1
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Burridge AJ, Winfield M, Przewieslik‐Allen A, Edwards KJ, Siddique I, Barral‐Arca R, Griffiths S, Cheng S, Huang Z, Feng C, Dreisigacker S, Bentley AR, Brown‐Guedira G, Barker GL. Development of a next generation SNP genotyping array for wheat. PLANT BIOTECHNOLOGY JOURNAL 2024; 22:2235-2247. [PMID: 38520342 PMCID: PMC11258986 DOI: 10.1111/pbi.14341] [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: 12/07/2023] [Revised: 03/05/2024] [Accepted: 03/06/2024] [Indexed: 03/25/2024]
Abstract
High-throughput genotyping arrays have provided a cost-effective, reliable and interoperable system for genotyping hexaploid wheat and its relatives. Existing, highly cited arrays including our 35K Wheat Breeder's array and the Illumina 90K array were designed based on a limited amount of varietal sequence diversity and with imperfect knowledge of SNP positions. Recent progress in wheat sequencing has given us access to a vast pool of SNP diversity, whilst technological improvements have allowed us to fit significantly more probes onto a 384-well format Axiom array than previously possible. Here we describe a novel Axiom genotyping array, the 'Triticum aestivum Next Generation' array (TaNG), largely derived from whole genome skim sequencing of 204 elite wheat lines and 111 wheat landraces taken from the Watkins 'Core Collection'. We used a novel haplotype optimization approach to select SNPs with the highest combined varietal discrimination and a design iteration step to test and replace SNPs which failed to convert to reliable markers. The final design with 43 372 SNPs contains a combination of haplotype-optimized novel SNPs and legacy cross-platform markers. We show that this design has an improved distribution of SNPs compared to previous arrays and can be used to generate genetic maps with a significantly higher number of distinct bins than our previous array. We also demonstrate the improved performance of TaNGv1.1 for Genome-wide association studies (GWAS) and its utility for Copy Number Variation (CNV) analysis. The array is commercially available with supporting marker annotations and initial genotyping results freely available.
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Affiliation(s)
| | - Mark Winfield
- School of Biological SciencesUniversity of BristolBristolUK
| | | | | | - Imteaz Siddique
- Thermo Fisher Scientific3450 Central ExpresswaySanta ClaraCAUSA
| | | | | | - Shifeng Cheng
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at ShenzhenChinese Academy of Agricultural SciencesShenzhenChina
| | - Zejian Huang
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at ShenzhenChinese Academy of Agricultural SciencesShenzhenChina
| | - Cong Feng
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at ShenzhenChinese Academy of Agricultural SciencesShenzhenChina
| | | | | | - Gina Brown‐Guedira
- Plant Science Research UnitUSDA Agricultural Research ServiceRaleighNCUSA
| | - Gary L. Barker
- School of Biological SciencesUniversity of BristolBristolUK
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2
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Chen J, Zhang Y, Wei J, Hu X, Yin H, Liu W, Li D, Tian W, Hao Y, He Z, Fernie AR, Chen W. Beyond pathways: Accelerated flavonoids candidate identification and novel exploration of enzymatic properties using combined mapping populations of wheat. PLANT BIOTECHNOLOGY JOURNAL 2024; 22:2033-2050. [PMID: 38408119 PMCID: PMC11182594 DOI: 10.1111/pbi.14323] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Revised: 02/06/2024] [Accepted: 02/12/2024] [Indexed: 02/28/2024]
Abstract
Although forward-genetics-metabolomics methods such as mGWAS and mQTL have proven effective in providing myriad loci affecting metabolite contents, they are somehow constrained by their respective constitutional flaws such as the hidden population structure for GWAS and insufficient recombinant rate for QTL. Here, the combination of mGWAS and mQTL was performed, conveying an improved statistical power to investigate the flavonoid pathways in common wheat. A total of 941 and 289 loci were, respectively, generated from mGWAS and mQTL, within which 13 of them were co-mapped using both approaches. Subsequently, the mGWAS or mQTL outputs alone and their combination were, respectively, utilized to delineate the metabolic routes. Using this approach, we identified two MYB transcription factor encoding genes and five structural genes, and the flavonoid pathway in wheat was accordingly updated. Moreover, we have discovered some rare-activity-exhibiting flavonoid glycosyl- and methyl-transferases, which may possess unique biological significance, and harnessing these novel catalytic capabilities provides potentially new breeding directions. Collectively, we propose our survey illustrates that the forward-genetics-metabolomics approaches including multiple populations with high density markers could be more frequently applied for delineating metabolic pathways in common wheat, which will ultimately contribute to metabolomics-assisted wheat crop improvement.
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Affiliation(s)
- Jie Chen
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan)Huazhong Agricultural UniversityWuhanChina
- Hubei Hongshan LaboratoryWuhanChina
- Yazhouwan National LaboratorySanyaChina
| | - Yueqi Zhang
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan)Huazhong Agricultural UniversityWuhanChina
- Hubei Hongshan LaboratoryWuhanChina
| | - Jiaqi Wei
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan)Huazhong Agricultural UniversityWuhanChina
- Hubei Hongshan LaboratoryWuhanChina
- Wuhan Academy of Agricultural SciencesWuhanChina
| | - Xin Hu
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan)Huazhong Agricultural UniversityWuhanChina
- Hubei Hongshan LaboratoryWuhanChina
| | - Huanran Yin
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan)Huazhong Agricultural UniversityWuhanChina
- Hubei Hongshan LaboratoryWuhanChina
| | - Wei Liu
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan)Huazhong Agricultural UniversityWuhanChina
- Hubei Hongshan LaboratoryWuhanChina
| | - Dongqin Li
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan)Huazhong Agricultural UniversityWuhanChina
| | - Wenfei Tian
- National Wheat Improvement Center, Institute of Crop SciencesChinese Academy of Agricultural SciencesBeijingChina
| | - Yuanfeng Hao
- National Wheat Improvement Center, Institute of Crop SciencesChinese Academy of Agricultural SciencesBeijingChina
| | - Zhonghu He
- National Wheat Improvement Center, Institute of Crop SciencesChinese Academy of Agricultural SciencesBeijingChina
| | | | - Wei Chen
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan)Huazhong Agricultural UniversityWuhanChina
- Hubei Hongshan LaboratoryWuhanChina
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3
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Cheng S, Feng C, Wingen LU, Cheng H, Riche AB, Jiang M, Leverington-Waite M, Huang Z, Collier S, Orford S, Wang X, Awal R, Barker G, O'Hara T, Lister C, Siluveru A, Quiroz-Chávez J, Ramírez-González RH, Bryant R, Berry S, Bansal U, Bariana HS, Bennett MJ, Bicego B, Bilham L, Brown JKM, Burridge A, Burt C, Buurman M, Castle M, Chartrain L, Chen B, Denbel W, Elkot AF, Fenwick P, Feuerhelm D, Foulkes J, Gaju O, Gauley A, Gaurav K, Hafeez AN, Han R, Horler R, Hou J, Iqbal MS, Kerton M, Kondic-Spica A, Kowalski A, Lage J, Li X, Liu H, Liu S, Lovegrove A, Ma L, Mumford C, Parmar S, Philp C, Playford D, Przewieslik-Allen AM, Sarfraz Z, Schafer D, Shewry PR, Shi Y, Slafer GA, Song B, Song B, Steele D, Steuernagel B, Tailby P, Tyrrell S, Waheed A, Wamalwa MN, Wang X, Wei Y, Winfield M, Wu S, Wu Y, Wulff BBH, Xian W, Xu Y, Xu Y, Yuan Q, Zhang X, Edwards KJ, Dixon L, Nicholson P, Chayut N, Hawkesford MJ, Uauy C, Sanders D, Huang S, Griffiths S. Harnessing landrace diversity empowers wheat breeding. Nature 2024:10.1038/s41586-024-07682-9. [PMID: 38885696 DOI: 10.1038/s41586-024-07682-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Accepted: 06/06/2024] [Indexed: 06/20/2024]
Abstract
Harnessing genetic diversity in major staple crops through the development of new breeding capabilities is essential to ensure food security1. Here we examined the genetic and phenotypic diversity of the A. E. Watkins landrace collection2 of bread wheat (Triticum aestivum), a major global cereal, by whole-genome re-sequencing of 827 Watkins landraces and 208 modern cultivars and in-depth field evaluation spanning a decade. We found that modern cultivars are derived from two of the seven ancestral groups of wheat and maintain very long-range haplotype integrity. The remaining five groups represent untapped genetic sources, providing access to landrace-specific alleles and haplotypes for breeding. Linkage disequilibrium-based haplotypes and association genetics analyses link Watkins genomes to the thousands of identified high-resolution quantitative trait loci and significant marker-trait associations. Using these structured germplasm, genotyping and informatics resources, we revealed many Watkins-unique beneficial haplotypes that can confer superior traits in modern wheat. Furthermore, we assessed the phenotypic effects of 44,338 Watkins-unique haplotypes, introgressed from 143 prioritized quantitative trait loci in the context of modern cultivars, bridging the gap between landrace diversity and current breeding. This study establishes a framework for systematically utilizing genetic diversity in crop improvement to achieve sustainable food security.
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Affiliation(s)
- Shifeng Cheng
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China.
| | - Cong Feng
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | | | - Hong Cheng
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | | | - Mei Jiang
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | | | - Zejian Huang
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | | | | | - Xiaoming Wang
- John Innes Centre, Norwich, UK
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, China
| | | | - Gary Barker
- Functional Genomics, School of Biological Sciences, University of Bristol, Bristol, UK
| | | | | | | | | | | | | | | | - Urmil Bansal
- School of Life and Environmental Sciences, Faculty of Science, The University of Sydney Plant Breeding Institute, Cobbitty, New South Wales, Australia
| | - Harbans S Bariana
- School of Life and Environmental Sciences, Faculty of Science, The University of Sydney Plant Breeding Institute, Cobbitty, New South Wales, Australia
- Western Sydney University, Richmond, New South Wales, Australia
| | - Malcolm J Bennett
- School of Biosciences, University of Nottingham, Sutton Bonington, UK
| | - Breno Bicego
- Department of Agricultural and Forest Sciences and Engineering, University of Lleida-AGROTECNIO-CERCA Center, Lleida, Spain
| | | | | | - Amanda Burridge
- Functional Genomics, School of Biological Sciences, University of Bristol, Bristol, UK
| | | | | | | | | | - Baizhi Chen
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Worku Denbel
- Debre Zeit Agricultural Research Center, Ethiopian Institute of Agricultural Research, Debre Zeit, Ethiopia
| | - Ahmed F Elkot
- Wheat Research Department, Field Crops Research Institute, Agricultural Research Center, Giza, Egypt
| | | | | | - John Foulkes
- School of Biosciences, University of Nottingham, Sutton Bonington, UK
| | - Oorbessy Gaju
- School of Biosciences, University of Nottingham, Sutton Bonington, UK
| | - Adam Gauley
- School of Biology, University of Leeds, Leeds, UK
- Agri-Food and Biosciences Institute, Belfast, UK
| | | | | | - Ruirui Han
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- Qingdao Agricultural University, Qingdao, China
| | | | - Junliang Hou
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Muhammad S Iqbal
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | | | - Ankica Kondic-Spica
- Institute of Field and Vegetable Crops, National Institute of the Republic of Serbia, Novi Sad, Republic of Serbia
| | | | | | - Xiaolong Li
- Key Laboratory of Quality and Safety Control for Subtropical Fruit and Vegetable, Ministry of Agriculture and Rural Affairs, College of Horticulture Science, Zhejiang A&F University, Hangzhou, China
| | - Hongbing Liu
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Shiyan Liu
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | | | - Lingling Ma
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | | | | | | | | | | | - Zareen Sarfraz
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | | | | | - Yan Shi
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Gustavo A Slafer
- Department of Agricultural and Forest Sciences and Engineering, University of Lleida-AGROTECNIO-CERCA Center, Lleida, Spain
- ICREA, Catalonian Institution for Research and Advanced Studies, Barcelona, Spain
| | - Baoxing Song
- National Key Laboratory of Wheat Improvement, Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agriculture Sciences in Weifang, Weifang, China
| | - Bo Song
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | | | | | | | | | - Abdul Waheed
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | | | - Xingwei Wang
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Yanping Wei
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Mark Winfield
- Functional Genomics, School of Biological Sciences, University of Bristol, Bristol, UK
| | - Shishi Wu
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Yubing Wu
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- Huazhong Agricultural University, Wuhan, China
| | - Brande B H Wulff
- John Innes Centre, Norwich, UK
- Center for Desert Agriculture, Plant Science Program, Biological and Environmental Science and Engineering Division (BESE), King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia
| | - Wenfei Xian
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- Department of Molecular Biology, Max Planck Institute for Biology Tübingen, Tübingen, Germany
| | - Yawen Xu
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- Huazhong Agricultural University, Wuhan, China
| | - Yunfeng Xu
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Quan Yuan
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Xin Zhang
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- Huazhong Agricultural University, Wuhan, China
| | - Keith J Edwards
- Functional Genomics, School of Biological Sciences, University of Bristol, Bristol, UK
| | - Laura Dixon
- School of Biology, University of Leeds, Leeds, UK
| | | | | | | | | | | | - Sanwen Huang
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- State Key Laboratory of Tropical Crop Breeding, Chinese Academy of Tropical Agricultural Sciences, Haikou, China
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Hong MJ, Ko CS, Kim DY. Genome-Wide Association Study to Identify Marker-Trait Associations for Seed Color in Colored Wheat ( Triticum aestivum L.). Int J Mol Sci 2024; 25:3600. [PMID: 38612412 PMCID: PMC11011601 DOI: 10.3390/ijms25073600] [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: 02/29/2024] [Revised: 03/18/2024] [Accepted: 03/19/2024] [Indexed: 04/14/2024] Open
Abstract
This study conducted phenotypic evaluations on a wheat F3 population derived from 155 F2 plants. Traits related to seed color, including chlorophyll a, chlorophyll b, carotenoid, anthocyanin, L*, a*, and b*, were assessed, revealing highly significant correlations among various traits. Genotyping using 81,587 SNP markers resulted in 3969 high-quality markers, revealing a genome-wide distribution with varying densities across chromosomes. A genome-wide association study using fixed and random model circulating probability unification (FarmCPU) and Bayesian-information and linkage-disequilibrium iteratively nested keyway (BLINK) identified 11 significant marker-trait associations (MTAs) associated with L*, a*, and b*, and chromosomal distribution patterns revealed predominant locations on chromosomes 2A, 2B, and 4B. A comprehensive annotation uncovered 69 genes within the genomic vicinity of each MTA, providing potential functional insights. Gene expression analysis during seed development identified greater than 2-fold increases or decreases in expression in colored wheat for 16 of 69 genes. Among these, eight genes, including transcription factors and genes related to flavonoid and ubiquitination pathways, exhibited distinct expression patterns during seed development, providing further approaches for exploring seed coloration. This comprehensive exploration expands our understanding of the genetic basis of seed color and paves the way for informed discussions on the molecular intricacies contributing to this phenotypic trait.
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Affiliation(s)
- Min Jeong Hong
- Advanced Radiation Technology Institute, Korea Atomic Energy Research Institute, 29 Geumgu, Jeongeup 56212, Republic of Korea; (M.J.H.); (C.S.K.)
| | - Chan Seop Ko
- Advanced Radiation Technology Institute, Korea Atomic Energy Research Institute, 29 Geumgu, Jeongeup 56212, Republic of Korea; (M.J.H.); (C.S.K.)
| | - Dae Yeon Kim
- Department of Plant Resources, College of Industrial Sciences, Kongju National University, 54 Daehak-ro, Yesan-eup 32439, Republic of Korea
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5
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Deng P, Du X, Wang Y, Yang X, Cheng X, Huang C, Li T, Li T, Chen C, Zhao J, Wang C, Liu X, Tian Z, Ji W. GenoBaits®WheatplusEE: a targeted capture sequencing panel for quick and accurate identification of wheat-Thinopyrum derivatives. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2024; 137:36. [PMID: 38291310 DOI: 10.1007/s00122-023-04538-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Accepted: 12/27/2023] [Indexed: 02/01/2024]
Abstract
KEY MESSAGE A total of 90,000 capture probes derived from wheat and Thinopyrum elongatum were integrated into one chip, which served as an economical genotype for explorating Thinopyrumspecies and their derivatives. Thinopyrum species play a crucial role as a source of new genetic variations for enhancing wheat traits, including resistance to both abiotic and biotic factors. Accurate identification of exogenous chromosome(s) or chromosome segments or genes is essential following the introduction of alien genetic material into wheat, but this task remains challenging. This study aimed to develop a high-resolution wheat-Thinopyrum elongatum array, named GenoBaits®WheatplusEE, to trace alien genetic information by genotyping using a target sequencing system. This GenoBaits®WheatplusEE array included 90,000 capture probes derived from two species and integrated into one chip, with 10,000 and 80,000 originating from wheat and Th. elongatum, respectively. The capture probes were strategically positioned in genes and evenly distributed across the genome, facilitating the development of a roadmap for identifying each alien gene. The array was applied to the high-throughput identification of the alien chromosomes or segments in Thinopyrum and distantly related species and their derivatives. Our results demonstrated that the GenoBaits®WheatplusEE array could be used for direct identification of the breakpoint of alien segments, determine copy number of alien chromosomes, and reveal variations in wheat chromosomes by a single round of target sequencing of the sample. Additionally, we could efficiently and cost-effectively genotype, supporting the exploration of subgenome composition, phylogenetic relationships, and polymorphisms in essential genes (e.g., Fhb7 gene) among Thinopyrum species and their derivatives. We hope that GenoBaits®WheatplusEE will become a widely adopted tool for exporting wild germplasm for wheat improvement in the future.
