1
|
Sivabharathi RC, Rajagopalan VR, Suresh R, Sudha M, Karthikeyan G, Jayakanthan M, Raveendran M. Haplotype-based breeding: A new insight in crop improvement. PLANT SCIENCE : AN INTERNATIONAL JOURNAL OF EXPERIMENTAL PLANT BIOLOGY 2024; 346:112129. [PMID: 38763472 DOI: 10.1016/j.plantsci.2024.112129] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/15/2024] [Revised: 05/09/2024] [Accepted: 05/15/2024] [Indexed: 05/21/2024]
Abstract
Haplotype-based breeding (HBB) is one of the cutting-edge technologies in the realm of crop improvement due to the increasing availability of Single Nucleotide Polymorphisms identified by Next Generation Sequencing technologies. The complexity of the data can be decreased with fewer statistical tests and a lower probability of spurious associations by combining thousands of SNPs into a few hundred haplotype blocks. The presence of strong genomic regions in breeding lines of most crop species facilitates the use of haplotypes to improve the efficiency of genomic and marker-assisted selection. Haplotype-based breeding as a Genomic Assisted Breeding (GAB) approach harnesses the genome sequence data to pinpoint the allelic variation used to hasten the breeding cycle and circumvent the challenges associated with linkage drag. This review article demonstrates ways to identify candidate genes, superior haplotype identification, haplo-pheno analysis, and haplotype-based marker-assisted selection. The crop improvement strategies that utilize superior haplotypes will hasten the breeding progress to safeguard global food security.
Collapse
Affiliation(s)
- R C Sivabharathi
- Department of Genetics and Plant breeding, CPBG, Tamil Nadu Agricultural University, Coimbatore 641003, India
| | - Veera Ranjani Rajagopalan
- Department of Plant Biotechnology, Centre for Plant Molecular Biology and Biotechnology, Tamil Nadu Agricultural University, Coimbatore, 641003, India
| | - R Suresh
- Department of Rice, CPBG, Tamil Nadu Agricultural University, Coimbatore 641003, India
| | - M Sudha
- Department of Plant Biotechnology, Centre for Plant Molecular Biology and Biotechnology, Tamil Nadu Agricultural University, Coimbatore, 641003, India.
| | - G Karthikeyan
- Department of Plant Pathology, CPPS, Tamil Nadu Agricultural University, Coimbatore 641003, India
| | - M Jayakanthan
- Department of Plant Molecular Biology and Bioinformatics, Centre for Plant Molecular Biology and Biotechnology, Tamil Nadu Agricultural University, Coimbatore 641003, India
| | - M Raveendran
- Directorate of research, Tamil Nadu Agricultural University, Coimbatore 641003, India.
| |
Collapse
|
2
|
Nisa WU, Sandhu S, Nair SK, Kaur H, Kumar A, Rashid Z, Saykhedkar G, Vikal Y. Insights into maydis leaf blight resistance in maize: a comprehensive genome-wide association study in sub-tropics of India. BMC Genomics 2024; 25:760. [PMID: 39103778 DOI: 10.1186/s12864-024-10655-x] [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: 05/17/2024] [Accepted: 07/23/2024] [Indexed: 08/07/2024] Open
Abstract
BACKGROUND In the face of contemporary climatic vulnerabilities and escalating global temperatures, the prevalence of maydis leaf blight (MLB) poses a potential threat to maize production. This study endeavours to discern marker-trait associations and elucidate the candidate genes that underlie resistance to MLB in maize by employing a diverse panel comprising 336 lines. The panel was screening for MLB across four environments, employing standard artificial inoculation techniques. Genome-wide association studies (GWAS) and haplotype analysis were conducted utilizing a total of 128,490 SNPs obtained from genotyping-by-sequencing (GBS). RESULTS GWAS identified 26 highly significant SNPs associated with MLB resistance, among the markers examined. Seven of these SNPs, reported in novel chromosomal bins (9.06, 5.01, 9.01, 7.04, 4.06, 1.04, and 6.05) were associated with genes: bzip23, NAGS1, CDPK7, aspartic proteinase NEP-2, VQ4, and Wun1, which were characterized for their roles in diminishing fungal activity, fortifying defence mechanisms against necrotrophic pathogens, modulating phyto-hormone signalling, and orchestrating oxidative burst responses. Gene mining approach identified 22 potential candidate genes associated with SNPs due to their functional relevance to resistance against necrotrophic pathogens. Notably, bin 8.06, which hosts five SNPs, showed a connection to defense-regulating genes against MLB, indicating the potential formation of a functional gene cluster that triggers a cascade of reactions against MLB. In silico studies revealed gene expression levels exceeding ten fragments per kilobase million (FPKM) for most genes and demonstrated coexpression among all candidate genes in the coexpression network. Haplotype regression analysis revealed the association of 13 common significant haplotypes at Bonferroni ≤ 0.05. The phenotypic variance explained by these significant haplotypes ranged from low to moderate, suggesting a breeding strategy that combines multiple resistance alleles to enhance resistance to MLB. Additionally, one particular haplotype block (Hap_8.3) was found to consist of two SNPs (S8_152715134, S8_152460815) identified in GWAS with 9.45% variation explained (PVE). CONCLUSION The identified SNPs/ haplotypes associated with the trait of interest contribute to the enrichment of allelic diversity and hold direct applicability in Genomics Assisted Breeding for enhancing MLB resistance in maize.
Collapse
Affiliation(s)
- Wajhat- Un- Nisa
- Dept. of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, India
| | - Surinder Sandhu
- Dept. of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, India.
| | | | - Harleen Kaur
- Dept. of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, India
| | - Ashok Kumar
- Regional Research Station, Punjab Agricultural University, Gurdaspur, Ludhiana, India
| | - Zerka Rashid
- International Maize and Wheat Improvement Centre (CIMMYT), Hyderabad, India
| | - Gajanan Saykhedkar
- International Maize and Wheat Improvement Centre (CIMMYT), Hyderabad, India
| | - Yogesh Vikal
- School of Agricultural Biotechnology, Punjab Agricultural University, Ludhiana, India
| |
Collapse
|
3
|
Wang J, Yang Q, Chen Y, Liu K, Zhang Z, Xiong Y, Yu H, Yu Y, Wang J, Song J, Qiu L. QTL mapping and genomic selection of stem and branch diameter in soybean ( Glycine max L.). FRONTIERS IN PLANT SCIENCE 2024; 15:1388365. [PMID: 38882575 PMCID: PMC11176531 DOI: 10.3389/fpls.2024.1388365] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/19/2024] [Accepted: 05/03/2024] [Indexed: 06/18/2024]
Abstract
Introduction Soybean stem diameter (SD) and branch diameter (BD) are closely related traits, and genetic clarification of SD and BD is crucial for soybean breeding. Methods SD and BD were genetically analyzed by a population of 363 RIL derived from the cross between Zhongdou41 (ZD41) and ZYD02878 using restricted two-stage multi-locus genome-wide association, inclusive composite interval mapping, and three-variance component multi-locus random SNP effect mixed linear modeling. Then candidate genes of major QTLs were selected and genetic selection model of SD and BD were constructed respectively. Results and discussion The results showed that SD and BD were significantly correlated (r = 0.74, P < 0.001). A total of 93 and 84 unique quantitative trait loci (QTL) were detected for SD and BD, respectively by three different methods. There were two and ten major QTLs for SD and BD, respectively, with phenotypic variance explained (PVE) by more than 10%. Within these loci, seven genes involved in the regulation of phytohormones (IAA and GA) and cell proliferation and showing extensive expression of shoot apical meristematic genes were selected as candidate genes. Genomic selection (GS) analysis showed that the trait-associated markers identified in this study reached 0.47-0.73 in terms of prediction accuracy, which was enhanced by 6.56-23.69% compared with genome-wide markers. These results clarify the genetic basis of SD and BD, which laid solid foundation in regulation gene cloning, and GS models constructed could be potentially applied in future breeding programs.
Collapse
Affiliation(s)
- Jing Wang
- MARA Key Laboratory of Sustainable Crop Production in the Middle Reaches of the Yangtze River (Co-construction by Ministry and Province), College of Agriculture, Yangtze University, Jingzhou, China
- The Shennong Laboratory, Zhengzhou, Henan, China
| | - Qichao Yang
- MARA Key Laboratory of Sustainable Crop Production in the Middle Reaches of the Yangtze River (Co-construction by Ministry and Province), College of Agriculture, Yangtze University, Jingzhou, China
- The Shennong Laboratory, Zhengzhou, Henan, China
| | - Yijie Chen
- MARA Key Laboratory of Sustainable Crop Production in the Middle Reaches of the Yangtze River (Co-construction by Ministry and Province), College of Agriculture, Yangtze University, Jingzhou, China
- The Shennong Laboratory, Zhengzhou, Henan, China
| | - Kanglin Liu
- MARA Key Laboratory of Sustainable Crop Production in the Middle Reaches of the Yangtze River (Co-construction by Ministry and Province), College of Agriculture, Yangtze University, Jingzhou, China
| | - Zhiqing Zhang
- MARA Key Laboratory of Sustainable Crop Production in the Middle Reaches of the Yangtze River (Co-construction by Ministry and Province), College of Agriculture, Yangtze University, Jingzhou, China
| | - Yajun Xiong
- MARA Key Laboratory of Sustainable Crop Production in the Middle Reaches of the Yangtze River (Co-construction by Ministry and Province), College of Agriculture, Yangtze University, Jingzhou, China
| | - Huan Yu
- MARA Key Laboratory of Sustainable Crop Production in the Middle Reaches of the Yangtze River (Co-construction by Ministry and Province), College of Agriculture, Yangtze University, Jingzhou, China
| | - Yingdong Yu
- MARA Key Laboratory of Sustainable Crop Production in the Middle Reaches of the Yangtze River (Co-construction by Ministry and Province), College of Agriculture, Yangtze University, Jingzhou, China
| | - Jun Wang
- MARA Key Laboratory of Sustainable Crop Production in the Middle Reaches of the Yangtze River (Co-construction by Ministry and Province), College of Agriculture, Yangtze University, Jingzhou, China
- The Shennong Laboratory, Zhengzhou, Henan, China
| | - Jian Song
- MARA Key Laboratory of Sustainable Crop Production in the Middle Reaches of the Yangtze River (Co-construction by Ministry and Province), College of Agriculture, Yangtze University, Jingzhou, China
| | - Lijuan Qiu
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
- National Key Facility for Gene Resources and Genetic Improvement, Key Laboratory of Crop Germplasm Utilization, Ministry of Agriculture and Rural Affairs, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| |
Collapse
|
4
|
Sachdeva S, Singh R, Maurya A, Singh VK, Singh UM, Kumar A, Singh GP. Multi-model genome-wide association studies for appearance quality in rice. FRONTIERS IN PLANT SCIENCE 2024; 14:1304388. [PMID: 38273959 PMCID: PMC10808671 DOI: 10.3389/fpls.2023.1304388] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Accepted: 12/22/2023] [Indexed: 01/27/2024]
Abstract
Improving the quality of the appearance of rice is critical to meet market acceptance. Mining putative quality-related genes has been geared towards the development of effective breeding approaches for rice. In the present study, two SL-GWAS (CMLM and MLM) and three ML-GWAS (FASTmrEMMA, mrMLM, and FASTmrMLM) genome-wide association studies were conducted in a subset of 3K-RGP consisting of 198 rice accessions with 553,831 SNP markers. A total of 594 SNP markers were identified using the mixed linear model method for grain quality traits. Additionally, 70 quantitative trait nucleotides (QTNs) detected by the ML-GWAS models were strongly associated with grain aroma (AR), head rice recovery (HRR, %), and percentage of grains with chalkiness (PGC, %). Finally, 39 QTNs were identified using single- and multi-locus GWAS methods. Among the 39 reliable QTNs, 20 novel QTNs were identified for the above-mentioned three quality-related traits. Based on annotation and previous studies, four functional candidate genes (LOC_Os01g66110, LOC_Os01g66140, LOC_Os07g44910, and LOC_Os02g14120) were found to influence AR, HRR (%), and PGC (%), which could be utilized in rice breeding to improve grain quality traits.
Collapse
Affiliation(s)
- Supriya Sachdeva
- Division of Genomic Resources, ICAR-National Bureau of Plant Genetic Resources (NBPGR), New Delhi, India
| | - Rakesh Singh
- Division of Genomic Resources, ICAR-National Bureau of Plant Genetic Resources (NBPGR), New Delhi, India
| | - Avantika Maurya
- Division of Genomic Resources, ICAR-National Bureau of Plant Genetic Resources (NBPGR), New Delhi, India
| | - Vikas Kumar Singh
- International Rice Research Institute, South Asia Hub, International Crop Reseach Institute for Semi Arid Tropics (ICRISAT), Hyderabad, India
| | - Uma Maheshwar Singh
- International Rice Research Institute, South Asia Regional Centre (ISARC), Varanasi, India
| | - Arvind Kumar
- International Crops Research Institute for the Semi-Arid Tropics, Patancheru, Telangana, India
| | - Gyanendra Pratap Singh
- Indian Council of Agricultural Research (ICAR)-National Bureau of Plant Genetic Resources, New Delhi, India
| |
Collapse
|
5
|
Tayade R, Imran M, Ghimire A, Khan W, Nabi RBS, Kim Y. Molecular, genetic, and genomic basis of seed size and yield characteristics in soybean. FRONTIERS IN PLANT SCIENCE 2023; 14:1195210. [PMID: 38034572 PMCID: PMC10684784 DOI: 10.3389/fpls.2023.1195210] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Accepted: 10/30/2023] [Indexed: 12/02/2023]
Abstract
Soybean (Glycine max L. Merr.) is a crucial oilseed cash crop grown worldwide and consumed as oil, protein, and food by humans and feed by animals. Comparatively, soybean seed yield is lower than cereal crops, such as maize, rice, and wheat, and the demand for soybean production does not keep up with the increasing consumption level. Therefore, increasing soybean yield per unit area is the most crucial breeding objective and is challenging for the scientific community. Moreover, yield and associated traits are extensively researched in cereal crops, but little is known about soybeans' genetics, genomics, and molecular regulation of yield traits. Soybean seed yield is a complex quantitative trait governed by multiple genes. Understanding the genetic and molecular processes governing closely related attributes to seed yield is crucial to increasing soybean yield. Advances in sequencing technologies have made it possible to conduct functional genomic research to understand yield traits' genetic and molecular underpinnings. Here, we provide an overview of recent progress in the genetic regulation of seed size in soybean, molecular, genetics, and genomic bases of yield, and related key seed yield traits. In addition, phytohormones, such as auxin, gibberellins, cytokinins, and abscisic acid, regulate seed size and yield. Hence, we also highlight the implications of these factors, challenges in soybean yield, and seed trait improvement. The information reviewed in this study will help expand the knowledge base and may provide the way forward for developing high-yielding soybean cultivars for future food demands.
Collapse
Affiliation(s)
- Rupesh Tayade
- Upland Field Machinery Research Center, Kyungpook National University, Daegu, Republic of Korea
| | - Muhammad Imran
- Division of Biosafety, National Institute of Agriculture Science, Rural Development Administration, Jeonju, Jeollabul-do, Republic of Korea
| | - Amit Ghimire
- Department of Applied Biosciences, Kyungpook National University, Daegu, Republic of Korea
- Department of Integrative Biology, Kyungpook National University, Daegu, Republic of Korea
| | - Waleed Khan
- Department of Applied Biosciences, Kyungpook National University, Daegu, Republic of Korea
- Department of Integrative Biology, Kyungpook National University, Daegu, Republic of Korea
| | - Rizwana Begum Syed Nabi
- Department of Southern Area Crop Science, National Institute of Crop Science, Rural Development Administration, Miryang, Republic of Korea
| | - Yoonha Kim
- Upland Field Machinery Research Center, Kyungpook National University, Daegu, Republic of Korea
- Department of Applied Biosciences, Kyungpook National University, Daegu, Republic of Korea
- Department of Integrative Biology, Kyungpook National University, Daegu, Republic of Korea
| |
Collapse
|
6
|
Calderón-Chagoya R, Vega-Murillo VE, García-Ruiz A, Ríos-Utrera Á, Martínez-Velázquez G, Montaño-Bermúdez M. Discovering Genomic Regions Associated with Reproductive Traits and Frame Score in Mexican Simmental and Simbrah Cattle Using Individual SNP and Haplotype Markers. Genes (Basel) 2023; 14:2004. [PMID: 38002947 PMCID: PMC10671695 DOI: 10.3390/genes14112004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Revised: 10/11/2023] [Accepted: 10/20/2023] [Indexed: 11/26/2023] Open
Abstract
Reproductive efficiency stands as a critical determinant of profitability within beef production systems. The incorporation of molecular markers can expedite advancements in reproductive performance. While the use of SNPs in association analysis is prevalent, approaches centered on haplotypes can offer a more comprehensive insight. The study used registered Simmental and Simbrah cattle genotyped with the GGP Bovine 150 k panel. Phenotypes included scrotal circumference (SC), heifer fertility (HF), stayability (STAY), and frame score (FS). After quality control, 105,129 autosomal SNPs from 967 animals were used. Haplotype blocks were defined based on linkage disequilibrium. Comparison between haplotypes and SNPs for reproductive traits and FS was conducted using Bayesian and frequentist models. 23, 13, 7, and 2 SNPs exhibited associations with FS, SC, HF, and STAY, respectively. In addition, seven, eight, seven, and one haplotypes displayed associations with FS, SC, HF, and STAY, respectively. Within these delineated genomic segments, potential candidate genes were associated.
Collapse
Affiliation(s)
- René Calderón-Chagoya
- Faculty of Veterinary Medicine and Zootechnics, National Autonomous University of Mexico, Ciudad de México 04510, Mexico;
- National Center for Disciplinary Research in Physiology and Animal Improvement, National Institute for Forestry, Agricultural and Livestock Research, Querétaro 76280, Mexico;
| | - Vicente Eliezer Vega-Murillo
- Faculty of Veterinary Medicine and Zootechnics, Veracruzana University, Veracruz 91710, Mexico; (V.E.V.-M.); (Á.R.-U.)
| | - Adriana García-Ruiz
- National Center for Disciplinary Research in Physiology and Animal Improvement, National Institute for Forestry, Agricultural and Livestock Research, Querétaro 76280, Mexico;
| | - Ángel Ríos-Utrera
- Faculty of Veterinary Medicine and Zootechnics, Veracruzana University, Veracruz 91710, Mexico; (V.E.V.-M.); (Á.R.-U.)
| | - Guillermo Martínez-Velázquez
- Experimental Field Santiago Ixcuintla, National Institute for Forestry, Agricultural and Livestock Research, Nayarit 63570, Mexico;
| | - Moisés Montaño-Bermúdez
- National Center for Disciplinary Research in Physiology and Animal Improvement, National Institute for Forestry, Agricultural and Livestock Research, Querétaro 76280, Mexico;
| |
Collapse
|
7
|
Manjunatha PB, Aski MS, Mishra GP, Gupta S, Devate NB, Singh A, Bansal R, Kumar S, Nair RM, Dikshit HK. Genome-wide association studies for phenological and agronomic traits in mungbean ( Vigna radiata L. Wilczek). FRONTIERS IN PLANT SCIENCE 2023; 14:1209288. [PMID: 37810385 PMCID: PMC10558178 DOI: 10.3389/fpls.2023.1209288] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Accepted: 08/25/2023] [Indexed: 10/10/2023]
Abstract
Mungbean (Vigna radiata L. Wilczek) is one of the important warm-season food legumes, contributing substantially to nutritional security and environmental sustainability. The genetic complexity of yield-associated agronomic traits in mungbean is not well understood. To dissect the genetic basis of phenological and agronomic traits, we evaluated 153 diverse mungbean genotypes for two phenological (days to heading and days to maturity) and eight agronomic traits (leaf nitrogen status using SPAD, plant height, number of primary branches, pod length, number of pods per plant, seeds per pod, 100-seed weight, and yield per plant) under two environmental conditions. A wide array of phenotypic variability was apparent among the studied genotypes for all the studied traits. The broad sense of heritability of traits ranged from 0.31 to 0.95 and 0.21 to 0.94 at the Delhi and Ludhiana locations, respectively. A total of 55,634 genome-wide single nucleotide polymorphisms (SNPs) were obtained by the genotyping-by-sequencing method, of which 15,926 SNPs were retained for genome-wide association studies (GWAS). GWAS with Bayesian information and linkage-disequilibrium iteratively nested keyway (BLINK) model identified 50 SNPs significantly associated with phenological and agronomic traits. In total, 12 SNPs were found to be significantly associated with phenological traits across environments, explaining 7%-18.5% of phenotypic variability, and 38 SNPs were significantly associated with agronomic traits, explaining 4.7%-27.6% of the phenotypic variability. The maximum number of SNPs (15) were located on chromosome 1, followed by seven SNPs each on chromosomes 2 and 8. The BLAST search identified 19 putative candidate genes that were involved in light signaling, nitrogen responses, phosphorus (P) transport and remobilization, photosynthesis, respiration, metabolic pathways, and regulating growth and development. Digital expression analysis of 19 genes revealed significantly higher expression of 12 genes, viz. VRADI01G08170, VRADI11G09170, VRADI02G00450, VRADI01G00700, VRADI07G14240, VRADI03G06030, VRADI02G14230, VRADI08G01540, VRADI09G02590, VRADI08G00110, VRADI02G14240, and VRADI02G00430 in the roots, cotyledons, seeds, leaves, shoot apical meristems, and flowers. The identified SNPs and putative candidate genes provide valuable genetic information for fostering genomic studies and marker-assisted breeding programs that improve yield and agronomic traits in mungbean.
