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Naqvi RZ, Siddiqui HA, Mahmood MA, Najeebullah S, Ehsan A, Azhar M, Farooq M, Amin I, Asad S, Mukhtar Z, Mansoor S, Asif M. Smart breeding approaches in post-genomics era for developing climate-resilient food crops. FRONTIERS IN PLANT SCIENCE 2022; 13:972164. [PMID: 36186056 PMCID: PMC9523482 DOI: 10.3389/fpls.2022.972164] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/17/2022] [Accepted: 08/15/2022] [Indexed: 06/16/2023]
Abstract
Improving the crop traits is highly required for the development of superior crop varieties to deal with climate change and the associated abiotic and biotic stress challenges. Climate change-driven global warming can trigger higher insect pest pressures and plant diseases thus affecting crop production sternly. The traits controlling genes for stress or disease tolerance are economically imperative in crop plants. In this scenario, the extensive exploration of available wild, resistant or susceptible germplasms and unraveling the genetic diversity remains vital for breeding programs. The dawn of next-generation sequencing technologies and omics approaches has accelerated plant breeding by providing the genome sequences and transcriptomes of several plants. The availability of decoded plant genomes offers an opportunity at a glance to identify candidate genes, quantitative trait loci (QTLs), molecular markers, and genome-wide association studies that can potentially aid in high throughput marker-assisted breeding. In recent years genomics is coupled with marker-assisted breeding to unravel the mechanisms to harness better better crop yield and quality. In this review, we discuss the aspects of marker-assisted breeding and recent perspectives of breeding approaches in the era of genomics, bioinformatics, high-tech phonemics, genome editing, and new plant breeding technologies for crop improvement. In nutshell, the smart breeding toolkit in the post-genomics era can steadily help in developing climate-smart future food crops.
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Bayer PE, Petereit J, Durant É, Monat C, Rouard M, Hu H, Chapman B, Li C, Cheng S, Batley J, Edwards D. Wheat Panache: A pangenome graph database representing presence-absence variation across sixteen bread wheat genomes. THE PLANT GENOME 2022; 15:e20221. [PMID: 35644986 DOI: 10.1002/tpg2.20221] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Accepted: 04/11/2022] [Indexed: 06/15/2023]
Abstract
Bread wheat (Triticum aestivum L.) is one of humanity's most important staple crops, characterized by a large and complex genome with a high level of gene presence-absence variation (PAV) between cultivars, hampering genomic approaches for crop improvement. With the growing global population and the increasing impact of climate change on crop yield, there is an urgent need to apply genomic approaches to accelerate wheat breeding. With recent advances in DNA sequencing technology, a growing number of high-quality reference genomes are becoming available, reflecting the genetic content of a diverse range of cultivars. However, information on the presence or absence of genomic regions has been hard to visualize and interrogate because of the size of these genomes and the lack of suitable bioinformatics tools. To address this limitation, we have produced a wheat pangenome graph maintained within an online database to facilitate interrogation and comparison of wheat cultivar genomes. The database allows users to visualize regions of the pangenome to assess PAV between bread wheat genomes.
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Affiliation(s)
- Philipp E Bayer
- School of Biological Sciences, The Univ. of Western Australia, Perth, 6009, Australia
| | - Jakob Petereit
- School of Biological Sciences, The Univ. of Western Australia, Perth, 6009, Australia
| | - Éloi Durant
- DIADE, Univ. of Montpellier, CIRAD, IRD, Montpellier, 34830, France
- Syngenta Seeds S.A.S., 12 chemin de l'Hobit, Saint-Sauveur, 31790, France
- Bioversity International, Parc Scientifique Agropolis II, Montpellier, 34397, France
- French Institute of Bioinformatics (IFB)-South Green Bioinformatics Platform, Bioversity, CIRAD, INRAE, IRD, Montpellier, 34398, France
| | - Cécile Monat
- Syngenta Seeds S.A.S., 12 chemin de l'Hobit, Saint-Sauveur, 31790, France
| | - Mathieu Rouard
- Bioversity International, Parc Scientifique Agropolis II, Montpellier, 34397, France
- French Institute of Bioinformatics (IFB)-South Green Bioinformatics Platform, Bioversity, CIRAD, INRAE, IRD, Montpellier, 34398, France
| | - Haifei Hu
- Western Crop Genetics Alliance, Murdoch Univ., 90 South Street, Murdoch, 6150, Australia
| | - Brett Chapman
- Western Crop Genetics Alliance, Murdoch Univ., 90 South Street, Murdoch, 6150, Australia
| | - Chengdao Li
- Western Crop Genetics Alliance, Murdoch Univ., 90 South Street, Murdoch, 6150, Australia
| | - Shifeng Cheng
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China
| | - Jacqueline Batley
- School of Biological Sciences, The Univ. of Western Australia, Perth, 6009, Australia
| | - David Edwards
- School of Biological Sciences, The Univ. of Western Australia, Perth, 6009, Australia
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3
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Hussain B, Akpınar BA, Alaux M, Algharib AM, Sehgal D, Ali Z, Aradottir GI, Batley J, Bellec A, Bentley AR, Cagirici HB, Cattivelli L, Choulet F, Cockram J, Desiderio F, Devaux P, Dogramaci M, Dorado G, Dreisigacker S, Edwards D, El-Hassouni K, Eversole K, Fahima T, Figueroa M, Gálvez S, Gill KS, Govta L, Gul A, Hensel G, Hernandez P, Crespo-Herrera LA, Ibrahim A, Kilian B, Korzun V, Krugman T, Li Y, Liu S, Mahmoud AF, Morgounov A, Muslu T, Naseer F, Ordon F, Paux E, Perovic D, Reddy GVP, Reif JC, Reynolds M, Roychowdhury R, Rudd J, Sen TZ, Sukumaran S, Ozdemir BS, Tiwari VK, Ullah N, Unver T, Yazar S, Appels R, Budak H. Capturing Wheat Phenotypes at the Genome Level. FRONTIERS IN PLANT SCIENCE 2022; 13:851079. [PMID: 35860541 PMCID: PMC9289626 DOI: 10.3389/fpls.2022.851079] [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: 01/09/2022] [Accepted: 05/19/2022] [Indexed: 06/15/2023]
Abstract
Recent technological advances in next-generation sequencing (NGS) technologies have dramatically reduced the cost of DNA sequencing, allowing species with large and complex genomes to be sequenced. Although bread wheat (Triticum aestivum L.) is one of the world's most important food crops, efficient exploitation of molecular marker-assisted breeding approaches has lagged behind that achieved in other crop species, due to its large polyploid genome. However, an international public-private effort spanning 9 years reported over 65% draft genome of bread wheat in 2014, and finally, after more than a decade culminated in the release of a gold-standard, fully annotated reference wheat-genome assembly in 2018. Shortly thereafter, in 2020, the genome of assemblies of additional 15 global wheat accessions was released. As a result, wheat has now entered into the pan-genomic era, where basic resources can be efficiently exploited. Wheat genotyping with a few hundred markers has been replaced by genotyping arrays, capable of characterizing hundreds of wheat lines, using thousands of markers, providing fast, relatively inexpensive, and reliable data for exploitation in wheat breeding. These advances have opened up new opportunities for marker-assisted selection (MAS) and genomic selection (GS) in wheat. Herein, we review the advances and perspectives in wheat genetics and genomics, with a focus on key traits, including grain yield, yield-related traits, end-use quality, and resistance to biotic and abiotic stresses. We also focus on reported candidate genes cloned and linked to traits of interest. Furthermore, we report on the improvement in the aforementioned quantitative traits, through the use of (i) clustered regularly interspaced short-palindromic repeats/CRISPR-associated protein 9 (CRISPR/Cas9)-mediated gene-editing and (ii) positional cloning methods, and of genomic selection. Finally, we examine the utilization of genomics for the next-generation wheat breeding, providing a practical example of using in silico bioinformatics tools that are based on the wheat reference-genome sequence.