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Affiliation(s)
- Pingchuan Deng
- State Key Laboratory of Crop Stress Biology in Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100, Shaanxi, China
| | - Xin Du
- State Key Laboratory of Crop Stress Biology in Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100, Shaanxi, China
| | - Yanzhen Wang
- State Key Laboratory of Crop Stress Biology in Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100, Shaanxi, China
- Center for Agricultural Genetic Resources Research, Shanxi Agricultural University, Taiyuan, 030031, Shanxi, China
| | - Xiaoying Yang
- State Key Laboratory of Crop Stress Biology in Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100, Shaanxi, China
| | - Xiaofang Cheng
- State Key Laboratory of Crop Stress Biology in Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100, Shaanxi, China
| | - Chenxi Huang
- State Key Laboratory of Crop Stress Biology in Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100, Shaanxi, China
| | - Tingting Li
- College of Bioengineering, Yangling Vocational Technical College, Yangling, 712100, Shaanxi, China
| | - Tingdong Li
- State Key Laboratory of Crop Stress Biology in Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100, Shaanxi, China
| | - Chunhuan Chen
- State Key Laboratory of Crop Stress Biology in Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100, Shaanxi, China
| | - Jixin Zhao
- State Key Laboratory of Crop Stress Biology in Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100, Shaanxi, China
| | - Changyou Wang
- State Key Laboratory of Crop Stress Biology in Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100, Shaanxi, China
| | - Xinlun Liu
- State Key Laboratory of Crop Stress Biology in Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100, Shaanxi, China
| | - Zengrong Tian
- State Key Laboratory of Crop Stress Biology in Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100, Shaanxi, China
| | - Wanquan Ji
- State Key Laboratory of Crop Stress Biology in Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100, Shaanxi, China.
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6
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Boehm J, Cai X. Enrichment and Diversification of the Wheat Genome via Alien Introgression. PLANTS (BASEL, SWITZERLAND) 2024; 13:339. [PMID: 38337872 PMCID: PMC10857235 DOI: 10.3390/plants13030339] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/20/2023] [Revised: 01/08/2024] [Accepted: 01/19/2024] [Indexed: 02/12/2024]
Abstract
Wheat, including durum and common wheat, respectively, is an allopolyploid with two or three homoeologous subgenomes originating from diploid wild ancestral species. The wheat genome's polyploid origin consisting of just three diploid ancestors has constrained its genetic variation, which has bottlenecked improvement. However, wheat has a large number of relatives, including cultivated crop species (e.g., barley and rye), wild grass species, and ancestral species. Moreover, each ancestor and relative has many other related subspecies that have evolved to inhabit specific geographic areas. Cumulatively, they represent an invaluable source of genetic diversity and variation available to enrich and diversify the wheat genome. The ancestral species share one or more homologous genomes with wheat, which can be utilized in breeding efforts through typical meiotic homologous recombination. Additionally, genome introgressions of distant relatives can be moved into wheat using chromosome engineering-based approaches that feature induced meiotic homoeologous recombination. Recent advances in genomics have dramatically improved the efficacy and throughput of chromosome engineering for alien introgressions, which has served to boost the genetic potential of the wheat genome in breeding efforts. Here, we report research strategies and progress made using alien introgressions toward the enrichment and diversification of the wheat genome in the genomics era.
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Affiliation(s)
- Jeffrey Boehm
- USDA-ARS, Wheat, Sorghum & Forage Research Unit, Lincoln, NE 68583, USA;
- Department of Agronomy and Horticulture, University of Nebraska, Lincoln, NE 68583, USA
| | - Xiwen Cai
- USDA-ARS, Wheat, Sorghum & Forage Research Unit, Lincoln, NE 68583, USA;
- Department of Agronomy and Horticulture, University of Nebraska, Lincoln, NE 68583, USA
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7
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Yang J, Wang J. Genome-Wide Association Study of Preharvest Sprouting in Wheat. Methods Mol Biol 2024; 2830:121-129. [PMID: 38977573 DOI: 10.1007/978-1-0716-3965-8_11] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/10/2024]
Abstract
Genome-wide association study (GWAS) is widely used to characterize genes or quantitative trait loci (QTLs) associated with preharvest sprouting and seed dormancy. GWAS can identify both previously discovered and novel QTLs across diverse genetic panels. The high-throughput SNP arrays or next-generation sequencing technologies have facilitated the identification of numerous genetic markers, thereby significantly enhancing the resolution of GWAS. Although various methods have been developed, the fundamental principles underlying these techniques remain constant. Here, we provide a basic technological flow to perform seed dormancy assay, followed by GWAS using population structure control, and compared it with previous identified QTLs and genes.
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Affiliation(s)
- Jian Yang
- Institute of Wheat, Henan Academy of Agricultural Sciences, Zhengzhou, China
| | - Jirui Wang
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, China
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Xu YF, Ma FF, Zhang JP, Liu H, Li LH, An DG. Unraveling the genetic basis of grain number-related traits in a wheat-Agropyron cristatum introgressed line through high-resolution linkage mapping. BMC PLANT BIOLOGY 2023; 23:563. [PMID: 37964231 PMCID: PMC10647127 DOI: 10.1186/s12870-023-04547-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Accepted: 10/19/2023] [Indexed: 11/16/2023]
Abstract
BACKGROUND Grain number per spike (GNS) is a pivotal determinant of grain yield in wheat. Pubing 3228 (PB3228), a wheat-Agropyron cristatum germplasm, exhibits a notably higher GNS. RESULTS In this study, we developed a recombinant inbred line (RIL) population derived from PB3228/Gao8901 (PG-RIL) and constructed a high-density genetic map comprising 101,136 loci, spanning 4357.3 cM using the Wheat 660 K SNP array. The genetic map demonstrated high collinearity with the wheat assembly IWGSC RefSeq v1.0. Traits related to grain number and spikelet number per spike were evaluated in seven environments for quantitative trait locus (QTL) analysis. Five environmentally stable QTLs were detected in at least three environments. Among these, two major QTLs, QGns-4A.2 and QGns-1A.1, associated with GNS, exhibited positive alleles contributed by PB3228. Further, the conditional QTL analysis revealed a predominant contribution of PB3228 to the GNS QTLs, with both grain number per spikelet (GNSL) and spikelet number per spike (SNS) contributing to the overall GNS trait. Four kompetitive allele-specific PCR (KASP) markers that linked to QGns-4A.2 and QGns-1A.1 were developed and found to be effective in verifying the QTL effect within a diversity panel. Compared to previous studies, QGns-4A.2 exhibited stability across different trials, while QGns-1A.1 represents a novel QTL. The results from unconditional and conditional QTL analyses are valuable for dissecting the genetic contribution of the component traits to GNS at the individual QTL level and for understanding the genetic basis of the superior grain number character in PB3228. The KASP markers can be utilized in marker-assisted selection for enhancing GNS. CONCLUSIONS Five environmentally stable QTLs related to grain number and spikelet number per spike were identified. PB3228 contributed to the majority of the QTLs associated with GNS.
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Affiliation(s)
- Yun-Feng Xu
- Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang, 050021, China
| | - Fei-Fei Ma
- Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang, 050021, China
| | - Jin-Peng Zhang
- The National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Hong Liu
- Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang, 050021, China
| | - Li-Hui Li
- The National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, 100081, China.
| | - Diao-Guo An
- Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang, 050021, China.
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Rabieyan E, Darvishzadeh R, Mohammadi R, Gul A, Rasheed A, Akhar FK, Abdi H, Alipour H. Genetic diversity, linkage disequilibrium, and population structure of tetraploid wheat landraces originating from Europe and Asia. BMC Genomics 2023; 24:682. [PMID: 37964224 PMCID: PMC10644499 DOI: 10.1186/s12864-023-09768-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2023] [Accepted: 10/26/2023] [Indexed: 11/16/2023] Open
Abstract
BACKGROUND Durum wheat is one of the most important crops, especially in the Mediterranean region. Insight into the genetic diversity of germplasm can improve the breeding program management in various traits. This study was done using single nucleotide polymorphisms (SNP) markers to characterize the genetic distinctiveness and differentiation of tetraploid wheat landraces collected from nine European and Asian countries. A sum of 23,334 polymorphic SNPs was detected in 126 tetraploid wheat landraces in relation to the reference genome. RESULTS The number of identified SNPs was 11,613 and 11,721 in A and B genomes, respectively. The highest and lowest diversity was on 6B and 6 A chromosomes, respectively. Structure analysis classified the landraces into two distinct subpopulations (K = 2). Evaluating the principal coordinate analysis (PCoA) and weighted pair-group method using arithmetic averages (WPGMA) clustering results demonstrated that landraces (99.2%) are categorized into one of the two chief subpopulations. Therefore, the grouping pattern did not clearly show the presence of a clear pattern of relationships between genetic diversity and their geographical derivation. Part of this result could be due to the historical exchange between different germplasms. Although the result did not separate landraces based on their region of origin, the landraces collected from Iran were classified into the same group and cluster. Analysis of molecular variance (AMOVA) also confirmed the results of population structure. Finally, Durum wheat landraces in some countries, including Turkey, Russia, Ukraine, and Afghanistan, were highly diverse, while others, including Iran and China, were low-diversity. CONCLUSION The recent study concluded that the 126 tetraploid wheat genotypes and their GBS-SNP markers are very appropriate for quantitative trait loci (QTLs) mapping and genome-wide association studies (GWAS). The core collection comprises two distinct subpopulations. Subpopulation II genotypes are the most diverse genotypes, and if they possess desired traits, they may be used in future breeding programs. The degree of diversity in the landraces of countries can provide the ground for the improvement of new cultivars with international cooperation. linkage disequilibrium (LD) hotspot distribution across the genome was investigated, which provides useful information about the genomic regions that contain intriguing genes.
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Affiliation(s)
- Ehsan Rabieyan
- Department of Agronomy and Plant Breeding, University of Tehran, Karaj, Iran
| | - Reza Darvishzadeh
- Department of Plant Production and Genetics, Faculty of Agriculture, Urmia University, Urmia, Iran
| | - Reza Mohammadi
- Dryland Agricultural Research Institute (DARI), AREEO, Sararood branch, Iran
| | - Alvina Gul
- Atta-ur-Rahman School of Applied Biosciences, National University of Sciences and Technology, Islamabad, Pakistan
| | - Awais Rasheed
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China
- International Maize and Wheat Improvement Center (CIMMYT), c/o CAAS, Beijing, 100081, China
- Department of Plant Sciences, Quaid-I-Azam University, Islamabad, 45320, Pakistan
| | - Fatemeh Keykha Akhar
- Department of Plant Biotechnology, College of Agriculture, Jahrom University, Jahrom, Iran
| | - Hossein Abdi
- Department of Plant Production and Genetics, Faculty of Agriculture, Urmia University, Urmia, Iran
| | - Hadi Alipour
- Department of Plant Production and Genetics, Faculty of Agriculture, Urmia University, Urmia, Iran.
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Luo X, Yang Y, Lin X, Xiao J. Deciphering spike architecture formation towards yield improvement in wheat. J Genet Genomics 2023; 50:835-845. [PMID: 36907353 DOI: 10.1016/j.jgg.2023.02.015] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Revised: 02/28/2023] [Accepted: 02/28/2023] [Indexed: 03/12/2023]
Abstract
Wheat is the most widely grown crop globally, providing 20% of the daily consumed calories and protein content around the world. With the growing global population and frequent occurrence of extreme weather caused by climate change, ensuring adequate wheat production is essential for food security. The architecture of the inflorescence plays a crucial role in determining the grain number and size, which is a key trait for improving yield. Recent advances in wheat genomics and gene cloning techniques have improved our understanding of wheat spike development and its applications in breeding practices. Here, we summarize the genetic regulation network governing wheat spike formation, the strategies used for identifying and studying the key factors affecting spike architecture, and the progress made in breeding applications. Additionally, we highlight future directions that will aid in the regulatory mechanistic study of wheat spike determination and targeted breeding for grain yield improvement.
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Affiliation(s)
- Xumei Luo
- Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yiman Yang
- Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China; Nanjing Agricultural University, Nanjing, Jiangsu 210095, China
| | - Xuelei Lin
- Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China.
| | - Jun Xiao
- Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China; CAS-JIC Centre of Excellence for Plant and Microbial Science (CEPAMS), Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China.
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11
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Xu X, Sun D, Ni Z, Zou X, Xu X, Sun M, Cao Q, Tong J, Ding F, Zhang Y, Wang F, Dong Y, Zhang L, Wang J, Xia X, He Z, Hao Y. Molecular identification and validation of four stable QTL for adult-plant resistance to powdery mildew in Chinese wheat cultivar Bainong 64. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2023; 136:232. [PMID: 37875655 DOI: 10.1007/s00122-023-04481-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/03/2023] [Accepted: 10/04/2023] [Indexed: 10/26/2023]
Abstract
KEY MESSAGE Four stable QTL for adult-plant resistance (APR) to powdery mildew were identified on chromosome arms 1DL, 2BS, 2DL, and 6BL in the widely grown Chinese wheat cultivar Bainong 64. These QTL had no effect on response to stripe rust or leaf rust. Wheat powdery mildew, caused by Blumeria graminis f. sp. tritici (Bgt), is a devastating fungal disease. Seedlings of Chinese wheat Bainong 64 are susceptible to Bgt, but adult plants have maintained resistance since it was released in 1996. A population of 171 recombinant inbred lines (RILs) developed from cross Jingshuang 16/Bainong 64 (JS16/BN64) was used to dissect genetic components of powdery mildew resistance. A genetic map comprising 5383 polymorphic markers was constructed using the 15 K SNP chip and kompetitive allele-specific PCR (KASP) markers. Composite interval mapping identified four stable QTL with favorable alleles all from BN64 on chromosome arms 1DL, 2BS, 2DL, and 6BL in at least four environments. They accounted for 8.3%, 13.8%, 14.4%, and 9.0% of the total phenotypic variation explained (PVE) in maximum, respectively. QPmjbr.caas-1DL, situated about 22 Mb from centromere, is probably a new QTL. QPmjbr.caas-2DL located near the end of arm 2DL and explained the largest PVE. Using genetic maps populated with KASP markers, QPmjbr.caas-2BS and QPmjbr.caas-6BL were fine mapped to a 1.8 cM genetic intervals spanning 13.6 Mb (76.0-89.6 Mb) and 1.7 cM and 4.9 Mb (659.9-664.8 Mb), respectively. The four QTL independent of stripe rust and leaf rust resistance were validated for powdery mildew resistance in another RIL population related to BN64 and a cultivar panel using representative KASP markers. Since BN64 has been a leading cultivar and an important breeding parent in China, the QTL and markers reported in this study will be useful for marker-assisted selection of APR.
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Affiliation(s)
- Xiaowan Xu
- College of Agronomy, Northwest A&F University, Yangling, 712100, Shaanxi, China
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100081, China
| | - Daojie Sun
- College of Agronomy, Northwest A&F University, Yangling, 712100, Shaanxi, China.
| | - Zhongqiu Ni
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100081, China
| | - Xinyu Zou
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100081, China
| | - Xiaoting Xu
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100081, China
| | - Mengjing Sun
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100081, China
| | - Qiang Cao
- College of Agronomy, Northwest A&F University, Yangling, 712100, Shaanxi, China
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100081, China
| | - Jingyang Tong
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100081, China
| | - Fugong Ding
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100081, China
| | - Yelun Zhang
- Institute of Cereal and Oil Crops, Hebei Academy of Agricultural and Forestry Sciences/The Key Laboratory of Crop Genetics and Breeding of Hebei Province, Shijiazhuang, 050035, Hebei, China
| | - Fengju Wang
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100081, China
| | - Yachao Dong
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100081, China
| | - Luyan Zhang
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100081, China
| | - Jiankang Wang
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100081, China
| | - Xianchun Xia
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100081, China
| | - Zhonghu He
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100081, China
- International Maize and Wheat Improvement Center (CIMMYT) China Office, c/o CAAS, 12 Zhongguancun South Street, Beijing, 100081, China
| | - Yuanfeng Hao
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100081, China.
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12
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Xu X, Ni Z, Zou X, Zhang Y, Tong J, Xu X, Dong Y, Han B, Li S, Wang D, Xia X, He Z, Hao Y. QTL Mapping Reveals Both All-Stage and Adult-Plant Resistance to Powdery Mildew in Chinese Elite Wheat Cultivars. PLANT DISEASE 2023; 107:3230-3237. [PMID: 37018212 DOI: 10.1094/pdis-02-23-0399-re] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Powdery mildew caused by Blumeria graminis f. sp. tritici is a threat to wheat production in China. Mapping quantitative trait loci (QTL) for resistance to powdery mildew and developing breeder-friendly markers are important initial steps in breeding resistant cultivars. An all-stage resistance gene and several QTL were identified using a population of 254 recombinant inbred lines developed from a Jingdong 8/Aikang 58 cross. The population was evaluated for powdery mildew resistance across six field environments over three consecutive growing seasons utilizing two different mixtures of B. graminis f. sp. tritici isolates, named #Bgt-HB and #Bgt-BJ. Using genotypic data obtained from the Wheat TraitBreed 50K single-nucleotide polymorphism array, seven stable QTL were identified on chromosome arms 1DL, 2AL, 2DS, 4DL, 5AL, 6BL.1, and 6BL.2. The QTL on 2AL conferred all-stage resistance to B. graminis f. sp. tritici race E20 in greenhouse tests and explained up to 52% of the phenotypic variance in field trials but was resistant only against #Bgt-HB. The gene involved in this QTL was predicted to be Pm4a based on genome location and gene sequence. QPmja.caas-1DL, QPmja.caas-4DL, and QPmja.caas-6BL.1 were identified as potentially new QTL for powdery mildew resistance. QPmja.caas-2DS and QPmja.caas-6BL.1 were effective against both B. graminis f. sp. tritici mixtures, indicating their probable broad-spectrum resistance. A Kompetitive allele-specific PCR marker closely linked to QPmja.caas-2DS was developed and validated in a panel of 286 wheat cultivars. Because both Jingdong 8 and Aikang 58 have been leading cultivars and breeding parents, the QTL and marker reported represent valuable resources for wheat researchers and breeders.
