GWAS case studies in wheat
With the advancements in next-generation sequencing technologies, leading to millions of single nucleotide polymorphisms in all crop species including wheat, genome-wide association study (GWAS) has become a leading approach for trait dissection. In wheat, GWAS has been conducted for a plethora of t...
| Autores principales: | , |
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| Formato: | Capítulo de libro |
| Lenguaje: | Inglés |
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Springer
2022
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/126248 |
| _version_ | 1855522573987610624 |
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| author | Sehgal, Deepmala Dreisigacker, Susanne |
| author_browse | Dreisigacker, Susanne Sehgal, Deepmala |
| author_facet | Sehgal, Deepmala Dreisigacker, Susanne |
| author_sort | Sehgal, Deepmala |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | With the advancements in next-generation sequencing technologies, leading to millions of single nucleotide polymorphisms in all crop species including wheat, genome-wide association study (GWAS) has become a leading approach for trait dissection. In wheat, GWAS has been conducted for a plethora of traits and more and more studies are being conducted and reported in journals. While application of GWAS has become a routine in wheat using the standardized approaches, there has been a great leap forward using newer models and combination of GWAS with other sets of data. This chapter has reviewed all these latest advancements in GWAS in wheat by citing the most important studies and their outputs. Specially, we have focused on studies that conducted meta-GWAS, multilocus GWAS, haplotype-based GWAS, Environmental- and Eigen-GWAS, and/or GWAS combined with gene regulatory network and pathway analyses or epistatic interactions analyses; all these have taken the association mapping approach to new heights in wheat. |
| format | Book Chapter |
| id | CGSpace126248 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2022 |
| publishDateRange | 2022 |
| publishDateSort | 2022 |
| publisher | Springer |
| publisherStr | Springer |
| record_format | dspace |
| spelling | CGSpace1262482023-12-08T19:36:04Z GWAS case studies in wheat Sehgal, Deepmala Dreisigacker, Susanne genetics haplotypes phenotypes quantitative trait loci wheat With the advancements in next-generation sequencing technologies, leading to millions of single nucleotide polymorphisms in all crop species including wheat, genome-wide association study (GWAS) has become a leading approach for trait dissection. In wheat, GWAS has been conducted for a plethora of traits and more and more studies are being conducted and reported in journals. While application of GWAS has become a routine in wheat using the standardized approaches, there has been a great leap forward using newer models and combination of GWAS with other sets of data. This chapter has reviewed all these latest advancements in GWAS in wheat by citing the most important studies and their outputs. Specially, we have focused on studies that conducted meta-GWAS, multilocus GWAS, haplotype-based GWAS, Environmental- and Eigen-GWAS, and/or GWAS combined with gene regulatory network and pathway analyses or epistatic interactions analyses; all these have taken the association mapping approach to new heights in wheat. 2022 2022-12-22T13:08:05Z 2022-12-22T13:08:05Z Book Chapter https://hdl.handle.net/10568/126248 en Limited Access Springer Sehgal, D., & Dreisigacker, S. (2022). GWAS case studies in wheat. In D. Torkamaneh & F. Belzile (Eds.), Genome-Wide Association Studies (Vol. 2481, pp. 341–351). Springer US. |
| spellingShingle | genetics haplotypes phenotypes quantitative trait loci wheat Sehgal, Deepmala Dreisigacker, Susanne GWAS case studies in wheat |
| title | GWAS case studies in wheat |
| title_full | GWAS case studies in wheat |
| title_fullStr | GWAS case studies in wheat |
| title_full_unstemmed | GWAS case studies in wheat |
| title_short | GWAS case studies in wheat |
| title_sort | gwas case studies in wheat |
| topic | genetics haplotypes phenotypes quantitative trait loci wheat |
| url | https://hdl.handle.net/10568/126248 |
| work_keys_str_mv | AT sehgaldeepmala gwascasestudiesinwheat AT dreisigackersusanne gwascasestudiesinwheat |