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Affiliation(s)
- Babar Hussain
- Department of Biological Sciences, Middle East Technical University, Ankara, Turkey
- Department of Biotechnology, Faculty of Life Sciences, University of Central Punjab, Lahore, Pakistan
| | | | - Michael Alaux
- Université Paris-Saclay, INRAE, URGI, Versailles, France
| | - Ahmed M. Algharib
- Department of Environment and Bio-Agriculture, Faculty of Agriculture, Al-Azhar University, Cairo, Egypt
| | - Deepmala Sehgal
- International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico
| | - Zulfiqar Ali
- Institute of Plant Breeding and Biotechnology, MNS University of Agriculture, Multan, Pakistan
| | - Gudbjorg I. Aradottir
- Department of Pathology, The National Institute of Agricultural Botany, Cambridge, United Kingdom
| | - Jacqueline Batley
- School of Biological Sciences and Institute of Agriculture, University of Western Australia, Perth, WA, Australia
| | - Arnaud Bellec
- French Plant Genomic Resource Center, INRAE-CNRGV, Castanet Tolosan, France
| | - Alison R. Bentley
- International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico
| | - Halise B. Cagirici
- Crop Improvement and Genetics Research, USDA, Agricultural Research Service, Albany, CA, United States
| | - Luigi Cattivelli
- Council for Agricultural Research and Economics-Research Centre for Genomics and Bioinformatics, Fiorenzuola d’Arda, Italy
| | - Fred Choulet
- French National Research Institute for Agriculture, Food and the Environment, INRAE, GDEC, Clermont-Ferrand, France
| | - James Cockram
- The John Bingham Laboratory, The National Institute of Agricultural Botany, Cambridge, United Kingdom
| | - Francesca Desiderio
- Council for Agricultural Research and Economics-Research Centre for Genomics and Bioinformatics, Fiorenzuola d’Arda, Italy
| | - Pierre Devaux
- Research & Innovation, Florimond Desprez Group, Cappelle-en-Pévèle, France
| | - Munevver Dogramaci
- USDA, Agricultural Research Service, Edward T. Schafer Agricultural Research Center, Fargo, ND, United States
| | - Gabriel Dorado
- Department of Bioquímica y Biología Molecular, Campus Rabanales C6-1-E17, Campus de Excelencia Internacional Agroalimentario (ceiA3), Universidad de Córdoba, Córdoba, Spain
| | | | - David Edwards
- University of Western Australia, Perth, WA, Australia
| | - Khaoula El-Hassouni
- State Plant Breeding Institute, The University of Hohenheim, Stuttgart, Germany
| | - Kellye Eversole
- International Wheat Genome Sequencing Consortium (IWGSC), Bethesda, MD, United States
| | - Tzion Fahima
- Institute of Evolution and Department of Environmental and Evolutionary Biology, University of Haifa, Haifa, Israel
| | - Melania Figueroa
- Commonwealth Scientific and Industrial Research Organization, Agriculture and Food, Canberra, ACT, Australia
| | - Sergio Gálvez
- Department of Languages and Computer Science, ETSI Informática, Campus de Teatinos, Universidad de Málaga, Andalucía Tech, Málaga, Spain
| | - Kulvinder S. Gill
- Department of Crop Science, Washington State University, Pullman, WA, United States
| | - Liubov Govta
- Institute of Evolution and Department of Environmental and Evolutionary Biology, University of Haifa, Haifa, Israel
| | - Alvina Gul
- Atta-ur-Rahman School of Applied Biosciences, National University of Sciences and Technology, Islamabad, Pakistan
| | - Goetz Hensel
- Center of Plant Genome Engineering, Heinrich-Heine-Universität, Düsseldorf, Germany
- Division of Molecular Biology, Centre of Region Haná for Biotechnological and Agriculture Research, Czech Advanced Technology and Research Institute, Palacký University, Olomouc, Czechia
| | - Pilar Hernandez
- Institute for Sustainable Agriculture (IAS-CSIC), Consejo Superior de Investigaciones Científicas (CSIC), Córdoba, Spain
| | | | - Amir Ibrahim
- Crop and Soil Science, Texas A&M University, College Station, TX, United States
| | | | | | - Tamar Krugman
- Institute of Evolution and Department of Environmental and Evolutionary Biology, University of Haifa, Haifa, Israel
| | - Yinghui Li
- Institute of Evolution and Department of Environmental and Evolutionary Biology, University of Haifa, Haifa, Israel
| | - Shuyu Liu
- Crop and Soil Science, Texas A&M University, College Station, TX, United States
| | - Amer F. Mahmoud
- Department of Plant Pathology, Faculty of Agriculture, Assiut University, Assiut, Egypt
| | - Alexey Morgounov
- Food and Agriculture Organization of the United Nations, Riyadh, Saudi Arabia
| | - Tugdem Muslu
- Molecular Biology, Genetics and Bioengineering, Sabanci University, Istanbul, Turkey
| | - Faiza Naseer
- Atta-ur-Rahman School of Applied Biosciences, National University of Sciences and Technology, Islamabad, Pakistan
| | - Frank Ordon
- Institute for Resistance Research and Stress Tolerance, Julius Kühn Institute, Quedlinburg, Germany
| | - Etienne Paux
- French National Research Institute for Agriculture, Food and the Environment, INRAE, GDEC, Clermont-Ferrand, France
| | - Dragan Perovic
- Institute for Resistance Research and Stress Tolerance, Julius Kühn Institute, Quedlinburg, Germany
| | - Gadi V. P. Reddy
- USDA-Agricultural Research Service, Southern Insect Management Research Unit, Stoneville, MS, United States
| | - Jochen Christoph Reif
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany
| | - Matthew Reynolds
- International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico
| | - Rajib Roychowdhury
- Institute of Evolution and Department of Environmental and Evolutionary Biology, University of Haifa, Haifa, Israel
| | - Jackie Rudd
- Crop and Soil Science, Texas A&M University, College Station, TX, United States
| | - Taner Z. Sen
- Crop Improvement and Genetics Research, USDA, Agricultural Research Service, Albany, CA, United States
| | | | | | | | - Naimat Ullah
- Institute of Biological Sciences (IBS), Gomal University, D. I. Khan, Pakistan
| | - Turgay Unver
- Ficus Biotechnology, Ostim Teknopark, Ankara, Turkey
| | - Selami Yazar
- General Directorate of Research, Ministry of Agriculture, Ankara, Turkey
| | | | - Hikmet Budak
- Montana BioAgriculture, Inc., Missoula, MT, United States
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Bayer PE, Gill M, Danilevicz MF, Edwards D. Producing High-Quality Single Nucleotide Polymorphism Data for Genome-Wide Association Studies. Methods Mol Biol 2022; 2481:153-159. [PMID: 35641763 DOI: 10.1007/978-1-0716-2237-7_9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Single-nucleotide polymorphisms (SNPs) have become the primary type of molecular genetic marker used in a diverse range of genetic and genomic studies. SNPs can be used to identify genomic regions linked to traits such as disease in genome-wide association studies, to understand population structure and diversity, or to understand mechanisms of genome evolution. One of the first steps of any SNP-based workflow, following SNP discovery, is quality control of SNP data. The protocol described here details how to perform quality control on SNP data to minimise errors in downstream analysis.
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Affiliation(s)
- Philipp E Bayer
- Applied Bioinformatics Group, School of Biological Sciences, The University of Western Australia, Perth, WA, Australia
| | - Mitchell Gill
- Applied Bioinformatics Group, School of Biological Sciences, The University of Western Australia, Perth, WA, Australia
| | - Monica F Danilevicz
- Applied Bioinformatics Group, School of Biological Sciences, The University of Western Australia, Perth, WA, Australia
| | - David Edwards
- Applied Bioinformatics Group, School of Biological Sciences, The University of Western Australia, Perth, WA, Australia.
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5
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Keeble-Gagnère G, Pasam R, Forrest KL, Wong D, Robinson H, Godoy J, Rattey A, Moody D, Mullan D, Walmsley T, Daetwyler HD, Tibbits J, Hayden MJ. Novel Design of Imputation-Enabled SNP Arrays for Breeding and Research Applications Supporting Multi-Species Hybridization. FRONTIERS IN PLANT SCIENCE 2021; 12:756877. [PMID: 35003156 PMCID: PMC8728019 DOI: 10.3389/fpls.2021.756877] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Accepted: 10/27/2021] [Indexed: 05/26/2023]
Abstract
Array-based single nucleotide polymorphism (SNP) genotyping platforms have low genotype error and missing data rates compared to genotyping-by-sequencing technologies. However, design decisions used to create array-based SNP genotyping assays for both research and breeding applications are critical to their success. We describe a novel approach applicable to any animal or plant species for the design of cost-effective imputation-enabled SNP genotyping arrays with broad utility and demonstrate its application through the development of the Illumina Infinium Wheat Barley 40K SNP array Version 1.0. We show that the approach delivers high quality and high resolution data for wheat and barley, including when samples are jointly hybridised. The new array aims to maximally capture haplotypic diversity in globally diverse wheat and barley germplasm while minimizing ascertainment bias. Comprising mostly biallelic markers that were designed to be species-specific and single-copy, the array permits highly accurate imputation in diverse germplasm to improve the statistical power of genome-wide association studies (GWAS) and genomic selection. The SNP content captures tetraploid wheat (A- and B-genome) and Aegilops tauschii Coss. (D-genome) diversity and delineates synthetic and tetraploid wheat from other wheat, as well as tetraploid species and subgroups. The content includes SNP tagging key trait loci in wheat and barley, as well as direct connections to other genotyping platforms and legacy datasets. The utility of the array is enhanced through the web-based tool, Pretzel (https://plantinformatics.io/) which enables the content of the array to be visualized and interrogated interactively in the context of numerous genetic and genomic resources to be connected more seamlessly to research and breeding. The array is available for use by the international wheat and barley community.
