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Dwivedi SL, Heslop-Harrison P, Amas J, Ortiz R, Edwards D. Epistasis and pleiotropy-induced variation for plant breeding. PLANT BIOTECHNOLOGY JOURNAL 2024. [PMID: 38875130 DOI: 10.1111/pbi.14405] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/18/2023] [Revised: 05/07/2024] [Accepted: 05/24/2024] [Indexed: 06/16/2024]
Abstract
Epistasis refers to nonallelic interaction between genes that cause bias in estimates of genetic parameters for a phenotype with interactions of two or more genes affecting the same trait. Partitioning of epistatic effects allows true estimation of the genetic parameters affecting phenotypes. Multigenic variation plays a central role in the evolution of complex characteristics, among which pleiotropy, where a single gene affects several phenotypic characters, has a large influence. While pleiotropic interactions provide functional specificity, they increase the challenge of gene discovery and functional analysis. Overcoming pleiotropy-based phenotypic trade-offs offers potential for assisting breeding for complex traits. Modelling higher order nonallelic epistatic interaction, pleiotropy and non-pleiotropy-induced variation, and genotype × environment interaction in genomic selection may provide new paths to increase the productivity and stress tolerance for next generation of crop cultivars. Advances in statistical models, software and algorithm developments, and genomic research have facilitated dissecting the nature and extent of pleiotropy and epistasis. We overview emerging approaches to exploit positive (and avoid negative) epistatic and pleiotropic interactions in a plant breeding context, including developing avenues of artificial intelligence, novel exploitation of large-scale genomics and phenomics data, and involvement of genes with minor effects to analyse epistatic interactions and pleiotropic quantitative trait loci, including missing heritability.
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Affiliation(s)
| | - Pat Heslop-Harrison
- Key Laboratory of Plant Resources Conservation and Sustainable Utilization, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, China
- Department of Genetics and Genome Biology, Institute for Environmental Futures, University of Leicester, Leicester, UK
| | - Junrey Amas
- Centre for Applied Bioinformatics, School of Biological Sciences, University of Western Australia, Perth, WA, Australia
| | - Rodomiro Ortiz
- Department of Plant Breeding, Swedish University of Agricultural Sciences, Alnarp, Sweden
| | - David Edwards
- Centre for Applied Bioinformatics, School of Biological Sciences, University of Western Australia, Perth, WA, Australia
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Kaur N, Lozada DN, Bhatta M, Barchenger DW, Khokhar ES, Nourbakhsh SS, Sanogo S. Insights into the genetic architecture of Phytophthora capsici root rot resistance in chile pepper (Capsicum spp.) from multi-locus genome-wide association study. BMC PLANT BIOLOGY 2024; 24:416. [PMID: 38760676 PMCID: PMC11100198 DOI: 10.1186/s12870-024-05097-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Accepted: 05/02/2024] [Indexed: 05/19/2024]
Abstract
BACKGROUND Phytophthora root rot, a major constraint in chile pepper production worldwide, is caused by the soil-borne oomycete, Phytophthora capsici. This study aimed to detect significant regions in the Capsicum genome linked to Phytophthora root rot resistance using a panel consisting of 157 Capsicum spp. genotypes. Multi-locus genome wide association study (GWAS) was conducted using single nucleotide polymorphism (SNP) markers derived from genotyping-by-sequencing (GBS). Individual plants were separately inoculated with P. capsici isolates, 'PWB-185', 'PWB-186', and '6347', at the 4-8 leaf stage and were scored for disease symptoms up to 14-days post-inoculation. Disease scores were used to calculate disease parameters including disease severity index percentage, percent of resistant plants, area under disease progress curve, and estimated marginal means for each genotype. RESULTS Most of the genotypes displayed root rot symptoms, whereas five accessions were completely resistant to all the isolates and displayed no symptoms of infection. A total of 55,117 SNP markers derived from GBS were used to perform multi-locus GWAS which identified 330 significant SNP markers associated with disease resistance. Of these, 56 SNP markers distributed across all the 12 chromosomes were common across the isolates, indicating association with more durable resistance. Candidate genes including nucleotide-binding site leucine-rich repeat (NBS-LRR), systemic acquired resistance (SAR8.2), and receptor-like kinase (RLKs), were identified within 0.5 Mb of the associated markers. CONCLUSIONS Results will be used to improve resistance to Phytophthora root rot in chile pepper by the development of Kompetitive allele-specific markers (KASP®) for marker validation, genomewide selection, and marker-assisted breeding.