Collapse
Affiliation(s)
- P. B. Manjunatha
- Division of Genetics, ICAR- Indian Agricultural Research Institute, New Delhi, India
| | - Muraleedhar S. Aski
- Division of Genetics, ICAR- Indian Agricultural Research Institute, New Delhi, India
| | - Gyan Prakash Mishra
- Division of Genetics, ICAR- Indian Agricultural Research Institute, New Delhi, India
| | - Soma Gupta
- Division of Genetics, ICAR- Indian Agricultural Research Institute, New Delhi, India
| | - Narayana Bhat Devate
- Division of Genetics, ICAR- Indian Agricultural Research Institute, New Delhi, India
| | - Akanksha Singh
- Amity Institute of Organic Agriculture, Amity University, Noida, India
| | - Ruchi Bansal
- Division of Plant Physiology, ICAR- Indian Agricultural Research Institute, New Delhi, India
| | - Shiv Kumar
- International Centre for Agricultural Research in the Dry Areas (ICARDA), New Delhi, India
| | | | - Harsh Kumar Dikshit
- Division of Genetics, ICAR- Indian Agricultural Research Institute, New Delhi, India
| |
Collapse
|
8
|
Susmitha P, Kumar P, Yadav P, Sahoo S, Kaur G, Pandey MK, Singh V, Tseng TM, Gangurde SS. Genome-wide association study as a powerful tool for dissecting competitive traits in legumes. FRONTIERS IN PLANT SCIENCE 2023; 14:1123631. [PMID: 37645459 PMCID: PMC10461012 DOI: 10.3389/fpls.2023.1123631] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Accepted: 06/08/2023] [Indexed: 08/31/2023]
Abstract
Legumes are extremely valuable because of their high protein content and several other nutritional components. The major challenge lies in maintaining the quantity and quality of protein and other nutritional compounds in view of climate change conditions. The global need for plant-based proteins has increased the demand for seeds with a high protein content that includes essential amino acids. Genome-wide association studies (GWAS) have evolved as a standard approach in agricultural genetics for examining such intricate characters. Recent development in machine learning methods shows promising applications for dimensionality reduction, which is a major challenge in GWAS. With the advancement in biotechnology, sequencing, and bioinformatics tools, estimation of linkage disequilibrium (LD) based associations between a genome-wide collection of single-nucleotide polymorphisms (SNPs) and desired phenotypic traits has become accessible. The markers from GWAS could be utilized for genomic selection (GS) to predict superior lines by calculating genomic estimated breeding values (GEBVs). For prediction accuracy, an assortment of statistical models could be utilized, such as ridge regression best linear unbiased prediction (rrBLUP), genomic best linear unbiased predictor (gBLUP), Bayesian, and random forest (RF). Both naturally diverse germplasm panels and family-based breeding populations can be used for association mapping based on the nature of the breeding system (inbred or outbred) in the plant species. MAGIC, MCILs, RIAILs, NAM, and ROAM are being used for association mapping in several crops. Several modifications of NAM, such as doubled haploid NAM (DH-NAM), backcross NAM (BC-NAM), and advanced backcross NAM (AB-NAM), have also been used in crops like rice, wheat, maize, barley mustard, etc. for reliable marker-trait associations (MTAs), phenotyping accuracy is equally important as genotyping. Highthroughput genotyping, phenomics, and computational techniques have advanced during the past few years, making it possible to explore such enormous datasets. Each population has unique virtues and flaws at the genomics and phenomics levels, which will be covered in more detail in this review study. The current investigation includes utilizing elite breeding lines as association mapping population, optimizing the choice of GWAS selection, population size, and hurdles in phenotyping, and statistical methods which will analyze competitive traits in legume breeding.
Collapse
Affiliation(s)
- Pusarla Susmitha
- Regional Agricultural Research Station, Acharya N.G. Ranga Agricultural University, Andhra Pradesh, India
| | - Pawan Kumar
- Department of Genetics and Plant Breeding, College of Agriculture, Chaudhary Charan Singh (CCS) Haryana Agricultural University, Hisar, India
| | - Pankaj Yadav
- Department of Bioscience and Bioengineering, Indian Institute of Technology, Rajasthan, India
| | - Smrutishree Sahoo
- Department of Genetics and Plant Breeding, School of Agriculture, Gandhi Institute of Engineering and Technology (GIET) University, Odisha, India
| | - Gurleen Kaur
- Horticultural Sciences Department, University of Florida, Gainesville, FL, United States
| | - Manish K. Pandey
- Department of Genomics, Prebreeding and Bioinformatics, International Crops Research Institute for the Semi-Arid Tropics, Hyderabad, India
| | - Varsha Singh
- Department of Plant and Soil Sciences, Mississippi State University, Starkville, MS, United States
| | - Te Ming Tseng
- Department of Plant and Soil Sciences, Mississippi State University, Starkville, MS, United States
| | - Sunil S. Gangurde
- Department of Plant Pathology, University of Georgia, Tifton, GA, United States
| |
Collapse
|
9
|
Rani R, Raza G, Ashfaq H, Rizwan M, Razzaq MK, Waheed MQ, Shimelis H, Babar AD, Arif M. Genome-wide association study of soybean ( Glycine max [L.] Merr.) germplasm for dissecting the quantitative trait nucleotides and candidate genes underlying yield-related traits. FRONTIERS IN PLANT SCIENCE 2023; 14:1229495. [PMID: 37636105 PMCID: PMC10450938 DOI: 10.3389/fpls.2023.1229495] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Accepted: 07/25/2023] [Indexed: 08/29/2023]
Abstract
Soybean (Glycine max [L.] Merr.) is one of the most significant crops in the world in terms of oil and protein. Owing to the rising demand for soybean products, there is an increasing need for improved varieties for more productive farming. However, complex correlation patterns among quantitative traits along with genetic interactions pose a challenge for soybean breeding. Association studies play an important role in the identification of accession with useful alleles by locating genomic sites associated with the phenotype in germplasm collections. In the present study, a genome-wide association study was carried out for seven agronomic and yield-related traits. A field experiment was conducted in 2015/2016 at two locations that include 155 diverse soybean germplasm. These germplasms were genotyped using SoySNP50K Illumina Infinium Bead-Chip. A total of 51 markers were identified for node number, plant height, pods per plant, seeds per plant, seed weight per plant, hundred-grain weight, and total yield using a multi-locus linear mixed model (MLMM) in FarmCPU. Among these significant SNPs, 18 were putative novel QTNs, while 33 co-localized with previously reported QTLs. A total of 2,356 genes were found in 250 kb upstream and downstream of significant SNPs, of which 17 genes were functional and the rest were hypothetical proteins. These 17 candidate genes were located in the region of 14 QTNs, of which ss715580365, ss715608427, ss715632502, and ss715620131 are novel QTNs for PH, PPP, SDPP, and TY respectively. Four candidate genes, Glyma.01g199200, Glyma.10g065700, Glyma.18g297900, and Glyma.14g009900, were identified in the vicinity of these novel QTNs, which encode lsd one like 1, Ergosterol biosynthesis ERG4/ERG24 family, HEAT repeat-containing protein, and RbcX2, respectively. Although further experimental validation of these candidate genes is required, several appear to be involved in growth and developmental processes related to the respective agronomic traits when compared with their homologs in Arabidopsis thaliana. This study supports the usefulness of association studies and provides valuable data for functional markers and investigating candidate genes within a diverse germplasm collection in future breeding programs.
Collapse
Affiliation(s)
- Reena Rani
- Agricultural Biotechnology Division, National Institute for Biotechnology and Genetic Engineering (NIBGE), Constituent College Pakistan Institute of Engineering and Applied Sciences (PIEAS), Faisalabad, Pakistan
| | - Ghulam Raza
- Agricultural Biotechnology Division, National Institute for Biotechnology and Genetic Engineering (NIBGE), Constituent College Pakistan Institute of Engineering and Applied Sciences (PIEAS), Faisalabad, Pakistan
| | - Hamza Ashfaq
- Agricultural Biotechnology Division, National Institute for Biotechnology and Genetic Engineering (NIBGE), Constituent College Pakistan Institute of Engineering and Applied Sciences (PIEAS), Faisalabad, Pakistan
| | - Muhammad Rizwan
- Plant Breeding and Genetics Division, Nuclear Institute of Agriculture (NIA), Tando Jam, Pakistan
| | - Muhammad Khuram Razzaq
- Soybean Research Institute, National Center for Soybean Improvement, Nanjing Agricultural University, Nanjing, China
| | - Muhammad Qandeel Waheed
- Plant Breeding and Genetics Division, Nuclear Institute for Agriculture and Biology (NIAB), Constituent College Pakistan Institute of Engineering and Applied Sciences (PIEAS), Faisalabad, Pakistan
| | - Hussein Shimelis
- School of Agricultural, Earth and Environmental Sciences, African Centre for Crop Improvement, University of KwaZulu-Natal, Pietermaritzburg, South Africa
| | - Allah Ditta Babar
- Agricultural Biotechnology Division, National Institute for Biotechnology and Genetic Engineering (NIBGE), Constituent College Pakistan Institute of Engineering and Applied Sciences (PIEAS), Faisalabad, Pakistan
| | - Muhammad Arif
- Agricultural Biotechnology Division, National Institute for Biotechnology and Genetic Engineering (NIBGE), Constituent College Pakistan Institute of Engineering and Applied Sciences (PIEAS), Faisalabad, Pakistan
| |
Collapse
|
10
|
Liyanage DK, Torkamaneh D, Belzile F, Balasubramanian P, Hill B, Thilakarathna MS. The Genotypic Variability among Short-Season Soybean Cultivars for Nitrogen Fixation under Drought Stress. PLANTS (BASEL, SWITZERLAND) 2023; 12:1004. [PMID: 36903865 PMCID: PMC10005650 DOI: 10.3390/plants12051004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Revised: 02/16/2023] [Accepted: 02/20/2023] [Indexed: 06/18/2023]
Abstract
Soybean fixes atmospheric nitrogen through the symbiotic rhizobia bacteria that inhabit root nodules. Drought stress negatively affect symbiotic nitrogen fixation (SNF) in soybean. The main objective of this study was to identify allelic variations associated with SNF in short-season Canadian soybean varieties under drought stress. A diversity panel of 103 early-maturity Canadian soybean varieties was evaluated under greenhouse conditions to determine SNF-related traits under drought stress. Drought was imposed after three weeks of plant growth, where plants were maintained at 30% field capacity (FC) (drought) and 80% FC (well-watered) until seed maturity. Under drought stress, soybean plants had lower seed yield, yield components, seed nitrogen content, % nitrogen derived from the atmosphere (%Ndfa), and total seed nitrogen fixed compared to those under well-watered conditions. Significant genotypic variability among soybean varieties was found for yield, yield parameters, and nitrogen fixation traits. A genome-wide association study (GWAS) was conducted using 2.16 M single nucleotide single nucleotide polymorphisms (SNPs) for different yield and nitrogen fixation related parameters for 30% FC and their relative performance (30% FC/80% FC). In total, five quantitative trait locus (QTL) regions, including candidate genes, were detected as significantly associated with %Ndfa under drought stress and relative performance. These genes can potentially aid in future breeding efforts to develop drought-resistant soybean varieties.
Collapse
Affiliation(s)
- Dilrukshi Kombala Liyanage
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB T6G 2P5, Canada
| | - Davoud Torkamaneh
- Département de Phytologie, Université Laval, Québec City, QC G1V 0A6, Canada
- Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Québec City, QC G1V 0A6, Canada
| | - François Belzile
- Département de Phytologie, Université Laval, Québec City, QC G1V 0A6, Canada
- Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Québec City, QC G1V 0A6, Canada
| | - Parthiba Balasubramanian
- Agriculture and Agri-Food Canada, Lethbridge Research and Development Centre, Lethbridge, AB T1J 4B1, Canada
| | - Brett Hill
- Agriculture and Agri-Food Canada, Lethbridge Research and Development Centre, Lethbridge, AB T1J 4B1, Canada
| | - Malinda S. Thilakarathna
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB T6G 2P5, Canada
| |
Collapse
|
11
|
Ogrodowicz P, Mikołajczak K, Kempa M, Mokrzycka M, Krajewski P, Kuczyńska A. Genome-wide association study of agronomical and root-related traits in spring barley collection grown under field conditions. FRONTIERS IN PLANT SCIENCE 2023; 14:1077631. [PMID: 36760640 PMCID: PMC9902773 DOI: 10.3389/fpls.2023.1077631] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Accepted: 01/06/2023] [Indexed: 06/18/2023]
Abstract
The root system is a key component for plant survival and productivity. In particular, under stress conditions, developing plants with a better root architecture can ensure productivity. The objectives of this study were to investigate the phenotypic variation of selected root- and yield-related traits in a diverse panel of spring barley genotypes. By performing a genome-wide association study (GWAS), we identified several associations underlying the variations occurring in root- and yield-related traits in response to natural variations in soil moisture. Here, we report the results of the GWAS based on both individual single-nucleotide polymorphism markers and linkage disequilibrium (LD) blocks of markers for 11 phenotypic traits related to plant morphology, grain quality, and root system in a group of spring barley accessions grown under field conditions. We also evaluated the root structure of these accessions by using a nondestructive method based on electrical capacitance. The results showed the importance of two LD-based blocks on chromosomes 2H and 7H in the expression of root architecture and yield-related traits. Our results revealed the importance of the region on the short arm of chromosome 2H in the expression of root- and yield-related traits. This study emphasized the pleiotropic effect of this region with respect to heading time and other important agronomic traits, including root architecture. Furthermore, this investigation provides new insights into the roles played by root traits in the yield performance of barley plants grown under natural conditions with daily variations in soil moisture content.
Collapse
|
12
|
Saleem A, Roldán-Ruiz I, Aper J, Muylle H. Genetic control of tolerance to drought stress in soybean. BMC PLANT BIOLOGY 2022; 22:615. [PMID: 36575367 PMCID: PMC9795773 DOI: 10.1186/s12870-022-03996-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/03/2022] [Accepted: 12/12/2022] [Indexed: 06/17/2023]
Abstract
BACKGROUND Drought stress limits the production of soybean [Glycine max (L.) Merr.], which is the most grown high-value legume crop worldwide. Breeding for drought tolerance is a difficult endeavor and understanding the genetic basis of drought tolerance in soybean is therefore crucial for harnessing the genomic regions involved in the tolerance mechanisms. A genome-wide association study (GWAS) analysis was applied in a soybean germplasm collection (the EUCLEG collection) of 359 accessions relevant for breeding in Europe, to identify genomic regions and candidate genes involved in the response to short duration and long duration drought stress (SDS and LDS respectively) in soybean. RESULTS The phenotypic response to drought was stronger in the long duration drought (LDS) than in the short duration drought (SDS) experiment. Over the four traits considered (canopy wilting, leaf senescence, maximum absolute growth rate and maximum plant height) the variation was in the range of 8.4-25.2% in the SDS, and 14.7-29.7% in the LDS experiments. The GWAS analysis identified a total of 17 and 22 significant marker-trait associations for four traits in the SDS and LDS experiments, respectively. In the genomic regions delimited by these markers we identified a total of 12 and 16 genes with putative functions that are of particular relevance for drought stress responses including stomatal movement, root formation, photosynthesis, ABA signaling, cellular protection and cellular repair mechanisms. Some of these genomic regions co-localized with previously known QTLs for drought tolerance traits including water use efficiency, chlorophyll content and photosynthesis. CONCLUSION Our results indicate that the mechanism of slow wilting in the SDS might be associated with the characteristics of the root system, whereas in the LDS, slow wilting could be due to low stomatal conductance and transpiration rates enabling a high WUE. Drought-induced leaf senescence was found to be associated to ABA and ROS responses. The QTLs related to WUE contributed to growth rate and canopy height maintenance under drought stress. Co-localization of several previously known QTLs for multiple agronomic traits with the SNPs identified in this study, highlights the importance of the identified genomic regions for the improvement of agronomic performance in addition to drought tolerance in the EUCLEG collection.
Collapse
Affiliation(s)
- Aamir Saleem
- Flanders Research Institute for Agriculture, Fisheries and Food (ILVO), Plant Sciences Unit, Caritasstraat 39, 9090, Melle, Belgium
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Technologiepark 927, 9052, Ghent, Belgium
| | - Isabel Roldán-Ruiz
- Flanders Research Institute for Agriculture, Fisheries and Food (ILVO), Plant Sciences Unit, Caritasstraat 39, 9090, Melle, Belgium
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Technologiepark 927, 9052, Ghent, Belgium
| | - Jonas Aper
- Protealis, Technologiepark-Zwijnaarde, Ghent, Belgium
| | - Hilde Muylle
- Flanders Research Institute for Agriculture, Fisheries and Food (ILVO), Plant Sciences Unit, Caritasstraat 39, 9090, Melle, Belgium.
| |
Collapse
|
13
|
Yoosefzadeh-Najafabadi M, Rajcan I, Eskandari M. Optimizing genomic selection in soybean: An important improvement in agricultural genomics. Heliyon 2022; 8:e11873. [PMID: 36468106 PMCID: PMC9713349 DOI: 10.1016/j.heliyon.2022.e11873] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Revised: 09/26/2022] [Accepted: 11/17/2022] [Indexed: 11/27/2022] Open
Abstract
Fast-paced yield improvement in strategic crops such as soybean is pivotal for achieving sustainable global food security. Precise genomic selection (GS), as one of the most effective genomic tools for recognizing superior genotypes, can accelerate the efficiency of breeding programs through shortening the breeding cycle, resulting in significant increases in annual yield improvement. In this study, we investigated the possible use of haplotype-based GS to increase the prediction accuracy of soybean yield and its component traits through augmenting the models by using sophisticated machine learning algorithms and optimized genetic information. The results demonstrated up to a 7% increase in the prediction accuracy when using haplotype-based GS over the full single nucleotide polymorphisms-based GS methods. In addition, we discover an auspicious haplotype block on chromosome 19 with significant impacts on yield and its components, which can be used for screening climate-resilient soybean genotypes with improved yield in large breeding populations.