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Affiliation(s)
| | - Raj Pasam
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC, Australia
| | - Kerrie L. Forrest
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC, Australia
| | - Debbie Wong
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC, Australia
| | | | | | | | | | | | | | - Hans D. Daetwyler
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC, Australia
- School of Applied Systems Biology, La Trobe University, Bundoora, VIC, Australia
| | - Josquin Tibbits
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC, Australia
| | - Matthew J. Hayden
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC, Australia
- School of Applied Systems Biology, La Trobe University, Bundoora, VIC, Australia
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6
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Guerra FP, Yáñez A, Matus I, del Pozo A. Genome-Wide Association of Stem Carbohydrate Accumulation and Remobilization during Grain Growth in Bread Wheat (Triticum aestivum L.) in Mediterranean Environments. PLANTS 2021; 10:plants10030539. [PMID: 33809230 PMCID: PMC8001439 DOI: 10.3390/plants10030539] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Revised: 03/08/2021] [Accepted: 03/10/2021] [Indexed: 11/20/2022]
Abstract
Water deficit represents an important challenge for wheat production in many regions of the world. Accumulation and remobilization of water-soluble carbohydrates (WSCs) in stems are part of the physiological responses regulated by plants to cope with water stress and, in turn, determine grain yield (GY). The genetic mechanisms underlying the variation in WSC are only partially understood. In this study, we aimed to identify Single Nucleotide Polymorphism (SNP) markers that account for variation in a suite of WSC and GY, evaluated in 225 cultivars and advanced lines of spring wheat. These genotypes were established in two sites in the Mediterranean region of Central Chile, under water-limited and full irrigation conditions, and assessed in two growing seasons, namely anthesis and maturity growth periods. A genome-wide association study (GWAS) was performed by using 3243 SNP markers. Genetic variance accounted for 5 to 52% of phenotypic variation of the assessed traits. A rapid linkage disequilibrium decay was observed across chromosomes (r2 ≤ 0.2 at 2.52 kbp). Marker-trait association tests identified 96 SNPs related to stem weight (SW), WSCs, and GY, among other traits, at the different sites, growing seasons, and growth periods. The percentage of SNPs that were part of the gene-coding regions was 34%. Most of these genes are involved in the defensive response to drought and biotic stress. A complimentary analysis detected significant effects of different haplotypes on WSC and SW, in anthesis and maturity. Our results evidence both genetic and environmental influence on WSC dynamics in spring wheat. At the same time, they provide a series of markers suitable for supporting assisted selection approaches and functional characterization of genes.
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Affiliation(s)
- Fernando P. Guerra
- Instituto de Ciencias Biológicas, Universidad de Talca, Talca 3460000, Chile;
| | - Alejandra Yáñez
- Centro de Mejoramiento Genético y Fenómica Vegetal, Facultad de Ciencias Agrarias, Universidad de Talca, Talca 3460000, Chile;
- Facultad de Ciencias Agrarias y Forestales, Universidad Católica del Maule, Talca 3460000, Chile
| | - Iván Matus
- Centro Regional de Investigación Quilamapu, Instituto de Investigaciones Agropecuarias, Chillán 3780000, Chile;
| | - Alejandro del Pozo
- Centro de Mejoramiento Genético y Fenómica Vegetal, Facultad de Ciencias Agrarias, Universidad de Talca, Talca 3460000, Chile;
- Correspondence: ; Tel.: +56-71-2200-223
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7
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Hao C, Jiao C, Hou J, Li T, Liu H, Wang Y, Zheng J, Liu H, Bi Z, Xu F, Zhao J, Ma L, Wang Y, Majeed U, Liu X, Appels R, Maccaferri M, Tuberosa R, Lu H, Zhang X. Resequencing of 145 Landmark Cultivars Reveals Asymmetric Sub-genome Selection and Strong Founder Genotype Effects on Wheat Breeding in China. MOLECULAR PLANT 2020; 13:1733-1751. [PMID: 32896642 DOI: 10.1016/j.molp.2020.09.001] [Citation(s) in RCA: 97] [Impact Index Per Article: 24.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Revised: 08/19/2020] [Accepted: 09/02/2020] [Indexed: 05/18/2023]
Abstract
Controlled pedigrees and the multi-decade timescale of national crop plant breeding programs offer a unique experimental context for examining how selection affects plant genomes. More than 3000 wheat cultivars have been registered, released, and documented since 1949 in China. In this study, a set of 145 elite cultivars selected from historical points of wheat breeding in China were re-sequenced. A total of 43.75 Tb of sequence data were generated with an average read depth of 17.94× for each cultivar, and more than 60.92 million SNPs and 2.54 million InDels were captured, based on the Chinese Spring RefSeq genome v1.0. Seventy years of breeder-driven selection led to dramatic changes in grain yield and related phenotypes, with distinct genomic regions and phenotypes targeted by different breeders across the decades. There are very clear instances illustrating how introduced Italian and other foreign germplasm was integrated into Chinese wheat programs and reshaped the genomic landscape of local modern cultivars. Importantly, the resequencing data also highlighted significant asymmetric breeding selection among the three sub-genomes: this was evident in both the collinear blocks for homeologous chromosomes and among sets of three homeologous genes. Accumulation of more newly assembled genes in newer cultivars implied the potential value of these genes in breeding. Conserved and extended sharing of linkage disequilibrium (LD) blocks was highlighted among pedigree-related cultivars, in which fewer haplotype differences were detected. Fixation or replacement of haplotypes from founder genotypes after generations of breeding was related to their breeding value. Based on the haplotype frequency changes in LD blocks of pedigree-related cultivars, we propose a strategy for evaluating the breeding value of any given line on the basis of the accumulation (pyramiding) of beneficial haplotypes. Collectively, our study demonstrates the influence of "founder genotypes" on the output of breeding efforts over many decades and also suggests that founder genotype perspectives are in fact more dynamic when applied in the context of modern genomics-informed breeding.
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Affiliation(s)
- Chenyang Hao
- Key Laboratory of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture and Rural Affairs/The National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Chengzhi Jiao
- Key Laboratory of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture and Rural Affairs/The National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China; Novogene Bioinformatics Institute, Beijing 100083, China
| | - Jian Hou
- Key Laboratory of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture and Rural Affairs/The National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Tian Li
- Key Laboratory of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture and Rural Affairs/The National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Hongxia Liu
- Key Laboratory of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture and Rural Affairs/The National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Yuquan Wang
- Key Laboratory of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture and Rural Affairs/The National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Jun Zheng
- Key Laboratory of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture and Rural Affairs/The National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Hong Liu
- Key Laboratory of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture and Rural Affairs/The National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Zhihong Bi
- Novogene Bioinformatics Institute, Beijing 100083, China
| | - Fengfeng Xu
- Novogene Bioinformatics Institute, Beijing 100083, China
| | - Jing Zhao
- Key Laboratory of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture and Rural Affairs/The National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Lin Ma
- Key Laboratory of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture and Rural Affairs/The National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Yamei Wang
- Key Laboratory of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture and Rural Affairs/The National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Uzma Majeed
- Key Laboratory of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture and Rural Affairs/The National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Xu Liu
- Key Laboratory of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture and Rural Affairs/The National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Rudi Appels
- AgriBio, Centre for AgriBioscience, Department of Economic Development, Jobs, Transport, and Resources, 5 Ring Road, La Trobe University, Bundoora, VIC 3083, Australia
| | - Marco Maccaferri
- Department of Agricultural and Food Sciences, University of Bologna, Bologna, Italy
| | - Roberto Tuberosa
- Department of Agricultural and Food Sciences, University of Bologna, Bologna, Italy
| | - Hongfeng Lu
- Novogene Bioinformatics Institute, Beijing 100083, China.
| | - Xueyong Zhang
- Key Laboratory of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture and Rural Affairs/The National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China.
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8
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Evidence for the Accumulation of Nonsynonymous Mutations and Favorable Pleiotropic Alleles During Wheat Breeding. G3-GENES GENOMES GENETICS 2020; 10:4001-4011. [PMID: 32900902 PMCID: PMC7642940 DOI: 10.1534/g3.120.401269] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
Plant breeding leads to the genetic improvement of target traits by selecting a small number of genotypes from among typically large numbers of candidate genotypes after careful evaluation. In this study, we first investigated how mutations at conserved nucleotide sites normally viewed as deleterious, such as nonsynonymous sites, accumulated in a wheat, Triticum aestivum, breeding lineage. By comparing a 150 year old ancestral and modern cultivar, we found recent nucleotide polymorphisms altered amino acids and occurred within conserved genes at frequencies expected in the absence of purifying selection. Mutations that are deleterious in other contexts likely had very small or no effects on target traits within the breeding lineage. Second, we investigated if breeders selected alleles with favorable effects on some traits and unfavorable effects on others and used different alleles to compensate for the latter. An analysis of a segregating population derived from the ancestral and modern parents provided one example of this phenomenon. The recent cultivar contains the Rht-B1b green revolution semi-dwarfing allele and compensatory alleles that reduce its negative effects. However, improvements in traits other than plant height were due to pleiotropic loci with favorable effects on traits and to favorable loci with no detectable pleiotropic effects. Wheat breeding appears to tolerate mutations at conserved nucleotide sites and to only select for alleles with both favorable and unfavorable effects on traits in exceptional situations.