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Affiliation(s)
- Navdeep Kaur
- Department of Plant and Environmental Sciences, New Mexico State University, Las Cruces, NM, 88003, USA
- Current address: Department of Horticultural Sciences, Texas A&M University, College Station, TX, 77843, USA
| | - Dennis N Lozada
- Department of Plant and Environmental Sciences, New Mexico State University, Las Cruces, NM, 88003, USA.
- Chile Pepper Institute, New Mexico State University, Las Cruces, NM, 88003, USA.
| | | | | | - Ehtisham S Khokhar
- Department of Plant and Environmental Sciences, New Mexico State University, Las Cruces, NM, 88003, USA
| | - Seyed Shahabeddin Nourbakhsh
- Department of Plant and Environmental Sciences, New Mexico State University, Las Cruces, NM, 88003, USA
- Department of Extension Plant Sciences, New Mexico State University, Las Cruces, NM, 88003, USA
| | - Soum Sanogo
- Department of Entomology, Plant Pathology and Weed Science, New Mexico State University, Las Cruces, NM, 88003, USA
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López-Fernández M, García-Abadillo J, Uauy C, Ruiz M, Giraldo P, Pascual L. Genome wide association in Spanish bread wheat landraces identifies six key genomic regions that constitute potential targets for improving grain yield related traits. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2023; 136:244. [PMID: 37957405 PMCID: PMC10643358 DOI: 10.1007/s00122-023-04492-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Accepted: 10/24/2023] [Indexed: 11/15/2023]
Abstract
KEY MESSAGE Association mapping conducted in 189 Spanish bread wheat landraces revealed six key genomic regions that constitute stable QTLs for yield and include 15 candidate genes. Genetically diverse landraces provide an ideal population to conduct association analysis. In this study, association mapping was conducted in a collection of 189 Spanish bread wheat landraces whose genomic diversity had been previously assessed. These genomic data were combined with characterization for yield-related traits, including grain size and shape, and phenological traits screened across five seasons. The association analysis revealed a total of 881 significant marker trait associations, involving 434 markers across the genome, that could be grouped in 366 QTLs based on linkage disequilibrium. After accounting for days to heading, we defined 33 high density QTL genomic regions associated to at least four traits. Considering the importance of detecting stable QTLs, 6 regions associated to several grain traits and thousand kernel weight in at least three environments were selected as the most promising ones to harbour targets for breeding. To dissect the genetic cause of the observed associations, we studied the function and in silico expression of the 413 genes located inside these six regions. This identified 15 candidate genes that provide a starting point for future analysis aimed at the identification and validation of wheat yield related genes.
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Affiliation(s)
- Matilde López-Fernández
- Department of Biotechnology-Plant Biology, School of Agricultural, Food and Biosystems Engineering (ETSIAAB), Universidad Politécnica de Madrid (UPM), Madrid, Spain
| | - Julián García-Abadillo
- Department of Biotechnology and Plant Biology, Centre for Biotechnology and Plant Genomics (CBGP), Universidad Politécnica de Madrid (UPM), Madrid, Spain
| | - Cristobal Uauy
- John Innes Centre, Norwich Research Park, Norwich, NR4 7UH, UK
| | - Magdalena Ruiz
- Instituto Nacional de Investigacion y Tecnologia Agraria y Alimentaria (INIA), CSIC, Autovía A2, Km. 36.2. Finca La Canaleja, 28805, Alcalá de Henares, Madrid, Spain
| | - Patricia Giraldo
- Department of Biotechnology-Plant Biology, School of Agricultural, Food and Biosystems Engineering (ETSIAAB), Universidad Politécnica de Madrid (UPM), Madrid, Spain.
