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Sequential quantitative trait locus mapping in experimental crosses.

Sequential quantitative trait locus mapping in experimental crosses. Research Abstract Details 

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  • Sequential quantitative trait locus mapping in experimental crosses. Abstract Text:

    jaya m satagopanJaya M Satagopan,saunak senSaunak Sen,gary a churchillGary A Churchill,

    The etiology of complex diseases is heterogeneous. The presence of risk alleles in one or more genetic loci affects the function of a variety of intermediate biological pathways, resulting in the overt expression of disease. Hence, there is an increasing focus on identifying the genetic basis of disease by systematically studying phenotypic traits pertaining to the underlying biological functions. In this paper we focus on identifying genetic loci linked to quantitative phenotypic traits in experimental crosses. Such genetic mapping methods often use a one stage design by genotyping all the markers of interest on the available subjects. A genome scan based on single locus or multi-locus models is used to identify the putative loci. Since the number of quantitative trait loci (QTLs) is very likely to be small relative to the number of markers genotyped, a one-stage selective genotyping approach is commonly used to reduce the genotyping burden, whereby markers are genotyped solely on individuals with extreme trait values. This approach is powerful in the presence of a single quantitative trait locus (QTL) but may result in substantial loss of information in the presence of multiple QTLs. Here we investigate the efficiency of sequential two stage designs to identify QTLs in experimental populations. Our investigations for backcross and F2 crosses suggest that genotyping all the markers on 60% of the subjects in Stage 1 and genotyping the chromosomes significant at 20% level using additional subjects in Stage 2 and testing using all the subjects provides an efficient approach to identify the QTLs and utilizes only 70% of the genotyping burden relative to a one stage design, regardless of the heritability and genotyping density. Complex traits are a consequence of multiple QTLs conferring main effects as well as epistatic interactions. We propose a two-stage analytic approach where a single-locus genome scan is conducted in Stage 1 to identify promising chromosomes, and interactions are examined using the loci on these chromosomes in Stage 2. We examine settings under which the two-stage analytic approach provides sufficient power to detect the putative QTLs.

    Sequential quantitative trait locus mapping in experimental crosses. Publishing Authors By Initials

    jm satagopanJM Satagopan,s senS Sen,ga churchillGA Churchill,

    For similar natural sciences: science: research: research design research abstracts see: natural sciences: science: research: research design research

    PUBMED ID PMID:

    MEDLINE DATE:

    Sequential quantitative trait locus mapping in experimental crosses. Journal Published:

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

    Journal: Statistical applications in genetics and molecular

    VOLUME: 6

    Page Numbers: Article12

    Journal Abbreviation:

    ISSN: 1544-6115

    DAY: 17

    MONTH: 04

    YEAR: 2007

    Sequential quantitative trait locus mapping in experimental crosses. Information

    Number of References:

    LANGUAGE: eng

    NlmUniqueID: 101176023

    Sequential quantitative trait locus mapping in experimental crosses. Keywords Mesh Terms:

    KEYWORDS: Research Design

    MESH TERMS: methods

    Chemical & Substance for Abstract: Sequential quantitative trait locus mapping in experimental crosses. Information

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    Grant and Affiliation Information for Sequential quantitative trait locus mapping in experimental crosses.

    AFFILIATION: Memorial Sloan-Kettering Cancer Center, USA. satagopj@mskcc.org

    Country: United States

    United States Research PublicationUnited States Research Publication

    AGENCY: United States NIGMS

    GRANT: GM074244

    ACRONYM: GM

    MEDLINETA: Stat Appl Genet Mol Biol

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