4011 KiB  
Article
Merging Genomics and Transcriptomics for Predicting Fusarium Head Blight Resistance in Wheat
by Sebastian Michel, Christian Wagner, Tetyana Nosenko, Barbara Steiner, Mina Samad-Zamini, Maria Buerstmayr, Klaus Mayer and Hermann Buerstmayr
Genes 2021, 12(1), 114; https://doi.org/10.3390/genes12010114 - 19 Jan 2021
Cited by 10 | Viewed by 4579
Abstract
Genomic selection with genome-wide distributed molecular markers has evolved into a well-implemented tool in many breeding programs during the last decade. The resistance against Fusarium head blight (FHB) in wheat is probably one of the most thoroughly studied systems within this framework. Aside [...] Read more.
Genomic selection with genome-wide distributed molecular markers has evolved into a well-implemented tool in many breeding programs during the last decade. The resistance against Fusarium head blight (FHB) in wheat is probably one of the most thoroughly studied systems within this framework. Aside from the genome, other biological strata like the transcriptome have likewise shown some potential in predictive breeding strategies but have not yet been investigated for the FHB-wheat pathosystem. The aims of this study were thus to compare the potential of genomic with transcriptomic prediction, and to assess the merit of blending incomplete transcriptomic with complete genomic data by the single-step method. A substantial advantage of gene expression data over molecular markers has been observed for the prediction of FHB resistance in the studied diversity panel of breeding lines and released cultivars. An increase in prediction ability was likewise found for the single-step predictions, although this can mostly be attributed to an increased accuracy among the RNA-sequenced genotypes. The usage of transcriptomics can thus be seen as a complement to already established predictive breeding pipelines with pedigree and genomic data, particularly when more cost-efficient multiplexing techniques for RNA-sequencing will become more accessible in the future. Full article
(This article belongs to the Special Issue Quantitative Genetics and Genomics to Accelerate Plant Breeding Research)
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22 pages, 1854 KiB  
Article
Improved Genetic Map Identified Major QTLs for Drought Tolerance- and Iron Deficiency Tolerance-Related Traits in Groundnut
by Manish K. Pandey, Sunil S. Gangurde, Vinay Sharma, Santosh K. Pattanashetti, Gopalakrishna K. Naidu, Issa Faye, Falalou Hamidou, Haile Desmae, Ndjido Ardo Kane, Mei Yuan, Vincent Vadez, Shyam N. Nigam and Rajeev K. Varshney
Genes 2021, 12(1), 37; https://doi.org/10.3390/genes12010037 - 30 Dec 2020
Cited by 31 | Viewed by 4064
Abstract
A deep understanding of the genetic control of drought tolerance and iron deficiency tolerance is essential to hasten the process of developing improved varieties with higher tolerance through genomics-assisted breeding. In this context, an improved genetic map with 1205 loci was developed spanning [...] Read more.
A deep understanding of the genetic control of drought tolerance and iron deficiency tolerance is essential to hasten the process of developing improved varieties with higher tolerance through genomics-assisted breeding. In this context, an improved genetic map with 1205 loci was developed spanning 2598.3 cM with an average 2.2 cM distance between loci in the recombinant inbred line (TAG 24 × ICGV 86031) population using high-density 58K single nucleotide polymorphism (SNP) “Axiom_Arachis” array. Quantitative trait locus (QTL) analysis was performed using extensive phenotyping data generated for 20 drought tolerance- and two iron deficiency tolerance-related traits from eight seasons (2004–2015) at two locations in India, one in Niger, and one in Senegal. The genome-wide QTL discovery analysis identified 19 major main-effect QTLs with 10.0–33.9% phenotypic variation explained (PVE) for drought tolerance- and iron deficiency tolerance- related traits. Major main-effect QTLs were detected for haulm weight (20.1% PVE), SCMR (soil plant analytical development (SPAD) chlorophyll meter reading, 22.4% PVE), and visual chlorosis rate (33.9% PVE). Several important candidate genes encoding glycosyl hydrolases; malate dehydrogenases; microtubule-associated proteins; and transcription factors such as MADS-box, basic helix-loop-helix (bHLH), NAM, ATAF, and CUC (NAC), and myeloblastosis (MYB) were identified underlying these QTL regions. The putative function of these genes indicated their possible involvement in plant growth, development of seed and pod, and photosynthesis under drought or iron deficiency conditions in groundnut. These genomic regions and candidate genes, after validation, may be useful to develop molecular markers for deploying genomics-assisted breeding for enhancing groundnut yield under drought stress and iron-deficient soil conditions. Full article
(This article belongs to the Special Issue Quantitative Genetics and Genomics to Accelerate Plant Breeding Research)
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15 pages, 1184 KiB  
Article
Identification of Novel Genomic Associations and Gene Candidates for Grain Starch Content in Sorghum
by Sirjan Sapkota, J. Lucas Boatwright, Kathleen Jordan, Richard Boyles and Stephen Kresovich
Genes 2020, 11(12), 1448; https://doi.org/10.3390/genes11121448 - 2 Dec 2020
Cited by 6 | Viewed by 2627
Abstract
Starch accumulated in the endosperm of cereal grains as reserve energy for germination serves as a staple in human and animal nutrition. Unraveling genetic control for starch metabolism is important for breeding grains with high starch content. In this study, we used a [...] Read more.
Starch accumulated in the endosperm of cereal grains as reserve energy for germination serves as a staple in human and animal nutrition. Unraveling genetic control for starch metabolism is important for breeding grains with high starch content. In this study, we used a sorghum association panel with 389 individuals and 141,557 single nucleotide polymorphisms (SNPs) to fit linear mixed models (LMM) for identifying genomic regions and potential candidate genes associated with starch content. Three associated genomic regions, one in chromosome (chr) 1 and two novel associations in chr-8, were identified using combination of LMM and Bayesian sparse LMM. All significant SNPs were located within protein coding genes, with SNPs ∼ 52 Mb of chr-8 encoding a Casperian strip membrane protein (CASP)-like protein (Sobic.008G111500) and a heat shock protein (HSP) 90 (Sobic.008G111600) that were highly expressed in reproductive tissues including within the embryo and endosperm. The HSP90 is a potential hub gene with gene network of 75 high-confidence first interactors that is enriched for five biochemical pathways including protein processing. The first interactors of HSP90 also showed high transcript abundance in reproductive tissues. The candidates of this study are likely involved in intricate metabolic pathways and represent candidate gene targets for source-sink activities and drought and heat stress tolerance during grain filling. Full article
(This article belongs to the Special Issue Quantitative Genetics and Genomics to Accelerate Plant Breeding Research)
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