| | - Laura Pascual
- Department of Biotechnology-Plant Biology, School of Agricultural, Food and Biosystems Engineering (ETSIAAB), Universidad Politécnica de Madrid (UPM), Madrid, Spain
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Kaur H, Sharma P, Kumar J, Singh VK, Vasistha NK, Gahlaut V, Tyagi V, Verma SK, Singh S, Dhaliwal HS, Sheikh I. Genetic analysis of iron, zinc and grain yield in wheat-Aegilops derivatives using multi-locus GWAS. Mol Biol Rep 2023; 50:9191-9202. [PMID: 37776411 DOI: 10.1007/s11033-023-08800-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Accepted: 09/05/2023] [Indexed: 10/02/2023]
Abstract
BACKGROUND Wheat is a major staple crop and helps to reduce worldwide micronutrient deficiency. Investigating the genetics that control the concentrations of iron (Fe) and zinc (Zn) in wheat is crucial. Hence, we undertook a comprehensive study aimed at elucidating the genomic regions linked to the contents of Fe and Zn in the grain. METHODS AND RESULTS We performed the multi-locus genome-wide association (ML-GWAS) using a panel of 161 wheat-Aegilops substitution and addition lines to dissect the genomic regions controlling grain iron (GFeC), and grain zinc (GZnC) contents. The wheat panel was genotyped using 10,825 high-quality SNPs and phenotyped in three different environments (E1-E3) during 2017-2019. A total of 111 marker-trait associations (MTAs) (at p-value < 0.001) were detected that belong to all three sub-genomes of wheat. The highest number of MTAs were identified for GFeC (58), followed by GZnC (44) and yield (9). Further, six stable MTAs were identified for these three traits and also two pleiotropic MTAs were identified for GFeC and GZnC. A total of 1291 putative candidate genes (CGs) were also identified for all three traits. These CGs encode a diverse set of proteins, including heavy metal-associated (HMA), bZIP family protein, AP2/ERF, and protein previously associated with GFeC, GZnC, and grain yield. CONCLUSIONS The significant MTAs and CGs pinpointed in this current study are poised to play a pivotal role in enhancing both the nutritional quality and yield of wheat, utilizing marker-assisted selection (MAS) techniques.
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Affiliation(s)
- Harneet Kaur
- Department of Genetics-Plant Breeding and Biotechnology, Dr. Khem Singh Gill Akal College of Agriculture, Eternal University, Baru Sahib, Sirmaur, 173101, India
| | - Prachi Sharma
- Department of Genetics-Plant Breeding and Biotechnology, Dr. Khem Singh Gill Akal College of Agriculture, Eternal University, Baru Sahib, Sirmaur, 173101, India
| | - Jitendra Kumar
- National Agri-Food Biotechnology Institute, Sector-81, Mohali, Punjab, 140306, India
| | - Vikas Kumar Singh
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, U.P., 250004, India
| | - Neeraj Kumar Vasistha
- Department of Genetics-Plant Breeding and Biotechnology, Dr. Khem Singh Gill Akal College of Agriculture, Eternal University, Baru Sahib, Sirmaur, 173101, India
- Department of Genetics and Plant Breeding, Rajiv Gandhi University, Itanagar, India
| | - Vijay Gahlaut
- Department of Biotechnology, Chandigarh University, Gharuan, Mohali, Punjab, 140413, India.
- University Center for Research and Development, Chandigarh University, Gharuan, Mohali, Punjab, 140413, India.
| | - Vikrant Tyagi
- Department of Genetics-Plant Breeding and Biotechnology, Dr. Khem Singh Gill Akal College of Agriculture, Eternal University, Baru Sahib, Sirmaur, 173101, India
| | | | - Sukhwinder Singh
- International Maize and Wheat Improvement Center (CIMMYT), El Batan, Texcoco, Mexico
- USDA-ARS, Southeast Area, Subtropical Horticulture Research Station, 13601 Old Cutler Road, Miami, FL, 33158, USA
| | - H S Dhaliwal
- Department of Genetics-Plant Breeding and Biotechnology, Dr. Khem Singh Gill Akal College of Agriculture, Eternal University, Baru Sahib, Sirmaur, 173101, India
| | - Imran Sheikh
- Department of Genetics-Plant Breeding and Biotechnology, Dr. Khem Singh Gill Akal College of Agriculture, Eternal University, Baru Sahib, Sirmaur, 173101, India.
