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The polymorphism architecture of mouse genetic resources elucidated using genome-wide resequencing data: implications for QTL discovery and systems genetics
Authors:Adam Roberts  Fernando Pardo-Manuel de Villena  Wei Wang  Leonard McMillan  David W Threadgill
Institution:(1) Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA;(2) Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA;(3) Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA;(4) Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA;(5) Bioinformatics and Computational Biology Training Program, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA;(6) Center for Environmental Health and Susceptibility and Center for Gastrointestinal Biology and Disease, University of North Carolina at Chapel Hill, Chapel Hill, 27599, USA;(7) Department of Genetics, University of North Carolina at Chapel Hill, CB# 7264, 103 Mason Farm Road, Chapel Hill, NC 27599-7264, USA
Abstract:Mouse genetic resources include inbred strains, recombinant inbred lines, chromosome substitution strains, heterogeneous stocks, and the Collaborative Cross (CC). These resources were generated through various breeding designs that potentially produce different genetic architectures, including the level of diversity represented, the spatial distribution of the variation, and the allele frequencies within the resource. By combining sequencing data for 16 inbred strains and the recorded history of related strains, the architecture of genetic variation in mouse resources was determined. The most commonly used resources harbor only a fraction of the genetic diversity of Mus musculus, which is not uniformly distributed thus resulting in many blind spots. Only resources that include wild-derived inbred strains from subspecies other than M. m. domesticus have no blind spots and a uniform distribution of the variation. Unlike other resources that are primarily suited for gene discovery, the CC is the only resource that can support genome-wide network analysis, which is the foundation of systems genetics. The CC captures significantly more genetic diversity with no blind spots and has a more uniform distribution of the variation than all other resources. Furthermore, the distribution of allele frequencies in the CC resembles that seen in natural populations like humans in which many variants are found at low frequencies and only a minority of variants are common. We conclude that the CC represents a dramatic improvement over existing genetic resources for mammalian systems biology applications.
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