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9
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Tahir Ul Qamar M, Zhu X, Khan MS, Xing F, Chen LL. Pan-genome: A promising resource for noncoding RNA discovery in plants. THE PLANT GENOME 2020; 13:e20046. [PMID: 33217199 DOI: 10.1002/tpg2.20046] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/14/2020] [Revised: 06/08/2020] [Accepted: 06/22/2020] [Indexed: 05/05/2023]
Abstract
Plant genomes contain both protein-coding and noncoding sequences including transposable elements (TEs) and noncoding RNAs (ncRNAs). The ncRNAs are recognized as important elements that play fundamental roles in the structural organization and function of plant genomes. Despite various hypotheses, TEs are believed to be a major precursor of ncRNAs. Transposable elements are also prime factors that cause genomic variation among members of a species. Hence, TEs pose a major challenge in the discovery and analysis of ncRNAs. With the increase in the number of sequenced plant genomes, it is now accepted that a single reference genome is insufficient to represent the complete genomic diversity and contents of a species, and exploring the pan-genome of a species is critical. In this review, we summarize the recent progress in the field of plant pan-genomes. We also discuss TEs and their roles in ncRNA biogenesis and present our perspectives on the application of pan-genomes for the discovery of ncRNAs to fully explore and exploit their biological roles in plants.
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Affiliation(s)
- Muhammad Tahir Ul Qamar
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, College of Life Science and Technology, Guangxi University, Nanning, 530004, P. R. China
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan, 430070, P. R. China
| | - Xitong Zhu
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan, 430070, P. R. China
| | - Muhammad Sarwar Khan
- Center of Agricultural Biochemistry and Biotechnology, University of Agriculture, Faisalabad, 38000, Pakistan
| | - Feng Xing
- College of Life Science, Xinyang Normal University, Xinyang, 464000, P. R. China
| | - Ling-Ling Chen
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, College of Life Science and Technology, Guangxi University, Nanning, 530004, P. R. China
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan, 430070, P. R. China
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Yang S, Yu W, Wei X, Wang Z, Zhao Y, Zhao X, Tian B, Yuan Y, Zhang X. An extended KASP-SNP resource for molecular breeding in Chinese cabbage(Brassica rapa L. ssp. pekinensis). PLoS One 2020; 15:e0240042. [PMID: 33007009 PMCID: PMC7531813 DOI: 10.1371/journal.pone.0240042] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2020] [Accepted: 09/18/2020] [Indexed: 12/31/2022] Open
Abstract
Kompetitive allele-specific PCR (KASP) is a cost-effective single-step SNP genotyping technology, With an objective to enhance the marker repertoire and develop high efficient KASP-SNP markers in Chinese cabbage, we re-sequenced four Chinese cabbage doubled haploid (DH) lines, Y177-47, Y635-10, Y510-1 and Y510-9, and generated a total of more than 38.5 billion clean base pairs. A total of 827,720 SNP loci were identified with an estimated density of 3,217 SNPs/Mb. Further, a total of 387,354 SNPs with at least 30 bp to the next most adjacent SNPs on either side were selected as resource for KASP markers. From this resource, 258 (96.27%) of 268 SNP loci were successfully transformed into KASP-SNP markers using a Roche LightCycler 480-II instrument. Among these markers, 221 (85.66%) were co-dominant markers, 220 (85.27%) were non-synonymous SNPs, and 257 (99.6%) were newly developed markers. In addition, 53 markers were applied for genotyping of 34 Brassica rapa accessions. Cluster analysis separated these 34 accessions into three clusters based on heading types. The millions of SNP loci, a large set of resource for KASP markers, as well as the newly developed KASP markers in this study may facilitate further genetic and molecular breeding studies in Brassica rapa.
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Affiliation(s)
- Shuangjuan Yang
- Institute of Horticulture, Henan Academy of Agricultural Sciences, Zhengzhou, China
| | - Wentao Yu
- Institute of Horticulture, Henan Academy of Agricultural Sciences, Zhengzhou, China
- College of Life Science, Zhengzhou University, Zhengzhou, China
| | - Xiaochun Wei
- Institute of Horticulture, Henan Academy of Agricultural Sciences, Zhengzhou, China
| | - Zhiyong Wang
- Institute of Horticulture, Henan Academy of Agricultural Sciences, Zhengzhou, China
| | - Yanyan Zhao
- Institute of Horticulture, Henan Academy of Agricultural Sciences, Zhengzhou, China
| | - Xiaobin Zhao
- Institute of Horticulture, Henan Academy of Agricultural Sciences, Zhengzhou, China
| | - Baoming Tian
- College of Life Science, Zhengzhou University, Zhengzhou, China
- * E-mail: (XW-Z); (BT); (YY)
| | - Yuxiang Yuan
- Institute of Horticulture, Henan Academy of Agricultural Sciences, Zhengzhou, China
- * E-mail: (XW-Z); (BT); (YY)
| | - Xiaowei Zhang
- Institute of Horticulture, Henan Academy of Agricultural Sciences, Zhengzhou, China
- * E-mail: (XW-Z); (BT); (YY)
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11
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Hyun DY, Sebastin R, Lee KJ, Lee GA, Shin MJ, Kim SH, Lee JR, Cho GT. Genotyping-by-Sequencing Derived Single Nucleotide Polymorphisms Provide the First Well-Resolved Phylogeny for the Genus Triticum (Poaceae). FRONTIERS IN PLANT SCIENCE 2020; 11:688. [PMID: 32625218 PMCID: PMC7311657 DOI: 10.3389/fpls.2020.00688] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/10/2020] [Accepted: 04/30/2020] [Indexed: 05/17/2023]
Abstract
Wheat (Triticum spp.) has been an important staple food crop for mankind since the beginning of agriculture. The genus Triticum L. is composed of diploid, tetraploid, and hexaploid species, majority of which have not yet been discriminated clearly, and hence their phylogeny and classification remain unresolved. Genotyping-by-sequencing (GBS) is an easy and affordable method that allows us to generate genome-wide single nucleotide polymorphism (SNP) markers. In this study, we used GBS to obtain SNPs covering all seven chromosomes from 283 accessions of Triticum-related genera. After filtering low-quality and redundant SNPs based on haplotype information, the GBS assay provided 14,188 high-quality SNPs that were distributed across the A (71%), B (26%), and D (2.4%) genomes. Cluster analysis and discriminant analysis of principal components (DAPC) allowed us to distinguish six distinct groups that matched well with Triticum species complexity. We constructed a Bayesian phylogenetic tree using 14,188 SNPs, in which 17 Triticum species and subspecies were discriminated. Dendrogram analysis revealed that the polyploid wheat species could be divided into groups according to the presence of A, B, D, and G genomes with strong nodal support and provided new insight into the evolution of spelt wheat. A total of 2,692 species-specific SNPs were identified to discriminate the common (T. aestivum) and durum (T. turgidum) wheat cultivar and landraces. In principal component analysis grouping, the two wheat species formed individual clusters and the SNPs were able to distinguish up to nine groups of 10 subspecies. This study demonstrated that GBS-derived SNPs could be used efficiently in genebank management to classify Triticum species and subspecies that are very difficult to distinguish by their morphological characters.
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12
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Arndell T, Sharma N, Langridge P, Baumann U, Watson-Haigh NS, Whitford R. gRNA validation for wheat genome editing with the CRISPR-Cas9 system. BMC Biotechnol 2019; 19:71. [PMID: 31684940 PMCID: PMC6829922 DOI: 10.1186/s12896-019-0565-z] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2018] [Accepted: 09/30/2019] [Indexed: 12/26/2022] Open
Abstract
BACKGROUND The CRISPR-Cas9 system is a powerful and versatile tool for crop genome editing. However, achieving highly efficient and specific editing in polyploid species can be a challenge. The efficiency and specificity of the CRISPR-Cas9 system depends critically on the gRNA used. Here, we assessed the activities and specificities of seven gRNAs targeting 5-enolpyruvylshikimate-3-phosphate synthase (EPSPS) in hexaploid wheat protoplasts. EPSPS is the biological target of the widely used herbicide glyphosate. RESULTS The seven gRNAs differed substantially in their on-target activities, with mean indel frequencies ranging from 0% to approximately 20%. There was no obvious correlation between experimentally determined and in silico predicted on-target gRNA activity. The presence of a single mismatch within the seed region of the guide sequence greatly reduced but did not abolish gRNA activity, whereas the presence of an additional mismatch, or the absence of a PAM, all but abolished gRNA activity. Large insertions (≥20 bp) of DNA vector-derived sequence were detected at frequencies up to 8.5% of total indels. One of the gRNAs exhibited several properties that make it potentially suitable for the development of non-transgenic glyphosate resistant wheat. CONCLUSIONS We have established a rapid and reliable method for gRNA validation in hexaploid wheat protoplasts. The method can be used to identify gRNAs that have favourable properties. Our approach is particularly suited to polyploid species, but should be applicable to any plant species amenable to protoplast transformation.
