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Yao Y, Guo W, Gou J, Hu Z, Liu J, Ma J, Zong Y, Xin M, Chen W, Li Q, Wang Z, Zhang R, Uauy C, Baloch FS, Ni Z, Sun Q. Wheat2035: Integrating pan-omics and advanced biotechnology for future wheat design. MOLECULAR PLANT 2025; 18:272-297. [PMID: 39780492 DOI: 10.1016/j.molp.2025.01.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/01/2024] [Revised: 01/03/2025] [Accepted: 01/07/2025] [Indexed: 01/11/2025]
Abstract
Wheat (Triticum aestivum) production is vital for global food security, providing energy and protein to millions of people worldwide. Recent advancements in wheat research have led to significant increases in production, fueled by technological and scientific innovation. Here, we summarize the major advancements in wheat research, particularly the integration of biotechnologies and a deeper understanding of wheat biology. The shift from multi-omics to pan-omics approaches in wheat research has greatly enhanced our understanding of the complex genome, genomic variations, and regulatory networks to decode complex traits. We also outline key scientific questions, potential research directions, and technological strategies for improving wheat over the next decade. Since global wheat production is expected to increase by 60% in 2050, continued innovation and collaboration are crucial. Integrating biotechnologies and a deeper understanding of wheat biology will be essential for addressing future challenges in wheat production, ensuring sustainable practices and improved productivity.
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Affiliation(s)
- Yingyin Yao
- State Key Laboratory of High-Efficiency Production of Wheat-Maize Double Cropping, China Agricultural University, Beijing 100193, China; Frontiers Science Center for Molecular Design Breeding, Key Laboratory of Crop Heterosis and Utilization (MOE), and Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China
| | - Weilong Guo
- State Key Laboratory of High-Efficiency Production of Wheat-Maize Double Cropping, China Agricultural University, Beijing 100193, China; Frontiers Science Center for Molecular Design Breeding, Key Laboratory of Crop Heterosis and Utilization (MOE), and Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China
| | - Jinying Gou
- State Key Laboratory of High-Efficiency Production of Wheat-Maize Double Cropping, China Agricultural University, Beijing 100193, China; Frontiers Science Center for Molecular Design Breeding, Key Laboratory of Crop Heterosis and Utilization (MOE), and Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China
| | - Zhaorong Hu
- State Key Laboratory of High-Efficiency Production of Wheat-Maize Double Cropping, China Agricultural University, Beijing 100193, China; Frontiers Science Center for Molecular Design Breeding, Key Laboratory of Crop Heterosis and Utilization (MOE), and Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China
| | - Jie Liu
- State Key Laboratory of High-Efficiency Production of Wheat-Maize Double Cropping, China Agricultural University, Beijing 100193, China; Frontiers Science Center for Molecular Design Breeding, Key Laboratory of Crop Heterosis and Utilization (MOE), and Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China
| | - Jun Ma
- State Key Laboratory of High-Efficiency Production of Wheat-Maize Double Cropping, China Agricultural University, Beijing 100193, China; Frontiers Science Center for Molecular Design Breeding, Key Laboratory of Crop Heterosis and Utilization (MOE), and Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China
| | - Yuan Zong
- State Key Laboratory of High-Efficiency Production of Wheat-Maize Double Cropping, China Agricultural University, Beijing 100193, China; Frontiers Science Center for Molecular Design Breeding, Key Laboratory of Crop Heterosis and Utilization (MOE), and Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China
| | - Mingming Xin
- State Key Laboratory of High-Efficiency Production of Wheat-Maize Double Cropping, China Agricultural University, Beijing 100193, China; Frontiers Science Center for Molecular Design Breeding, Key Laboratory of Crop Heterosis and Utilization (MOE), and Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China
| | - Wei Chen
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China
| | - Qiang Li
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China
| | - Zihao Wang
- State Key Laboratory of High-Efficiency Production of Wheat-Maize Double Cropping, China Agricultural University, Beijing 100193, China; Frontiers Science Center for Molecular Design Breeding, Key Laboratory of Crop Heterosis and Utilization (MOE), and Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China
| | - Ruijie Zhang
- State Key Laboratory of High-Efficiency Production of Wheat-Maize Double Cropping, China Agricultural University, Beijing 100193, China; Frontiers Science Center for Molecular Design Breeding, Key Laboratory of Crop Heterosis and Utilization (MOE), and Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China
| | - Cristobal Uauy
- John Innes Centre, Norwich Research Park, Norwich NR4 7UH, UK
| | - Faheem Shehzad Baloch
- Department of Biotechnology, Faculty of Science, Mersin University, Yenişehir, Mersin 33343, Turkey; Department of Plant Resources and Environment, Jeju National University, Jeju City, Republic of Korea
| | - Zhongfu Ni
- State Key Laboratory of High-Efficiency Production of Wheat-Maize Double Cropping, China Agricultural University, Beijing 100193, China; Frontiers Science Center for Molecular Design Breeding, Key Laboratory of Crop Heterosis and Utilization (MOE), and Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China.
| | - Qixin Sun
- State Key Laboratory of High-Efficiency Production of Wheat-Maize Double Cropping, China Agricultural University, Beijing 100193, China; Frontiers Science Center for Molecular Design Breeding, Key Laboratory of Crop Heterosis and Utilization (MOE), and Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China.
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Zhuang L, Liu H, Hou J, Jian C, Liu Y, Li H, Xi W, Zhao J, Hao P, Liu S, Cao L, Pan Y, Zhang Y, Zhao L, Jiao C, Liu H, Zhang X, Li T, Hao C. Genetic improvement of important agronomic traits in Chinese wheat breeding over the past 70 years. BMC PLANT BIOLOGY 2024; 24:1151. [PMID: 39614144 DOI: 10.1186/s12870-024-05841-8] [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: 07/18/2024] [Accepted: 11/18/2024] [Indexed: 12/01/2024]
Abstract
BACKGROUND Understanding the genetic improvement patterns of agronomic traits in Chinese wheat (Triticum aestivum L.) breeding is essential for devising future breeding strategies. However, a systematic analysis of the genetic improvement of important traits in Chinese wheat is lacking. This study aimed to provide insights into the improvement progress of yield-related traits in the Chinese wheat breeding process and clarify the selection pressure on important agronomic traits in different agroecological zones. Phenotypic evaluations of 481 wheat accessions including 157 Chinese landraces (CLs) and 324 modern Chinese cultivars (MCCs), were carried out in multiple locations and years. RESULTS The population structure analyses showed that all accessions could be basically divided into CLs and MCCs subpopulations. Pearson correlation analysis revealed that the negative correlation between grain number per spike and thousand-grain weight gradually decreased while thousand-grain weight, grain number per spike, and effective tiller number exhibited synergistic improvements during the modern breeding process. Phenotypic differences among MCCs released from the 1950s to the 2000s indicated that grain number per spike and grain weight-related traits increased linearly, whereas plant height and effective tiller number decreased significantly. Furthermore, since the 1950s, the heading date, flowering date, and maturity date have become earlier, while the spike length and spikelet number per spike have not changed significantly with the advancement of breeding years. The annual genetic gain analysis of agronomic traits showed that plant height had the greatest increase (‒0.96%), followed by thousand-grain weight (0.38%), while the lowest for grain number per spike (0.13%). Phenotypic difference analysis of CLs and MCCs with different geographical origins further revealed that heading date, flowering date, plant height, thousand-grain weight, grain width, and grain thickness experienced strong selection with the same trend in seven agroecological zones. Among zones, the northern winter wheat zone experienced the strongest selection pressure, and plant height and thousand-grain weight were strongly selected in all zones. CONCLUSIONS This study reveals that CLs and MCCs in China with obvious phenotypic differences, plant height and thousand-grain weight were strongly selected during wheat breeding, and further improvement of wheat in China will inevitably involve a continuous increase in grain number per spike.
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Affiliation(s)
- Lei Zhuang
- State Key Laboratory of Crop Gene Resources and Breeding, National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Haixia Liu
- State Key Laboratory of Crop Gene Resources and Breeding, National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Jian Hou
- State Key Laboratory of Crop Gene Resources and Breeding, National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Chao Jian
- State Key Laboratory of Crop Gene Resources and Breeding, National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Yunchuan Liu
- State Key Laboratory of Crop Gene Resources and Breeding, National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Huifang Li
- State Key Laboratory of Wheat and Maize Crop Science, and Center for Crop Genome Engineering, College of Agronomy, Henan Agricultural University, Zhengzhou, Henan, 450046, China
| | - Wei Xi
- State Key Laboratory of Crop Gene Resources and Breeding, National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Jing Zhao
- State Key Laboratory of Crop Gene Resources and Breeding, National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Pingan Hao
- State Key Laboratory of Crop Gene Resources and Breeding, National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Shujuan Liu
- State Key Laboratory of Crop Gene Resources and Breeding, National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Lina Cao
- State Key Laboratory of Crop Gene Resources and Breeding, National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Yuxue Pan
- State Key Laboratory of Crop Gene Resources and Breeding, National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Yinhui Zhang
- State Key Laboratory of Crop Gene Resources and Breeding, National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Li Zhao
- State Key Laboratory of Crop Gene Resources and Breeding, National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Chengzhi Jiao
- State Key Laboratory of Crop Gene Resources and Breeding, National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Hongxia Liu
- State Key Laboratory of Crop Gene Resources and Breeding, National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China.
| | - Xueyong Zhang
- State Key Laboratory of Crop Gene Resources and Breeding, National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China.
| | - Tian Li
- State Key Laboratory of Crop Gene Resources and Breeding, National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China.
| | - Chenyang Hao
- State Key Laboratory of Crop Gene Resources and Breeding, National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China.
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Liu X, Zhang X, Meng X, Liu P, Lei M, Jin H, Wang Y, Jin Y, Cui G, Mu Z, Liu J, Jia X. Identification of genetic loci for powdery mildew resistance in common wheat. FRONTIERS IN PLANT SCIENCE 2024; 15:1443239. [PMID: 39445142 PMCID: PMC11496114 DOI: 10.3389/fpls.2024.1443239] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/03/2024] [Accepted: 09/02/2024] [Indexed: 10/25/2024]
Abstract
Powdery mildew (PM) poses an extreme threat to wheat yields and quality. In this study, 262 recombinant inbred lines (RILs) of Doumai and Shi 4185 cross were used to map PM resistance genes across four environments. High-density genetic linkage map of the Doumai/Shi 4185 RIL population was constructed using the wheat Illumina iSelect 90K single-nucleotide polymorphism (SNP) array. In total, four stable quantitative trait loci (QTLs) for PM resistance, QPm.caas-2AS, QPm.caas-4AS, QPm.caas-4BL, and QPm.caas-6BS, were detected and explained 5.6%-15.6% of the phenotypic variances. Doumai contributed all the resistance alleles of QPm.caas-2AS, QPm.caas-4AS, QPm.caas-4BL, and QPm.caas-6BS. Among these, QPm.caas-4AS and QPm.caas-6BS overlapped with the previously reported loci, whereas QPm.caas-2AS and QPm.caas-4BL are potentially novel. In addition, six high-confidence genes encoding the NBS-LRR-like resistance protein, disease resistance protein family, and calcium/calmodulin-dependent serine/threonine-kinase were selected as the candidate genes for PM resistance. Three kompetitive allele-specific PCR (KASP) markers, Kasp_PMR_2AS for QPm.caas-2AS, Kasp_PMR_4BL for QPm.caas-4BL, and Kasp_PMR_6BS for QPm.caas-6BS, were developed, and their genetic effects were validated in a natural population including 100 cultivars. These findings will offer valuable QTLs and available KASP markers to enhance wheat marker-assisted breeding for PM resistance.