Collapse
Affiliation(s)
| | - Istvan Rajcan
- Department of Plant Agriculture, University of Guelph, Guelph, ON N1G 2W1, Canada
| | - Milad Eskandari
- Department of Plant Agriculture, University of Guelph, Guelph, ON N1G 2W1, Canada
| |
Collapse
|
14
|
Kim DG, Lyu JI, Kim JM, Seo JS, Choi HI, Jo YD, Kim SH, Eom SH, Ahn JW, Bae CH, Kwon SJ. Identification of Loci Governing Agronomic Traits and Mutation Hotspots via a GBS-Based Genome-Wide Association Study in a Soybean Mutant Diversity Pool. Int J Mol Sci 2022; 23:10441. [PMID: 36142354 PMCID: PMC9499481 DOI: 10.3390/ijms231810441] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Revised: 09/05/2022] [Accepted: 09/07/2022] [Indexed: 11/25/2022] Open
Abstract
In this study, we performed a genotyping-by-sequencing analysis and a genome-wide association study of a soybean mutant diversity pool previously constructed by gamma irradiation. A GWAS was conducted to detect significant associations between 37,249 SNPs, 11 agronomic traits, and 6 phytochemical traits. In the merged data set, 66 SNPs on 13 chromosomes were highly associated (FDR p < 0.05) with the following 4 agronomic traits: days of flowering (33 SNPs), flower color (16 SNPs), node number (6 SNPs), and seed coat color (11 SNPs). These results are consistent with the findings of earlier studies on other genetic features (e.g., natural accessions and recombinant inbred lines). Therefore, our observations suggest that the genomic changes in the mutants generated by gamma irradiation occurred at the same loci as the mutations in the natural soybean population. These findings are indicative of the existence of mutation hotspots, or the acceleration of genome evolution in response to high doses of radiation. Moreover, this study demonstrated that the integration of GBS and GWAS to investigate a mutant population derived from gamma irradiation is suitable for dissecting the molecular basis of complex traits in soybeans.
Collapse
Affiliation(s)
- Dong-Gun Kim
- Advanced Radiation Technology Institute, Korea Atomic Energy Research Institute, Jeongup 56212, Korea
| | - Jae Il Lyu
- Advanced Radiation Technology Institute, Korea Atomic Energy Research Institute, Jeongup 56212, Korea
- Research Center of Crop Breeding for Omics and Artificial Intelligence, Kongju National University, Yesan 32439, Korea
| | - Jung Min Kim
- Advanced Radiation Technology Institute, Korea Atomic Energy Research Institute, Jeongup 56212, Korea
| | - Ji Su Seo
- Advanced Radiation Technology Institute, Korea Atomic Energy Research Institute, Jeongup 56212, Korea
| | - Hong-Il Choi
- Advanced Radiation Technology Institute, Korea Atomic Energy Research Institute, Jeongup 56212, Korea
| | - Yeong Deuk Jo
- Department of Horticultural Science, Chungnam National University, Daejeon 34134, Korea
| | - Sang Hoon Kim
- Advanced Radiation Technology Institute, Korea Atomic Energy Research Institute, Jeongup 56212, Korea
| | - Seok Hyun Eom
- Department of Horticultural Biotechnology, Institute of Life Sciences & Resources, Kyung Hee University, Yongin 17104, Korea
| | - Joon-Woo Ahn
- Advanced Radiation Technology Institute, Korea Atomic Energy Research Institute, Jeongup 56212, Korea
| | - Chang-Hyu Bae
- Department of Life Resources, Graduate School, Sunchon National University, Suncheon 57922, Korea
| | - Soon-Jae Kwon
- Advanced Radiation Technology Institute, Korea Atomic Energy Research Institute, Jeongup 56212, Korea
| |
Collapse
|
15
|
Bhat JA, Karikari B, Adeboye KA, Ganie SA, Barmukh R, Hu D, Varshney RK, Yu D. Identification of superior haplotypes in a diverse natural population for breeding desirable plant height in soybean. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2022; 135:2407-2422. [PMID: 35639109 PMCID: PMC9271120 DOI: 10.1007/s00122-022-04120-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/13/2022] [Accepted: 04/28/2022] [Indexed: 06/14/2023]
Abstract
KEY MESSAGE Plant height of soybean is associated with a haplotype block on chromosome 19, which classified 211 soybean accessions into five distinct groups showing significant differences for the target trait. Genetic variation is pivotal for crop improvement. Natural populations are precious genetic resources. However, efficient strategies for the targeted utilization of these resources for quantitative traits, such as plant height (PH), are scarce. Being an important agronomic trait associated with soybean yield and quality, it is imperative to unravel the genetic mechanisms underlying PH in soybean. Here, a genome-wide association study (GWAS) was performed to identify single nucleotide polymorphisms (SNPs) significantly associated with PH in a natural population of 211 cultivated soybeans, which was genotyped with NJAU 355 K Soy SNP Array and evaluated across six environments. A total of 128 SNPs distributed across 17 chromosomes were found to be significantly associated with PH across six environments and a combined environment. Three significant SNPs were consistently identified in at least three environments on Chr.02 (AX-93958260), Chr.17 (AX-94154834), and Chr.19 (AX-93897200). Genomic regions of ~ 130 kb flanking these three consistent SNPs were considered as stable QTLs, which included 169 genes. Of these, 22 genes (including Dt1) were prioritized and defined as putative candidates controlling PH. The genomic region flanking 12 most significant SNPs was in strong linkage disequilibrium (LD). These SNPs formed a single haplotype block containing five haplotypes for PH, namely Hap-A, Hap-B, Hap-C, Hap-D, and Hap-E. Deployment of such superior haplotypes in breeding programs will enable development of improved soybean varieties with desirable plant height.
Collapse
Affiliation(s)
- Javaid Akhter Bhat
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, National Center for Soybean Improvement, Nanjing Agricultural University, Nanjing, 210095, China.
- International Genome Center, Jiangsu University, Zhenjiang, 212013, China.
| | - Benjamin Karikari
- Department of Crop Science, Faculty of Agriculture, Food and Consumer Sciences, University for Development Studies, Tamale, Ghana
| | - Kehinde Adewole Adeboye
- Department of Agricultural Technology, Ekiti State Polytechnic, P. M. B. 1101, Isan, Nigeria
| | - Showkat Ahmad Ganie
- Department of Plant Science and Landscape Architecture, University of Connecticut, Storrs, USA
| | - Rutwik Barmukh
- Center of Excellence in Genomics and Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, 502324, India
| | - Dezhou Hu
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, National Center for Soybean Improvement, Nanjing Agricultural University, Nanjing, 210095, China
| | - Rajeev K Varshney
- Center of Excellence in Genomics and Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, 502324, India.
- Murdoch's Centre for Crop and Food Innovation, State Agricultural Biotechnology Centre, Food Futures Institute, Murdoch University, Murdoch, WA, Australia.
| | - Deyue Yu
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, National Center for Soybean Improvement, Nanjing Agricultural University, Nanjing, 210095, China.
| |
Collapse
|
16
|
Maldonado Dos Santos JV, Sant'Ana GC, Wysmierski PT, Todeschini MH, Garcia A, Meda AR. Genetic relationships and genome selection signatures between soybean cultivars from Brazil and United States after decades of breeding. Sci Rep 2022; 12:10663. [PMID: 35739190 PMCID: PMC9226155 DOI: 10.1038/s41598-022-15022-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2021] [Accepted: 06/16/2022] [Indexed: 11/21/2022] Open
Abstract
Soybean is one of the most important crops worldwide. Brazil and the United States (US) are the world's two biggest producers of this legume. The increase of publicly available DNA sequencing data as well as high-density genotyping data of multiple soybean germplasms has made it possible to understand the genetic relationships and identify genomics regions that underwent selection pressure during soy domestication and breeding. In this study, we analyzed the genetic relationships between Brazilian (N = 235) and US soybean cultivars (N = 675) released in different decades and screened for genomic signatures between Brazilian and US cultivars. The population structure analysis demonstrated that the Brazilian germplasm has a narrower genetic base than the US germplasm. The US cultivars were grouped according to maturity groups, while Brazilian cultivars were separated according to decade of release. We found 73 SNPs that differentiate Brazilian and US soybean germplasm. Maturity-associated SNPs showed high allelic frequency differences between Brazilian and US accessions. Other important loci were identified separating cultivars released before and after 1996 in Brazil. Our data showed important genomic regions under selection during decades of soybean breeding in Brazil and the US that should be targeted to adapt lines from different origins in these countries.
Collapse
Affiliation(s)
| | | | | | | | - Alexandre Garcia
- Tropical Melhoramento & Genética (TMG), 87 Celso Garcia Road, Cambe, PR, Brazil
| | | |
Collapse
|
17
|
Yoosefzadeh-Najafabadi M, Eskandari M, Torabi S, Torkamaneh D, Tulpan D, Rajcan I. Machine-Learning-Based Genome-Wide Association Studies for Uncovering QTL Underlying Soybean Yield and Its Components. Int J Mol Sci 2022; 23:5538. [PMID: 35628351 PMCID: PMC9141736 DOI: 10.3390/ijms23105538] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2022] [Revised: 05/11/2022] [Accepted: 05/13/2022] [Indexed: 12/14/2022] Open
Abstract
A genome-wide association study (GWAS) is currently one of the most recommended approaches for discovering marker-trait associations (MTAs) for complex traits in plant species. Insufficient statistical power is a limiting factor, especially in narrow genetic basis species, that conventional GWAS methods are suffering from. Using sophisticated mathematical methods such as machine learning (ML) algorithms may address this issue and advance the implication of this valuable genetic method in applied plant-breeding programs. In this study, we evaluated the potential use of two ML algorithms, support-vector machine (SVR) and random forest (RF), in a GWAS and compared them with two conventional methods of mixed linear models (MLM) and fixed and random model circulating probability unification (FarmCPU), for identifying MTAs for soybean-yield components. In this study, important soybean-yield component traits, including the number of reproductive nodes (RNP), non-reproductive nodes (NRNP), total nodes (NP), and total pods (PP) per plant along with yield and maturity, were assessed using a panel of 227 soybean genotypes evaluated at two locations over two years (four environments). Using the SVR-mediated GWAS method, we were able to discover MTAs colocalized with previously reported quantitative trait loci (QTL) with potential causal effects on the target traits, supported by the functional annotation of candidate gene analyses. This study demonstrated the potential benefit of using sophisticated mathematical approaches, such as SVR, in a GWAS to complement conventional GWAS methods for identifying MTAs that can improve the efficiency of genomic-based soybean-breeding programs.
Collapse
Affiliation(s)
| | - Milad Eskandari
- Department of Plant Agriculture, University of Guelph, Guelph, ON N1G 2W1, Canada; (M.Y.-N.); (S.T.); (I.R.)
| | - Sepideh Torabi
- Department of Plant Agriculture, University of Guelph, Guelph, ON N1G 2W1, Canada; (M.Y.-N.); (S.T.); (I.R.)
| | - Davoud Torkamaneh
- Département de Phytologie, Université Laval, Québec City, QC G1V 0A6, Canada;
| | - Dan Tulpan
- Department of Animal Biosciences, University of Guelph, Guelph, ON N1G 2W1, Canada;
| | - Istvan Rajcan
- Department of Plant Agriculture, University of Guelph, Guelph, ON N1G 2W1, Canada; (M.Y.-N.); (S.T.); (I.R.)
| |
Collapse
|
18
|
Li H, Ikram M, Xia Y, Li R, Yuan Q, Zhao W, Siddique KHM, Guo P. Genome-wide identification and development of InDel markers in tobacco ( Nicotiana tabacum L.) using RAD-seq. PHYSIOLOGY AND MOLECULAR BIOLOGY OF PLANTS : AN INTERNATIONAL JOURNAL OF FUNCTIONAL PLANT BIOLOGY 2022; 28:1077-1089. [PMID: 35722506 PMCID: PMC9203652 DOI: 10.1007/s12298-022-01187-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/06/2022] [Revised: 05/16/2022] [Accepted: 05/17/2022] [Indexed: 05/03/2023]
Abstract
Insertions and deletions (InDels) can be used as molecular markers in genetic studies and marker-assisted selection breeding. However, genetic improvement in tobacco has been hindered by limited genetic diversity information and relatedness within available germplasm. A Chinese tobacco variety, Yueyan-98, was resequenced using restriction-site associated DNA (RAD-seq) approach to develop InDel markers. In total, 32,884 InDel loci were detected between Yueyan-98 and the K326 reference sequence [18,598 (56.55%) deletions and 14,288 (43.45%) insertions], ranging from 1 to 62 bp in length. Of the 6,733 InDels (> 4 bp) that were suitable for polyacrylamide gel electrophoresis, 150 were randomly selected. These 150 InDels were unevenly distributed on 23 chromosomes, and the highest numbers of InDels were observed on chromosomes Nt05, Nt13, and Nt23. The average density of adjacent InDels was 19.36 Mb. Thirty-seven InDels were located in genic regions. Polymerase chain reaction (PCR)-based markers were developed to validate polymorphism; 113 (79.80%) of the 150 InDel markers showed polymorphism and were further used for genetic diversity analysis of 50 tobacco accessions (13 from China, 1 from Mexico, and 36 from the USA). The average expected heterozygosity (He) and polymorphism information content (PIC) values were 0.28 ± 0.16 and 0.38 ± 0.10, respectively. The average Shannon diversity index (I) was 0.34 ± 0.18, with genetic diversity ranging from 0.13-0.57. The 50 accessions were classified into two groups with a genetic similarity coefficient of 0.68. Principal coordinate analysis (PCoA) and population structure analysis showed similar results and divided the population into two groups unrelated to their geographical origins. AMOVA showed 4% variance among the population and the remaining 96% within the population, suggesting low genetic differentiation between two subpopulations. Furthermore, 10 InDels (19 alleles) were significantly identified for tobacco plant height using GLM+Q model at P < 0.005. Among these, three markers (Nt-I-26, Nt-I-41, and Nt-I-44) were detected in at least two environments, with phenotypic variance explained (PVE) ranging from 14.03 to 32.68%. The polymorphic InDel markers developed can be used for hybrid identification, genetic diversity, genetic linkage map construction, gene mapping, and MAS breeding programs of tobacco. Supplementary Information The online version contains supplementary material available at 10.1007/s12298-022-01187-3.
Collapse
Affiliation(s)
- Haiyang Li
- Guangdong Provincial Key Laboratory of Plant Adaptation and Molecular Design, International Crop Research Center for Stress Resistance, School of Life Sciences, Guangzhou University, Guangzhou, 510006 China
| | - Muhammad Ikram
- Guangdong Provincial Key Laboratory of Plant Adaptation and Molecular Design, International Crop Research Center for Stress Resistance, School of Life Sciences, Guangzhou University, Guangzhou, 510006 China
| | - Yanshi Xia
- Guangdong Provincial Key Laboratory of Plant Adaptation and Molecular Design, International Crop Research Center for Stress Resistance, School of Life Sciences, Guangzhou University, Guangzhou, 510006 China
| | - Ronghua Li
- Guangdong Provincial Key Laboratory of Plant Adaptation and Molecular Design, International Crop Research Center for Stress Resistance, School of Life Sciences, Guangzhou University, Guangzhou, 510006 China
| | - Qinghua Yuan
- Guangdong Provincial Engineering & Technology Research Center for Tobacco Breeding and Comprehensive Utilization, Guangdong Key Laboratory for Crops Genetic Improvement, Crops Research Institute, Guangdong Academy of Agricultural Sciences (GAAS), Guangzhou, 510640 China
| | - Weicai Zhao
- Nanxiong Research Institutes of Guangdong Tobacco Co. Ltd, Nanxiong, 512400 China
| | - Kadambot H. M. Siddique
- The UWA Institute of Agriculture and School of Agriculture & Environment, The University of Western Australia, Perth, WA 6001 Australia
| | - Peiguo Guo
- Guangdong Provincial Key Laboratory of Plant Adaptation and Molecular Design, International Crop Research Center for Stress Resistance, School of Life Sciences, Guangzhou University, Guangzhou, 510006 China
| |
Collapse
|
19
|
Ficht A, Bruce R, Torkamaneh D, Grainger CM, Eskandari M, Rajcan I. Genetic analysis of sucrose concentration in soybean seeds using a historical soybean genomic panel. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2022; 135:1375-1383. [PMID: 35112143 DOI: 10.1007/s00122-022-04040-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Accepted: 01/12/2022] [Indexed: 06/14/2023]
Abstract
KEY MESSAGE Significant QTL for sucrose concentration have been identified using a historical soybean genomic panel, which could aid in the development of food-grade soybean cultivars. Soybean (Glycine max (L.) Merr) is a crop of global importance for both human and animal consumption, which was domesticated in China more than 6000 years ago. A concern about losing genetic diversity as a result of decades of breeding has been expressed by soybean researchers. In order to develop new cultivars, it is critical for breeders to understand the genetic variability present for traits of interest in their program germplasm. Sucrose concentration is becoming an increasingly important trait for the production of soy-food products. The objective of this study was to use a genome-wide association study (GWAS) to identify putative QTL for sucrose concentration in soybean seed. A GWAS panel consisting of 266 historic and current soybean accessions was genotyped with 76 k genotype-by-sequencing (GBS) SNP data and phenotyped in four field locations in Ontario (Canada) from 2015 to 2017. Seven putative QTL were identified on chromosomes 1, 6, 8, 9, 10, 13 and 14. A key gene related to sucrose synthase (Glyma.06g182700) was found to be associated with the QTL located on chromosome 6. This information will facilitate efforts to increase the available genetic variability for sucrose concentration in soybean breeding programs and develop new and improved high-sucrose soybean cultivars suitable for the soy-food industry.
Collapse
Affiliation(s)
- Alexandra Ficht
- Department of Plant Agriculture, University of Guelph, 50 Stone Road East, Guelph, ON, N1G 2W1, Canada
| | - Robert Bruce
- Department of Plant Agriculture, University of Guelph, 50 Stone Road East, Guelph, ON, N1G 2W1, Canada
| | - Davoud Torkamaneh
- Department of Plant Agriculture, University of Guelph, 50 Stone Road East, Guelph, ON, N1G 2W1, Canada
| | - Christopher M Grainger
- Department of Plant Agriculture, University of Guelph, 50 Stone Road East, Guelph, ON, N1G 2W1, Canada
| | - Milad Eskandari
- Department of Plant Agriculture, University of Guelph, 50 Stone Road East, Guelph, ON, N1G 2W1, Canada
| | - Istvan Rajcan
- Department of Plant Agriculture, University of Guelph, 50 Stone Road East, Guelph, ON, N1G 2W1, Canada.
| |
Collapse
|
20
|
Ballesta P, Ahmar S, Lobos GA, Mieres-Castro D, Jiménez-Aspee F, Mora-Poblete F. Heritable Variation of Foliar Spectral Reflectance Enhances Genomic Prediction of Hydrogen Cyanide in a Genetically Structured Population of Eucalyptus. FRONTIERS IN PLANT SCIENCE 2022; 13:871943. [PMID: 35432412 PMCID: PMC9008590 DOI: 10.3389/fpls.2022.871943] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Accepted: 03/01/2022] [Indexed: 06/14/2023]
Abstract
Plants produce a wide diversity of specialized metabolites, which fulfill a wide range of biological functions, helping plants to interact with biotic and abiotic factors. In this study, an integrated approach based on high-throughput plant phenotyping, genome-wide haplotypes, and pedigree information was performed to examine the extent of heritable variation of foliar spectral reflectance and to predict the leaf hydrogen cyanide content in a genetically structured population of a cyanogenic eucalyptus (Eucalyptus cladocalyx F. Muell). In addition, the heritable variation (based on pedigree and genomic data) of more of 100 common spectral reflectance indices was examined. The first profile of heritable variation along the spectral reflectance curve indicated the highest estimate of genomic heritability ( h g 2 =0.41) within the visible region of the spectrum, suggesting that several physiological and biological responses of trees to environmental stimuli (ex., light) are under moderate genetic control. The spectral reflectance index with the highest genomic-based heritability was leaf rust disease severity index 1 ( h g 2 =0.58), followed by the anthocyanin reflectance index and the Browning reflectance index ( h g 2 =0.54). Among the Bayesian prediction models based on spectral reflectance data, Bayes B had a better goodness of fit than the Bayes-C and Bayesian ridge regression models (in terms of the deviance information criterion). All models that included spectral reflectance data outperformed conventional genomic prediction models in their predictive ability and goodness-of-fit measures. Finally, we confirmed the proposed hypothesis that high-throughput phenotyping indirectly capture endophenotypic variants related to specialized metabolites (defense chemistry), and therefore, generally more accurate predictions can be made integrating phenomics and genomics.