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Affiliation(s)
- Taj Arndell
- Present address: CSIRO, Agriculture and Food, Canberra, ACT Australia
| | - Niharika Sharma
- Present address: New South Wales Department of Primary Industries, Research Excellence, Orange, NSW Australia
| | - Peter Langridge
- School of Agriculture, Food & Wine, The University of Adelaide, Waite Campus, Urrbrae, SA 5064 Australia
| | - Ute Baumann
- School of Agriculture, Food & Wine, The University of Adelaide, Waite Campus, Urrbrae, SA 5064 Australia
| | - Nathan S. Watson-Haigh
- Present address: Bioinformatics Hub, School of Biological Sciences, The University of Adelaide, Adelaide, SA 5005 Australia
| | - Ryan Whitford
- School of Agriculture, Food & Wine, The University of Adelaide, Waite Campus, Urrbrae, SA 5064 Australia
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Scheben A, Verpaalen B, Lawley CT, Chan CKK, Bayer PE, Batley J, Edwards D. CropSNPdb: a database of SNP array data for Brassica crops and hexaploid bread wheat. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2019; 98:142-152. [PMID: 30548723 DOI: 10.1111/tpj.14194] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/05/2018] [Revised: 11/26/2018] [Accepted: 11/27/2018] [Indexed: 05/23/2023]
Abstract
Advances in sequencing technology have led to a rapid rise in the genomic data available for plants, driving new insights into the evolution, domestication and improvement of crops. Single nucleotide polymorphisms (SNPs) are a major component of crop genomic diversity, and are invaluable as genetic markers in research and breeding programs. High-throughput SNP arrays, or 'SNP chips', can generate reproducible sets of informative SNP markers and have been broadly adopted. Although there are many public repositories for sequencing data, which are routinely uploaded, there are no formal repositories for crop SNP array data. To make SNP array data more easily accessible, we have developed CropSNPdb (http://snpdb.appliedbioinformatics.com.au), a database for SNP array data produced by the Illumina Infinium™ hexaploid bread wheat (Triticum aestivum) 90K and Brassica 60K arrays. We currently host SNPs from datasets covering 526 Brassica lines and 309 bread wheat lines, and provide search, download and upload utilities for users. CropSNPdb provides a useful repository for these data, which can be applied for a range of genomics and molecular crop-breeding activities.
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Affiliation(s)
- Armin Scheben
- School of Biological Sciences and Institute of Agriculture, The University of Western Australia, Perth, WA, 6009, Australia
| | - Brent Verpaalen
- School of Biological Sciences and Institute of Agriculture, The University of Western Australia, Perth, WA, 6009, Australia
| | | | - Chon-Kit K Chan
- School of Biological Sciences and Institute of Agriculture, The University of Western Australia, Perth, WA, 6009, Australia
- Australian Genome Research Facility, Melbourne, Vic., 3000, Australia
| | - Philipp E Bayer
- School of Biological Sciences and Institute of Agriculture, The University of Western Australia, Perth, WA, 6009, Australia
| | - Jacqueline Batley
- School of Biological Sciences and Institute of Agriculture, The University of Western Australia, Perth, WA, 6009, Australia
| | - David Edwards
- School of Biological Sciences and Institute of Agriculture, The University of Western Australia, Perth, WA, 6009, Australia
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14
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Alipour H, Bai G, Zhang G, Bihamta MR, Mohammadi V, Peyghambari SA. Imputation accuracy of wheat genotyping-by-sequencing (GBS) data using barley and wheat genome references. PLoS One 2019; 14:e0208614. [PMID: 30615624 PMCID: PMC6322752 DOI: 10.1371/journal.pone.0208614] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2018] [Accepted: 11/20/2018] [Indexed: 02/04/2023] Open
Abstract
Genotyping-by-sequencing (GBS) provides high SNP coverage and has recently emerged as a popular technology for genetic and breeding applications in bread wheat (Triticum aestivum L.) and many other plant species. Although GBS can discover millions of SNPs, a high rate of missing data is a major concern for many applications. Accurate imputation of those missing data can significantly improve the utility of GBS data. This study compared imputation accuracies among four genome references including three wheat references (Chinese Spring survey sequence, W7984, and IWGSC RefSeq v1.0) and one barley reference genome by comparing imputed data derived from low-depth sequencing to actual data from high-depth sequencing. After imputation, the average number of imputed data points was the highest in the B genome (~48.99%). The D genome had the lowest imputed data points (~15.02%) but the highest imputation accuracy. Among the four reference genomes, IWGSC RefSeq v1.0 reference provided the most imputed data points, but the lowest imputation accuracy for the SNPs with < 10% minor allele frequency (MAF). The W7984 reference, however, provided the highest imputation accuracy for the SNPs with < 10% MAF.
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Affiliation(s)
- Hadi Alipour
- Department of Agronomy, Kansas State University, Manhattan, Kansas, United States of America
- Department of Plant Breeding and Biotechnology, Faculty of Agriculture, Urmia University, Urmia, Iran
| | - Guihua Bai
- USDA-ARS, Hard Winter Wheat Genetics Research Unit, Manhattan, Kansas, United States of America
| | - Guorong Zhang
- Department of Agronomy, Kansas State University, Manhattan, Kansas, United States of America
- * E-mail:
| | - Mohammad Reza Bihamta
- Department of Agronomy and Plant Breeding, Faculty of Agriculture, University of Tehran, Karaj, Iran
| | - Valiollah Mohammadi
- Department of Agronomy and Plant Breeding, Faculty of Agriculture, University of Tehran, Karaj, Iran
| | - Seyed Ali Peyghambari
- Department of Agronomy and Plant Breeding, Faculty of Agriculture, University of Tehran, Karaj, Iran
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Abstract
The genomics revolution brought on by advances in high-throughput sequencing has led to the production of vast amounts of data. Databases play an essential role in storing and managing this information to make it available to researchers and crop breeders. This chapter provides an outline of how to use databases and tools for wheat genome research.
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16
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Genotyping by Sequencing Reasserts the Close Relationship between Tef and Its Putative Wild Eragrostis Progenitors. DIVERSITY-BASEL 2018. [DOI: 10.3390/d10020017] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
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17
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High throughput SNP discovery and genotyping in hexaploid wheat. PLoS One 2018; 13:e0186329. [PMID: 29293495 PMCID: PMC5749704 DOI: 10.1371/journal.pone.0186329] [Citation(s) in RCA: 129] [Impact Index Per Article: 21.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2017] [Accepted: 09/13/2017] [Indexed: 12/03/2022] Open
Abstract
Because of their abundance and their amenability to high-throughput genotyping techniques, Single Nucleotide Polymorphisms (SNPs) are powerful tools for efficient genetics and genomics studies, including characterization of genetic resources, genome-wide association studies and genomic selection. In wheat, most of the previous SNP discovery initiatives targeted the coding fraction, leaving almost 98% of the wheat genome largely unexploited. Here we report on the use of whole-genome resequencing data from eight wheat lines to mine for SNPs in the genic, the repetitive and non-repetitive intergenic fractions of the wheat genome. Eventually, we identified 3.3 million SNPs, 49% being located on the B-genome, 41% on the A-genome and 10% on the D-genome. We also describe the development of the TaBW280K high-throughput genotyping array containing 280,226 SNPs. Performance of this chip was examined by genotyping a set of 96 wheat accessions representing the worldwide diversity. Sixty-nine percent of the SNPs can be efficiently scored, half of them showing a diploid-like clustering. The TaBW280K was proven to be a very efficient tool for diversity analyses, as well as for breeding as it can discriminate between closely related elite varieties. Finally, the TaBW280K array was used to genotype a population derived from a cross between Chinese Spring and Renan, leading to the construction a dense genetic map comprising 83,721 markers. The results described here will provide the wheat community with powerful tools for both basic and applied research.
