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Khojasteh M, Darzi Ramandi H, Taghavi SM, Taheri A, Rahmanzadeh A, Chen G, Foolad MR, Osdaghi E. Unraveling the genetic basis of quantitative resistance to diseases in tomato: a meta-QTL analysis and mining of transcript profiles. PLANT CELL REPORTS 2024; 43:184. [PMID: 38951262 DOI: 10.1007/s00299-024-03268-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: 11/18/2023] [Accepted: 06/11/2024] [Indexed: 07/03/2024]
Abstract
KEY MESSAGE Whole-genome QTL mining and meta-analysis in tomato for resistance to bacterial and fungal diseases identified 73 meta-QTL regions with significantly refined/reduced confidence intervals. Tomato production is affected by a range of biotic stressors, causing yield losses and quality reductions. While sources of genetic resistance to many tomato diseases have been identified and characterized, stability of the resistance genes or quantitative trait loci (QTLs) across the resources has not been determined. Here, we examined 491 QTLs previously reported for resistance to tomato diseases in 40 independent studies and 54 unique mapping populations. We identified 29 meta-QTLs (MQTLs) for resistance to bacterial pathogens and 44 MQTLs for resistance to fungal pathogens, and were able to reduce the average confidence interval (CI) of the QTLs by 4.1-fold and 6.7-fold, respectively, compared to the average CI of the original QTLs. The corresponding physical length of the CIs of MQTLs ranged from 56 kb to 6.37 Mb, with a median of 921 kb, of which 27% had a CI lower than 500 kb and 53% had a CI lower than 1 Mb. Comparison of defense responses between tomato and Arabidopsis highlighted 73 orthologous genes in the MQTL regions, which were putatively determined to be involved in defense against bacterial and fungal diseases. Intriguingly, multiple genes were identified in some MQTL regions that are implicated in plant defense responses, including PR-P2, NDR1, PDF1.2, Pip1, SNI1, PTI5, NSL1, DND1, CAD1, SlACO, DAD1, SlPAL, Ph-3, EDS5/SID1, CHI-B/PR-3, Ph-5, ETR1, WRKY29, and WRKY25. Further, we identified a number of candidate resistance genes in the MQTL regions that can be useful for both marker/gene-assisted breeding as well as cloning and genetic transformation.
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Affiliation(s)
- Moein Khojasteh
- Department of Plant Protection, School of Agriculture, Shiraz University, Shiraz, 71441-65186, Iran
- School of Agriculture and Biology/State Key Laboratory of Microbial Metabolism, Shanghai Jiao Tong University, Shanghai, 200240, China
- Department of Plant Protection, University of Tehran, Karaj, 31587-77871, Iran
| | - Hadi Darzi Ramandi
- Department of Plant Production and Genetics, Faculty of Agriculture, Bu-Ali Sina University, P.O. Box 657833131, Hamedan, Iran
- Department of Molecular Physiology, Agricultural Biotechnology Research Institute of Iran, Agricultural Research Education and Extension Organization (AREEO), Karaj, Iran
| | - S Mohsen Taghavi
- Department of Plant Protection, School of Agriculture, Shiraz University, Shiraz, 71441-65186, Iran.
| | - Ayat Taheri
- Joint International Research Laboratory of Metabolic and Developmental Sciences, Plant Biotechnology Research Center, Fudan-SJTU-Nottingham Plant Biotechnology R&D Center, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, China
| | - Asma Rahmanzadeh
- Department of Plant Protection, School of Agriculture, Shiraz University, Shiraz, 71441-65186, Iran
- Department of Plant Protection, University of Tehran, Karaj, 31587-77871, Iran
| | - Gongyou Chen
- School of Agriculture and Biology/State Key Laboratory of Microbial Metabolism, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Majid R Foolad
- Department of Plant Science and the Intercollege Graduate Degree Program in Plant Biology, The Pennsylvania State University, University Park, PA, 16802, USA.
| | - Ebrahim Osdaghi
- Department of Plant Protection, University of Tehran, Karaj, 31587-77871, Iran.
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Du B, Wu J, Wang Q, Sun C, Sun G, Zhou J, Zhang L, Xiong Q, Ren X, Lu B. Genome-wide screening of meta-QTL and candidate genes controlling yield and yield-related traits in barley (Hordeum vulgare L.). PLoS One 2024; 19:e0303751. [PMID: 38768114 PMCID: PMC11104655 DOI: 10.1371/journal.pone.0303751] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Accepted: 04/30/2024] [Indexed: 05/22/2024] Open
Abstract
Increasing yield is an important goal of barley breeding. In this study, 54 papers published from 2001-2022 on QTL mapping for yield and yield-related traits in barley were collected, which contained 1080 QTLs mapped to the barley high-density consensus map for QTL meta-analysis. These initial QTLs were integrated into 85 meta-QTLs (MQTL) with a mean confidence interval (CI) of 2.76 cM, which was 7.86-fold narrower than the CI of the initial QTL. Among these 85 MQTLs, 68 MQTLs were validated in GWAS studies, and 25 breeder's MQTLs were screened from them. Seventeen barley orthologs of yield-related genes in rice and maize were identified within the hcMQTL region based on comparative genomics strategy and were presumed to be reliable candidates for controlling yield-related traits. The results of this study provide useful information for molecular marker-assisted breeding and candidate gene mining of yield-related traits in barley.
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Affiliation(s)
- Binbin Du
- College of Biotechnology and Pharmaceutical Engineering, West Anhui University, Lu’an, China
| | - Jia Wu
- College of Biotechnology and Pharmaceutical Engineering, West Anhui University, Lu’an, China
| | | | - Chaoyue Sun
- College of Biotechnology and Pharmaceutical Engineering, West Anhui University, Lu’an, China
| | - Genlou Sun
- Biology Department, Saint Mary’s University, Halifax, Canada
| | - Jie Zhou
- Lu’an Academy of Agricultural Science, Lu’an, China
| | - Lei Zhang
- Lu’an Academy of Agricultural Science, Lu’an, China
| | | | - Xifeng Ren
- Hubei Hongshan Laboratory, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, China
| | - Baowei Lu
- College of Biotechnology and Pharmaceutical Engineering, West Anhui University, Lu’an, China
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3
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Aloryi KD, Okpala NE, Guo H, Karikari B, Amo A, Bello SF, Saini DK, Akaba S, Tian X. Integrated meta-analysis and transcriptomics pinpoint genomic loci and novel candidate genes associated with submergence tolerance in rice. BMC Genomics 2024; 25:338. [PMID: 38575927 PMCID: PMC10993490 DOI: 10.1186/s12864-024-10219-z] [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: 11/13/2023] [Accepted: 03/13/2024] [Indexed: 04/06/2024] Open
Abstract
BACKGROUND Due to rising costs, water shortages, and labour shortages, farmers across the globe now prefer a direct seeding approach. However, submergence stress remains a major bottleneck limiting the success of this approach in rice cultivation. The merger of accumulated rice genetic resources provides an opportunity to detect key genomic loci and candidate genes that influence the flooding tolerance of rice. RESULTS In the present study, a whole-genome meta-analysis was conducted on 120 quantitative trait loci (QTL) obtained from 16 independent QTL studies reported from 2004 to 2023. These QTL were confined to 18 meta-QTL (MQTL), and ten MQTL were successfully validated by independent genome-wide association studies from diverse natural populations. The mean confidence interval (CI) of the identified MQTL was 3.44 times narrower than the mean CI of the initial QTL. Moreover, four core MQTL loci with genetic distance less than 2 cM were obtained. By combining differentially expressed genes (DEG) from two transcriptome datasets with 858 candidate genes identified in the core MQTL regions, we found 38 common differentially expressed candidate genes (DECGs). In silico expression analysis of these DECGs led to the identification of 21 genes with high expression in embryo and coleoptile under submerged conditions. These DECGs encode proteins with known functions involved in submergence tolerance including WRKY, F-box, zinc fingers, glycosyltransferase, protein kinase, cytochrome P450, PP2C, hypoxia-responsive family, and DUF domain. By haplotype analysis, the 21 DECGs demonstrated distinct genetic differentiation and substantial genetic distance mainly between indica and japonica subspecies. Further, the MQTL7.1 was successfully validated using flanked marker S2329 on a set of genotypes with phenotypic variation. CONCLUSION This study provides a new perspective on understanding the genetic basis of submergence tolerance in rice. The identified MQTL and novel candidate genes lay the foundation for marker-assisted breeding/engineering of flooding-tolerant cultivars conducive to direct seeding.
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Grants
- 2023AFA022 Hubei Provincial Natural Science Foundation of China
- 2023AFA022 Hubei Provincial Natural Science Foundation of China
- 2023AFA022 Hubei Provincial Natural Science Foundation of China
- 2023AFA022 Hubei Provincial Natural Science Foundation of China
- 2023AFA022 Hubei Provincial Natural Science Foundation of China
- 2023AFA022 Hubei Provincial Natural Science Foundation of China
- 2023AFA022 Hubei Provincial Natural Science Foundation of China
- 2023AFA022 Hubei Provincial Natural Science Foundation of China
- 2023AFA022 Hubei Provincial Natural Science Foundation of China
- 2020BBB060 Key R&D Project in Hubei Province, China
- 2020BBB060 Key R&D Project in Hubei Province, China
- 2020BBB060 Key R&D Project in Hubei Province, China
- 2020BBB060 Key R&D Project in Hubei Province, China
- 2020BBB060 Key R&D Project in Hubei Province, China
- 2020BBB060 Key R&D Project in Hubei Province, China
- 2020BBB060 Key R&D Project in Hubei Province, China
- 2020BBB060 Key R&D Project in Hubei Province, China
- 2020BBB060 Key R&D Project in Hubei Province, China
- 2018YFD0301306 the National Key Research and Development Program of China
- 2018YFD0301306 the National Key Research and Development Program of China
- 2018YFD0301306 the National Key Research and Development Program of China
- 2018YFD0301306 the National Key Research and Development Program of China
- 2018YFD0301306 the National Key Research and Development Program of China
- 2018YFD0301306 the National Key Research and Development Program of China
- 2018YFD0301306 the National Key Research and Development Program of China
- 2018YFD0301306 the National Key Research and Development Program of China
- 2018YFD0301306 the National Key Research and Development Program of China
- Key R&D Project in Hubei Province, China
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Affiliation(s)
- Kelvin Dodzi Aloryi
- Hubei Collaborative Innovation Centre for Grain Industry, College of Agriculture, Yangtze University, Jingzhou, China
| | - Nnaemeka Emmanuel Okpala
- Hubei Collaborative Innovation Centre for Grain Industry, College of Agriculture, Yangtze University, Jingzhou, China
| | - Hong Guo
- University of Chinese Academy of Sciences, 100049, Beijing, China
| | - Benjamin Karikari
- Département de phytologie, Université Laval, Québec, QC, Canada
- Department of Agricultural Biotechnology, Faculty of Agriculture, Food and Consumer Sciences, University for Development Studies, Tamale, Ghana
| | - Aduragbemi Amo
- Department of Horticultural Sciences, Texas A&M University, College Station, TX, USA
- Texas A&M AgriLife Research and Extension Center, Weslaco, TX, USA
| | - Semiu Folaniyi Bello
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, South China Agricultural University, Guangzhou, Guangdong, China
| | - Dinesh Kumar Saini
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
- Department of Plant and Soil Science, Texas Tech University, Lubbock, TX, USA
| | - Selorm Akaba
- School of Agriculture, University of Cape Coast, Cape Coast, Ghana
| | - Xiaohai Tian
- Hubei Collaborative Innovation Centre for Grain Industry, College of Agriculture, Yangtze University, Jingzhou, China.
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Satasiya P, Patel S, Patel R, Raigar OP, Modha K, Parekh V, Joshi H, Patel V, Chaudhary A, Sharma D, Prajapati M. Meta-analysis of identified genomic regions and candidate genes underlying salinity tolerance in rice (Oryza sativa L.). Sci Rep 2024; 14:5730. [PMID: 38459066 PMCID: PMC10923909 DOI: 10.1038/s41598-024-54764-9] [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: 02/13/2023] [Accepted: 02/16/2024] [Indexed: 03/10/2024] Open
Abstract
Rice output has grown globally, yet abiotic factors are still a key cause for worry. Salinity stress seems to have the more impact on crop production out of all abiotic stresses. Currently one of the most significant challenges in paddy breeding for salinity tolerance with the help of QTLs, is to determine the QTLs having the best chance of improving salinity tolerance with the least amount of background noise from the tolerant parent. Minimizing the size of the QTL confidence interval (CI) is essential in order to primarily include the genes responsible for salinity stress tolerance. By considering that, a genome-wide meta-QTL analysis on 768 QTLs from 35 rice populations published from 2001 to 2022 was conducted to identify consensus regions and the candidate genes underlying those regions responsible for the salinity tolerance, as it reduces the confidence interval (CI) to many folds from the initial QTL studies. In the present investigation, a total of 65 MQTLs were extracted with an average CI reduced from 17.35 to 1.66 cM including the smallest of 0.01 cM. Identification of the MQTLs for individual traits and then classifying the target traits into correlated morphological, physiological and biochemical aspects, resulted in more efficient interpretation of the salinity tolerance, identifying the candidate genes and to understand the salinity tolerance mechanism as a whole. The results of this study have a huge potential to improve the rice genotypes for salinity tolerance with the help of MAS and MABC.
