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Zhou Y, Bai S, Li H, Sun G, Zhang D, Ma F, Zhao X, Nie F, Li J, Chen L, Lv L, Zhu L, Fan R, Ge Y, Shaheen A, Guo G, Zhang Z, Ma J, Liang H, Qiu X, Hu J, Sun T, Hou J, Xu H, Xue S, Jiang W, Huang J, Li S, Zou C, Song CP. Introgressing the Aegilops tauschii genome into wheat as a basis for cereal improvement. NATURE PLANTS 2021; 7:774-786. [PMID: 34045708 DOI: 10.1038/s41477-021-00934-w] [Citation(s) in RCA: 52] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Accepted: 04/30/2021] [Indexed: 05/04/2023]
Abstract
Increasing crop production is necessary to feed the world's expanding population, and crop breeders often utilize genetic variations to improve crop yield and quality. However, the narrow diversity of the wheat D genome seriously restricts its selective breeding. A practical solution is to exploit the genomic variations of Aegilops tauschii via introgression. Here, we established a rapid introgression platform for transferring the overall genetic variations of A. tauschii to elite wheats, thereby enriching the wheat germplasm pool. To accelerate the process, we assembled four new reference genomes, resequenced 278 accessions of A. tauschii and constructed the variation landscape of this wheat progenitor species. Genome comparisons highlighted diverse functional genes or novel haplotypes with potential applications in wheat improvement. We constructed the core germplasm of A. tauschii, including 85 accessions covering more than 99% of the species' overall genetic variations. This was crossed with elite wheat cultivars to generate an A. tauschii-wheat synthetic octoploid wheat (A-WSOW) pool. Laboratory and field analysis with two examples of the introgression lines confirmed its great potential for wheat breeding. Our high-quality reference genomes, genomic variation landscape of A. tauschii and the A-WSOW pool provide valuable resources to facilitate gene discovery and breeding in wheat.
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Affiliation(s)
- Yun Zhou
- State Key Laboratory of Crop Stress Adaptation and Improvement, School of Life Sciences, Henan University, Kaifeng, China
| | - Shenglong Bai
- State Key Laboratory of Crop Stress Adaptation and Improvement, School of Life Sciences, Henan University, Kaifeng, China
| | - Hao Li
- State Key Laboratory of Crop Stress Adaptation and Improvement, School of Life Sciences, Henan University, Kaifeng, China
| | - Guiling Sun
- State Key Laboratory of Crop Stress Adaptation and Improvement, School of Life Sciences, Henan University, Kaifeng, China
| | - Dale Zhang
- State Key Laboratory of Crop Stress Adaptation and Improvement, School of Life Sciences, Henan University, Kaifeng, China
| | - Feifei Ma
- State Key Laboratory of Crop Stress Adaptation and Improvement, School of Life Sciences, Henan University, Kaifeng, China
| | - Xinpeng Zhao
- State Key Laboratory of Crop Stress Adaptation and Improvement, School of Life Sciences, Henan University, Kaifeng, China
| | - Fang Nie
- State Key Laboratory of Crop Stress Adaptation and Improvement, School of Life Sciences, Henan University, Kaifeng, China
| | - Jingyao Li
- State Key Laboratory of Crop Stress Adaptation and Improvement, School of Life Sciences, Henan University, Kaifeng, China
| | - Liyang Chen
- Novogene Bioinformatics Institute, Beijing, China
| | - Linlin Lv
- State Key Laboratory of Crop Stress Adaptation and Improvement, School of Life Sciences, Henan University, Kaifeng, China
| | - Lele Zhu
- State Key Laboratory of Crop Stress Adaptation and Improvement, School of Life Sciences, Henan University, Kaifeng, China
| | - Ruixiao Fan
- State Key Laboratory of Crop Stress Adaptation and Improvement, School of Life Sciences, Henan University, Kaifeng, China
| | - Yifan Ge
- State Key Laboratory of Crop Stress Adaptation and Improvement, School of Life Sciences, Henan University, Kaifeng, China
| | - Aaqib Shaheen
- State Key Laboratory of Crop Stress Adaptation and Improvement, School of Life Sciences, Henan University, Kaifeng, China