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Kumar M, Kumar S, Sandhu KS, Kumar N, Saripalli G, Prakash R, Nambardar A, Sharma H, Gautam T, Balyan HS, Gupta PK. GWAS and genomic prediction for pre-harvest sprouting tolerance involving sprouting score and two other related traits in spring wheat. MOLECULAR BREEDING : NEW STRATEGIES IN PLANT IMPROVEMENT 2023; 43:14. [PMID: 37313293 PMCID: PMC10248620 DOI: 10.1007/s11032-023-01357-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Accepted: 01/26/2023] [Indexed: 06/15/2023]
Abstract
In wheat, a genome-wide association study (GWAS) and genomic prediction (GP) analysis were conducted for pre-harvest sprouting (PHS) tolerance and two of its related traits. For this purpose, an association panel of 190 accessions was phenotyped for PHS (using sprouting score), falling number, and grain color over two years and genotyped with 9904 DArTseq based SNP markers. GWAS for main-effect quantitative trait nucleotides (M-QTNs) using three different models (CMLM, SUPER, and FarmCPU) and epistatic QTNs (E-QTNs) using PLINK were performed. A total of 171 M-QTNs (CMLM, 47; SUPER, 70; FarmCPU, 54) for all three traits, and 15 E-QTNs involved in 20 first-order epistatic interactions were identified. Some of the above QTNs overlapped the previously reported QTLs, MTAs, and cloned genes, allowing delineating 26 PHS-responsive genomic regions that spread over 16 wheat chromosomes. As many as 20 definitive and stable QTNs were considered important for use in marker-assisted recurrent selection (MARS). The gene, TaPHS1, for PHS tolerance (PHST) associated with one of the QTNs was also validated using the KASP assay. Some of the M-QTNs were shown to have a key role in the abscisic acid pathway involved in PHST. Genomic prediction accuracies (based on the cross-validation approach) using three different models ranged from 0.41 to 0.55, which are comparable to the results of previous studies. In summary, the results of the present study improved our understanding of the genetic architecture of PHST and its related traits in wheat and provided novel genomic resources for wheat breeding based on MARS and GP. Supplementary Information The online version contains supplementary material available at 10.1007/s11032-023-01357-5.
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Affiliation(s)
- Manoj Kumar
- Department of Genetics and Plant Breeding, Chaudhary Charan Singh University, Meerut, UP India
| | - Sachin Kumar
- Department of Genetics and Plant Breeding, Chaudhary Charan Singh University, Meerut, UP India
| | | | - Neeraj Kumar
- Department of Plant and Environmental Sciences, Clemson University, Clemson, SC USA
| | - Gautam Saripalli
- Department of Genetics and Plant Breeding, Chaudhary Charan Singh University, Meerut, UP India
- Department of Plant Science and Landscape Architecture, University of Maryland, College Park, MD USA
| | - Ram Prakash
- Department of Genetics and Plant Breeding, Chaudhary Charan Singh University, Meerut, UP India
| | - Akash Nambardar
- Department of Genetics and Plant Breeding, Chaudhary Charan Singh University, Meerut, UP India
| | - Hemant Sharma
- Department of Genetics and Plant Breeding, Chaudhary Charan Singh University, Meerut, UP India
| | - Tinku Gautam
- Department of Genetics and Plant Breeding, Chaudhary Charan Singh University, Meerut, UP India
| | - Harindra Singh Balyan
- Department of Genetics and Plant Breeding, Chaudhary Charan Singh University, Meerut, UP India
| | - Pushpendra Kumar Gupta
- Department of Genetics and Plant Breeding, Chaudhary Charan Singh University, Meerut, UP India
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Singh S, Gaurav SS, Vasistha NK, Kumar U, Joshi AK, Mishra VK, Chand R, Gupta PK. Genetics of spot blotch resistance in bread wheat ( Triticum aestivum L.) using five models for GWAS. FRONTIERS IN PLANT SCIENCE 2023; 13:1036064. [PMID: 36743576 PMCID: PMC9891466 DOI: 10.3389/fpls.2022.1036064] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/03/2022] [Accepted: 12/28/2022] [Indexed: 06/18/2023]
Abstract