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18
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Dwivedi SL, Scheben A, Edwards D, Spillane C, Ortiz R. Assessing and Exploiting Functional Diversity in Germplasm Pools to Enhance Abiotic Stress Adaptation and Yield in Cereals and Food Legumes. FRONTIERS IN PLANT SCIENCE 2017; 8:1461. [PMID: 28900432 PMCID: PMC5581882 DOI: 10.3389/fpls.2017.01461] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/21/2017] [Accepted: 08/07/2017] [Indexed: 05/03/2023]
Abstract
There is a need to accelerate crop improvement by introducing alleles conferring host plant resistance, abiotic stress adaptation, and high yield potential. Elite cultivars, landraces and wild relatives harbor useful genetic variation that needs to be more easily utilized in plant breeding. We review genome-wide approaches for assessing and identifying alleles associated with desirable agronomic traits in diverse germplasm pools of cereals and legumes. Major quantitative trait loci and single nucleotide polymorphisms (SNPs) associated with desirable agronomic traits have been deployed to enhance crop productivity and resilience. These include alleles associated with variation conferring enhanced photoperiod and flowering traits. Genetic variants in the florigen pathway can provide both environmental flexibility and improved yields. SNPs associated with length of growing season and tolerance to abiotic stresses (precipitation, high temperature) are valuable resources for accelerating breeding for drought-prone environments. Both genomic selection and genome editing can also harness allelic diversity and increase productivity by improving multiple traits, including phenology, plant architecture, yield potential and adaptation to abiotic stresses. Discovering rare alleles and useful haplotypes also provides opportunities to enhance abiotic stress adaptation, while epigenetic variation has potential to enhance abiotic stress adaptation and productivity in crops. By reviewing current knowledge on specific traits and their genetic basis, we highlight recent developments in the understanding of crop functional diversity and identify potential candidate genes for future use. The storage and integration of genetic, genomic and phenotypic information will play an important role in ensuring broad and rapid application of novel genetic discoveries by the plant breeding community. Exploiting alleles for yield-related traits would allow improvement of selection efficiency and overall genetic gain of multigenic traits. An integrated approach involving multiple stakeholders specializing in management and utilization of genetic resources, crop breeding, molecular biology and genomics, agronomy, stress tolerance, and reproductive/seed biology will help to address the global challenge of ensuring food security in the face of growing resource demands and climate change induced stresses.
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Affiliation(s)
| | - Armin Scheben
- School of Biological Sciences, Institute of Agriculture, University of Western Australia, PerthWA, Australia
| | - David Edwards
- School of Biological Sciences, Institute of Agriculture, University of Western Australia, PerthWA, Australia
| | - Charles Spillane
- Plant and AgriBiosciences Research Centre, Ryan Institute, National University of Ireland GalwayGalway, Ireland
| | - Rodomiro Ortiz
- Department of Plant Breeding, Swedish University of Agricultural SciencesAlnarp, Sweden
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19
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Talukder SK, Saha MC. Toward Genomics-Based Breeding in C3 Cool-Season Perennial Grasses. FRONTIERS IN PLANT SCIENCE 2017; 8:1317. [PMID: 28798766 PMCID: PMC5526908 DOI: 10.3389/fpls.2017.01317] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/19/2017] [Accepted: 07/12/2017] [Indexed: 05/13/2023]
Abstract
Most important food and feed crops in the world belong to the C3 grass family. The future of food security is highly reliant on achieving genetic gains of those grasses. Conventional breeding methods have already reached a plateau for improving major crops. Genomics tools and resources have opened an avenue to explore genome-wide variability and make use of the variation for enhancing genetic gains in breeding programs. Major C3 annual cereal breeding programs are well equipped with genomic tools; however, genomic research of C3 cool-season perennial grasses is lagging behind. In this review, we discuss the currently available genomics tools and approaches useful for C3 cool-season perennial grass breeding. Along with a general review, we emphasize the discussion focusing on forage grasses that were considered orphan and have little or no genetic information available. Transcriptome sequencing and genotype-by-sequencing technology for genome-wide marker detection using next-generation sequencing (NGS) are very promising as genomics tools. Most C3 cool-season perennial grass members have no prior genetic information; thus NGS technology will enhance collinear study with other C3 model grasses like Brachypodium and rice. Transcriptomics data can be used for identification of functional genes and molecular markers, i.e., polymorphism markers and simple sequence repeats (SSRs). Genome-wide association study with NGS-based markers will facilitate marker identification for marker-assisted selection. With limited genetic information, genomic selection holds great promise to breeders for attaining maximum genetic gain of the cool-season C3 perennial grasses. Application of all these tools can ensure better genetic gains, reduce length of selection cycles, and facilitate cultivar development to meet the future demand for food and fodder.
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20
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Montenegro JD, Golicz AA, Bayer PE, Hurgobin B, Lee H, Chan CKK, Visendi P, Lai K, Doležel J, Batley J, Edwards D. The pangenome of hexaploid bread wheat. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2017; 90:1007-1013. [PMID: 28231383 DOI: 10.1111/tpj.13515] [Citation(s) in RCA: 214] [Impact Index Per Article: 30.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/17/2016] [Accepted: 02/06/2017] [Indexed: 05/19/2023]
Abstract
There is an increasing understanding that variation in gene presence-absence plays an important role in the heritability of agronomic traits; however, there have been relatively few studies on variation in gene presence-absence in crop species. Hexaploid wheat is one of the most important food crops in the world and intensive breeding has reduced the genetic diversity of elite cultivars. Major efforts have produced draft genome assemblies for the cultivar Chinese Spring, but it is unknown how well this represents the genome diversity found in current modern elite cultivars. In this study we build an improved reference for Chinese Spring and explore gene diversity across 18 wheat cultivars. We predict a pangenome size of 140 500 ± 102 genes, a core genome of 81 070 ± 1631 genes and an average of 128 656 genes in each cultivar. Functional annotation of the variable gene set suggests that it is enriched for genes that may be associated with important agronomic traits. In addition to variation in gene presence, more than 36 million intervarietal single nucleotide polymorphisms were identified across the pangenome. This study of the wheat pangenome provides insight into genome diversity in elite wheat as a basis for genomics-based improvement of this important crop. A wheat pangenome, GBrowse, is available at http://appliedbioinformatics.com.au/cgi-bin/gb2/gbrowse/WheatPan/, and data are available to download from http://wheatgenome.info/wheat_genome_databases.php.
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Affiliation(s)
- Juan D Montenegro
- School of Agriculture and Food Sciences, University of Queensland, Brisbane, Australia
| | - Agnieszka A Golicz
- School of Agriculture and Food Sciences, University of Queensland, Brisbane, Australia
- School of Plant Biology, University of Western Australia, Crawley, WA, 6009, Australia
| | - Philipp E Bayer
- School of Plant Biology, University of Western Australia, Crawley, WA, 6009, Australia
| | - Bhavna Hurgobin
- School of Agriculture and Food Sciences, University of Queensland, Brisbane, Australia
- School of Plant Biology, University of Western Australia, Crawley, WA, 6009, Australia
| | - HueyTyng Lee
- School of Agriculture and Food Sciences, University of Queensland, Brisbane, Australia
- School of Plant Biology, University of Western Australia, Crawley, WA, 6009, Australia
| | - Chon-Kit Kenneth Chan
- School of Plant Biology, University of Western Australia, Crawley, WA, 6009, Australia
| | - Paul Visendi
- School of Agriculture and Food Sciences, University of Queensland, Brisbane, Australia
| | | | - Jaroslav Doležel
- Institute of Experimental Botany, Centre of the Region Haná for Biotechnological and Agricultural Research, Šlechtitelů 31, CZ-783 71, Olomouc, Czech Republic
| | - Jacqueline Batley
- School of Agriculture and Food Sciences, University of Queensland, Brisbane, Australia
- School of Plant Biology, University of Western Australia, Crawley, WA, 6009, Australia
- Institute of Agriculture, University of Western Australia, Crawley, WA, 6009, Australia
| | - David Edwards
- School of Agriculture and Food Sciences, University of Queensland, Brisbane, Australia
- School of Plant Biology, University of Western Australia, Crawley, WA, 6009, Australia
- Institute of Agriculture, University of Western Australia, Crawley, WA, 6009, Australia
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21
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Powell JJ, Fitzgerald TL, Stiller J, Berkman PJ, Gardiner DM, Manners JM, Henry RJ, Kazan K. The defence-associated transcriptome of hexaploid wheat displays homoeolog expression and induction bias. PLANT BIOTECHNOLOGY JOURNAL 2017; 15:533-543. [PMID: 27735125 PMCID: PMC5362679 DOI: 10.1111/pbi.12651] [Citation(s) in RCA: 64] [Impact Index Per Article: 9.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/16/2016] [Accepted: 10/07/2016] [Indexed: 05/20/2023]
Abstract
Bread wheat (Triticum aestivum L.) is an allopolyploid species containing three ancestral genomes. Therefore, three homoeologous copies exist for the majority of genes in the wheat genome. Whether different homoeologs are differentially expressed (homoeolog expression bias) in response to biotic and abiotic stresses is poorly understood. In this study, we applied a RNA-seq approach to analyse homoeolog-specific global gene expression patterns in wheat during infection by the fungal pathogen Fusarium pseudograminearum, which causes crown rot disease in cereals. To ensure specific detection of homoeologs, we first optimized read alignment methods and validated the results experimentally on genes with known patterns of subgenome-specific expression. Our global analysis identified widespread patterns of differential expression among homoeologs, indicating homoeolog expression bias underpins a large proportion of the wheat transcriptome. In particular, genes differentially expressed in response to Fusarium infection were found to be disproportionately contributed from B and D subgenomes. In addition, we found differences in the degree of responsiveness to pathogen infection among homoeologous genes with B and D homoeologs exhibiting stronger responses to pathogen infection than A genome copies. We call this latter phenomenon as 'homoeolog induction bias'. Understanding how homoeolog expression and induction biases operate may assist the improvement of biotic stress tolerance in wheat and other polyploid crop species.
