Sampling strategies for genotyping common bean (Phaseolus vulgaris L.) Genebank accessions with DArTseq: a comparison of single plants, multiple plants, and DNA pools
Introduction Genotyping large-scale gene bank collections requires an appropriate sampling strategy to represent the diversity within and between accessions. Methods A panel of 44 common bean ( Phaseolus vulgaris L.) landraces from the Alliance Bioversity and The Alliance of Bioversity International...
| Main Authors: | , , , |
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| Format: | Journal Article |
| Language: | Inglés |
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Frontiers Media
2024
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| Online Access: | https://hdl.handle.net/10568/149257 |
| _version_ | 1855531962211500032 |
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| author | Correa Abondano, Miguel Ospina, Jessica Alejandra Wenzl, Peter Carvajal-Yepes, Monica |
| author_browse | Carvajal-Yepes, Monica Correa Abondano, Miguel Ospina, Jessica Alejandra Wenzl, Peter |
| author_facet | Correa Abondano, Miguel Ospina, Jessica Alejandra Wenzl, Peter Carvajal-Yepes, Monica |
| author_sort | Correa Abondano, Miguel |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Introduction Genotyping large-scale gene bank collections requires an appropriate sampling strategy to represent the diversity within and between accessions. Methods A panel of 44 common bean ( Phaseolus vulgaris L.) landraces from the Alliance Bioversity and The Alliance of Bioversity International and the International Center for Tropical Agriculture (CIAT) gene bank was genotyped with DArTseq using three sampling strategies: a single plant per accession, 25 individual plants per accession jointly analyzed after genotyping ( in silico–pool ), and by pooling tissue from 25 individual plants per accession ( seq-pool ). Sampling strategies were compared to assess the technical aspects of the samples, the marker information content, and the genetic composition of the panel. Results The seq-pool strategy resulted in more consistent DNA libraries for quality and call rate, although with fewer polymorphic markers (6,142 single-nucleotide polymorphisms) than the in silico–pool (14,074) or the single plant sets (6,555). Estimates of allele frequencies by seq-pool and in silico–pool genotyping were consistent, but the results suggest that the difference between pools depends on population heterogeneity. Principal coordinate analysis, hierarchical clustering, and the estimation of admixture coefficients derived from a single plant, in silico – pool , and seq-pool successfully identified the well-known structure of Andean and Mesoamerican gene pools of P. vulgaris across all datasets. Conclusion In conclusion, seq-pool proved to be a viable approach for characterizing common bean germplasm compared to genotyping individual plants separately by balancing genotyping effort and costs. This study provides insights and serves as a valuable guide for gene bank researchers embarking on genotyping initiatives to characterize their collections. It aids curators in effectively managing the collections and facilitates marker-trait association studies, enabling the identification of candidate markers for key traits. |
| format | Journal Article |
| id | CGSpace149257 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2024 |
| publishDateRange | 2024 |
| publishDateSort | 2024 |
| publisher | Frontiers Media |
| publisherStr | Frontiers Media |
| record_format | dspace |
| spelling | CGSpace1492572025-12-08T10:29:22Z Sampling strategies for genotyping common bean (Phaseolus vulgaris L.) Genebank accessions with DArTseq: a comparison of single plants, multiple plants, and DNA pools Correa Abondano, Miguel Ospina, Jessica Alejandra Wenzl, Peter Carvajal-Yepes, Monica common beans gene banks genetic resources genotyping sampling Introduction Genotyping large-scale gene bank collections requires an appropriate sampling strategy to represent the diversity within and between accessions. Methods A panel of 44 common bean ( Phaseolus vulgaris L.) landraces from the Alliance Bioversity and The Alliance of Bioversity International and the International Center for Tropical Agriculture (CIAT) gene bank was genotyped with DArTseq using three sampling strategies: a single plant per accession, 25 individual plants per accession jointly analyzed after genotyping ( in silico–pool ), and by pooling tissue from 25 individual plants per accession ( seq-pool ). Sampling strategies were compared to assess the technical aspects of the samples, the marker information content, and the genetic composition of the panel. Results The seq-pool strategy resulted in more consistent DNA libraries for quality and call rate, although with fewer polymorphic markers (6,142 single-nucleotide polymorphisms) than the in silico–pool (14,074) or the single plant sets (6,555). Estimates of allele frequencies by seq-pool and in silico–pool genotyping were consistent, but the results suggest that the difference between pools depends on population heterogeneity. Principal coordinate analysis, hierarchical clustering, and the estimation of admixture coefficients derived from a single plant, in silico – pool , and seq-pool successfully identified the well-known structure of Andean and Mesoamerican gene pools of P. vulgaris across all datasets. Conclusion In conclusion, seq-pool proved to be a viable approach for characterizing common bean germplasm compared to genotyping individual plants separately by balancing genotyping effort and costs. This study provides insights and serves as a valuable guide for gene bank researchers embarking on genotyping initiatives to characterize their collections. It aids curators in effectively managing the collections and facilitates marker-trait association studies, enabling the identification of candidate markers for key traits. 2024-07-11 2024-07-25T08:26:22Z 2024-07-25T08:26:22Z Journal Article https://hdl.handle.net/10568/149257 en Open Access application/pdf Frontiers Media Correa Abondano, M.; Ospina, J.A.; Wenzl, P.; Carvajal-Yepes, M. (2024) Sampling strategies for genotyping common bean (Phaseolus vulgaris L.) Genebank accessions with DArTseq: a comparison of single plants, multiple plants, and DNA pools. Frontiers in Plant Science 15:1338332. ISSN: 1664-462X |
| spellingShingle | common beans gene banks genetic resources genotyping sampling Correa Abondano, Miguel Ospina, Jessica Alejandra Wenzl, Peter Carvajal-Yepes, Monica Sampling strategies for genotyping common bean (Phaseolus vulgaris L.) Genebank accessions with DArTseq: a comparison of single plants, multiple plants, and DNA pools |
| title | Sampling strategies for genotyping common bean (Phaseolus vulgaris L.) Genebank accessions with DArTseq: a comparison of single plants, multiple plants, and DNA pools |
| title_full | Sampling strategies for genotyping common bean (Phaseolus vulgaris L.) Genebank accessions with DArTseq: a comparison of single plants, multiple plants, and DNA pools |
| title_fullStr | Sampling strategies for genotyping common bean (Phaseolus vulgaris L.) Genebank accessions with DArTseq: a comparison of single plants, multiple plants, and DNA pools |
| title_full_unstemmed | Sampling strategies for genotyping common bean (Phaseolus vulgaris L.) Genebank accessions with DArTseq: a comparison of single plants, multiple plants, and DNA pools |
| title_short | Sampling strategies for genotyping common bean (Phaseolus vulgaris L.) Genebank accessions with DArTseq: a comparison of single plants, multiple plants, and DNA pools |
| title_sort | sampling strategies for genotyping common bean phaseolus vulgaris l genebank accessions with dartseq a comparison of single plants multiple plants and dna pools |
| topic | common beans gene banks genetic resources genotyping sampling |
| url | https://hdl.handle.net/10568/149257 |
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