Collapse
Affiliation(s)
- Paulina Ballesta
- The National Fund for Scientific and Technological Development, Talca, Chile
| | - Sunny Ahmar
- The National Fund for Scientific and Technological Development, Talca, Chile
| | - Gustavo A. Lobos
- Plant Breeding and Phenomic Center, Faculty of Agricultural Sciences, Universidad de Talca, Talca, Chile
| | | | - Felipe Jiménez-Aspee
- Department of Food Biofunctionality, Institute of Nutritional Sciences, University of Hohenheim, Stuttgart, Germany
| | | |
Collapse
|
21
|
Singh N, Rawal HC, Angadi UB, Sharma TR, Singh NK, Mondal TK. A first-generation haplotype map (HapMap-1) of tea (Camellia sinensis L. O. Kuntz). Bioinformatics 2022; 38:318-324. [PMID: 34601584 DOI: 10.1093/bioinformatics/btab690] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2021] [Revised: 08/30/2021] [Accepted: 09/29/2021] [Indexed: 02/03/2023] Open
Abstract
MOTIVATION Tea is a cross-pollinated woody perennial plant, which is why, application of conventional breeding is limited for its genetic improvement. However, lack of the genome-wide high-density SNP markers and genome-wide haplotype information has greatly hampered the utilization of tea genetic resources toward fast-track tea breeding programs. To address this challenge, we have generated a first-generation haplotype map of tea (Tea HapMap-1). Out-crossing and highly heterozygous nature of tea plants, make them more complicated for DNA-level variant discovery. RESULTS In this study, whole genome re-sequencing data of 369 tea genotypes were used to generate 2,334,564 biallelic SNPs and 1,447,985 InDels. Around 2928.04 million paired-end reads were used with an average mapping depth of ∼0.31× per accession. Identified polymorphic sites in this study will be useful in mapping the genomic regions responsible for important traits of tea. These resources lay the foundation for future research to understand the genetic diversity within tea germplasm and utilize genes that determine tea quality. This will further facilitate the understanding of tea genome evolution and tea metabolite pathways thus, offers an effective germplasm utilization for breeding the tea varieties. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Collapse
Affiliation(s)
- Nisha Singh
- ICAR-National Institute for Plant Biotechnology, LBS Building, Pusa campus, New Delhi 110012, India
| | - Hukam C Rawal
- ICAR-National Institute for Plant Biotechnology, LBS Building, Pusa campus, New Delhi 110012, India
| | - Ulavappa B Angadi
- ICAR-Indian Agricultural Statistics Research Institute, New Delhi 110012, India
| | - Tilak Raj Sharma
- ICAR-National Institute for Plant Biotechnology, LBS Building, Pusa campus, New Delhi 110012, India
| | - Nagendra Kumar Singh
- ICAR-National Institute for Plant Biotechnology, LBS Building, Pusa campus, New Delhi 110012, India
| | - Tapan Kumar Mondal
- ICAR-National Institute for Plant Biotechnology, LBS Building, Pusa campus, New Delhi 110012, India
| |
Collapse
|
22
|
Priyanatha C, Torkamaneh D, Rajcan I. Genome-Wide Association Study of Soybean Germplasm Derived From Canadian × Chinese Crosses to Mine for Novel Alleles to Improve Seed Yield and Seed Quality Traits. FRONTIERS IN PLANT SCIENCE 2022; 13:866300. [PMID: 35419011 PMCID: PMC8996715 DOI: 10.3389/fpls.2022.866300] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Accepted: 03/04/2022] [Indexed: 05/16/2023]
Abstract
Genome-wide association study (GWAS) has emerged in the past decade as a viable tool for identifying beneficial alleles from a genomic diversity panel. In an ongoing effort to improve soybean [Glycine max (L.) Merr.], which is the third largest field crop in Canada, a GWAS was conducted to identify novel alleles underlying seed yield and seed quality and agronomic traits. The genomic panel consisted of 200 genotypes including lines derived from several generations of bi-parental crosses between modern Canadian × Chinese cultivars (CD-CH). The genomic diversity panel was field evaluated at two field locations in Ontario in 2019 and 2020. Genotyping-by-sequencing (GBS) was conducted and yielded almost 32 K high-quality SNPs. GWAS was conducted using Fixed and random model Circulating Probability Unification (FarmCPU) model on the following traits: seed yield, seed protein concentration, seed oil concentration, plant height, 100 seed weight, days to maturity, and lodging score that allowed to identify five QTL regions controlling seed yield and seed oil and protein content. A candidate gene search identified a putative gene for each of the three traits. The results of this GWAS study provide insight into potentially valuable genetic resources residing in Chinese modern cultivars that breeders may use to further improve soybean seed yield and seed quality traits.
Collapse
Affiliation(s)
| | - Davoud Torkamaneh
- Département de Phytologie, Université Laval, Québec, QC, Canada
- Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Québec, QC, Canada
| | - Istvan Rajcan
- Department of Plant Agriculture, University of Guelph, Guelph, ON, Canada
- *Correspondence: Istvan Rajcan,
| |
Collapse
|
23
|
Raman R, Warren A, Krysinska-Kaczmarek M, Rohan M, Sharma N, Dron N, Davidson J, Moore K, Hobson K. Genome-Wide Association Analyses Track Genomic Regions for Resistance to Ascochyta rabiei in Australian Chickpea Breeding Germplasm. FRONTIERS IN PLANT SCIENCE 2022; 13:877266. [PMID: 35665159 PMCID: PMC9159299 DOI: 10.3389/fpls.2022.877266] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Accepted: 04/08/2022] [Indexed: 05/05/2023]
Abstract
Ascochyta blight (AB), caused by a necrotrophic fungus, Ascochyta rabiei (syn. Phoma rabiei) has the potential to destroy the chickpea industry worldwide, due to limited sources of genetic resistance in the cultivated gene pool, high evolutionary potential of the pathogen and challenges with integrated disease management. Therefore, the deployment of stable genetic resistance in new cultivars could provide an effective disease control strategy. To investigate the genetic basis of AB resistance, genotyping-by-sequencing based DArTseq-single nucleotide polymorphism (SNP) marker data along with phenotypic data of 251 advanced breeding lines and chickpea cultivars were used to perform genome-wide association (GWAS) analysis. Host resistance was evaluated seven weeks after sowing using two highly aggressive single spore isolates (F17191-1 and TR9571) of A. rabiei. GWAS analyses based on single-locus and multi-locus mixed models and haplotyping trend regression identified twenty-six genomic regions on Ca1, Ca4, and Ca6 that showed significant association with resistance to AB. Two haplotype blocks (HB) on chromosome Ca1; HB5 (992178-1108145 bp), and HB8 (1886221-1976301 bp) were associated with resistance against both isolates. Nine HB on the chromosome, Ca4, spanning a large genomic region (14.9-56.6 Mbp) were also associated with resistance, confirming the role of this chromosome in providing resistance to AB. Furthermore, trait-marker associations in two F3 derived populations for resistance to TR9571 isolate at the seedling stage under glasshouse conditions were also validated. Eighty-nine significantly associated SNPs were located within candidate genes, including genes encoding for serine/threonine-protein kinase, Myb protein, quinone oxidoreductase, and calmodulin-binding protein all of which are implicated in disease resistance. Taken together, this study identifies valuable sources of genetic resistance, SNP markers and candidate genes underlying genomic regions associated with AB resistance which may enable chickpea breeding programs to make genetic gains via marker-assisted/genomic selection strategies.
Collapse
Affiliation(s)
- Rosy Raman
- NSW Department of Primary Industries, Wagga Wagga Agricultural Institute, Wagga Wagga, NSW, Australia
- *Correspondence: Rosy Raman,
| | - Annie Warren
- NSW Department of Primary Industries, Tamworth Agricultural Institute, Tamworth, NSW, Australia
| | | | - Maheswaran Rohan
- NSW Department of Primary Industries, Wagga Wagga Agricultural Institute, Wagga Wagga, NSW, Australia
| | - Niharika Sharma
- NSW Department of Primary Industries, Orange Agricultural Institute, Orange, NSW, Australia
| | - Nicole Dron
- NSW Department of Primary Industries, Tamworth Agricultural Institute, Tamworth, NSW, Australia
| | - Jenny Davidson
- South Australian Research and Development Institute, Urrbrae, SA, Australia
| | - Kevin Moore
- NSW Department of Primary Industries, Tamworth Agricultural Institute, Tamworth, NSW, Australia
| | - Kristy Hobson
- NSW Department of Primary Industries, Tamworth Agricultural Institute, Tamworth, NSW, Australia
| |
Collapse
|
24
|
Gu X, Huang S, Zhu Z, Ma Y, Yang X, Yao L, Gao X, Zhang M, Liu W, Qiu L, Zhao H, Wang Q, Li Z, Li Z, Meng Q, Yang S, Wang C, Hu X, Ding J. Genome-wide association of single nucleotide polymorphism loci and candidate genes for frogeye leaf spot (Cercospora sojina) resistance in soybean. BMC PLANT BIOLOGY 2021; 21:588. [PMID: 34895144 PMCID: PMC8665500 DOI: 10.1186/s12870-021-03366-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/27/2021] [Accepted: 11/25/2021] [Indexed: 06/14/2023]
Abstract
BACKGROUND Frogeye leaf spot (FLS) is a destructive fungal disease that affects soybean production. The most economical and effective strategy to control FLS is the use of resistant cultivars. However, the use of a limited number of resistant loci in FLS management will be countered by the emergence of new high-virulence Cercospora sojina races. Therefore, we identified quantitative trait loci (QTL) that control resistance to FLS and identified novel resistant genes using a genome-wide association study (GWAS) on 234 Chinese soybean cultivars. RESULTS A total of 30,890 single nucleotide polymorphism (SNP) markers were used to estimate linkage disequilibrium (LD) and population structure. The GWAS results showed four loci (p < 0.0001) distributed over chromosomes (Chr.) 5 and 20, that are significantly associated with FLS resistance. No previous studies have reported resistance loci in these regions. Subsequently, 45 genes in the two resistance-related haplotype blocks were annotated. Among them, Glyma20g31630 encoding pyruvate dehydrogenase (PDH), Glyma05g28980, which encodes mitogen-activated protein kinase 7 (MPK7), and Glyma20g31510, Glyma20g31520 encoding calcium-dependent protein kinase 4 (CDPK4) in the haplotype blocks deserves special attention. CONCLUSIONS This study showed that GWAS can be employed as an effective strategy for identifying disease resistance traits in soybean and narrowing SNPs and candidate genes. The prediction of candidate genes in the haplotype blocks identified by disease resistance loci can provide a useful reference to study systemic disease resistance.
Collapse
Affiliation(s)
- Xin Gu
- Wuhu Institute of Technology, Wuhu, 241003, China
- Jiamusi Branch of Heilongjiang Academy of Agricultural Sciences, Ministry of Agriculture Harmful Biology of Crop Scientific Monitoring Station Jiamusi Experiment Station, China Agriculture Research System of MOF and MARA, Jiamusi, 154007, China
| | - Shanshan Huang
- Key Laboratory of Crop Biotechnology Breeding of the Ministry of Agriculture, Beidahuang Kenfeng Seed Co., Ltd., Harbin, 150030, China
| | - Zhiguo Zhu
- Wuhu Institute of Technology, Wuhu, 241003, China
| | - Yansong Ma
- Key Laboratory of Crop Biotechnology Breeding of the Ministry of Agriculture, Beidahuang Kenfeng Seed Co., Ltd., Harbin, 150030, China
| | - Xiaohe Yang
- Jiamusi Branch of Heilongjiang Academy of Agricultural Sciences, Ministry of Agriculture Harmful Biology of Crop Scientific Monitoring Station Jiamusi Experiment Station, China Agriculture Research System of MOF and MARA, Jiamusi, 154007, China
| | - Liangliang Yao
- Jiamusi Branch of Heilongjiang Academy of Agricultural Sciences, Ministry of Agriculture Harmful Biology of Crop Scientific Monitoring Station Jiamusi Experiment Station, China Agriculture Research System of MOF and MARA, Jiamusi, 154007, China
| | - Xuedong Gao
- Jiamusi Branch of Heilongjiang Academy of Agricultural Sciences, Ministry of Agriculture Harmful Biology of Crop Scientific Monitoring Station Jiamusi Experiment Station, China Agriculture Research System of MOF and MARA, Jiamusi, 154007, China
| | - Maoming Zhang
- Jiamusi Branch of Heilongjiang Academy of Agricultural Sciences, Ministry of Agriculture Harmful Biology of Crop Scientific Monitoring Station Jiamusi Experiment Station, China Agriculture Research System of MOF and MARA, Jiamusi, 154007, China
| | - Wei Liu
- Jiamusi Branch of Heilongjiang Academy of Agricultural Sciences, Ministry of Agriculture Harmful Biology of Crop Scientific Monitoring Station Jiamusi Experiment Station, China Agriculture Research System of MOF and MARA, Jiamusi, 154007, China
| | - Lei Qiu
- Jiamusi Branch of Heilongjiang Academy of Agricultural Sciences, Ministry of Agriculture Harmful Biology of Crop Scientific Monitoring Station Jiamusi Experiment Station, China Agriculture Research System of MOF and MARA, Jiamusi, 154007, China
| | - Haihong Zhao
- Jiamusi Branch of Heilongjiang Academy of Agricultural Sciences, Ministry of Agriculture Harmful Biology of Crop Scientific Monitoring Station Jiamusi Experiment Station, China Agriculture Research System of MOF and MARA, Jiamusi, 154007, China
| | - Qingsheng Wang
- Jiamusi Branch of Heilongjiang Academy of Agricultural Sciences, Ministry of Agriculture Harmful Biology of Crop Scientific Monitoring Station Jiamusi Experiment Station, China Agriculture Research System of MOF and MARA, Jiamusi, 154007, China
| | - Zengjie Li
- Jiamusi Branch of Heilongjiang Academy of Agricultural Sciences, Ministry of Agriculture Harmful Biology of Crop Scientific Monitoring Station Jiamusi Experiment Station, China Agriculture Research System of MOF and MARA, Jiamusi, 154007, China
| | - Zhimin Li
- Jiamusi Branch of Heilongjiang Academy of Agricultural Sciences, Ministry of Agriculture Harmful Biology of Crop Scientific Monitoring Station Jiamusi Experiment Station, China Agriculture Research System of MOF and MARA, Jiamusi, 154007, China
| | - Qingying Meng
- Jiamusi Branch of Heilongjiang Academy of Agricultural Sciences, Ministry of Agriculture Harmful Biology of Crop Scientific Monitoring Station Jiamusi Experiment Station, China Agriculture Research System of MOF and MARA, Jiamusi, 154007, China
| | - Shuai Yang
- Potato Research Institute, Heilongjiang Academy of Agricultural Sciences, Harbin, 150086, China
| | - Chao Wang
- Key Laboratory of Crop Biotechnology Breeding of the Ministry of Agriculture, Beidahuang Kenfeng Seed Co., Ltd., Harbin, 150030, China
| | - Xiping Hu
- Key Laboratory of Crop Biotechnology Breeding of the Ministry of Agriculture, Beidahuang Kenfeng Seed Co., Ltd., Harbin, 150030, China.
| | - Junjie Ding
- Jiamusi Branch of Heilongjiang Academy of Agricultural Sciences, Ministry of Agriculture Harmful Biology of Crop Scientific Monitoring Station Jiamusi Experiment Station, China Agriculture Research System of MOF and MARA, Jiamusi, 154007, China.
| |
Collapse
|
25
|
Chakraborty S, Sharma A, Sharma A, Sihota R, Bhattacharjee S, Acharya M. Haplotype-based genomic analysis reveals novel association of CNTNAP5 genic region with primary angle closure glaucoma. J Biosci 2021. [DOI: 10.1007/s12038-020-00137-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
|
26
|
Yoosefzadeh-Najafabadi M, Torabi S, Tulpan D, Rajcan I, Eskandari M. Genome-Wide Association Studies of Soybean Yield-Related Hyperspectral Reflectance Bands Using Machine Learning-Mediated Data Integration Methods. FRONTIERS IN PLANT SCIENCE 2021; 12:777028. [PMID: 34880894 PMCID: PMC8647880 DOI: 10.3389/fpls.2021.777028] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Accepted: 10/18/2021] [Indexed: 05/12/2023]
Abstract
In conjunction with big data analysis methods, plant omics technologies have provided scientists with cost-effective and promising tools for discovering genetic architectures of complex agronomic traits using large breeding populations. In recent years, there has been significant progress in plant phenomics and genomics approaches for generating reliable large datasets. However, selecting an appropriate data integration and analysis method to improve the efficiency of phenome-phenome and phenome-genome association studies is still a bottleneck. This study proposes a hyperspectral wide association study (HypWAS) approach as a phenome-phenome association analysis through a hierarchical data integration strategy to estimate the prediction power of hyperspectral reflectance bands in predicting soybean seed yield. Using HypWAS, five important hyperspectral reflectance bands in visible, red-edge, and near-infrared regions were identified significantly associated with seed yield. The phenome-genome association analysis of each tested hyperspectral reflectance band was performed using two conventional genome-wide association studies (GWAS) methods and a machine learning mediated GWAS based on the support vector regression (SVR) method. Using SVR-mediated GWAS, more relevant QTL with the physiological background of the tested hyperspectral reflectance bands were detected, supported by the functional annotation of candidate gene analyses. The results of this study have indicated the advantages of using hierarchical data integration strategy and advanced mathematical methods coupled with phenome-phenome and phenome-genome association analyses for a better understanding of the biology and genetic backgrounds of hyperspectral reflectance bands affecting soybean yield formation. The identified yield-related hyperspectral reflectance bands using HypWAS can be used as indirect selection criteria for selecting superior genotypes with improved yield genetic gains in large breeding populations.
