Abstract
BackgroundMany studies have found segregating quantitative trait loci (QTL) for milk production traits in different dairy cattle populations. However, even for relatively large effects with a saturated marker map the confidence interval for QTL location by linkage analysis spans tens of map units, or hundreds of genes. Combining mapping and arraying has been suggested as an approach to identify candidate genes. Thus, gene expression analysis in the mammary gland of genes positioned in the confidence interval of the QTL can bridge the gap between fine mapping and quantitative trait nucleotide (QTN) determination.ResultsWe hybridized Affymetrix microarray (MG-U74v2), containing 12,488 murine probes, with RNA derived from mammary gland of virgin, pregnant, lactating and involuting C57BL/6J mice in a total of nine biological replicates. We combined microarray data from two additional studies that used the same design in mice with a total of 75 biological replicates. The same filtering and normalization was applied to each microarray data using GeneSpring software. Analysis of variance identified 249 differentially expressed probe sets common to the three experiments along the four developmental stages of puberty, pregnancy, lactation and involution. 212 genes were assigned to their bovine map positions through comparative mapping, and thus form a list of candidate genes for previously identified QTLs for milk production traits. A total of 82 of the genes showed mammary gland-specific expression with at least 3-fold expression over the median representing all tissues tested in GeneAtlas.ConclusionThis work presents a web tool for candidate genes for QTL (cgQTL) that allows navigation between the map of bovine milk production QTL, potential candidate genes and their level of expression in mammary gland arrays and in GeneAtlas. Three out of four confirmed genes that affect QTL in livestock (ABCG2, DGAT1, GDF8, IGF2) were over expressed in the target organ. Thus, cgQTL can be used to determine priority of candidate genes for QTN analysis based on differential expression in the target organ.
Highlights
Many studies have found segregating quantitative trait loci (QTL) for milk production traits in different dairy cattle populations
Any marker within the confidence interval (CI) can be used for linkage disequilibrium (LD) mapping, it is reasonable to start with polymorphisms embedded within genes that are likely candidates for the QTL [5]
Gene expression analysis can bridge the gap between fine mapping and quantitative trait nucleotide (QTN) determination by revealing regulatory variation in genes for complex traits [8,9,10]
Summary
Many studies have found segregating quantitative trait loci (QTL) for milk production traits in different dairy cattle populations. Combining mapping and arraying has been suggested as an approach to identify candidate genes. Gene expression analysis in the mammary gland of genes positioned in the confidence interval of the QTL can bridge the gap between fine mapping and quantitative trait nucleotide (QTN) determination. Many studies have found segregating quantitative trait loci (QTL) for milk production traits in different dairy cattle populations [reviewed by Khatkar et al, [1] and Polineni et al, [2]; [3]]. Gene expression analysis can bridge the gap between fine mapping and quantitative trait nucleotide (QTN) determination by revealing regulatory variation in genes for complex traits [8,9,10]. Additional criteria may be proposed to select QTL candidate genes as follows: 1. Genes are preferentially expressed in organs related to the quantitative trait, i.e. the mammary gland for milk production traits
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