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Target Enrichment Improves Mapping of Complex Traits by Deep Sequencing
Complex traits such as crop performance and human diseases are controlled by multiple genetic loci, many of which have small effects and often go undetected by traditional quantitative trait locus (QTL) mapping. Recently, bulked segregant analysis with large F2 pools and genome-level markers (named...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Genetics Society of America
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4704726/ https://www.ncbi.nlm.nih.gov/pubmed/26530422 http://dx.doi.org/10.1534/g3.115.023671 |
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author | Guo, Jianjun Fan, Jue Hauser, Bernard A. Rhee, Seung Y. |
author_facet | Guo, Jianjun Fan, Jue Hauser, Bernard A. Rhee, Seung Y. |
author_sort | Guo, Jianjun |
collection | PubMed |
description | Complex traits such as crop performance and human diseases are controlled by multiple genetic loci, many of which have small effects and often go undetected by traditional quantitative trait locus (QTL) mapping. Recently, bulked segregant analysis with large F2 pools and genome-level markers (named extreme-QTL or X-QTL mapping) has been used to identify many QTL. To estimate parameters impacting QTL detection for X-QTL mapping, we simulated the effects of population size, marker density, and sequencing depth of markers on QTL detectability for traits with differing heritabilities. These simulations indicate that a high (>90%) chance of detecting QTL with at least 5% effect requires 5000× sequencing depth for a trait with heritability of 0.4−0.7. For most eukaryotic organisms, whole-genome sequencing at this depth is not economically feasible. Therefore, we tested and confirmed the feasibility of applying deep sequencing of target-enriched markers for X-QTL mapping. We used two traits in Arabidopsis thaliana with different heritabilities: seed size (H(2) = 0.61) and seedling greening in response to salt (H(2) = 0.94). We used a modified G test to identify QTL regions and developed a model-based statistical framework to resolve individual peaks by incorporating recombination rates. Multiple QTL were identified for both traits, including previously undiscovered QTL. We call our method target-enriched X-QTL (TEX-QTL) mapping; this mapping approach is not limited by the genome size or the availability of recombinant inbred populations and should be applicable to many organisms and traits. |
format | Online Article Text |
id | pubmed-4704726 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Genetics Society of America |
record_format | MEDLINE/PubMed |
spelling | pubmed-47047262016-01-08 Target Enrichment Improves Mapping of Complex Traits by Deep Sequencing Guo, Jianjun Fan, Jue Hauser, Bernard A. Rhee, Seung Y. G3 (Bethesda) Investigations Complex traits such as crop performance and human diseases are controlled by multiple genetic loci, many of which have small effects and often go undetected by traditional quantitative trait locus (QTL) mapping. Recently, bulked segregant analysis with large F2 pools and genome-level markers (named extreme-QTL or X-QTL mapping) has been used to identify many QTL. To estimate parameters impacting QTL detection for X-QTL mapping, we simulated the effects of population size, marker density, and sequencing depth of markers on QTL detectability for traits with differing heritabilities. These simulations indicate that a high (>90%) chance of detecting QTL with at least 5% effect requires 5000× sequencing depth for a trait with heritability of 0.4−0.7. For most eukaryotic organisms, whole-genome sequencing at this depth is not economically feasible. Therefore, we tested and confirmed the feasibility of applying deep sequencing of target-enriched markers for X-QTL mapping. We used two traits in Arabidopsis thaliana with different heritabilities: seed size (H(2) = 0.61) and seedling greening in response to salt (H(2) = 0.94). We used a modified G test to identify QTL regions and developed a model-based statistical framework to resolve individual peaks by incorporating recombination rates. Multiple QTL were identified for both traits, including previously undiscovered QTL. We call our method target-enriched X-QTL (TEX-QTL) mapping; this mapping approach is not limited by the genome size or the availability of recombinant inbred populations and should be applicable to many organisms and traits. Genetics Society of America 2015-10-30 /pmc/articles/PMC4704726/ /pubmed/26530422 http://dx.doi.org/10.1534/g3.115.023671 Text en Copyright © 2016 Guo et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Investigations Guo, Jianjun Fan, Jue Hauser, Bernard A. Rhee, Seung Y. Target Enrichment Improves Mapping of Complex Traits by Deep Sequencing |
title | Target Enrichment Improves Mapping of Complex Traits by Deep Sequencing |
title_full | Target Enrichment Improves Mapping of Complex Traits by Deep Sequencing |
title_fullStr | Target Enrichment Improves Mapping of Complex Traits by Deep Sequencing |
title_full_unstemmed | Target Enrichment Improves Mapping of Complex Traits by Deep Sequencing |
title_short | Target Enrichment Improves Mapping of Complex Traits by Deep Sequencing |
title_sort | target enrichment improves mapping of complex traits by deep sequencing |
topic | Investigations |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4704726/ https://www.ncbi.nlm.nih.gov/pubmed/26530422 http://dx.doi.org/10.1534/g3.115.023671 |
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