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Affiliation(s)
- Xiaoting Xu
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), Beijing 100081, China
| | - Zhongqiu Ni
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), Beijing 100081, China
| | - Xinyu Zou
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), Beijing 100081, China
| | - Yelun Zhang
- Institute of Cereal and Oil Crops, Hebei Academy of Agricultural and Forestry Sciences/Hebei Laboratory of Crop Genetics and Breeding, Shijiazhuang 050031, Hebei, China
| | - Jingyang Tong
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), Beijing 100081, China
| | - Xiaowan Xu
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), Beijing 100081, China
| | - Yachao Dong
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), Beijing 100081, China
| | - Bin Han
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), Beijing 100081, China
| | - Simin Li
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), Beijing 100081, China
| | - Desen Wang
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), Beijing 100081, China
| | - Xianchun Xia
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), Beijing 100081, China
| | - Zhonghu He
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), Beijing 100081, China
- International Maize and Wheat Improvement Center (CIMMYT) China Office, Beijing 100081, China
| | - Yuanfeng Hao
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), Beijing 100081, China
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13
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Zhao C, Zhou J, Li C, You J, Liu Y, Tang H, Deng M, Xu Q, Zhang Y, Jiang Q, Chen G, Qi P, Jiang Y, Wang J, Li W, Pu Z, Chen G, Jiang Y, Zheng Z, Liu C, Zheng Y, Wei Y, Ma J. A major QTL simultaneously increases the number of spikelets per spike and thousand-kernel weight in a wheat line. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2023; 136:213. [PMID: 37740730 DOI: 10.1007/s00122-023-04459-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/17/2023] [Accepted: 08/31/2023] [Indexed: 09/25/2023]
Abstract
KEY MESSAGE A novel and stably expressed QTL QSNS.sicau-SSY-7A for spikelet number per spike in wheat without negative effects on thousand-kernel weight was identified and validated in different genetic backgrounds. Spikelet number per spike (SNS) is an important determinant of yield in wheat. In the present study, we combined bulked segregant analysis (BSA) and the wheat 660 K single-nucleotide polymorphism (SNP) array to rapidly identify genomic regions associated with SNS from a recombinant inbred line (RIL) population derived from a cross between the wheat lines S849-8 and SY95-71. A genetic map was constructed using Kompetitive Allele Specific PCR markers in the SNP-enriched region on the long arm of chromosome 7A. A major and stably expressed QTL, QSNS.sicau-SSY-7A, was detected in multiple environments. It was located in a 1.6 cM interval on chromosome arm 7AL flanked by the markers AX-109983514 and AX-109820548. This QTL explained 6.86-15.72% of the phenotypic variance, with LOD values ranging from 3.66 to 8.66. Several genes associated with plant growth and development were identified in the interval where QSNS.sicau-SSY-7A was located on the 'Chinese Spring' wheat and wild emmer reference genomes. Furthermore, the effects of QSNS.sicau-SSY-7A and WHEAT ORTHOLOG OFAPO1(WAPO1) on SNS were analyzed. Interestingly, QSNS.sicau-SSY-7A significantly increased SNS without negative effects on thousand-kernel weight, anthesis date and plant height, demonstrating its great potential for breeding aimed at improving grain yield. Taken together, these results indicate that QSNS.sicau-SSY-7A is a promising locus for yield improvement, and its linkage markers are helpful for fine mapping and molecular breeding.
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Affiliation(s)
- Conghao Zhao
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, China
| | - Jieguang Zhou
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, China
| | - Cong Li
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, China
| | - Jianing You
- Industrial Crop Research Institute, Sichuan Academy of Agricultural Sciences, Chengdu, China
| | - Yanling Liu
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, China
| | - Huaping Tang
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, China
| | - Mei Deng
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, China
| | - Qiang Xu
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, China
| | - Yazhou Zhang
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, China
| | - Qiantao Jiang
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, China
| | - Guoyue Chen
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, China
| | - Pengfei Qi
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, China
| | - Yunfeng Jiang
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, China
| | - Jirui Wang
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, China
| | - Wei Li
- College of Agronomy, Sichuan Agricultural University, Chengdu, China
| | - Zhien Pu
- College of Agronomy, Sichuan Agricultural University, Chengdu, China
| | - Guangdeng Chen
- College of Resources, Sichuan Agricultural University, Chengdu, China
| | - Yun Jiang
- Institute of Biotechnology and Nuclear Technology Research, Sichuan Academy ofAgricultural Sciences, Chengdu, China
| | - Zhi Zheng
- CSIRO Agriculture and Food, 306 Carmody Road, Saint Lucia, QLD, 4067, Australia
| | - Chunji Liu
- CSIRO Agriculture and Food, 306 Carmody Road, Saint Lucia, QLD, 4067, Australia
| | - Youliang Zheng
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, China
| | - Yuming Wei
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, China.
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, China.
| | - Jian Ma
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, China.
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, China.
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14
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Ting NC, Chan PL, Buntjer J, Ordway JM, Wischmeyer C, Ooi LCL, Low ETL, Marjuni M, Sambanthamurthi R, Singh R. High-resolution genetic linkage map and height-related QTLs in an oil palm ( Elaeis guineensis) family planted across multiple sites. PHYSIOLOGY AND MOLECULAR BIOLOGY OF PLANTS : AN INTERNATIONAL JOURNAL OF FUNCTIONAL PLANT BIOLOGY 2023; 29:1301-1318. [PMID: 38024957 PMCID: PMC10678900 DOI: 10.1007/s12298-023-01360-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/23/2023] [Revised: 09/09/2023] [Accepted: 09/14/2023] [Indexed: 12/01/2023]
Abstract
A refined SNP array containing 92,459 probes was developed and applied for chromosome scanning, construction of a high-density genetic linkage map and QTL analysis in a selfed Nigerian oil palm family (T128). Genotyping of the T128 mapping family generated 76,447 good quality SNPs for detailed scanning of aberration and homozygosity in the individual pseudo-chromosomes. Of them, 25,364 polymorphic SNPs were used for linkage analysis resulting in an 84.4% mapping rate. A total of 21,413 SNPs were mapped into 16 linkage groups (LGs), covering a total map length of 1364.5 cM. This genetic map is 16X denser than the previous version used to establish pseudo-chromosomes of the oil palm reference genome published in 2013. The QTLs associated with height, height increment and rachis length were identified in LGs TT05, 06, 08, 15 and 16. The present QTLs as well as those published previously were tagged to the reference genome to determine their chromosomal locations. Almost all the QTLs identified in this study were either close to or co-located with those reported in other populations. Determining the QTL position on chromosomes was also helpful in mining for the underlying candidate genes. In total, 55 putative genes and transcription factors involved in the biosynthesis, conjugation and signalling of the major phytohormones, especially for gibberellins and cell wall morphogenesis were found to be present in the identified genomic QTL regions, and their potential roles in plant dwarfism are discussed. Supplementary Information The online version contains supplementary material available at 10.1007/s12298-023-01360-2.
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Affiliation(s)
- Ngoot-Chin Ting
- Malaysian Palm Oil Board (MPOB), Advanced Biotechnology and Breeding Centre, 6, Persiaran Institusi, Bandar Baru Bangi, 43000 Kajang, Selangor Malaysia
| | - Pek-Lan Chan
- Malaysian Palm Oil Board (MPOB), Advanced Biotechnology and Breeding Centre, 6, Persiaran Institusi, Bandar Baru Bangi, 43000 Kajang, Selangor Malaysia
| | | | | | | | - Leslie Cheng-Li Ooi
- Malaysian Palm Oil Board (MPOB), Advanced Biotechnology and Breeding Centre, 6, Persiaran Institusi, Bandar Baru Bangi, 43000 Kajang, Selangor Malaysia
| | - Eng Ti Leslie Low
- Malaysian Palm Oil Board (MPOB), Advanced Biotechnology and Breeding Centre, 6, Persiaran Institusi, Bandar Baru Bangi, 43000 Kajang, Selangor Malaysia
| | - Marhalil Marjuni
- Malaysian Palm Oil Board (MPOB), Advanced Biotechnology and Breeding Centre, 6, Persiaran Institusi, Bandar Baru Bangi, 43000 Kajang, Selangor Malaysia
| | - Ravigadevi Sambanthamurthi
- Malaysian Palm Oil Board (MPOB), Advanced Biotechnology and Breeding Centre, 6, Persiaran Institusi, Bandar Baru Bangi, 43000 Kajang, Selangor Malaysia
| | - Rajinder Singh
- Malaysian Palm Oil Board (MPOB), Advanced Biotechnology and Breeding Centre, 6, Persiaran Institusi, Bandar Baru Bangi, 43000 Kajang, Selangor Malaysia
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Wu C, Ma K, Chen W, Li J, Liu M, Cheng P, Wang B, Li Q. Identification and Molecular Mapping of the Gene YrFL in Wheat Cultivar Flanders with Durable Resistance to Stripe Rust. PLANT DISEASE 2023; 107:2716-2723. [PMID: 36774583 DOI: 10.1094/pdis-11-22-2683-re] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
Stripe rust, caused by Puccinia striiformis f. sp. tritici (Pst), is one of the most severe diseases of wheat (Triticum aestivum L.) worldwide. Identification and characterization of resistance genes is advantageous to cultivating wheat varieties with durable resistance, which is the most economic and effective strategy to control stripe rust. Flanders, a common wheat cultivar released in France in 1986, confers effective resistance to stripe rust both at the seedling and adult plant stages. To elucidate the genetic basis of resistance in Flanders, F1, F2, and F2:3 generations derived from the cross Mingxian169 × Flanders were evaluated with the most prevalent Chinese Pst race CYR33 at the seedling stage. Inheritance analysis showed that the stripe rust resistance of Flanders was controlled by a single dominant gene, temporarily designated as YrFL. Bulked segregant analysis (BSA) combined with a wheat 660K single-nucleotide polymorphism (SNP) array indicated that polymorphic SNP markers were mainly located in the 0 to 150 Mb on wheat chromosome 5A. One hundred and eleven kompetitive allele-specific PCR (KASP) and 39 simple sequence repeat (SSR) markers on chromosome 5A were used to locate the YrFL. Linkage analysis mapped YrFL with 19 KASP and three SSR markers on wheat chromosome 5AS, and the genetic distances of the closest flanking markers AX108925494 and Xbarc56 to YrFL were 0.6 and 2.0 cM, respectively. Chromosome location, resistance characterization, and molecular marker positions indicated that YrFL is likely a novel stripe rust resistance gene on wheat chromosome 5AS and could be pyramided with other resistance genes to improve resistance in wheat breeding programs.
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Affiliation(s)
- Caijuan Wu
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Plant Protection, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Kangjie Ma
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Plant Protection, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Wenbin Chen
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Plant Protection, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Jianhao Li
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Plant Protection, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Mingjie Liu
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Plant Protection, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Peng Cheng
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Plant Protection, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Baotong Wang
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Plant Protection, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Qiang Li
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Plant Protection, Northwest A&F University, Yangling, Shaanxi 712100, China
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Yan Q, Jia G, Tan W, Tian R, Zheng X, Feng J, Luo X, Si B, Li X, Huang K, Wang M, Chen X, Ren Y, Yang S, Zhou X. Genome-wide QTL mapping for stripe rust resistance in spring wheat line PI 660122 using the Wheat 15K SNP array. FRONTIERS IN PLANT SCIENCE 2023; 14:1232897. [PMID: 37701804 PMCID: PMC10493333 DOI: 10.3389/fpls.2023.1232897] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Accepted: 07/31/2023] [Indexed: 09/14/2023]
Abstract
Introduction Stripe rust is a global disease of wheat. Identification of new resistance genes is key to developing and growing resistant varieties for control of the disease. Wheat line PI 660122 has exhibited a high level of stripe rust resistance for over a decade. However, the genetics of stripe rust resistance in this line has not been studied. A set of 239 recombinant inbred lines (RILs) was developed from a cross between PI 660122 and an elite Chinese cultivar Zhengmai 9023. Methods The RIL population was phenotyped for stripe rust response in three field environments and genotyped with the Wheat 15K single-nucleotide polymorphism (SNP) array. Results A total of nine quantitative trait loci (QTLs) for stripe rust resistance were mapped to chromosomes 1B (one QTL), 2B (one QTL), 4B (two QTLs), 4D (two QTLs), 6A (one QTL), 6D (one QTL), and 7D (one QTL), of which seven QTLs were stable and designated as QYrPI660122.swust-4BS, QYrPI660122.swust-4BL, QYrPI660122.swust-4DS, QYrPI660122.swust-4DL, QYrZM9023.swust-6AS, QYrZM9023.swust-6DS, and QYrPI660122.swust-7DS. QYrPI660122.swust-4DS was a major all-stage resistance QTL explaining the highest percentage (10.67%-20.97%) of the total phenotypic variation and was mapped to a 12.15-cM interval flanked by SNP markers AX-110046962 and AX-111093894 on chromosome 4DS. Discussion The QTL and their linked SNP markers in this study can be used in wheat breeding to improve resistance to stripe rust. In addition, 26 lines were selected based on stripe rust resistance and agronomic traits in the field for further selection and release of new cultivars.
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Affiliation(s)
- Qiong Yan
- Wheat Research Institute, School of Life Sciences and Engineering, Southwest University of Science and Technology, Mianyang, Sichuan, China
| | - Guoyun Jia
- Wheat Research Institute, School of Life Sciences and Engineering, Southwest University of Science and Technology, Mianyang, Sichuan, China
| | - Wenjing Tan
- Wheat Research Institute, School of Life Sciences and Engineering, Southwest University of Science and Technology, Mianyang, Sichuan, China
| | - Ran Tian
- Wheat Research Institute, School of Life Sciences and Engineering, Southwest University of Science and Technology, Mianyang, Sichuan, China
| | - Xiaochen Zheng
- Wheat Research Institute, School of Life Sciences and Engineering, Southwest University of Science and Technology, Mianyang, Sichuan, China
| | - Junming Feng
- Wheat Research Institute, School of Life Sciences and Engineering, Southwest University of Science and Technology, Mianyang, Sichuan, China
| | - Xiaoqin Luo
- Wheat Research Institute, School of Life Sciences and Engineering, Southwest University of Science and Technology, Mianyang, Sichuan, China
| | - Binfan Si
- Wheat Research Institute, School of Life Sciences and Engineering, Southwest University of Science and Technology, Mianyang, Sichuan, China
| | - Xin Li
- Wheat Research Institute, School of Life Sciences and Engineering, Southwest University of Science and Technology, Mianyang, Sichuan, China
| | - Kebing Huang
- Wheat Research Institute, School of Life Sciences and Engineering, Southwest University of Science and Technology, Mianyang, Sichuan, China
| | - Meinan Wang
- Department of Plant Pathology, Washington State University, Pullman, WA, United States
| | - Xianming Chen
- Department of Plant Pathology, Washington State University, Pullman, WA, United States
- Wheat Health, Genetics, and Quality Research Unit, US Department of Agriculture-Agricultural Research Service (USDA-ARS), Pullman, WA, United States
| | - Yong Ren
- Crop Characteristic Resources Creation and Utilization Key Laboratory of Sichuan Province, Mianyang Institute of Agricultural Science, Mianyang, Sichuan, China
| | - Suizhuang Yang
- Wheat Research Institute, School of Life Sciences and Engineering, Southwest University of Science and Technology, Mianyang, Sichuan, China
| | - Xinli Zhou
- Wheat Research Institute, School of Life Sciences and Engineering, Southwest University of Science and Technology, Mianyang, Sichuan, China
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17
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Draeger TN, Rey MD, Hayta S, Smedley M, Martin AC, Moore G. DMC1 stabilizes crossovers at high and low temperatures during wheat meiosis. FRONTIERS IN PLANT SCIENCE 2023; 14:1208285. [PMID: 37615022 PMCID: PMC10442654 DOI: 10.3389/fpls.2023.1208285] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Accepted: 07/17/2023] [Indexed: 08/25/2023]
Abstract
Effective chromosome synapsis and crossover formation during meiosis are essential for fertility, especially in grain crops such as wheat. These processes function most efficiently in wheat at temperatures between 17-23 °C, although the genetic mechanisms for such temperature dependence are unknown. In a previously identified mutant of the hexaploid wheat reference variety 'Chinese Spring' lacking the long arm of chromosome 5D, exposure to low temperatures during meiosis resulted in asynapsis and crossover failure. In a second mutant (ttmei1), containing a 4 Mb deletion in chromosome 5DL, exposure to 13 °C led to similarly high levels of asynapsis and univalence. Moreover, exposure to 30 °C led to a significant, but less extreme effect on crossovers. Previously, we proposed that, of 41 genes deleted in this 4 Mb region, the major meiotic gene TaDMC1-D1 was the most likely candidate for preservation of synapsis and crossovers at low (and possibly high) temperatures. In the current study, using RNA-guided Cas9, we developed a new Chinese Spring CRISPR mutant, containing a 39 bp deletion in the 5D copy of DMC1, representing the first reported CRISPR-Cas9 targeted mutagenesis in Chinese Spring, and the first CRISPR mutant for DMC1 in wheat. In controlled environment experiments, wild-type Chinese Spring, CRISPR dmc1-D1 and backcrossed ttmei1 mutants were exposed to either high or low temperatures during the temperature-sensitive period from premeiotic interphase to early meiosis I. After 6-7 days at 13 °C, crossovers decreased by over 95% in the dmc1-D1 mutants, when compared with wild-type plants grown under the same conditions. After 24 hours at 30 °C, dmc1-D1 mutants exhibited a reduced number of crossovers and increased univalence, although these differences were less marked than at 13 °C. Similar results were obtained for ttmei1 mutants, although their scores were more variable, possibly reflecting higher levels of background mutation. These experiments confirm our previous hypothesis that DMC1-D1 is responsible for preservation of normal crossover formation at low and, to a certain extent, high temperatures. Given that reductions in crossovers have significant effects on grain yield, these results have important implications for wheat breeding, particularly in the face of climate change.