Genetic architecture of resistance to spot blotch in wheat was examined using a Genome-Wide Association Study (GWAS) involving an association panel comprising 303 diverse genotypes. The association panel was evaluated at two different locations in India including Banaras Hindu University (BHU), Varanasi (Uttar Pradesh), and Borlaug Institute for South Asia (BISA), Pusa, Samastipur (Bihar) for two consecutive years (2017-2018 and 2018-2019), thus making four environments (E1, BHU 2017-18; E2, BHU 2018-19; E3, PUSA, 2017-18; E4, PUSA, 2018-19). The panel was genotyped for 12,196 SNPs based on DArT-seq (outsourced to DArT Ltd by CIMMYT); these SNPs included 5,400 SNPs, which could not be assigned to individual chromosomes and were therefore, described as unassigned by the vendor. Phenotypic data was recorded on the following three disease-related traits: (i) Area Under Disease Progress Curve (AUDPC), (ii) Incubation Period (IP), and (iii) Lesion Number (LN). GWAS was conducted using each of five different models, which included two single-locus models (CMLM and SUPER) and three multi-locus models (MLMM, FarmCPU, and BLINK). This exercise gave 306 MTAs, but only 89 MTAs (33 for AUDPC, 30 for IP and 26 for LN) including a solitary MTA detected using all the five models and 88 identified using four of the five models (barring SUPER) were considered to be important. These were used for further analysis, which included identification of candidate genes (CGs) and their annotation. A majority of these MTAs were novel. Only 70 of the 89 MTAs were assigned to individual chromosomes; the remaining 19 MTAs belonged to unassigned SNPs, for which chromosomes were not known. Seven MTAs were selected on the basis of minimum P value, number of models, number of environments and location on chromosomes with respect to QTLs reported earlier. These 7 MTAs, which included five main effect MTAs and two for epistatic interactions, were considered to be important for marker-assisted selection (MAS). The present study thus improved our understanding of the genetics of resistance against spot blotch in wheat and provided seven MTAs, which may be used for MAS after due validation.
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Affiliation(s)
- Sahadev Singh
- Molecular Biology Laboratory, Department of Genetics and Plant Breeding, Chaudhary Charan Singh University, Meerut, India
| | - Shailendra Singh Gaurav
- Molecular Biology Laboratory, Department of Genetics and Plant Breeding, Chaudhary Charan Singh University, Meerut, India
| | - Neeraj Kumar Vasistha
- Department of Genetics-Plant Breeding and Biotechnology, Dr Khem Singh Gill, Akal College of Agriculture, Eternal University, Sirmaur, India
| | - Uttam Kumar
- Borlaug Institute for South Asia (BISA), Ludhiana, India
| | - Arun Kumar Joshi
- The International Maize and Wheat Improvement Center (CIMMYT), Borlaug Institute for South Asia (BISA), G-2, B-Block, NASC Complex, DPS Marg, New Delhi, India
| | - Vinod Kumar Mishra
- Department of Genetics and Plant Breeding, Indian Institute of Agricultural Science, Banaras Hindu University, Varanasi, India
| | - Ramesh Chand
- Department of Mycology and Plant Pathology, Indian Institute of Agricultural Science Banaras Hindu University, Varanasi, India
| | - Pushpendra Kumar Gupta
- Molecular Biology Laboratory, Department of Genetics and Plant Breeding, Chaudhary Charan Singh University, Meerut, India
- Borlaug Institute for South Asia (BISA), Ludhiana, India
- Murdoch’s Centre for Crop & Food Innovation, Murdoch University, Murdoch, WA, Australia
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Khan H, Krishnappa G, Kumar S, Mishra CN, Krishna H, Devate NB, Rathan ND, Parkash O, Yadav SS, Srivastava P, Biradar S, Kumar M, Singh GP. Genome-wide association study for grain yield and component traits in bread wheat (Triticum aestivum L.). Front Genet 2022; 13:982589. [PMID: 36092913 PMCID: PMC9458894 DOI: 10.3389/fgene.2022.982589] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Accepted: 07/20/2022] [Indexed: 11/25/2022] Open
Abstract
