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Discovery of single nucleotide polymorphisms in complex genomes using SGSautoSNP

Discovery of single nucleotide polymorphisms in complex genomes using SGSautoSNP

Lorenc, Michał T., Hayashi, Satomi, Stiller, Jiri, Lee, Hong, Manoli, Sahana, Ruperao, Pradeep, Visendi, Paul, Berkman, Paul J., Lai, Kaitao, Batley, Jacqueline and Edwards, David (2012) Discovery of single nucleotide polymorphisms in complex genomes using SGSautoSNP. Biology, 1 (3). pp. 370-382. ISSN 2079-7737 (Print), 2079-7737 (Online) (doi:https://doi.org/10.3390/biology1020370)

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Abstract

Single nucleotide polymorphisms (SNPs) are becoming the dominant form of molecular marker for genetic and genomic analysis. The advances in second generation DNA sequencing provide opportunities to identify very large numbers of SNPs in a range of species. However, SNP identification remains a challenge for large and polyploid genomes due to their size and complexity. We have developed a pipeline for the robust identification of SNPs in large and complex genomes using Illumina second generation DNA sequence data and demonstrated this by the discovery of SNPs in the hexaploid wheat genome. We have developed a SNP discovery pipeline called SGSautoSNP (Second-Generation Sequencing AutoSNP) and applied this to discover more than 800,000 SNPs between four hexaploid wheat cultivars across chromosomes 7A, 7B and 7D. All SNPs are presented for download and viewing within a public GBrowse database.

Item Type: Article
Uncontrolled Keywords: single nucleotide polymorphisms; wheat; autoSNP; genome diversity; genotyping by sequencing; haplotype
Subjects: S Agriculture > S Agriculture (General)
Faculty / Department / Research Group: Faculty of Engineering & Science
Faculty of Engineering & Science > Natural Resources Institute
Faculty of Engineering & Science > Natural Resources Institute > Agriculture, Health & Environment Department
Faculty of Engineering & Science > Natural Resources Institute > Molecular Virology and Entomology Research Group
Last Modified: 03 Nov 2017 12:15
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: None
URI: http://gala.gre.ac.uk/id/eprint/17915

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