DESCRIPTION:

QTL associated with obesity QTL 2. This interval was obtained by using a fixed interval width of 25 Mbp around the peak marker (20861477)

LABEL:

QTL-Obq2-Mouse-Chr 1

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:109231

AUTHORS:

Brown AC, Olver WI, Donnelly CJ, May ME, Naggert JK, Shaffer DJ, Roopenian DC

TITLE:

Searching QTL by gene expression: analysis of diabesity.

JOURNAL:

BMC genetics Mar 2005, Vol 6, pp. 12

ABSTRACT:

Recent developments in sequence databases provide the opportunity to relate the expression pattern of genes to their genomic position, thus creating a transcriptome map. Quantitative trait loci (QTL) are phenotypically-defined chromosomal regions that contribute to allelically variant biological traits, and by overlaying QTL on the transcriptome, the search for candidate genes becomes extremely focused.We used our novel data mining tool, ExQuest, to select genes within known diabesity QTL showing enriched expression in primary diabesity affected tissues. We then quantified transcripts in adipose, pancreas, and liver tissue from Tally Ho mice, a multigenic model for Type II diabetes (T2D), and from diabesity-resistant C57BL/6J controls. Analysis of the resulting quantitative PCR data using the Global Pattern Recognition analytical algorithm identified a number of genes whose expression is altered, and thus are novel candidates for diabesity QTL and/or pathways associated with diabesity.Transcription-based data mining of genes in QTL-limited intervals followed by efficient quantitative PCR methods is an effective strategy for identifying genes that may contribute to complex pathophysiological processes. PUBMED: 15760467
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