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Affiliation(s)
- Pratik Satasiya
- Department of Genetics and Plant Breeding, N. M. College of Agriculture, Navsari Agricultural University, Navsari, Gujarat, India
| | - Sanyam Patel
- Department of Genetics and Plant Breeding, N. M. College of Agriculture, Navsari Agricultural University, Navsari, Gujarat, India
| | - Ritesh Patel
- Department of Genetics and Plant Breeding, N. M. College of Agriculture, Navsari Agricultural University, Navsari, Gujarat, India
| | - Om Prakash Raigar
- School of Agricultural Biotechnology, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Kaushal Modha
- Department of Genetics and Plant Breeding, N. M. College of Agriculture, Navsari Agricultural University, Navsari, Gujarat, India
| | - Vipul Parekh
- Department of Biotechnology, College of Forestry, Navsari Agricultural University, Navsari, Gujarat, India
| | - Haimil Joshi
- Coastal Soil Salinity Research Station Danti-Umbharat, Navsari Agricultural University, Navsari, Gujarat, India
| | - Vipul Patel
- Regional Rice Research Station, Vyara, Navsari Agricultural University, Navsari, Gujarat, India
| | - Ankit Chaudhary
- Kishorbhai Institute of Agriculture Sciences and Research Centre, Uka Tarsadia University, Bardoli, Gujarat, India.
| | - Deepak Sharma
- Department of Genetics and Plant Breeding, N. M. College of Agriculture, Navsari Agricultural University, Navsari, Gujarat, India
| | - Maulik Prajapati
- Department of Genetics and Plant Breeding, N. M. College of Agriculture, Navsari Agricultural University, Navsari, Gujarat, India
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5
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Du B, Wu J, Wang M, Wu J, Sun C, Zhang X, Ren X, Wang Q. Detection of consensus genomic regions and candidate genes for quality traits in barley using QTL meta-analysis. FRONTIERS IN PLANT SCIENCE 2024; 14:1319889. [PMID: 38283973 PMCID: PMC10811794 DOI: 10.3389/fpls.2023.1319889] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Accepted: 12/26/2023] [Indexed: 01/30/2024]
Abstract
Improving barley grain quality is a major goal in barley breeding. In this study, a total of 35 papers focusing on quantitative trait loci (QTLs) mapping for barley quality traits published since 2000 were collected. Among the 454 QTLs identified in these studies, 349 of them were mapped onto high-density consensus maps, which were used for QTL meta-analysis. Through QTL meta-analysis, the initial QTLs were integrated into 41 meta-QTLs (MQTLs) with an average confidence interval (CI) of 1. 66 cM, which is 88.9% narrower than that of the initial QTLs. Among the 41 identified MQTLs, 25 were subsequently validated in publications using genome-wide association study (GWAS). From these 25 validated MQTLs, ten breeder's MQTLs were selected. Synteny analysis comparing barley and wheat MQTLs revealed orthologous relationships between eight breeder's MQTLs and 45 wheat MQTLs. Additionally, 17 barley homologs associated with rice quality traits were identified within the regions of the breeder's MQTLs through comparative analysis. The findings of this study provide valuable insights for molecular marker-assisted breeding and the identification of candidate genes related to quality traits in barley.
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Affiliation(s)
- Binbin Du
- College of Biotechnology and Pharmaceutical Engineering, West Anhui University, Lu’an, Anhui, China
| | - Jindong Wu
- College of Biotechnology and Pharmaceutical Engineering, West Anhui University, Lu’an, Anhui, China
| | - Meng Wang
- Xingtai Agriculture and Rural Bureau, Xingtai, Hebei, China
| | - Jia Wu
- College of Biotechnology and Pharmaceutical Engineering, West Anhui University, Lu’an, Anhui, China
| | - Chaoyue Sun
- College of Biotechnology and Pharmaceutical Engineering, West Anhui University, Lu’an, Anhui, China
| | - Xingen Zhang
- College of Biotechnology and Pharmaceutical Engineering, West Anhui University, Lu’an, Anhui, China
| | - Xifeng Ren
- Hubei Hongshan Laboratory, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, Hubei, China
| | - Qifei Wang
- Institute of Crop and Nuclear Technology Utilization, Zhejiang Academy of Agricultural Sciences, Hangzhou, Zhejiang, China
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Sharma D, Kumari A, Sharma P, Singh A, Sharma A, Mir ZA, Kumar U, Jan S, Parthiban M, Mir RR, Bhati P, Pradhan AK, Yadav A, Mishra DC, Budhlakoti N, Yadav MC, Gaikwad KB, Singh AK, Singh GP, Kumar S. Meta-QTL analysis in wheat: progress, challenges and opportunities. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2023; 136:247. [PMID: 37975911 DOI: 10.1007/s00122-023-04490-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Accepted: 10/16/2023] [Indexed: 11/19/2023]
Abstract
Wheat, an important cereal crop globally, faces major challenges due to increasing global population and changing climates. The production and productivity are challenged by several biotic and abiotic stresses. There is also a pressing demand to enhance grain yield and quality/nutrition to ensure global food and nutritional security. To address these multifaceted concerns, researchers have conducted numerous meta-QTL (MQTL) studies in wheat, resulting in the identification of candidate genes that govern these complex quantitative traits. MQTL analysis has successfully unraveled the complex genetic architecture of polygenic quantitative traits in wheat. Candidate genes associated with stress adaptation have been pinpointed for abiotic and biotic traits, facilitating targeted breeding efforts to enhance stress tolerance. Furthermore, high-confidence candidate genes (CGs) and flanking markers to MQTLs will help in marker-assisted breeding programs aimed at enhancing stress tolerance, yield, quality and nutrition. Functional analysis of these CGs can enhance our understanding of intricate trait-related genetics. The discovery of orthologous MQTLs shared between wheat and other crops sheds light on common evolutionary pathways governing these traits. Breeders can leverage the most promising MQTLs and CGs associated with multiple traits to develop superior next-generation wheat cultivars with improved trait performance. This review provides a comprehensive overview of MQTL analysis in wheat, highlighting progress, challenges, validation methods and future opportunities in wheat genetics and breeding, contributing to global food security and sustainable agriculture.
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Affiliation(s)
- Divya Sharma
- ICAR-National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, India
| | - Anita Kumari
- Department of Botany, University of Delhi, Delhi, India
| | - Priya Sharma
- Department of Botany, University of Delhi, Delhi, India
| | - Anupma Singh
- ICAR-National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, India
| | - Anshu Sharma
- ICAR-National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, India
| | - Zahoor Ahmad Mir
- ICAR-National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, India
| | - Uttam Kumar
- Borlaug Institute for South Asia (BISA), Ludhiana, India
| | - Sofora Jan
- Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir (SKUAST-K), Srinagar, Kashmir, India
| | - M Parthiban
- Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir (SKUAST-K), Srinagar, Kashmir, India
| | - Reyazul Rouf Mir
- Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir (SKUAST-K), Srinagar, Kashmir, India
| | - Pradeep Bhati
- Borlaug Institute for South Asia (BISA), Ludhiana, India
| | - Anjan Kumar Pradhan
- ICAR-National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, India
| | - Aakash Yadav
- ICAR-National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, India
| | | | - Neeraj Budhlakoti
- ICAR- Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Mahesh C Yadav
- ICAR-National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, India
| | - Kiran B Gaikwad
- Division of Genetics, Indian Council of Agricultural Research (ICAR)-Indian Agricultural Research Institute, New Delhi, India
| | - Amit Kumar Singh
- ICAR-National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, India
| | | | - Sundeep Kumar
- ICAR-National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, India.
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7
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Peng S, Liu Y, Xu Y, Zhao J, Gao P, Liu Q, Yan S, Xiao Y, Zuo SM, Kang H. Genome-Wide Association Study Identifies a Plant-Height-Associated Gene OsPG3 in a Population of Commercial Rice Varieties. Int J Mol Sci 2023; 24:11454. [PMID: 37511211 PMCID: PMC10380248 DOI: 10.3390/ijms241411454] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Revised: 07/05/2023] [Accepted: 07/11/2023] [Indexed: 07/30/2023] Open
Abstract
Plant height is one of the most crucial components of plant structure. However, due to its complexity, the genetic architecture of rice plant height has not been fully elucidated. In this study, we performed a genome-wide association study (GWAS) to determine rice plant height using 178 commercial rice varieties and identified 37 loci associated with rice plant height (LAPH). Among these loci, in LAPH2, we identified a polygalacturonase gene, OsPG3, which was genetically and functionally associated with rice plant height. The rice plant exhibits a super dwarf phenotype when the knockout of the OsPG3 gene occurs via CRISPR-Cas9 gene-editing technology. RNA-Seq analysis indicated that OsPG3 modulates the expression of genes involved in phytohormone metabolism and cell-wall-biosynthesis pathways. Our findings suggest that OsPG3 plays a vital role in controlling rice plant height by regulating cell wall biosynthesis. Given that rice architecture is one of the most critical phenotypes in rice breeding, OsPG3 has potential in rice's molecular design breeding toward an ideal plant height.
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Affiliation(s)
- Shasha Peng
- College of Agronomy, Hunan Agricultural University, Changsha 410128, China
- State Key Laboratory for Biology of Plant Diseases and Insect Pests, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Yanchen Liu
- State Key Laboratory for Biology of Plant Diseases and Insect Pests, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Yuchen Xu
- College of Agronomy, Hunan Agricultural University, Changsha 410128, China
- State Key Laboratory for Biology of Plant Diseases and Insect Pests, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Jianhua Zhao
- Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding/Zhongshan Biological Breeding Laboratory/Key Laboratory of Plant Functional Genomics of the Ministry of Education, Agricultural College of Yangzhou University, Yangzhou 225009, China
| | - Peng Gao
- Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding/Zhongshan Biological Breeding Laboratory/Key Laboratory of Plant Functional Genomics of the Ministry of Education, Agricultural College of Yangzhou University, Yangzhou 225009, China
| | - Qi Liu
- State Key Laboratory for Biology of Plant Diseases and Insect Pests, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Shuangyong Yan
- Tianjin Key Laboratory of Crop Genetic Breeding, Tianjin Crop Research Institute, Tianjin Academy of Agriculture Sciences, Tianjin 300112, China
| | - Yinghui Xiao
- College of Agronomy, Hunan Agricultural University, Changsha 410128, China
| | - Shi-Min Zuo
- Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding/Zhongshan Biological Breeding Laboratory/Key Laboratory of Plant Functional Genomics of the Ministry of Education, Agricultural College of Yangzhou University, Yangzhou 225009, China
| | - Houxiang Kang
- State Key Laboratory for Biology of Plant Diseases and Insect Pests, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing 100193, China
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8
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Bilgrami S, Darzi Ramandi H, Farokhzadeh S, Rousseau-Gueutin M, Sobhani Najafabadi A, Ghaderian M, Huang P, Liu L. Meta-analysis of seed weight QTLome using a consensus and highly dense genetic map in Brassica napus L. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2023; 136:161. [PMID: 37354229 DOI: 10.1007/s00122-023-04401-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Accepted: 06/02/2023] [Indexed: 06/26/2023]
Abstract
KEY MESSAGE We report here the discovery of high-confidence MQTL regions and of putative candidate genes associated with seed weight in B. napus using a highly dense consensus genetic map and by comparing various large-scale multiomics datasets. Seed weight (SW) is a direct determinant of seed yield in Brassica napus and is controlled by many loci. To unravel the main genomic regions associated with this complex trait, we used 13 available genetic maps to construct a consensus and highly dense map, comprising 40,401 polymorphic markers and 9191 genetic bins, harboring a cumulative length of 3047.8 cM. Then, we performed a meta-analysis using 639 projected SW quantitative trait loci (QTLs) obtained from studies conducted since 1999, enabling the identification of 57 meta-QTLS (MQTLs). The confidence intervals of our MQTLs were 9.8 and 4.3 times lower than the average CIs of the original QTLs for the A and C subgenomes, respectively, resulting in the detection of some key genes and several putative novel candidate genes associated with SW. By comparing the genes identified in MQTL intervals with multiomics datasets and coexpression analyses of common genes, we defined a more reliable and shorter list of putative candidate genes potentially involved in the regulation of seed maturation and SW. As an example, we provide a list of promising genes with high expression levels in seeds and embryos (e.g., BnaA03g04230D, BnaC03g08840D, BnaA10g29580D and BnaA03g27410D) that can be more finely studied through functional genetics experiments or that may be useful for MQTL-assisted breeding for SW. The high-density genetic consensus map and the single nucleotide polymorphism (SNP) physical map generated from the latest B. napus cv. Darmor-bzh v10 assembly will be a valuable resource for further mapping and map-based cloning of other important traits.