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Affiliation(s)
| | - María-Dolores Rey
- Agroforestry and Plant Biochemistry, Proteomics and Systems Biology, Department of Biochemistry and Molecular Biology, University of Córdoba, Córdoba, Spain
| | - Sadiye Hayta
- John Innes Centre, Norwich Research Park, Norwich, United Kingdom
| | - Mark Smedley
- John Innes Centre, Norwich Research Park, Norwich, United Kingdom
| | - Azahara C. Martin
- Department of Plant Genetic Improvement, Institute for Sustainable Agriculture, Spanish National Research Council (CSIC), Córdoba, Spain
| | - Graham Moore
- John Innes Centre, Norwich Research Park, Norwich, United Kingdom
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18
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Yadav IS, Rawat N, Chhuneja P, Kaur S, Uauy C, Lazo G, Gu YQ, Doležel J, Tiwari VK. Comparative genomic analysis of 5M g chromosome of Aegilops geniculata and 5U u chromosome of Aegilops umbellulata reveal genic diversity in the tertiary gene pool. FRONTIERS IN PLANT SCIENCE 2023; 14:1144000. [PMID: 37521926 PMCID: PMC10373596 DOI: 10.3389/fpls.2023.1144000] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Accepted: 06/22/2023] [Indexed: 08/01/2023]
Abstract
Wheat is one of the most important cereal crops for the global food security. Due to its narrow genetic base, modern bread wheat cultivars face challenges from increasing abiotic and biotic stresses. Since genetic improvement is the most sustainable approach, finding novel genes and alleles is critical for enhancing the genetic diversity of wheat. The tertiary gene pool of wheat is considered a gold mine for genetic diversity as novel genes and alleles can be identified and transferred to wheat cultivars. Aegilops geniculata and Ae. umbellulata are the key members of the tertiary gene pool of wheat and harbor important genes against abiotic and biotic stresses. Homoeologous-group five chromosomes (5Uu and 5Mg) have been extensively studied from Ae. geniculata and Ae. umbellulata as they harbor several important genes including Lr57, Lr76, Yr40, Yr70, Sr53 and chromosomal pairing loci. In the present study, using chromosome DNA sequencing and RNAseq datasets, we performed comparative analysis to study homoeologous gene evolution in 5Mg, 5Uu, and group 5 wheat chromosomes. Our findings highlight the diversity of transcription factors and resistance genes, resulting from the differential expansion of the gene families. Both the chromosomes were found to be enriched with the "response to stimulus" category of genes providing resistance against biotic and abiotic stress. Phylogenetic study positioned the M genome closer to the D genome, with higher proximity to the A genome than the B genome. Over 4000 genes were impacted by SNPs on 5D, with 4-5% of those genes displaying non-disruptive variations that affect gene function.
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Affiliation(s)
- Inderjit S. Yadav
- Department of Plant Sciences and Landscape Architecture, University of Maryland, College Park, MD, United States
- School of Agricultural Biotechnology, Punjab Agricultural University, Ludhiana, India
| | - Nidhi Rawat
- Department of Plant Sciences and Landscape Architecture, University of Maryland, College Park, MD, United States
| | - Parveen Chhuneja
- School of Agricultural Biotechnology, Punjab Agricultural University, Ludhiana, India
| | - Satinder Kaur
- School of Agricultural Biotechnology, Punjab Agricultural University, Ludhiana, India
| | | | - Gerard Lazo
- Agricultural Research Service, United States Department of Agriculture (USDA), Albany, CA, United States
| | - Yong Q. Gu
- Agricultural Research Service, United States Department of Agriculture (USDA), Albany, CA, United States
| | - Jaroslav Doležel
- Centre of Plant Structural and Functional Genomics, Institute of Experimental Botany, Olomouc, Czechia
| | - Vijay K. Tiwari
- Department of Plant Sciences and Landscape Architecture, University of Maryland, College Park, MD, United States
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19
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Pasam RK, Kant S, Thoday-Kennedy E, Dimech A, Joshi S, Keeble-Gagnere G, Forrest K, Tibbits J, Hayden M. Haplotype-Based Genome-Wide Association Analysis Using Exome Capture Assay and Digital Phenotyping Identifies Genetic Loci Underlying Salt Tolerance Mechanisms in Wheat. PLANTS (BASEL, SWITZERLAND) 2023; 12:2367. [PMID: 37375992 DOI: 10.3390/plants12122367] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Revised: 06/14/2023] [Accepted: 06/16/2023] [Indexed: 06/29/2023]
Abstract
Soil salinity can impose substantial stress on plant growth and cause significant yield losses. Crop varieties tolerant to salinity stress are needed to sustain yields in saline soils. This requires effective genotyping and phenotyping of germplasm pools to identify novel genes and QTL conferring salt tolerance that can be utilised in crop breeding schemes. We investigated a globally diverse collection of 580 wheat accessions for their growth response to salinity using automated digital phenotyping performed under controlled environmental conditions. The results show that digitally collected plant traits, including digital shoot growth rate and digital senescence rate, can be used as proxy traits for selecting salinity-tolerant accessions. A haplotype-based genome-wide association study was conducted using 58,502 linkage disequilibrium-based haplotype blocks derived from 883,300 genome-wide SNPs and identified 95 QTL for salinity tolerance component traits, of which 54 were novel and 41 overlapped with previously reported QTL. Gene ontology analysis identified a suite of candidate genes for salinity tolerance, some of which are already known to play a role in stress tolerance in other plant species. This study identified wheat accessions that utilise different tolerance mechanisms and which can be used in future studies to investigate the genetic and genic basis of salinity tolerance. Our results suggest salinity tolerance has not arisen from or been bred into accessions from specific regions or groups. Rather, they suggest salinity tolerance is widespread, with small-effect genetic variants contributing to different levels of tolerance in diverse, locally adapted germplasm.
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Affiliation(s)
- Raj K Pasam
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC 3083, Australia
| | - Surya Kant
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC 3083, Australia
- Agriculture Victoria, Grains Innovation Park, Horsham, VIC 3400, Australia
- School of Applied Systems Biology, La Trobe University, Bundoora, VIC 3083, Australia
| | | | - Adam Dimech
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC 3083, Australia
| | - Sameer Joshi
- Agriculture Victoria, Grains Innovation Park, Horsham, VIC 3400, Australia
| | | | - Kerrie Forrest
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC 3083, Australia
| | - Josquin Tibbits
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC 3083, Australia
| | - Matthew Hayden
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC 3083, Australia
- School of Applied Systems Biology, La Trobe University, Bundoora, VIC 3083, Australia
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20
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Kang Y, Choi C, Kim JY, Min KD, Kim C. Optimizing genomic selection of agricultural traits using K-wheat core collection. FRONTIERS IN PLANT SCIENCE 2023; 14:1112297. [PMID: 37389296 PMCID: PMC10303932 DOI: 10.3389/fpls.2023.1112297] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Accepted: 02/02/2023] [Indexed: 07/01/2023]
Abstract
The agricultural traits that constitute basic plant breeding information are usually quantitative or complex in nature. This quantitative and complex combination of traits complicates the process of selection in breeding. This study examined the potential of genome-wide association studies (GWAS) and genomewide selection (GS) for breeding ten agricultural traits by using genome-wide SNPs. As a first step, a trait-associated candidate marker was identified by GWAS using a genetically diverse 567 Korean (K)-wheat core collection. The accessions were genotyped using an Axiom® 35K wheat DNA chip, and ten agricultural traits were determined (awn color, awn length, culm color, culm length, ear color, ear length, days to heading, days to maturity, leaf length, and leaf width). It is essential to sustain global wheat production by utilizing accessions in wheat breeding. Among the traits associated with awn color and ear color that showed a high positive correlation, a SNP located on chr1B was significantly associated with both traits. Next, GS evaluated the prediction accuracy using six predictive models (G-BLUP, LASSO, BayseA, reproducing kernel Hilbert space, support vector machine (SVM), and random forest) and various training populations (TPs). With the exception of the SVM, all statistical models demonstrated a prediction accuracy of 0.4 or better. For the optimization of the TP, the number of TPs was randomly selected (10%, 30%, 50% and 70%) or divided into three subgroups (CC-sub 1, CC-sub 2 and CC-sub 3) based on the subpopulation structure. Based on subgroup-based TPs, better prediction accuracy was found for awn color, culm color, culm length, ear color, ear length, and leaf width. A variety of Korean wheat cultivars were used for validation to evaluate the prediction ability of populations. Seven out of ten cultivars showed phenotype-consistent results based on genomics-evaluated breeding values (GEBVs) calculated by the reproducing kernel Hilbert space (RKHS) predictive model. Our research provides a basis for improving complex traits in wheat breeding programs through genomics assisted breeding. The results of our research can be used as a basis for improving wheat breeding programs by using genomics-assisted breeding.
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Affiliation(s)
- Yuna Kang
- Department of Crop Science, Chungnam National University, Daejeon, Republic of Korea
| | - Changhyun Choi
- Wheat Research Team, National Institution Crop Sciences, Wanju-gun, Republic of Korea
| | - Jae Yoon Kim
- Department of Plant Resources, Kongju National University, Yesan, Republic of Korea
| | - Kyeong Do Min
- Department of Plant Resources, Kongju National University, Yesan, Republic of Korea
| | - Changsoo Kim
- Department of Crop Science, Chungnam National University, Daejeon, Republic of Korea
- Department of Smart Agriculture Systems, Chungnam National University, Daejeon, Republic of Korea
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21
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Amalova A, Yermekbayev K, Griffiths S, Winfield MO, Morgounov A, Abugalieva S, Turuspekov Y. Population Structure of Modern Winter Wheat Accessions from Central Asia. PLANTS (BASEL, SWITZERLAND) 2023; 12:2233. [PMID: 37375859 DOI: 10.3390/plants12122233] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Revised: 05/31/2023] [Accepted: 06/02/2023] [Indexed: 06/29/2023]
Abstract
Despite the importance of winter wheat in Central Asian countries, there are limited reports describing their diversity within this region. In this study, the population structures of 115 modern winter wheat cultivars from four Central Asian countries were compared to germplasms from six other geographic origins using 10,746 polymorphic single-nucleotide polymorphism (SNP) markers. After applying the STRUCTURE package, we found that in terms of the most optimal K steps, samples from Kazakhstan and Kyrgyzstan were grouped together with samples from Russia, while samples from Tajikistan and Uzbekistan were grouped with samples from Afghanistan. The mean value of Nei's genetic diversity index for the germplasm from four groups from Central Asia was 0.261, which is comparable to that of the six other groups studied: Europe, Australia, the USA, Afghanistan, Turkey, and Russia. The Principal Coordinate Analysis (PCoA) showed that samples from Kyrgyzstan, Tajikistan, and Uzbekistan were close to samples from Turkey, while Kazakh accessions were located near samples from Russia. The evaluation of 10,746 SNPs in Central Asian wheat suggested that 1006 markers had opposing allele frequencies. Further assessment of the physical positions of these 1006 SNPs in the Wheat Ensembl database indicated that most of these markers are constituents of genes associated with plant stress tolerance and adaptability. Therefore, the SNP markers identified can be effectively used in regional winter wheat breeding projects for facilitating plant adaptation and stress resistance.
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Affiliation(s)
- Akerke Amalova
- Laboratory of Molecular Genetics, Institute of Plant Biology and Biotechnology, Almaty 050040, Kazakhstan
| | - Kanat Yermekbayev
- Laboratory of Molecular Genetics, Institute of Plant Biology and Biotechnology, Almaty 050040, Kazakhstan
- Crop Genetics Department, John Innes Centre, Norwich NR4 7UH, UK
| | - Simon Griffiths
- Crop Genetics Department, John Innes Centre, Norwich NR4 7UH, UK
| | | | - Alexey Morgounov
- Science Department, S. Seifullin Kazakh Agrotechnical University, Astana 010011, Kazakhstan
| | - Saule Abugalieva
- Laboratory of Molecular Genetics, Institute of Plant Biology and Biotechnology, Almaty 050040, Kazakhstan
- Faculty of Biology and Biotechnology, Al-Farabi Kazakh National University, Almaty 050040, Kazakhstan
| | - Yerlan Turuspekov
- Laboratory of Molecular Genetics, Institute of Plant Biology and Biotechnology, Almaty 050040, Kazakhstan
- Faculty of Biology and Biotechnology, Al-Farabi Kazakh National University, Almaty 050040, Kazakhstan
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22
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Machado IP, DoVale JC, Sabadin F, Fritsche-Neto R. On the usefulness of mock genomes to define heterotic pools, testers, and hybrid predictions in orphan crops. FRONTIERS IN PLANT SCIENCE 2023; 14:1164555. [PMID: 37332727 PMCID: PMC10272588 DOI: 10.3389/fpls.2023.1164555] [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: 02/13/2023] [Accepted: 05/10/2023] [Indexed: 06/20/2023]
Abstract
The advances in genomics in recent years have increased the accuracy and efficiency of breeding programs for many crops. Nevertheless, the adoption of genomic enhancement for several other crops essential in developing countries is still limited, especially for those that do not have a reference genome. These crops are more often called orphans. This is the first report to show how the results provided by different platforms, including the use of a simulated genome, called the mock genome, can generate in population structure and genetic diversity studies, especially when the intention is to use this information to support the formation of heterotic groups, choice of testers, and genomic prediction of single crosses. For that, we used a method to assemble a reference genome to perform the single-nucleotide polymorphism (SNP) calling without needing an external genome. Thus, we compared the analysis results using the mock genome with the standard approaches (array and genotyping-by-sequencing (GBS)). The results showed that the GBS-Mock presented similar results to the standard methods of genetic diversity studies, division of heterotic groups, the definition of testers, and genomic prediction. These results showed that a mock genome constructed from the population's intrinsic polymorphisms to perform the SNP calling is an effective alternative for conducting genomic studies of this nature in orphan crops, especially those that do not have a reference genome.
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Affiliation(s)
| | - Júlio César DoVale
- Department of Crop Science, Federal University of Ceará, Fortaleza, Brazil
| | - Felipe Sabadin
- School of Plant and Environmental Sciences, Virginia Tech: Virginia Polytechnic Institute and State University, Blacksburg, VA, United States
| | - Roberto Fritsche-Neto
- LSU AgCenter, Louisiana State University Agricultural Center, Baton Rouge, LA, United States
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23
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Wang S, Wang T, Xuan Q, Qu X, Xu Q, Jiang Q, Pu Z, Li Y, Jiang Y, Chen G, Deng M, Liu Y, Tang H, Chen G, He Y, Gou L, Wei Y, Zheng Y, Ma J. Major and stably expressed QTL for traits related to the mature wheat embryo independent of kernel size. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2023; 136:90. [PMID: 37000252 DOI: 10.1007/s00122-023-04346-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Accepted: 03/14/2023] [Indexed: 06/19/2023]
Abstract
Two major and stably expressed QTL for traits related to mature wheat embryo independent of kernel size were identified and validated in a natural population that contained 171 Sichuan wheat accessions and 49 Sichuan wheat landraces. As the juvenile of a highly differentiated plant, mature wheat (Triticum aestivum L.) embryos are highly significant to agricultural production. To understand the genetic basis of traits related to wheat embryo size, the embryo of mature kernels in a recombination inbred line that contained 126 lines from four environments was measured. The genetic loci of embryo size, including embryo length (EL), embryo width (EW), embryo area (EA), embryo length/kernel length (EL/KL), embryo width/kernel width (EW/KW), and EL/EW, were identified based on a genetic linkage map constructed based on PCR markers and the Wheat 55 K single nucleotide polymorphism (SNP) array. A total of 50 quantitative trait loci (QTL) for traits related to wheat embryo size were detected. Among them, QEL.sicau-2SY-4A for EL and QEW.sicau-2SY-7B for EW were major and stably expressed and were genetically independent of KL and KW, respectively. Their effects were further verified in a natural population that contained 171 Sichuan wheat accessions and 49 Sichuan wheat landraces. Further analysis showed that TraesCS4A02G343300 and TraesCS7B02G006800 could be candidate genes for QEL.sicau-2SY-4A and QEW.sicau-2SY-7B, respectively. In addition, significant positive correlations between EL and kernel-related traits and the 1,000-grain weight were detected. Collectively, this study broadens our understanding of the genetic basis of wheat embryo size and will be helpful for the further fine-mapping of interesting loci in the future.
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Affiliation(s)
- Surong Wang
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, 611130, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, 611130, China
| | - Tianyu Wang
- College of Agronomy, Sichuan Agricultural University, Chengdu, 611130, China
| | - Qijing Xuan
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, 611130, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, 611130, China
| | - Xiangru Qu
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, 611130, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, 611130, China
| | - Qiang Xu
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, 611130, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, 611130, China
| | - Qiantao Jiang
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, 611130, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, 611130, China
| | - Zhien Pu
- College of Agronomy, Sichuan Agricultural University, Chengdu, 611130, China
| | - Yang Li
- College of Agronomy, Sichuan Agricultural University, Chengdu, 611130, China
| | - Yunfeng Jiang
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, 611130, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, 611130, China
| | - Guoyue Chen
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, 611130, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, 611130, China
| | - Mei Deng
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, 611130, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, 611130, China
| | - Yanling Liu
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, 611130, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, 611130, China
| | - Huaping Tang
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, 611130, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, 611130, China
| | - Guangdeng Chen
- College of Resources, Sichuan Agricultural University, Chengdu, 611130, China
| | - Yuanjiang He
- Mianyang Academy of Agricultural Science/Crop Characteristic Resources Creation and Utilization Key Laboratory of Sichuan Providence, Mianyang, 621000, China
| | - Lulu Gou
- College of Agronomy, Sichuan Agricultural University, Chengdu, 611130, China
| | - Yuming Wei
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, 611130, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, 611130, China
| | - Youliang Zheng
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, 611130, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, 611130, China
| | - Jian Ma
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, 611130, China.
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, 611130, China.