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Affiliation(s)
- Xia Liu
- College of Agriculture, Shanxi Agricultural University, Taigu, China
- Center for Agricultural Genetic Resources Research, Shanxi Agricultural University/Key Laboratory of Gene Resources and Germplasm Enhancement, Ministry of Agriculture and Rural Affairs/Key Laboratory of Crop Genetics and Molecular Improvement of Shanxi Province, Taiyuan, China
| | - Xiaoqing Zhang
- National Agricultural Technology Extension Service Center of the Ministry, Agriculture and Rural Affairs, Beijing, China
| | - Xianghai Meng
- Dryland Farming Institute, Hebei Academy of Agricultural and Forestry Sciences, Hengshui, China
| | - Peng Liu
- Wheat Research Institute, Dezhou Academy of Agricultural Sciences, Dezhou, China
| | - Menglin Lei
- Center for Agricultural Genetic Resources Research, Shanxi Agricultural University/Key Laboratory of Gene Resources and Germplasm Enhancement, Ministry of Agriculture and Rural Affairs/Key Laboratory of Crop Genetics and Molecular Improvement of Shanxi Province, Taiyuan, China
| | - Hui Jin
- Institute of Forage and Grassland Sciences, Heilongjiang Academy of Agricultural Sciences, Harbin, China
| | - Yanzhen Wang
- Center for Agricultural Genetic Resources Research, Shanxi Agricultural University/Key Laboratory of Gene Resources and Germplasm Enhancement, Ministry of Agriculture and Rural Affairs/Key Laboratory of Crop Genetics and Molecular Improvement of Shanxi Province, Taiyuan, China
| | - Yirong Jin
- Wheat Research Institute, Dezhou Academy of Agricultural Sciences, Dezhou, China
| | - Guoqing Cui
- Center for Agricultural Genetic Resources Research, Shanxi Agricultural University/Key Laboratory of Gene Resources and Germplasm Enhancement, Ministry of Agriculture and Rural Affairs/Key Laboratory of Crop Genetics and Molecular Improvement of Shanxi Province, Taiyuan, China
| | - Zhixin Mu
- Center for Agricultural Genetic Resources Research, Shanxi Agricultural University/Key Laboratory of Gene Resources and Germplasm Enhancement, Ministry of Agriculture and Rural Affairs/Key Laboratory of Crop Genetics and Molecular Improvement of Shanxi Province, Taiyuan, China
| | - Jindong Liu
- Institute of Crop Sciences, National Wheat Improvement Centre, Chinese Academy of Agricultural Sciences (CAAS), Beijing, China
| | - Xiaoyun Jia
- College of Agriculture, Shanxi Agricultural University, Taigu, China
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Rabieyan E, Darvishzadeh R, Alipour H. Genetic analyses and prediction for lodging‑related traits in a diverse Iranian hexaploid wheat collection. Sci Rep 2024; 14:275. [PMID: 38167972 PMCID: PMC10761700 DOI: 10.1038/s41598-023-49927-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: 05/02/2023] [Accepted: 12/13/2023] [Indexed: 01/05/2024] Open
Abstract
Lodging is one of the most important limiting environmental factors for achieving the maximum yield and quality of grains in cereals, including wheat. However, little is known about the genetic foundation underlying lodging resistance (LR) in wheat. In this study, 208 landraces and 90 cultivars were phenotyped in two cropping seasons (2018-2019 and 2019-2020) for 19 LR-related traits. A genome-wide association study (GWAS) and genomics prediction were carried out to dissect the genomic regions of LR. The number of significant marker pairs (MPs) was highest for genome B in both landraces (427,017) and cultivars (37,359). The strongest linkage disequilibrium (LD) between marker pairs was found on chromosome 4A (0.318). For stem lodging-related traits, 465, 497, and 478 marker-trait associations (MTAs) and 45 candidate genes were identified in year 1, year 2, and pooled. Gene ontology exhibited genomic region on Chr. 2B, 6B, and 7B control lodging. Most of these genes have key roles in defense response, calcium ion transmembrane transport, carbohydrate metabolic process, nitrogen compound metabolic process, and some genes harbor unknown functions that, all together may respond to lodging as a complex network. The module associated with starch and sucrose biosynthesis was highlighted. Regarding genomic prediction, the GBLUP model performed better than BRR and RRBLUP. This suggests that GBLUP would be a good tool for wheat genome selection. As a result of these findings, it has been possible to identify pivotal QTLs and genes that could be used to improve stem lodging resistance in Triticum aestivum L.
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Affiliation(s)
- Ehsan Rabieyan
- Department of Plant Production and Genetics, Urmia University, Urmia, Iran
| | - Reza Darvishzadeh
- Department of Plant Production and Genetics, Urmia University, Urmia, Iran
| | - Hadi Alipour
- Department of Plant Production and Genetics, Urmia University, Urmia, Iran.
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Khodaverdi M, Mullinger MD, Shafer HR, Preston JC. Melica as an emerging model system for comparative studies in temperate Pooideae grasses. ANNALS OF BOTANY 2023; 132:1175-1190. [PMID: 37696761 PMCID: PMC10902897 DOI: 10.1093/aob/mcad136] [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: 04/03/2023] [Revised: 07/10/2023] [Accepted: 09/07/2023] [Indexed: 09/13/2023]
Abstract
BACKGROUND AND AIMS Pooideae grasses contain some of the world's most important crop and forage species. Although much work has been conducted on understanding the genetic basis of trait diversification within a few annual Pooideae, comparative studies at the subfamily level are limited by a lack of perennial models outside 'core' Pooideae. We argue for development of the perennial non-core genus Melica as an additional model for Pooideae, and provide foundational data regarding the group's biogeography and history of character evolution. METHODS Supplementing available ITS and ndhF sequence data, we built a preliminary Bayesian-based Melica phylogeny, and used it to understand how the genus has diversified in relation to geography, climate and trait variation surveyed from various floras. We also determine biomass accumulation under controlled conditions for Melica species collected across different latitudes and compare inflorescence development across two taxa for which whole genome data are forthcoming. KEY RESULTS Our phylogenetic analyses reveal three strongly supported geographically structured Melica clades that are distinct from previously hypothesized subtribes. Despite less geographical affinity between clades, the two sister 'Ciliata' and 'Imperfecta' clades segregate from the more phylogenetically distant 'Nutans' clade in thermal climate variables and precipitation seasonality, with the 'Imperfecta' clade showing the highest levels of trait variation. Growth rates across Melica are positively correlated with latitude of origin. Variation in inflorescence morphology appears to be explained largely through differences in secondary branch distance, phyllotaxy and number of spikelets per secondary branch. CONCLUSIONS The data presented here and in previous studies suggest that Melica possesses many of the necessary features to be developed as an additional model for Pooideae grasses, including a relatively fast generation time, perenniality, and interesting variation in physiology and morphology. The next step will be to generate a genome-based phylogeny and transformation tools for functional analyses.
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Affiliation(s)
- Masoumeh Khodaverdi
- Department of Plant Biology, The University of Vermont, 111 Jeffords Hall, 63 Carrigan Drive, Burlington, VT 05405, USA
| | - Mark D Mullinger
- Department of Plant Biology, The University of Vermont, 111 Jeffords Hall, 63 Carrigan Drive, Burlington, VT 05405, USA
| | - Hannah R Shafer
- Department of Plant Biology, The University of Vermont, 111 Jeffords Hall, 63 Carrigan Drive, Burlington, VT 05405, USA
| | - Jill C Preston
- Department of Plant Biology, The University of Vermont, 111 Jeffords Hall, 63 Carrigan Drive, Burlington, VT 05405, USA
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Jia J, Zhao G, Li D, Wang K, Kong C, Deng P, Yan X, Zhang X, Lu Z, Xu S, Jiao Y, Chong K, Liu X, Cui D, Li G, Zhang Y, Du C, Wu L, Li T, Yan D, Zhan K, Chen F, Wang Z, Zhang L, Kong X, Ru Z, Wang D, Gao L. Genome resources for the elite bread wheat cultivar Aikang 58 and mining of elite homeologous haplotypes for accelerating wheat improvement. MOLECULAR PLANT 2023; 16:1893-1910. [PMID: 37897037 DOI: 10.1016/j.molp.2023.10.015] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/14/2022] [Revised: 07/12/2023] [Accepted: 10/23/2023] [Indexed: 10/29/2023]
Abstract
Despite recent progress in crop genomics studies, the genomic changes brought about by modern breeding selection are still poorly understood, thus hampering genomics-assisted breeding, especially in polyploid crops with compound genomes such as common wheat (Triticum aestivum). In this work, we constructed genome resources for the modern elite common wheat variety Aikang 58 (AK58). Comparative genomics between AK58 and the landrace cultivar Chinese Spring (CS) shed light on genomic changes that occurred through recent varietal improvement. We also explored subgenome diploidization and divergence in common wheat and developed a homoeologous locus-based genome-wide association study (HGWAS) approach, which was more effective than single homoeolog-based GWAS in unraveling agronomic trait-associated loci. A total of 123 major HGWAS loci were detected using a genetic population derived from AK58 and CS. Elite homoeologous haplotypes (HHs), formed by combinations of subgenomic homoeologs of the associated loci, were found in both parents and progeny, and many could substantially improve wheat yield and related traits. We built a website where users can download genome assembly sequence and annotation data for AK58, perform blast analysis, and run JBrowse. Our work enriches genome resources for wheat, provides new insights into genomic changes during modern wheat improvement, and suggests that efficient mining of elite HHs can make a substantial contribution to genomics-assisted breeding in common wheat and other polyploid crops.
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Affiliation(s)
- Jizeng Jia
- College of Agronomy, Collaborative Innovation Center of Henan Grain Crops, State Key Laboratory of Wheat and Maize Crop Science, and Center for Crop Genome Engineering, Henan Agricultural University, Zhengzhou 450046, Henan, China; State Key Laboratory of Crop Gene Resources and Breeding, the National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Guangyao Zhao
- State Key Laboratory of Crop Gene Resources and Breeding, the National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Danping Li
- State Key Laboratory of Crop Gene Resources and Breeding, the National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Kai Wang
- Xi'An Shansheng Biosciences Co., Ltd., Xi'an 710000, China
| | - Chuizheng Kong
- State Key Laboratory of Crop Gene Resources and Breeding, the National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Pingchuan Deng
- Zhejiang Provincial Key Laboratory of Crop Genetic Resources, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, Zhejiang 310058, China; State Key Laboratory of Crop Stress Biology in Arid Areas, College of Agronomy, Northwest A&F University, Yangling, Shaanxi 612100, China
| | - Xueqing Yan
- State Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xueyong Zhang
- State Key Laboratory of Crop Gene Resources and Breeding, the National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Zefu Lu
- State Key Laboratory of Crop Gene Resources and Breeding, the National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Shujuan Xu
- University of Chinese Academy of Sciences, Beijing 100049, China; Key Laboratory of Plant Molecular Physiology, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China
| | - Yuannian Jiao
- State Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Kang Chong
- University of Chinese Academy of Sciences, Beijing 100049, China; Key Laboratory of Plant Molecular Physiology, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China
| | - Xu Liu
- State Key Laboratory of Crop Gene Resources and Breeding, the National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Dangqun Cui
- College of Agronomy, Collaborative Innovation Center of Henan Grain Crops, State Key Laboratory of Wheat and Maize Crop Science, and Center for Crop Genome Engineering, Henan Agricultural University, Zhengzhou 450046, Henan, China
| | - Guangwei Li
- College of Agronomy, Collaborative Innovation Center of Henan Grain Crops, State Key Laboratory of Wheat and Maize Crop Science, and Center for Crop Genome Engineering, Henan Agricultural University, Zhengzhou 450046, Henan, China
| | - Yijing Zhang
- State Key Laboratory of Genetic Engineering, Collaborative Innovation Center of Genetics and Development, Department of Biochemistry, Institute of Plant Biology, School of Life Sciences, Fudan University, Shanghai 200438, China
| | - Chunguang Du
- College of Agronomy, Collaborative Innovation Center of Henan Grain Crops, State Key Laboratory of Wheat and Maize Crop Science, and Center for Crop Genome Engineering, Henan Agricultural University, Zhengzhou 450046, Henan, China
| | - Liang Wu
- Zhejiang Provincial Key Laboratory of Crop Genetic Resources, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, Zhejiang 310058, China; Hainan Yazhou Bay Seed Laboratory, Hainan Institute of Zhejiang University, Sanya, Hainan 562000, China
| | - Tianbao Li
- College of Agronomy, Collaborative Innovation Center of Henan Grain Crops, State Key Laboratory of Wheat and Maize Crop Science, and Center for Crop Genome Engineering, Henan Agricultural University, Zhengzhou 450046, Henan, China; State Key Laboratory of Crop Gene Resources and Breeding, the National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Dong Yan
- State Key Laboratory of Crop Gene Resources and Breeding, the National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Kehui Zhan
- College of Agronomy, Collaborative Innovation Center of Henan Grain Crops, State Key Laboratory of Wheat and Maize Crop Science, and Center for Crop Genome Engineering, Henan Agricultural University, Zhengzhou 450046, Henan, China
| | - Feng Chen
- College of Agronomy, Collaborative Innovation Center of Henan Grain Crops, State Key Laboratory of Wheat and Maize Crop Science, and Center for Crop Genome Engineering, Henan Agricultural University, Zhengzhou 450046, Henan, China
| | - Zhiyong Wang
- College of Agronomy, Collaborative Innovation Center of Henan Grain Crops, State Key Laboratory of Wheat and Maize Crop Science, and Center for Crop Genome Engineering, Henan Agricultural University, Zhengzhou 450046, Henan, China
| | - Lichao Zhang
- State Key Laboratory of Crop Gene Resources and Breeding, the National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Xiuying Kong
- State Key Laboratory of Crop Gene Resources and Breeding, the National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China.
| | - Zhengang Ru
- School of Life Science and Technology, Henan Institute of Science and Technology, Xinxiang, Henan 453003, China.
| | - Daowen Wang
- College of Agronomy, Collaborative Innovation Center of Henan Grain Crops, State Key Laboratory of Wheat and Maize Crop Science, and Center for Crop Genome Engineering, Henan Agricultural University, Zhengzhou 450046, Henan, China.
| | - Lifeng Gao
- State Key Laboratory of Crop Gene Resources and Breeding, the National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China.
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7
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Niu J, Ma S, Zheng S, Zhang C, Lu Y, Si Y, Tian S, Shi X, Liu X, Naeem MK, Sun H, Hu Y, Wu H, Cui Y, Chen C, Long W, Zhang Y, Gu M, Cui M, Lu Q, Zhou W, Peng J, Akhunov E, He F, Zhao S, Ling HQ. Whole-genome sequencing of diverse wheat accessions uncovers genetic changes during modern breeding in China and the United States. THE PLANT CELL 2023; 35:4199-4216. [PMID: 37647532 PMCID: PMC10689146 DOI: 10.1093/plcell/koad229] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Revised: 07/25/2023] [Accepted: 08/08/2023] [Indexed: 09/01/2023]
Abstract
Breeding has dramatically changed the plant architecture of wheat (Triticum aestivum), resulting in the development of high-yielding varieties adapted to modern farming systems. However, how wheat breeding shaped the genomic architecture of this crop remains poorly understood. Here, we performed a comprehensive comparative analysis of a whole-genome resequencing panel of 355 common wheat accessions (representing diverse landraces and modern cultivars from China and the United States) at the phenotypic and genomic levels. The genetic diversity of modern wheat cultivars was clearly reduced compared to landraces. Consistent with these genetic changes, most phenotypes of cultivars from China and the United States were significantly altered. Of the 21 agronomic traits investigated, 8 showed convergent changes between the 2 countries. Moreover, of the 207 loci associated with these 21 traits, more than half overlapped with genomic regions that showed evidence of selection. The distribution of selected loci between the Chinese and American cultivars suggests that breeding for increased productivity in these 2 regions was accomplished by pyramiding both shared and region-specific variants. This work provides a framework to understand the genetic architecture of the adaptation of wheat to diverse agricultural production environments, as well as guidelines for optimizing breeding strategies to design better wheat varieties.