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Affiliation(s)
- Sayedehsaba Bilgrami
- College of Agronomy and Biotechnology, Southwest University, Beibei, Chongqing, 400715, China
| | - Hadi Darzi Ramandi
- Department of Agronomy and Plant Breeding, Faculty of Agriculture, Bu-Ali Sina University, Hamedan, Iran
| | - Sara Farokhzadeh
- Department of Plant Production, College of Agriculture and Natural Resources of Darab, Shiraz University, Darab, Iran
| | | | - Ahmad Sobhani Najafabadi
- Department of Biotechnology, Agricultural Biotechnology Research Institute of Iran - Isfahan Branch, Agricultural Research, Education and Extension Organization (AREEO), Isfahan, Iran
| | - Mostafa Ghaderian
- Division of Biostatistics and Bioinformatics, Department of Environmental and Public Health Sciences, University of Cincinnati, Cincinnati, OH, 45220, USA
| | - Pu Huang
- College of Agronomy and Biotechnology, Southwest University, Beibei, Chongqing, 400715, China
| | - Liezhao Liu
- College of Agronomy and Biotechnology, Southwest University, Beibei, Chongqing, 400715, China.
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Rahimi Y, Khahani B, Jamali A, Alipour H, Bihamta MR, Ingvarsson PK. Genome-wide association study to identify genomic loci associated with early vigor in bread wheat under simulated water deficit complemented with quantitative trait loci meta-analysis. G3 (BETHESDA, MD.) 2023; 13:jkac320. [PMID: 36458966 PMCID: PMC10248217 DOI: 10.1093/g3journal/jkac320] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/10/2022] [Revised: 11/16/2022] [Accepted: 11/17/2022] [Indexed: 12/05/2022]
Abstract
A genome-wide association study (GWAS) was used to identify associated loci with early vigor under simulated water deficit and grain yield under field drought in a diverse collection of Iranian bread wheat landraces. In addition, a meta-quantitative trait loci (MQTL) analysis was used to further expand our approach by retrieving already published quantitative trait loci (QTL) from recombinant inbred lines, double haploids, back-crosses, and F2 mapping populations. In the current study, around 16%, 14%, and 16% of SNPs were in significant linkage disequilibrium (LD) in the A, B, and D genomes, respectively, and varied between 5.44% (4A) and 21.85% (6A). Three main subgroups were identified among the landraces with different degrees of admixture, and population structure was further explored through principal component analysis. Our GWAS identified 54 marker-trait associations (MTAs) that were located across the wheat genome but with the highest number found in the B sub-genome. The gene ontology (GO) analysis of MTAs revealed that around 75% were located within or closed to protein-coding genes. In the MQTL analysis, 23 MQTLs, from a total of 215 QTLs, were identified and successfully projected onto the reference map. MQT-YLD4, MQT-YLD9, MQT-YLD13, MQT-YLD17, MQT-YLD18, MQT-YLD19, and MQTL-RL1 contributed to the highest number of projected QTLs and were therefore regarded as the most reliable and stable QTLs under water deficit conditions. These MQTLs greatly facilitate the identification of putative candidate genes underlying at each MQTL interval due to the reduced confidence of intervals associated with MQTLs. These findings provide important information on the genetic basis of early vigor traits and grain yield under water deficit conditions and set the foundation for future investigations into adaptation to water deficit in bread wheat.
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Affiliation(s)
- Yousef Rahimi
- Department of Plant Biology, Uppsala BioCenter, Linnean Centre for Plant Biology in Uppsala, Swedish University of Agricultural Sciences, 75007 Uppsala, Sweden
| | - Bahman Khahani
- Department of Plant Genetics and Production, College of Agriculture, Shiraz University, 71441-65186 Shiraz, Iran
| | - Ali Jamali
- Department of Agronomy and Plant Breeding, Faculty of Agriculture, University of Tehran, 31587-77871 Karaj, Iran
| | - Hadi Alipour
- Department of Plant Breeding and Biotechnology, Faculty of Agriculture, Urmia University, 5756151818 Urmia, Iran
| | - Mohammad Reza Bihamta
- Department of Agronomy and Plant Breeding, Faculty of Agriculture, University of Tehran, 31587-77871 Karaj, Iran
| | - Pär K Ingvarsson
- Department of Plant Biology, Uppsala BioCenter, Linnean Centre for Plant Biology in Uppsala, Swedish University of Agricultural Sciences, 75007 Uppsala, Sweden
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Kong B, Ma J, Zhang P, Chen T, Liu Y, Che Z, Shahinnia F, Yang D. Deciphering key genomic regions controlling flag leaf size in wheat via integration of meta-QTL and in silico transcriptome assessment. BMC Genomics 2023; 24:33. [PMID: 36658498 PMCID: PMC9854125 DOI: 10.1186/s12864-023-09119-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Accepted: 01/05/2023] [Indexed: 01/20/2023] Open
Abstract
BACKGROUND Grain yield is a complex and polygenic trait influenced by the photosynthetic source-sink relationship in wheat. The top three leaves, especially the flag leaf, are considered the major sources of photo-assimilates accumulated in the grain. Determination of significant genomic regions and candidate genes affecting flag leaf size can be used in breeding for grain yield improvement. RESULTS With the final purpose of understanding key genomic regions for flag leaf size, a meta-analysis of 521 initial quantitative trait loci (QTLs) from 31 independent QTL mapping studies over the past decades was performed, where 333 loci eventually were refined into 64 meta-QTLs (MQTLs). The average confidence interval (CI) of these MQTLs was 5.28 times less than that of the initial QTLs. Thirty-three MQTLs overlapped the marker trait associations (MTAs) previously reported in genome-wide association studies (GWAS) for flag leaf traits in wheat. A total of 2262 candidate genes for flag leaf size, which were involved in the peroxisome, basal transcription factor, and tyrosine metabolism pathways were identified in MQTL regions by the in silico transcriptome assessment. Of these, the expression analysis of the available genes revealed that 134 genes with > 2 transcripts per million (TPM) were highly and specifically expressed in the leaf. These candidate genes could be critical to affect flag leaf size in wheat. CONCLUSIONS The findings will make further insight into the genetic determinants of flag leaf size and provide some reliable MQTLs and putative candidate genes for the genetic improvement of flag leaf size in wheat.
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Affiliation(s)
- Binxue Kong
- State Key Laboratory of Aridland Crop Science, Lanzhou, 730070, China
- College of Life Science and Technology, Gansu Agricultural University, Lanzhou, 730070, China
| | - Jingfu Ma
- State Key Laboratory of Aridland Crop Science, Lanzhou, 730070, China
- College of Life Science and Technology, Gansu Agricultural University, Lanzhou, 730070, China
| | - Peipei Zhang
- State Key Laboratory of Aridland Crop Science, Lanzhou, 730070, China
| | - Tao Chen
- State Key Laboratory of Aridland Crop Science, Lanzhou, 730070, China
- College of Life Science and Technology, Gansu Agricultural University, Lanzhou, 730070, China
| | - Yuan Liu
- State Key Laboratory of Aridland Crop Science, Lanzhou, 730070, China
- College of Life Science and Technology, Gansu Agricultural University, Lanzhou, 730070, China
| | - Zhuo Che
- Plant Seed Master Station of Gansu Province, Lanzhou, 730000, China
| | - Fahimeh Shahinnia
- Bavarian State Research Centre for Agriculture, Institute for Crop Science and Plant Breeding, 85354, Freising, Germany
| | - Delong Yang
- State Key Laboratory of Aridland Crop Science, Lanzhou, 730070, China.
- College of Life Science and Technology, Gansu Agricultural University, Lanzhou, 730070, China.
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11
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Ma J, Liu Y, Zhang P, Chen T, Tian T, Wang P, Che Z, Shahinnia F, Yang D. Identification of quantitative trait loci (QTL) and meta-QTL analysis for kernel size-related traits in wheat (Triticum aestivum L.). BMC PLANT BIOLOGY 2022; 22:607. [PMID: 36550393 PMCID: PMC9784057 DOI: 10.1186/s12870-022-03989-9] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Accepted: 12/08/2022] [Indexed: 06/17/2023]
Abstract
BACKGROUND Kernel size-related traits, including kernel length (KL), kernel width (KW), kernel diameter ratio (KDR) and kernel thickness (KT), are critical determinants for wheat kernel weight and yield and highly governed by a type of quantitative genetic basis. Genome-wide identification of major and stable quantitative trait loci (QTLs) and functional genes are urgently required for genetic improvement in wheat kernel yield. A hexaploid wheat population consisting of 120 recombinant inbred lines was developed to identify QTLs for kernel size-related traits under different water environments. The meta-analysis and transcriptome evaluation were further integrated to identify major genomic regions and putative candidate genes. RESULTS The analysis of variance (ANOVA) revealed more significant genotypic effects for kernel size-related traits, indicating the moderate to high heritability of 0.61-0.89. Thirty-two QTLs for kernel size-related traits were identified, explaining 3.06%-14.2% of the phenotypic variation. Eleven stable QTLs were detected in more than three water environments. The 1103 original QTLs from the 34 previous studies and the present study were employed for the MQTL analysis and refined into 58 MQTLs. The average confidence interval of the MQTLs was 3.26-fold less than that of the original QTLs. The 1864 putative candidate genes were mined within the regions of 12 core MQTLs, where 70 candidate genes were highly expressed in spikes and kernels by comprehensive analysis of wheat transcriptome data. They were involved in various metabolic pathways, such as carbon fixation in photosynthetic organisms, carbon metabolism, mRNA surveillance pathway, RNA transport and biosynthesis of secondary metabolites. CONCLUSIONS Major genomic regions and putative candidate genes for kernel size-related traits in wheat have been revealed by an integrative strategy with QTL linkage mapping, meta-analysis and transcriptomic assessment. The findings provide a novel insight into understanding the genetic determinants of kernel size-related traits and will be useful for the marker-assisted selection of high yield in wheat breeding.
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Grants
- GHSJ 2020-Z4 Research Program Sponsored by State Key Laboratory of Aridland Crop Science, China
- GHSJ 2020-Z4 Research Program Sponsored by State Key Laboratory of Aridland Crop Science, China
- GHSJ 2020-Z4 Research Program Sponsored by State Key Laboratory of Aridland Crop Science, China
- GHSJ 2020-Z4 Research Program Sponsored by State Key Laboratory of Aridland Crop Science, China
- GHSJ 2020-Z4 Research Program Sponsored by State Key Laboratory of Aridland Crop Science, China
- GHSJ 2020-Z4 Research Program Sponsored by State Key Laboratory of Aridland Crop Science, China
- GHSJ 2020-Z4 Research Program Sponsored by State Key Laboratory of Aridland Crop Science, China
- GHSJ 2020-Z4 Research Program Sponsored by State Key Laboratory of Aridland Crop Science, China
- 21YF5NA089 Key Research and Development Program of Gansu Province, China
- 21YF5NA089 Key Research and Development Program of Gansu Province, China
- 21YF5NA089 Key Research and Development Program of Gansu Province, China
- 21YF5NA089 Key Research and Development Program of Gansu Province, China
- 21YF5NA089 Key Research and Development Program of Gansu Province, China
- 21YF5NA089 Key Research and Development Program of Gansu Province, China
- 21YF5NA089 Key Research and Development Program of Gansu Province, China
- 21YF5NA089 Key Research and Development Program of Gansu Province, China
- 2022CYZC-44 Industrial Support Plan of Colleges and Universities in Gansu Province
- 2022CYZC-44 Industrial Support Plan of Colleges and Universities in Gansu Province
- 2022CYZC-44 Industrial Support Plan of Colleges and Universities in Gansu Province
- 2022CYZC-44 Industrial Support Plan of Colleges and Universities in Gansu Province
- 2022CYZC-44 Industrial Support Plan of Colleges and Universities in Gansu Province
- 2022CYZC-44 Industrial Support Plan of Colleges and Universities in Gansu Province
- 2022CYZC-44 Industrial Support Plan of Colleges and Universities in Gansu Province
- 2022CYZC-44 Industrial Support Plan of Colleges and Universities in Gansu Province
- 31760385 National Natural Science Foundation of China
- 31760385 National Natural Science Foundation of China
- 31760385 National Natural Science Foundation of China
- 31760385 National Natural Science Foundation of China
- 31760385 National Natural Science Foundation of China
- 31760385 National Natural Science Foundation of China
- 31760385 National Natural Science Foundation of China
- 31760385 National Natural Science Foundation of China
- 22ZD6NA010 Key Sci & Tech Special Project of Gansu Province
- 22ZD6NA010 Key Sci & Tech Special Project of Gansu Province
- 22ZD6NA010 Key Sci & Tech Special Project of Gansu Province
- 22ZD6NA010 Key Sci & Tech Special Project of Gansu Province
- 22ZD6NA010 Key Sci & Tech Special Project of Gansu Province
- 22ZD6NA010 Key Sci & Tech Special Project of Gansu Province
- 22ZD6NA010 Key Sci & Tech Special Project of Gansu Province
- 22ZD6NA010 Key Sci & Tech Special Project of Gansu Province
- Key Sci & Tech Special Project of Gansu Province
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Affiliation(s)
- Jingfu Ma
- State Key Lab of Aridland Crop Science, Lanzhou, Gansu, China
- College of Agronomy, Gansu Agricultural University, Lanzhou, Gansu, China
| | - Yuan Liu
- College of Life Science and Technology, Gansu Agricultural University, Lanzhou, Gansu, China
| | - Peipei Zhang
- State Key Lab of Aridland Crop Science, Lanzhou, Gansu, China
| | - Tao Chen
- College of Life Science and Technology, Gansu Agricultural University, Lanzhou, Gansu, China
| | - Tian Tian
- College of Life Science and Technology, Gansu Agricultural University, Lanzhou, Gansu, China
| | - Peng Wang
- College of Life Science and Technology, Gansu Agricultural University, Lanzhou, Gansu, China
| | - Zhuo Che
- Plant Seed Master Station of Gansu Province, Lanzhou, Gansu, China
| | - Fahimeh Shahinnia
- Institute for Crop Science and Plant Breeding, Bavarian State Research Centre for Agriculture, Freising, Germany
| | - Delong Yang
- State Key Lab of Aridland Crop Science, Lanzhou, Gansu, China.