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Affiliation(s)
- Jonathan J. Powell
- Commonwealth Scientific and Industrial Research Organisation AgricultureSt LuciaQueenslandAustralia
- Queensland Alliance for Agriculture and Food InnovationUniversity of QueenslandSt LuciaQueenslandAustralia
| | - Timothy L. Fitzgerald
- Commonwealth Scientific and Industrial Research Organisation AgricultureSt LuciaQueenslandAustralia
| | - Jiri Stiller
- Commonwealth Scientific and Industrial Research Organisation AgricultureSt LuciaQueenslandAustralia
| | - Paul J. Berkman
- Commonwealth Scientific and Industrial Research Organisation AgricultureSt LuciaQueenslandAustralia
| | - Donald M. Gardiner
- Commonwealth Scientific and Industrial Research Organisation AgricultureSt LuciaQueenslandAustralia
| | - John M. Manners
- Commonwealth Scientific and Industrial Research Organisation AgricultureBlack MountainAustralian Capital TerritoryAustralia
| | - Robert J. Henry
- Queensland Alliance for Agriculture and Food InnovationUniversity of QueenslandSt LuciaQueenslandAustralia
| | - Kemal Kazan
- Commonwealth Scientific and Industrial Research Organisation AgricultureSt LuciaQueenslandAustralia
- Queensland Alliance for Agriculture and Food InnovationUniversity of QueenslandSt LuciaQueenslandAustralia
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23
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Liu M, Stiller J, Holušová K, Vrána J, Liu D, Doležel J, Liu C. Chromosome-specific sequencing reveals an extensive dispensable genome component in wheat. Sci Rep 2016; 6:36398. [PMID: 27821854 PMCID: PMC5099574 DOI: 10.1038/srep36398] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2016] [Accepted: 10/14/2016] [Indexed: 12/22/2022] Open
Abstract
The hexaploid wheat genotype Chinese Spring (CS) has been used worldwide as the reference base for wheat genetics and genomics, and significant resources have been used by the international community to generate a reference wheat genome based on this genotype. By sequencing flow-sorted 3B chromosome from a hexaploid wheat genotype CRNIL1A and comparing the obtained sequences with those available for CS, we detected that a large number of sequences in the former were missing in the latter. If the distribution of such sequences in the hexaploid wheat genome is random, CRNILA sequences missing in CS could be as much as 159.3 Mb even if only fragments of 50 bp or longer were considered. Analysing RNA sequences available in the public domains also revealed that dispensable genes are common in hexaploid wheat. Together with those extensive intra- and interchromosomal rearrangements in CS, the existence of such dispensable genes is another factor highlighting potential issues with the use of reference genomes in various studies. Strong deviation in distributions of these dispensable sequences among genotypes with different geographical origins provided the first evidence indicating that they could be associated with adaptation in wheat.
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Affiliation(s)
- Miao Liu
- CSIRO Agriculture and Food, 306 Carmody Road, St Lucia, QLD 4067, Australia
- Triticeae Research Institute, Sichuan Agricultural University, Wenjiang, Chengdu 611130, China
| | - Jiri Stiller
- CSIRO Agriculture and Food, 306 Carmody Road, St Lucia, QLD 4067, Australia
| | - Kateřina Holušová
- Institute of Experimental Botany, Centre of the Region Haná for Biotechnological and Agricultural Research, Šlechtitelů 31, CZ-78371 Olomouc, Czech Republic
| | - Jan Vrána
- Institute of Experimental Botany, Centre of the Region Haná for Biotechnological and Agricultural Research, Šlechtitelů 31, CZ-78371 Olomouc, Czech Republic
| | - Dengcai Liu
- Triticeae Research Institute, Sichuan Agricultural University, Wenjiang, Chengdu 611130, China
| | - Jaroslav Doležel
- Institute of Experimental Botany, Centre of the Region Haná for Biotechnological and Agricultural Research, Šlechtitelů 31, CZ-78371 Olomouc, Czech Republic
| | - Chunji Liu
- CSIRO Agriculture and Food, 306 Carmody Road, St Lucia, QLD 4067, Australia
- School of Plant Biology, The University of Western Australia, Perth, WA 6009, Australia
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Abstract
An integrated database with a variety of Web-based systems named WheatGenome.info hosting wheat genome and genomic data has been developed to support wheat research and crop improvement. The resource includes multiple Web-based applications, which are implemented as a variety of Web-based systems. These include a GBrowse2-based wheat genome viewer with BLAST search portal, TAGdb for searching wheat second generation genome sequence data, wheat autoSNPdb, links to wheat genetic maps using CMap and CMap3D, and a wheat genome Wiki to allow interaction between diverse wheat genome sequencing activities. This portal provides links to a variety of wheat genome resources hosted at other research organizations. This integrated database aims to accelerate wheat genome research and is freely accessible via the web interface at http://www.wheatgenome.info/ .
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25
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Golicz AA, Batley J, Edwards D. Towards plant pangenomics. PLANT BIOTECHNOLOGY JOURNAL 2016; 14:1099-105. [PMID: 26593040 DOI: 10.1111/pbi.12499] [Citation(s) in RCA: 65] [Impact Index Per Article: 8.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/02/2015] [Revised: 09/18/2015] [Accepted: 10/04/2015] [Indexed: 05/05/2023]
Abstract
As an increasing number of genome sequences become available for a wide range of species, there is a growing understanding that the genome of a single individual is insufficient to represent the gene diversity within a whole species. Many studies examine the sequence diversity within genes, and this allelic variation is an important source of phenotypic variation which can be selected for by man or nature. However, the significant gene presence/absence variation that has been observed within species and the impact of this variation on traits is only now being studied in detail. The sum of the genes for a species is termed the pangenome, and the determination and characterization of the pangenome is a requirement to understand variation within a species. In this review, we explore the current progress in pangenomics as well as methods and approaches for the characterization of pangenomes for a wide range of plant species.
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Affiliation(s)
- Agnieszka A Golicz
- School of Agriculture and Food Sciences, University of Queensland, St. Lucia, QLD, Australia
- School of Plant Biology, University of Western Australia, Perth, WA, Australia
| | - Jacqueline Batley
- School of Agriculture and Food Sciences, University of Queensland, St. Lucia, QLD, Australia
- School of Plant Biology, University of Western Australia, Perth, WA, Australia
| | - David Edwards
- School of Agriculture and Food Sciences, University of Queensland, St. Lucia, QLD, Australia
- School of Plant Biology, University of Western Australia, Perth, WA, Australia
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Cubizolles N, Rey E, Choulet F, Rimbert H, Laugier C, Balfourier F, Bordes J, Poncet C, Jack P, James C, Gielen J, Argillier O, Jaubertie JP, Auzanneau J, Rohde A, Ouwerkerk PBF, Korzun V, Kollers S, Guerreiro L, Hourcade D, Robert O, Devaux P, Mastrangelo AM, Feuillet C, Sourdille P, Paux E. Exploiting the Repetitive Fraction of the Wheat Genome for High-Throughput Single-Nucleotide Polymorphism Discovery and Genotyping. THE PLANT GENOME 2016; 9. [PMID: 27898760 DOI: 10.3835/plantgenome2015.09.0078] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
Transposable elements (TEs) account for more than 80% of the wheat genome. Although they represent a major obstacle for genomic studies, TEs are also a source of polymorphism and consequently of molecular markers such as insertion site-based polymorphism (ISBP) markers. Insertion site-based polymorphisms have been found to be a great source of genome-specific single-nucleotide polymorphism (SNPs) in the hexaploid wheat ( L.) genome. Here, we report on the development of a high-throughput SNP discovery approach based on sequence capture of ISBP markers. By applying this approach to the reference sequence of chromosome 3B from hexaploid wheat, we designed 39,077 SNPs that are evenly distributed along the chromosome. We demonstrate that these SNPs can be efficiently scored with the KASPar (Kompetitive allele-specific polymerase chain reaction) genotyping technology. Finally, through genetic diversity and genome-wide association studies, we also demonstrate that ISBP-derived SNPs can be used in marker-assisted breeding programs.