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Affiliation(s)
- Jianqing Niu
- Hainan Yazhou Bay Seed Laboratory, Hainan, Sanya 572024, China
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
| | - Shengwei Ma
- Hainan Yazhou Bay Seed Laboratory, Hainan, Sanya 572024, China
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
| | - Shusong Zheng
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
| | - Chi Zhang
- BGI Genomics, BGI-Shenzhen, Shenzhen 518083, China
| | - Yaru Lu
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
| | - Yaoqi Si
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
| | - Shuiquan Tian
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
- College of Advanced Agricultural Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xiaoli Shi
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
| | - Xiaolin Liu
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
- College of Advanced Agricultural Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Muhammad Kashif Naeem
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
| | - Hua Sun
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
| | - Yafei Hu
- BGI Genomics, BGI-Shenzhen, Shenzhen 518083, China
| | - Huilan Wu
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
| | - Yan Cui
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
| | - Chunlin Chen
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
| | - Wenbo Long
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
| | - Yue Zhang
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
| | - Mengjun Gu
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
| | - Man Cui
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
| | - Qiao Lu
- College of Advanced Agricultural Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Wenjuan Zhou
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
| | - Junhua Peng
- Huazhi Bio-tech Company Ltd., Changsha, Hunan 410125, China
| | - Eduard Akhunov
- Wheat Genetic Resources Center, Kansas State University, Manhattan, KS 66506, USA
| | - Fei He
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
| | - Shancen Zhao
- BGI Genomics, BGI-Shenzhen, Shenzhen 518083, China
| | - Hong-Qing Ling
- Hainan Yazhou Bay Seed Laboratory, Hainan, Sanya 572024, China
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
- College of Advanced Agricultural Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
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Bürger M. The breadth of bread: unearthing genomic trade-offs in 355 wheat accessions. THE PLANT CELL 2023; 35:4191-4192. [PMID: 37697442 PMCID: PMC10689129 DOI: 10.1093/plcell/koad235] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Revised: 09/05/2023] [Accepted: 09/05/2023] [Indexed: 09/13/2023]
Affiliation(s)
- Marco Bürger
- Assistant Features Editor, The Plant Cell, American Society of Plant Biologists
- Plant Biology Laboratory, Salk Institute for Biological Studies, La Jolla, CA 92037, USA
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9
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Wang Z, Miao L, Chen Y, Peng H, Ni Z, Sun Q, Guo W. Deciphering the evolution and complexity of wheat germplasm from a genomic perspective. J Genet Genomics 2023; 50:846-860. [PMID: 37611848 DOI: 10.1016/j.jgg.2023.08.002] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Revised: 07/29/2023] [Accepted: 08/09/2023] [Indexed: 08/25/2023]
Abstract
Bread wheat provides an essential fraction of the daily calorific intake for humanity. Due to its huge and complex genome, progress in studying on the wheat genome is substantially trailed behind those of the other two major crops, rice and maize, for at least a decade. With rapid advances in genome assembling and reduced cost of high-throughput sequencing, emerging de novo genome assemblies of wheat and whole-genome sequencing data are leading to a paradigm shift in wheat research. Here, we review recent progress in dissecting the complex genome and germplasm evolution of wheat since the release of the first high-quality wheat genome. New insights have been gained in the evolution of wheat germplasm during domestication and modern breeding progress, genomic variations at multiple scales contributing to the diversity of wheat germplasm, and complex transcriptional and epigenetic regulations of functional genes in polyploid wheat. Genomics databases and bioinformatics tools meeting the urgent needs of wheat genomics research are also summarized. The ever-increasing omics data, along with advanced tools and well-structured databases, are expected to accelerate deciphering the germplasm and gene resources in wheat for future breeding advances.
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Affiliation(s)
- Zihao Wang
- Frontiers Science Center for Molecular Design Breeding, Key Laboratory of Crop Heterosis and Utilization, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China
| | - Lingfeng Miao
- Frontiers Science Center for Molecular Design Breeding, Key Laboratory of Crop Heterosis and Utilization, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China
| | - Yongming Chen
- Frontiers Science Center for Molecular Design Breeding, Key Laboratory of Crop Heterosis and Utilization, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China
| | - Huiru Peng
- Frontiers Science Center for Molecular Design Breeding, Key Laboratory of Crop Heterosis and Utilization, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China
| | - Zhongfu Ni
- Frontiers Science Center for Molecular Design Breeding, Key Laboratory of Crop Heterosis and Utilization, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China
| | - Qixin Sun
- Frontiers Science Center for Molecular Design Breeding, Key Laboratory of Crop Heterosis and Utilization, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China
| | - Weilong Guo
- Frontiers Science Center for Molecular Design Breeding, Key Laboratory of Crop Heterosis and Utilization, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China.
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10
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Taranto F, Esposito S, Fania F, Sica R, Marzario S, Logozzo G, Gioia T, De Vita P. Breeding effects on durum wheat traits detected using GWAS and haplotype block analysis. FRONTIERS IN PLANT SCIENCE 2023; 14:1206517. [PMID: 37794940 PMCID: PMC10546023 DOI: 10.3389/fpls.2023.1206517] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/15/2023] [Accepted: 08/08/2023] [Indexed: 10/06/2023]
Abstract
Introduction The recent boosting of genomic data in durum wheat (Triticum turgidum subsp. durum) offers the opportunity to better understand the effects of breeding on the genetic structures that regulate the expression of traits of agronomic interest. Furthermore, the identification of DNA markers useful for marker-assisted selection could also improve the reliability of technical protocols used for variety protection and registration. Methods Within this motivation context, 123 durum wheat accessions, classified into three groups: landraces (LR), ancient (OC) and modern cultivars (MC), were evaluated in two locations, for 34 agronomic traits, including UPOV descriptors, to assess the impact of changes that occurred during modern breeding. Results The association mapping analysis, performed with 4,241 SNP markers and six multi-locus-GWAS models, revealed 28 reliable Quantitative Trait Nucleotides (QTNs) related to plant morphology and kernel-related traits. Some important genes controlling flowering time and plant height were in linkage disequilibrium (LD) decay with QTNs identified in this study. A strong association for yellow berry was found on chromosome 6A (Q.Yb-6A) in a region containing the nadh-ubiquinone oxidoreductase subunit, a gene involved in starch metabolism. The Q.Kcp-2A harbored the PPO locus, with the associated marker (Ku_c13700_1196) in LD decay with Ppo-A1 and Ppo-A2. Interestingly, the Q.FGSGls-2B.1, identified by RAC875_c34512_685 for flag leaf glaucosity, mapped less than 1 Mb from the Epistatic inhibitors of glaucousness (Iw1), thus representing a good candidate for supporting the morphological DUS traits also with molecular markers. LD haplotype block approach revealed a higher diversity, richness and length of haploblocks in MC than OC and LR (580 in LR, 585 in OC and 612 in MC), suggesting a possible effect exerted by breeding programs on genomic regions associated with the agronomic traits. Discussion Our findings pave new ways to support the phenotypic characterization necessary for variety registration by using a panel of cost-effectiveness SNP markers associated also to the UPOV descriptors. Moreover, the panel of associated SNPs might represent a reservoir of favourable alleles to use in durum wheat breeding and genetics.
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Affiliation(s)
- F. Taranto
- Italian National Council of Research (CNR), Institute of Biosciences and Bioresources (IBBR), Bari, Italy
| | - S. Esposito
- Council for Agricultural Research and Economics (CREA), Research Centre for Cereal and Industrial Crops (CREA-CI), Foggia, Italy
| | - F. Fania
- Council for Agricultural Research and Economics (CREA), Research Centre for Cereal and Industrial Crops (CREA-CI), Foggia, Italy
- Department of Agriculture, Food, Natural Resources, and Engineering (DAFNE) - University of Foggia, Foggia, Italy
| | - R. Sica
- School of Agricultural, Forestry, Food and Environmental Sciences, University of Basilicata, Potenza, Italy
| | - S. Marzario
- School of Agricultural, Forestry, Food and Environmental Sciences, University of Basilicata, Potenza, Italy
| | - G. Logozzo
- School of Agricultural, Forestry, Food and Environmental Sciences, University of Basilicata, Potenza, Italy
| | - T. Gioia
- School of Agricultural, Forestry, Food and Environmental Sciences, University of Basilicata, Potenza, Italy
| | - P. De Vita
- Council for Agricultural Research and Economics (CREA), Research Centre for Cereal and Industrial Crops (CREA-CI), Foggia, Italy
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11
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Rabieyan E, Bihamta MR, Moghaddam ME, Alipour H, Mohammadi V, Azizyan K, Javid S. Analysis of genetic diversity and genome-wide association study for drought tolerance related traits in Iranian bread wheat. BMC PLANT BIOLOGY 2023; 23:431. [PMID: 37715130 PMCID: PMC10503013 DOI: 10.1186/s12870-023-04416-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Accepted: 08/20/2023] [Indexed: 09/17/2023]
Abstract
BACKGROUND Drought is most likely the most significant abiotic stress affecting wheat yield. The discovery of drought-tolerant genotypes is a promising strategy for dealing with the world's rapidly diminishing water resources and growing population. A genome-wide association study (GWAS) was conducted on 298 Iranian bread wheat landraces and cultivars to investigate the genetic basis of yield, yield components, and drought tolerance indices in two cropping seasons (2018-2019 and 2019-2020) under rainfed and well-watered environments. RESULTS A heatmap display of hierarchical clustering divided cultivars and landraces into four categories, with high-yielding and drought-tolerant genotypes clustering in the same group. The results of the principal component analysis (PCA) demonstrated that selecting genotypes based on the mean productivity (MP), geometric mean productivity (GMP), harmonic mean (HM), and stress tolerance index (STI) can help achieve high-yield genotypes in the environment. Genome B had the highest number of significant marker pairs in linkage disequilibrium (LD) for both landraces (427,017) and cultivars (370,359). Similar to cultivars, marker pairs on chromosome 4A represented the strongest LD (r2 = 0.32). However, the genomes D, A, and B have the highest LD, respectively. The single-locus mixed linear model (MLM) and multi-locus random-SNP-effect mixed linear model (mrMLM) identified 1711 and 1254 significant marker-trait association (MTAs) (-log10 P > 3) for all traits, respectively. A total of 874 common quantitative trait nucleotides (QTNs) were simultaneously discovered by both MLM and mrMLM methods. Gene ontology revealed that 11, 18, 6, and 11 MTAs were found in protein-coding regions (PCRs) for spike weight (SW), thousand kernel weight (TKW), grain number per spike (GN), and grain yield (GY), respectively. CONCLUSION The results identified rich regions of quantitative trait loci (QTL) on Ch. 4A and 5A suggest that these chromosomes are important for drought tolerance and could be used in wheat breeding programs. Furthermore, the findings indicated that landraces studied in Iranian bread wheat germplasm possess valuable alleles, that are responsive to water-limited conditions. This GWAS experiment is one of the few types of research conducted on drought tolerance that can be exploited in the genome-mediated development of novel varieties of wheat.
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Affiliation(s)
- Ehsan Rabieyan
- Department of Agronomy and Plant Breeding, Faculty of Agricultural Sciences and Engineering, University of Tehran, Karaj, Iran
| | - Mohammad Reza Bihamta
- Department of Agronomy and Plant Breeding, Faculty of Agricultural Sciences and Engineering, University of Tehran, Karaj, Iran.
| | - Mohsen Esmaeilzadeh Moghaddam
- Cereal Department, Seed and Plant Improvement Institute, Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran
| | - Hadi Alipour
- Department of Plant Production and Genetics, Faculty of Agriculture, Urmia University, Urmia, Iran.
| | - Valiollah Mohammadi
- Department of Agronomy and Plant Breeding, Faculty of Agricultural Sciences and Engineering, University of Tehran, Karaj, Iran
| | - Kobra Azizyan
- Department of Agronomy and Plant Breeding, Faculty of Agricultural Sciences and Engineering, University of Tehran, Karaj, Iran
| | - Saeideh Javid
- Department of Agronomy and Plant Breeding, Faculty of Agricultural Sciences and Engineering, University of Tehran, Karaj, Iran
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12
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Mulugeta B, Ortiz R, Geleta M, Hailesilassie T, Hammenhag C, Hailu F, Tesfaye K. Harnessing genome-wide genetic diversity, population structure and linkage disequilibrium in Ethiopian durum wheat gene pool. FRONTIERS IN PLANT SCIENCE 2023; 14:1192356. [PMID: 37546270 PMCID: PMC10400094 DOI: 10.3389/fpls.2023.1192356] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Accepted: 07/05/2023] [Indexed: 08/08/2023]
Abstract
Yanyang Liu, Henan Academy of Agricultural Sciences (HNAAS), China; Landraces are an important genetic source for transferring valuable novel genes and alleles required to enhance genetic variation. Therefore, information on the gene pool's genetic diversity and population structure is essential for the conservation and sustainable use of durum wheat genetic resources. Hence, the aim of this study was to assess genetic diversity, population structure, and linkage disequilibrium, as well as to identify regions with selection signature. Five hundred (500) individuals representing 46 landraces, along with 28 cultivars were evaluated using the Illumina Infinium 25K wheat SNP array, resulting in 8,178 SNPs for further analysis. Gene diversity (GD) and the polymorphic information content (PIC) ranged from 0.13-0.50 and 0.12-0.38, with mean GD and PIC values of 0.34 and 0.27, respectively. Linkage disequilibrium (LD) revealed 353,600 pairs of significant SNPs at a cut-off (r2 > 0.20, P < 0.01), with an average r2 of 0.21 for marker pairs. The nucleotide diversity (π) and Tajima's D (TD) per chromosome for the populations ranged from 0.29-0.36 and 3.46-5.06, respectively, with genome level, mean π values of 0.33 and TD values of 4.43. Genomic scan using the Fst outlier test revealed 85 loci under selection signatures, with 65 loci under balancing selection and 17 under directional selection. Putative candidate genes co-localized with regions exhibiting strong selection signatures were associated with grain yield, plant height, host plant resistance to pathogens, heading date, grain quality, and phenolic content. The Bayesian Model (STRUCTURE) and distance-based (principal coordinate analysis, PCoA, and unweighted pair group method with arithmetic mean, UPGMA) methods grouped the genotypes into five subpopulations, where landraces from geographically non-adjoining environments were clustered in the same cluster. This research provides further insights into population structure and genetic relationships in a diverse set of durum wheat germplasm, which could be further used in wheat breeding programs to address production challenges sustainably.
