Criteria for evaluating molecular markers: Comprehensive quality metrics to improve marker-assisted selection
Despite strong interest over many years, the usage of quantitative trait loci in plant breeding has often failed to live up to expectations. A key weak point in the utilisation of QTLs is the “quality” of markers used during marker-assisted selection (MAS): unreliable markers result in variable outc...
| Main Authors: | , , |
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| Format: | Journal Article |
| Language: | Inglés |
| Published: |
Public Library of Science
2019
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| Online Access: | https://hdl.handle.net/10568/164743 |
| _version_ | 1855543325780606976 |
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| author | Platten, John Damien Cobb, Joshua Nathaniel Zantua, Rochelle E. |
| author_browse | Cobb, Joshua Nathaniel Platten, John Damien Zantua, Rochelle E. |
| author_facet | Platten, John Damien Cobb, Joshua Nathaniel Zantua, Rochelle E. |
| author_sort | Platten, John Damien |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Despite strong interest over many years, the usage of quantitative trait loci in plant breeding has often failed to live up to expectations. A key weak point in the utilisation of QTLs is the “quality” of markers used during marker-assisted selection (MAS): unreliable markers result in variable outcomes, leading to a perception that MAS products fail to achieve reliable improvement. Most reports of markers used for MAS focus on markers derived from the mapping population. There are very few studies that examine the reliability of these markers in other genetic backgrounds, and critically, no metrics exist to describe and quantify this reliability. To improve the MAS process, this work proposes five core metrics that fully describe the reliability of a marker. These metrics give a comprehensive and quantitative measure of the ability of a marker to correctly classify germplasm as QTL[+]/[–], particularly against a background of high allelic diversity. Markers that score well on these metrics will have far higher reliability in breeding, and deficiencies in specific metrics give information on circumstances under which a marker may not be reliable. The metrics are applicable across different marker types and platforms, allowing an objective comparison of the performance of different markers irrespective of the platform. Evaluating markers using these metrics demonstrates that trait-specific markers consistently out-perform markers designed for other purposes. These metrics also provide a superb set of criteria for designing superior marker systems for a target QTL, enabling the selection of an optimal marker set before committing to design. |
| format | Journal Article |
| id | CGSpace164743 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2019 |
| publishDateRange | 2019 |
| publishDateSort | 2019 |
| publisher | Public Library of Science |
| publisherStr | Public Library of Science |
| record_format | dspace |
| spelling | CGSpace1647432025-01-24T14:21:05Z Criteria for evaluating molecular markers: Comprehensive quality metrics to improve marker-assisted selection Platten, John Damien Cobb, Joshua Nathaniel Zantua, Rochelle E. Despite strong interest over many years, the usage of quantitative trait loci in plant breeding has often failed to live up to expectations. A key weak point in the utilisation of QTLs is the “quality” of markers used during marker-assisted selection (MAS): unreliable markers result in variable outcomes, leading to a perception that MAS products fail to achieve reliable improvement. Most reports of markers used for MAS focus on markers derived from the mapping population. There are very few studies that examine the reliability of these markers in other genetic backgrounds, and critically, no metrics exist to describe and quantify this reliability. To improve the MAS process, this work proposes five core metrics that fully describe the reliability of a marker. These metrics give a comprehensive and quantitative measure of the ability of a marker to correctly classify germplasm as QTL[+]/[–], particularly against a background of high allelic diversity. Markers that score well on these metrics will have far higher reliability in breeding, and deficiencies in specific metrics give information on circumstances under which a marker may not be reliable. The metrics are applicable across different marker types and platforms, allowing an objective comparison of the performance of different markers irrespective of the platform. Evaluating markers using these metrics demonstrates that trait-specific markers consistently out-perform markers designed for other purposes. These metrics also provide a superb set of criteria for designing superior marker systems for a target QTL, enabling the selection of an optimal marker set before committing to design. 2019-01-15 2024-12-19T12:54:14Z 2024-12-19T12:54:14Z Journal Article https://hdl.handle.net/10568/164743 en Open Access Public Library of Science Platten, John Damien; Cobb, Joshua Nathaniel and Zantua, Rochelle E. 2019. Criteria for evaluating molecular markers: Comprehensive quality metrics to improve marker-assisted selection. PLoS ONE, Volume 14 no. 1 p. e0210529 |
| spellingShingle | Platten, John Damien Cobb, Joshua Nathaniel Zantua, Rochelle E. Criteria for evaluating molecular markers: Comprehensive quality metrics to improve marker-assisted selection |
| title | Criteria for evaluating molecular markers: Comprehensive quality metrics to improve marker-assisted selection |
| title_full | Criteria for evaluating molecular markers: Comprehensive quality metrics to improve marker-assisted selection |
| title_fullStr | Criteria for evaluating molecular markers: Comprehensive quality metrics to improve marker-assisted selection |
| title_full_unstemmed | Criteria for evaluating molecular markers: Comprehensive quality metrics to improve marker-assisted selection |
| title_short | Criteria for evaluating molecular markers: Comprehensive quality metrics to improve marker-assisted selection |
| title_sort | criteria for evaluating molecular markers comprehensive quality metrics to improve marker assisted selection |
| url | https://hdl.handle.net/10568/164743 |
| work_keys_str_mv | AT plattenjohndamien criteriaforevaluatingmolecularmarkerscomprehensivequalitymetricstoimprovemarkerassistedselection AT cobbjoshuanathaniel criteriaforevaluatingmolecularmarkerscomprehensivequalitymetricstoimprovemarkerassistedselection AT zantuarochellee criteriaforevaluatingmolecularmarkerscomprehensivequalitymetricstoimprovemarkerassistedselection |