Use of a dense single nucleotide polymorphism map for in silico mapping in the mouse.
Use of a dense single nucleotide polymorphism map for in silico mapping in the mouse.
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DOI:
10.1371/journal.pbio.0020393
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发表时间:
2004-12
期刊:
影响因子:
9.8
通讯作者:
Wiltshire T
中科院分区:
文献类型:
--
作者:
Pletcher MT;McClurg P;Batalov S;Su AI;Barnes SW;Lagler E;Korstanje R;Wang X;Nusskern D;Bogue MA;Mural RJ;Paigen B;Wiltshire T
Rapid expansion of available data, both phenotypic and genotypic, for multiple strains of mice has enabled the development of new methods to interrogate the mouse genome for functional genetic perturbations. In silico mapping provides an expedient way to associate the natural diversity of phenotypic traits with ancestrally inherited polymorphisms for the purpose of dissecting genetic traits. In mouse, the current single nucleotide polymorphism (SNP) data have lacked the density across the genome and coverage of enough strains to properly achieve this goal. To remedy this, 470,407 allele calls were produced for 10,990 evenly spaced SNP loci across 48 inbred mouse strains. Use of the SNP set with statistical models that considered unique patterns within blocks of three SNPs as an inferred haplotype could successfully map known single gene traits and a cloned quantitative trait gene. Application of this method to high-density lipoprotein and gallstone phenotypes reproduced previously characterized quantitative trait loci (QTL). The inferred haplotype data also facilitates the refinement of QTL regions such that candidate genes can be more easily identified and characterized as shown for adenylate cyclase 7. A large resource of genetic markers, typed in 48 strains of mice, combined with statistical techniques, allow "in silico" mapping of genetic regions involved in interesting traits in mice
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影响因子:
6.5
作者:
Lyons, MA;Wittenburg, H;Paigen, B
通讯作者:
Paigen, B
影响因子:
30.8
作者:
Lindblad-Toh, K;Winchester, E;Lander, ES
通讯作者:
Lander, ES
影响因子:
3.5
作者:
Bachmanov, AA;Li, X;Beauchamp, GK
通讯作者:
Beauchamp, GK
影响因子:
15.9
作者:
Machleder, D;Ivandic, B;Lusis, AJ
通讯作者:
Lusis, AJ
影响因子:
56.9
作者:
Mural, RJ;Adams, MD;Venter, JC
通讯作者:
Venter, JC