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Affiliation(s)
- Behailu Mulugeta
- Institute of Biotechnology, Addis Ababa University, Addis Ababa, Ethiopia
- Department of Plant Breeding, Swedish University of Agricultural Sciences, Alnarp, Sweden
- Sinana Agricultural Research Center, Oromia Agricultural Research Institute, Bale-Robe, Ethiopia
| | - Rodomiro Ortiz
- Department of Plant Breeding, Swedish University of Agricultural Sciences, Alnarp, Sweden
| | - Mulatu Geleta
- Department of Plant Breeding, Swedish University of Agricultural Sciences, Alnarp, Sweden
| | | | - Cecilia Hammenhag
- Department of Plant Breeding, Swedish University of Agricultural Sciences, Alnarp, Sweden
| | - Faris Hailu
- Bio and Emerging Technology Institute, Addis Ababa, Ethiopia
| | - Kassahun Tesfaye
- Institute of Biotechnology, Addis Ababa University, Addis Ababa, Ethiopia
- Department of Biology and Biotechnology, Wollo University, Dessie, Ethiopia
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13
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Mulugeta B, Tesfaye K, Ortiz R, Johansson E, Hailesilassie T, Hammenhag C, Hailu F, Geleta M. Marker-trait association analyses revealed major novel QTLs for grain yield and related traits in durum wheat. FRONTIERS IN PLANT SCIENCE 2023; 13:1009244. [PMID: 36777537 PMCID: PMC9909559 DOI: 10.3389/fpls.2022.1009244] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Accepted: 12/20/2022] [Indexed: 06/18/2023]
Abstract
The growing global demand for wheat for food is rising due to the influence of population growth and climate change. The dissection of complex traits by employing a genome-wide association study (GWAS) allows the identification of DNA markers associated with complex traits to improve the productivity of crops. We used GWAS with 10,045 single nucleotide polymorphism (SNP) markers to search for genomic regions associated with grain yield and related traits based on diverse panels of Ethiopian durum wheat. In Ethiopia, multi-environment trials of the genotypes were carried out at five locations. The genotyping was conducted using the 25k Illumina Wheat SNP array to explore population structure, linkage disequilibrium (LD), and marker-trait associations (MTAs). For GWAS, the multi-locus Fixed and Random Model Circulating Probability Unification (FarmCPU) model was applied. Broad-sense heritability estimates were high, ranging from 0.63 (for grain yield) to 0.97 (for thousand-kernel weight). The population structure based on principal component analysis, and model-based cluster analysis revealed two genetically distinct clusters with limited admixtures. The LD among SNPs declined within the range of 2.02-10.04 Mbp with an average of 4.28 Mbp. The GWAS scan based on the mean performance of the genotypes across the environments identified 44 significant MTAs across the chromosomes. Twenty-six of these MTAs are novel, whereas the remaining 18 were previously reported and confirmed in this study. We also identified candidate genes for the novel loci potentially regulating the traits. Hence, this study highlights the significance of the Ethiopian durum wheat gene pool for improving durum wheat globally. Furthermore, a breeding strategy focusing on accumulating favorable alleles at these loci could improve durum wheat production in the East African highlands and elsewhere.
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Affiliation(s)
- Behailu Mulugeta
- Institute of Biotechnology, Addis Ababa University, Addis Ababa, Ethiopia
- Department of Plant Breeding, Swedish University of Agricultural Sciences, Alnarp, Sweden
- Sinana Agricultural Research Center, Oromia Agricultural Research Institute, Bale-Robe, Ethiopia
| | - Kassahun Tesfaye
- Institute of Biotechnology, Addis Ababa University, Addis Ababa, Ethiopia
- Director General, Bio and Emerging Technology Institute (BETin), Addis Ababa, Ethiopia
| | - Rodomiro Ortiz
- Department of Plant Breeding, Swedish University of Agricultural Sciences, Alnarp, Sweden
| | - Eva Johansson
- Department of Plant Breeding, Swedish University of Agricultural Sciences, Alnarp, Sweden
| | | | - Cecilia Hammenhag
- Department of Plant Breeding, Swedish University of Agricultural Sciences, Alnarp, Sweden
| | - Faris Hailu
- Department of Biology and Biotechnology, Wollo University, Dessie, Ethiopia
| | - Mulatu Geleta
- Department of Plant Breeding, Swedish University of Agricultural Sciences, Alnarp, Sweden
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14
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Discovering Loci for Breeding Prospective and Phenology in Wheat Mediterranean Landraces by Environmental and eigenGWAS. Int J Mol Sci 2023; 24:ijms24021700. [PMID: 36675215 PMCID: PMC9863576 DOI: 10.3390/ijms24021700] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 12/27/2022] [Accepted: 01/12/2023] [Indexed: 01/19/2023] Open
Abstract
Knowledge of the genetic basis of traits controlling phenology, differentiation patterns, and environmental adaptation is essential to develop new cultivars under climate change conditions. Landrace collections are an appropriate platform to study the hidden variation caused by crop breeding. The use of genome-wide association analysis for phenology, climatic data and differentiation among Mediterranean landraces led to the identification of 651 marker-trait associations that could be grouped in 46 QTL hotspots. A candidate gene analysis using the annotation of the genome sequence of the wheat cultivar 'Chinese Spring' detected 1097 gene models within 33 selected QTL hotspots. From all the gene models, 42 were shown to be differentially expressed (upregulated) under abiotic stress conditions, and 9 were selected based on their levels of expression. Different gene families previously reported for their involvement in different stress responses were found (protein kinases, ras-like GTP binding proteins and ethylene-responsive transcription factors). Finally, the synteny analysis in the QTL hotspots regions among the genomes of wheat and other cereal species identified 23, 21 and 7 ortho-QTLs for Brachypodium, rice and maize, respectively, confirming the importance of these loci.
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15
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Lehnert H, Berner T, Lang D, Beier S, Stein N, Himmelbach A, Kilian B, Keilwagen J. Insights into breeding history, hotspot regions of selection, and untapped allelic diversity for bread wheat breeding. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2022; 112:897-918. [PMID: 36073999 DOI: 10.1111/tpj.15952] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Revised: 08/17/2022] [Accepted: 08/22/2022] [Indexed: 06/15/2023]
Abstract
Breeding has increasingly altered the genetics of crop plants since the domestication of their wild progenitors. It is postulated that the genetic diversity of elite wheat breeding pools is too narrow to cope with future challenges. In contrast, plant genetic resources (PGRs) of wheat stored in genebanks are valuable sources of unexploited genetic diversity. Therefore, to ensure breeding progress in the future, it is of prime importance to identify the useful allelic diversity available in PGRs and to transfer it into elite breeding pools. Here, a diverse collection consisting of modern winter wheat cultivars and genebank accessions was investigated based on reduced-representation genomic sequencing and an iSelect single nucleotide polymorphism (SNP) chip array. Analyses of these datasets provided detailed insights into population structure, levels of genetic diversity, sources of new allelic diversity, and genomic regions affected by breeding activities. We identified 57 regions representing genomic signatures of selection and 827 regions representing private alleles associated exclusively with genebank accessions. The presence of known functional wheat genes, quantitative trait loci, and large chromosomal modifications, i.e., introgressions from wheat wild relatives, provided initial evidence for putative traits associated within these identified regions. These findings were supported by the results of ontology enrichment analyses. The results reported here will stimulate further research and promote breeding in the future by allowing for the targeted introduction of novel allelic diversity into elite wheat breeding pools.
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Affiliation(s)
- Heike Lehnert
- Institute for Biosafety in Plant Biotechnology, Julius Kuehn Institute, Quedlinburg, Germany
| | - Thomas Berner
- Institute for Biosafety in Plant Biotechnology, Julius Kuehn Institute, Quedlinburg, Germany
| | - Daniel Lang
- PGSB, Helmholtz Center Munich, German Research Center for Environmental Health, Plant Genome and Systems Biology, Neuherberg, Germany
| | - Sebastian Beier
- Research Group Bioinformatics and Information Technology, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany
| | - Nils Stein
- Research Group Genomics of Genetic Resources, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany
- Center of integrated Breeding Research (CiBreed), Department of Crop Sciences, Georg-August-University, Göttingen, Germany
| | - Axel Himmelbach
- Research Group Genomics of Genetic Resources, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany
| | | | - Jens Keilwagen
- Institute for Biosafety in Plant Biotechnology, Julius Kuehn Institute, Quedlinburg, Germany
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16
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Shan D, Ali M, Shahid M, Arif A, Waheed MQ, Xia X, Trethowan R, Tester M, Poland J, Ogbonnaya FC, Rasheed A, He Z, Li H. Genetic networks underlying salinity tolerance in wheat uncovered with genome-wide analyses and selective sweeps. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2022; 135:2925-2941. [PMID: 35915266 DOI: 10.1007/s00122-022-04153-5] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Accepted: 06/16/2022] [Indexed: 06/15/2023]
Abstract
A genetic framework underpinning salinity tolerance at reproductive stage was revealed by genome-wide SNP markers and major adaptability genes in synthetic-derived wheats, and trait-associated loci were used to predict phenotypes. Using wild relatives of crops to identify genes related to improved productivity and resilience to climate extremes is a prioritized area of crop genetic improvement. High salinity is a widespread crop production constraint, and development of salt-tolerant cultivars is a sustainable solution. We evaluated a panel of 294 wheat accessions comprising synthetic-derived wheat lines (SYN-DERs) and modern bread wheat advanced lines under control and high salinity conditions at two locations. The GWAS analysis revealed a quantitative genetic framework of more than 200 loci with minor effect underlying salinity tolerance at reproductive stage. The significant trait-associated SNPs were used to predict phenotypes using a GBLUP model, and the prediction accuracy (r2) ranged between 0.57 and 0.74. The r2 values for flag leaf weight, days to flowering, biomass, and number of spikes per plant were all above 0.70, validating the phenotypic effects of the loci discovered in this study. Furthermore, the germplasm sets were compared to identify selection sweeps associated with salt tolerance loci in SYN-DERs. Six loci associated with salinity tolerance were found to be differentially selected in the SYN-DERs (12.4 Mb on chromosome (chr)1B, 7.1 Mb on chr2A, 11.2 Mb on chr2D, 200 Mb on chr3D, 600 Mb on chr6B, and 700.9 Mb on chr7B). A total of 228 reported markers and genes, including 17 well-characterized genes, were uncovered using GWAS and EigenGWAS. A linkage disequilibrium (LD) block on chr5A, including the Vrn-A1 gene at 575 Mb and its homeologs on chr5D, were strongly associated with multiple yield-related traits and flowering time under salinity stress conditions. The diversity panel was screened with more than 68 kompetitive allele-specific PCR (KASP) markers of functional genes in wheat, and the pleiotropic effects of superior alleles of Rht-1, TaGASR-A1, and TaCwi-A1 were revealed under salinity stress. To effectively utilize the extensive genetic information obtained from the GWAS analysis, a genetic interaction network was constructed to reveal correlations among the investigated traits. The genetic network data combined with GWAS, selective sweeps, and the functional gene survey provided a quantitative genetic framework for identifying differentially retained loci associated with salinity tolerance in wheat.
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Affiliation(s)
- Danting Shan
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), CIMMYT-China Office, 12 Zhongguancun South Street, Beijing, 100081, China
- Nanfan Research Institute, CAAS, Sanya, 572024, Hainan, China
| | - Mohsin Ali
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), CIMMYT-China Office, 12 Zhongguancun South Street, Beijing, 100081, China
- Nanfan Research Institute, CAAS, Sanya, 572024, Hainan, China
| | - Mohammed Shahid
- International Center for Biosaline Agriculture (ICBA), Al Ruwayyah 2, Academic City, Dubai, UAE
| | - Anjuman Arif
- National Institute of Agriculture and Biology (NIAB), Faisalabad, Pakistan
| | | | - Xianchun Xia
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), CIMMYT-China Office, 12 Zhongguancun South Street, Beijing, 100081, China
| | - Richard Trethowan
- Plant Breeding Institute, School of Life and Environmental Sciences, The University of Sydney, Sydney, 2006, Australia
| | - Mark Tester
- Division of Biological and Environmental Sciences and Engineering (BESE), King Abdullah University of Science and Technology (KASUT), Thuwal, 23955-6900, Saudi Arabia
| | - Jesse Poland
- Division of Biological and Environmental Sciences and Engineering (BESE), King Abdullah University of Science and Technology (KASUT), Thuwal, 23955-6900, Saudi Arabia
- Kansas State University, Manhattan, KS, USA
| | | | - Awais Rasheed
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), CIMMYT-China Office, 12 Zhongguancun South Street, Beijing, 100081, China.
| | - Zhonghu He
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), CIMMYT-China Office, 12 Zhongguancun South Street, Beijing, 100081, China
| | - Huihui Li
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), CIMMYT-China Office, 12 Zhongguancun South Street, Beijing, 100081, China.
