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The mouse QTL map helps interpret human genome-wide association studies for HDL cholesterol

Leduc, Magalie S.; Lyons, Malcolm; Darvishi, Katayoon; Walsh, Kenneth; Sheehan, Susan; Amend, Sarah; Cox, Allison; Orho-Melander, Marju LU ; Kathiresan, Sekar and Paigen, Beverly, et al. (2011) In Journal of Lipid Research 52(6). p.1139-1149
Abstract
Genome-wide association (GWA) studies represent a powerful strategy for identifying susceptibility genes for complex diseases in human populations but results must be confirmed and replicated. Because of the close homology between mouse and human genomes, the mouse can be used to add evidence to genes suggested by human studies. We used the mouse quantitative trait loci (QTL) map to interpret results from a GWA study for genes associated with plasma HDL cholesterol levels. We first positioned single nucleotide polymorphisms (SNPs) from a human GWA study on the genomic map for mouse HDL QTL. We then used mouse bioinformatics, sequencing, and expression studies to add evidence for one well-known HDL gene (Abca1) and three newly identified... (More)
Genome-wide association (GWA) studies represent a powerful strategy for identifying susceptibility genes for complex diseases in human populations but results must be confirmed and replicated. Because of the close homology between mouse and human genomes, the mouse can be used to add evidence to genes suggested by human studies. We used the mouse quantitative trait loci (QTL) map to interpret results from a GWA study for genes associated with plasma HDL cholesterol levels. We first positioned single nucleotide polymorphisms (SNPs) from a human GWA study on the genomic map for mouse HDL QTL. We then used mouse bioinformatics, sequencing, and expression studies to add evidence for one well-known HDL gene (Abca1) and three newly identified genes (Galnt2, Wwox, and Cdh13), thus supporting the results of the human study. For GWA peaks that occur in human haplotype blocks with multiple genes, we examined the homologous regions in the mouse to prioritize the genes using expression, sequencing, and bioinformatics from the mouse model, showing that some genes were unlikely candidates and adding evidence for candidate genes Mvk and Mmab in one haplotype block and Fads1 and Fads2 in the second haplotype block. Our study highlights the value of mouse genetics for evaluating genes found in human GWA studies.-Leduc, M. S., M. Lyons, K. Darvishi, K. Walsh, S. Sheehan, S. Amend, A. Cox, M. Orho-Melander, S. Kathiresan, B. Paigen, and R. Korstanje. The mouse QTL map helps interpret human genome-wide association studies for HDL cholesterol. J. Lipid Res. 2011. 52: 1139-1149. (Less)
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published
subject
keywords
genomics, high density lipoprotein, comparative genomics, quantitative, trait loci, mouse model
in
Journal of Lipid Research
volume
52
issue
6
pages
1139 - 1149
publisher
American Society for Biochemistry and Molecular Biology
external identifiers
  • wos:000290559500009
  • scopus:79955982125
ISSN
1539-7262
DOI
10.1194/jlr.M009175
language
English
LU publication?
yes
id
37063daa-ea17-4114-99b9-162f47d13ea5 (old id 1986808)
date added to LUP
2011-07-01 09:19:48
date last changed
2017-01-01 03:51:43
@article{37063daa-ea17-4114-99b9-162f47d13ea5,
  abstract     = {Genome-wide association (GWA) studies represent a powerful strategy for identifying susceptibility genes for complex diseases in human populations but results must be confirmed and replicated. Because of the close homology between mouse and human genomes, the mouse can be used to add evidence to genes suggested by human studies. We used the mouse quantitative trait loci (QTL) map to interpret results from a GWA study for genes associated with plasma HDL cholesterol levels. We first positioned single nucleotide polymorphisms (SNPs) from a human GWA study on the genomic map for mouse HDL QTL. We then used mouse bioinformatics, sequencing, and expression studies to add evidence for one well-known HDL gene (Abca1) and three newly identified genes (Galnt2, Wwox, and Cdh13), thus supporting the results of the human study. For GWA peaks that occur in human haplotype blocks with multiple genes, we examined the homologous regions in the mouse to prioritize the genes using expression, sequencing, and bioinformatics from the mouse model, showing that some genes were unlikely candidates and adding evidence for candidate genes Mvk and Mmab in one haplotype block and Fads1 and Fads2 in the second haplotype block. Our study highlights the value of mouse genetics for evaluating genes found in human GWA studies.-Leduc, M. S., M. Lyons, K. Darvishi, K. Walsh, S. Sheehan, S. Amend, A. Cox, M. Orho-Melander, S. Kathiresan, B. Paigen, and R. Korstanje. The mouse QTL map helps interpret human genome-wide association studies for HDL cholesterol. J. Lipid Res. 2011. 52: 1139-1149.},
  author       = {Leduc, Magalie S. and Lyons, Malcolm and Darvishi, Katayoon and Walsh, Kenneth and Sheehan, Susan and Amend, Sarah and Cox, Allison and Orho-Melander, Marju and Kathiresan, Sekar and Paigen, Beverly and Korstanje, Ron},
  issn         = {1539-7262},
  keyword      = {genomics,high density lipoprotein,comparative genomics,quantitative,trait loci,mouse model},
  language     = {eng},
  number       = {6},
  pages        = {1139--1149},
  publisher    = {American Society for Biochemistry and Molecular Biology},
  series       = {Journal of Lipid Research},
  title        = {The mouse QTL map helps interpret human genome-wide association studies for HDL cholesterol},
  url          = {http://dx.doi.org/10.1194/jlr.M009175},
  volume       = {52},
  year         = {2011},
}