| | - Guanghui Guo
- State Key Laboratory of Crop Stress Adaptation and Improvement, School of Life Sciences, Henan University, Kaifeng, China
| | - Zhen Zhang
- State Key Laboratory of Crop Stress Adaptation and Improvement, School of Life Sciences, Henan University, Kaifeng, China
| | - Jianchao Ma
- State Key Laboratory of Crop Stress Adaptation and Improvement, School of Life Sciences, Henan University, Kaifeng, China
| | - Huihui Liang
- State Key Laboratory of Crop Stress Adaptation and Improvement, School of Life Sciences, Henan University, Kaifeng, China
| | - Xiaolong Qiu
- State Key Laboratory of Crop Stress Adaptation and Improvement, School of Life Sciences, Henan University, Kaifeng, China
| | - Jiamin Hu
- State Key Laboratory of Crop Stress Adaptation and Improvement, School of Life Sciences, Henan University, Kaifeng, China
| | - Ting Sun
- State Key Laboratory of Crop Stress Adaptation and Improvement, School of Life Sciences, Henan University, Kaifeng, China
| | - Jingyi Hou
- State Key Laboratory of Crop Stress Adaptation and Improvement, School of Life Sciences, Henan University, Kaifeng, China
| | - Hongxing Xu
- State Key Laboratory of Crop Stress Adaptation and Improvement, School of Life Sciences, Henan University, Kaifeng, China
| | - Shulin Xue
- State Key Laboratory of Crop Stress Adaptation and Improvement, School of Life Sciences, Henan University, Kaifeng, China
| | - Wenkai Jiang
- Novogene Bioinformatics Institute, Beijing, China
| | - Jinling Huang
- State Key Laboratory of Crop Stress Adaptation and Improvement, School of Life Sciences, Henan University, Kaifeng, China
- Department of Biology, East Carolina University, Greenville, NC, USA
| | - Suoping Li
- State Key Laboratory of Crop Stress Adaptation and Improvement, School of Life Sciences, Henan University, Kaifeng, China
| | - Changsong Zou
- State Key Laboratory of Crop Stress Adaptation and Improvement, School of Life Sciences, Henan University, Kaifeng, China.
| | - Chun-Peng Song
- State Key Laboratory of Crop Stress Adaptation and Improvement, School of Life Sciences, Henan University, Kaifeng, China.
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Akhunov ED, Akhunova AR, Anderson OD, Anderson JA, Blake N, Clegg MT, Coleman-Derr D, Conley EJ, Crossman CC, Deal KR, Dubcovsky J, Gill BS, Gu YQ, Hadam J, Heo H, Huo N, Lazo GR, Luo MC, Ma YQ, Matthews DE, McGuire PE, Morrell PL, Qualset CO, Renfro J, Tabanao D, Talbert LE, Tian C, Toleno DM, Warburton ML, You FM, Zhang W, Dvorak J. Nucleotide diversity maps reveal variation in diversity among wheat genomes and chromosomes. BMC Genomics 2010; 11:702. [PMID: 21156062 PMCID: PMC3022916 DOI: 10.1186/1471-2164-11-702] [Citation(s) in RCA: 138] [Impact Index Per Article: 9.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2010] [Accepted: 12/14/2010] [Indexed: 01/19/2023] Open
Abstract
BACKGROUND A genome-wide assessment of nucleotide diversity in a polyploid species must minimize the inclusion of homoeologous sequences into diversity estimates and reliably allocate individual haplotypes into their respective genomes. The same requirements complicate the development and deployment of single nucleotide polymorphism (SNP) markers in polyploid species. We report here a strategy that satisfies these requirements and deploy it in the sequencing of genes in cultivated hexaploid wheat (Triticum aestivum, genomes AABBDD) and wild tetraploid wheat (Triticum turgidum ssp. dicoccoides, genomes AABB) from the putative site of wheat domestication in Turkey. Data are used to assess the distribution of diversity among and within wheat genomes and to develop a panel of SNP markers for polyploid wheat. RESULTS Nucleotide diversity was estimated in 2114 wheat genes and was similar between the A and B genomes and reduced in the D genome. Within a genome, diversity was diminished on some chromosomes. Low diversity was always accompanied by an excess of rare alleles. A total of 5,471 SNPs was discovered in 1791 wheat genes. Totals of 1,271, 