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Ma F, Xu Y, Wang R, Tong Y, Zhang A, Liu D, An D. Identification of major QTLs for yield-related traits with improved genetic map in wheat. FRONTIERS IN PLANT SCIENCE 2023; 14:1138696. [PMID: 37008504 PMCID: PMC10063875 DOI: 10.3389/fpls.2023.1138696] [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: 01/06/2023] [Accepted: 03/08/2023] [Indexed: 06/19/2023]
Abstract
INTRODUCTION Identification of stable major quantitative trait loci (QTLs) for yield-related traits is important for yield potential improvement in wheat breeding. METHODS In the present study, we genotyped a recombinant inbred line (RIL) population using the Wheat 660K SNP array and constructed a high-density genetic map. The genetic map showed high collinearity with the wheat genome assembly. Fourteen yield-related traits were evaluated in six environments for QTL analysis. RESULTS AND DISCUSSION A total of 12 environmentally stable QTLs were identified in at least three environments, explaining up to 34.7% of the phenotypic variation. Of these, QTkw-1B.2 for thousand kernel weight (TKW), QPh-2D.1 (QSl-2D.2/QScn-2D.1) for plant height (PH), spike length (SL) and spikelet compactness (SCN), QPh-4B.1 for PH, and QTss-7A.3 for total spikelet number per spike (TSS) were detected in at least five environments. A set of Kompetitive Allele Specific PCR (KASP) markers were converted based on the above QTLs and used to genotype a diversity panel comprising of 190 wheat accessions across four growing seasons. QPh-2D.1 (QSl-2D.2/QScn-2D.1), QPh-4B.1 and QTss-7A.3 were successfully validated. Compared with previous studies, QTkw-1B.2 and QPh-4B.1 should be novel QTLs. These results provided a solid foundation for further positional cloning and marker-assisted selection of the targeted QTLs in wheat breeding programs.
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Affiliation(s)
- Feifei Ma
- Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang, China
| | - Yunfeng Xu
- Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang, China
| | - Ruifang Wang
- Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang, China
| | - Yiping Tong
- State Key Laboratory of Plant Cell and Chromosome Engineering, National Center for Plant Gene Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China
| | - Aimin Zhang
- State Key Laboratory of North China Crop Improvement and Regulation, College of Agronomy, Hebei Agricultural University, Baoding, Hebei, China
- State Key Laboratory of Plant Cell and Chromosome Engineering, National Center for Plant Gene Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China
| | - Dongcheng Liu
- State Key Laboratory of North China Crop Improvement and Regulation, College of Agronomy, Hebei Agricultural University, Baoding, Hebei, China
| | - Diaoguo An
- Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang, China
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Klymiuk V, Haile T, Ens J, Wiebe K, N’Diaye A, Fatiukha A, Krugman T, Ben-David R, Hübner S, Cloutier S, Pozniak CJ. Genetic architecture of rust resistance in a wheat ( Triticum turgidum) diversity panel. FRONTIERS IN PLANT SCIENCE 2023; 14:1145371. [PMID: 36998679 PMCID: PMC10043469 DOI: 10.3389/fpls.2023.1145371] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Accepted: 02/24/2023] [Indexed: 06/19/2023]
Abstract
INTRODUCTION Wheat rust diseases are widespread and affect all wheat growing areas around the globe. Breeding strategies focus on incorporating genetic disease resistance. However, pathogens can quickly evolve and overcome the resistance genes deployed in commercial cultivars, creating a constant need for identifying new sources of resistance. METHODS We have assembled a diverse tetraploid wheat panel comprised of 447 accessions of three Triticum turgidum subspecies and performed a genome-wide association study (GWAS) for resistance to wheat stem, stripe, and leaf rusts. The panel was genotyped with the 90K Wheat iSelect single nucleotide polymorphism (SNP) array and subsequent filtering resulted in a set of 6,410 non-redundant SNP markers with known physical positions. RESULTS Population structure and phylogenetic analyses revealed that the diversity panel could be divided into three subpopulations based on phylogenetic/geographic relatedness. Marker-trait associations (MTAs) were detected for two stem rust, two stripe rust and one leaf rust resistance loci. Of them, three MTAs coincide with the known rust resistance genes Sr13, Yr15 and Yr67, while the other two may harbor undescribed resistance genes. DISCUSSION The tetraploid wheat diversity panel, developed and characterized herein, captures wide geographic origins, genetic diversity, and evolutionary history since domestication making it a useful community resource for mapping of other agronomically important traits and for conducting evolutionary studies.
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Affiliation(s)
- Valentyna Klymiuk
- Crop Development Centre and Department of Plant Sciences, University of Saskatchewan, Saskatoon, SK, Canada
| | - Teketel Haile
- Crop Development Centre and Department of Plant Sciences, University of Saskatchewan, Saskatoon, SK, Canada
| | - Jennifer Ens
- Crop Development Centre and Department of Plant Sciences, University of Saskatchewan, Saskatoon, SK, Canada
| | - Krystalee Wiebe
- Crop Development Centre and Department of Plant Sciences, University of Saskatchewan, Saskatoon, SK, Canada
| | - Amidou N’Diaye
- Crop Development Centre and Department of Plant Sciences, University of Saskatchewan, Saskatoon, SK, Canada
| | - Andrii Fatiukha
- Crop Development Centre and Department of Plant Sciences, University of Saskatchewan, Saskatoon, SK, Canada
| | - Tamar Krugman
- Institute of Evolution, University of Haifa, Haifa, Israel
| | - Roi Ben-David
- Department of Vegetables and Field Crops, Institute of Plant Sciences, Agricultural Research Organization (ARO) – The Volcani Center, Rishon LeZion, Israel
| | - Sariel Hübner
- Galilee Research Institute (MIGAL), Tel Hai Academic College, Upper Galilee, Israel
| | - Sylvie Cloutier
- Ottawa Research and Development Centre, Agriculture and Agri-Food Canada, Ottawa, ON, Canada
- Department of Biology, University of Ottawa, Ottawa, ON, Canada
| | - Curtis J. Pozniak
- Crop Development Centre and Department of Plant Sciences, University of Saskatchewan, Saskatoon, SK, Canada
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Niu J, Si Y, Tian S, Liu X, Shi X, Ma S, Yu Z, Ling HQ, Zheng S. A Wheat 660 K SNP array-based high-density genetic map facilitates QTL mapping of flag leaf-related traits in wheat. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2023; 136:51. [PMID: 36913011 DOI: 10.1007/s00122-023-04248-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Accepted: 11/26/2022] [Indexed: 06/18/2023]
Abstract
A high-density genetic map containing 122,620 SNP markers was constructed, which facilitated the identification of eight major flag leaf-related QTL in relatively narrow intervals. The flag leaf plays an important role in photosynthetic capacity and yield potential in wheat. In this study, we used a recombinant inbred line population containing 188 lines derived from a cross between 'Lankao86' (LK86) and 'Ermangmai' to construct a genetic map using the Wheat 660 K single-nucleotide polymorphism (SNP) array. The high-density genetic map contains 122,620 SNP markers spanning 5185.06 cM. It shows good collinearity with the physical map of Chinese Spring and anchors multiple sequences of previously unplaced scaffolds onto chromosomes. Based on the high-density genetic map, we identified seven, twelve, and eight quantitative trait loci (QTL) for flag leaf length (FLL), width (FLW), and area (FLA) across eight environments, respectively. Among them, three, one, and four QTL for FLL, FLW, and FLA are major and stably express in more than four environments. The physical distance between the flanking markers for QFll.igdb-3B/QFlw.igdb-3B/QFla.igdb-3B is only 444 kb containing eight high confidence genes. These results suggested that we could directly map the candidate genes in a relatively small region by the high-density genetic map constructed with the Wheat 660 K array. Furthermore, the identification of environmentally stable QTL for flag leaf morphology laid a foundation for the following gene cloning and flag leaf morphology improvement.
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Affiliation(s)
- Jianqing Niu
- Hainan Yazhou Bay Seed Lab, Sanya, Hainan, China
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
| | - Yaoqi Si
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
| | - Shuiquan Tian
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Xiaolin Liu
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Xiaoli Shi
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
| | - Shengwei Ma
- Hainan Yazhou Bay Seed Lab, Sanya, Hainan, China
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
| | - Zhongqing Yu
- National Key Laboratory of Crop Biology, College of Life Sciences, Shandong Agricultural University, Taian, China
| | - Hong-Qing Ling
- Hainan Yazhou Bay Seed Lab, Sanya, Hainan, China.
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China.
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China.
| | - Shusong Zheng
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China.
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Velimirović A, Jovović Z, Perović D, Lehnert H, Mikić S, Mandić D, Pržulj N, Mangini G, Finetti-Sialer MM. SNP Diversity and Genetic Structure of "Rogosija", an Old Western Balkan Durum Wheat Collection. PLANTS (BASEL, SWITZERLAND) 2023; 12:1157. [PMID: 36904017 PMCID: PMC10005349 DOI: 10.3390/plants12051157] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Revised: 02/23/2023] [Accepted: 03/01/2023] [Indexed: 06/18/2023]
Abstract
Durum wheat landraces represent a genetic resource for the identification and isolation of new valuable genes and alleles, useful to increase the crop adaptability to climate change. Several durum wheat landraces, all denominated "Rogosija", were extensively cultivated in the Western Balkan Peninsula until the first half of the 20th century. Within the conservation program of the Montenegro Plant Gene Bank, these landraces were collected, but without being characterized. The main goal of this study was to estimate the genetic diversity of the "Rogosija collection" consisting of 89 durum accessions, using 17 morphological descriptors and the 25K Illumina single nucleotide polymorphism (SNP) array. The genetic structure analysis of the Rogosija collection showed two distinguished clusters localized in two different Montenegro eco-geographic micro-areas, characterized by continental Mediterranean climate and maritime Mediterranean climate. Data suggest that these clusters could be composed of two different Balkan durum landrace collections evolved in two different eco-geographic micro-areas. Moreover, the origin of Balkan durum landraces is discussed.
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Affiliation(s)
- Ana Velimirović
- Biotechnical Faculty Podgorica, University of Montenegro, Mihaila Lalića 15, 81000 Podgorica, Montenegro
| | - Zoran Jovović
- Biotechnical Faculty Podgorica, University of Montenegro, Mihaila Lalića 15, 81000 Podgorica, Montenegro
| | - Dragan Perović
- Federal Research Centre for Cultivated Plants, Institute for Resistance Research and Stress Tolerance, Julius Kuehn-Institute, Erwin-Baur-Strasse 27, 06484 Quedlinburg, Germany
| | - Heike Lehnert
- Federal Research Centre for Cultivated Plants, Institute for Biosafety in Plant Biotechnology, Julius Kuehn-Institute, Erwin-Baur-Strasse 27, 06484 Quedlinburg, Germany
| | - Sanja Mikić
- Institute of Field and Vegetable Crops, Maksima Gorkog 30, 21101 Novi Sad, Serbia
| | - Dragan Mandić
- Agricultural Institute of Republika Srpska, Knjaza Miloša 17, 78000 Banja Luka, Republika Srpska, Bosnia and Herzegovina
| | - Novo Pržulj
- Faculty of Agriculture, University of Banjaluka, Bulevar vojvode P. Bojovića 1a, 78000 Banja Luka, Republika Srpska, Bosnia and Herzegovina
| | - Giacomo Mangini
- Institute of Biosciences and Bioresources, National Research Council (IBBR-CNR), Via Amendola 165/A, 70126 Bari, Italy
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Wittern L, Steed G, Taylor LJ, Ramirez DC, Pingarron-Cardenas G, Gardner K, Greenland A, Hannah MA, Webb AAR. Wheat EARLY FLOWERING 3 affects heading date without disrupting circadian oscillations. PLANT PHYSIOLOGY 2023; 191:1383-1403. [PMID: 36454669 PMCID: PMC9922389 DOI: 10.1093/plphys/kiac544] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Revised: 09/23/2022] [Accepted: 11/29/2022] [Indexed: 05/26/2023]
Abstract
Plant breeders have indirectly selected for variation at circadian-associated loci in many of the world's major crops, when breeding to increase yield and improve crop performance. Using an eight-parent Multiparent Advanced Generation Inter-Cross (MAGIC) population, we investigated how variation in circadian clock-associated genes contributes to the regulation of heading date in UK and European winter wheat (Triticum aestivum) varieties. We identified homoeologues of EARLY FLOWERING 3 (ELF3) as candidates for the Earliness per se (Eps) D1 and B1 loci under field conditions. We then confirmed a single-nucleotide polymorphism within the coding region of TaELF3-B1 as a candidate polymorphism underlying the Eps-B1 locus. We found that a reported deletion at the Eps-D1 locus encompassing TaELF3-D1 is, instead, an allele that lies within an introgression region containing an inversion relative to the Chinese Spring D genome. Using Triticum turgidum cv. Kronos carrying loss-of-function alleles of TtELF3, we showed that ELF3 regulates heading, with loss of a single ELF3 homoeologue sufficient to alter heading date. These studies demonstrated that ELF3 forms part of the circadian oscillator; however, the loss of all homoeologues was required to affect circadian rhythms. Similarly, loss of functional LUX ARRHYTHMO (LUX) in T. aestivum, an orthologue of a protein partner of Arabidopsis (Arabidopsis thaliana) ELF3, severely disrupted circadian rhythms. ELF3 and LUX transcripts are not co-expressed at dusk, suggesting that the structure of the wheat circadian oscillator might differ from that of Arabidopsis. Our demonstration that alterations to ELF3 homoeologues can affect heading date separately from effects on the circadian oscillator suggests a role for ELF3 in cereal photoperiodic responses that could be selected for without pleiotropic deleterious alterations to circadian rhythms.
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29
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Wang R, Xing S, Bourke PM, Qi X, Lin M, Esselink D, Arens P, Voorrips RE, Visser RG, Sun L, Zhong Y, Gu H, Li Y, Li S, Maliepaard C, Fang J. Development of a 135K SNP genotyping array for Actinidia arguta and its applications for genetic mapping and QTL analysis in kiwifruit. PLANT BIOTECHNOLOGY JOURNAL 2023; 21:369-380. [PMID: 36333116 PMCID: PMC9884011 DOI: 10.1111/pbi.13958] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Revised: 10/22/2022] [Accepted: 10/31/2022] [Indexed: 05/11/2023]
Abstract
Kiwifruit (Actinidia spp) is a woody, perennial and deciduous vine. In this genus, there are multiple ploidy levels but the main cultivated cultivars are polyploid. Despite the availability of many genomic resources in kiwifruit, SNP genotyping is still a challenge given these different levels of polyploidy. Recent advances in SNP array technologies have offered a high-throughput genotyping platform for genome-wide DNA polymorphisms. In this study, we developed a high-density SNP genotyping array to facilitate genetic studies and breeding applications in kiwifruit. SNP discovery was performed by genome-wide DNA sequencing of 40 kiwifruit genotypes. The identified SNPs were stringently filtered for sequence quality, predicted conversion performance and distribution over the available Actinidia chinensis genome. A total of 134 729 unique SNPs were put on the array. The array was evaluated by genotyping 400 kiwifruit individuals. We performed a multidimensional scaling analysis to assess the diversity of kiwifruit germplasm, showing that the array was effective to distinguish kiwifruit accessions. Using a tetraploid F1 population, we constructed an integrated linkage map covering 3060.9 cM across 29 linkage groups and performed QTL analysis for the sex locus that has been identified on Linkage Group 3 (LG3) in Actinidia arguta. Finally, our dataset presented evidence of tetrasomic inheritance with partial preferential pairing in A. arguta. In conclusion, we developed and evaluated a 135K SNP genotyping array for kiwifruit. It has the advantage of a comprehensive design that can be an effective tool in genetic studies and breeding applications in this high-value crop.
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Affiliation(s)
- Ran Wang
- Zhengzhou Fruit Research InstituteChinese Academy of Agricultural SciencesZhengzhouChina
- Plant BreedingWageningen University & ResearchWageningenThe Netherlands
| | - Siyuan Xing
- Animal Breeding and GenomicsWageningen University & ResearchWageningenThe Netherlands
| | - Peter M. Bourke
- Plant BreedingWageningen University & ResearchWageningenThe Netherlands
| | - Xiuquan Qi
- Zhengzhou Fruit Research InstituteChinese Academy of Agricultural SciencesZhengzhouChina
| | - Miaomiao Lin
- Zhengzhou Fruit Research InstituteChinese Academy of Agricultural SciencesZhengzhouChina
| | - Danny Esselink
- Plant BreedingWageningen University & ResearchWageningenThe Netherlands
| | - Paul Arens
- Plant BreedingWageningen University & ResearchWageningenThe Netherlands
| | | | | | - Leiming Sun
- Zhengzhou Fruit Research InstituteChinese Academy of Agricultural SciencesZhengzhouChina
| | - Yunpeng Zhong
- Zhengzhou Fruit Research InstituteChinese Academy of Agricultural SciencesZhengzhouChina
| | - Hong Gu
- Zhengzhou Fruit Research InstituteChinese Academy of Agricultural SciencesZhengzhouChina
| | - Yukuo Li
- Zhengzhou Fruit Research InstituteChinese Academy of Agricultural SciencesZhengzhouChina
| | - Sikai Li
- Zhengzhou Fruit Research InstituteChinese Academy of Agricultural SciencesZhengzhouChina
| | - Chris Maliepaard
- Plant BreedingWageningen University & ResearchWageningenThe Netherlands
| | - Jinbao Fang
- Zhengzhou Fruit Research InstituteChinese Academy of Agricultural SciencesZhengzhouChina
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30
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Xiang M, Liu S, Wang X, Zhang M, Yan W, Wu J, Wang Q, Li C, Zheng W, He Y, Ge Y, Wang C, Kang Z, Han D, Zeng Q. Development of breeder chip for gene detection and molecular-assisted selection by target sequencing in wheat. MOLECULAR BREEDING : NEW STRATEGIES IN PLANT IMPROVEMENT 2023; 43:13. [PMID: 37313130 PMCID: PMC10248658 DOI: 10.1007/s11032-023-01359-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Accepted: 02/03/2023] [Indexed: 06/15/2023]
Abstract
Wheat is an essential food crop and its high and stable yield is suffering from great challenges due to the limitations of current breeding technology and various stresses. Accelerating molecularly assisted stress-resistance breeding is critical. Through a meta-analysis of published loci in wheat over the last two decades, we selected 60 loci with main breeding objectives, high heritability, and reliable genotyping, such as stress resistance, yield, plant height, and resistance to spike germination. Then, using genotyping by target sequencing (GBTS) technology, we developed a liquid phase chip based on 101 functional or closely linked markers. The genotyping of 42 loci was confirmed in an extensive collection of Chinese wheat cultivars, indicating that the chip can be used in molecular-assisted selection (MAS) for target breeding goals. Besides, we can perform the preliminary parentage analysis with the genotype data. The most significant contribution of this work lies in translating a large number of molecular markers into a viable chip and providing reliable genotypes. Breeders can quickly screen germplasm resources, parental breeding materials, and intermediate materials for the presence of excellent allelic variants using the genotyping data by this chip, which is high throughput, convenient, reliable, and cost-efficient. Supplementary Information The online version contains supplementary material available at 10.1007/s11032-023-01359-3.