- Nanfan Research Institute, CAAS, Sanya, 572024, Hainan, China.
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17
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Liu W, Li Y, Sun Y, Tang J, Che J, Yang S, Wang X, Zhang R, Zhang H. Genetic analysis of morphological traits in spring wheat from the Northeast of China by a genome-wide association study. Front Genet 2022; 13:934757. [PMID: 36061191 PMCID: PMC9434797 DOI: 10.3389/fgene.2022.934757] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2022] [Accepted: 07/15/2022] [Indexed: 11/13/2022] Open
Abstract
Identification of the gene for agronomic traits is important for the wheat marker-assisted selection (MAS) breeding. To identify the new and stable loci for agronomic traits, including flag leaf length (FLL), flag leaf width (FLW), uppermost internode length (UIL), and plant morphology (PM, including prostrate, semi-prostrate, and erect). A total of 251 spring wheat accessions collected from the Northeast of China were used to conduct genome-wide association study (GWAS) by 55K SNP arrays. A total of 30 loci for morphological traits were detected, and each explained 4.8–17.9% of the phenotypic variations. Of these, 13 loci have been reported by previous studies, and the other 17 are novel. We have identified seven genes involved in the signal transduction, cell-cycle progression, and plant development pathway as candidate genes. This study provides new insights into the genetic basis of morphological traits. The associated SNPs and accessions with more of favorable alleles identified in this study could be used to promote the wheat breeding progresses.
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Affiliation(s)
- Wenlin Liu
- Crop Resources Institute, Heilongjiang Academy of Agricultural Sciences, Harbin, China
| | - Yuyao Li
- Heilongjiang Academy of Agricultural Sciences, Harbin, China
| | - Yan Sun
- Crop Resources Institute, Heilongjiang Academy of Agricultural Sciences, Harbin, China
| | - Jingquan Tang
- Crop Resources Institute, Heilongjiang Academy of Agricultural Sciences, Harbin, China
| | - Jingyu Che
- KeShan Branch of Heilongjiang Academy of Agricultural Sciences, Qiqihaer, China
| | - Shuping Yang
- Crop Resources Institute, Heilongjiang Academy of Agricultural Sciences, Harbin, China
| | - Xiangyu Wang
- Crop Resources Institute, Heilongjiang Academy of Agricultural Sciences, Harbin, China
| | - Rui Zhang
- Institute of Forage and Grassland Sciences, Heilongjiang Academy of Agricultural Sciences, Harbin, China
| | - Hongji Zhang
- Crop Resources Institute, Heilongjiang Academy of Agricultural Sciences, Harbin, China
- *Correspondence: Hongji Zhang,
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18
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Ali M, Danting S, Wang J, Sadiq H, Rasheed A, He Z, Li H. Genetic Diversity and Selection Signatures in Synthetic-Derived Wheats and Modern Spring Wheat. FRONTIERS IN PLANT SCIENCE 2022; 13:877496. [PMID: 35903232 PMCID: PMC9315363 DOI: 10.3389/fpls.2022.877496] [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: 02/16/2022] [Accepted: 06/10/2022] [Indexed: 06/15/2023]
Abstract
Synthetic hexaploid wheats and their derived advanced lines were subject to empirical selection in developing genetically superior cultivars. To investigate genetic diversity, patterns of nucleotide diversity, population structure, and selection signatures during wheat breeding, we tested 422 wheat accessions, including 145 synthetic-derived wheats, 128 spring wheat cultivars, and 149 advanced breeding lines from Pakistan. A total of 18,589 high-quality GBS-SNPs were identified that were distributed across the A (40%), B (49%), and D (11%) genomes. Values of population diversity parameters were estimated across chromosomes and genomes. Genome-wide average values of genetic diversity and polymorphic information content were estimated to be 0.30 and 0.25, respectively. Neighbor-joining (NJ) tree, principal component analysis (PCA), and kinship analyses revealed that synthetic-derived wheats and advanced breeding lines were genetically diverse. The 422 accessions were not separated into distinct groups by NJ analysis and confirmed using the PCA. This conclusion was validated with both relative kinship and Rogers' genetic distance analyses. EigenGWAS analysis revealed that 32 unique genome regions had undergone selection. We found that 50% of the selected regions were located in the B-genome, 29% in the D-genome, and 21% in the A-genome. Previously known functional genes or QTL were found within the selection regions associated with phenology-related traits such as vernalization, adaptability, disease resistance, and yield-related traits. The selection signatures identified in the present investigation will be useful for understanding the targets of modern wheat breeding in Pakistan.
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Affiliation(s)
- Mohsin Ali
- Institute of Crop Sciences and CIMMYT China Office, Chinese Academy of Agricultural Sciences (CAAS), Beijing, China
- Nanfan Research Institute, Chinese Academy of Agricultural Sciences (CAAS), Sanya, China
| | - Shan Danting
- Institute of Crop Sciences and CIMMYT China Office, Chinese Academy of Agricultural Sciences (CAAS), Beijing, China
- Nanfan Research Institute, Chinese Academy of Agricultural Sciences (CAAS), Sanya, China
| | - Jiankang Wang
- Institute of Crop Sciences and CIMMYT China Office, Chinese Academy of Agricultural Sciences (CAAS), Beijing, China
| | - Hafsa Sadiq
- Department of Plant Sciences, Quaid-i-Azam University, Islamabad, Pakistan
| | - Awais Rasheed
- Institute of Crop Sciences and CIMMYT China Office, Chinese Academy of Agricultural Sciences (CAAS), Beijing, China
- Department of Plant Sciences, Quaid-i-Azam University, Islamabad, Pakistan
| | - Zhonghu He
- Institute of Crop Sciences and CIMMYT China Office, Chinese Academy of Agricultural Sciences (CAAS), Beijing, China
| | - Huihui Li
- Institute of Crop Sciences and CIMMYT China Office, Chinese Academy of Agricultural Sciences (CAAS), Beijing, China
- Nanfan Research Institute, Chinese Academy of Agricultural Sciences (CAAS), Sanya, China
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19
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Rabieyan E, Bihamta MR, Moghaddam ME, Mohammadi V, Alipour H. Genome-wide association mapping and genomic prediction for pre‑harvest sprouting resistance, low α-amylase and seed color in Iranian bread wheat. BMC PLANT BIOLOGY 2022; 22:300. [PMID: 35715737 PMCID: PMC9204952 DOI: 10.1186/s12870-022-03628-3] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Accepted: 05/05/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND Pre-harvest sprouting (PHS) refers to a phenomenon, in which the physiologically mature seeds are germinated on the spike before or during the harvesting practice owing to high humidity or prolonged period of rainfall. Pre-harvest sprouting (PHS) remarkably decreases seed quality and yield in wheat; hence it is imperative to uncover genomic regions responsible for PHS tolerance to be used in wheat breeding. A genome-wide association study (GWAS) was carried out using 298 bread wheat landraces and varieties from Iran to dissect the genomic regions of PHS tolerance in a well-irrigated environment. Three different approaches (RRBLUP, GBLUP and BRR) were followed to estimate prediction accuracies in wheat genomic selection. RESULTS Genomes B, A, and D harbored the largest number of significant marker pairs (MPs) in both landraces (427,017, 328,006, 92,702 MPs) and varieties (370,359, 266,708, 63,924 MPs), respectively. However, the LD levels were found the opposite, i.e., genomes D, A, and B have the highest LD, respectively. Association mapping by using GLM and MLM models resulted in 572 and 598 marker-trait associations (MTAs) for imputed SNPs (- log10 P > 3), respectively. Gene ontology exhibited that the pleitropic MPs located on 1A control seed color, α-Amy activity, and PHS. RRBLUP model indicated genetic effects better than GBLUP and BRR, offering a favorable tool for wheat genomic selection. CONCLUSIONS Gene ontology exhibited that the pleitropic MPs located on 1A can control seed color, α-Amy activity, and PHS. The verified markers in the current work can provide an opportunity to clone the underlying QTLs/genes, fine mapping, and genome-assisted selection.Our observations uncovered key MTAs related to seed color, α-Amy activity, and PHS that can be exploited in the genome-mediated development of novel varieties in wheat.
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Affiliation(s)
- Ehsan Rabieyan
- Department of Agronomy and Plant Breeding, Faculty of Agricultural Sciences and Engineering, University of Tehran, Karaj, Iran
| | - Mohammad Reza Bihamta
- Department of Agronomy and Plant Breeding, Faculty of Agricultural Sciences and Engineering, University of Tehran, Karaj, Iran
| | | | - Valiollah Mohammadi
- Department of Agronomy and Plant Breeding, Faculty of Agricultural Sciences and Engineering, University of Tehran, Karaj, Iran
| | - Hadi Alipour
- Department of Plant Production and Genetics, Faculty of Agriculture, Urmia University, Urmia, Iran
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20
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Hussain S, Habib M, Ahmed Z, Sadia B, Bernardo A, Amand PS, Bai G, Ghori N, Khan AI, Awan FS, Maqbool R. Genotyping-by-Sequencing Based Molecular Genetic Diversity of Pakistani Bread Wheat ( Triticum aestivum L.) Accessions. Front Genet 2022; 13:772517. [PMID: 35464861 PMCID: PMC9019749 DOI: 10.3389/fgene.2022.772517] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Accepted: 01/07/2022] [Indexed: 11/29/2022] Open
Abstract
Spring wheat (Triticum aestivum L.) is one of the most imperative staple food crops, with an annual production of 765 million tons globally to feed ∼40% world population. Genetic diversity in available germplasm is crucial for sustainable wheat improvement to ensure global food security. A diversity panel of 184 Pakistani wheat accessions was genotyped using 123,596 high-quality single nucleotide polymorphism (SNP) markers generated by genotyping-by-sequencing with 42% of the SNPs mapped on B, 36% on A, and 22% on D sub-genomes of wheat. Chromosome 2B contains the most SNPs (9,126), whereas 4D has the least (2,660) markers. The mean polymorphic information content, genetic diversity, and major allele frequency of the population were 0.157, 0.1844, and 0.87, respectively. Analysis of molecular variance revealed a higher genetic diversity (80%) within the sub-population than among the sub-populations (20%). The genome-wide linkage disequilibrium was 0.34 Mbp for the whole wheat genome. Among the three subgenomes, A has the highest LD decay value (0.29 Mbp), followed by B (0.2 Mbp) and D (0.07 Mbp) genomes, respectively. The results of population structure, principal coordinate analysis, phylogenetic tree, and kinship analysis also divided the whole population into three clusters comprising 31, 33, and 120 accessions in group 1, group 2, and group 3, respectively. All groups were dominated by the local wheat accessions. Estimation of genetic diversity will be a baseline for the selection of breeding parents for mutations and the genome-wide association and marker-assisted selection studies.
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Affiliation(s)
- Shabbir Hussain
- Center of Agricultural Biochemistry and Biotechnology, University of Agriculture, Faisalabad, Pakistan
| | - Madiha Habib
- Center of Agricultural Biochemistry and Biotechnology, University of Agriculture, Faisalabad, Pakistan
| | - Zaheer Ahmed
- Department of Plant Breeding and Genetics, University of Agriculture, Faisalabad, Pakistan
| | - Bushra Sadia
- Center of Agricultural Biochemistry and Biotechnology, University of Agriculture, Faisalabad, Pakistan
| | - Amy Bernardo
- USDA, Hard Winter Wheat Genetics Research Unit, Manhattan, KS, United States
| | - Paul St Amand
- USDA, Hard Winter Wheat Genetics Research Unit, Manhattan, KS, United States
| | - Guihua Bai
- USDA, Hard Winter Wheat Genetics Research Unit, Manhattan, KS, United States
| | - Nida Ghori
- USDA, Hard Winter Wheat Genetics Research Unit, Manhattan, KS, United States
| | - Azeem I Khan
- Department of Plant Breeding and Genetics, University of Agriculture, Faisalabad, Pakistan
| | - Faisal S Awan
- Center of Agricultural Biochemistry and Biotechnology, University of Agriculture, Faisalabad, Pakistan
| | - Rizwana Maqbool
- Department of Plant Breeding and Genetics, University of Agriculture, Faisalabad, Pakistan
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21
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Barabaschi D, Cattivelli L. Plant breeding highlights master genes in major regulatory pathways. MOLECULAR PLANT 2022; 15:391-392. [PMID: 35217223 DOI: 10.1016/j.molp.2022.02.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Revised: 02/18/2022] [Accepted: 02/19/2022] [Indexed: 06/14/2023]
Affiliation(s)
- Delfina Barabaschi
- CREA Research Centre for Genomics and Bioinformatics, Via San Protaso 302, Fiorenzuola d'Arda 29017, Italy
| | - Luigi Cattivelli
- CREA Research Centre for Genomics and Bioinformatics, Via San Protaso 302, Fiorenzuola d'Arda 29017, Italy.