- College of Life Science and Technology, Gansu Agricultural University, Lanzhou, Gansu, China.
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Raj SRG, Nadarajah K. QTL and Candidate Genes: Techniques and Advancement in Abiotic Stress Resistance Breeding of Major Cereals. Int J Mol Sci 2022; 24:ijms24010006. [PMID: 36613450 PMCID: PMC9820233 DOI: 10.3390/ijms24010006] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 12/06/2022] [Accepted: 12/13/2022] [Indexed: 12/24/2022] Open
Abstract
At least 75% of the world's grain production comes from the three most important cereal crops: rice (Oryza sativa), wheat (Triticum aestivum), and maize (Zea mays). However, abiotic stressors such as heavy metal toxicity, salinity, low temperatures, and drought are all significant hazards to the growth and development of these grains. Quantitative trait locus (QTL) discovery and mapping have enhanced agricultural production and output by enabling plant breeders to better comprehend abiotic stress tolerance processes in cereals. Molecular markers and stable QTL are important for molecular breeding and candidate gene discovery, which may be utilized in transgenic or molecular introgression. Researchers can now study synteny between rice, maize, and wheat to gain a better understanding of the relationships between the QTL or genes that are important for a particular stress adaptation and phenotypic improvement in these cereals from analyzing reports on QTL and candidate genes. An overview of constitutive QTL, adaptive QTL, and significant stable multi-environment and multi-trait QTL is provided in this article as a solid framework for use and knowledge in genetic enhancement. Several QTL, such as DRO1 and Saltol, and other significant success cases are discussed in this review. We have highlighted techniques and advancements for abiotic stress tolerance breeding programs in cereals, the challenges encountered in introgressing beneficial QTL using traditional breeding techniques such as mutation breeding and marker-assisted selection (MAS), and the in roads made by new breeding methods such as genome-wide association studies (GWASs), the clustered regularly interspaced short palindromic repeat (CRISPR)/Cas9 system, and meta-QTL (MQTL) analysis. A combination of these conventional and modern breeding approaches can be used to apply the QTL and candidate gene information in genetic improvement of cereals against abiotic stresses.
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Aloryi KD, Okpala NE, Amo A, Bello SF, Akaba S, Tian X. A meta-quantitative trait loci analysis identified consensus genomic regions and candidate genes associated with grain yield in rice. FRONTIERS IN PLANT SCIENCE 2022; 13:1035851. [PMID: 36466247 PMCID: PMC9709451 DOI: 10.3389/fpls.2022.1035851] [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: 09/03/2022] [Accepted: 10/19/2022] [Indexed: 06/17/2023]
Abstract
Improving grain yield potential in rice is an important step toward addressing global food security challenges. The meta-QTL analysis offers stable and robust QTLs irrespective of the genetic background of mapping populations and phenotype environment and effectively narrows confidence intervals (CI) for candidate gene (CG) mining and marker-assisted selection improvement. To achieve these aims, a comprehensive bibliographic search for grain yield traits (spikelet fertility, number of grains per panicle, panicles number per plant, and 1000-grain weight) QTLs was conducted, and 462 QTLs were retrieved from 47 independent QTL research published between 2002 and 2022. QTL projection was performed using a reference map with a cumulative length of 2,945.67 cM, and MQTL analysis was conducted on 313 QTLs. Consequently, a total of 62 MQTLs were identified with reduced mean CI (up to 3.40 fold) compared to the mean CI of original QTLs. However, 10 of these MQTLs harbored at least six of the initial QTLs from diverse genetic backgrounds and environments and were considered the most stable and robust MQTLs. Also, MQTLs were compared with GWAS studies and resulted in the identification of 16 common significant loci modulating the evaluated traits. Gene annotation, gene ontology (GO) enrichment, and RNA-seq analyses of chromosome regions of the stable MQTLs detected 52 potential CGs including those that have been cloned in previous studies. These genes encode proteins known to be involved in regulating grain yield including cytochrome P450, zinc fingers, MADs-box, AP2/ERF domain, F-box, ubiquitin ligase domain protein, homeobox domain, DEAD-box ATP domain, and U-box domain. This study provides the framework for molecular dissection of grain yield in rice. Moreover, the MQTLs and CGs identified could be useful for fine mapping, gene cloning, and marker-assisted selection to improve rice productivity.
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Affiliation(s)
- Kelvin Dodzi Aloryi
- Hubei Collaborative Innovation Centre for Grain Industry, College of Agriculture, Yangtze University, Jingzhou, China
| | - Nnaemeka Emmanuel Okpala
- Hubei Collaborative Innovation Centre for Grain Industry, College of Agriculture, Yangtze University, Jingzhou, China
| | - Aduragbemi Amo
- Institute of Plant Breeding, Genetics and Genomics University of Georgia, Athens, GA, United States
| | - Semiu Folaniyi Bello
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, South China Agricultural University, Guangzhou, Guangdong, China
| | - Selorm Akaba
- School of Agriculture, University of Cape Coast, Cape Coast, Ghana
| | - Xiaohai Tian
- Hubei Collaborative Innovation Centre for Grain Industry, College of Agriculture, Yangtze University, Jingzhou, China
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14
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Du B, Wu J, Islam MS, Sun C, Lu B, Wei P, Liu D, Chen C. Genome-wide meta-analysis of QTL for morphological related traits of flag leaf in bread wheat. PLoS One 2022; 17:e0276602. [PMID: 36279291 PMCID: PMC9591062 DOI: 10.1371/journal.pone.0276602] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Accepted: 10/11/2022] [Indexed: 11/05/2022] Open
Abstract
Flag leaf is an important organ for photosynthesis of wheat plants, and a key factor affecting wheat yield. In this study, quantitative trait loci (QTL) for flag leaf morphological traits in wheat reported since 2010 were collected to investigate the genetic mechanism of these traits. Integration of 304 QTLs from various mapping populations into a high-density consensus map composed of various types of molecular markers as well as QTL meta-analysis discovered 55 meta-QTLs (MQTL) controlling morphological traits of flag leaves, of which 10 MQTLs were confirmed by GWAS. Four high-confidence MQTLs (MQTL-1, MQTL-11, MQTL-13, and MQTL-52) were screened out from 55 MQTLs, with an average confidence interval of 0.82 cM and a physical distance of 9.4 Mb, according to the definition of hcMQTL. Ten wheat orthologs from rice (7) and Arabidopsis (3) that regulated leaf angle, development and morphogenesis traits were identified in the hcMQTL region using comparative genomics, and were speculated to be potential candidate genes regulating flag leaf morphological traits in wheat. The results from this study provides valuable information for fine mapping and molecular markers assisted selection to improve morphological characters in wheat flag leaf.
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Affiliation(s)
- Binbin Du
- College of Biotechnology and Pharmaceutical Engineering, West Anhui University, Lu’an, China
| | - Jia Wu
- College of Biotechnology and Pharmaceutical Engineering, West Anhui University, Lu’an, China
| | - Md. Samiul Islam
- Department of Plant Pathology, College of Plant Science and Technology and the Key Lab of Crop Disease Monitoring & Safety Control in Hubei Province, Huazhong Agricultural University, Wuhan, China
| | - Chaoyue Sun
- College of Biotechnology and Pharmaceutical Engineering, West Anhui University, Lu’an, China
| | - Baowei Lu
- College of Biotechnology and Pharmaceutical Engineering, West Anhui University, Lu’an, China
| | - Peipei Wei
- College of Biotechnology and Pharmaceutical Engineering, West Anhui University, Lu’an, China
| | - Dong Liu
- College of Biotechnology and Pharmaceutical Engineering, West Anhui University, Lu’an, China
| | - Cunwu Chen
- College of Biotechnology and Pharmaceutical Engineering, West Anhui University, Lu’an, China
- * E-mail:
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15
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Rahmanzadeh A, Khahani B, Taghavi SM, Khojasteh M, Osdaghi E. Genome-wide meta-QTL analyses provide novel insight into disease resistance repertoires in common bean. BMC Genomics 2022; 23:680. [PMID: 36192697 PMCID: PMC9531352 DOI: 10.1186/s12864-022-08914-w] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2021] [Accepted: 09/27/2022] [Indexed: 11/02/2023] Open
Abstract
BACKGROUND Common bean (Phaseolus vulgaris) is considered a staple food in a number of developing countries. Several diseases attack the crop leading to substantial economic losses around the globe. However, the crop has rarely been investigated for multiple disease resistance traits using Meta-analysis approach. RESULTS AND CONCLUSIONS In this study, in order to identify the most reliable and stable quantitative trait loci (QTL) conveying disease resistance in common bean, we carried out a meta-QTL (MQTL) analysis using 152 QTLs belonging to 44 populations reported in 33 publications within the past 20 years. These QTLs were decreased into nine MQTLs and the average of confidence interval (CI) was reduced by 2.64 folds with an average of 5.12 cM in MQTLs. Uneven distribution of MQTLs across common bean genome was noted where sub-telomeric regions carry most of the corresponding genes and MQTLs. One MQTL was identified to be specifically associated with resistance to halo blight disease caused by the bacterial pathogen Pseudomonas savastanoi pv. phaseolicola, while three and one MQTLs were specifically associated with resistance to white mold and anthracnose caused by the fungal pathogens Sclerotinia sclerotiorum and Colletotrichum lindemuthianum, respectively. Furthermore, two MQTLs were detected governing resistance to halo blight and anthracnose, while two MQTLs were detected for resistance against anthracnose and white mold, suggesting putative genes governing resistance against these diseases at a shared locus. Comparative genomics and synteny analyses provide a valuable strategy to identify a number of well‑known functionally described genes as well as numerous putative novels candidate genes in common bean, Arabidopsis and soybean genomes.
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Affiliation(s)
- Asma Rahmanzadeh
- Department of Plant Protection, School of Agriculture, Shiraz University, Shiraz, 71441-65186, Iran
| | - Bahman Khahani
- Department of Plant Genetics and Production, College of Agriculture, Shiraz University, Shiraz, Iran
| | - S Mohsen Taghavi
- Department of Plant Protection, School of Agriculture, Shiraz University, Shiraz, 71441-65186, Iran
| | - Moein Khojasteh
- Department of Plant Protection, School of Agriculture, Shiraz University, Shiraz, 71441-65186, Iran.
| | - Ebrahim Osdaghi
- Department of Plant Protection, College of Agriculture, University of Tehran, Karaj, 31587-77871, Iran.
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16
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Kong W, Deng X, Liao Z, Wang Y, Zhou M, Wang Z, Li Y. De novo assembly of two chromosome-level rice genomes and bin-based QTL mapping reveal genetic diversity of grain weight trait in rice. FRONTIERS IN PLANT SCIENCE 2022; 13:995634. [PMID: 36072319 PMCID: PMC9443666 DOI: 10.3389/fpls.2022.995634] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/16/2022] [Accepted: 08/01/2022] [Indexed: 06/15/2023]
Abstract
Following the "green revolution," indica and japonica hybrid breeding has been recognized as a new breakthrough in further improving rice yields. However, heterosis-related grain weight QTLs and the basis of yield advantage among subspecies has not been well elucidated. We herein de novo assembled the chromosome level genomes of an indica/xian rice (Luohui 9) and a japonica/geng rice (RPY geng) and found that gene number differences and structural variations between these two genomes contribute to the differences in agronomic traits and also provide two different favorable allele pools to produce better derived recombinant inbred lines (RILs). In addition, we generated a high-generation (> F15) population of 272 RILs from the cross between Luohui 9 and RPY geng and two testcross hybrid populations derived from the crosses of RILs and two cytoplasmic male sterile lines (YTA, indica and Z7A, japonica). Based on three derived populations, we totally identified eight 1,000-grain weight (KGW) QTLs and eight KGW heterosis loci. Of QTLs, qKGW-6.1 and qKGW-8.1 were accepted as novel KGW QTLs that have not been reported previously. Interestingly, allele genotyping results revealed that heading date related gene (Ghd8) in qKGW-8.1 and qLH-KGW-8.1, can affect grain weight in RILs and rice core accessions and may also play an important role in grain weight heterosis. Our results provided two high-quality genomes and novel gene editing targets for grain weight for future rice yield improvement project.
