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Identification of candidate genes and mutations in QTL regions for chicken growth using bioinformatic analysis of NGS and SNP-chip data

Ahsan, Muhammad and Xidan, Li and Lundberg, Andreas E and Kierczak, Marcin and Siegel, Paul B. and Carlborg, Örjan and Marklund, Stefan (2013). Identification of candidate genes and mutations in QTL regions for chicken growth using bioinformatic analysis of NGS and SNP-chip data. Frontiers in genetics. 4, 1-8
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Official URL: http://dx.doi.org/10.3389/fgene.2013.00226

Abstract

Mapping of chromosomal regions harboring genetic polymorphisms that regulate complex traits is usually followed by a search for the causative mutations underlying the observed effects. This is often a challenging task even after fine mapping, as millions of base pairs including many genes will typically need to be investigated. Thus to trace the causative mutation(s) there is a great need for efficient bioinformatic strategies. Here, we searched for genes and mutations regulating growth in the Virginia chicken lines – an experimental population comprising two lines that have been divergently selected for body weight at 56 days for more than 50 generations. Several quantitative trait loci (QTL) have been mapped in an F2 intercross between the lines, and the regions have subsequently been replicated and fine mapped using an Advanced Intercross Line. We have further analyzed the QTL regions where the largest genetic divergence between the High-Weight selected (HWS) and Low-Weight selected (LWS) lines was observed. Such regions, covering about 37% of the actual QTL regions, were identified by comparing the allele frequencies of the HWS and LWS lines using both individual 60K SNP chip genotyping of birds and analysis of read proportions from genome resequencing of DNA pools. Based on a combination of criteria including significance of the QTL, allele frequency difference of identified mutations between the selected lines, gene information on relevance for growth, and the predicted functional effects of identified mutations we propose here a subset of candidate mutations of highest priority for further evaluation in functional studies. The candidate mutations were identified within the GCG, IGFBP2, GRB14, CRIM1, FGF16, VEGFR-2, ALG11, EDN1, SNX6, and BIRC7 genes. We believe that the proposed method of combining different types of genomic information increases the probability that the genes underlying the observed QTL effects are represented among the candidate mutations identified.

Authors/Creators:Ahsan, Muhammad and Xidan, Li and Lundberg, Andreas E and Kierczak, Marcin and Siegel, Paul B. and Carlborg, Örjan and Marklund, Stefan
Title:Identification of candidate genes and mutations in QTL regions for chicken growth using bioinformatic analysis of NGS and SNP-chip data
Series/Journal:Frontiers in genetics (1664-8021)
Year of publishing :2013
Volume:4
Page range:1-8
Number of Pages:8
Publisher:Frontiers
ISSN:1664-8021
Language:English
Additional Information:This document is protected by copyright and was first published by Frontiers. All rights reserved. It is reproduced with permission.
Publication Type:Journal article
Refereed:Yes
Article category:Scientific peer reviewed
Version:Published version
Full Text Status:Public
Agris subject categories.:L Animal production > L10 Animal genetics and breeding
X Agricola extesions > X30 Life sciences
Subjects:(A) Swedish standard research categories 2011 > 1 Natural sciences > 106 Biological Sciences (Medical to be 3 and Agricultural to be 4) > Bioinformatics and Systems Biology (methods development to be 10203)
(A) Swedish standard research categories 2011 > 1 Natural sciences > 106 Biological Sciences (Medical to be 3 and Agricultural to be 4) > Genetics (medical genetics to be 30107 and agricultural genetics to be 40402)
Agrovoc terms:genetic divergence, QTL (quantitative trait loci), growth
Keywords:candidate genes , growth, functional prediction, genetic divergence, QTL, SNP, resequencing
URN:NBN:urn:nbn:se:slu:epsilon-e-1946
Permanent URL:
http://urn.kb.se/resolve?urn=urn:nbn:se:slu:epsilon-e-1946
Additional ID:
Type of IDID
DOI10.3389/fgene.2013.00226
ID Code:11197
Faculty:VH - Faculty of Veterinary Medicine and Animal Science
Department:(VH) > Dept. of Clinical Sciences
Deposited By: SLUpub Connector
Deposited On:03 Jun 2014 11:24
Metadata Last Modified:24 Jan 2015 01:50

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