1,218, and 2,203 SNPs were discovered in 488, 463, and 641 genes of wheat putative diploid ancestors, T. urartu, Aegilops speltoides, and Ae. tauschii, respectively. A public database containing genome-specific primers, SNPs, and other information was constructed. A total of 987 genes with nucleotide diversity estimated in one or more of the wheat genomes was placed on an Ae. tauschii genetic map, and the map was superimposed on wheat deletion-bin maps. The agreement between the maps was assessed. CONCLUSIONS In a young polyploid, exemplified by T. aestivum, ancestral species are the primary source of genetic diversity. Low effective recombination due to self-pollination and a genetic mechanism precluding homoeologous chromosome pairing during polyploid meiosis can lead to the loss of diversity from large chromosomal regions. The net effect of these factors in T. aestivum is large variation in diversity among genomes and chromosomes, which impacts the development of SNP markers and their practical utility. Accumulation of new mutations in older polyploid species, such as wild emmer, results in increased diversity and its more uniform distribution across the genome.
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Affiliation(s)
- Eduard D Akhunov
- Department of Plant Sciences, University of California, Davis, CA 95616, USA
- Department of Plant Pathology, KSU, Manhattan, KS 66506, USA
| | - Alina R Akhunova
- Department of Plant Sciences, University of California, Davis, CA 95616, USA
- Department of Plant Pathology, KSU, Manhattan, KS 66506, USA
| | - Olin D Anderson
- Genomics and Gene Discovery Unit, USDA/ARS Western Regional Research Center, Albany, CA 94710, USA
| | - James A Anderson
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN 55108, USA
| | - Nancy Blake
- Department of Plant Sciences and Plant Pathology, Montana State University, Bozeman, MT 59717, USA
| | - Michael T Clegg
- Department of Ecology and Evolutionary Biology, University of California, Irvine, CA 92697, USA
| | - Devin Coleman-Derr
- Genomics and Gene Discovery Unit, USDA/ARS Western Regional Research Center, Albany, CA 94710, USA
| | - Emily J Conley
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN 55108, USA
| | - Curt C Crossman
- Genomics and Gene Discovery Unit, USDA/ARS Western Regional Research Center, Albany, CA 94710, USA
| | - Karin R Deal
- Department of Plant Sciences, University of California, Davis, CA 95616, USA
| | - Jorge Dubcovsky
- Department of Plant Sciences, University of California, Davis, CA 95616, USA
| | - Bikram S Gill
- Department of Plant Pathology, Kansas State University, Manhattan KS 66506, USA
| | - Yong Q Gu
- Genomics and Gene Discovery Unit, USDA/ARS Western Regional Research Center, Albany, CA 94710, USA
| | - Jakub Hadam
- Department of Plant Pathology, Kansas State University, Manhattan KS 66506, USA
| | - Hwayoung Heo
- Department of Plant Sciences and Plant Pathology, Montana State University, Bozeman, MT 59717, USA
| | - Naxin Huo
- Genomics and Gene Discovery Unit, USDA/ARS Western Regional Research Center, Albany, CA 94710, USA
| | - Gerard R Lazo
- Genomics and Gene Discovery Unit, USDA/ARS Western Regional Research Center, Albany, CA 94710, USA
| | - Ming-Cheng Luo
- Department of Plant Sciences, University of California, Davis, CA 95616, USA
| | - Yaqin Q Ma
- Department of Plant Sciences, University of California, Davis, CA 95616, USA
- Department of Botany and Plant Sciences, University of California, Riverside, CA 92521, USA
| | | | - Patrick E McGuire
- Department of Plant Sciences, University of California, Davis, CA 95616, USA
| | - Peter L Morrell
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN 55108, USA
| | - Calvin O Qualset
- Department of Plant Sciences, University of California, Davis, CA 95616, USA
| | - James Renfro
- Genomics and Gene Discovery Unit, USDA/ARS Western Regional Research Center, Albany, CA 94710, USA
| | - Dindo Tabanao
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN 55108, USA