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Affiliation(s)
- Weilong Kong
- State Key Laboratory of Hybrid Rice, College of Life Sciences, Wuhan University, Wuhan, China
| | - Xiaoxiao Deng
- State Key Laboratory of Hybrid Rice, College of Life Sciences, Wuhan University, Wuhan, China
| | - Zhenyang Liao
- Center for Genomics and Biotechnology, Fujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Fujian Agriculture and Forestry University, Fuzhou, China
| | - Yibin Wang
- Center for Genomics and Biotechnology, Fujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Fujian Agriculture and Forestry University, Fuzhou, China
| | - Mingao Zhou
- State Key Laboratory of Hybrid Rice, College of Life Sciences, Wuhan University, Wuhan, China
| | - Zhaohai Wang
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding (Jiangxi Agricultural University), Ministry of Education of the People’s Republic of China, Nanchang, China
| | - Yangsheng Li
- State Key Laboratory of Hybrid Rice, College of Life Sciences, Wuhan University, Wuhan, China
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Anilkumar C, Sah RP, Muhammed Azharudheen TP, Behera S, Singh N, Prakash NR, Sunitha NC, Devanna BN, Marndi BC, Patra BC, Nair SK. Understanding complex genetic architecture of rice grain weight through QTL-meta analysis and candidate gene identification. Sci Rep 2022; 12:13832. [PMID: 35974066 PMCID: PMC9381546 DOI: 10.1038/s41598-022-17402-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Accepted: 07/25/2022] [Indexed: 11/17/2022] Open
Abstract
Quantitative trait loci (QTL) for rice grain weight identified using bi-parental populations in various environments were found inconsistent and have a modest role in marker assisted breeding and map-based cloning programs. Thus, the identification of a consistent consensus QTL region across populations is critical to deploy in marker aided breeding programs. Using the QTL meta-analysis technique, we collated rice grain weight QTL information from numerous studies done across populations and in diverse environments to find constitutive QTL for grain weight. Using information from 114 original QTL in meta-analysis, we discovered three significant Meta-QTL (MQTL) for grain weight on chromosome 3. According to gene ontology, these three MQTL have 179 genes, 25 of which have roles in developmental functions. Amino acid sequence BLAST of these genes indicated their orthologue conservation among core cereals with similar functions. MQTL3.1 includes the OsAPX1, PDIL, SAUR, and OsASN1 genes, which are involved in grain development and have been discovered to play a key role in asparagine biosynthesis and metabolism, which is crucial for source-sink regulation. Five potential candidate genes were identified and their expression analysis indicated a significant role in early grain development. The gene sequence information retrieved from the 3 K rice genome project revealed the deletion of six bases coding for serine and alanine in the last exon of OsASN1 led to an interruption in the synthesis of α-helix of the protein, which negatively affected the asparagine biosynthesis pathway in the low grain weight genotypes. Further, the MQTL3.1 was validated using linked marker RM7197 on a set of genotypes with extreme phenotypes. MQTL that have been identified and validated in our study have significant scope in MAS breeding and map-based cloning programs for improving rice grain weight.
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Affiliation(s)
- C Anilkumar
- ICAR-National Rice Research Institute, Cuttack, India.
| | | | | | | | - Namita Singh
- Indira Gandhi Krishi Vishwavidyalaya, Raipur, India
| | - Nitish Ranjan Prakash
- ICAR-Central Soil Salinity Research Institute, Regional Research Station, Canning Town, India
| | - N C Sunitha
- University of Agricultural Sciences, Bangalore, India
| | - B N Devanna
- ICAR-National Rice Research Institute, Cuttack, India
| | - B C Marndi
- ICAR-National Rice Research Institute, Cuttack, India
| | - B C Patra
- ICAR-National Rice Research Institute, Cuttack, India
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18
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Veisi S, Sabouri A, Abedi A. Meta-analysis of QTLs and candidate genes associated with seed germination in rice ( Oryza sativa L.). PHYSIOLOGY AND MOLECULAR BIOLOGY OF PLANTS : AN INTERNATIONAL JOURNAL OF FUNCTIONAL PLANT BIOLOGY 2022; 28:1587-1605. [PMID: 36389095 PMCID: PMC9530108 DOI: 10.1007/s12298-022-01232-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Revised: 08/18/2022] [Accepted: 09/16/2022] [Indexed: 06/12/2023]
Abstract
Seed germination is one of the critical stages of plant life, and many quantitative trait loci (QTLs) control this complex trait. Meta-analysis of QTLs is a powerful computational technique for estimating the most stable QTLs regardless of the population's genetic background. Besides, this analysis effectively narrows down the confidence interval (CI) to identify candidate genes (CGs) and marker development. In the current study, a comprehensive genome-wide meta-analysis was performed on QTLs associated with germination in rice. This analysis was conducted based on the data reported over the last two decades. In this case, various analyses were performed, including seed germination rate, plumule length, radicle length, germination percentage, coleoptile length, coleorhiza length, radicle fresh weight, germination potential, and germination index. A total of 67 QTLs were projected onto a reference map for these traits and then integrated into 32 meta-QTLs (MQTLs) to provide a genetic framework for seed germination. The average CI of MQTLs was considerably reduced from 15.125 to 8.73 cM compared to the initial QTLs. This situation identified 728 well-known functionally characterized genes and novel putative CGs for investigated traits. The fold change calculation demonstrated that 155 CGs had significant changes in expression analysis. In this case, 112 and 43 CGs were up-regulated and down-regulated during germination, respectively. This study provides an overview and compares genetic loci controlling traits related to seed germination in rice. The findings can bridge the gap between QTLs and CGs for seed germination. Supplementary Information The online version contains supplementary material available at 10.1007/s12298-022-01232-1.
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Affiliation(s)
- Sheida Veisi
- Department of Agronomy and Plant Breeding, Faculty of Agricultural Sciences, University of Guilan, P.O. Box: 41635-1314, Rasht, Iran
| | - Atefeh Sabouri
- Department of Agronomy and Plant Breeding, Faculty of Agricultural Sciences, University of Guilan, P.O. Box: 41635-1314, Rasht, Iran
| | - Amin Abedi
- Department of Plant Biotechnology, Faculty of Agricultural Sciences, University of Guilan, Rasht, Iran
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19
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Javed T, I I, Singhal RK, Shabbir R, Shah AN, Kumar P, Jinger D, Dharmappa PM, Shad MA, Saha D, Anuragi H, Adamski R, Siuta D. Recent Advances in Agronomic and Physio-Molecular Approaches for Improving Nitrogen Use Efficiency in Crop Plants. FRONTIERS IN PLANT SCIENCE 2022; 13:877544. [PMID: 35574130 PMCID: PMC9106419 DOI: 10.3389/fpls.2022.877544] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Accepted: 03/11/2022] [Indexed: 05/05/2023]
Abstract
The efficiency with which plants use nutrients to create biomass and/or grain is determined by the interaction of environmental and plant intrinsic factors. The major macronutrients, especially nitrogen (N), limit plant growth and development (1.5-2% of dry biomass) and have a direct impact on global food supply, fertilizer demand, and concern with environmental health. In the present time, the global consumption of N fertilizer is nearly 120 MT (million tons), and the N efficiency ranges from 25 to 50% of applied N. The dynamic range of ideal internal N concentrations is extremely large, necessitating stringent management to ensure that its requirements are met across various categories of developmental and environmental situations. Furthermore, approximately 60 percent of arable land is mineral deficient and/or mineral toxic around the world. The use of chemical fertilizers adds to the cost of production for the farmers and also increases environmental pollution. Therefore, the present study focused on the advancement in fertilizer approaches, comprising the use of biochar, zeolite, and customized nano and bio-fertilizers which had shown to be effective in improving nitrogen use efficiency (NUE) with lower soil degradation. Consequently, adopting precision farming, crop modeling, and the use of remote sensing technologies such as chlorophyll meters, leaf color charts, etc. assist in reducing the application of N fertilizer. This study also discussed the role of crucial plant attributes such as root structure architecture in improving the uptake and transport of N efficiency. The crosstalk of N with other soil nutrients plays a crucial role in nutrient homeostasis, which is also discussed thoroughly in this analysis. At the end, this review highlights the more efficient and accurate molecular strategies and techniques such as N transporters, transgenes, and omics, which are opening up intriguing possibilities for the detailed investigation of the molecular components that contribute to nitrogen utilization efficiency, thus expanding our knowledge of plant nutrition for future global food security.
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Affiliation(s)
- Talha Javed
- College of Agriculture, Fujian Agriculture and Forestry University, Fuzhou, China
- Department of Agronomy, University of Agriculture Faisalabad, Faisalabad, Pakistan
| | - Indu I
- Indian Council of Agricultural Research (ICAR)-Indian Grassland and Fodder Research Institute, Jhansi, India
| | - Rajesh Kumar Singhal
- Indian Council of Agricultural Research (ICAR)-Indian Grassland and Fodder Research Institute, Jhansi, India
| | - Rubab Shabbir
- College of Agriculture, Fujian Agriculture and Forestry University, Fuzhou, China
- Department of Plant Breeding and Genetics, Seed Science and Technology, University of Agriculture Faisalabad, Faisalabad, Pakistan
| | - Adnan Noor Shah
- Department of Agricultural Engineering, Khwaja Fareed University of Engineering and Information Technology, Rahim Yar Khan, Pakistan
| | - Pawan Kumar
- Indian Council of Agricultural Research (ICAR)-Central Institute for Arid Horticulture, Bikaner, India
| | - Dinesh Jinger
- Research Centre, Indian Council of Agricultural Research (ICAR)-Indian Institute of Soil and Water Conservation, Anand, India
| | - Prathibha M. Dharmappa
- Indian Council of Agricultural Research (ICAR)-Indian Institute of Horticultural Research, Bengaluru, India
| | - Munsif Ali Shad
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene, Hubei Hongshan Laboratory, Wuhan, China
| | - Debanjana Saha
- Centurion University of Technology and Management, Jatni, India
| | - Hirdayesh Anuragi
- Indian Council of Agricultural Research (ICAR)- Central Agroforestry Research Institute, Jhansi, India
| | - Robert Adamski
- Faculty of Process and Environmental Engineering, Łódź University of Technology, Łódź, Poland
| | - Dorota Siuta
- Faculty of Process and Environmental Engineering, Łódź University of Technology, Łódź, Poland
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20
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Singh R, Saripalli G, Gautam T, Kumar A, Jan I, Batra R, Kumar J, Kumar R, Balyan HS, Sharma S, Gupta PK. Meta-QTLs, ortho-MetaQTLs and candidate genes for grain Fe and Zn contents in wheat ( Triticum aestivum L.). PHYSIOLOGY AND MOLECULAR BIOLOGY OF PLANTS : AN INTERNATIONAL JOURNAL OF FUNCTIONAL PLANT BIOLOGY 2022; 28:637-650. [PMID: 35465199 PMCID: PMC8986950 DOI: 10.1007/s12298-022-01149-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Revised: 02/09/2022] [Accepted: 02/15/2022] [Indexed: 05/06/2023]
Abstract
Majority of cereals are deficient in essential micronutrients including grain iron (GFe) and grain zinc (GZn), which are therefore the subject of research involving biofortification. In the present study, 11 meta-QTLs (MQTLs) including nine novel MQTLs for GFe and GZn contents were identified in wheat. Eight of these 11 MQTLs controlled both GFe and GZn. The confidence intervals of the MQTLs were narrower (0.51-15.75 cM) relative to those of the corresponding QTLs (0.6 to 55.1 cM). Two ortho-MQTLs involving three cereals (wheat, rice and maize) were also identified. Results of MQTLs were also compared with the results of earlier genome wide association studies (GWAS). As many as 101 candidate genes (CGs) underlying MQTLs were also identified. Twelve of these CGs were prioritized; these CGs encoded proteins with important domains (zinc finger, RING/FYVE/PHD type, flavin adenine dinucleotide linked oxidase, etc.) that are involved in metal ion binding, heme binding, iron binding, etc. qRT-PCR analysis was conducted for four of these 12 prioritized CGs using genotypes which have differed for GFe and GZn. Significant differential expression in these genotypes was observed at 14 and 28 days after anthesis. The MQTLs/CGs identified in the present study may be utilized in marker-assisted selection (MAS) for improvement of GFe/GZn contents and also for understanding the molecular basis of GFe/GZn homeostasis in wheat. Supplementary Information The online version contains supplementary material available at 10.1007/s12298-022-01149-9.
