cgQTL

cgQTL integrates QTL mapping with mammary gland gene expression data to identify and prioritize candidate genes underlying milk production quantitative trait loci in dairy cattle.

Key Features:

• Integration of mapping and expression data: Combines QTL mapping with mammary gland gene expression profiling to narrow candidate genes within large QTL confidence intervals.
• Microarray analysis: Uses Affymetrix MG-U74v2 microarrays (12,488 murine probes) to profile RNA from C57BL/6J mouse mammary glands across virgin, pregnant, lactating, and involuting stages, including data from two additional studies totaling 75 biological replicates.
• Data processing: Performs consistent filtering and normalization of microarray data using GeneSpring.
• Differential expression identification: Applies analysis of variance to identify 249 differentially expressed probe sets, of which 212 genes were mapped to bovine positions by comparative mapping.
• Mammary gland-specific expression filtering: Prioritizes genes with mammary gland-specific expression defined as at least three-fold higher than the median across tissues in GeneAtlas.
• Addressing broad QTL intervals: Targets reduction of candidate gene lists arising from linkage-derived QTL confidence intervals that can span tens of map units or hundreds of genes.
• Validation of candidates: Identified three out of four confirmed genes (ABCG2, DGAT1, GDF8, IGF2) known to affect QTLs in livestock that are overexpressed in the target organ.

Scientific Applications:

• Candidate prioritization: Prioritizes candidate genes within bovine milk production QTLs for downstream functional validation and genetic analysis.
• Translation from QTL to QTN: Facilitates selection of candidates for quantitative trait nucleotide (QTN) determination by integrating expression evidence with mapping data.
• Comparative genomics: Uses cross-species mapping from mouse expression data to bovine genomic positions to inform livestock genetics.

Methodology:

Combines QTL mapping with mammary gland microarray profiling on Affymetrix MG-U74v2 arrays, applies filtering and normalization in GeneSpring, uses analysis of variance to detect differentially expressed probe sets, maps mouse probes to bovine positions by comparative mapping, and defines mammary-specific expression as ≥3-fold over the median in GeneAtlas.