Genomic regions governing days to heading (DH), grain filling duration (GFD), grain number per spike (GNPS), grain weight per spike (GWPS), plant height (PH), and grain yield (GY) were investigated in a set of 280 diverse bread wheat genotypes. The genome-wide association studies (GWAS) panel was genotyped using a 35K Axiom Array and phenotyped in five environments. The GWAS analysis showed a total of 27 Bonferroni-corrected marker-trait associations (MTAs) on 15 chromosomes representing all three wheat subgenomes. The GFD showed the highest MTAs (8), followed by GWPS (7), GY (4), GNPS (3), PH (3), and DH (2). Furthermore, 20 MTAs were identified with more than 10% phenotypic variation. A total of five stable MTAs (AX-95024590, AX-94425015, AX-95210025 AX-94539354, and AX-94978133) were identified in more than one environment and associated with the expression of DH, GFD, GNPS, and GY. Similarly, two novel pleiotropic genomic regions with associated MTAs i.e. AX-94978133 (4D) and AX-94539354 (6A) harboring co-localized QTLs governing two or more traits were also identified. In silico analysis revealed that the SNPs were located on important putative candidate genes such as F-box-like domain superfamily, Lateral organ boundaries, LOB, Thioredoxin-like superfamily Glutathione S-transferase, RNA-binding domain superfamily, UDP-glycosyltransferase family, Serine/threonine-protein kinase, Expansin, Patatin, Exocyst complex component Exo70, DUF1618 domain, Protein kinase domain involved in the regulation of grain size, grain number, growth and development, grain filling duration, and abiotic stress tolerance. The identified novel MTAs will be validated to estimate their effects in different genetic backgrounds for subsequent use in marker-assisted selection (MAS).
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Affiliation(s)
- Hanif Khan
- ICAR-Indian Institute of Wheat and Barley Research, Karnal, India
| | - Gopalareddy Krishnappa
- ICAR-Indian Institute of Wheat and Barley Research, Karnal, India
- ICAR-Sugarcane Breeding Institute, Coimbatore, India
- *Correspondence: Gopalareddy Krishnappa, ; Gyanendra Pratap Singh,
| | - Satish Kumar
- ICAR-Indian Institute of Wheat and Barley Research, Karnal, India
| | | | - Hari Krishna
- ICAR-Indian Agricultural Research Institute, New Delhi, India
| | | | | | - Om Parkash
- ICAR-Indian Institute of Wheat and Barley Research, Karnal, India
| | - Sonu Singh Yadav
- ICAR-Indian Institute of Wheat and Barley Research, Karnal, India
| | | | - Suma Biradar
- University of Agricultural Sciences, Dharwad, India
| | - Monu Kumar
- ICAR-Indian Agricultural Research Institute, Jharkhand, India
| | - Gyanendra Pratap Singh
- ICAR-Indian Institute of Wheat and Barley Research, Karnal, India
- *Correspondence: Gopalareddy Krishnappa, ; Gyanendra Pratap Singh,
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Malik P, Kumar J, Sharma S, Meher PK, Balyan HS, Gupta PK, Sharma S. GWAS for main effects and epistatic interactions for grain morphology traits in wheat. PHYSIOLOGY AND MOLECULAR BIOLOGY OF PLANTS : AN INTERNATIONAL JOURNAL OF FUNCTIONAL PLANT BIOLOGY 2022; 28:651-668. [PMID: 35465203 PMCID: PMC8986918 DOI: 10.1007/s12298-022-01164-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/25/2021] [Revised: 03/05/2022] [Accepted: 03/07/2022] [Indexed: 06/05/2023]
Abstract
In the present study in wheat, GWAS was conducted for identification of marker trait associations (MTAs) for the following six grain morphology traits: (1) grain cross-sectional area (GCSA), (2) grain perimeter (GP), (3) grain length (GL), (4) grain width (GWid), (5) grain length-width ratio (GLWR) and (6) grain form-density (GFD). The data were recorded on a subset of spring wheat reference set (SWRS) comprising 225 diverse genotypes, which were genotyped using 10,904 SNPs and phenotyped for two consecutive years (2017-2018, 2018-2019). GWAS was conducted using five different models including two single-locus models (CMLM, SUPER), one multi-locus model (FarmCPU), one multi-trait model (mvLMM) and a model for Q x Q epistatic interactions. False discovery rate (FDR) [P value -log10(p) ≥ 5] and Bonferroni correction [P value -log10(p) ≥ 6] (corrected p value < 0.05) were applied to eliminate false positives due to multiple testing. This exercise gave 88 main effect and 29 epistatic MTAs after FDR and 13 main effect and 6 epistatic MTAs after Bonferroni corrections. MTAs obtained after Bonferroni corrections were further utilized for identification of 55 candidate genes (CGs). In silico expression analysis of CGs in different tissues at different parts of the seed at different developmental stages was also carried out. MTAs and CGs identified during the present study are useful addition to available resources for MAS to supplement wheat breeding programmes after due validation and also for future strategic basic research. Supplementary Information The online version contains supplementary material available at 10.1007/s12298-022-01164-w.