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Affiliation(s)
- Rakhi Singh
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, 250 004 Meerut, U.P India
| | - Gautam Saripalli
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, 250 004 Meerut, U.P India
- Department of Plant Science and Landscape Architecture, University of Maryland College Park, MD-20742 College Park, MD United States
| | - Tinku Gautam
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, 250 004 Meerut, U.P India
| | - Anuj Kumar
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, 250 004 Meerut, U.P India
| | - Irfat Jan
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, 250 004 Meerut, U.P India
| | - Ritu Batra
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, 250 004 Meerut, U.P India
| | - Jitendra Kumar
- Dept. of Biotechnology, Govt. of India, National Agri-Food Biotechnology Institute (NABI), Sector 81 (Knowledge City), S.A.S. Nagar, 140306 Mohali, Punjab India
| | - Rahul Kumar
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, 250 004 Meerut, U.P India
| | - Harindra Singh Balyan
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, 250 004 Meerut, U.P India
| | - Shailendra Sharma
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, 250 004 Meerut, U.P India
| | - Pushpendra Kumar Gupta
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, 250 004 Meerut, U.P India
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21
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Saini DK, Srivastava P, Pal N, Gupta PK. Meta-QTLs, ortho-meta-QTLs and candidate genes for grain yield and associated traits in wheat (Triticum aestivum L.). TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2022; 135:1049-1081. [PMID: 34985537 DOI: 10.1007/s00122-021-04018-3] [Citation(s) in RCA: 43] [Impact Index Per Article: 21.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Accepted: 12/10/2021] [Indexed: 05/03/2023]
Abstract
In wheat, 2852 major QTLs of 8998 QTLs available for yield and related traits were used for meta-analysis; 141 meta-QTLs were identified, which included 13 breeder's MQTLs and 24 ortho-MQTLs; 1202 candidate genes and 50 homologues of genes for yield from other cereals were also identified. Meta-QTL analysis was conducted using 2852 of the 8998 known QTLs, retrieved from 230 reports published during 1999-2020 (including 19 studies on tetraploid wheat) for grain yield (GY) and the following ten component traits: (i) grain weight (GWei), (ii) grain morphology-related traits (GMRTs), (iii) grain number (GN), (iv) spikes-related traits (SRTs), (v) plant height (PH), (vi) tiller number (TN), (vii) harvest index (HI), (viii) biomass yield (BY), (ix) days to heading/flowering and maturity (DTH/F/M), and (x) grain filling duration (GFD). The study resulted in the identification of 141 meta-QTLs (MQTLs), with an average confidence interval (CI) of 1.4 cM as against a CI of > 12.1 cM (8.8 fold reduction) in the QTLs that were used. The corresponding physical length of CI ranged from 0.01 Mb to 661.9 Mb (mean, 31.5 Mb). Seventy-seven (77) of these 141 MQTLs overlapped marker-trait associations (MTAs) reported in genome-wide association studies. Also, 63 MQTLs (each based on at least 10 QTLs) were considered stable and robust, with 13 MQTLs described as breeder's MQTLs (selected based on small CI, large LOD, and high level of phenotypic variation explained). Thirty-five yield-related genes from rice, barley, and maize were also utilized to identify 50 wheat homologues in MQTLs. Further, the use of synteny and collinearity allowed the identification of 24 ortho-MQTLs which were common among the wheat, barley, rice, and maize. The results of the present study should prove useful for wheat breeding and future basic research in cereals including wheat, barley, rice, and maize.
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Affiliation(s)
- Dinesh Kumar Saini
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, 141004, India
| | - Puja Srivastava
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, 141004, India.
| | - Neeraj Pal
- Department of Molecular Biology and Genetic Engineering, G. B. Pant University of Agriculture and Technology, Pantnagar, Uttarakhand, 263145, India
| | - P K Gupta
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, 250004, India
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22
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Prakash NR, Lokeshkumar BM, Rathor S, Warraich AS, Yadav S, Vinaykumar NM, Dushynthkumar BM, Krishnamurthy SL, Sharma PC. Meta-analysis and validation of genomic loci governing seedling and reproductive stage salinity tolerance in rice. PHYSIOLOGIA PLANTARUM 2022; 174:e13629. [PMID: 35040153 DOI: 10.1111/ppl.13629] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Revised: 10/29/2021] [Accepted: 01/13/2022] [Indexed: 05/24/2023]
Abstract
Identification of concurrent genomic regions contributing tolerance to salinity at the seedling and reproductive stages were done using 45 quantitative trait loci (QTL) mapping studies reporting 915 individual QTLs. The QTL-data were used to perform a meta-analysis to predict, validate and analyze the Meta-QTLs governing component traits contributing to salinity tolerance. We predicted a total of 65 and 49 Meta-QTLs distributed across the genome governing seedling and reproductive stage salinity tolerance, respectively. Salinity stress (EC ~10.0 dSm-1 ) was evaluated in a set of 32 genotypes grown hydroponically, from these eight extreme (highly tolerant and highly susceptible) genotypes were selected for validation of significant Meta-QTLs. Another set of eight previously known and reported (highly tolerant and highly susceptible) genotypes were evaluated under saline micro plot conditions (EC ~8.0 dSm-1 ) and used for validation of significant Meta-QTLs for reproductive stage salinity tolerance. The microsatellite marker "RM5635" linked to MSQTL4.2 (~295.43 kb) was able to clearly differentiate contrasting genotypes for seedling stage salinity tolerance, whereas at the reproductive stage, none of the markers were able to validate the predicted Meta-QTL for salinity tolerance. Earlier reported, gene expression studies were used for candidate gene analysis of validated MSQTL4.2, which indicated the down regulation of Os04g0423100, a gene encoding Mono-oxygenase-FAD binding domain containing protein. The traits associated with this Meta-QTL were root and shoot sodium and potassium concentration and leaf chlorophyll content. The identified and validated genomic region assumes a great significant role in seedling stage salinity tolerance in rice, and it can be used for marker-assisted backcross breeding programs.
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Affiliation(s)
| | | | - Suman Rathor
- ICAR-Central Soil Salinity Research Institute, Karnal, Haryana, India
| | | | - Satyendra Yadav
- ICAR-Central Soil Salinity Research Institute, Karnal, Haryana, India
| | | | | | | | - Parbodh C Sharma
- ICAR-Central Soil Salinity Research Institute, Karnal, Haryana, India
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23
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Daryani P, Darzi Ramandi H, Dezhsetan S, Mirdar Mansuri R, Hosseini Salekdeh G, Shobbar ZS. Pinpointing genomic regions associated with root system architecture in rice through an integrative meta-analysis approach. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2022; 135:81-106. [PMID: 34623472 DOI: 10.1007/s00122-021-03953-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Accepted: 09/20/2021] [Indexed: 06/13/2023]
Abstract
Applying an integrated meta-analysis approach led to identification of meta-QTLs/ candidate genes associated with rice root system architecture, which can be used in MQTL-assisted breeding/ genetic engineering of root traits. Root system architecture (RSA) is an important factor for facilitating water and nutrient uptake from deep soils and adaptation to drought stress conditions. In the present research, an integrated meta-analysis approach was employed to find candidate genes and genomic regions involved in rice RSA traits. A whole-genome meta-analysis was performed for 425 initial QTLs reported in 34 independent experiments controlling RSA traits under control and drought stress conditions in the previous twenty years. Sixty-four consensus meta-QTLs (MQTLs) were detected, unevenly distributed on twelve rice chromosomes. The confidence interval (CI) of the identified MQTLs was obtained as 0.11-14.23 cM with an average of 3.79 cM, which was 3.88 times narrower than the mean CI of the original QTLs. Interestingly, 52 MQTLs were co-located with SNP peak positions reported in rice genome-wide association studies (GWAS) for root morphological traits. The genes located in these RSA-related MQTLs were detected and explored to find the drought-responsive genes in the rice root based on the RNA-seq and microarray data. Multiple RSA and drought tolerance-associated genes were found in the MQTLs including the genes involved in auxin biosynthesis or signaling (e.g. YUCCA, WOX, AUX/IAA, ARF), root angle (DRO1-related genes), lateral root development (e.g. DSR, WRKY), root diameter (e.g. OsNAC5), plant cell wall (e.g. EXPA), and lignification (e.g. C4H, PAL, PRX and CAD). The genes located within both the SNP peak positions and the QTL-overview peaks for RSA are suggested as novel candidate genes for further functional analysis. The promising candidate genes and MQTLs can be used as basis for genetic engineering and MQTL-assisted breeding of root phenotypes to improve yield potential, stability and performance in a water-stressed environment.
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Affiliation(s)
- Parisa Daryani
- Department of Agronomy & Plant Breeding, University of Mohaghegh Ardabili, Ardabil, Iran
- Department of Systems Biology, Agricultural Biotechnology Research Institute of Iran (ABRII), Agricultural Research Education and Extension Organization (AREEO), 31535-1897, Karaj, Iran
| | - Hadi Darzi Ramandi
- Department of Molecular Physiology, Agricultural Biotechnology Research Institute of Iran, Agricultural Research Education and Extension Organization (AREEO), Karaj, Iran
| | - Sara Dezhsetan
- Department of Agronomy & Plant Breeding, University of Mohaghegh Ardabili, Ardabil, Iran.
| | - Raheleh Mirdar Mansuri
- Department of Systems Biology, Agricultural Biotechnology Research Institute of Iran (ABRII), Agricultural Research Education and Extension Organization (AREEO), 31535-1897, Karaj, Iran
| | - Ghasem Hosseini Salekdeh
- Department of Systems Biology, Agricultural Biotechnology Research Institute of Iran (ABRII), Agricultural Research Education and Extension Organization (AREEO), 31535-1897, Karaj, Iran
- Department of Molecular Sciences, Macquarie University, Sydney, NSW, Australia
| | - Zahra-Sadat Shobbar
- Department of Systems Biology, Agricultural Biotechnology Research Institute of Iran (ABRII), Agricultural Research Education and Extension Organization (AREEO), 31535-1897, Karaj, Iran.
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24
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Sandhu N, Pruthi G, Prakash Raigar O, Singh MP, Phagna K, Kumar A, Sethi M, Singh J, Ade PA, Saini DK. Meta-QTL Analysis in Rice and Cross-Genome Talk of the Genomic Regions Controlling Nitrogen Use Efficiency in Cereal Crops Revealing Phylogenetic Relationship. Front Genet 2021; 12:807210. [PMID: 34992638 PMCID: PMC8724540 DOI: 10.3389/fgene.2021.807210] [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: 11/01/2021] [Accepted: 11/30/2021] [Indexed: 11/13/2022] Open
Abstract
The phenomenal increase in the use of nitrogenous fertilizers coupled with poor nitrogen use efficiency is among the most important threats to the environment, economic, and social health. During the last 2 decades, a number of genomic regions associated with nitrogen use efficiency (NUE) and related traits have been reported by different research groups, but none of the stable and major effect QTL have been utilized in the marker-assisted introgression/pyramiding program. Compiling the data available in the literature could be very useful in identifying stable and major effect genomic regions associated with the root and NUE-related trait improving the rice grain yield. In the present study, we performed meta-QTL analysis on 1,330 QTL from 29 studies published in the past 2 decades. A total of 76 MQTL with a stable effect over different genetic backgrounds and environments were identified. The significant reduction in the confidence interval of the MQTL compared to the initial QTL resulted in the identification of annotated and putative candidate genes related to the traits considered in the present study. A hot spot region associated with correlated traits on chr 1, 4, and 8 and candidate genes associated with nitrate transporters, nitrogen content, and ammonium uptake on chromosomes 2, 4, 6, and 8 have been identified. The identified MQTL, putative candidate genes, and their orthologues were validated on our previous studies conducted on rice and wheat. The research-based interventions such as improving nitrogen use efficiency via identification of major genomic regions and candidate genes can be a plausible, simple, and low-cost solution to address the challenges of the crop improvement program.
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Affiliation(s)
| | | | | | | | - Kanika Phagna
- Indian Institute of Science Education and Research, Berhampur, India
| | - Aman Kumar
- Punjab Agricultural University, Ludhiana, India
| | - Mehak Sethi
- Punjab Agricultural University, Ludhiana, India
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25
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Pal N, Saini DK, Kumar S. Meta-QTLs, ortho-MQTLs and candidate genes for the traits contributing to salinity stress tolerance in common wheat ( Triticum aestivum L.). PHYSIOLOGY AND MOLECULAR BIOLOGY OF PLANTS : AN INTERNATIONAL JOURNAL OF FUNCTIONAL PLANT BIOLOGY 2021; 27:2767-2786. [PMID: 35035135 PMCID: PMC8720133 DOI: 10.1007/s12298-021-01112-0] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/19/2021] [Revised: 12/04/2021] [Accepted: 12/07/2021] [Indexed: 05/20/2023]
Abstract
A meta-analysis of QTLs associated with the traits contributing to salinity tolerance was undertaken in wheat to detect consensus and robust meta-QTLs (MQTLs) using 844 known QTLs retrieved from 26 earlier studies. A consensus map with a total length of 4621.56 cM including 7710 markers was constructed using 21 individual linkage maps and three previously published integrated genetic maps. Out of 844 QTLs, 571 QTLs were projected on the consensus map which gave origin to 100 MQTLs. Interestingly, 49 MQTLs were co-located with marker-trait associations reported in wheat genome-wide association studies for the traits contributing to salinity stress tolerance. Five potential MQTLs associated with the major salinity-responsive traits were also identified to be utilized in the breeding programme. In the resulted MQTLs, the average confidence interval (CI, 3.58 cM) was reduced up to 4.16 folds compared to the mean CI of the initial QTLs. Furthermore, as many as 617 gene models including 81 most likely candidate genes (CGs) were identified in the high confidence MQTL regions. These most likely CGs encoded proteins mainly belonging to the following families: B-box-type zinc finger, cytochrome P450 protein, pentatricopeptide repeat, phospholipid/glycerol acyltransferase, F-box protein, small auxin-up RNA, UDP-glucosyltransferase, glutathione S-transferase protein, etc. In addition, ortho-MQTL analysis based on synteny among wheat, rice and barley was also performed which permitted the identification of six ortho-MQTLs among these three cereals. This meta-analysis defines a genome-wide landscape on the most stable and consistent loci associated with reliable molecular markers and candidate genes for salinity tolerance in wheat. SUPPLEMENTARY INFORMATION The online version contains supplementary material available at 10.1007/s12298-021-01112-0.
