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Prediction of cis-QTLs in a pair of inbred mouse strains with the use of expression and haplotype data from public databases.

Prediction of cis-QTLs in a pair of inbred mouse strains with the use of expression and haplotype data from public databases. Research Abstract Details 

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  • Prediction of cis-QTLs in a pair of inbred mouse strains with the use of expression and haplotype data from public databases. Abstract Text:

    richard a radcliffeRichard A Radcliffe,michael j leeMichael J Lee,robert w williamsRobert W Williams,

    Cis-QTLs are important candidates for any other trait that maps to the same locus. In this article we have used publicly available databases and a small microarray data set to "map" cis-QTLs in the ILS and ISS inbred mouse strains without the need to generate microarray data from an ILSXISS segregating population. Expression data were obtained from brains of C57BL/6, DBA/2, ILS, and ISS. Cis-QTLs were mapped for the 760 transcripts found to be differentially expressed between the C57BL/6 and DBA/2 using expression data previously obtained from the BXD RIs. The 469 detected cis-QTLs were then examined for SNP haplotypes and expression patterns that could relate the ILS and ISS to the C57BL/6 and DBA/2. Of the 338 cis-QTL transcripts that had informative haplotypes, 189 were significantly different between the ILS and ISS with 184 showing segregation of haplotype with expression. These were considered to be probable cis-QTLs in the ILS and ISS. There were almost certainly additional ILS/ISS cis-QTLs among the other transcripts with informative haplotypes, but in the absence of an ILS/ISS expression difference, the level of confidence was reduced. Several of the putative ILS/ISS cis-QTLs are considered important candidate genes because they are linked to ILS/ISS behavioral QTLs. A potential ascertainment bias related to strain-dependent target sequences was observed suggesting that as much as 35% of the cis-QTLs were hybridization artifacts. Nonetheless, the results suggest that this approach is an economical and widely applicable method for mapping cis-QTLs in a strain pair of interest.

    Prediction of cis-QTLs in a pair of inbred mouse strains with the use of expression and haplotype data from public databases. Publishing Authors By Initials

    ra radcliffeRA Radcliffe,mj leeMJ Lee,rw williamsRW Williams,

    For similar genetic structures: genome: genome components: genes: quantitative trait loci research abstracts see: genetic structures: genome: genome components: genes: quantitative trait loci research

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    Prediction of cis-QTLs in a pair of inbred mouse strains with the use of expression and haplotype data from public databases. Journal Published:

    PUBLICATION TYPE: Research Support, N.I.H., Extr

    Journal: Mammalian genome : official journal of the Interna

    VOLUME: 17

    Page Numbers: 629-42

    Journal Abbreviation: Mamm. Genome

    ISSN: 0938-8990

    DAY: 12

    MONTH: 06

    YEAR: 2006

    Prediction of cis-QTLs in a pair of inbred mouse strains with the use of expression and haplotype data from public databases. Information

    Number of References:

    LANGUAGE: eng

    NlmUniqueID: 9100916

    Prediction of cis-QTLs in a pair of inbred mouse strains with the use of expression and haplotype data from public databases. Keywords Mesh Terms:

    KEYWORDS: Quantitative Trait Loci

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    Chemical & Substance for Abstract: Prediction of cis-QTLs in a pair of inbred mouse strains with the use of expression and haplotype data from public databases. Information

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    Grant and Affiliation Information for Prediction of cis-QTLs in a pair of inbred mouse strains with the use of expression and haplotype data from public databases.

    AFFILIATION: Department of Pharmaceutical Sciences, University of Colorado at Denver and Health Sciences Center, 4200 E. Ninth Avenue, Denver, CO 80262, USA. Richard.Radcliffe@UCHSC.edu

    Country: United States

    United States Research PublicationUnited States Research Publication

    AGENCY: United States NIAAA

    GRANT: U01 AA 13499

    ACRONYM: AA

    MEDLINETA: Mamm Genome

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