DESCRIPTION:

This gene set contains 33 genes that showed greater expression in C57BL/6 (B6) than in C57BL/6 (B6) mice when Microarray Mouse Expression Array 430A analysis was used. Background: Study integrated five different ethanol-associated QTL (chr1, chr2, chr4, chr9 or chr19) and gene expression data of B6 and D2 inbred mouse strains with the goal of accelerating movement from QTLs to the QTGs (Quantitative Trait Gene).

LABEL:

DiffExpr EtOH B6 > D2

SCORE TYPE:

P-Value

DATE ADDED:

2009-01-21

DATE UPDATED:

2020-05-06

SPECIES:

AUTHORS:

Hitzemann R, Reed C, Malmanger B, Lawler M, Hitzemann B, Cunningham B, McWeeney S, Belknap J, Harrington C, Buck K, Phillips T, Crabbe J

TITLE:

On the integration of alcohol-related quantitative trait loci and gene expression analyses.

JOURNAL:

Alcoholism, clinical and experimental research Oct 2004, Vol 28, pp. 1437-48

ABSTRACT:

BACKGROUND: Quantitative trait loci (QTLs) have been detected for a wide variety of ethanol-related phenotypes, including acute and chronic ethanol withdrawal, acute locomotor activation, and ethanol preference. This study was undertaken to determine whether the process of moving from QTL to quantitative trait gene (QTG) could be accelerated by the integration of functional genomics (gene expression) into the analysis strategy. METHODS: Six ethanol-related QTLs, all detected in C57BL/6J and DBA/2J intercrosses were entered into the analysis. Each of the QTLs had been confirmed in independent genetic models at least once; the cumulative probabilities for QTL existence ranged from 10 to 10. Brain gene expression data for the C57BL/6 and DBA/2 strains (n = 6 per strain) and an F2 intercross sample (n = 56) derived from these strains were obtained by using the Affymetrix U74Av2 and 430A arrays; additional data with the U74Av2 array were available for the extended amygdala, dorsomedial striatum, and hippocampus. Low-level analysis was performed by using multiple methods to determine the likelihood that a transcript was truly differentially expressed. For the 430A array data, the F2 sample was used to determine which of the differentially expressed transcripts within the QTL intervals were cis-regulated and, thus, strong candidates for QTGs. RESULTS: Within the 6 QTL intervals, 39 transcripts (430A array) were identified as being highly likely to be differentially expressed between the C57BL/6 and DBA/2 strains at a false discovery rate of 0.01 or better. Twenty-eight of these transcripts showed significant (logarithm of odds > or =3.6) to highly significant (logarithm of odds >7) cis-regulation. The process correctly detected Mpdz (chromosome 4) as a candidate QTG for acute withdrawal. CONCLUSIONS: Although improvements are needed in the expression databases, the integration of QTL and gene expression analyses seems to have potential as a high-throughput strategy for moving from QTL to QTG. PUBMED: 15597075
Find other GeneSets from this publication