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Affiliation(s)
- Parveen Malik
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, U.P 250 004 India
| | - Jitendra Kumar
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, U.P 250 004 India
- Department of Biotechnology, National Agri-Food Biotechnology Institute (NABI), Govt. of India, Sector 81 (Knowledge City), S.A.S. Nagar, Mohali, Punjab 140306 India
| | - Shiveta Sharma
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, U.P 250 004 India
| | - Prabina Kumar Meher
- Centre for Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, New Delhi, 110012 India
| | - Harindra Singh Balyan
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, U.P 250 004 India
| | - Pushpendra Kumar Gupta
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, U.P 250 004 India
| | - Shailendra Sharma
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, U.P 250 004 India
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Gahlaut V, Jaiswal V, Balyan HS, Joshi AK, Gupta PK. Multi-Locus GWAS for Grain Weight-Related Traits Under Rain-Fed Conditions in Common Wheat ( Triticum aestivum L.). FRONTIERS IN PLANT SCIENCE 2021; 12:758631. [PMID: 34745191 PMCID: PMC8568012 DOI: 10.3389/fpls.2021.758631] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/14/2021] [Accepted: 09/20/2021] [Indexed: 05/04/2023]
Abstract
In wheat, a multi-locus genome-wide association study (ML-GWAS) was conducted for the four grain weight-related traits (days to anthesis, grain filling duration, grain number per ear, and grain weight per ear) using data recorded under irrigated (IR) and rain-fed (RF) conditions. Seven stress-related indices were estimated for these four traits: (i) drought resistance index (DI), (ii) geometric mean productivity (GMP), (iii) mean productivity index (MPI), (iv) relative drought index (RDI), (v) stress tolerance index (STI), (vi) yield index, and (vii) yield stability index (YSI). The association panel consisted of a core collection of 320 spring wheat accessions representing 28 countries. The panel was genotyped using 9,627 single nucleotide polymorphisms (SNPs). The genome-wide association (GWA) analysis provided 30 significant marker-trait associations (MTAs), distributed as follows: (i) IR (15 MTAs), (ii) RF (14 MTAs), and (iii) IR+RF (1 MTA). In addition, 153 MTAs were available for the seven stress-related indices. Five MTAs co-localized with previously reported QTLs/MTAs. Candidate genes (CGs) associated with different MTAs were also worked out. Gene ontology (GO) analysis and expression analysis together allowed the selection of the two CGs, which may be involved in response to drought stress. These two CGs included: TraesCS1A02G331000 encoding RNA helicase and TraesCS4B02G051200 encoding microtubule-associated protein 65. The results supplemented the current knowledge on genetics for drought tolerance in wheat. The results may also be used for future wheat breeding programs to develop drought-tolerant wheat cultivars.
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Affiliation(s)
- Vijay Gahlaut
- Department of Genetics and Plant Breeding, Chaudhary Charan Singh University, Meerut, India
- Council of Scientific & Industrial Research-Institute of Himalayan Bioresource Technology, Palampur, India
| | - Vandana Jaiswal
- Department of Genetics and Plant Breeding, Chaudhary Charan Singh University, Meerut, India
- Council of Scientific & Industrial Research-Institute of Himalayan Bioresource Technology, Palampur, India
| | - Harindra S. Balyan
- Department of Genetics and Plant Breeding, Chaudhary Charan Singh University, Meerut, India
| | - Arun Kumar Joshi
- International Maize and Wheat Improvement Center (CIMMYT), New Delhi, India
- Borlaug Institute for South Asia (BISA), New Delhi, India
| | - Pushpendra K. Gupta
- Department of Genetics and Plant Breeding, Chaudhary Charan Singh University, Meerut, India
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