Collapse
Affiliation(s)
| | - Sepideh Torabi
- Department of Plant Agriculture, University of Guelph, Guelph, ON, Canada
| | - Dan Tulpan
- Department of Animal Biosciences, University of Guelph, Guelph, ON, Canada
| | - Istvan Rajcan
- Department of Plant Agriculture, University of Guelph, Guelph, ON, Canada
| | - Milad Eskandari
- Department of Plant Agriculture, University of Guelph, Guelph, ON, Canada
| |
Collapse
|
27
|
Helal MMU, Gill RA, Tang M, Yang L, Hu M, Yang L, Xie M, Zhao C, Cheng X, Zhang Y, Zhang X, Liu S. SNP- and Haplotype-Based GWAS of Flowering-Related Traits in Brassica napus. PLANTS (BASEL, SWITZERLAND) 2021; 10:plants10112475. [PMID: 34834840 PMCID: PMC8619824 DOI: 10.3390/plants10112475] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/26/2021] [Revised: 11/09/2021] [Accepted: 11/09/2021] [Indexed: 05/05/2023]
Abstract
Traits related to flowering time are the most promising agronomic traits that directly impact the seed yield and oil quality of rapeseed (Brassica napus L.). Developing early flowering and maturity rapeseed varieties is an important breeding objective in B. napus. Many studies have reported on days to flowering, but few have reported on budding, bolting, and the interval between bolting and DTF. Therefore, elucidating the genetic architecture of QTLs and genes regulating flowering time, we presented an integrated investigation on SNP and haplotype-based genome-wide association study of 373 diverse B. napus germplasm, which were genotyped by the 60K SNP array and were phenotyped in the four environments. The results showed that a total of 15 and 37 QTLs were detected from SNP and haplotype-based GWAS, respectively. Among them, seven QTL clusters were identified by haplotype-based GWAS. Moreover, three and eight environmentally stable QTLs were detected by SNP-GWAS and haplotype-based GWAS, respectively. By integrating the above two approaches and by co-localizing the four traits, ten (10) genomic regions were under selection on chromosomes A03, A07, A08, A10, C06, C07, and C08. Interestingly, the genomic regions FT.A07.1, FT.A08, FT.C06, and FT.C07 were identified as novel. In these ten regions, a total of 197 genes controlling FT were detected, of which 14 highly expressed DEGs were orthologous to 13 Arabidopsis thaliana genes after integration with transcriptome results. In a nutshell, the above results uncovered the genetic architecture of important agronomic traits related to flowering time and provided a basis for multiple molecular marker-trait associations in B. napus.
Collapse
Affiliation(s)
- MMU Helal
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, The Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of Chinese Academy of Agricultural Sciences, Wuhan 430062, China; (M.M.U.H.); (R.A.G.); (M.T.); (L.Y.); (M.H.); (L.Y.); (M.X.); (C.Z.); (X.C.); (S.L.)
| | - Rafaqat Ali Gill
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, The Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of Chinese Academy of Agricultural Sciences, Wuhan 430062, China; (M.M.U.H.); (R.A.G.); (M.T.); (L.Y.); (M.H.); (L.Y.); (M.X.); (C.Z.); (X.C.); (S.L.)
| | - Minqiang Tang
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, The Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of Chinese Academy of Agricultural Sciences, Wuhan 430062, China; (M.M.U.H.); (R.A.G.); (M.T.); (L.Y.); (M.H.); (L.Y.); (M.X.); (C.Z.); (X.C.); (S.L.)
- Key Laboratory of Germplasm Innovation of Tropical Special Forest Trees and Ornamental Plants (Ministry of Education), College of Forestry, Hainan University, Haikou 570228, China
| | - Li Yang
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, The Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of Chinese Academy of Agricultural Sciences, Wuhan 430062, China; (M.M.U.H.); (R.A.G.); (M.T.); (L.Y.); (M.H.); (L.Y.); (M.X.); (C.Z.); (X.C.); (S.L.)
| | - Ming Hu
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, The Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of Chinese Academy of Agricultural Sciences, Wuhan 430062, China; (M.M.U.H.); (R.A.G.); (M.T.); (L.Y.); (M.H.); (L.Y.); (M.X.); (C.Z.); (X.C.); (S.L.)
| | - Lingli Yang
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, The Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of Chinese Academy of Agricultural Sciences, Wuhan 430062, China; (M.M.U.H.); (R.A.G.); (M.T.); (L.Y.); (M.H.); (L.Y.); (M.X.); (C.Z.); (X.C.); (S.L.)
| | - Meili Xie
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, The Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of Chinese Academy of Agricultural Sciences, Wuhan 430062, China; (M.M.U.H.); (R.A.G.); (M.T.); (L.Y.); (M.H.); (L.Y.); (M.X.); (C.Z.); (X.C.); (S.L.)
| | - Chuanji Zhao
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, The Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of Chinese Academy of Agricultural Sciences, Wuhan 430062, China; (M.M.U.H.); (R.A.G.); (M.T.); (L.Y.); (M.H.); (L.Y.); (M.X.); (C.Z.); (X.C.); (S.L.)
| | - Xiaohui Cheng
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, The Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of Chinese Academy of Agricultural Sciences, Wuhan 430062, China; (M.M.U.H.); (R.A.G.); (M.T.); (L.Y.); (M.H.); (L.Y.); (M.X.); (C.Z.); (X.C.); (S.L.)
| | - Yuanyuan Zhang
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, The Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of Chinese Academy of Agricultural Sciences, Wuhan 430062, China; (M.M.U.H.); (R.A.G.); (M.T.); (L.Y.); (M.H.); (L.Y.); (M.X.); (C.Z.); (X.C.); (S.L.)
- Correspondence: (Y.Z.); (X.Z.)
| | - Xiong Zhang
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, The Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of Chinese Academy of Agricultural Sciences, Wuhan 430062, China; (M.M.U.H.); (R.A.G.); (M.T.); (L.Y.); (M.H.); (L.Y.); (M.X.); (C.Z.); (X.C.); (S.L.)
- Correspondence: (Y.Z.); (X.Z.)
| | - Shengyi Liu
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, The Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of Chinese Academy of Agricultural Sciences, Wuhan 430062, China; (M.M.U.H.); (R.A.G.); (M.T.); (L.Y.); (M.H.); (L.Y.); (M.X.); (C.Z.); (X.C.); (S.L.)
| |
Collapse
|
28
|
Bhat JA, Yu D, Bohra A, Ganie SA, Varshney RK. Features and applications of haplotypes in crop breeding. Commun Biol 2021; 4:1266. [PMID: 34737387 PMCID: PMC8568931 DOI: 10.1038/s42003-021-02782-y] [Citation(s) in RCA: 44] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2021] [Accepted: 10/09/2021] [Indexed: 12/17/2022] Open
Abstract
Climate change with altered pest-disease dynamics and rising abiotic stresses threatens resource-constrained agricultural production systems worldwide. Genomics-assisted breeding (GAB) approaches have greatly contributed to enhancing crop breeding efficiency and delivering better varieties. Fast-growing capacity and affordability of DNA sequencing has motivated large-scale germplasm sequencing projects, thus opening exciting avenues for mining haplotypes for breeding applications. This review article highlights ways to mine haplotypes and apply them for complex trait dissection and in GAB approaches including haplotype-GWAS, haplotype-based breeding, haplotype-assisted genomic selection. Improvement strategies that efficiently deploy superior haplotypes to hasten breeding progress will be key to safeguarding global food security.
Collapse
Affiliation(s)
- Javaid Akhter Bhat
- National Center for Soybean Improvement, State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China
| | - Deyue Yu
- National Center for Soybean Improvement, State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China
| | - Abhishek Bohra
- Crop Improvement Division, ICAR- Indian Institute of Pulses Research (ICAR- IIPR), Kanpur, India
| | - Showkat Ahmad Ganie
- Department of Biotechnology, Visva-Bharati, Santiniketan, 731235, WB, India.
| | - Rajeev K Varshney
- Center of Excellence in Genomics & Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, 502324, India.
- State Agricultural Biotechnology Centre, Centre for Crop & Food Research Innovation, Food Futures Institute, Murdoch University, Murdoch, WA, Australia.
| |
Collapse
|
29
|
Delfini J, Moda-Cirino V, dos Santos Neto J, Zeffa DM, Nogueira AF, Ribeiro LAB, Ruas PM, Gepts P, Gonçalves LSA. Genome-Wide Association Study Identifies Genomic Regions for Important Morpho-Agronomic Traits in Mesoamerican Common Bean. FRONTIERS IN PLANT SCIENCE 2021; 12:748829. [PMID: 34691125 PMCID: PMC8528967 DOI: 10.3389/fpls.2021.748829] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Accepted: 09/15/2021] [Indexed: 05/25/2023]
Abstract
The population growth trend in recent decades has resulted in continuing efforts to guarantee food security in which leguminous plants, such as the common bean (Phaseolus vulgaris L.), play a particularly important role as they are relatively cheap and have high nutritional value. To meet this demand for food, the main target for genetic improvement programs is to increase productivity, which is a complex quantitative trait influenced by many component traits. This research aims to identify Quantitative Trait Nucleotides (QTNs) associated with productivity and its components using multi-locus genome-wide association studies. Ten morpho-agronomic traits [plant height (PH), first pod insertion height (FPIH), number of nodules (NN), pod length (PL), total number of pods per plant (NPP), number of locules per pod (LP), number of seeds per pod (SP), total seed weight per plant (TSW), 100-seed weight (W100), and grain yield (YLD)] were evaluated in four environments for 178 Mesoamerican common bean domesticated accessions belonging to the Brazilian Diversity Panel. In order to identify stable QTNs, only those identified by multiple methods (mrMLM, FASTmrMLM, pLARmEB, and ISIS EM-BLASSO) or in multiple environments were selected. Among the identified QTNs, 64 were detected at least thrice by different methods or in different environments, and 39 showed significant phenotypic differences between their corresponding alleles. The alleles that positively increased the corresponding traits, except PH (for which lower values are desired), were considered favorable alleles. The most influenced trait by the accumulation of favorable alleles was PH, showing a 51.7% reduction, while NN, TSW, YLD, FPIH, and NPP increased between 18 and 34%. Identifying QTNs in several environments (four environments and overall adjusted mean) and by multiple methods reinforces the reliability of the associations obtained and the importance of conducting these studies in multiple environments. Using these QTNs through molecular techniques for genetic improvement, such as marker-assisted selection or genomic selection, can be a strategy to increase common bean production.
Collapse
Affiliation(s)
- Jessica Delfini
- Área de Genética e Melhoramento Vegetal, Instituto de Desenvolvimento Rural do Paraná, Londrina, Brazil
- Departamento de Agronomia, Universidade Estadual de Londrina, Londrina, Brazil
| | - Vânia Moda-Cirino
- Área de Genética e Melhoramento Vegetal, Instituto de Desenvolvimento Rural do Paraná, Londrina, Brazil
| | - José dos Santos Neto
- Área de Genética e Melhoramento Vegetal, Instituto de Desenvolvimento Rural do Paraná, Londrina, Brazil
- Departamento de Agronomia, Universidade Estadual de Londrina, Londrina, Brazil
| | - Douglas Mariani Zeffa
- Área de Genética e Melhoramento Vegetal, Instituto de Desenvolvimento Rural do Paraná, Londrina, Brazil
- Departamento de Agronomia, Universidade Estadual de Maringá, Maringá, Brazil
| | - Alison Fernando Nogueira
- Área de Genética e Melhoramento Vegetal, Instituto de Desenvolvimento Rural do Paraná, Londrina, Brazil
- Departamento de Agronomia, Universidade Estadual de Londrina, Londrina, Brazil
| | - Luriam Aparecida Brandão Ribeiro
- Área de Genética e Melhoramento Vegetal, Instituto de Desenvolvimento Rural do Paraná, Londrina, Brazil
- Departamento de Agronomia, Universidade Estadual de Londrina, Londrina, Brazil
| | - Paulo Maurício Ruas
- Departamento de Biologia, Universidade Estadual de Londrina, Londrina, Brazil
| | - Paul Gepts
- Section of Crop and Ecosystem Sciences, Department of Plant Sciences, University of California, Davis, Davis, CA, United States
| | - Leandro Simões Azeredo Gonçalves
- Departamento de Agronomia, Universidade Estadual de Londrina, Londrina, Brazil
- Departamento de Agronomia, Universidade Estadual de Maringá, Maringá, Brazil
| |
Collapse
|
30
|
Ravelombola W, Qin J, Shi A, Song Q, Yuan J, Wang F, Chen P, Yan L, Feng Y, Zhao T, Meng Y, Guan K, Yang C, Zhang M. Genome-wide association study and genomic selection for yield and related traits in soybean. PLoS One 2021; 16:e0255761. [PMID: 34388193 PMCID: PMC8362977 DOI: 10.1371/journal.pone.0255761] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2021] [Accepted: 07/22/2021] [Indexed: 12/23/2022] Open
Abstract
Soybean [Glycine max (L.) Merr.] is a crop of great interest worldwide. Exploring molecular approaches to increase yield genetic gain has been one of the main challenges for soybean breeders and geneticists. Agronomic traits such as maturity, plant height, and seed weight have been found to contribute to yield. In this study, a total of 250 soybean accessions were genotyped with 10,259 high-quality SNPs postulated from genotyping by sequencing (GBS) and evaluated for grain yield, maturity, plant height, and seed weight over three years. A genome-wide association study (GWAS) was performed using a Bayesian Information and Linkage Disequilibrium Iteratively Nested Keyway (BLINK) model. Genomic selection (GS) was evaluated using a ridge regression best linear unbiased predictor (rrBLUP) model. The results revealed that 20, 31, 37, and 23 SNPs were significantly associated with maturity, plant height, seed weight, and yield, respectively; Many SNPs were mapped to previously described maturity and plant height loci (E2, E4, and Dt1) and a new plant height locus was mapped to chromosome 20. Candidate genes were found in the vicinity of the two SNPs with the highest significant levels associated with yield, maturity, plant height, seed weight, respectively. A 11.5-Mb region of chromosome 10 was associated with both yield and seed weight. Overall, the accuracy of GS was dependent on the trait, year, and population structure, and high accuracy indicates that these agronomic traits can be selected in molecular breeding through GS. The SNP markers identified in this study can be used to improve yield and agronomic traits through the marker-assisted selection and GS in breeding programs.
Collapse
Affiliation(s)
- Waltram Ravelombola
- Department of Horticulture, University of Arkansas, Fayetteville, AR, United States of America
| | - Jun Qin
- The Key Laboratory of Crop Genetics and Breeding of Hebei Province, National Soybean Improvement Center Shijiazhuang Sub-Center, North China Key Laboratory of Biology and Genetic Improvement of Soybean, Ministry of Agriculture, Laboratory of Crop Genetics and Breeding of Hebei Cereal & Oil Crop Institute, Hebei Academy of Agricultural and Forestry Sciences, Shijiazhuang, Hebei, China
| | - Ainong Shi
- Department of Horticulture, University of Arkansas, Fayetteville, AR, United States of America
| | - Qijian Song
- Soybean Genomics and Improvement Laboratory, Beltsville Agricultural Research Center, USDA-ARS, Beltsville, MD, United States of America
| | - Jin Yuan
- The Key Laboratory of Crop Genetics and Breeding of Hebei Province, National Soybean Improvement Center Shijiazhuang Sub-Center, North China Key Laboratory of Biology and Genetic Improvement of Soybean, Ministry of Agriculture, Laboratory of Crop Genetics and Breeding of Hebei Cereal & Oil Crop Institute, Hebei Academy of Agricultural and Forestry Sciences, Shijiazhuang, Hebei, China
| | - Fengmin Wang
- The Key Laboratory of Crop Genetics and Breeding of Hebei Province, National Soybean Improvement Center Shijiazhuang Sub-Center, North China Key Laboratory of Biology and Genetic Improvement of Soybean, Ministry of Agriculture, Laboratory of Crop Genetics and Breeding of Hebei Cereal & Oil Crop Institute, Hebei Academy of Agricultural and Forestry Sciences, Shijiazhuang, Hebei, China
| | - Pengyin Chen
- Fisher Delta Research Center, University of Missouri, MO, United States of America
| | - Long Yan
- The Key Laboratory of Crop Genetics and Breeding of Hebei Province, National Soybean Improvement Center Shijiazhuang Sub-Center, North China Key Laboratory of Biology and Genetic Improvement of Soybean, Ministry of Agriculture, Laboratory of Crop Genetics and Breeding of Hebei Cereal & Oil Crop Institute, Hebei Academy of Agricultural and Forestry Sciences, Shijiazhuang, Hebei, China
| | - Yan Feng
- The Key Laboratory of Crop Genetics and Breeding of Hebei Province, National Soybean Improvement Center Shijiazhuang Sub-Center, North China Key Laboratory of Biology and Genetic Improvement of Soybean, Ministry of Agriculture, Laboratory of Crop Genetics and Breeding of Hebei Cereal & Oil Crop Institute, Hebei Academy of Agricultural and Forestry Sciences, Shijiazhuang, Hebei, China
| | - Tiantian Zhao
- The Key Laboratory of Crop Genetics and Breeding of Hebei Province, National Soybean Improvement Center Shijiazhuang Sub-Center, North China Key Laboratory of Biology and Genetic Improvement of Soybean, Ministry of Agriculture, Laboratory of Crop Genetics and Breeding of Hebei Cereal & Oil Crop Institute, Hebei Academy of Agricultural and Forestry Sciences, Shijiazhuang, Hebei, China
| | - Yaning Meng
- The Key Laboratory of Crop Genetics and Breeding of Hebei Province, National Soybean Improvement Center Shijiazhuang Sub-Center, North China Key Laboratory of Biology and Genetic Improvement of Soybean, Ministry of Agriculture, Laboratory of Crop Genetics and Breeding of Hebei Cereal & Oil Crop Institute, Hebei Academy of Agricultural and Forestry Sciences, Shijiazhuang, Hebei, China
| | - Kexin Guan
- The Key Laboratory of Crop Genetics and Breeding of Hebei Province, National Soybean Improvement Center Shijiazhuang Sub-Center, North China Key Laboratory of Biology and Genetic Improvement of Soybean, Ministry of Agriculture, Laboratory of Crop Genetics and Breeding of Hebei Cereal & Oil Crop Institute, Hebei Academy of Agricultural and Forestry Sciences, Shijiazhuang, Hebei, China
| | - Chunyan Yang
- The Key Laboratory of Crop Genetics and Breeding of Hebei Province, National Soybean Improvement Center Shijiazhuang Sub-Center, North China Key Laboratory of Biology and Genetic Improvement of Soybean, Ministry of Agriculture, Laboratory of Crop Genetics and Breeding of Hebei Cereal & Oil Crop Institute, Hebei Academy of Agricultural and Forestry Sciences, Shijiazhuang, Hebei, China
| | - Mengchen Zhang
- The Key Laboratory of Crop Genetics and Breeding of Hebei Province, National Soybean Improvement Center Shijiazhuang Sub-Center, North China Key Laboratory of Biology and Genetic Improvement of Soybean, Ministry of Agriculture, Laboratory of Crop Genetics and Breeding of Hebei Cereal & Oil Crop Institute, Hebei Academy of Agricultural and Forestry Sciences, Shijiazhuang, Hebei, China
| |
Collapse
|
31
|
Li X, Zhou Y, Bu Y, Wang X, Zhang Y, Guo N, Zhao J, Xing H. Genome-wide association analysis for yield-related traits at the R6 stage in a Chinese soybean mini core collection. Genes Genomics 2021; 43:897-912. [PMID: 33956328 DOI: 10.1007/s13258-021-01109-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2021] [Accepted: 04/26/2021] [Indexed: 11/28/2022]
Abstract
BACKGROUND Soybean (Glycine max (L.) Merr.) is an economically important crop for vegetable oil and protein production, and yield is a critical trait for grain/vegetable uses of soybean. However, our knowledge of the genes controlling the vegetable soybean yield remains limited. OBJECTIVE To better understand the genetic basis of the vegetable soybean yield. METHODS The 100-pod fresh weight (PFW), 100-seed fresh weight (SFW), kernel percent (KP) and moisture content of fresh seeds (MCFS) at the R6 stage are four yield-related traits for vegetable soybean. We investigated a soybean mini core collection composed of 224 germplasm accessions for four yield-related traits in two consecutive years. Based on 1514 single nucleotide polymorphisms (SNPs), genome-wide association studies (GWAS) were conducted using a mixed linear model (MLM). RESULTS Extensive phenotypic variation existed in the soybean mini core collection and significant positive correlations were shown among most of traits. A total of 16 SNP markers for PFW, SFW, KP and MCFS were detected in all environments via GWAS. Nine SNP markers were repeatedly identified in two environments. Among these markers, eight were located in or near regions where yield-related QTLs have been reported in previous studies, and one was a novel genetic locus identified in this study. In addition, we conducted candidate gene analysis to the large-effect SNP markers, a total of twelve genes were proposed as potential candidate genes of soybean yield at the R6 stage. CONCLUSION These results will be beneficial for understanding the genetic basis of soybean yield at the R6 stage and facilitating the pyramiding of favourable alleles for future high-yield breeding by marker-assisted selection in vegetable soybean.