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Affiliation(s)
- Neeraj Pal
- Department of Molecular Biology and Genetic Engineering, G. B. Pant, University of Agriculture and Technology, Pantnagar, Uttarakhand 263145 India
| | - Dinesh Kumar Saini
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab 141004 India
| | - Sundip Kumar
- Department of Molecular Biology and Genetic Engineering, G. B. Pant, University of Agriculture and Technology, Pantnagar, Uttarakhand 263145 India
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26
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Kumar S, Singh VP, Saini DK, Sharma H, Saripalli G, Kumar S, Balyan HS, Gupta PK. Meta-QTLs, ortho-MQTLs, and candidate genes for thermotolerance in wheat ( Triticum aestivum L.). MOLECULAR BREEDING : NEW STRATEGIES IN PLANT IMPROVEMENT 2021; 41:69. [PMID: 37309361 PMCID: PMC10236124 DOI: 10.1007/s11032-021-01264-7] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Accepted: 11/04/2021] [Indexed: 06/14/2023]
Abstract
Meta-QTL analysis for thermotolerance in wheat was conducted to identify robust meta-QTLs (MQTLs). In this study, 441 QTLs related to 31 heat-responsive traits were projected on the consensus map with 50,310 markers. This exercise resulted in the identification of 85 MQTLs with confidence interval (CI) ranging from 0.11 to 34.9 cM with an average of 5.6 cM. This amounted to a 2.96-fold reduction relative to the mean CI (16.5 cM) of the QTLs used. Seventy-seven (77) of these MQTLs were also compared and verified with the results of recent genome-wide association studies (GWAS). The 85 MQTLs included seven MQTLs that are particularly useful for breeding purposes (we called them breeders' MQTLs). Seven ortho-MQTLs between wheat and rice genomes were also identified using synteny and collinearity. The MQTLs were used for the identification of 1,704 candidate genes (CGs). In silico expression analysis of these CGs permitted identification of 182 differentially expressed genes (DEGs), which included 36 high confidence CGs with known functions previously reported to be important for thermotolerance. These high confidence CGs encoded proteins belonging to the following families: protein kinase, WD40 repeat, glycosyltransferase, ribosomal protein, SNARE associated Golgi protein, GDSL lipase/esterase, SANT/Myb domain, K homology domain, etc. Thus, the present study resulted in the identification of MQTLs (including breeders' MQTLs), ortho-MQTLs, and underlying CGs, which could prove useful not only for molecular breeding for the development of thermotolerant wheat cultivars but also for future studies focused on understanding the molecular basis of thermotolerance. Supplementary Information The online version contains supplementary material available at 10.1007/s11032-021-01264-7.
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Affiliation(s)
- Sourabh Kumar
- Department of Genetics and Plant Breeding, Chaudhary Charan Singh University, Meerut, UP India
| | - Vivudh Pratap Singh
- Department of Genetics and Plant Breeding, Chaudhary Charan Singh University, Meerut, UP India
| | - Dinesh Kumar Saini
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab India
| | - Hemant Sharma
- Department of Genetics and Plant Breeding, Chaudhary Charan Singh University, Meerut, UP India
| | - Gautam Saripalli
- Department of Genetics and Plant Breeding, Chaudhary Charan Singh University, Meerut, UP India
| | - Sachin Kumar
- Department of Genetics and Plant Breeding, Chaudhary Charan Singh University, Meerut, UP India
| | - Harindra Singh Balyan
- Department of Genetics and Plant Breeding, Chaudhary Charan Singh University, Meerut, UP India
| | - Pushpendra Kumar Gupta
- Department of Genetics and Plant Breeding, Chaudhary Charan Singh University, Meerut, UP India
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Siekmann D, Jansen G, Zaar A, Kilian A, Fromme FJ, Hackauf B. A Genome-Wide Association Study Pinpoints Quantitative Trait Genes for Plant Height, Heading Date, Grain Quality, and Yield in Rye ( Secale cereale L.). FRONTIERS IN PLANT SCIENCE 2021; 12:718081. [PMID: 34777409 PMCID: PMC8586073 DOI: 10.3389/fpls.2021.718081] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Accepted: 09/22/2021] [Indexed: 06/03/2023]
Abstract
Rye is the only cross-pollinating Triticeae crop species. Knowledge of rye genes controlling complex-inherited traits is scarce, which, currently, largely disables the genomics assisted introgression of untapped genetic variation from self-incompatible germplasm collections in elite inbred lines for hybrid breeding. We report on the first genome-wide association study (GWAS) in rye based on the phenotypic evaluation of 526 experimental hybrids for plant height, heading date, grain quality, and yield in 2 years and up to 19 environments. We established a cross-validated NIRS calibration model as a fast, effective, and robust analytical method to determine grain quality parameters. We observed phenotypic plasticity in plant height and tiller number as a resource use strategy of rye under drought and identified increased grain arabinoxylan content as a striking phenotype in osmotically stressed rye. We used DArTseq™ as a genotyping-by-sequencing technology to reduce the complexity of the rye genome. We established a novel high-density genetic linkage map that describes the position of almost 19k markers and that allowed us to estimate a low genome-wide LD based on the assessed genetic diversity in elite germplasm. We analyzed the relationship between plant height, heading date, agronomic, as well as grain quality traits, and genotype based on 20k novel single-nucleotide polymorphism markers. In addition, we integrated the DArTseq™ markers in the recently established 'Lo7' reference genome assembly. We identified cross-validated SNPs in 'Lo7' protein-coding genes associated with all traits studied. These include associations of the WUSCHEL-related homeobox transcription factor DWT1 and grain yield, the DELLA protein gene SLR1 and heading date, the Ethylene overproducer 1-like protein gene ETOL1 and thousand-grain weight, protein and starch content, as well as the Lectin receptor kinase SIT2 and plant height. A Leucine-rich repeat receptor protein kinase and a Xyloglucan alpha-1,6-xylosyltransferase count among the cross-validated genes associated with water-extractable arabinoxylan content. This study demonstrates the power of GWAS, hybrid breeding, and the reference genome sequence in rye genetics research to dissect and identify the function of genes shaping genetic diversity in agronomic and grain quality traits of rye. The described links between genetic causes and phenotypic variation will accelerate genomics-enabled rye improvement.
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Affiliation(s)
- Dörthe Siekmann
- Julius Kühn Institute, Federal Research Centre for Cultivated Plants, Institute for Breeding Research on Agricultural Crops, Sanitz, Germany
- HYBRO Saatzucht GmbH & Co. KG, Schenkenberg, Germany
| | - Gisela Jansen
- Julius Kühn Institute, Federal Research Centre for Cultivated Plants, Institute for Resistance Research and Stress Tolerance, Sanitz, Germany
| | - Anne Zaar
- Julius Kühn Institute, Federal Research Centre for Cultivated Plants, Institute for Resistance Research and Stress Tolerance, Sanitz, Germany
| | | | | | - Bernd Hackauf
- Julius Kühn Institute, Federal Research Centre for Cultivated Plants, Institute for Breeding Research on Agricultural Crops, Sanitz, Germany
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Shariatipour N, Heidari B, Tahmasebi A, Richards C. Comparative Genomic Analysis of Quantitative Trait Loci Associated With Micronutrient Contents, Grain Quality, and Agronomic Traits in Wheat ( Triticum aestivum L.). FRONTIERS IN PLANT SCIENCE 2021; 12:709817. [PMID: 34712248 PMCID: PMC8546302 DOI: 10.3389/fpls.2021.709817] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Accepted: 09/06/2021] [Indexed: 05/02/2023]
Abstract
Comparative genomics and meta-quantitative trait loci (MQTLs) analysis are important tools for the identification of reliable and stable QTLs and functional genes controlling quantitative traits. We conducted a meta-analysis to identify the most stable QTLs for grain yield (GY), grain quality traits, and micronutrient contents in wheat. A total of 735 QTLs retrieved from 27 independent mapping populations reported in the last 13 years were used for the meta-analysis. The results showed that 449 QTLs were successfully projected onto the genetic consensus map which condensed to 100 MQTLs distributed on wheat chromosomes. This consolidation of MQTLs resulted in a three-fold reduction in the confidence interval (CI) compared with the CI for the initial QTLs. Projection of QTLs revealed that the majority of QTLs and MQTLs were in the non-telomeric regions of chromosomes. The majority of micronutrient MQTLs were located on the A and D genomes. The QTLs of thousand kernel weight (TKW) were frequently associated with QTLs for GY and grain protein content (GPC) with co-localization occurring at 55 and 63%, respectively. The co- localization of QTLs for GY and grain Fe was found to be 52% and for QTLs of grain Fe and Zn, it was found to be 66%. The genomic collinearity within Poaceae allowed us to identify 16 orthologous MQTLs (OrMQTLs) in wheat, rice, and maize. Annotation of promising candidate genes (CGs) located in the genomic intervals of the stable MQTLs indicated that several CGs (e.g., TraesCS2A02G141400, TraesCS3B02G040900, TraesCS4D02G323700, TraesCS3B02G077100, and TraesCS4D02G290900) had effects on micronutrients contents, yield, and yield-related traits. The mapping refinements leading to the identification of these CGs provide an opportunity to understand the genetic mechanisms driving quantitative variation for these traits and apply this information for crop improvement programs.
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Affiliation(s)
- Nikwan Shariatipour
- Department of Plant Production and Genetics, School of Agriculture, Shiraz University, Shiraz, Iran
| | - Bahram Heidari
- Department of Plant Production and Genetics, School of Agriculture, Shiraz University, Shiraz, Iran
| | - Ahmad Tahmasebi
- Department of Plant Production and Genetics, School of Agriculture, Shiraz University, Shiraz, Iran
| | - Christopher Richards
- USDA ARS National Laboratory for Genetic Resources Preservation, Fort Collins, CO, United States
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Saini DK, Chopra Y, Pal N, Chahal A, Srivastava P, Gupta PK. Meta-QTLs, ortho-MQTLs and candidate genes for nitrogen use efficiency and root system architecture in bread wheat ( Triticum aestivum L.). PHYSIOLOGY AND MOLECULAR BIOLOGY OF PLANTS : AN INTERNATIONAL JOURNAL OF FUNCTIONAL PLANT BIOLOGY 2021; 27:2245-2267. [PMID: 34744364 PMCID: PMC8526679 DOI: 10.1007/s12298-021-01085-0] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Revised: 09/26/2021] [Accepted: 09/27/2021] [Indexed: 05/04/2023]
Abstract
In wheat, meta-QTLs (MQTLs), ortho-MQTLs, and candidate genes (CGs) were identified for nitrogen use efficiency and root system architecture. For this purpose, 1788 QTLs were available from 24 studies published during 2006-2020. Of these, 1098 QTLs were projected onto the consensus map resulting in 118 MQTLs. The average confidence interval (CI) of MQTLs was reduced up to 8.56 folds in comparison to the average CI of QTLs. Of the 118 MQTLs, 112 were anchored to the physical map of the wheat reference genome. The physical interval of MQTLs ranged from 0.02 to 666.18 Mb with a mean of 94.36 Mb. Eighty-eight of these 112 MQTLs were verified by marker-trait associations (MTAs) identified in published genome-wide association studies (GWAS); the MQTLs that were verified using GWAS also included 9 most robust MQTLs, which are particularly useful for breeders; we call them 'Breeder's QTLs'. Some selected wheat MQTLs were further utilized for the identification of ortho-MQTLs for wheat and maize; 9 such ortho-MQTLs were available. As many as 1991 candidate genes (CGs) were also detected, which included 930 CGs with an expression level of > 2 transcripts per million in relevant organs/tissues. Among the CGs, 97 CGs with functions previously reported as important for the traits under study were selected. Based on homology analysis and expression patterns, 49 orthologues of 35 rice genes were also identified in MQTL regions. The results of the present study may prove useful for the improvement of selection strategy for yield potential, stability, and performance under N-limiting conditions. SUPPLEMENTARY INFORMATION The online version contains supplementary material available at 10.1007/s12298-021-01085-0.
