DESCRIPTION:

QTL associated with HDL QTL 24. This interval was obtained by using a fixed interval width of 25 Mbp around the peak marker (142693035)

LABEL:

QTL-Hdlq24-Mouse-Chr 6

SCORE TYPE:

Binary

DATE ADDED:

2012-04-02

DATE UPDATED:

2020-05-06

SPECIES:

URI:

http://www.informatics.jax.org/searches/accession_report.cgi?id=MGI:3041286

AUTHORS:

Stylianou IM, Affourtit JP, Shockley KR, Wilpan RY, Abdi FA, Bhardwaj S, Rollins J, Churchill GA, Paigen B

TITLE:

Applying gene expression, proteomics and single-nucleotide polymorphism analysis for complex trait gene identification.

JOURNAL:

Genetics Mar 2008, Vol 178, pp. 1795-805

ABSTRACT:

Previous quantitative trait locus (QTL) analysis of an intercross involving the inbred mouse strains NZB/BlNJ and SM/J revealed QTL for a variety of complex traits. Many QTL have large intervals containing hundreds of genes, and methods are needed to rapidly sort through these genes for probable candidates. We chose nine QTL: the three most significant for high-density lipoprotein (HDL) cholesterol, gallstone formation, and obesity. We searched for candidate genes using three different approaches: mRNA microarray gene expression technology to assess >45,000 transcripts, publicly available SNPs to locate genes that are not identical by descent and that contain nonsynonymous coding differences, and a mass-spectrometry-based proteomics technology to interrogate nearly 1000 proteins for differential expression in the liver of the two parental inbred strains. This systematic approach reduced the number of candidate genes within each QTL from hundreds to a manageable list. Each of the three approaches selected candidates that the other two approaches missed. For example, candidate genes such as Apoa2 and Acads had differential protein levels although the mRNA levels were similar. We conclude that all three approaches are important and that focusing on a single approach such as mRNA expression may fail to identify a QTL gene. PUBMED: 18245842
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