Collapse
Affiliation(s)
- Xiangnan Li
- National Center for Soybean Improvement, Key Laboratory of Biology and Genetics and Breeding for Soybean, Ministry of Agriculture, State Key Laboratory for Crop Genetics and Germplasm Enhancement, College of Agriculture, Nanjing Agricultural University, Weigang No. 1, Nanjing, 210095, Jiangsu, China
| | - Yang Zhou
- National Center for Soybean Improvement, Key Laboratory of Biology and Genetics and Breeding for Soybean, Ministry of Agriculture, State Key Laboratory for Crop Genetics and Germplasm Enhancement, College of Agriculture, Nanjing Agricultural University, Weigang No. 1, Nanjing, 210095, Jiangsu, China
| | - Yuanpeng Bu
- National Center for Soybean Improvement, Key Laboratory of Biology and Genetics and Breeding for Soybean, Ministry of Agriculture, State Key Laboratory for Crop Genetics and Germplasm Enhancement, College of Agriculture, Nanjing Agricultural University, Weigang No. 1, Nanjing, 210095, Jiangsu, China
| | - Xinfang Wang
- National Center for Soybean Improvement, Key Laboratory of Biology and Genetics and Breeding for Soybean, Ministry of Agriculture, State Key Laboratory for Crop Genetics and Germplasm Enhancement, College of Agriculture, Nanjing Agricultural University, Weigang No. 1, Nanjing, 210095, Jiangsu, China
| | - Yumei Zhang
- National Center for Soybean Improvement, Key Laboratory of Biology and Genetics and Breeding for Soybean, Ministry of Agriculture, State Key Laboratory for Crop Genetics and Germplasm Enhancement, College of Agriculture, Nanjing Agricultural University, Weigang No. 1, Nanjing, 210095, Jiangsu, China
| | - Na Guo
- National Center for Soybean Improvement, Key Laboratory of Biology and Genetics and Breeding for Soybean, Ministry of Agriculture, State Key Laboratory for Crop Genetics and Germplasm Enhancement, College of Agriculture, Nanjing Agricultural University, Weigang No. 1, Nanjing, 210095, Jiangsu, China
| | - Jinming Zhao
- National Center for Soybean Improvement, Key Laboratory of Biology and Genetics and Breeding for Soybean, Ministry of Agriculture, State Key Laboratory for Crop Genetics and Germplasm Enhancement, College of Agriculture, Nanjing Agricultural University, Weigang No. 1, Nanjing, 210095, Jiangsu, China.
| | - Han Xing
- National Center for Soybean Improvement, Key Laboratory of Biology and Genetics and Breeding for Soybean, Ministry of Agriculture, State Key Laboratory for Crop Genetics and Germplasm Enhancement, College of Agriculture, Nanjing Agricultural University, Weigang No. 1, Nanjing, 210095, Jiangsu, China.
| |
Collapse
|
32
|
Wu P, Wang K, Zhou J, Chen D, Jiang A, Jiang Y, Zhu L, Qiu X, Li X, Tang G. A combined GWAS approach reveals key loci for socially-affected traits in Yorkshire pigs. Commun Biol 2021; 4:891. [PMID: 34285319 PMCID: PMC8292486 DOI: 10.1038/s42003-021-02416-3] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2021] [Accepted: 06/29/2021] [Indexed: 02/06/2023] Open
Abstract
Socially affected traits in pigs are controlled by direct genetic effects and social genetic effects, which can make elucidation of their genetic architecture challenging. We evaluated the genetic basis of direct genetic effects and social genetic effects by combining single-locus and haplotype-based GWAS on imputed whole-genome sequences. Nineteen SNPs and 25 haplotype loci are identified for direct genetic effects on four traits: average daily feed intake, average daily gain, days to 100 kg and time in feeder per day. Nineteen SNPs and 11 haplotype loci are identified for social genetic effects on average daily feed intake, average daily gain, days to 100 kg and feeding speed. Two significant SNPs from single-locus GWAS (SSC6:18,635,874 and SSC6:18,635,895) are shared by a significant haplotype locus with haplotype alleles 'GGG' for both direct genetic effects and social genetic effects in average daily feed intake. A candidate gene, MT3, which is involved in growth, nervous, and immune processes, is identified. We demonstrate the genetic differences between direct genetic effects and social genetic effects and provide an anchor for investigating the genetic architecture underlying direct genetic effects and social genetic effects on socially affected traits in pigs.
Collapse
Affiliation(s)
- Pingxian Wu
- grid.80510.3c0000 0001 0185 3134Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, Sichuan China
| | - Kai Wang
- grid.80510.3c0000 0001 0185 3134Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, Sichuan China
| | - Jie Zhou
- grid.80510.3c0000 0001 0185 3134Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, Sichuan China
| | - Dejuan Chen
- grid.80510.3c0000 0001 0185 3134Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, Sichuan China
| | - Anan Jiang
- grid.80510.3c0000 0001 0185 3134Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, Sichuan China
| | - Yanzhi Jiang
- grid.80510.3c0000 0001 0185 3134College of Life Science, Sichuan Agricultural University, Yaan, Sichuan China
| | - Li Zhu
- grid.80510.3c0000 0001 0185 3134Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, Sichuan China
| | - Xiaotian Qiu
- grid.410634.4National Animal Husbandry Service, Beijing, Beijing, China
| | - Xuewei Li
- grid.80510.3c0000 0001 0185 3134Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, Sichuan China
| | - Guoqing Tang
- grid.80510.3c0000 0001 0185 3134Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, Sichuan China
| |
Collapse
|
33
|
Genomic regions associated with heat stress tolerance in tropical maize (Zea mays L.). Sci Rep 2021; 11:13730. [PMID: 34215789 PMCID: PMC8253795 DOI: 10.1038/s41598-021-93061-7] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2021] [Accepted: 06/21/2021] [Indexed: 11/20/2022] Open
Abstract
With progressive climate change and the associated increase in mean temperature, heat stress tolerance has emerged as one of the key traits in the product profile of the maize breeding pipeline for lowland tropics. The present study aims to identify the genomic regions associated with heat stress tolerance in tropical maize. An association mapping panel, called the heat tolerant association mapping (HTAM) panel, was constituted by involving a total of 543 tropical maize inbred lines from diverse genetic backgrounds, test-crossed and phenotyped across nine locations in South Asia under natural heat stress. The panel was genotyped using a genotyping-by-sequencing (GBS) platform. Considering the large variations in vapor pressure deficit (VPD) at high temperature (Tmax) across different phenotyping locations, genome-wide association study (GWAS) was conducted separately for each location. The individual location GWAS identified a total of 269 novel significant single nucleotide polymorphisms (SNPs) for grain yield under heat stress at a p value of < 10–5. A total of 175 SNPs were found in 140 unique gene models implicated in various biological pathway responses to different abiotic stresses. Haplotype trend regression (HTR) analysis of the significant SNPs identified 26 haplotype blocks and 96 single SNP variants significant across one to five locations. The genomic regions identified based on GWAS and HTR analysis considering genomic region x environment interactions are useful for breeding efforts aimed at developing heat stress resilient maize cultivars for current and future climatic conditions through marker-assisted introgression into elite genetic backgrounds and/or genome-wide selection.
Collapse
|
34
|
Sun CY, Yang YM, Jia L, Liu XQ, Xu HQ, Lv HY, Huang ZW, Zhang D. QTL mapping of the genetic basis of stem diameter in soybean. PLANTA 2021; 253:109. [PMID: 33871705 DOI: 10.1007/s00425-021-03628-x] [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: 10/09/2020] [Accepted: 04/12/2021] [Indexed: 06/12/2023]
Abstract
MAIN CONCLUSION QTL mapping of stem diameter was carried out in three RIL populations using a high-density genetic map, and candidate genes related to stem diameter were predicted. Stem diameter is an important agronomic trait affecting soybean lodging and productivity. However, this trait is underexploited, and the underlying genetic mechanism in soybean remains unclear. In this study, three recombinant inbred line (RIL) populations, including 156 F10 lines from Nannong 94-156 × Bogao (N × B), 127 F9 lines from Dongnong 50 × Williams 82 (D × W), and 146 F9 lines from Suinong 14 × Enrei (S × E), were used to identify QTLs for soybean stem diameter across multiple environments. Phenotype analysis revealed that stem diameter exhibited strong positive correlations with plant height and 100-seed weight, two of the most important yield components. A total of 12 QTLs for stem diameter were identified on eight chromosomes across three RIL populations and five environments. The most influential QTL that was stably identified across all the populations and environments, q11, explained 12.58-26.63% of the phenotypic variation. Detection of several environment-specific QTLs, including q14, q16, and q20, suggests that environments may also have important effects in shaping the natural variation in soybean stem diameter. Furthermore, we predicted candidate genes underlying the QTLs and found that several promising candidate genes may be responsible for the variation in stem diameter in soybean. Overall, the markers/genes linked closely or underlying the major QTLs may be used for marker-assisted selection of soybean varieties to enhance lodging resistance and even yield. Our results lay the foundation for the fine mapping of stem development-related genes to reveal the molecular mechanisms.
Collapse
Affiliation(s)
- Chong-Yuan Sun
- Collaborative Innovation Center of Henan Grain Crops, College of Agronomy, Henan Agricultural University, Zhengzhou, 450002, China
| | - Yu-Ming Yang
- Collaborative Innovation Center of Henan Grain Crops, College of Agronomy, Henan Agricultural University, Zhengzhou, 450002, China
| | - Lin Jia
- Collaborative Innovation Center of Henan Grain Crops, College of Agronomy, Henan Agricultural University, Zhengzhou, 450002, China
| | - Xiao-Qian Liu
- Collaborative Innovation Center of Henan Grain Crops, College of Agronomy, Henan Agricultural University, Zhengzhou, 450002, China
| | - Huan-Qing Xu
- Collaborative Innovation Center of Henan Grain Crops, College of Agronomy, Henan Agricultural University, Zhengzhou, 450002, China
| | - Hai-Yan Lv
- Collaborative Innovation Center of Henan Grain Crops, College of Agronomy, Henan Agricultural University, Zhengzhou, 450002, China
| | - Zhong-Wen Huang
- School of Life Science and Technology, Henan Institute of Science and Technology/Henan Collaborative Innovation Center of Modern Biological Breeding, Xinxiang, 453003, China
| | - Dan Zhang
- Collaborative Innovation Center of Henan Grain Crops, College of Agronomy, Henan Agricultural University, Zhengzhou, 450002, China.
| |
Collapse
|
35
|
Longmei N, Gill GK, Zaidi PH, Kumar R, Nair SK, Hindu V, Vinayan MT, Vikal Y. Genome wide association mapping for heat tolerance in sub-tropical maize. BMC Genomics 2021; 22:154. [PMID: 33663389 PMCID: PMC7934507 DOI: 10.1186/s12864-021-07463-y] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2020] [Accepted: 02/22/2021] [Indexed: 01/06/2023] Open
Abstract
Background Heat tolerance is becoming increasingly important where maize is grown under spring season in India which coincide with grain filling stage of crop resulting in tassel blast, reduced pollen viability, pollination failure and barren ears that causes devastating yield losses. So, there is need to identify the genomic regions associated with heat tolerance component traits which could be further employed in maize breeding program. Results An association mapping panel, consisting of 662 doubled haploid (DH) lines, was evaluated for yield contributing traits under normal and natural heat stress conditions. Genome wide association studies (GWAS) carried out using 187,000 SNPs and 130 SNPs significantly associated for grain yield (GY), days to 50% anthesis (AD), days to 50% silking (SD), anthesis-silking interval (ASI), plant height (PH), ear height (EH) and ear position (EPO) were identified under normal conditions. A total of 46 SNPs strongly associated with GY, ASI, EH and EPO were detected under heat stress conditions. Fifteen of the SNPs was found to have common association with more than one trait such as two SNPs viz. S10_1,905,273 and S10_1,905,274 showed colocalization with GY, PH and EH whereas S10_7,132,845 SNP associated with GY, AD and SD under normal conditions. No such colocalization of SNP markers with multiple traits was observed under heat stress conditions. Haplotypes trend regression analysis revealed 122 and 85 haplotype blocks, out of which, 20 and 6 haplotype blocks were associated with more than one trait under normal and heat stress conditions, respectively. Based on SNP association and haplotype mapping, nine and seven candidate genes were identified respectively, which belongs to different gene models having different biological functions in stress biology. Conclusions The present study identified significant SNPs and haplotype blocks associated with yield contributing traits that help in selection of donor lines with favorable alleles for multiple traits. These results provided insights of genetics of heat stress tolerance. The genomic regions detected in the present study need further validation before being applied in the breeding pipelines. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-021-07463-y.
Collapse
Affiliation(s)
- Ningthaipuilu Longmei
- Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Gurjit Kaur Gill
- Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Pervez Haider Zaidi
- International Maize and Wheat Improvement Centre (CIMMYT), Asia Regional Office, Hyderabad, India
| | - Ramesh Kumar
- Indian Institutes of Maize, Ludhiana, Punjab, India
| | - Sudha Krishnan Nair
- International Maize and Wheat Improvement Centre (CIMMYT), Asia Regional Office, Hyderabad, India
| | - Vermuri Hindu
- International Maize and Wheat Improvement Centre (CIMMYT), Asia Regional Office, Hyderabad, India
| | - Madhumal Thayil Vinayan
- International Maize and Wheat Improvement Centre (CIMMYT), Asia Regional Office, Hyderabad, India
| | - Yogesh Vikal
- School of Agricultural Biotechnology, Punjab Agricultural University, Ludhiana, Punjab, India.
| |
Collapse
|
36
|
Minamikawa MF, Kunihisa M, Noshita K, Moriya S, Abe K, Hayashi T, Katayose Y, Matsumoto T, Nishitani C, Terakami S, Yamamoto T, Iwata H. Tracing founder haplotypes of Japanese apple varieties: application in genomic prediction and genome-wide association study. HORTICULTURE RESEARCH 2021; 8:49. [PMID: 33642580 PMCID: PMC7917097 DOI: 10.1038/s41438-021-00485-3] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/28/2020] [Revised: 12/28/2020] [Accepted: 01/03/2021] [Indexed: 05/21/2023]
Abstract
Haplotypes provide useful information for genomics-based approaches, genomic prediction, and genome-wide association study. As a small number of superior founders have contributed largely to the breeding history of fruit trees, the information of founder haplotypes may be relevant for performing the genomics-based approaches in these plants. In this study, we proposed a method to estimate 14 haplotypes from 7 founders and automatically trace the haplotypes forward to apple parental (185 varieties) and breeding (659 F1 individuals from 16 full-sib families) populations based on 11,786 single-nucleotide polymorphisms, by combining multiple algorithms. Overall, 92% of the single-nucleotide polymorphisms information in the parental and breeding populations was characterized by the 14 founder haplotypes. The use of founder haplotype information improved the accuracy of genomic prediction in 7 traits and the resolution of genome-wide association study in 13 out of 27 fruit quality traits analyzed in this study. We also visualized the significant propagation of the founder haplotype with the largest genetic effect in genome-wide association study over the pedigree tree of the parental population. These results suggest that the information of founder haplotypes can be useful for not only genetic improvement of fruit quality traits in apples but also for understanding the selection history of founder haplotypes in the breeding program of Japanese apple varieties.
Collapse
Affiliation(s)
- Mai F Minamikawa
- Laboratory of Biometry and Bioinformatics, Department of Agricultural and Environmental Biology, Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo, Tokyo, 113-8657, Japan
| | - Miyuki Kunihisa
- Institute of Fruit Tree and Tea Science, National Agriculture and Food Research Organization (NARO), 2-1 Fujimoto, Tsukuba, Ibaraki, 305-8605, Japan
| | - Koji Noshita
- Laboratory of Biometry and Bioinformatics, Department of Agricultural and Environmental Biology, Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo, Tokyo, 113-8657, Japan
| | - Shigeki Moriya
- Division of Apple Research, Institute of Fruit Tree and Tea Science, NARO, 92-24 Shimokuriyagawa Nabeyashiki, Morioka, Iwate, 020-0123, Japan
| | - Kazuyuki Abe
- Division of Apple Research, Institute of Fruit Tree and Tea Science, NARO, 92-24 Shimokuriyagawa Nabeyashiki, Morioka, Iwate, 020-0123, Japan
| | - Takeshi Hayashi
- Institute of Crop Science, NARO, 2-1-2 Kannondai, Tsukuba, Ibaraki, 305-8518, Japan
| | - Yuichi Katayose
- Institute of Crop Science, NARO, 2-1-2 Kannondai, Tsukuba, Ibaraki, 305-8518, Japan
| | - Toshimi Matsumoto
- Institute of Crop Science, NARO, 2-1-2 Kannondai, Tsukuba, Ibaraki, 305-8518, Japan
- Institute of Agrobiological Sciences, NARO, 1-2 Owashi, Tsukuba, Ibaraki, 305-8634, Japan
| | - Chikako Nishitani
- Institute of Fruit Tree and Tea Science, National Agriculture and Food Research Organization (NARO), 2-1 Fujimoto, Tsukuba, Ibaraki, 305-8605, Japan
| | - Shingo Terakami
- Institute of Fruit Tree and Tea Science, National Agriculture and Food Research Organization (NARO), 2-1 Fujimoto, Tsukuba, Ibaraki, 305-8605, Japan
| | - Toshiya Yamamoto
- Institute of Fruit Tree and Tea Science, National Agriculture and Food Research Organization (NARO), 2-1 Fujimoto, Tsukuba, Ibaraki, 305-8605, Japan
| | - Hiroyoshi Iwata
- Laboratory of Biometry and Bioinformatics, Department of Agricultural and Environmental Biology, Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo, Tokyo, 113-8657, Japan.
| |
Collapse
|
37
|
Wang P, Sun X, Zhang K, Fang Y, Wang J, Yang C, Li WX, Ning H. Mapping QTL/QTN and mining candidate genes for plant height and its response to planting densities in soybean [ Glycine max (L.) Merr.] through a FW-RIL population. MOLECULAR BREEDING : NEW STRATEGIES IN PLANT IMPROVEMENT 2021; 41:12. [PMID: 37309477 PMCID: PMC10236039 DOI: 10.1007/s11032-021-01209-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/28/2020] [Accepted: 01/26/2021] [Indexed: 06/13/2023]
Abstract
Plant height (PH) determines the morphology and seed yield of soybean, so it is an important breeding target, which is controlled by multiple genes and affected by plant density. In this research, it was used about a four-way recombinant inbred lines (FW-RIL) with 144 families constructed by double cross (Kenfeng 14 × Kenfeng 15) × (Heinong 48 × Kenfeng 19) as experimental materials, with the purpose to map QTL/QTN associated with PH under densities of 2.2×105 plant/ha (D1) and 3×105 plant/ha (D2) in five environments. The results showed that response of PH to densities varied in accordance to genotypes among environments. A total of 26 QTLs and 13 QTNs were identified specifically in D1; 20 QTLs and 21 QTNs were identified specifically in D2. Nine QTLs and one QTN were discovered commonly in two densities. Fifteen QTLs and 9 QTNs were repeatedly detected by multiple statistical methods, densities, or environments, which could be considered stable. Eighteen QTLs were detected, as well as 7 QTNs underlying responses of PH to density increment. Six QTNs, co-located in the interval of QTL, were detected in more than two environments or methods with a longer genome length over 3000 kb. Based on gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, five genes were predicted as candidates, which were likely to be involved in growth and development of PH. The results will help elucidate the genetic basis and improve molecular assistant selection of PH. Supplementary Information The online version contains supplementary material available at 10.1007/s11032-021-01209-0.