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22
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Francki MG, Stainer GS, Walker E, Rebetzke GJ, Stefanova KT, French RJ. Phenotypic Evaluation and Genetic Analysis of Seedling Emergence in a Global Collection of Wheat Genotypes ( Triticum aestivum L.) Under Limited Water Availability. FRONTIERS IN PLANT SCIENCE 2021; 12:796176. [PMID: 35003185 PMCID: PMC8739788 DOI: 10.3389/fpls.2021.796176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/16/2021] [Accepted: 11/15/2021] [Indexed: 06/14/2023]
Abstract
The challenge in establishing an early-sown wheat crop in southern Australia is the need for consistently high seedling emergence when sowing deep in subsoil moisture (>10 cm) or into dry top-soil (4 cm). However, the latter is strongly reliant on a minimum soil water availability to ensure successful seedling emergence. This study aimed to: (1) evaluate 233 Australian and selected international wheat genotypes for consistently high seedling emergence under limited soil water availability when sown in 4 cm of top-soil in field and glasshouse (GH) studies; (2) ascertain genetic loci associated with phenotypic variation using a genome-wide association study (GWAS); and (3) compare across loci for traits controlling coleoptile characteristics, germination, dormancy, and pre-harvest sprouting. Despite significant (P < 0.001) environment and genotype-by-environment interactions within and between field and GH experiments, eight genotypes that included five cultivars, two landraces, and one inbred line had consistently high seedling emergence (mean value > 85%) across nine environments. Moreover, 21 environment-specific quantitative trait loci (QTL) were detected in GWAS analysis on chromosomes 1B, 1D, 2B, 3A, 3B, 4A, 4B, 5B, 5D, and 7D, indicating complex genetic inheritance controlling seedling emergence. We aligned QTL for known traits and individual genes onto the reference genome of wheat and identified 16 QTL for seedling emergence in linkage disequilibrium with coleoptile length, width, and cross-sectional area, pre-harvest sprouting and dormancy, germination, seed longevity, and anthocyanin development. Therefore, it appears that seedling emergence is controlled by multifaceted networks of interrelated genes and traits regulated by different environmental cues.
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Affiliation(s)
- Michael G. Francki
- Department of Primary Industries and Regional Development, South Perth, WA, Australia
- State Agricultural Biotechnology Centre, Murdoch University, Murdoch, WA, Australia
| | - Grantley S. Stainer
- Department of Primary Industries and Regional Development, Merredin, WA, Australia
| | - Esther Walker
- Department of Primary Industries and Regional Development, South Perth, WA, Australia
- State Agricultural Biotechnology Centre, Murdoch University, Murdoch, WA, Australia
| | - Gregory J. Rebetzke
- Commonwealth Scientific and Industrial Research Organisation, Agriculture and Food, Canberra, ACT, Australia
| | - Katia T. Stefanova
- Department of Primary Industries and Regional Development, South Perth, WA, Australia
| | - Robert J. French
- Department of Primary Industries and Regional Development, Merredin, WA, Australia
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23
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Singh S, Jighly A, Sehgal D, Burgueño J, Joukhadar R, Singh SK, Sharma A, Vikram P, Sansaloni CP, Govindan V, Bhavani S, Randhawa M, Solis-Moya E, Singh S, Pardo N, Arif MAR, Laghari KA, Basandrai D, Shokat S, Chaudhary HK, Saeed NA, Basandrai AK, Ledesma-Ramírez L, Sohu VS, Imtiaz M, Sial MA, Wenzl P, Singh GP, Bains NS. Direct introgression of untapped diversity into elite wheat lines. NATURE FOOD 2021; 2:819-827. [PMID: 37117978 DOI: 10.1038/s43016-021-00380-z] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Accepted: 08/27/2021] [Indexed: 04/30/2023]
Abstract
The effective utilization of natural variation has become essential in addressing the challenges that climate change and population growth pose to global food security. Currently adopted protracted approaches to introgress exotic alleles into elite cultivars need substantial transformation. Here, through a strategic three-way crossing scheme among diverse exotics and the best historical elites (exotic/elite1//elite2), 2,867 pre-breeding lines were developed, genotyped and screened for multiple agronomic traits in four mega-environments. A meta-genome-wide association study, selective sweeps and haplotype-block-based analyses unveiled selection footprints in the genomes of pre-breeding lines as well as exotic-specific associations with agronomic traits. A simulation with a neutrality assumption demonstrated that many pre-breeding lines had significant exotic contributions despite substantial selection bias towards elite genomes. National breeding programmes worldwide have adopted 95 lines for germplasm enhancement, and 7 additional lines are being advanced in varietal release trials. This study presents a great leap forwards in the mobilization of GenBank variation to the breeding pipelines.
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Affiliation(s)
- Sukhwinder Singh
- International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico.
- Geneshifters, Pullman, WA, USA.
| | - A Jighly
- Agriculture Victoria, AgriBio, Centre for AgriBiosciences, Bundoora, Victoria, Australia
| | - D Sehgal
- International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico
| | - J Burgueño
- International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico
| | - R Joukhadar
- Agriculture Victoria, AgriBio, Centre for AgriBiosciences, Bundoora, Victoria, Australia
| | - S K Singh
- ICAR-Indian Institute of Wheat and Barley Research, Karnal, India
| | - A Sharma
- Department of Plant Breeding & Genetics, Punjab Agricultural University, Ludhiana, India
| | - P Vikram
- International Center for Biosaline Agriculture, Dubai, United Arab Emirates
| | - C P Sansaloni
- International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico
| | - V Govindan
- International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico
| | - S Bhavani
- International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico
| | - M Randhawa
- CIMMYT-World Agroforestry Centre (ICRAF), Nairobi, Kenya
| | - E Solis-Moya
- Carretera Celaya-San Miguel de Allende, Celaya, México
| | - S Singh
- ICAR-National Institute of Plant Biotechnology, New Delhi, India
| | - N Pardo
- International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico
| | - M A R Arif
- Nuclear Institute for Agriculture and Biology, Faisalabad, Pakistan
| | - K A Laghari
- Nuclear Institute of Agriculture, Tando Jam, Pakistan
| | - D Basandrai
- CSK Himachal Pradesh Agricultural University Palampur, Palampur, India
| | - S Shokat
- Nuclear Institute for Agriculture and Biology, Faisalabad, Pakistan
- Department of Plant and Environmental Sciences, Crop Science, University of Copenhagen, Taastrup, Denmark
| | - H K Chaudhary
- CSK Himachal Pradesh Agricultural University Palampur, Palampur, India
| | - N A Saeed
- Nuclear Institute for Agriculture and Biology, Faisalabad, Pakistan
| | - A K Basandrai
- CSK Himachal Pradesh Agricultural University Palampur, Palampur, India
| | | | - V S Sohu
- Department of Plant Breeding & Genetics, Punjab Agricultural University, Ludhiana, India
| | | | - M A Sial
- Nuclear Institute of Agriculture, Tando Jam, Pakistan
| | | | - G P Singh
- ICAR-Indian Institute of Wheat and Barley Research, Karnal, India
| | - N S Bains
- Department of Plant Breeding & Genetics, Punjab Agricultural University, Ludhiana, India
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24
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Alipour H, Abdi H, Rahimi Y, Bihamta MR. Dissection of the genetic basis of genotype-by-environment interactions for grain yield and main agronomic traits in Iranian bread wheat landraces and cultivars. Sci Rep 2021; 11:17742. [PMID: 34493739 PMCID: PMC8423731 DOI: 10.1038/s41598-021-96576-1] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2021] [Accepted: 08/11/2021] [Indexed: 02/07/2023] Open
Abstract
Understanding the genetic basis of performance stability is essential to maintain productivity, especially under severe conditions. In the present study, 268 Iranian bread wheat landraces and cultivars were evaluated in four well-watered and two rain-fed conditions for different traits. According to breeding programs, cultivars were in a group with a high mean and stability in terms of GY, GN, and SW traits, while in terms of PH, they had a low mean and high stability. The stability of cultivars and landraces was related to dynamic and static stability, respectively. The highest number of marker pairs and lowest LD decay distance in both cultivars and landraces was observed on the B genome. Population structure differentiated indigenous cultivars and landraces, and the GWAS results for each were almost different despite the commonalities. Chromosomes 1B, 3B, 7B, 2A, and 4A had markers with pleiotropic effects on the stability of different traits. Due to two rain-fed environments, the Gene Ontology (GO) confirmed the accuracy of the results. The identified markers in this study can be helpful in breeding high-performance and stable genotypes and future breeding programs such as fine mapping and cloning.
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Affiliation(s)
- Hadi Alipour
- Department of Plant Production and Genetics, Faculty of Agriculture, Urmia University, Urmia, Iran.
| | - Hossein Abdi
- Department of Plant Production and Genetics, Faculty of Agriculture, Urmia University, Urmia, Iran
| | - Yousef Rahimi
- Department of Plant Biology, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Mohammad Reza Bihamta
- Department of Agronomy and Plant Breeding, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran
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25
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Liu S, Huang S, Zeng Q, Wang X, Yu R, Wang Q, Singh RP, Bhavani S, Kang Z, Wu J, Han D. Refined mapping of stripe rust resistance gene YrP10090 within a desirable haplotype for wheat improvement on chromosome 6A. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2021; 134:2005-2021. [PMID: 33683400 DOI: 10.1007/s00122-021-03801-6] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/25/2020] [Accepted: 02/23/2021] [Indexed: 06/12/2023]
Abstract
A large genomic region spanning over 300 Mb on chromosome 6A under intense artificial selection harbors multiple loci associated with favorable traits including stripe rust resistance in wheat. The development of resistance cultivars can be an optimal strategy for controlling wheat stripe rust disease. Although loci for stripe rust resistance have been identified on chromosome 6A in previous studies, it is unclear whether these loci span a common genetic interval, and few studies have attempted to analyze the haplotype changes that have accompanied wheat improvement over the period of modern breeding. In this study, we used F2:3 families and F6:7 recombinant inbred lines (RILs) derived from a cross between a resistant CIMMYT wheat accession P10090 and the susceptible landrace Mingxian 169 to improve the resolution of the QTL on chromosome 6A. The co-located QTL, designated as YrP10090, was flanked by SNP markers AX-94460938 and AX-110585473 with a genetic interval of 3.5 cM, however, corresponding to a large physical distance of over 300 Mb in RefSeq v.1.0 (positions 107.1-446.5 Mb). More than 1,300 SNP markers in this genetic region were extracted for haplotype analysis in a panel of 1,461 worldwide common wheat accessions, and three major haplotypes (Hap1, Hap2, and Hap3) were identified. The favorable haplotype Hap1 associated with stripe rust resistance exhibited a large degree of linkage disequilibrium. Selective sweep analyses were performed between different haplotype groups, revealing specific genomic regions with strong artificial selection signals. These regions harbored multiple desirable traits associated with resilience to environmental stress, different yield components, and quality characteristics. P10090 and its derivatives that carry the desirable haplotype can provide a concrete foundation for bread wheat improvement including the genomic selection.
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Affiliation(s)
- Shengjie Liu
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, Shaanxi, 712100, People's Republic of China
| | - Shuo Huang
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, Shaanxi, 712100, People's Republic of China
| | - Qingdong Zeng
- State Key Laboratory of Crop Stress Biology for Arid Areas, Plant Protection, Northwest A&F University, Yangling, Shaanxi, 712100, People's Republic of China
| | - Xiaoting Wang
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, Shaanxi, 712100, People's Republic of China
| | - Rui Yu
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, Shaanxi, 712100, People's Republic of China
| | - Qilin Wang
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, Shaanxi, 712100, People's Republic of China
| | - Ravi P Singh
- International Maize and Wheat Improvement Center (CIMMYT), El Batan, 56237, Texcoco, Estado de Mexico, Mexico
| | - Sridhar Bhavani
- International Maize and Wheat Improvement Center (CIMMYT), El Batan, 56237, Texcoco, Estado de Mexico, Mexico
| | - Zhensheng Kang
- State Key Laboratory of Crop Stress Biology for Arid Areas, Plant Protection, Northwest A&F University, Yangling, Shaanxi, 712100, People's Republic of China
| | - Jianhui Wu
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, Shaanxi, 712100, People's Republic of China.
| | - Dejun Han
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, Shaanxi, 712100, People's Republic of China.
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Soriano JM, Colasuonno P, Marcotuli I, Gadaleta A. Meta-QTL analysis and identification of candidate genes for quality, abiotic and biotic stress in durum wheat. Sci Rep 2021; 11:11877. [PMID: 34088972 PMCID: PMC8178383 DOI: 10.1038/s41598-021-91446-2] [Citation(s) in RCA: 40] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Accepted: 05/25/2021] [Indexed: 11/15/2022] Open
Abstract
The genetic improvement of durum wheat and enhancement of plant performance often depend on the identification of stable quantitative trait loci (QTL) and closely linked molecular markers. This is essential for better understanding the genetic basis of important agronomic traits and identifying an effective method for improving selection efficiency in breeding programmes. Meta-QTL analysis is a useful approach for dissecting the genetic basis of complex traits, providing broader allelic coverage and higher mapping resolution for the identification of putative molecular markers to be used in marker-assisted selection. In the present study, extensive QTL meta-analysis was conducted on 45 traits of durum wheat, including quality and biotic and abiotic stress-related traits. A total of 368 QTL distributed on all 14 chromosomes of genomes A and B were projected: 171 corresponded to quality-related traits, 127 to abiotic stress and 71 to biotic stress, of which 318 were grouped in 85 meta-QTL (MQTL), 24 remained as single QTL and 26 were not assigned to any MQTL. The number of MQTL per chromosome ranged from 4 in chromosomes 1A and 6A to 9 in chromosome 7B; chromosomes 3A and 7A showed the highest number of individual QTL (4), and chromosome 7B the highest number of undefined QTL (4). The recently published genome sequence of durum wheat was used to search for candidate genes within the MQTL peaks. This work will facilitate cloning and pyramiding of QTL to develop new cultivars with specific quantitative traits and speed up breeding programs.
