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SNP discovery by high-throughput sequencing in soybean
BACKGROUND: With the advance of new massively parallel genotyping technologies, quantitative trait loci (QTL) fine mapping and map-based cloning become more achievable in identifying genes for important and complex traits. Development of high-density genetic markers in the QTL regions of specific ma...
Autores principales: | , , , , , |
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2010
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3091665/ https://www.ncbi.nlm.nih.gov/pubmed/20701770 http://dx.doi.org/10.1186/1471-2164-11-469 |
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author | Wu, Xiaolei Ren, Chengwei Joshi, Trupti Vuong, Tri Xu, Dong Nguyen, Henry T |
author_facet | Wu, Xiaolei Ren, Chengwei Joshi, Trupti Vuong, Tri Xu, Dong Nguyen, Henry T |
author_sort | Wu, Xiaolei |
collection | PubMed |
description | BACKGROUND: With the advance of new massively parallel genotyping technologies, quantitative trait loci (QTL) fine mapping and map-based cloning become more achievable in identifying genes for important and complex traits. Development of high-density genetic markers in the QTL regions of specific mapping populations is essential for fine-mapping and map-based cloning of economically important genes. Single nucleotide polymorphisms (SNPs) are the most abundant form of genetic variation existing between any diverse genotypes that are usually used for QTL mapping studies. The massively parallel sequencing technologies (Roche GS/454, Illumina GA/Solexa, and ABI/SOLiD), have been widely applied to identify genome-wide sequence variations. However, it is still remains unclear whether sequence data at a low sequencing depth are enough to detect the variations existing in any QTL regions of interest in a crop genome, and how to prepare sequencing samples for a complex genome such as soybean. Therefore, with the aims of identifying SNP markers in a cost effective way for fine-mapping several QTL regions, and testing the validation rate of the putative SNPs predicted with Solexa short sequence reads at a low sequencing depth, we evaluated a pooled DNA fragment reduced representation library and SNP detection methods applied to short read sequences generated by Solexa high-throughput sequencing technology. RESULTS: A total of 39,022 putative SNPs were identified by the Illumina/Solexa sequencing system using a reduced representation DNA library of two parental lines of a mapping population. The validation rates of these putative SNPs predicted with low and high stringency were 72% and 85%, respectively. One hundred sixty four SNP markers resulted from the validation of putative SNPs and have been selectively chosen to target a known QTL, thereby increasing the marker density of the targeted region to one marker per 42 K bp. CONCLUSIONS: We have demonstrated how to quickly identify large numbers of SNPs for fine mapping of QTL regions by applying massively parallel sequencing combined with genome complexity reduction techniques. This SNP discovery approach is more efficient for targeting multiple QTL regions in a same genetic population, which can be applied to other crops. |
format | Text |
id | pubmed-3091665 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-30916652011-05-11 SNP discovery by high-throughput sequencing in soybean Wu, Xiaolei Ren, Chengwei Joshi, Trupti Vuong, Tri Xu, Dong Nguyen, Henry T BMC Genomics Research Article BACKGROUND: With the advance of new massively parallel genotyping technologies, quantitative trait loci (QTL) fine mapping and map-based cloning become more achievable in identifying genes for important and complex traits. Development of high-density genetic markers in the QTL regions of specific mapping populations is essential for fine-mapping and map-based cloning of economically important genes. Single nucleotide polymorphisms (SNPs) are the most abundant form of genetic variation existing between any diverse genotypes that are usually used for QTL mapping studies. The massively parallel sequencing technologies (Roche GS/454, Illumina GA/Solexa, and ABI/SOLiD), have been widely applied to identify genome-wide sequence variations. However, it is still remains unclear whether sequence data at a low sequencing depth are enough to detect the variations existing in any QTL regions of interest in a crop genome, and how to prepare sequencing samples for a complex genome such as soybean. Therefore, with the aims of identifying SNP markers in a cost effective way for fine-mapping several QTL regions, and testing the validation rate of the putative SNPs predicted with Solexa short sequence reads at a low sequencing depth, we evaluated a pooled DNA fragment reduced representation library and SNP detection methods applied to short read sequences generated by Solexa high-throughput sequencing technology. RESULTS: A total of 39,022 putative SNPs were identified by the Illumina/Solexa sequencing system using a reduced representation DNA library of two parental lines of a mapping population. The validation rates of these putative SNPs predicted with low and high stringency were 72% and 85%, respectively. One hundred sixty four SNP markers resulted from the validation of putative SNPs and have been selectively chosen to target a known QTL, thereby increasing the marker density of the targeted region to one marker per 42 K bp. CONCLUSIONS: We have demonstrated how to quickly identify large numbers of SNPs for fine mapping of QTL regions by applying massively parallel sequencing combined with genome complexity reduction techniques. This SNP discovery approach is more efficient for targeting multiple QTL regions in a same genetic population, which can be applied to other crops. BioMed Central 2010-08-11 /pmc/articles/PMC3091665/ /pubmed/20701770 http://dx.doi.org/10.1186/1471-2164-11-469 Text en Copyright ©2010 Wu et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Wu, Xiaolei Ren, Chengwei Joshi, Trupti Vuong, Tri Xu, Dong Nguyen, Henry T SNP discovery by high-throughput sequencing in soybean |
title | SNP discovery by high-throughput sequencing in soybean |
title_full | SNP discovery by high-throughput sequencing in soybean |
title_fullStr | SNP discovery by high-throughput sequencing in soybean |
title_full_unstemmed | SNP discovery by high-throughput sequencing in soybean |
title_short | SNP discovery by high-throughput sequencing in soybean |
title_sort | snp discovery by high-throughput sequencing in soybean |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3091665/ https://www.ncbi.nlm.nih.gov/pubmed/20701770 http://dx.doi.org/10.1186/1471-2164-11-469 |
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