SNP discovery in swine by reduced representation and high throughput pyrosequencing.

Abstract:

BACKGROUND:Relatively little information is available for sequence variation in the pig. We previously used a combination of short read (25 base pair) high-throughput sequencing and reduced genomic representation to discover > 60,000 single nucleotide polymorphisms (SNP) in cattle, but the current lack of complete genome sequence limits this approach in swine. Longer-read pyrosequencing-based technologies have the potential to overcome this limitation by providing sufficient flanking sequence information for assay design. Swine SNP were discovered in the present study using a reduced representation of 450 base pair (bp) porcine genomic fragments (approximately 4% of the swine genome) prepared from a pool of 26 animals relevant to current pork production, and a GS-FLX instrument producing 240 bp reads. RESULTS:Approximately 5 million sequence reads were collected and assembled into contigs having an overall observed depth of 7.65-fold coverage. The approximate minor allele frequency was estimated from the number of observations of the alternate alleles. The average coverage at the SNPs was 12.6-fold. This approach identified 115,572 SNPs in 47,830 contigs. Comparison to partial swine genome draft sequence indicated 49,879 SNP (43%) and 22,045 contigs (46%) mapped to a position on a sequenced pig chromosome and the distribution was essentially random. A sample of 176 putative SNPs was examined and 168 (95.5%) were confirmed to have segregating alleles; the correlation of the observed minor allele frequency (MAF) to that predicted from the sequence data was 0.58. CONCLUSION:The process was an efficient means to identify a large number of porcine SNP having high validation rate to be used in an ongoing international collaboration to produce a highly parallel genotyping assay for swine. By using a conservative approach, a robust group of SNPs were detected with greater confidence and relatively high MAF that should be suitable for genotyping in a wide variety of commercial populations.

journal_name

BMC Genet

journal_title

BMC genetics

authors

Wiedmann RT,Smith TP,Nonneman DJ

doi

10.1186/1471-2156-9-81

subject

Has Abstract

pub_date

2008-12-04 00:00:00

pages

81

issn

1471-2156

pii

1471-2156-9-81

journal_volume

9

pub_type

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