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Affiliation(s)
- Jose Miguel Soriano
- Sustainable Field Crops Programme, IRTA (Institute for Food and Agricultural Research and Technology), 25198, Lleida, Spain.
| | - Pasqualina Colasuonno
- Department of Agricultural and Environmental Science, University of Bari 'Aldo Moro', Via G. Amendola 165/A, 70126, Bari, Italy
| | - Ilaria Marcotuli
- Department of Agricultural and Environmental Science, University of Bari 'Aldo Moro', Via G. Amendola 165/A, 70126, Bari, Italy.
| | - Agata Gadaleta
- Department of Agricultural and Environmental Science, University of Bari 'Aldo Moro', Via G. Amendola 165/A, 70126, Bari, Italy
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Soriano JM, Sansaloni C, Ammar K, Royo C. Labelling Selective Sweeps Used in Durum Wheat Breeding from a Diverse and Structured Panel of Landraces and Cultivars. BIOLOGY 2021; 10:biology10040258. [PMID: 33805192 PMCID: PMC8064341 DOI: 10.3390/biology10040258] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/23/2021] [Revised: 03/17/2021] [Accepted: 03/23/2021] [Indexed: 12/12/2022]
Abstract
Simple Summary Evaluation of the genetic diversity of a crop species is a critical step for breeding. Landraces are essential to avoid genetic erosion, and Mediterranean landraces are an important group of genetic resources due to their high genetic variability, adaptation to local conditions in rainfed environments, and their resilience to pests and pathogens. This study uses a genome-wide association approach employing eigenvectors to identify selective sweeps among Mediterranean durum wheat landraces and a world panel of modern cultivars. Abstract A panel of 387 durum wheat genotypes including Mediterranean landraces and modern cultivars was characterized with 46,161 diversity arrays technology (DArTseq) markers. Analysis of population structure uncovered the existence of five subpopulations (SP) related to the pattern of migration of durum wheat from the domestication area to the west of the Mediterranean basin (SPs 1, 2, and 3) and further improved germplasm (SPs 4 and 5). The total genetic diversity (HT) was 0.40 with a genetic differentiation (GST) of 0.08 and a mean gene flow among SPs of 6.02. The lowest gene flow was detected between SP 1 (presumably the ancient genetic pool of the panel) and SPs 4 and 5. However, gene flow from SP 2 to modern cultivars was much higher. The highest gene flow was detected between SP 3 (western Mediterranean germplasm) and SP 5 (North American and European cultivars). A genome wide association study (GWAS) approach using the top ten eigenvectors as phenotypic data revealed the presence of 89 selective sweeps, represented as quantitative trait loci (QTL) hotspots, widely distributed across the durum wheat genome. A principal component analysis (PCoA) using 147 markers with −log10p > 5 identified three regions located on chromosomes 2A, 2B and 3A as the main drivers for differentiation of Mediterranean landraces. Gene flow between SPs offers clues regarding the putative use of Mediterranean old durum germplasm by the breeding programs represented in the structure analysis. EigenGWAS identified selective sweeps among landraces and modern cultivars. The analysis of the corresponding genomic regions in the ‘Zavitan’, ‘Svevo’ and ‘Chinese Spring’ genomes discovered the presence of important functional genes including Ppd, Vrn, Rht, and gene models involved in important biological processes including LRR-RLK, MADS-box, NAC, and F-box.
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Affiliation(s)
- Jose Miguel Soriano
- Sustainable Field Crops Programme, Institute for Food and Agricultural Research and Technology (IRTA), 25198 Lleida, Spain;
- Correspondence:
| | - Carolina Sansaloni
- Centro Internacional de Mejoramiento de Maíz y Trigo (CIMMYT), El Batán, Texcoco 56237, Mexico; (C.S.); (K.A.)
| | - Karim Ammar
- Centro Internacional de Mejoramiento de Maíz y Trigo (CIMMYT), El Batán, Texcoco 56237, Mexico; (C.S.); (K.A.)
| | - Conxita Royo
- Sustainable Field Crops Programme, Institute for Food and Agricultural Research and Technology (IRTA), 25198 Lleida, Spain;
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Tyrka M, Mokrzycka M, Bakera B, Tyrka D, Szeliga M, Stojałowski S, Matysik P, Rokicki M, Rakoczy-Trojanowska M, Krajewski P. Evaluation of genetic structure in European wheat cultivars and advanced breeding lines using high-density genotyping-by-sequencing approach. BMC Genomics 2021; 22:81. [PMID: 33509072 PMCID: PMC7842024 DOI: 10.1186/s12864-020-07351-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Accepted: 12/27/2020] [Indexed: 01/07/2023] Open
Abstract
BACKGROUND The genetic diversity and gene pool characteristics must be clarified for efficient genome-wide association studies, genomic selection, and hybrid breeding. The aim of this study was to evaluate the genetic structure of 509 wheat accessions representing registered varieties and advanced breeding lines via the high-density genotyping-by-sequencing approach. RESULTS More than 30% of 13,499 SNP markers representing 2162 clusters were mapped to genes, whereas 22.50% of 26,369 silicoDArT markers overlapped with coding sequences and were linked in 3527 blocks. Regarding hexaploidy, perfect sequence matches following BLAST searches were not sufficient for the unequivocal mapping to unique loci. Moreover, allelic variations in homeologous loci interfered with heterozygosity calculations for some markers. Analyses of the major genetic changes over the last 27 years revealed the selection pressure on orthologs of the gibberellin biosynthesis-related GA2 gene and the senescence-associated SAG12 gene. A core collection representing the wheat population was generated for preserving germplasm and optimizing breeding programs. CONCLUSIONS Our results confirmed considerable differences among wheat subgenomes A, B and D, with D characterized by the lowest diversity but the highest LD. They revealed genomic regions that have been targeted by breeding.
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Affiliation(s)
- Mirosław Tyrka
- Rzeszow University of Technology, Powstańców Warszawy 12, 35-959, Rzeszów, Poland
| | - Monika Mokrzycka
- Institute of Plant Genetics, Polish Academy of Science, Strzeszyńska 34, 60-479, Poznań, Poland
| | - Beata Bakera
- Warsaw University of Life Sciences, Nowoursynowska 166, 02-787, Warszawa, Poland
| | - Dorota Tyrka
- Rzeszow University of Technology, Powstańców Warszawy 12, 35-959, Rzeszów, Poland
| | - Magdalena Szeliga
- Rzeszow University of Technology, Powstańców Warszawy 12, 35-959, Rzeszów, Poland
| | - Stefan Stojałowski
- West Pomeranian University of Technology Szczecin, Słowackiego 17, 71-434, Szczecin, Poland
| | - Przemysław Matysik
- Plant Breeding Strzelce Group IHAR Ltd., Kasztanowa 5, 63-004, Tulce, Poland
| | - Michał Rokicki
- Poznań Plant Breeding Ltd., Główna 20, 99-307, Strzelce, Poland
| | | | - Paweł Krajewski
- Institute of Plant Genetics, Polish Academy of Science, Strzeszyńska 34, 60-479, Poznań, Poland.
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Hessenauer P, Feau N, Gill U, Schwessinger B, Brar GS, Hamelin RC. Evolution and Adaptation of Forest and Crop Pathogens in the Anthropocene. PHYTOPATHOLOGY 2021; 111:49-67. [PMID: 33200962 DOI: 10.1094/phyto-08-20-0358-fi] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Anthropocene marks the era when human activity is making a significant impact on earth, its ecological and biogeographical systems. The domestication and intensification of agricultural and forest production systems have had a large impact on plant and tree health. Some pathogens benefitted from these human activities and have evolved and adapted in response to the expansion of crop and forest systems, resulting in global outbreaks. Global pathogen genomics data including population genomics and high-quality reference assemblies are crucial for understanding the evolution and adaptation of pathogens. Crops and forest trees have remarkably different characteristics, such as reproductive time and the level of domestication. They also have different production systems for disease management with more intensive management in crops than forest trees. By comparing and contrasting results from pathogen population genomic studies done on widely different agricultural and forest production systems, we can improve our understanding of pathogen evolution and adaptation to different selection pressures. We find that in spite of these differences, similar processes such as hybridization, host jumps, selection, specialization, and clonal expansion are shaping the pathogen populations in both crops and forest trees. We propose some solutions to reduce these impacts and lower the probability of global pathogen outbreaks so that we can envision better management strategies to sustain global food production as well as ecosystem services.
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Affiliation(s)
- Pauline Hessenauer
- Faculty of Forestry, Geography and Geomatics, Laval University, Quebec City, QC, G1V 0A6 Canada
| | - Nicolas Feau
- Faculty of Forestry, The University of British Columbia, Vancouver, BC, V6T 1Z4 Canada
| | - Upinder Gill
- College of Agriculture, Food Systems, and Natural Resources, North Dakota State University, Fargo, ND 58102, U.S.A
| | - Benjamin Schwessinger
- Research School of Biology, Australian National University, Acton, ACT 2601 Australia
| | - Gurcharn S Brar
- Faculty of Land and Food Systems, The University of British Columbia, Vancouver, BC, V6T 1Z4 Canada
| | - Richard C Hamelin
- Faculty of Forestry, Geography and Geomatics, Laval University, Quebec City, QC, G1V 0A6 Canada
- Faculty of Forestry, The University of British Columbia, Vancouver, BC, V6T 1Z4 Canada
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Royo C, Ammar K, Villegas D, Soriano JM. Agronomic, Physiological and Genetic Changes Associated With Evolution, Migration and Modern Breeding in Durum Wheat. FRONTIERS IN PLANT SCIENCE 2021; 12:674470. [PMID: 34305973 PMCID: PMC8296143 DOI: 10.3389/fpls.2021.674470] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Accepted: 06/07/2021] [Indexed: 05/04/2023]
Abstract
A panel of 172 Mediterranean durum wheat landraces and 200 modern cultivars was phenotyped during three years for 21 agronomic and physiological traits and genotyped with 46,161 DArTseq markers. Modern cultivars showed greater yield, number of grains per spike (NGS) and harvest index (HI), but similar number of spikes per unit area (NS) and grain weight than the landraces. Modern cultivars had earlier heading but longer heading-anthesis and grain-filling periods than the landraces. They had greater RUE (Radiation Use Efficiency) up to anthesis and lower canopy temperature at anthesis than the landraces, but the opposite was true during the grain-filling period. Landraces produced more biomass at both anthesis and maturity. The 120 genotypes with a membership coefficient q > 0.8 to the five genetic subpopulations (SP) that structured the panel were related with the geographic distribution and evolutionary history of durum wheat. SP1 included landraces from eastern countries, the domestication region of the "Fertile Crescent." SP2 and SP3 consisted of landraces from the north and the south Mediterranean shores, where durum wheat spread during its migration westward. Decreases in NS, grain-filling duration and HI, but increases in early soil coverage, days to heading, biomass at anthesis, grain-filling rate, plant height and peduncle length occurred during this migration. SP4 grouped modern cultivars gathering the CIMMYT/ICARDA genetic background, and SP5 contained modern north-American cultivars. SP4 was agronomically distant from the landraces, but SP5 was genetically and agronomically close to SP1. GWAS identified 2,046 marker-trait associations (MTA) and 144 QTL hotspots integrating 1,927 MTAs. Thirty-nine haplotype blocks (HB) with allelic differences among SPs and associated with 16 agronomic traits were identified within 13 QTL hotspots. Alleles in chromosomes 5A and 7A detected in landraces were associated with decreased yield. The late heading and short grain-filling period of SP2 and SP3 were associated with a hotspot on chromosome 7B. The heavy grains of SP3 were associated with hotspots on chromosomes 2A and 7A. The greater NGS and HI of modern cultivars were associated with allelic variants on chromosome 7A. A hotspot on chromosome 3A was associated with the high NGS, earliness and short stature of SP4.
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Affiliation(s)
- Conxita Royo
- Sustainable Field Crops Programme, Institute for Food and Agricultural Research and Technology (IRTA), Lleida, Spain
- *Correspondence: Conxita Royo ;
| | - Karim Ammar
- International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico
| | - Dolors Villegas
- Sustainable Field Crops Programme, Institute for Food and Agricultural Research and Technology (IRTA), Lleida, Spain
| | - Jose M. Soriano
- Sustainable Field Crops Programme, Institute for Food and Agricultural Research and Technology (IRTA), Lleida, Spain
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Hao C, Jiao C, Hou J, Li T, Liu H, Wang Y, Zheng J, Liu H, Bi Z, Xu F, Zhao J, Ma L, Wang Y, Majeed U, Liu X, Appels R, Maccaferri M, Tuberosa R, Lu H, Zhang X. Resequencing of 145 Landmark Cultivars Reveals Asymmetric Sub-genome Selection and Strong Founder Genotype Effects on Wheat Breeding in China. MOLECULAR PLANT 2020; 13:1733-1751. [PMID: 32896642 DOI: 10.1016/j.molp.2020.09.001] [Citation(s) in RCA: 137] [Impact Index Per Article: 27.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Revised: 08/19/2020] [Accepted: 09/02/2020] [Indexed: 05/18/2023]
Abstract
Controlled pedigrees and the multi-decade timescale of national crop plant breeding programs offer a unique experimental context for examining how selection affects plant genomes. More than 3000 wheat cultivars have been registered, released, and documented since 1949 in China. In this study, a set of 145 elite cultivars selected from historical points of wheat breeding in China were re-sequenced. A total of 43.75 Tb of sequence data were generated with an average read depth of 17.94× for each cultivar, and more than 60.92 million SNPs and 2.54 million InDels were captured, based on the Chinese Spring RefSeq genome v1.0. Seventy years of breeder-driven selection led to dramatic changes in grain yield and related phenotypes, with distinct genomic regions and phenotypes targeted by different breeders across the decades. There are very clear instances illustrating how introduced Italian and other foreign germplasm was integrated into Chinese wheat programs and reshaped the genomic landscape of local modern cultivars. Importantly, the resequencing data also highlighted significant asymmetric breeding selection among the three sub-genomes: this was evident in both the collinear blocks for homeologous chromosomes and among sets of three homeologous genes. Accumulation of more newly assembled genes in newer cultivars implied the potential value of these genes in breeding. Conserved and extended sharing of linkage disequilibrium (LD) blocks was highlighted among pedigree-related cultivars, in which fewer haplotype differences were detected. Fixation or replacement of haplotypes from founder genotypes after generations of breeding was related to their breeding value. Based on the haplotype frequency changes in LD blocks of pedigree-related cultivars, we propose a strategy for evaluating the breeding value of any given line on the basis of the accumulation (pyramiding) of beneficial haplotypes. Collectively, our study demonstrates the influence of "founder genotypes" on the output of breeding efforts over many decades and also suggests that founder genotype perspectives are in fact more dynamic when applied in the context of modern genomics-informed breeding.