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Affiliation(s)
- Mingjie Xiang
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100 Shaanxi China
| | - Shengjie Liu
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100 Shaanxi China
| | - Xiaoting Wang
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100 Shaanxi China
| | - Mingming Zhang
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100 Shaanxi China
| | - Weiyi Yan
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Plant Protection, Northwest A&F University, Yangling, 712100 Shaanxi China
| | - Jianhui Wu
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100 Shaanxi China
| | - Qilin Wang
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100 Shaanxi China
| | - Chunlian Li
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100 Shaanxi China
| | - Weijun Zheng
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100 Shaanxi China
| | - Yilin He
- MolBreeding Biotechnology Co., Ltd., Shijiazhuang, 050035 Hebei China
| | - Yunxia Ge
- MolBreeding Biotechnology Co., Ltd., Shijiazhuang, 050035 Hebei China
| | - Changfa Wang
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100 Shaanxi China
| | - Zhensheng Kang
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Plant Protection, Northwest A&F University, Yangling, 712100 Shaanxi China
- Yangling Seed Industry Innovation Center, Yangling, 712100 Shaanxi China
| | - Dejun Han
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100 Shaanxi China
| | - Qingdong Zeng
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Plant Protection, Northwest A&F University, Yangling, 712100 Shaanxi China
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Mapping of QTLs and Screening Candidate Genes Associated with the Ability of Sugarcane Tillering and Ratooning. Int J Mol Sci 2023; 24:ijms24032793. [PMID: 36769121 PMCID: PMC9917849 DOI: 10.3390/ijms24032793] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Revised: 01/20/2023] [Accepted: 01/29/2023] [Indexed: 02/05/2023] Open
Abstract
The processes of sugarcane tillering and ratooning, which directly affect the yield of plant cane and ratoon, are of vital importance to the population establishment and the effective stalk number per unit area. In the present study, the phenotypic data of 285 F1 progenies from a cross of sugarcane varieties YT93-159 × ROC22 were collected in eight environments, which consisted of plant cane and ratoon cultivated in three different ecological sites. The broad sense heritability (H2) of the tillering and the ratoon sprouting was 0.64 and 0.63, respectively, indicating that they were middle to middle-high heritable traits, and there is a significantly positive correlation between the two traits. Furthermore, a total of 26 quantitative trait loci (QTLs) related to the tillering ability and 11 QTLs associated with the ratooning ability were mapped on two high-quality genetic maps derived from a 100K SNP chip, and their phenotypic variance explained (PVE) ranged from 4.27-25.70% and 6.20-13.54%, respectively. Among them, four consistent QTLs of qPCTR-R9, qPCTR-Y28, qPCTR-Y60/qRSR-Y60 and PCTR-Y8-1/qRSR-Y8 were mapped in two environments, of which, qPCTR-Y8-1/qRSR-Y8 had the PVEs of 11.90% in the plant cane and 7.88% in the ratoon. Furthermore, a total of 25 candidate genes were identified in the interval of the above four consistent QTLs and four major QTLs of qPCTR-Y8-1, qPCTR-Y8-2, qRSR-R51 and qRSR-Y43-2, with the PVEs from 11.73-25.70%. All these genes were associated with tillering, including eight transcription factors (TFs), while 15 of them were associated with ratooning, of which there were five TFs. These QTLs and genes can provide a scientific reference for genetic improvement of tillering and ratooning traits in sugarcane.
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Broccanello C, Bellin D, DalCorso G, Furini A, Taranto F. Genetic approaches to exploit landraces for improvement of Triticum turgidum ssp. durum in the age of climate change. FRONTIERS IN PLANT SCIENCE 2023; 14:1101271. [PMID: 36778704 PMCID: PMC9911883 DOI: 10.3389/fpls.2023.1101271] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Accepted: 01/09/2023] [Indexed: 06/18/2023]
Abstract
Addressing the challenges of climate change and durum wheat production is becoming an important driver for food and nutrition security in the Mediterranean area, where are located the major producing countries (Italy, Spain, France, Greece, Morocco, Algeria, Tunisia, Turkey, and Syria). One of the emergent strategies, to cope with durum wheat adaptation, is the exploration and exploitation of the existing genetic variability in landrace populations. In this context, this review aims to highlight the important role of durum wheat landraces as a useful genetic resource to improve the sustainability of Mediterranean agroecosystems, with a focus on adaptation to environmental stresses. We described the most recent molecular techniques and statistical approaches suitable for the identification of beneficial genes/alleles related to the most important traits in landraces and the development of molecular markers for marker-assisted selection. Finally, we outline the state of the art about landraces genetic diversity and signature of selection, already identified from these accessions, for adaptability to the environment.
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Affiliation(s)
| | - Diana Bellin
- Department of Biotechnology, University of Verona, Verona, Italy
| | | | - Antonella Furini
- Department of Biotechnology, University of Verona, Verona, Italy
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Sehgal D, Dhakate P, Ambreen H, Shaik KHB, Rathan ND, Anusha NM, Deshmukh R, Vikram P. Wheat Omics: Advancements and Opportunities. PLANTS (BASEL, SWITZERLAND) 2023; 12:426. [PMID: 36771512 PMCID: PMC9919419 DOI: 10.3390/plants12030426] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Revised: 12/07/2022] [Accepted: 12/14/2022] [Indexed: 06/18/2023]
Abstract
Plant omics, which includes genomics, transcriptomics, metabolomics and proteomics, has played a remarkable role in the discovery of new genes and biomolecules that can be deployed for crop improvement. In wheat, great insights have been gleaned from the utilization of diverse omics approaches for both qualitative and quantitative traits. Especially, a combination of omics approaches has led to significant advances in gene discovery and pathway investigations and in deciphering the essential components of stress responses and yields. Recently, a Wheat Omics database has been developed for wheat which could be used by scientists for further accelerating functional genomics studies. In this review, we have discussed various omics technologies and platforms that have been used in wheat to enhance the understanding of the stress biology of the crop and the molecular mechanisms underlying stress tolerance.
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Affiliation(s)
- Deepmala Sehgal
- International Maize and Wheat Improvement Center (CIMMYT), El Batán, Texcoco 56237, Mexico
- Syngenta, Jealott’s Hill International Research Centre, Bracknell, Berkshire RG42 6EY, UK
| | - Priyanka Dhakate
- National Institute of Plant Genome Research, Aruna Asaf Ali Marg, New Delhi 110076, India
| | - Heena Ambreen
- School of Life Sciences, University of Sussex, Brighton BN1 9RH, UK
| | - Khasim Hussain Baji Shaik
- Faculty of Agriculture Sciences, Georg-August-Universität, Wilhelmsplatz 1, 37073 Göttingen, Germany
| | - Nagenahalli Dharmegowda Rathan
- Indian Agricultural Research Institute (ICAR-IARI), New Delhi 110012, India
- Corteva Agriscience, Hyderabad 502336, Telangana, India
| | | | - Rupesh Deshmukh
- Department of Biotechnology, Central University of Haryana, Mahendragarh 123031, Haryana, India
| | - Prashant Vikram
- Bioseed Research India Ltd., Hyderabad 5023324, Telangana, India
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Zhao L, Zheng Y, Wang Y, Wang S, Wang T, Wang C, Chen Y, Zhang K, Zhang N, Dong Z, Chen F. A HST1-like gene controls tiller angle through regulating endogenous auxin in common wheat. PLANT BIOTECHNOLOGY JOURNAL 2023; 21:122-135. [PMID: 36128872 PMCID: PMC9829390 DOI: 10.1111/pbi.13930] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Revised: 09/01/2022] [Accepted: 09/15/2022] [Indexed: 05/29/2023]
Abstract
Tiller angle is one of the most important agronomic traits and one key factor for wheat ideal plant architecture, which can both increase photosynthetic efficiency and greatly enhance grain yield. Here, a deacetylase HST1-like (TaHST1L) gene controlling wheat tiller angle was identified by the combination of a genome-wide association study (GWAS) and bulked segregant analysis (BSA). Ethyl methane sulfonate (EMS)-mutagenized tetraploid wheat lines with the premature stop codon of TaHST1L exhibited significantly smaller tiller angles than the wild type. TaHST1L-overexpressing (OE) plants exhibited significantly larger tiller angles and increased tiller numbers in both winter and spring wheat, while TaHST1L-silenced RNAi plants displayed significantly smaller tiller angles and decreased tiller numbers. Moreover, TaHST1L strongly interacted with TaIAA17 and inhibited its expression at the protein level, and thus possibly improved the content of endogenous auxin in the basal tissue of tillers. The transcriptomics and metabolomics results indicated that TaHST1L might change plant architecture by mediating auxin signal transduction and regulating endogenous auxin levels. In addition, a 242-bp insertion/deletion (InDel) in the TaHST1L-A1 promoter altered transcriptional activity and TaHST1L-A1b allele with the 242-bp insertion widened the tiller angle of TaHST1L-OE transgenic rice plants. Wheat varieties with TaHST1L-A1b allele possessed the increased tiller angle and grain yield. Further analysis in wheat and its progenitors indicated that the 242-bp InDel possibly originated from wild emmer and was strongly domesticated in the current varieties. Therefore, TaHST1L involved in the auxin signalling pathway showed the big potential to improve wheat yield by controlling plant architecture.
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Affiliation(s)
- Lei Zhao
- National Key Laboratory of Wheat and Maize Crop Science / CIMMYT‐China Wheat and Maize Joint Research Center /Agronomy CollegeHenan Agricultural UniversityZhengzhouChina
| | - Yueting Zheng
- National Key Laboratory of Wheat and Maize Crop Science / CIMMYT‐China Wheat and Maize Joint Research Center /Agronomy CollegeHenan Agricultural UniversityZhengzhouChina
| | - Ying Wang
- National Key Laboratory of Wheat and Maize Crop Science / CIMMYT‐China Wheat and Maize Joint Research Center /Agronomy CollegeHenan Agricultural UniversityZhengzhouChina
| | - Shasha Wang
- National Key Laboratory of Wheat and Maize Crop Science / CIMMYT‐China Wheat and Maize Joint Research Center /Agronomy CollegeHenan Agricultural UniversityZhengzhouChina
| | - Tongzhu Wang
- National Key Laboratory of Wheat and Maize Crop Science / CIMMYT‐China Wheat and Maize Joint Research Center /Agronomy CollegeHenan Agricultural UniversityZhengzhouChina
| | - Canguan Wang
- National Key Laboratory of Wheat and Maize Crop Science / CIMMYT‐China Wheat and Maize Joint Research Center /Agronomy CollegeHenan Agricultural UniversityZhengzhouChina
| | - Yue Chen
- National Key Laboratory of Wheat and Maize Crop Science / CIMMYT‐China Wheat and Maize Joint Research Center /Agronomy CollegeHenan Agricultural UniversityZhengzhouChina
| | - Kunpu Zhang
- National Key Laboratory of Wheat and Maize Crop Science / CIMMYT‐China Wheat and Maize Joint Research Center /Agronomy CollegeHenan Agricultural UniversityZhengzhouChina
| | - Ning Zhang
- National Key Laboratory of Wheat and Maize Crop Science / CIMMYT‐China Wheat and Maize Joint Research Center /Agronomy CollegeHenan Agricultural UniversityZhengzhouChina
| | - Zhongdong Dong
- National Key Laboratory of Wheat and Maize Crop Science / CIMMYT‐China Wheat and Maize Joint Research Center /Agronomy CollegeHenan Agricultural UniversityZhengzhouChina
| | - Feng Chen
- National Key Laboratory of Wheat and Maize Crop Science / CIMMYT‐China Wheat and Maize Joint Research Center /Agronomy CollegeHenan Agricultural UniversityZhengzhouChina
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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: 1] [Impact Index Per Article: 0.5] [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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Gohar S, Sajjad M, Zulfiqar S, Liu J, Wu J, Rahman MU. Domestication of newly evolved hexaploid wheat—A journey of wild grass to cultivated wheat. Front Genet 2022; 13:1022931. [PMID: 36263418 PMCID: PMC9574122 DOI: 10.3389/fgene.2022.1022931] [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: 08/19/2022] [Accepted: 09/12/2022] [Indexed: 11/13/2022] Open
Abstract
Domestication of wheat started with the dawn of human civilization. Since then, improvement in various traits including resistance to diseases, insect pests, saline and drought stresses, grain yield, and quality were improved through selections by early farmers and then planned hybridization after the discovery of Mendel’s laws. In the 1950s, genetic variability was created using mutagens followed by the selection of superior mutants. Over the last 3 decades, research was focused on developing superior hybrids, initiating marker-assisted selection and targeted breeding, and developing genetically modified wheat to improve the grain yield, tolerance to drought, salinity, terminal heat and herbicide, and nutritive quality. Acceptability of genetically modified wheat by the end-user remained a major hurdle in releasing into the environment. Since the beginning of the 21st century, changing environmental conditions proved detrimental to achieving sustainability in wheat production particularly in developing countries. It is suggested that high-tech phenotyping assays and genomic procedures together with speed breeding procedures will be instrumental in achieving food security beyond 2050.
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Affiliation(s)
- Sasha Gohar
- Plant Genomics and Molecular Breeding Laboratory, National Institute for Biotechnology and Genetic Engineering, Faisalabad, Pakistan
- Department of Biotechnology, Pakistan Institute of Engineering and Applied Sciences (PIEAS), Islamabad, Pakistan
| | - Muhammad Sajjad
- Department of Biosciences, COMSATS University Islamabad, Islamabad, Pakistan
| | - Sana Zulfiqar
- Plant Genomics and Molecular Breeding Laboratory, National Institute for Biotechnology and Genetic Engineering, Faisalabad, Pakistan
- Department of Biotechnology, Pakistan Institute of Engineering and Applied Sciences (PIEAS), Islamabad, Pakistan
| | - Jiajun Liu
- State Key Laboratory of Crop Biology, Shandong Agricultural University, Tai'an, Shandong, China
| | - Jiajie Wu
- State Key Laboratory of Crop Biology, Shandong Agricultural University, Tai'an, Shandong, China
- *Correspondence: Jiajie Wu, ; Mehboob-ur- Rahman,
| | - Mehboob-ur- Rahman
- Plant Genomics and Molecular Breeding Laboratory, National Institute for Biotechnology and Genetic Engineering, Faisalabad, Pakistan
- Department of Biotechnology, Pakistan Institute of Engineering and Applied Sciences (PIEAS), Islamabad, Pakistan
- *Correspondence: Jiajie Wu, ; Mehboob-ur- Rahman,
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Zhang X, Li J, Ge Y, Guan H, Li G, Zhang S, Wang X, Li X, Chang Z, Zhang P, Jia J, Liu C. Molecular cytogenetic characterization of a new wheat- Thinopyrum intermedium homoeologous group-6 chromosome disomic substitution line with resistance to leaf rust and stripe rust. FRONTIERS IN PLANT SCIENCE 2022; 13:1006281. [PMID: 36147230 PMCID: PMC9486089 DOI: 10.3389/fpls.2022.1006281] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Accepted: 08/12/2022] [Indexed: 06/16/2023]
Abstract
Thinopyrum intermedium (JJJsJsStSt, 2n = 6x = 42), a member of tertiary gene pool of hexaploid wheat (Triticum aestivum L., AABBDD, 2n = 6x = 42), provides several beneficial genes for wheat improvement. In this study, line CH51 was developed from the BC1F8 progeny of a partial wheat-Th. intermedium amphiploid TAI8335 (2n = 56) and wheat cultivar (cv.) Jintai 170. Somatic metaphase chromosome counting showed that CH51 had stable 42 chromosomes. Genomic in situ hybridization (GISH) analysis showed that CH51 had 40 wheat chromosomes and two Th. intermedium chromosomes involving translocation between Js- and St-genome chromosomes. Non-denaturing fluorescence in situ hybridization (ND-FISH) analysis revealed that CH51 lacked a pair of wheat chromosome 6B. Wheat 55K SNP array analysis verified that chromosome 6B had the highest percentage of missing SNP loci in both CH51 and Chinese Spring (CS) nullisomic 6B-tetrasomic 6D (CS-N6BT6D) and had the highest percentage of polymorphic SNP loci between CH51 and cv. Jintai 170. We identified that CH51 was a wheat-Th. intermedium T6StS.6JsL (6B) disomic substitution line. Disease resistance assessment showed that CH51 exhibited high levels of resistance to the prevalent Chinese leaf rust and stripe rust races in the field. Therefore, the newly developed line CH51 can be utilized as a potential germplasm in wheat disease resistance breeding.