Collapse
Affiliation(s)
- Ping Wang
- Key Laboratory of Soybean Biology, Ministry of Education/Key Laboratory of Soybean Biology and Breeding/Genetics, Ministry of Agriculture, Northeast Agricultural University, Harbin, China
- Huaiyin Institute of Technology, Huai’an, China
| | - Xu Sun
- Key Laboratory of Soybean Biology, Ministry of Education/Key Laboratory of Soybean Biology and Breeding/Genetics, Ministry of Agriculture, Northeast Agricultural University, Harbin, China
| | - Kaixin Zhang
- Key Laboratory of Soybean Biology, Ministry of Education/Key Laboratory of Soybean Biology and Breeding/Genetics, Ministry of Agriculture, Northeast Agricultural University, Harbin, China
| | - Yanlong Fang
- Key Laboratory of Soybean Biology, Ministry of Education/Key Laboratory of Soybean Biology and Breeding/Genetics, Ministry of Agriculture, Northeast Agricultural University, Harbin, China
| | - Jiajing Wang
- Key Laboratory of Soybean Biology, Ministry of Education/Key Laboratory of Soybean Biology and Breeding/Genetics, Ministry of Agriculture, Northeast Agricultural University, Harbin, China
| | - Chang Yang
- Key Laboratory of Soybean Biology, Ministry of Education/Key Laboratory of Soybean Biology and Breeding/Genetics, Ministry of Agriculture, Northeast Agricultural University, Harbin, China
| | - Wen-Xia Li
- Key Laboratory of Soybean Biology, Ministry of Education/Key Laboratory of Soybean Biology and Breeding/Genetics, Ministry of Agriculture, Northeast Agricultural University, Harbin, China
| | - Hailong Ning
- Key Laboratory of Soybean Biology, Ministry of Education/Key Laboratory of Soybean Biology and Breeding/Genetics, Ministry of Agriculture, Northeast Agricultural University, Harbin, China
| |
Collapse
|
38
|
Koua AP, Oyiga BC, Baig MM, Léon J, Ballvora A. Breeding Driven Enrichment of Genetic Variation for Key Yield Components and Grain Starch Content Under Drought Stress in Winter Wheat. FRONTIERS IN PLANT SCIENCE 2021; 12:684205. [PMID: 34484257 PMCID: PMC8415485 DOI: 10.3389/fpls.2021.684205] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/22/2021] [Accepted: 07/20/2021] [Indexed: 05/12/2023]
Abstract
Drought is one of the major abiotic stress factors limiting wheat production worldwide, thus threatening food security. The dissection of the genetic footprint of drought stress response offers strong opportunities toward understanding and improving drought tolerance (DT) in wheat. In this study, we investigated the genotypic variability for drought response among 200 diverse wheat cultivars (genotypes) using agronomic, developmental, and grain quality traits (GQT), and conducted genome-wide association studies (GWAS) to uncover the genetic architectures of these important traits. Results indicated significant effects of genotype, water regime and their interactions for all agronomic traits. Grain yield (GY) was the most drought-responsive trait and was highly correlated with kernels number per meter square (KN). Genome-wide association studies revealed 17 and 20 QTL regions under rainfed and drought conditions, respectively, and identified one LD block on chromosome 3A and two others on 5D associated with breeding progress (BP). The major haplotypes of these LD blocks have been positively selected through breeding and are associated with higher starch accumulation and GY under drought conditions. Upon validation, the identified QTL regions caring favorable alleles for high starch and yield will shed light on mechanisms of tolerance to drought and can be used to develop drought resistant cultivars.
Collapse
Affiliation(s)
- Ahossi Patrice Koua
- Department of Plant Breeding, Institut für Nutzpflanzenwissenschaften und Ressourcenschutz (INRES), Rheinische Friedrich-Wilhelms-University, Bonn, Germany
| | - Benedict Chijioke Oyiga
- Department of Plant Breeding, Institut für Nutzpflanzenwissenschaften und Ressourcenschutz (INRES), Rheinische Friedrich-Wilhelms-University, Bonn, Germany
| | - Mirza Majid Baig
- Department of Plant Breeding, Institut für Nutzpflanzenwissenschaften und Ressourcenschutz (INRES), Rheinische Friedrich-Wilhelms-University, Bonn, Germany
| | - Jens Léon
- Department of Plant Breeding, Institut für Nutzpflanzenwissenschaften und Ressourcenschutz (INRES), Rheinische Friedrich-Wilhelms-University, Bonn, Germany
- Field Lab Campus Klein-Altendorf, Rheinische Friedrich-Wilhelms-University, Bonn, Germany
| | - Agim Ballvora
- Department of Plant Breeding, Institut für Nutzpflanzenwissenschaften und Ressourcenschutz (INRES), Rheinische Friedrich-Wilhelms-University, Bonn, Germany
- *Correspondence: Agim Ballvora
| |
Collapse
|
39
|
Liu JY, Zhang YW, Han X, Zuo JF, Zhang Z, Shang H, Song Q, Zhang YM. An evolutionary population structure model reveals pleiotropic effects of GmPDAT for traits related to seed size and oil content in soybean. JOURNAL OF EXPERIMENTAL BOTANY 2020; 71:6988-7002. [PMID: 32926130 DOI: 10.1093/jxb/eraa426] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Accepted: 09/10/2020] [Indexed: 05/20/2023]
Abstract
Seed oil traits in soybean that are of benefit to human nutrition and health have been selected for during crop domestication. However, these domesticated traits have significant differences across various evolutionary types. In this study, we found that the integration of evolutionary population structure (evolutionary types) with genome-wide association studies increased the power of gene detection, and it identified one locus for traits related to seed size and oil content on chromosome 13. This domestication locus, together with another one in a 200-kb region, was confirmed by the GEMMA and EMMAX software. The candidate gene, GmPDAT, had higher expressional levels in high-oil and large-seed accessions than in low-oil and small-seed accessions. Overexpression lines had increased seed size and oil content, whereas RNAi lines had decreased seed size and oil content. The molecular mechanism of GmPDAT was deduced based on results from linkage analysis for triacylglycerols and on histocytological comparisons of transgenic soybean seeds. Our results illustrate a new approach for identifying domestication genes with pleiotropic effects.
Collapse
Affiliation(s)
- Jin-Yang Liu
- Crop Information Center, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, China
- Institute of Industrial Crops, Jiangsu Academy of Agricultural Sciences, Nanjing, China
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China
| | - Ya-Wen Zhang
- Crop Information Center, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, China
| | - Xu Han
- Crop Information Center, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, China
| | - Jian-Fang Zuo
- Crop Information Center, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, China
| | - Zhibin Zhang
- Zhengzhou Research Base, State Key Laboratory of Cotton Biology, Zhengzhou University, Zhengzhou, China
| | - Haihong Shang
- Zhengzhou Research Base, State Key Laboratory of Cotton Biology, Zhengzhou University, Zhengzhou, China
| | - Qijian Song
- Soybean Genomics and Improvement Laboratory, Agricultural Research Service, United States Department of Agriculture, Beltsville, Maryland, USA
| | - Yuan-Ming Zhang
- Crop Information Center, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, China
| |
Collapse
|
40
|
New Transcriptome-Based SNP Markers for Noug ( Guizotia abyssinica) and Their Conversion to KASP Markers for Population Genetics Analyses. Genes (Basel) 2020; 11:genes11111373. [PMID: 33233626 PMCID: PMC7709008 DOI: 10.3390/genes11111373] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2020] [Revised: 11/10/2020] [Accepted: 11/18/2020] [Indexed: 11/17/2022] Open
Abstract
The development and use of genomic resources are essential for understanding the population genetics of crops for their efficient conservation and enhancement. Noug (Guizotia abyssinica) is an economically important oilseed crop in Ethiopia and India. The present study sought to develop new DNA markers for this crop. Transcriptome sequencing was conducted on two genotypes and 628 transcript sequences containing 959 single nucleotide polymorphisms (SNPs) were developed. A competitive allele-specific PCR (KASP) assay was developed for the SNPs and used for genotyping of 24 accessions. A total of 554 loci were successfully genotyped across the accessions, and 202 polymorphic loci were used for population genetics analyses. Polymorphism information content (PIC) of the loci varied from 0.01 to 0.37 with a mean of 0.24, and about 49% of the loci showed significant deviation from the Hardy-Weinberg equilibrium. The mean expected heterozygosity was 0.27 suggesting moderately high genetic variation within accessions. Low but significant differentiation existed among accessions (FST = 0.045, p < 0.0001). Landrace populations from isolated areas may have useful mutations and should be conserved and used in breeding this crop. The genomic resources developed in this study were shown to be useful for population genetics research and can also be used in, e.g., association genetics.
Collapse
|
41
|
Karikari B, Wang Z, Zhou Y, Yan W, Feng J, Zhao T. Identification of quantitative trait nucleotides and candidate genes for soybean seed weight by multiple models of genome-wide association study. BMC PLANT BIOLOGY 2020; 20:404. [PMID: 32873245 PMCID: PMC7466808 DOI: 10.1186/s12870-020-02604-z] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/07/2020] [Accepted: 08/16/2020] [Indexed: 05/15/2023]
Abstract
BACKGROUND Seed weight is a complex yield-related trait with a lot of quantitative trait loci (QTL) reported through linkage mapping studies. Integration of QTL from linkage mapping into breeding program is challenging due to numerous limitations, therefore, Genome-wide association study (GWAS) provides more precise location of QTL due to higher resolution and diverse genetic diversity in un-related individuals. RESULTS The present study utilized 573 breeding lines population with 61,166 single nucleotide polymorphisms (SNPs) to identify quantitative trait nucleotides (QTNs) and candidate genes for seed weight in Chinese summer-sowing soybean. GWAS was conducted with two single-locus models (SLMs) and six multi-locus models (MLMs). Thirty-nine SNPs were detected by the two SLMs while 209 SNPs were detected by the six MLMs. In all, two hundred and thirty-one QTNs were found to be associated with seed weight in YHSBLP with various effects. Out of these, seventy SNPs were concurrently detected by both SLMs and MLMs on 8 chromosomes. Ninety-four QTNs co-localized with previously reported QTL/QTN by linkage/association mapping studies. A total of 36 candidate genes were predicted. Out of these candidate genes, four hub genes (Glyma06g44510, Glyma08g06420, Glyma12g33280 and Glyma19g28070) were identified by the integration of co-expression network. Among them, three were relatively expressed higher in the high HSW genotypes at R5 stage compared with low HSW genotypes except Glyma12g33280. Our results show that using more models especially MLMs are effective to find important QTNs, and the identified HSW QTNs/genes could be utilized in molecular breeding work for soybean seed weight and yield. CONCLUSION Application of two single-locus plus six multi-locus models of GWAS identified 231 QTNs. Four hub genes (Glyma06g44510, Glyma08g06420, Glyma12g33280 & Glyma19g28070) detected via integration of co-expression network among the predicted candidate genes.
Collapse
Affiliation(s)
- Benjamin Karikari
- National Center for Soybean Improvement, Key Laboratory of Biology and Genetic Improvement of Soybean (Ministry of Agriculture), State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, People's Republic of China
| | - Zili Wang
- National Center for Soybean Improvement, Key Laboratory of Biology and Genetic Improvement of Soybean (Ministry of Agriculture), State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, People's Republic of China
| | - Yilan Zhou
- National Center for Soybean Improvement, Key Laboratory of Biology and Genetic Improvement of Soybean (Ministry of Agriculture), State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, People's Republic of China
| | - Wenliang Yan
- National Center for Soybean Improvement, Key Laboratory of Biology and Genetic Improvement of Soybean (Ministry of Agriculture), State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, People's Republic of China
| | - Jianying Feng
- National Center for Soybean Improvement, Key Laboratory of Biology and Genetic Improvement of Soybean (Ministry of Agriculture), State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, People's Republic of China.
| | - Tuanjie Zhao
- National Center for Soybean Improvement, Key Laboratory of Biology and Genetic Improvement of Soybean (Ministry of Agriculture), State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, People's Republic of China.
| |
Collapse
|
42
|
Qi Z, Song J, Zhang K, Liu S, Tian X, Wang Y, Fang Y, Li X, Wang J, Yang C, Jiang S, Sun X, Tian Z, Li W, Ning H. Identification of QTNs Controlling 100-Seed Weight in Soybean Using Multilocus Genome-Wide Association Studies. Front Genet 2020; 11:689. [PMID: 32765581 PMCID: PMC7378803 DOI: 10.3389/fgene.2020.00689] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2019] [Accepted: 06/04/2020] [Indexed: 01/08/2023] Open
Abstract
Hundred-seed weight (HSW) is an important measure of yield and a useful indicator to monitor the inheritance of quantitative traits affected by genotype and environmental conditions. To identify quantitative trait nucleotides (QTNs) and mine genes useful for breeding high-yielding and high-quality soybean (Glycine max) cultivars, we conducted a multilocus genome-wide association study (GWAS) on HSW of soybean based on phenotypic data from 20 different environments and genotypic data for 109,676 single-nucleotide polymorphisms (SNPs) in 144 four-way recombinant inbred lines. Using five multilocus GWAS methods, we identified 118 QTNs controlling HSW. Among these, 31 common QTNs were detected by various methods or across multiple environments. Pathway analysis identified three potential candidate genes associated with HSW in soybean. We used allele information to study the common QTNs in 20 large-seed and 20 small-seed lines and identified a higher percentage of superior alleles in the large-seed lines than in small-seed lines. These observations will contribute to construct the gene networks controlling HSW in soybean, which can improve the genetic understanding of HSW, and provide assistance for molecular breeding of soybean large-seed varieties.
Collapse
Affiliation(s)
- Zhongying Qi
- Key Laboratory of Soybean Biology, Ministry of Education, Key Laboratory of Soybean Biology and Breeding/Genetics, Ministry of Agriculture, Northeast Agricultural University, Harbin, China
| | - Jie Song
- Key Laboratory of Soybean Biology, Ministry of Education, Key Laboratory of Soybean Biology and Breeding/Genetics, Ministry of Agriculture, Northeast Agricultural University, Harbin, China
| | - Kaixin Zhang
- Key Laboratory of Soybean Biology, Ministry of Education, Key Laboratory of Soybean Biology and Breeding/Genetics, Ministry of Agriculture, Northeast Agricultural University, Harbin, China
| | - Shulin Liu
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China
| | - Xiaocui Tian
- Key Laboratory of Soybean Biology, Ministry of Education, Key Laboratory of Soybean Biology and Breeding/Genetics, Ministry of Agriculture, Northeast Agricultural University, Harbin, China
| | - Yue Wang
- Key Laboratory of Soybean Biology, Ministry of Education, Key Laboratory of Soybean Biology and Breeding/Genetics, Ministry of Agriculture, Northeast Agricultural University, Harbin, China
| | - Yanlong Fang
- Key Laboratory of Soybean Biology, Ministry of Education, Key Laboratory of Soybean Biology and Breeding/Genetics, Ministry of Agriculture, Northeast Agricultural University, Harbin, China
| | - Xiyu Li
- Key Laboratory of Soybean Biology, Ministry of Education, Key Laboratory of Soybean Biology and Breeding/Genetics, Ministry of Agriculture, Northeast Agricultural University, Harbin, China
| | - Jiajing Wang
- Key Laboratory of Soybean Biology, Ministry of Education, Key Laboratory of Soybean Biology and Breeding/Genetics, Ministry of Agriculture, Northeast Agricultural University, Harbin, China
| | - Chang Yang
- Key Laboratory of Soybean Biology, Ministry of Education, Key Laboratory of Soybean Biology and Breeding/Genetics, Ministry of Agriculture, Northeast Agricultural University, Harbin, China
| | - Sitong Jiang
- Key Laboratory of Soybean Biology, Ministry of Education, Key Laboratory of Soybean Biology and Breeding/Genetics, Ministry of Agriculture, Northeast Agricultural University, Harbin, China
| | - Xu Sun
- Key Laboratory of Soybean Biology, Ministry of Education, Key Laboratory of Soybean Biology and Breeding/Genetics, Ministry of Agriculture, Northeast Agricultural University, Harbin, China
| | - Zhixi Tian
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China
| | - Wenxia Li
- Key Laboratory of Soybean Biology, Ministry of Education, Key Laboratory of Soybean Biology and Breeding/Genetics, Ministry of Agriculture, Northeast Agricultural University, Harbin, China
| | - Hailong Ning
- Key Laboratory of Soybean Biology, Ministry of Education, Key Laboratory of Soybean Biology and Breeding/Genetics, Ministry of Agriculture, Northeast Agricultural University, Harbin, China
| |
Collapse
|
43
|
Weckwerth W, Ghatak A, Bellaire A, Chaturvedi P, Varshney RK. PANOMICS meets germplasm. PLANT BIOTECHNOLOGY JOURNAL 2020; 18:1507-1525. [PMID: 32163658 PMCID: PMC7292548 DOI: 10.1111/pbi.13372] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/07/2019] [Revised: 02/17/2020] [Accepted: 02/26/2020] [Indexed: 05/14/2023]
Abstract
Genotyping-by-sequencing has enabled approaches for genomic selection to improve yield, stress resistance and nutritional value. More and more resource studies are emerging providing 1000 and more genotypes and millions of SNPs for one species covering a hitherto inaccessible intraspecific genetic variation. The larger the databases are growing, the better statistical approaches for genomic selection will be available. However, there are clear limitations on the statistical but also on the biological part. Intraspecific genetic variation is able to explain a high proportion of the phenotypes, but a large part of phenotypic plasticity also stems from environmentally driven transcriptional, post-transcriptional, translational, post-translational, epigenetic and metabolic regulation. Moreover, regulation of the same gene can have different phenotypic outputs in different environments. Consequently, to explain and understand environment-dependent phenotypic plasticity based on the available genotype variation we have to integrate the analysis of further molecular levels reflecting the complete information flow from the gene to metabolism to phenotype. Interestingly, metabolomics platforms are already more cost-effective than NGS platforms and are decisive for the prediction of nutritional value or stress resistance. Here, we propose three fundamental pillars for future breeding strategies in the framework of Green Systems Biology: (i) combining genome selection with environment-dependent PANOMICS analysis and deep learning to improve prediction accuracy for marker-dependent trait performance; (ii) PANOMICS resolution at subtissue, cellular and subcellular level provides information about fundamental functions of selected markers; (iii) combining PANOMICS with genome editing and speed breeding tools to accelerate and enhance large-scale functional validation of trait-specific precision breeding.
