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Bulk Segregant Analysis Using Single Nucleotide Polymorphism Microarrays
Bulk segregant analysis (BSA) using microarrays, and extreme array mapping (XAM) have recently been used to rapidly identify genomic regions associated with phenotypes in multiple species. These experiments, however, require the identification of single feature polymorphisms (SFP) between the cross...
Autores principales: | , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2011
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3029305/ https://www.ncbi.nlm.nih.gov/pubmed/21297997 http://dx.doi.org/10.1371/journal.pone.0015993 |
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author | Becker, Anthony Chao, Dai-Yin Zhang, Xu Salt, David E. Baxter, Ivan |
author_facet | Becker, Anthony Chao, Dai-Yin Zhang, Xu Salt, David E. Baxter, Ivan |
author_sort | Becker, Anthony |
collection | PubMed |
description | Bulk segregant analysis (BSA) using microarrays, and extreme array mapping (XAM) have recently been used to rapidly identify genomic regions associated with phenotypes in multiple species. These experiments, however, require the identification of single feature polymorphisms (SFP) between the cross parents for each new combination of genotypes, which raises the cost of experiments. The availability of the genomic polymorphism data in Arabidopsis thaliana, coupled with the efficient designs of Single Nucleotide Polymorphism (SNP) genotyping arrays removes the requirement for SFP detection and lowers the per array cost, thereby lowering the overall cost per experiment. To demonstrate that these approaches would be functional on SNP arrays and determine confidence intervals, we analyzed hybridizations of natural accessions to the Arabidopsis ATSNPTILE array and simulated BSA or XAM given a variety of gene models, populations, and bulk selection parameters. Our results show a striking degree of correlation between the genotyping output of both methods, which suggests that the benefit of SFP genotyping in context of BSA can be had with the cheaper, more efficient SNP arrays. As a final proof of concept, we hybridized the DNA from bulks of an F2 mapping population of a Sulfur and Selenium ionomics mutant to both the Arabidopsis ATTILE1R and ATSNPTILE arrays, which produced almost identical results. We have produced R scripts that prompt the user for the required parameters and perform the BSA analysis using the ATSNPTILE1 array and have provided them as supplemental data files. |
format | Text |
id | pubmed-3029305 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-30293052011-02-04 Bulk Segregant Analysis Using Single Nucleotide Polymorphism Microarrays Becker, Anthony Chao, Dai-Yin Zhang, Xu Salt, David E. Baxter, Ivan PLoS One Research Article Bulk segregant analysis (BSA) using microarrays, and extreme array mapping (XAM) have recently been used to rapidly identify genomic regions associated with phenotypes in multiple species. These experiments, however, require the identification of single feature polymorphisms (SFP) between the cross parents for each new combination of genotypes, which raises the cost of experiments. The availability of the genomic polymorphism data in Arabidopsis thaliana, coupled with the efficient designs of Single Nucleotide Polymorphism (SNP) genotyping arrays removes the requirement for SFP detection and lowers the per array cost, thereby lowering the overall cost per experiment. To demonstrate that these approaches would be functional on SNP arrays and determine confidence intervals, we analyzed hybridizations of natural accessions to the Arabidopsis ATSNPTILE array and simulated BSA or XAM given a variety of gene models, populations, and bulk selection parameters. Our results show a striking degree of correlation between the genotyping output of both methods, which suggests that the benefit of SFP genotyping in context of BSA can be had with the cheaper, more efficient SNP arrays. As a final proof of concept, we hybridized the DNA from bulks of an F2 mapping population of a Sulfur and Selenium ionomics mutant to both the Arabidopsis ATTILE1R and ATSNPTILE arrays, which produced almost identical results. We have produced R scripts that prompt the user for the required parameters and perform the BSA analysis using the ATSNPTILE1 array and have provided them as supplemental data files. Public Library of Science 2011-01-27 /pmc/articles/PMC3029305/ /pubmed/21297997 http://dx.doi.org/10.1371/journal.pone.0015993 Text en This is an open-access article distributed under the terms of the Creative Commons Public Domain declaration which stipulates that, once placed in the public domain, this work may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. https://creativecommons.org/publicdomain/zero/1.0/ This is an open-access article distributed under the terms of the Creative Commons Public Domain declaration, which stipulates that, once placed in the public domain, this work may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. |
spellingShingle | Research Article Becker, Anthony Chao, Dai-Yin Zhang, Xu Salt, David E. Baxter, Ivan Bulk Segregant Analysis Using Single Nucleotide Polymorphism Microarrays |
title | Bulk Segregant Analysis Using Single Nucleotide Polymorphism Microarrays |
title_full | Bulk Segregant Analysis Using Single Nucleotide Polymorphism Microarrays |
title_fullStr | Bulk Segregant Analysis Using Single Nucleotide Polymorphism Microarrays |
title_full_unstemmed | Bulk Segregant Analysis Using Single Nucleotide Polymorphism Microarrays |
title_short | Bulk Segregant Analysis Using Single Nucleotide Polymorphism Microarrays |
title_sort | bulk segregant analysis using single nucleotide polymorphism microarrays |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3029305/ https://www.ncbi.nlm.nih.gov/pubmed/21297997 http://dx.doi.org/10.1371/journal.pone.0015993 |
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