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Affiliation(s)
- Xiaojun Zhang
- College of Agriculture, Shanxi Agricultural University, Taiyuan, Shanxi, China
| | - Jianbo Li
- College of Agriculture, Shanxi Agricultural University, Taiyuan, Shanxi, China
- Crop Research Institute, Shandong Academy of Agricultural Sciences, Jinan, Shandong, China
- Plant Breeding Institute, School of Life and Environmental Sciences, The University of Sydney, Sydney, NSW, Australia
| | - Yudi Ge
- School of Life Sciences, Shanxi University, Taiyuan, Shanxi, China
| | - Haixia Guan
- Plant Breeding Institute, School of Life and Environmental Sciences, The University of Sydney, Sydney, NSW, Australia
| | - Guangrong Li
- School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, China
| | - Shuwei Zhang
- College of Agriculture, Shanxi Agricultural University, Taiyuan, Shanxi, China
| | - Xiaolu Wang
- Crop Research Institute, Shandong Academy of Agricultural Sciences, Jinan, Shandong, China
| | - Xin Li
- College of Agriculture, Shanxi Agricultural University, Taiyuan, Shanxi, China
| | - Zhijian Chang
- College of Agriculture, Shanxi Agricultural University, Taiyuan, Shanxi, China
| | - Peng Zhang
- Plant Breeding Institute, School of Life and Environmental Sciences, The University of Sydney, Sydney, NSW, Australia
| | - Juqing Jia
- College of Agriculture, Shanxi Agricultural University, Taiyuan, Shanxi, China
| | - Cheng Liu
- Crop Research Institute, Shandong Academy of Agricultural Sciences, Jinan, Shandong, China
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Liu X, Xu Z, Feng B, Zhou Q, Ji G, Guo S, Liao S, Lin D, Fan X, Wang T. Quantitative trait loci identification and breeding value estimation of grain weight-related traits based on a new wheat 50K single nucleotide polymorphism array-derived genetic map. FRONTIERS IN PLANT SCIENCE 2022; 13:967432. [PMID: 36110352 PMCID: PMC9468616 DOI: 10.3389/fpls.2022.967432] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/12/2022] [Accepted: 08/04/2022] [Indexed: 06/01/2023]
Abstract
Mining novel and less utilized thousand grain weight (TGW) related genes are useful for improving wheat yield. In this study, a recombinant inbred line population from a cross between Zhongkemai 138 (ZKM138, high TGW) and Chuanmai 44 (CM44, low TGW) was used to construct a new Wheat 50K SNP array-derived genetic map that spanned 1,936.59 cM and contained 4, 139 markers. Based on this map, ninety-one quantitative trait loci (QTL) were detected for eight grain-related traits in six environments. Among 58 QTLs, whose superior alleles were contributed by ZKM138, QTgw.cib-6A was a noticeable major stable QTL and was also highlighted by bulked segregant analysis with RNA sequencing (BSR-Seq). It had a pyramiding effect on TGW enhancement but no significant trade-off effect on grain number per spike or tiller number, with two other QTLs (QTgw.cib-2A.2 and QTgw.cib-6D), possibly explaining the excellent grain performance of ZKM138. After comparison with known loci, QTgw.cib-6A was deduced to be a novel locus that differed from nearby TaGW2 and TaBT1. Seven simple sequence repeat (SSR) and thirty-nine kompetitive allele-specific PCR (KASP) markers were finally developed to narrow the candidate interval of QTgw.cib-6A to 4.1 Mb. Only six genes in this interval were regarded as the most likely candidate genes. QTgw.cib-6A was further validated in different genetic backgrounds and presented 88.6% transmissibility of the ZKM138-genotype and a 16.4% increase of TGW in ZKM138 derivatives. And the geographic pattern of this locus revealed that its superior allele is present in only 6.47% of 433 Chinese modern wheat varieties, indicating its potential contribution to further high-yield breeding.
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Affiliation(s)
- Xiaofeng Liu
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Zhibin Xu
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
| | - Bo Feng
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
| | - Qiang Zhou
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
| | - Guangsi Ji
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Shaodan Guo
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
| | - Simin Liao
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Dian Lin
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Xiaoli Fan
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
| | - Tao Wang
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
- Innovative Academy for Seed Design, Chinese Academy of Sciences, Beijing, China
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Geyer M, Mohler V, Hartl L. Genetics of the Inverse Relationship between Grain Yield and Grain Protein Content in Common Wheat. PLANTS 2022; 11:plants11162146. [PMID: 36015449 PMCID: PMC9413592 DOI: 10.3390/plants11162146] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Revised: 08/05/2022] [Accepted: 08/16/2022] [Indexed: 12/01/2022]
Abstract
Grain protein content (GPC) is one of the most important criteria to determine the quality of common wheat (Triticum aestivum). One of the major obstacles for bread wheat production is the negative correlation between GPC and grain yield (GY). Previous studies demonstrated that the deviation from this inverse relationship is highly heritable. However, little is known about the genetics controlling these deviations in common wheat. To fill this gap, we performed quantitative trait locus (QTL) analysis for GY, GPC, and four derived GY-GPC indices using an eight-way multiparent advanced generation intercross population comprising 394 lines. Interval mapping was conducted using phenotypic data from up to nine environments and genotypic data from a 20k single-nucleotide polymorphism array. The four indices were highly heritable (0.76–0.88) and showed distinct correlations to GY and GPC. Interval mapping revealed that GY, GPC, and GY-GPC indices were controlled by 6, 12, and 12 unique QTL, of which each explained only a small amount of phenotypic variance (R2 ≤ 10%). Ten of the 12 index QTL were independent of loci affecting GY and GPC. QTL regions harboured several candidate genes, including Rht-1, WAPO-A1, TaTEF-7A, and NRT2.6-7A. The study confirmed the usefulness of indices to mitigate the inverse GY-GPC relationship in breeding, though the selection method should reflect their polygenic inheritance.
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40
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Tanin MJ, Saini DK, Sandhu KS, Pal N, Gudi S, Chaudhary J, Sharma A. Consensus genomic regions associated with multiple abiotic stress tolerance in wheat and implications for wheat breeding. Sci Rep 2022; 12:13680. [PMID: 35953529 PMCID: PMC9372038 DOI: 10.1038/s41598-022-18149-0] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Accepted: 08/05/2022] [Indexed: 12/03/2022] Open
Abstract
In wheat, a meta-analysis was performed using previously identified QTLs associated with drought stress (DS), heat stress (HS), salinity stress (SS), water-logging stress (WS), pre-harvest sprouting (PHS), and aluminium stress (AS) which predicted a total of 134 meta-QTLs (MQTLs) that involved at least 28 consistent and stable MQTLs conferring tolerance to five or all six abiotic stresses under study. Seventy-six MQTLs out of the 132 physically anchored MQTLs were also verified with genome-wide association studies. Around 43% of MQTLs had genetic and physical confidence intervals of less than 1 cM and 5 Mb, respectively. Consequently, 539 genes were identified in some selected MQTLs providing tolerance to 5 or all 6 abiotic stresses. Comparative analysis of genes underlying MQTLs with four RNA-seq based transcriptomic datasets unravelled a total of 189 differentially expressed genes which also included at least 11 most promising candidate genes common among different datasets. The promoter analysis showed that the promoters of these genes include many stress responsiveness cis-regulatory elements, such as ARE, MBS, TC-rich repeats, As-1 element, STRE, LTR, WRE3, and WUN-motif among others. Further, some MQTLs also overlapped with as many as 34 known abiotic stress tolerance genes. In addition, numerous ortho-MQTLs among the wheat, maize, and rice genomes were discovered. These findings could help with fine mapping and gene cloning, as well as marker-assisted breeding for multiple abiotic stress tolerances in wheat.
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Affiliation(s)
- Mohammad Jafar Tanin
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India.
| | - Dinesh Kumar Saini
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Karansher Singh Sandhu
- Department of Crop and Soil Sciences, Washington State University, Pullman, WA, 99163, USA
| | - Neeraj Pal
- Department of Molecular Biology and Genetic Engineering, G. B. Pant University of Agriculture and Technology, Pantnagar, Uttarakhand, India
| | - Santosh Gudi
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Jyoti Chaudhary
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, Uttar Pradesh, India
| | - Achla Sharma
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
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41
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Tanin MJ, Saini DK, Sandhu KS, Pal N, Gudi S, Chaudhary J, Sharma A. Consensus genomic regions associated with multiple abiotic stress tolerance in wheat and implications for wheat breeding. Sci Rep 2022; 12:13680. [PMID: 35953529 DOI: 10.1101/2022.06.24.497482] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Accepted: 08/05/2022] [Indexed: 05/20/2023] Open
Abstract
In wheat, a meta-analysis was performed using previously identified QTLs associated with drought stress (DS), heat stress (HS), salinity stress (SS), water-logging stress (WS), pre-harvest sprouting (PHS), and aluminium stress (AS) which predicted a total of 134 meta-QTLs (MQTLs) that involved at least 28 consistent and stable MQTLs conferring tolerance to five or all six abiotic stresses under study. Seventy-six MQTLs out of the 132 physically anchored MQTLs were also verified with genome-wide association studies. Around 43% of MQTLs had genetic and physical confidence intervals of less than 1 cM and 5 Mb, respectively. Consequently, 539 genes were identified in some selected MQTLs providing tolerance to 5 or all 6 abiotic stresses. Comparative analysis of genes underlying MQTLs with four RNA-seq based transcriptomic datasets unravelled a total of 189 differentially expressed genes which also included at least 11 most promising candidate genes common among different datasets. The promoter analysis showed that the promoters of these genes include many stress responsiveness cis-regulatory elements, such as ARE, MBS, TC-rich repeats, As-1 element, STRE, LTR, WRE3, and WUN-motif among others. Further, some MQTLs also overlapped with as many as 34 known abiotic stress tolerance genes. In addition, numerous ortho-MQTLs among the wheat, maize, and rice genomes were discovered. These findings could help with fine mapping and gene cloning, as well as marker-assisted breeding for multiple abiotic stress tolerances in wheat.
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Affiliation(s)
- Mohammad Jafar Tanin
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India.
| | - Dinesh Kumar Saini
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Karansher Singh Sandhu
- Department of Crop and Soil Sciences, Washington State University, Pullman, WA, 99163, USA
| | - Neeraj Pal
- Department of Molecular Biology and Genetic Engineering, G. B. Pant University of Agriculture and Technology, Pantnagar, Uttarakhand, India
| | - Santosh Gudi
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Jyoti Chaudhary
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, Uttar Pradesh, India
| | - Achla Sharma
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
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Qu X, Li C, Liu H, Liu J, Luo W, Xu Q, Tang H, Mu Y, Deng M, Pu Z, Ma J, Jiang Q, Chen G, Qi P, Jiang Y, Wei Y, Zheng Y, Lan X, Ma J. Quick mapping and characterization of a co-located kernel length and thousand-kernel weight-related QTL in wheat. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2022; 135:2849-2860. [PMID: 35804167 DOI: 10.1007/s00122-022-04154-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/18/2021] [Accepted: 06/16/2022] [Indexed: 06/15/2023]
Abstract
A co-located KL and TKW-related QTL with no negative effect on PH and AD was rapidly identified using BSA and wheat 660 K SNP array. Its effect was validated in a panel of 218 wheat accessions. Kernel length (KL) and thousand-kernel weight (TKW) of wheat (Triticum aestivum L.) contribute significantly to kernel yield. In the present study, a recombinant inbred line (RIL) population derived from the cross between the wheat line S849-8 with larger kernels and more spikelets per spike and the line SY95-71 was developed. Further, of both the bulked segregant analysis (BSA) and the wheat 660 K single nucleotide polymorphism (SNP) array were used to rapidly identify genomic regions for kernel-related traits from this RIL population. Kompetitive Allele Specific PCR markers were further developed in the SNP-enriched region on the 2D chromosome to construct a genetic map. Both QKL.sicau-SSY-2D for KL and QTKW.sicau-SSY-2D for TKW were identified at multiple environments on chromosome arm 2DL. These two QTLs explained 9.68-23.02% and 6.73-18.32% of the phenotypic variation, respectively. The effects of this co-located QTL were successfully verified in a natural population consisting of 218 Sichuan wheat accessions. Interestingly, the major QTL was significantly and positively correlated with spike length, but did not negatively affect spikelet number per spike (SNS), plant height, or anthesis date. These results indicated that it is possible to synchronously improve kernel weight and SNS by using this QTL. Additionally, several genes associated with kernel development and filling rate were predicted and sequenced in the QTL-containing physical intervals of reference genomes of 'Chinese spring' and Aegilops tauschii. Collectively, these results provide a QTL with great breeding potential and its linked markers which should be helpful for fine mapping and molecular breeding.
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Affiliation(s)
- Xiangru Qu
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, 611130, China
| | - Cong Li
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, 611130, China
| | - Hang Liu
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, 611130, China
| | - Jiajun Liu
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, 611130, China
| | - Wei Luo
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, 611130, China
| | - Qiang Xu
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, 611130, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, 611130, China
| | - Huaping Tang
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, 611130, China
| | - Yang Mu
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, 611130, China
| | - Mei Deng
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, 611130, China
| | - Zhien Pu
- College of Agronomy, Sichuan Agricultural University, Chengdu, 611130, China
| | - Jun Ma
- College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
| | - Qiantao Jiang
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, 611130, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, 611130, China
| | - Guoyue Chen
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, 611130, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, 611130, China
| | - Pengfei Qi
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, 611130, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, 611130, China
| | - Yunfeng Jiang
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, 611130, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, 611130, China
| | - Yuming Wei
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, 611130, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, 611130, China
| | - Youliang Zheng
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, 611130, China
| | - Xiujin Lan
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, 611130, China
| | - Jian Ma
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, 611130, China.
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, 611130, China.
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Genievskaya Y, Pecchioni N, Laidò G, Anuarbek S, Rsaliyev A, Chudinov V, Zatybekov A, Turuspekov Y, Abugalieva S. Genome-Wide Association Study of Leaf Rust and Stem Rust Seedling and Adult Resistances in Tetraploid Wheat Accessions Harvested in Kazakhstan. PLANTS (BASEL, SWITZERLAND) 2022; 11:plants11151904. [PMID: 35893608 PMCID: PMC9329756 DOI: 10.3390/plants11151904] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Revised: 07/13/2022] [Accepted: 07/20/2022] [Indexed: 05/05/2023]
Abstract
Leaf rust (LR) and stem rust (SR) are diseases increasingly impacting wheat production worldwide. Fungal pathogens producing rust diseases in wheat may cause yield losses of up to 50−60%. One of the most effective methods for preventing such losses is the development of resistant cultivars with high yield potential. This goal can be achieved through complex breeding studies, including the identification of key genetic factors controlling rust disease resistance. The objective of this study was to identify sources of tetraploid wheat resistance to LR and SR races, both at the seedling growth stage in the greenhouse and at the adult plant stage in field experiments, under the conditions of the North Kazakhstan region. A panel consisting of 193 tetraploid wheat accessions was used in a genome-wide association study (GWAS) for the identification of quantitative trait loci (QTLs) associated with LR and SR resistance, using 16,425 polymorphic single-nucleotide polymorphism (SNP) markers in the seedling and adult stages of plant development. The investigated panel consisted of seven tetraploid subspecies (Triticum turgidum ssp. durum, ssp. turanicum, ssp. turgidum, ssp. polonicum, ssp. carthlicum, ssp. dicoccum, and ssp. dicoccoides). The GWAS, based on the phenotypic evaluation of the tetraploid collection’s reaction to the two rust species at the seedling (in the greenhouse) and adult (in the field) stages, revealed 38 QTLs (p < 0.001), comprising 17 for LR resistance and 21 for SR resistance. Ten QTLs were associated with the reaction to LR at the seedling stage, while six QTLs were at the adult plant stage and one QTL was at both the seedling and adult stages. Eleven QTLs were associated with SR response at the seedling stage, while nine QTLs were at the adult plant stage and one QTL was at both the seedling and adult stages. A comparison of these results with previous LR and SR studies indicated that 11 of the 38 QTLs are presumably novel loci. The QTLs identified in this work can potentially be used for marker-assisted selection of tetraploid and hexaploid wheat for the breeding of new LR- and SR-resistant cultivars.
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Affiliation(s)
- Yuliya Genievskaya
- Laboratory of Molecular Genetics, Institute of Plant Biology and Biotechnology, Almaty 050040, Kazakhstan; (Y.G.); (S.A.); (A.Z.); (Y.T.)
- Faculty of Biology and Biotechnology, Al-Farabi Kazakh National University, Almaty 050040, Kazakhstan
| | - Nicola Pecchioni
- Research Centre for Cereal and Industrial Crops, 71122 Foggia, Italy; (N.P.); (G.L.)
| | - Giovanni Laidò
- Research Centre for Cereal and Industrial Crops, 71122 Foggia, Italy; (N.P.); (G.L.)
| | - Shynar Anuarbek
- Laboratory of Molecular Genetics, Institute of Plant Biology and Biotechnology, Almaty 050040, Kazakhstan; (Y.G.); (S.A.); (A.Z.); (Y.T.)
| | - Aralbek Rsaliyev
- Laboratory of Phytosanitary Safety, Research Institute of Biological Safety Problems, Gvardeisky 080409, Kazakhstan;
| | - Vladimir Chudinov
- Breeding Department, Karabalyk Agricultural Experimental Station, Nauchnoe 110908, Kazakhstan;
| | - Alibek Zatybekov
- Laboratory of Molecular Genetics, Institute of Plant Biology and Biotechnology, Almaty 050040, Kazakhstan; (Y.G.); (S.A.); (A.Z.); (Y.T.)
| | - Yerlan Turuspekov
- Laboratory of Molecular Genetics, Institute of Plant Biology and Biotechnology, Almaty 050040, Kazakhstan; (Y.G.); (S.A.); (A.Z.); (Y.T.)
- Faculty of Biology and Biotechnology, Al-Farabi Kazakh National University, Almaty 050040, Kazakhstan
| | - Saule Abugalieva
- Laboratory of Molecular Genetics, Institute of Plant Biology and Biotechnology, Almaty 050040, Kazakhstan; (Y.G.); (S.A.); (A.Z.); (Y.T.)