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Affiliation(s)
- Dinesh Kumar Saini
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, 141004 India
| | - Yuvraj Chopra
- College of Agriculture, Punjab Agricultural University, Ludhiana, 141004 India
- Present Address: Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE 68583 USA
| | - Neeraj Pal
- Department of Molecular Biology and Genetic Engineering, G. B. Pant, University of Agriculture and Technology, Pantnagar, Uttarakhand 263145 India
| | - Amneek Chahal
- College of Agriculture, Punjab Agricultural University, Ludhiana, 141004 India
| | - Puja Srivastava
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, 141004 India
| | - Pushpendra Kumar Gupta
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, 250004 India
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Yang Y, Amo A, Wei D, Chai Y, Zheng J, Qiao P, Cui C, Lu S, Chen L, Hu YG. Large-scale integration of meta-QTL and genome-wide association study discovers the genomic regions and candidate genes for yield and yield-related traits in bread wheat. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2021; 134:3083-3109. [PMID: 34142166 DOI: 10.1007/s00122-021-03881-4] [Citation(s) in RCA: 50] [Impact Index Per Article: 16.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/09/2021] [Accepted: 06/02/2021] [Indexed: 05/20/2023]
Abstract
Based on the large-scale integration of meta-QTL and Genome-Wide Association Study, 76 high-confidence MQTL regions and 237 candidate genes that affected wheat yield and yield-related traits were discovered. Improving yield and yield-related traits are key goals in wheat breeding program. The integration of accumulated wheat genetic resources provides an opportunity to uncover important genomic regions and candidate genes that affect wheat yield. Here, a comprehensive meta-QTL analysis was conducted on 2230 QTL of yield-related traits obtained from 119 QTL studies. These QTL were refined into 145 meta-QTL (MQTL), and 89 MQTL were verified by GWAS with different natural populations. The average confidence interval (CI) of these MQTL was 2.92 times less than that of the initial QTL. Furthermore, 76 core MQTL regions with a physical distance less than 25 Mb were detected. Based on the homology analysis and expression patterns, 237 candidate genes in the MQTL involved in photoperiod response, grain development, multiple plant growth regulator pathways, carbon and nitrogen metabolism and spike and flower organ development were determined. A novel candidate gene TaKAO-4A was confirmed to be significantly associated with grain size, and a CAPS marker was developed based on its dominant haplotype. In summary, this study clarified a method based on the integration of meta-QTL, GWAS and homology comparison to reveal the genomic regions and candidate genes that affect important yield-related traits in wheat. This work will help to lay a foundation for the identification, transfer and aggregation of these important QTL or candidate genes in wheat high-yield breeding.
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Affiliation(s)
- Yang Yang
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, Shaanxi, China
| | - Aduragbemi Amo
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, Shaanxi, China
| | - Di Wei
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, Shaanxi, China
| | - Yongmao Chai
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, Shaanxi, China
| | - Jie Zheng
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, Shaanxi, China
| | - Pengfang Qiao
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, Shaanxi, China
| | - Chunge Cui
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, Shaanxi, China
| | - Shan Lu
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, Shaanxi, China
| | - Liang Chen
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, Shaanxi, China.
| | - Yin-Gang Hu
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, Shaanxi, China.
- Institute of Water Saving Agriculture in Arid Regions of China, Northwest A&F University, Yangling, Shaanxi, China.
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Meta-QTL and ortho-MQTL analyses identified genomic regions controlling rice yield, yield-related traits and root architecture under water deficit conditions. Sci Rep 2021; 11:6942. [PMID: 33767323 PMCID: PMC7994909 DOI: 10.1038/s41598-021-86259-2] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2020] [Accepted: 03/11/2021] [Indexed: 02/01/2023] Open
Abstract
Meta-QTL (MQTL) analysis is a robust approach for genetic dissection of complex quantitative traits. Rice varieties adapted to non-flooded cultivation are highly desirable in breeding programs due to the water deficit global problem. In order to identify stable QTLs for major agronomic traits under water deficit conditions, we performed a comprehensive MQTL analysis on 563 QTLs from 67 rice populations published from 2001 to 2019. Yield and yield-related traits including grain weight, heading date, plant height, tiller number as well as root architecture-related traits including root dry weight, root length, root number, root thickness, the ratio of deep rooting and plant water content under water deficit condition were investigated. A total of 61 stable MQTLs over different genetic backgrounds and environments were identified. The average confidence interval of MQTLs was considerably refined compared to the initial QTLs, resulted in the identification of some well-known functionally characterized genes and several putative novel CGs for investigated traits. Ortho-MQTL mining based on genomic collinearity between rice and maize allowed identification of five ortho-MQTLs between these two cereals. The results can help breeders to improve yield under water deficit conditions.
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Bilgrami SS, Ramandi HD, Shariati V, Razavi K, Tavakol E, Fakheri BA, Mahdi Nezhad N, Ghaderian M. Detection of genomic regions associated with tiller number in Iranian bread wheat under different water regimes using genome-wide association study. Sci Rep 2020; 10:14034. [PMID: 32820220 PMCID: PMC7441066 DOI: 10.1038/s41598-020-69442-9] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2019] [Accepted: 07/09/2020] [Indexed: 11/09/2022] Open
Abstract
Two of the important traits for wheat yield are tiller and fertile tiller number, both of which have been thought to increase cereal yield in favorable and unfavorable environments. A total of 6,349 single nucleotide polymorphism (SNP) markers from the 15 K wheat Infinium array were employed for genome-wide association study (GWAS) of tillering number traits, generating a physical distance of 14,041.6 Mb based on the IWGSC wheat genome sequence. GWAS analysis using Fixed and random model Circulating Probability Unification (FarmCPU) identified a total of 47 significant marker-trait associations (MTAs) for total tiller number (TTN) and fertile tiller number (FTN) in Iranian bread wheat under different water regimes. After applying a 5% false discovery rate (FDR) threshold, a total of 13 and 11 MTAs distributed on 10 chromosomes were found to be significantly associated with TTN and FTN, respectively. Linked single nucleotide polymorphisms for IWB39005 (2A) and IWB44377 (7A) were highly significantly associated (FDR < 0.01) with TTN and FTN traits. Moreover, to validate GWAS results, meta-analysis was performed and 30 meta-QTL regions were identified on 11 chromosomes. The integration of GWAS and meta-QTLs revealed that tillering trait in wheat is a complex trait which is conditioned by the combined effects of minor changes in multiple genes. The information provided by this study can enrich the currently available candidate genes and genetic resources pools, offering evidence for subsequent analysis of genetic adaptation of wheat to different climatic conditions of Iran and other countries.
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Affiliation(s)
- Sayedeh Saba Bilgrami
- Department of Plant Molecular Biotechnology, National Institute of Genetic Engineering and Biotechnology (NIGEB), Tehran, Iran.,College of Agronomy and Biotechnology, Southwest University, Beibei, 400715, Chongqing, China
| | - Hadi Darzi Ramandi
- Department of Molecular Physiology, Agricultural Biotechnology Research Institute of Iran, Research, Education and Extension Organization (AREEO), Karaj, Iran
| | - Vahid Shariati
- Department of Plant Molecular Biotechnology, National Institute of Genetic Engineering and Biotechnology (NIGEB), Tehran, Iran.
| | - Khadijeh Razavi
- Department of Plant Molecular Biotechnology, National Institute of Genetic Engineering and Biotechnology (NIGEB), Tehran, Iran.
| | - Elahe Tavakol
- Department of Plant Production and Genetics, Shiraz University, Shiraz, Iran
| | - Barat Ali Fakheri
- Department of Plant Breeding and Biotechnology, Faculty of Agriculture, University of Zabol, Zabol, Iran
| | - Nafiseh Mahdi Nezhad
- Department of Plant Breeding and Biotechnology, Faculty of Agriculture, University of Zabol, Zabol, Iran
| | - Mostafa Ghaderian
- Department of Plant Breeding and Biotechnology, Faculty of Agriculture, Isfahan University of Technology, Isfahan, Iran
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Zhang R, Liu C, Song X, Sun F, Xiao D, Wei Y, Hou X, Zhang C. Genome-wide association study of turnip mosaic virus resistance in non-heading Chinese cabbage. 3 Biotech 2020; 10:363. [PMID: 32832324 DOI: 10.1007/s13205-020-02344-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2019] [Accepted: 06/30/2020] [Indexed: 10/23/2022] Open
Abstract
A genome-wide association study (GWAS) using 83 diverse non-heading Chinese cabbage (NHCC) accessions identified 42,526 high-quality single nucleotide polymorphism markers associated with turnip mosaic virus (TuMV) resistance. Seventeen associated loci were identified, along with the related genes that were differentially expressed between resistant and susceptible varieties, suggesting that they may be candidate genes for TuMV tolerance. Nine mutant genes of Arabidopsis were selected for inoculation with TuMV-GFP (green fluorescence protein) to further confirm the disease resistance of these genes. Quantitative polymerase chain reaction (qPCR) analysis showed that the virus content in the Arabidopsis mutants with the homologous genes of cell wall-associated proteins, pectin methyl-esterase (PME), transcription factors (TFs), resistance gene (R), VAN3/SFC protein and F-box gene were significantly higher than that in the mutants with the homologous genes of methylation and J protein. Our results provide the basis of further study of the potential function of these candidate TuMV resistance genes and demonstrate that the described diverse NHCC can be efficiently used for GWAS of various quantitative traits. Taken together, the findings of this study will be useful to improve TuMV resistance in NHCC breeding and to discover new genes related to TuMV resistance.
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Affiliation(s)
- Rujia Zhang
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, College of Horticulture, Nanjing Agricultural University, Nanjing, 210095 Jiangsu People's Republic of China
| | - Chang Liu
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, College of Horticulture, Nanjing Agricultural University, Nanjing, 210095 Jiangsu People's Republic of China
| | - Xiaoming Song
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, College of Horticulture, Nanjing Agricultural University, Nanjing, 210095 Jiangsu People's Republic of China
| | - Feifei Sun
- Nanjing Vegetable Science Research Institute, Nanjing, 210042 Jiangsu People's Republic of China
| | - Dong Xiao
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, College of Horticulture, Nanjing Agricultural University, Nanjing, 210095 Jiangsu People's Republic of China
| | - Yanping Wei
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, College of Horticulture, Nanjing Agricultural University, Nanjing, 210095 Jiangsu People's Republic of China
| | - Xilin Hou
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, College of Horticulture, Nanjing Agricultural University, Nanjing, 210095 Jiangsu People's Republic of China
| | - Changwei Zhang
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, College of Horticulture, Nanjing Agricultural University, Nanjing, 210095 Jiangsu People's Republic of China
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Kumar A, Saripalli G, Jan I, Kumar K, Sharma PK, Balyan HS, Gupta PK. Meta-QTL analysis and identification of candidate genes for drought tolerance in bread wheat ( Triticum aestivum L.). PHYSIOLOGY AND MOLECULAR BIOLOGY OF PLANTS : AN INTERNATIONAL JOURNAL OF FUNCTIONAL PLANT BIOLOGY 2020; 26:1713-1725. [PMID: 32801498 PMCID: PMC7415061 DOI: 10.1007/s12298-020-00847-6] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/22/2020] [Revised: 06/30/2020] [Accepted: 07/03/2020] [Indexed: 05/18/2023]
Abstract
Meta-QTL (MQTL) analysis for drought tolerance was undertaken in bread wheat to identify consensus and robust MQTLs using 340 known QTLs from 11 earlier studies; 13 MQTLs located on 6 chromosomes (1D, 3B, 5A, 6D, 7A and 7D) were identified, with maximum of 4 MQTLs on chromosome 5A. Mean confidence intervals for MQTLs were much narrower (mean, 6.01 cM; range 2.07-19.46 cM), relative to those in original QTLs (mean, 13.6 cM; range, 1.0-119.1 cM). Two MQTLs, namely MQTL4 and MQTL12, were major MQTLs with potential for use in marker-assisting breeding. As many as 228 candidate genes (CGs) were also identified using 6 of the 13 MQTLs. In-silico expression analysis of these 228 CGs allowed identification of 14 important CGs, with + 3 to - 8 fold change in expression under drought (relative to normal conditions) in a tolerant cv. named TAM107. These CGs encoded proteins belonging to the following families: NAD-dependent epimerase/dehydratase, protein kinase, NAD(P)-binding domain protein, heat shock protein 70 (Hsp70), glycosyltransferase 2-like, etc. Important MQTLs and CGs identified in the present study should prove useful for future molecular breeding and for the study of molecular basis of drought tolerance in cereals in general and wheat in particular.
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Affiliation(s)
- Anuj Kumar
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, 250004 India
| | - Gautam Saripalli
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, 250004 India
| | - Irfat Jan
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, 250004 India
| | - Kuldeep Kumar
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, 250004 India
| | - P. K. Sharma
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, 250004 India
| | - H. S. Balyan
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, 250004 India
| | - P. K. Gupta
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, 250004 India
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