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Shavrukov Y. Comparison of SNP and CAPS markers application in genetic research in wheat and barley. BMC PLANT BIOLOGY 2016; 16 Suppl 1:11. [PMID: 26821936 PMCID: PMC4895257 DOI: 10.1186/s12870-015-0689-9] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2023]
Abstract
BACKGROUND Barley and bread wheat show large differences in frequencies of Single Nucleotide Polymorphism (SNP) as determined from genome-wide studies. These frequencies have been estimated as 2.4-3 times higher in the entire barley genome than within each diploid genomes of wheat (A, B or D). However, barley SNPs within individual genes occur significantly more frequently than quoted. Differences between wheat and barley are based on the origin and evolutionary history of the species. Bread wheat contains rarer SNPs due to the double genetic 'bottle-neck' created by natural hybridisation and spontaneous polyploidisation. Furthermore, wheat has the lowest level of useful SNP-derived markers while barley is estimated to have the highest level of polymorphism. RESULTS Different strategies are required for the development of suitable molecular markers in these cereal species. For example, SNP markers based on high-throughput technology (Infinium or KASP) are very effective and useful in both barley and bread wheat. In contrast, Cleaved Amplified Polymorphic Sequences (CAPS) are more widely and successfully employed in small-scale experiments with highly polymorphic genetic regions containing multiple SNPs in barley, but not in wheat. However, preliminary 'in silico' search databases for assessing the potential value of SNPs have yet to be developed. CONCLUSIONS This mini-review summarises results supporting the development of different strategies for the application of effective SNP and CAPS markers in wheat and barley.
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Affiliation(s)
- Yuri Shavrukov
- School of Agriculture, Food and Wine, University of Adelaide, Adelaide, Australia.
- Department of Biological Sciences, Flinders University, Adelaide, Australia.
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28
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Doddamani D, Khan AW, Katta MAVSK, Agarwal G, Thudi M, Ruperao P, Edwards D, Varshney RK. CicArVarDB: SNP and InDel database for advancing genetics research and breeding applications in chickpea. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2015; 2015:bav078. [PMID: 26289427 PMCID: PMC4541373 DOI: 10.1093/database/bav078] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/03/2014] [Accepted: 07/22/2015] [Indexed: 11/12/2022]
Abstract
Molecular markers are valuable tools for breeders to help accelerate crop improvement. High throughput sequencing technologies facilitate the discovery of large-scale variations such as single nucleotide polymorphisms (SNPs) and simple sequence repeats (SSRs). Sequencing of chickpea genome along with re-sequencing of several chickpea lines has enabled the discovery of 4.4 million variations including SNPs and InDels. Here we report a repository of 1.9 million variations (SNPs and InDels) anchored on eight pseudomolecules in a custom database, referred as CicArVarDB that can be accessed at http://cicarvardb.icrisat.org/. It includes an easy interface for users to select variations around specific regions associated with quantitative trait loci, with embedded webBLAST search and JBrowse visualisation. We hope that this database will be immensely useful for the chickpea research community for both advancing genetics research as well as breeding applications for crop improvement. Database URL:http://cicarvardb.icrisat.org.
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Affiliation(s)
- Dadakhalandar Doddamani
- Research Program Grain Legumes, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad 502 324, Telangana State, India
| | - Aamir W Khan
- Research Program Grain Legumes, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad 502 324, Telangana State, India
| | - Mohan A V S K Katta
- Research Program Grain Legumes, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad 502 324, Telangana State, India
| | - Gaurav Agarwal
- Research Program Grain Legumes, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad 502 324, Telangana State, India
| | - Mahendar Thudi
- Research Program Grain Legumes, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad 502 324, Telangana State, India
| | - Pradeep Ruperao
- School of Agriculture and Food Sciences, University of Queensland, St Lucia, Queensland, Australia 4072, School of Plant Biology, The University of Western Australia, Perth, Western Australia, Australia 6009 and
| | - David Edwards
- School of Plant Biology, The University of Western Australia, Perth, Western Australia, Australia 6009 and Institute of Agriculture, The University of Western Australia, Perth, Western Australia, Australia 6009
| | - Rajeev K Varshney
- Research Program Grain Legumes, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad 502 324, Telangana State, India, School of Plant Biology, The University of Western Australia, Perth, Western Australia, Australia 6009 and
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29
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Ramirez-Gonzalez RH, Segovia V, Bird N, Fenwick P, Holdgate S, Berry S, Jack P, Caccamo M, Uauy C. RNA-Seq bulked segregant analysis enables the identification of high-resolution genetic markers for breeding in hexaploid wheat. PLANT BIOTECHNOLOGY JOURNAL 2015; 13:613-24. [PMID: 25382230 DOI: 10.1111/pbi.12281] [Citation(s) in RCA: 130] [Impact Index Per Article: 14.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/24/2014] [Revised: 09/19/2014] [Accepted: 09/22/2014] [Indexed: 05/19/2023]
Abstract
The identification of genetic markers linked to genes of agronomic importance is a major aim of crop research and breeding programmes. Here, we identify markers for Yr15, a major disease resistance gene for wheat yellow rust, using a segregating F2 population. After phenotyping, we implemented RNA sequencing (RNA-Seq) of bulked pools to identify single-nucleotide polymorphisms (SNP) associated with Yr15. Over 27 000 genes with SNPs were identified between the parents, and then classified based on the results from the sequenced bulks. We calculated the bulk frequency ratio (BFR) of SNPs between resistant and susceptible bulks, selecting those showing sixfold enrichment/depletion in the corresponding bulks (BFR > 6). Using additional filtering criteria, we reduced the number of genes with a putative SNP to 175. The 35 SNPs with the highest BFR values were converted into genome-specific KASP assays using an automated bioinformatics pipeline (PolyMarker) which circumvents the limitations associated with the polyploid wheat genome. Twenty-eight assays were polymorphic of which 22 (63%) mapped in the same linkage group as Yr15. Using these markers, we mapped Yr15 to a 0.77-cM interval. The three most closely linked SNPs were tested across varieties and breeding lines representing UK elite germplasm. Two flanking markers were diagnostic in over 99% of lines tested, thus providing a reliable haplotype for marker-assisted selection in these breeding programmes. Our results demonstrate that the proposed methodology can be applied in polyploid F2 populations to generate high-resolution genetic maps across target intervals.
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Affiliation(s)
| | | | | | | | | | | | | | | | - Cristobal Uauy
- John Innes Centre, Norwich, UK
- National Institute of Agricultural Botany, Cambridge, UK
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Bayer PE, Ruperao P, Mason AS, Stiller J, Chan CKK, Hayashi S, Long Y, Meng J, Sutton T, Visendi P, Varshney RK, Batley J, Edwards D. High-resolution skim genotyping by sequencing reveals the distribution of crossovers and gene conversions in Cicer arietinum and Brassica napus. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2015; 128:1039-47. [PMID: 25754422 DOI: 10.1007/s00122-015-2488-y] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/18/2014] [Accepted: 02/24/2015] [Indexed: 05/03/2023]
Abstract
We characterise the distribution of crossover and non-crossover recombination in Brassica napus and Cicer arietinum using a low-coverage genotyping by sequencing pipeline SkimGBS. The growth of next-generation DNA sequencing technologies has led to a rapid increase in sequence-based genotyping for applications including diversity assessment, genome structure validation and gene-trait association. We have established a skim-based genotyping by sequencing method for crop plants and applied this approach to genotype-segregating populations of Brassica napus and Cicer arietinum. Comparison of progeny genotypes with those of the parental individuals allowed the identification of crossover and non-crossover (gene conversion) events. Our results identify the positions of recombination events with high resolution, permitting the mapping and frequency assessment of recombination in segregating populations.
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Affiliation(s)
- Philipp E Bayer
- School of Agriculture and Food Sciences, University of Queensland, Brisbane, 4072, Australia
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Scanning the effects of ethyl methanesulfonate on the whole genome of Lotus japonicus using second-generation sequencing analysis. G3-GENES GENOMES GENETICS 2015; 5:559-67. [PMID: 25660167 PMCID: PMC4390572 DOI: 10.1534/g3.114.014571] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
Genetic structure can be altered by chemical mutagenesis, which is a common method applied in molecular biology and genetics. Second-generation sequencing provides a platform to reveal base alterations occurring in the whole genome due to mutagenesis. A model legume, Lotus japonicus ecotype Miyakojima, was chemically mutated with alkylating ethyl methanesulfonate (EMS) for the scanning of DNA lesions throughout the genome. Using second-generation sequencing, two individually mutated third-generation progeny (M3, named AM and AS) were sequenced and analyzed to identify single nucleotide polymorphisms and reveal the effects of EMS on nucleotide sequences in these mutant genomes. Single-nucleotide polymorphisms were found in every 208 kb (AS) and 202 kb (AM) with a bias mutation of G/C-to-A/T changes at low percentage. Most mutations were intergenic. The mutation spectrum of the genomes was comparable in their individual chromosomes; however, each mutated genome has unique alterations, which are useful to identify causal mutations for their phenotypic changes. The data obtained demonstrate that whole genomic sequencing is applicable as a high-throughput tool to investigate genomic changes due to mutagenesis. The identification of these single-point mutations will facilitate the identification of phenotypically causative mutations in EMS-mutated germplasm.
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