- Faculty of Biology and Biotechnology, Al-Farabi Kazakh National University, Almaty 050040, Kazakhstan
- Correspondence: ; Tel.: +7-727-394-8006
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Pal N, Jan I, Saini DK, Kumar K, Kumar A, Sharma PK, Kumar S, Balyan HS, Gupta PK. Meta-QTLs for multiple disease resistance involving three rusts in common wheat (Triticum aestivum L.). TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2022; 135:2385-2405. [PMID: 35699741 DOI: 10.1007/s00122-022-04119-7] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Accepted: 04/28/2022] [Indexed: 05/20/2023]
Abstract
In wheat, multiple disease resistance meta-QTLs (MDR-MQTLs) and underlying candidate genes for the three rusts were identified which may prove useful for development of resistant cultivars. Rust diseases in wheat are a major threat to global food security. Therefore, development of multiple disease-resistant cultivars (resistant to all three rusts) is a major goal in all wheat breeding programs worldwide. In the present study, meta-QTLs and candidate genes for multiple disease resistance (MDR) involving all three rusts were identified using 152 individual QTL mapping studies for resistance to leaf rust (LR), stem rust (SR), and yellow rust (YR). From these 152 studies, a total of 1,146 QTLs for resistance to three rusts were retrieved, which included 368 QTLs for LR, 291 QTLs for SR, and 487 QTLs for YR. Of these 1,146 QTLs, only 718 QTLs could be projected onto the consensus map saturated with 2, 34,619 markers. Meta-analysis of the projected QTLs resulted in the identification of 86 MQTLs, which included 71 MDR-MQTLs. Ten of these MDR-MQTLs were referred to as the 'Breeders' MQTLs'. Seventy-eight of the 86 MQTLs could also be anchored to the physical map of the wheat genome, and 54 MQTLs were validated by marker-trait associations identified during earlier genome-wide association studies. Twenty MQTLs (including 17 MDR-MQTLs) identified in the present study were co-localized with 44 known R genes. In silico expression analysis allowed identification of several differentially expressed candidate genes (DECGs) encoding proteins carrying different domains including the following: NBS-LRR, WRKY domains, F-box domains, sugar transporters, transferases, etc. The introgression of these MDR loci into high-yielding cultivars should prove useful for developing high yielding cultivars with resistance to all the three rusts.
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Affiliation(s)
- Neeraj Pal
- Department of Molecular Biology and Genetic Engineering, G. B. Pant University of Agriculture and Technology, Pantnagar, Uttrakhand, 263145, India
| | - Irfat Jan
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, 250004, India
| | - Dinesh Kumar Saini
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, 141004, India
| | - Kuldeep Kumar
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, 250004, India
| | - Anuj Kumar
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, 250004, India
| | - P K Sharma
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, 250004, India
| | - Sundip Kumar
- Department of Molecular Biology and Genetic Engineering, G. B. Pant University of Agriculture and Technology, Pantnagar, Uttrakhand, 263145, India
| | - H S Balyan
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, 250004, India
| | - P K Gupta
- Department of Genetics and Plant Breeding, Ch. Charan Singh University, Meerut, 250004, India.
- Murdoch's Centre for Crop & Food Innovation, Murdoch University, Murdoch, Perth, WA 6150, Australia.
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Desjardins SD, Simmonds J, Guterman I, Kanyuka K, Burridge AJ, Tock AJ, Sanchez-Moran E, Franklin FCH, Henderson IR, Edwards KJ, Uauy C, Higgins JD. FANCM promotes class I interfering crossovers and suppresses class II non-interfering crossovers in wheat meiosis. Nat Commun 2022; 13:3644. [PMID: 35752733 PMCID: PMC9233680 DOI: 10.1038/s41467-022-31438-6] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Accepted: 06/17/2022] [Indexed: 11/09/2022] Open
Abstract
FANCM suppresses crossovers in plants by unwinding recombination intermediates. In wheat, crossovers are skewed toward the chromosome ends, thus limiting generation of novel allelic combinations. Here, we observe that FANCM maintains the obligate crossover in tetraploid and hexaploid wheat, thus ensuring that every chromosome pair exhibits at least one crossover, by localizing class I crossover protein HEI10 at pachytene. FANCM also suppresses class II crossovers that increased 2.6-fold in fancm msh5 quadruple mutants. These data are consistent with a role for FANCM in second-end capture of class I designated crossover sites, whilst FANCM is also required to promote formation of non-crossovers. In hexaploid wheat, genetic mapping reveals that crossovers increase by 31% in fancm compared to wild type, indicating that fancm could be an effective tool to accelerate breeding. Crossover rate differences in fancm correlate with wild type crossover distributions, suggesting that chromatin may influence the recombination landscape in similar ways in both wild type and fancm. The FANCM helicase functions in limiting crossovers (COs) by unwinding inter-homolog repair intermediates. Here, the authors generate null mutants of fancm in tetraploid and hexaploid wheat and show that FANCM promotes class I interfering COs and suppresses class II noninterfering COs in wheat meiosis.
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Affiliation(s)
- Stuart D Desjardins
- Department of Genetics and Genome Biology, Adrian Building, University of Leicester, University Road, Leicester, LE1 7RH, UK
| | - James Simmonds
- Department of Crop Genetics, John Innes Centre, Norwich, NR4 7UH, UK
| | - Inna Guterman
- Department of Genetics and Genome Biology, Adrian Building, University of Leicester, University Road, Leicester, LE1 7RH, UK
| | - Kostya Kanyuka
- NIAB, 93 Lawrence Weaver Road, Cambridge, CB3 0LE, UK.,Biointeractions and Crop Protection, Rothamsted Research, Harpenden, AL5 2JQ, UK
| | - Amanda J Burridge
- Life Sciences Building, University of Bristol, 24 Tyndall Avenue, Bristol, BS8 1TQ, UK
| | - Andrew J Tock
- Department of Plant Sciences, University of Cambridge, Downing Street, Cambridge, CB2 3EA, UK
| | | | - F Chris H Franklin
- School of Biosciences, University of Birmingham, Birmingham, B15 2TT, UK
| | - Ian R Henderson
- Department of Plant Sciences, University of Cambridge, Downing Street, Cambridge, CB2 3EA, UK
| | - Keith J Edwards
- Life Sciences Building, University of Bristol, 24 Tyndall Avenue, Bristol, BS8 1TQ, UK
| | - Cristobal Uauy
- Department of Crop Genetics, John Innes Centre, Norwich, NR4 7UH, UK
| | - James D Higgins
- Department of Genetics and Genome Biology, Adrian Building, University of Leicester, University Road, Leicester, LE1 7RH, UK.
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Gudi S, Saini DK, Singh G, Halladakeri P, Kumar P, Shamshad M, Tanin MJ, Singh S, Sharma A. Unravelling consensus genomic regions associated with quality traits in wheat using meta-analysis of quantitative trait loci. PLANTA 2022; 255:115. [PMID: 35508739 DOI: 10.1007/s00425-022-03904-4] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Accepted: 04/26/2022] [Indexed: 05/03/2023]
Abstract
Meta-analysis in wheat for three major quality traits identified 110 meta-QTL (MQTL) with reduced confidence interval (CI). Five GWAS validated MQTL (viz., 1A.1, 1B.2, 3B.4, 5B.2, and 6B.2), each involving more than 20 initial QTL and reduced CI (95%) (< 2 cM), were selected for quality breeding programmes. Functional characterization including candidate gene mining and expression analysis discovered 44 high confidence candidate genes associated with quality traits. A meta-analysis of quantitative trait loci (QTL) associated with dough rheology properties, nutritional traits, and processing quality traits was conducted in wheat. For this purpose, as many as 2458 QTL were collected from 50 interval mapping studies published during 2013-2020. Of the total QTL, 1126 QTL were projected onto the consensus map saturated with 249,603 markers which led to the identification of 110 meta-QTL (MQTL). These MQTL exhibited an 18.84-fold reduction in the average CI compared to the average CI of the initial QTL (ranging from 14.87 to 95.55 cM with an average of 40.35 cM). Of the 110, 108 MQTL were physically anchored to the wheat reference genome, including 51 MQTL verified with marker-trait associations (MTAs) reported from earlier genome-wide association studies. Candidate gene (CG) mining allowed the identification of 2533 unique gene models from the MQTL regions. In-silico expression analysis discovered 439 differentially expressed gene models with > 2 transcripts per million expressions in grains and related tissues, which also included 44 high-confidence CGs involved in the various cellular and biochemical processes related to quality traits. Nine functionally characterized wheat genes associated with grain protein content, high-molecular-weight glutenin, and starch synthase enzymes were also found to be co-localized with some of the MQTL. Synteny analysis between wheat and rice MQTL regions identified 23 wheat MQTL syntenic to 16 rice MQTL associated with quality traits. Furthermore, 64 wheat orthologues of 30 known rice genes were detected in 44 MQTL regions. Markers flanking the MQTL identified in the present study can be used for marker-assisted breeding and as fixed effects in the genomic selection models for improving the prediction accuracy during quality breeding. Wheat orthologues of rice genes and other CGs available from MQTLs can be promising targets for further functional validation and to better understand the molecular mechanism underlying the quality traits in wheat.
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Affiliation(s)
- Santosh Gudi
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India.
| | - Dinesh Kumar Saini
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Gurjeet Singh
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Priyanka Halladakeri
- Department of Genetics and Plant Breeding, Anand Agricultural University, Gujarat, India
| | - Pradeep Kumar
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Mohammad Shamshad
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Mohammad Jafar Tanin
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Satinder Singh
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Achla Sharma
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
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Shi X, Zhou Z, Li W, Qin M, Yang P, Hou J, Huang F, Lei Z, Wu Z, Wang J. Genome-wide association study reveals the genetic architecture for calcium accumulation in grains of hexaploid wheat (Triticum aestivum L.). BMC PLANT BIOLOGY 2022; 22:229. [PMID: 35508960 PMCID: PMC9066855 DOI: 10.1186/s12870-022-03602-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Accepted: 04/15/2022] [Indexed: 05/31/2023]
Abstract
BACKGROUND Hexaploid wheat (Triticum aestivum L.) is a leading cereal crop worldwide. Understanding the mechanism of calcium (Ca) accumulation in wheat is important to reduce the risk of human micronutrient deficiencies. However, the mechanisms of Ca accumulation in wheat grain are only partly understood. RESULTS Here, a genome-wide association study (GWAS) was performed to dissect the genetic basis of Ca accumulation in wheat grain using an association population consisting of 207 varieties, with phenotypic data from three locations. In total, 11 non-redundant genetic loci associated with Ca concentration were identified and they explained, on average, 9.61-26.93% of the phenotypic variation. Cultivars containing more superior alleles had increased grain Ca concentrations. Notably, four non-redundant loci were mutually verified by different statistical models in at least two environments, indicating their stability across different environments. Four putative candidate genes linked to Ca accumulation were revealed from the stable genetic loci. Among them, two genes, associated with the stable genetic loci on chromosomes 4A (AX-108912427) and 3B (AX-110922471), encode the subunits of V-type Proton ATPase (TraesCS4A02G428900 and TraesCS3B02G241000), which annotated as the typical generators of a proton gradient that might be involved in Ca homeostasis in wheat grain. CONCLUSION To identify genetic loci associated with Ca accumulation, we conducted GWAS on Ca concentrations and detected 11 genetic loci; whereas four genetic loci were stable across different environments. A genetic loci hot spot exists at the end of chromosome 4A and associated with the putative candidate gene TraesCS4A02G428900. The candidate gene TraesCS4A02G428900 encodes V-type proton ATPase subunit e and highly expressed in wheat grains, and it possibly involved in Ca accumulation. This study increases our understanding of the genetic architecture of Ca accumulation in wheat grains, which is potentially helpful for wheat Ca biofortification pyramid breeding.
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Affiliation(s)
- Xia Shi
- Henan Institute of Crop Molecular Breeding, Henan Academy of Agricultural Sciences, Zhengzhou, 450002, China
| | - Zhengfu Zhou
- Henan Institute of Crop Molecular Breeding, Henan Academy of Agricultural Sciences, Zhengzhou, 450002, China
| | - Wenxu Li
- Henan Institute of Crop Molecular Breeding, Henan Academy of Agricultural Sciences, Zhengzhou, 450002, China
| | - Maomao Qin
- Henan Institute of Crop Molecular Breeding, Henan Academy of Agricultural Sciences, Zhengzhou, 450002, China
| | - Pan Yang
- Henan Institute of Crop Molecular Breeding, Henan Academy of Agricultural Sciences, Zhengzhou, 450002, China
| | - Jinna Hou
- Henan Institute of Crop Molecular Breeding, Henan Academy of Agricultural Sciences, Zhengzhou, 450002, China
| | - Fangfang Huang
- College of Life Sciences, Henan Agricultural University, Zhengzhou, 450002, China
| | - Zhensheng Lei
- Henan Institute of Crop Molecular Breeding, Henan Academy of Agricultural Sciences, Zhengzhou, 450002, China.
- The Shennong Laboratory, Zhengzhou, 450002, Henan, China.
- College of Chemistry and Environment Engineering, Pingdingshan University, Pingdingshan, 467000, China.
| | - Zhengqing Wu
- Henan Institute of Crop Molecular Breeding, Henan Academy of Agricultural Sciences, Zhengzhou, 450002, China.
| | - Jiansheng Wang
- College of Chemistry and Environment Engineering, Pingdingshan University, Pingdingshan, 467000, China.
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Shewry PR, Lovegrove A, Wingen LU, Griffiths S. Opinion Exploiting genomics to improve the benefits of wheat: Prospects and limitations. J Cereal Sci 2022; 105:103444. [PMID: 35712025 PMCID: PMC9106566 DOI: 10.1016/j.jcs.2022.103444] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Revised: 02/14/2022] [Accepted: 02/25/2022] [Indexed: 11/17/2022]
Abstract
The last decade has seen an explosion in wheat genomic resources. These include genomic sequences and high-density molecular markers. Genomic resources allow the exploitation of novel genetic variation. Genomic resources are being used to improve the health benefits of wheat.
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Affiliation(s)
- Peter R. Shewry
- Rothamsted Research, Harpenden, Hertfordshire, AL5 2JQ, UK
- Corresponding author.
| | | | - Luzie U. Wingen
- John Innes Centre, Norwich Research Park, Colney Lane, Norwich, NR4 7UH, UK
| | - Simon Griffiths
- John Innes Centre, Norwich Research Park, Colney Lane, Norwich, NR4 7UH, UK
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49
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Burridge AJ, Winfield MO, Wilkinson PA, Przewieslik-Allen AM, Edwards KJ, Barker GLA. The Use and Limitations of Exome Capture to Detect Novel Variation in the Hexaploid Wheat Genome. FRONTIERS IN PLANT SCIENCE 2022; 13:841855. [PMID: 35498663 PMCID: PMC9039655 DOI: 10.3389/fpls.2022.841855] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Accepted: 02/28/2022] [Indexed: 06/14/2023]
Abstract
The bread wheat (Triticum aestivum) pangenome is a patchwork of variable regions, including translocations and introgressions from progenitors and wild relatives. Although a large number of these have been documented, it is likely that many more remain unknown. To map these variable regions and make them more traceable in breeding programs, wheat accessions need to be genotyped or sequenced. The wheat genome is large and complex and consequently, sequencing efforts are often targeted through exome capture. In this study, we employed exome capture prior to sequencing 12 wheat varieties; 10 elite T. aestivum cultivars and two T. aestivum landrace accessions. Sequence coverage across chromosomes was greater toward distal regions of chromosome arms and lower in centromeric regions, reflecting the capture probe distribution which itself is determined by the known telomere to centromere gene gradient. Superimposed on this general pattern, numerous drops in sequence coverage were observed. Several of these corresponded with reported introgressions. Other drops in coverage could not be readily explained and may point to introgressions that have not, to date, been documented.
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Affiliation(s)
| | - Mark O. Winfield
- School of Life Sciences, University of Bristol, Bristol, United Kingdom
| | - Paul A. Wilkinson
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, United Kingdom
| | | | - Keith J. Edwards
- School of Life Sciences, University of Bristol, Bristol, United Kingdom
| | - Gary L. A. Barker
- School of Life Sciences, University of Bristol, Bristol, United Kingdom
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50
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Leigh FJ, Wright TIC, Horsnell RA, Dyer S, Bentley AR. Progenitor species hold untapped diversity for potential climate-responsive traits for use in wheat breeding and crop improvement. Heredity (Edinb) 2022; 128:291-303. [PMID: 35383318 PMCID: PMC9076643 DOI: 10.1038/s41437-022-00527-z] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2020] [Revised: 03/13/2022] [Accepted: 03/15/2022] [Indexed: 01/07/2023] Open
Abstract
Climate change will have numerous impacts on crop production worldwide necessitating a broadening of the germplasm base required to source and incorporate novel traits. Major variation exists in crop progenitor species for seasonal adaptation, photosynthetic characteristics, and root system architecture. Wheat is crucial for securing future food and nutrition security and its evolutionary history and progenitor diversity offer opportunities to mine favourable functional variation in the primary gene pool. Here we provide a review of the status of characterisation of wheat progenitor variation and the potential to use this knowledge to inform the use of variation in other cereal crops. Although significant knowledge of progenitor variation has been generated, we make recommendations for further work required to systematically characterise underlying genetics and physiological mechanisms and propose steps for effective use in breeding. This will enable targeted exploitation of useful variation, supported by the growing portfolio of genomics and accelerated breeding approaches. The knowledge and approaches generated are also likely to be useful across wider crop improvement.
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Affiliation(s)
- Fiona J Leigh
- The John Bingham Laboratory, NIAB, 93 Lawrence Weaver Road, Cambridge, CB3 0LE, UK
| | - Tally I C Wright
- The John Bingham Laboratory, NIAB, 93 Lawrence Weaver Road, Cambridge, CB3 0LE, UK
| | - Richard A Horsnell
- The John Bingham Laboratory, NIAB, 93 Lawrence Weaver Road, Cambridge, CB3 0LE, UK
| | - Sarah Dyer
- The John Bingham Laboratory, NIAB, 93 Lawrence Weaver Road, Cambridge, CB3 0LE, UK.,European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Alison R Bentley
- The John Bingham Laboratory, NIAB, 93 Lawrence Weaver Road, Cambridge, CB3 0LE, UK. .,International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico.
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