Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Becker, Anthony, Chao, Dai-Yin, Zhang, Xu, Salt, David E., Baxter, Ivan
Formato: Texto
Lenguaje:English
Publicado: Public Library of Science 2011
Materias:
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
_version_ 1782197218402369536
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
work_keys_str_mv AT beckeranthony bulksegregantanalysisusingsinglenucleotidepolymorphismmicroarrays
AT chaodaiyin bulksegregantanalysisusingsinglenucleotidepolymorphismmicroarrays
AT zhangxu bulksegregantanalysisusingsinglenucleotidepolymorphismmicroarrays
AT saltdavide bulksegregantanalysisusingsinglenucleotidepolymorphismmicroarrays
AT baxterivan bulksegregantanalysisusingsinglenucleotidepolymorphismmicroarrays