Back to Search Start Over

PigVar: a database of pig variations and positive selection signatures.

Authors :
Zhong-Yin Zhou
Aimin Li
Otecko, Newton O.
Yan-Hu Liu
Irwin, David M.
Lu Wang
Adeola, Adeniyi C.
Junying Zhang
Hai-Bing Xie
Ya-Ping Zhang
Source :
Database: The Journal of Biological Databases & Curation. 2017, Vol. 2017 Issue 1, p1-10. 10p. 2 Color Photographs, 1 Diagram, 1 Chart, 2 Graphs.
Publication Year :
2017

Abstract

Pigs are excellent large-animal models for medical research and a promising organ donor source for transplant patients. Next-generation sequencing technology has yielded a dramatic increase in the volume of genomic data for pigs. However, the limited amount of variation data provided by dbSNP, and non-congruent criteria used for calling variation, present considerable hindrances to the utility of this data. We used a uniform pipeline, based on GATK, to identify non-redundant, high-quality, whole-genome SNPs from 280 pigs and 6 outgroup species. A total of 64.6 million SNPs were identified in 280 pigs and 36.8 million in the outgroups. We then used LUMPY to identify a total of 7 236 813 structural variations (SVs) in 211 pigs. Positively selected loci were identified through five statistical tests of different evolutionary attributes of the SNPs. Combining the non-redundant variations and the evolutionary selective scores, we built the first pig-specific variation database, PigVar (http://www.ibiomedical.net/pigvar/), which is a web-based open-access resource. PigVar collects parameters of the variations including summary lists of the locations of the variations within protein-coding and long intergenic non-coding RNA (lincRNA) genes, whether the SNPs are synonymous or non-synonymous, their ancestral and derived states, geographic sampling locations, as well as breed information. The PigVar database will be kept operational and updated to facilitate medical research using the pig as model and agricultural research including pig breeding. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
17580463
Volume :
2017
Issue :
1
Database :
Academic Search Index
Journal :
Database: The Journal of Biological Databases & Curation
Publication Type :
Academic Journal
Accession number :
126912391
Full Text :
https://doi.org/10.1093/database/bax048