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Genome partitioning and whole-genome analysis.

Authors: Schork, N J;

Genome partitioning and whole-genome analysis.

Abstract

Standard DNA marker-based approaches to mapping genes that influence complex traits typically consider a limited number of hypotheses. Most of these hypotheses concentrate on the effect of a single individual locus (or relatively few loci) on the trait of interest. Although of tremendous importance scientifically, such hypotheses do not accommodate the full range of genetic phenomena that may contribute to phenotypic expression. We present novel approaches to complex trait analysis that make as complete use of marker information as is possible. The proposed methodologies can be used to entertain a wide variety of hypotheses, including those that engage, for example, the contribution of a particular chromosome, genome-wide heterozygosity, and multiple genomic regions, to phenotypic expression. We consider a number of possible extensions of the proposed methods as well as their limitations. Although we discuss many methodological details in the context of quantitative trait locus mapping involving sampling units such as human pedigrees and hybrids resulting from crosses between inbred strains of model organisms, our procedures can be easily adapted to standard sibpair and other sampling unit-based designs. Ultimately, the proposed approaches not only have the potential to increase power to identify individual loci that harbor trait-influencing genes, but also present a framework for testing a number of hypotheses about the nature of the genetic determinants of phenotypes in general.

Country
United States
Related Organizations
Keywords

Genetic Markers, 570, Genetic-Screening, 576, Quantitative Trait, Heritable, Animals-Inbred-Strains, SUPPORT-U-S-GOVT-P-H-S, Animals, Humans, Genome-Human, Genetic Testing, SUPPORT-NON-U-S-GOVT, Alleles, Crosses, Genetic, Models, Statistical, Animal, Genome, Human, Genetic-Markers, Crosses-Genetic, Genetics-Population, Quantitative-Trait, Genetics, Population, Phenotype, Models-Statistical, Human, Animals, Inbred Strains

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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
24
Top 10%
Top 10%
Average
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