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Affiliation(s)
- Chenyang Hao
- Key Laboratory of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture and Rural Affairs/The National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Chengzhi Jiao
- Key Laboratory of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture and Rural Affairs/The National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China; Novogene Bioinformatics Institute, Beijing 100083, China
| | - Jian Hou
- Key Laboratory of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture and Rural Affairs/The National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Tian Li
- Key Laboratory of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture and Rural Affairs/The National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Hongxia Liu
- Key Laboratory of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture and Rural Affairs/The National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Yuquan Wang
- Key Laboratory of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture and Rural Affairs/The National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Jun Zheng
- Key Laboratory of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture and Rural Affairs/The National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Hong Liu
- Key Laboratory of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture and Rural Affairs/The National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Zhihong Bi
- Novogene Bioinformatics Institute, Beijing 100083, China
| | - Fengfeng Xu
- Novogene Bioinformatics Institute, Beijing 100083, China
| | - Jing Zhao
- Key Laboratory of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture and Rural Affairs/The National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Lin Ma
- Key Laboratory of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture and Rural Affairs/The National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Yamei Wang
- Key Laboratory of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture and Rural Affairs/The National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Uzma Majeed
- Key Laboratory of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture and Rural Affairs/The National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Xu Liu
- Key Laboratory of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture and Rural Affairs/The National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Rudi Appels
- AgriBio, Centre for AgriBioscience, Department of Economic Development, Jobs, Transport, and Resources, 5 Ring Road, La Trobe University, Bundoora, VIC 3083, Australia
| | - Marco Maccaferri
- Department of Agricultural and Food Sciences, University of Bologna, Bologna, Italy
| | - Roberto Tuberosa
- Department of Agricultural and Food Sciences, University of Bologna, Bologna, Italy
| | - Hongfeng Lu
- Novogene Bioinformatics Institute, Beijing 100083, China.
| | - Xueyong Zhang
- Key Laboratory of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture and Rural Affairs/The National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China.
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Sehgal D, Mondal S, Crespo-Herrera L, Velu G, Juliana P, Huerta-Espino J, Shrestha S, Poland J, Singh R, Dreisigacker S. Haplotype-Based, Genome-Wide Association Study Reveals Stable Genomic Regions for Grain Yield in CIMMYT Spring Bread Wheat. Front Genet 2020; 11:589490. [PMID: 33335539 PMCID: PMC7737720 DOI: 10.3389/fgene.2020.589490] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2020] [Accepted: 10/21/2020] [Indexed: 01/16/2023] Open
Abstract
We untangled key regions of the genetic architecture of grain yield (GY) in CIMMYT spring bread wheat by conducting a haplotype-based, genome-wide association study (GWAS), together with an investigation of epistatic interactions using seven large sets of elite yield trials (EYTs) consisting of a total of 6,461 advanced breeding lines. These lines were phenotyped under irrigated and stress environments in seven growing seasons (2011-2018) and genotyped with genotyping-by-sequencing markers. Genome-wide 519 haplotype blocks were constructed, using a linkage disequilibrium-based approach covering 14,036 Mb in the wheat genome. Haplotype-based GWAS identified 7, 4, 10, and 15 stable (significant in three or more EYTs) associations in irrigated (I), mild drought (MD), severe drought (SD), and heat stress (HS) testing environments, respectively. Considering all EYTs and the four testing environments together, 30 stable associations were deciphered with seven hotspots identified on chromosomes 1A, 1B, 2B, 4A, 5B, 6B, and 7B, where multiple haplotype blocks were associated with GY. Epistatic interactions contributed significantly to the genetic architecture of GY, explaining variation of 3.5-21.1%, 3.7-14.7%, 3.5-20.6%, and 4.4- 23.1% in I, MD, SD, and HS environments, respectively. Our results revealed the intricate genetic architecture of GY, controlled by both main and epistatic effects. The importance of these results for practical applications in the CIMMYT breeding program is discussed.
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Affiliation(s)
- Deepmala Sehgal
- International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico
| | - Suchismita Mondal
- International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico
| | | | - Govindan Velu
- International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico
| | - Philomin Juliana
- International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico
| | | | | | - Jesse Poland
- Kansas State University, Manhattan, KS, United States
| | - Ravi Singh
- International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico
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Wang J, Fu W, Wang R, Hu D, Cheng H, Zhao J, Jiang Y, Kang Z. WGVD: an integrated web-database for wheat genome variation and selective signatures. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2020; 2020:5979748. [PMID: 33181826 PMCID: PMC7661095 DOI: 10.1093/database/baaa090] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/01/2020] [Revised: 09/10/2020] [Accepted: 09/16/2020] [Indexed: 01/08/2023]
Abstract
Bread wheat is one of the most important crops worldwide. With the release of the complete wheat reference genome and the development of next-generation sequencing technology, a mass of genomic data from bread wheat and its progenitors has been yield and has provided genomic resources for wheat genetics research. To conveniently and effectively access and use these data, we established Wheat Genome Variation Database, an integrated web-database including genomic variations from whole-genome resequencing and exome-capture data for bread wheat and its progenitors, as well as selective signatures during the process of wheat domestication and improvement. In this version, WGVD contains 7 346 814 single nucleotide polymorphisms (SNPs) and 1 044 400 indels focusing on genic regions and upstream or downstream regions. We provide allele frequency distribution patterns of these variations for 5 ploidy wheat groups or 17 worldwide bread wheat groups, the annotation of the variant types and the genotypes of all individuals for 2 versions of bread wheat reference genome (IWGSC RefSeq v1.0 and IWGSC RefSeq v2.0). Selective footprints for Aegilops tauschii, wild emmer, domesticated emmer, bread wheat landrace and bread wheat variety are evaluated with two statistical tests (FST and Pi) based on SNPs from whole-genome resequencing data. In addition, we provide the Genome Browser to visualize the genomic variations, the selective footprints, the genotype patterns and the read coverage depth, and the alignment tool Blast to search the homologous regions between sequences. All of these features of WGVD will promote wheat functional studies and wheat breeding. Database URL http://animal.nwsuaf.edu.cn/code/index.php/Wheat
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Affiliation(s)
- Jierong Wang
- State Key Laboratory of Crop Stress Biology for Arid Areas and College of Plant Protection, Northwest A&F University, 3 Taicheng Rd, Yangling 712100, Shaanxi, China
| | - Weiwei Fu
- College of Animal Science and Technology, Northwest A&F University, 22 Xinong Rd, Yangling, 712100, Shaanxi, China
| | - Rui Wang
- College of Animal Science and Technology, Northwest A&F University, 22 Xinong Rd, Yangling, 712100, Shaanxi, China
| | - Dexiang Hu
- College of Animal Science and Technology, Northwest A&F University, 22 Xinong Rd, Yangling, 712100, Shaanxi, China
| | - Hong Cheng
- College of Animal Science and Technology, Northwest A&F University, 22 Xinong Rd, Yangling, 712100, Shaanxi, China
| | - Jing Zhao
- State Key Laboratory of Crop Stress Biology for Arid Areas and College of Plant Protection, Northwest A&F University, 3 Taicheng Rd, Yangling 712100, Shaanxi, China
| | - Yu Jiang
- College of Animal Science and Technology, Northwest A&F University, 22 Xinong Rd, Yangling, 712100, Shaanxi, China
| | - Zhensheng Kang
- State Key Laboratory of Crop Stress Biology for Arid Areas and College of Plant Protection, Northwest A&F University, 3 Taicheng Rd, Yangling 712100, Shaanxi, China
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Nikitina E, Kuznetsova V, Kroupin P, Karlov GI, Divashuk MG. Development of Specific Thinopyrum Cytogenetic Markers for Wheat-Wheatgrass Hybrids Using Sequencing and qPCR Data. Int J Mol Sci 2020; 21:E4495. [PMID: 32599865 PMCID: PMC7349979 DOI: 10.3390/ijms21124495] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2020] [Revised: 06/15/2020] [Accepted: 06/21/2020] [Indexed: 01/19/2023] Open
Abstract
The cytogenetic study of wide hybrids of wheat has both practical and fundamental values. Partial wheat-wheatgrass hybrids (WWGHs) are interesting as a breeding bridge to confer valuable genes to wheat genome, as well as a model object that contains related genomes of Triticeae. The development of cytogenetic markers is a process that requires long and laborious fluorescence in situ hybridization (FISH) testing of various probes before a suitable probe is found. In this study, we aimed to find an approach that allows to facilitate this process. Based on the data sequencing of Thinopyrum ponticum, we selected six tandem repeat (TR) clusters using RepeatExplorer2 pipeline and designed primers for each of them. We estimated the found TRs' abundance in the genomes of Triticum aestivum, Thinopyrum ponticum, Thinopyrum intermedium and four different WWGH accessions using real-time qPCR, and localized them on the chromosomes of the studied WWGHs using fluorescence in situ hybridization. As a result, we obtained three tandem repeat cytogenetic markers that specifically labeled wheatgrass chromosomes in the presence of bread wheat chromosomes. Moreover, we designed and tested primers for these repeats, and demonstrated that they can be used as qPCR markers for quick and cheap monitoring of the presence of certain chromosomes of wheatgrass in breeding programs.
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Affiliation(s)
- Ekaterina Nikitina
- Laboratory of Applied Genomics and Crop Breeding, All-Russia Research Institute of Agricultural Biotechnology, Timiryazevskaya str. 42, Moscow 127550, Russia; (E.N.); (V.K.); (P.K.); (G.I.K.)
| | - Victoria Kuznetsova
- Laboratory of Applied Genomics and Crop Breeding, All-Russia Research Institute of Agricultural Biotechnology, Timiryazevskaya str. 42, Moscow 127550, Russia; (E.N.); (V.K.); (P.K.); (G.I.K.)
| | - Pavel Kroupin
- Laboratory of Applied Genomics and Crop Breeding, All-Russia Research Institute of Agricultural Biotechnology, Timiryazevskaya str. 42, Moscow 127550, Russia; (E.N.); (V.K.); (P.K.); (G.I.K.)
| | - Gennady I. Karlov
- Laboratory of Applied Genomics and Crop Breeding, All-Russia Research Institute of Agricultural Biotechnology, Timiryazevskaya str. 42, Moscow 127550, Russia; (E.N.); (V.K.); (P.K.); (G.I.K.)
| | - Mikhail G. Divashuk
- Laboratory of Applied Genomics and Crop Breeding, All-Russia Research Institute of Agricultural Biotechnology, Timiryazevskaya str. 42, Moscow 127550, Russia; (E.N.); (V.K.); (P.K.); (G.I.K.)
- Kurchatov Genomics Center—ARRIAB, All-Russia Research Institute of Agricultural Biotechnology, Timiryazevskaya str. 42, Moscow 127550, Russia
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Rasheed A, Takumi S, Hassan MA, Imtiaz M, Ali M, Morgunov AI, Mahmood T, He Z. Appraisal of wheat genomics for gene discovery and breeding applications: a special emphasis on advances in Asia. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2020; 133:1503-1520. [PMID: 31897516 DOI: 10.1007/s00122-019-03523-w] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/31/2019] [Accepted: 12/23/2019] [Indexed: 06/10/2023]
Abstract
We discussed the most recent efforts in wheat functional genomics to discover new genes and their deployment in breeding with special emphasis on advances in Asian countries. Wheat research community is making significant progress to bridge genotype-to-phenotype gap and then applying this knowledge in genetic improvement. The advances in genomics and phenomics have intrigued wheat researchers in Asia to make best use of this knowledge in gene and trait discovery. These advancements include, but not limited to, map-based gene cloning, translational genomics, gene mapping, association genetics, gene editing and genomic selection. We reviewed more than 57 homeologous genes discovered underpinning important traits and multiple strategies used for their discovery. Further, the complementary advancements in wheat phenomics and analytical approaches to understand the genetics of wheat adaptability, resilience to climate extremes and resistance to pest and diseases were discussed. The challenge to build a gold standard reference genome sequence of bread wheat is now achieved and several de novo reference sequences from the cultivars representing different gene pools will be available soon. New pan-genome sequencing resources of wheat will strengthen the foundation required for accelerated gene discovery and provide more opportunities to practice the knowledge-based breeding.
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Affiliation(s)
- Awais Rasheed
- Institute of Crop Science, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China.
- International Maize and Wheat Improvement Center (CIMMYT), CAAS, 12 Zhongguancun South Street, Beijing, 100081, China.
- Department of Plant Sciences, Quaid-i-Azam University, Islamabad, 45320, Pakistan.
| | - Shigeo Takumi
- Graduate School of Agricultural Science, Kobe University, Rokkodai 1-1, Nada, Kobe, 657-8501, Japan
| | - Muhammad Adeel Hassan
- Institute of Crop Science, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China
| | - Muhammad Imtiaz
- International Maize and Wheat Improvement Center (CIMMYT) Pakistan office, c/o National Agriculture Research Center (NARC), Islamabad, Pakistan
| | - Mohsin Ali
- Institute of Crop Science, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China
| | - Alex I Morgunov
- International Maize and Wheat Improvement Center (CIMMYT), Yenimahalle, Ankara, 06170, Turkey
| | - Tariq Mahmood
- Department of Plant Sciences, Quaid-i-Azam University, Islamabad, 45320, Pakistan
| | - Zhonghu He
- Institute of Crop Science, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China
- International Maize and Wheat Improvement Center (CIMMYT), CAAS, 12 Zhongguancun South Street, Beijing, 100081, China
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