- Philippine Rice Research Institute, Maligaya, Nueva Ecija, Philippines
| | - Luther E Talbert
- Department of Plant Sciences and Plant Pathology, Montana State University, Bozeman, MT 59717, USA
| | - Chao Tian
- Department of Plant Sciences, University of California, Davis, CA 95616, USA
| | - Donna M Toleno
- Department of Ecology and Evolutionary Biology, University of California, Irvine, CA 92697, USA
| | - Marilyn L Warburton
- The International Maize and Wheat Improvement Center (CIMMYT), 06600 Mexico, D.F., Mexico
- Corn Host Plant Research Resistance Unit, USDA/ARS MSU MS 39762, USA
| | - Frank M You
- Department of Plant Sciences, University of California, Davis, CA 95616, USA
| | - Wenjun Zhang
- Department of Plant Sciences, University of California, Davis, CA 95616, USA
| | - Jan Dvorak
- Department of Plant Sciences, University of California, Davis, CA 95616, USA
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3
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Akhunov ED, Akhunova AR, Anderson OD, Anderson JA, Blake N, Clegg MT, Coleman-Derr D, Conley EJ, Crossman CC, Deal KR, Dubcovsky J, Gill BS, Gu YQ, Hadam J, Heo H, Huo N, Lazo GR, Luo MC, Ma YQ, Matthews DE, McGuire PE, Morrell PL, Qualset CO, Renfro J, Tabanao D, Talbert LE, Tian C, Toleno DM, Warburton ML, You FM, Zhang W, Dvorak J. Nucleotide diversity maps reveal variation in diversity among wheat genomes and chromosomes. BMC Genomics 2010. [PMID: 21156062 DOI: 10.1186/1471‐2164‐11‐702] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND A genome-wide assessment of nucleotide diversity in a polyploid species must minimize the inclusion of homoeologous sequences into diversity estimates and reliably allocate individual haplotypes into their respective genomes. The same requirements complicate the development and deployment of single nucleotide polymorphism (SNP) markers in polyploid species. We report here a strategy that satisfies these requirements and deploy it in the sequencing of genes in cultivated hexaploid wheat (Triticum aestivum, genomes AABBDD) and wild tetraploid wheat (Triticum turgidum ssp. dicoccoides, genomes AABB) from the putative site of wheat domestication in Turkey. Data are used to assess the distribution of diversity among and within wheat genomes and to develop a panel of SNP markers for polyploid wheat. RESULTS Nucleotide diversity was estimated in 2114 wheat genes and was similar between the A and B genomes and reduced in the D genome. Within a genome, diversity was diminished on some chromosomes. Low diversity was always accompanied by an excess of rare alleles. A total of 5,471 SNPs was discovered in 1791 wheat genes. Totals of 1,271, 1,218, and 2,203 SNPs were discovered in 488, 463, and 641 genes of wheat putative diploid ancestors, T. urartu, Aegilops speltoides, and Ae. tauschii, respectively. A public database containing genome-specific primers, SNPs, and other information was constructed. A total of 987 genes with nucleotide diversity estimated in one or more of the wheat genomes was placed on an Ae. tauschii genetic map, and the map was superimposed on wheat deletion-bin maps. The agreement between the maps was assessed. CONCLUSIONS In a young polyploid, exemplified by T. aestivum, ancestral species are the primary source of genetic diversity. Low effective recombination due to self-pollination and a genetic mechanism precluding homoeologous chromosome pairing during polyploid meiosis can lead to the loss of diversity from large chromosomal regions. The net effect of these factors in T. aestivum is large variation in diversity among genomes and chromosomes, which impacts the development of SNP markers and their practical utility. Accumulation of new mutations in older polyploid species, such as wild emmer, results in increased diversity and its more uniform distribution across the genome.
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Affiliation(s)
- Eduard D Akhunov
- Department of Plant Sciences, University of California, Davis, CA 95616, USA
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