Collapse
Affiliation(s)
- Wolfram Weckwerth
- Molecular Systems Biology (MOSYS)Department of Functional and Evolutionary EcologyFaculty of Life SciencesUniversity of ViennaViennaAustria
- Vienna Metabolomics Center (VIME)University of ViennaViennaAustria
| | - Arindam Ghatak
- Molecular Systems Biology (MOSYS)Department of Functional and Evolutionary EcologyFaculty of Life SciencesUniversity of ViennaViennaAustria
| | - Anke Bellaire
- Molecular Systems Biology (MOSYS)Department of Functional and Evolutionary EcologyFaculty of Life SciencesUniversity of ViennaViennaAustria
| | - Palak Chaturvedi
- Molecular Systems Biology (MOSYS)Department of Functional and Evolutionary EcologyFaculty of Life SciencesUniversity of ViennaViennaAustria
| | - Rajeev K. Varshney
- Center of Excellence in Genomics & Systems BiologyInternational Crops Research Institute for the Semi‐Arid Tropics (ICRISAT)HyderabadTelanganaIndia
| |
Collapse
|
44
|
Weckwerth W, Ghatak A, Bellaire A, Chaturvedi P, Varshney RK. PANOMICS meets germplasm. PLANT BIOTECHNOLOGY JOURNAL 2020; 18. [PMID: 32163658 PMCID: PMC7292548 DOI: 10.1111/pbi.13372,10.13140/rg.2.1.1233.5760] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 05/09/2023]
Abstract
Genotyping-by-sequencing has enabled approaches for genomic selection to improve yield, stress resistance and nutritional value. More and more resource studies are emerging providing 1000 and more genotypes and millions of SNPs for one species covering a hitherto inaccessible intraspecific genetic variation. The larger the databases are growing, the better statistical approaches for genomic selection will be available. However, there are clear limitations on the statistical but also on the biological part. Intraspecific genetic variation is able to explain a high proportion of the phenotypes, but a large part of phenotypic plasticity also stems from environmentally driven transcriptional, post-transcriptional, translational, post-translational, epigenetic and metabolic regulation. Moreover, regulation of the same gene can have different phenotypic outputs in different environments. Consequently, to explain and understand environment-dependent phenotypic plasticity based on the available genotype variation we have to integrate the analysis of further molecular levels reflecting the complete information flow from the gene to metabolism to phenotype. Interestingly, metabolomics platforms are already more cost-effective than NGS platforms and are decisive for the prediction of nutritional value or stress resistance. Here, we propose three fundamental pillars for future breeding strategies in the framework of Green Systems Biology: (i) combining genome selection with environment-dependent PANOMICS analysis and deep learning to improve prediction accuracy for marker-dependent trait performance; (ii) PANOMICS resolution at subtissue, cellular and subcellular level provides information about fundamental functions of selected markers; (iii) combining PANOMICS with genome editing and speed breeding tools to accelerate and enhance large-scale functional validation of trait-specific precision breeding.
Collapse
Affiliation(s)
- Wolfram Weckwerth
- Molecular Systems Biology (MOSYS)Department of Functional and Evolutionary EcologyFaculty of Life SciencesUniversity of ViennaViennaAustria
- Vienna Metabolomics Center (VIME)University of ViennaViennaAustria
| | - Arindam Ghatak
- Molecular Systems Biology (MOSYS)Department of Functional and Evolutionary EcologyFaculty of Life SciencesUniversity of ViennaViennaAustria
| | - Anke Bellaire
- Molecular Systems Biology (MOSYS)Department of Functional and Evolutionary EcologyFaculty of Life SciencesUniversity of ViennaViennaAustria
| | - Palak Chaturvedi
- Molecular Systems Biology (MOSYS)Department of Functional and Evolutionary EcologyFaculty of Life SciencesUniversity of ViennaViennaAustria
| | - Rajeev K. Varshney
- Center of Excellence in Genomics & Systems BiologyInternational Crops Research Institute for the Semi‐Arid Tropics (ICRISAT)HyderabadTelanganaIndia
| |
Collapse
|
45
|
Bruce RW, Torkamaneh D, Grainger CM, Belzile F, Eskandari M, Rajcan I. Haplotype diversity underlying quantitative traits in Canadian soybean breeding germplasm. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2020; 133:1967-1976. [PMID: 32193569 DOI: 10.1007/s00122-020-03569-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/18/2019] [Accepted: 02/18/2020] [Indexed: 05/12/2023]
Abstract
KEY MESSAGE Identification of marker-trait associations and trait-associated haplotypes in breeding germplasm identifies regions under selection and highlights changes in haplotype diversity over decades of soybean improvement in Canada. Understanding marker-trait associations using genome-wide association in soybean is typically carried out in diverse germplasm groups where identified loci are often not applicable to soybean breeding efforts. To address this challenge, this study focuses on defining marker-trait associations in breeding germplasm and studying the underlying haplotypes in these regions to assess genetic change through decades of selection. Phenotype data were generated for 175 accessions across multiple environments in Ontario, Canada. A set of 76,549 SNPs were used in the association analysis. A total of 23 genomic regions were identified as significantly associated with yield (5), days to maturity (5), seed oil (3), seed protein (5) and 100-seed weight (5), of which 14 are novel. Each significant region was haplotyped to assess haplotype diversity of the underlying genomic region, identifying ten regions with trait-associated haplotypes in the breeding germplasm. The range of genomic length for these regions (7.2 kb to 6.8 Mb) indicates variation in regional LD for the trait-associated regions. Six of these regions showed changes between eras of breeding, from historical to modern and experimental soybean accessions. Continued selection on these regions may necessitate introgression of novel parental genetic diversity as some haplotypes were fixed within the breeding germplasm. This finding highlights the importance of studying associations and haplotype diversity at a breeding program scale to understand breeders' selections and trends in soybean improvement over time. The haplotypes may also be used as a tool for selection of parental germplasm to inform breeder's decisions on further soybean improvement.
Collapse
Affiliation(s)
- Robert W Bruce
- Department of Plant Agriculture, University of Guelph, Guelph, ON, Canada
| | - Davoud Torkamaneh
- Department of Plant Agriculture, University of Guelph, Guelph, ON, Canada
- Département de Phytologie, Université Laval, Quebec City, QC, Canada
- Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Quebec City, QC, Canada
| | | | - François Belzile
- Département de Phytologie, Université Laval, Quebec City, QC, Canada
- Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Quebec City, QC, Canada
| | - Milad Eskandari
- Department of Plant Agriculture, University of Guelph, Guelph, ON, Canada
| | - Istvan Rajcan
- Department of Plant Agriculture, University of Guelph, Guelph, ON, Canada.
| |
Collapse
|
46
|
Sun M, Jing Y, Zhao X, Teng W, Qiu L, Zheng H, Li W, Han Y. Genome-wide association study of partial resistance to sclerotinia stem rot of cultivated soybean based on the detached leaf method. PLoS One 2020; 15:e0233366. [PMID: 32421759 PMCID: PMC7233537 DOI: 10.1371/journal.pone.0233366] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2019] [Accepted: 05/04/2020] [Indexed: 12/12/2022] Open
Abstract
Sclerotinia stem rot (SSR) is a devastating fungal disease that causes severe yield losses of soybean worldwide. In the present study, a representative population of 185 soybean accessions was selected and utilized to identify the quantitative trait nucleotide (QTN) of partial resistance to soybean SSR via a genome-wide association study (GWAS). A total of 22,048 single-nucleotide polymorphisms (SNPs) with minor allele frequencies (MAF) > 5% and missing data < 3% were used to assess linkage disequilibrium (LD) levels. Association signals associated with SSR partial resistance were identified by two models, including compressed mixed linear model (CMLM) and multi-locus random-SNP-effect mixed linear model (mrMLM). Finally, seven QTNs with major effects (a known locus and six novel loci) via CMLM and nine novel QTNs with minor effects via mrMLM were detected in relation to partial resistance to SSR, respectively. One of all the novel loci (Gm05:14834789 on Chr.05), which was co-located by these two methods, might be a stable one that showed high significance in SSR partial resistance. Additionally, a total of 71 major and 85 minor candidate genes located in the 200-kb genomic region of each peak SNP detected by CMLM and mrMLM were found, respectively. By using a gene-based association, a total of six SNPs from three major effects genes and eight SNPs from four minor effects genes were identified. Of them, Glyma.18G012200 has been characterized as a significant element in controlling fungal disease in plants.
Collapse
Affiliation(s)
- Mingming Sun
- Key Laboratory of Soybean Biology in Chinese Ministry of Education (key Laboratory of Soybean Biology and Breeding/Genetics of Chinese Agriculture Ministry), Northeast Agricultural University, Harbin, China
- Heilongjiang Journal Press of Agricultural Science and Technology, Heilongjiang Academy of Agricultural Sciences, Harbin, China
| | - Yan Jing
- Key Laboratory of Soybean Biology in Chinese Ministry of Education (key Laboratory of Soybean Biology and Breeding/Genetics of Chinese Agriculture Ministry), Northeast Agricultural University, Harbin, China
| | - Xue Zhao
- Key Laboratory of Soybean Biology in Chinese Ministry of Education (key Laboratory of Soybean Biology and Breeding/Genetics of Chinese Agriculture Ministry), Northeast Agricultural University, Harbin, China
| | - Weili Teng
- Key Laboratory of Soybean Biology in Chinese Ministry of Education (key Laboratory of Soybean Biology and Breeding/Genetics of Chinese Agriculture Ministry), Northeast Agricultural University, Harbin, China
| | - Lijuan Qiu
- Institute of Crop Science, National Key Facility for Crop Gene Resources and Genetic Improvement (NFCRI) Chinese Academy of Agricultural Sciences, Beijing, China
| | - Hongkun Zheng
- Bioinformatics Division, Biomarker Technologies Corporation, Beijing, China
| | - Wenbin Li
- Key Laboratory of Soybean Biology in Chinese Ministry of Education (key Laboratory of Soybean Biology and Breeding/Genetics of Chinese Agriculture Ministry), Northeast Agricultural University, Harbin, China
| | - Yingpeng Han
- Key Laboratory of Soybean Biology in Chinese Ministry of Education (key Laboratory of Soybean Biology and Breeding/Genetics of Chinese Agriculture Ministry), Northeast Agricultural University, Harbin, China
| |
Collapse
|
47
|
Haplotype-Based Genome-Wide Association Study and Identification of Candidate Genes Associated with Carcass Traits in Hanwoo Cattle. Genes (Basel) 2020; 11:genes11050551. [PMID: 32423003 PMCID: PMC7290854 DOI: 10.3390/genes11050551] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2020] [Revised: 04/30/2020] [Accepted: 05/05/2020] [Indexed: 12/20/2022] Open
Abstract
Hanwoo, is the most popular native beef cattle in South Korea. Due to its extensive popularity, research is ongoing to enhance its carcass quality and marbling traits. In this study we conducted a haplotype-based genome-wide association study (GWAS) by constructing haplotype blocks by three methods: number of single nucleotide polymorphisms (SNPs) in a haplotype block (nsnp), length of genomic region in kb (Len) and linkage disequilibrium (LD). Significant haplotype blocks and genes associated with them were identified for carcass traits such as BFT (back fat thickness), EMA (eye Muscle area), CWT (carcass weight) and MS (marbling score). Gene-set enrichment analysis and functional annotation of genes in the significantly-associated loci revealed candidate genes, including PLCB1 and PLCB4 present on BTA13, coding for phospholipases, which might be important candidates for increasing fat deposition due to their role in lipid metabolism and adipogenesis. CEL (carboxyl ester lipase), a bile-salt activated lipase, responsible for lipid catabolic process was also identified within the significantly-associated haplotype block on BTA11. The results were validated in a different Hanwoo population. The genes and pathways identified in this study may serve as good candidates for improving carcass traits in Hanwoo cattle.
Collapse
|
48
|
Wang L, Yang Y, Zhang S, Che Z, Yuan W, Yu D. GWAS reveals two novel loci for photosynthesis-related traits in soybean. Mol Genet Genomics 2020; 295:705-716. [PMID: 32166500 DOI: 10.1007/s00438-020-01661-1] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2019] [Accepted: 02/27/2020] [Indexed: 10/24/2022]
Abstract
Photosynthesis plays an extremely important role throughout the life cycle of plants. Improving the photosynthetic rate is a major target for increasing crop productivity. This study was conducted to identify single nucleotide polymorphisms (SNPs) associated with the net photosynthetic rate (Pn), stomatal conductance (Cond), intercellular carbon dioxide concentration (Ci) and transpiration rate (Trmmol) through genome-wide association study (GWAS) and to inspect the relationships among these traits in soybean (Glycine max (L.) Merr.). A population of 219 soybean accessions was used in this research. A total of 12 quantitative trait loci (QTLs) associated with Pn, Cond, Ci and Trmmol were detected and distributed on chromosomes 1, 2, 6, 7, 9, 11, 12, 13, 15, 16, 18, and 19, and some of these QTL overlapped with previously reported QTLs. Furthermore, four candidate genes were identified, and there were significantly different expression levels between the high-light-efficiency accessions and low-light-efficiency accessions. These putative genes may participate in the regulation of photosynthesis through different metabolic pathways. Therefore, the associated novel QTLs and candidate genes detected in this study will provide a theoretical basis for genetic studies of photosynthesis and provide new avenues for crop improvement.
Collapse
Affiliation(s)
- Li Wang
- National Center for Soybean Improvement, National Key Laboratory of Crop Genetics and Germplasm Enhancement, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, 210095, China
| | - Yuming Yang
- National Center for Soybean Improvement, National Key Laboratory of Crop Genetics and Germplasm Enhancement, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, 210095, China
| | - Shuyu Zhang
- National Center for Soybean Improvement, National Key Laboratory of Crop Genetics and Germplasm Enhancement, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, 210095, China
| | - Zhijun Che
- School of Life Sciences, Guangzhou University, Guangzhou, 510006, China
| | - Wenjie Yuan
- National Center for Soybean Improvement, National Key Laboratory of Crop Genetics and Germplasm Enhancement, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, 210095, China
| | - Deyue Yu
- National Center for Soybean Improvement, National Key Laboratory of Crop Genetics and Germplasm Enhancement, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, 210095, China.
| |
Collapse
|
49
|
Yao M, Guan M, Zhang Z, Zhang Q, Cui Y, Chen H, Liu W, Jan HU, Voss-Fels KP, Werner CR, He X, Liu Z, Guan C, Snowdon RJ, Hua W, Qian L. GWAS and co-expression network combination uncovers multigenes with close linkage effects on the oleic acid content accumulation in Brassica napus. BMC Genomics 2020; 21:320. [PMID: 32326904 PMCID: PMC7181522 DOI: 10.1186/s12864-020-6711-0] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2019] [Accepted: 03/31/2020] [Indexed: 11/19/2022] Open
Abstract
Background Strong artificial and natural selection causes the formation of highly conserved haplotypes that harbor agronomically important genes. GWAS combination with haplotype analysis has evolved as an effective method to dissect the genetic architecture of complex traits in crop species. Results We used the 60 K Brassica Infinium SNP array to perform a genome-wide analysis of haplotype blocks associated with oleic acid (C18:1) in rapeseed. Six haplotype regions were identified as significantly associated with oleic acid (C18:1) that mapped to chromosomes A02, A07, A08, C01, C02, and C03. Additionally, whole-genome sequencing of 50 rapeseed accessions revealed three genes (BnmtACP2-A02, BnABCI13-A02 and BnECI1-A02) in the A02 chromosome haplotype region and two genes (BnFAD8-C02 and BnSDP1-C02) in the C02 chromosome haplotype region that were closely linked to oleic acid content phenotypic variation. Moreover, the co-expression network analysis uncovered candidate genes from these two different haplotype regions with potential regulatory interrelationships with oleic acid content accumulation. Conclusions Our results suggest that several candidate genes are closely linked, which provides us with an opportunity to develop functional haplotype markers for the improvement of the oleic acid content in rapeseed.
Collapse
Affiliation(s)
- Min Yao
- Collaborative Innovation Center of Grain and Oil Crops in South China, Hunan Agricultural University, Changsha, 410128, China
| | - Mei Guan
- Collaborative Innovation Center of Grain and Oil Crops in South China, Hunan Agricultural University, Changsha, 410128, China
| | - Zhenqian Zhang
- Collaborative Innovation Center of Grain and Oil Crops in South China, Hunan Agricultural University, Changsha, 410128, China
| | - Qiuping Zhang
- Collaborative Innovation Center of Grain and Oil Crops in South China, Hunan Agricultural University, Changsha, 410128, China
| | - Yixin Cui
- College of Horticulture and Landscape Architecture, Southwest University, Chongqing, 400715, China
| | - Hao Chen
- Collaborative Innovation Center of Grain and Oil Crops in South China, Hunan Agricultural University, Changsha, 410128, China
| | - Wei Liu
- Collaborative Innovation Center of Grain and Oil Crops in South China, Hunan Agricultural University, Changsha, 410128, China
| | - Habib U Jan
- Precision Medicine Lab, Rehman Medical Institute (RMI), Phase 5, Hayatabad, Peshawar, 25000, Pakistan
| | - Kai P Voss-Fels
- Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, St Lucia, QLD, Australia
| | - Christian R Werner
- The Roslin Institute University of Edinburgh Easter Bush Research Centre Midlothian, Edinburgh, EH25 9RG, UK
| | - Xin He
- Collaborative Innovation Center of Grain and Oil Crops in South China, Hunan Agricultural University, Changsha, 410128, China
| | - Zhongsong Liu
- Collaborative Innovation Center of Grain and Oil Crops in South China, Hunan Agricultural University, Changsha, 410128, China
| | - Chunyun Guan
- Collaborative Innovation Center of Grain and Oil Crops in South China, Hunan Agricultural University, Changsha, 410128, China
| | - Rod J Snowdon
- Department of Plant Breeding, IFZ Research Centre for Biosystems, Land Use and Nutrition, Justus Liebig University, Heinrich-Buff-Ring 26-32, 35392, Giessen, Germany
| | - Wei Hua
- Collaborative Innovation Center of Grain and Oil Crops in South China, Hunan Agricultural University, Changsha, 410128, China. .,Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Wuhan, 430062, China.
| | - Lunwen Qian
- Collaborative Innovation Center of Grain and Oil Crops in South China, Hunan Agricultural University, Changsha, 410128, China.
| |
Collapse
|
50
|
Steketee CJ, Schapaugh WT, Carter TE, Li Z. Genome-Wide Association Analyses Reveal Genomic Regions Controlling Canopy Wilting in Soybean. G3 (BETHESDA, MD.) 2020; 10:1413-1425. [PMID: 32111650 PMCID: PMC7144087 DOI: 10.1534/g3.119.401016] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/23/2019] [Accepted: 02/20/2020] [Indexed: 12/27/2022]
Abstract
Drought stress causes the greatest soybean [Glycine max (L.) Merr.] yield losses among the abiotic stresses in rain-fed U.S. growing areas. Because less than 10% of U.S. soybean hectares are irrigated, combating this stress requires soybean plants which possess physiological mechanisms to tolerate drought for a period of time. Phenotyping for these mechanisms is challenging, and the genetic architecture for these traits is poorly understood. A morphological trait, slow or delayed canopy wilting, has been observed in a few exotic plant introductions (PIs), and may lead to yield improvement in drought stressed fields. In this study, we visually scored wilting during stress for a panel of 162 genetically diverse maturity group VI-VIII soybean lines genotyped with the SoySNP50K iSelect BeadChip. Field evaluation of canopy wilting was conducted under rain-fed conditions at two locations (Athens, GA and Salina, KS) in 2015 and 2016. Substantial variation in canopy wilting was observed among the genotypes. Using a genome-wide association mapping approach, 45 unique SNPs that tagged 44 loci were associated with canopy wilting in at least one environment with one region identified in a single environment and data from across all environments. Several new soybean accessions were identified with canopy wilting superior to those of check genotypes. The germplasm and genomic regions identified can be used to better understand the slow canopy wilting trait and be incorporated into elite germplasm to improve drought tolerance in soybean.
Collapse
Affiliation(s)
- Clinton J Steketee
- Institute of Plant Breeding, Genetics, and Genomics and Department of Crop and Soil Sciences, The University of Georgia, Athens, GA, 30602
| | | | - Thomas E Carter
- Department of Crop and Soil Sciences, North Carolina State University, USDA-ARS, Raleigh, NC, 27607
| | - Zenglu Li
- Institute of Plant Breeding, Genetics, and Genomics and Department of Crop and Soil Sciences, The University of Georgia, Athens, GA, 30602
| |
Collapse
|