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

Magalie S. Leduc, Malcolm Lyons, Katayoon Darvishi, Kenneth Walsh, Susan Sheehan, Sarah Amend, Allison Cox, Marju Orho-Melander, Sekar Kathiresan, Beverly Paigen, Ron Korstanje

Research output: Contribution to journalArticle

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.

Original languageEnglish (US)
Pages (from-to)1139-1149
Number of pages11
JournalJournal of Lipid Research
Volume52
Issue number6
DOIs
StatePublished - Jun 1 2011
Externally publishedYes

Fingerprint

Quantitative Trait Loci
Genome-Wide Association Study
Human Genome
HDL Cholesterol
Genes
Haplotypes
Computational Biology
Bioinformatics
Single Nucleotide Polymorphism
Genome
Gene Expression
Polymorphism
Gene expression

Keywords

  • Comparative genomics
  • Genomics
  • High density lipoprotein
  • Mouse model
  • Quantitative trait loci

ASJC Scopus subject areas

  • Biochemistry
  • Cell Biology
  • Endocrinology

Cite this

Leduc, M. S., Lyons, M., Darvishi, K., Walsh, K., Sheehan, S., Amend, S., ... Korstanje, R. (2011). The mouse QTL map helps interpret human genome-wide association studies for HDL cholesterol. Journal of Lipid Research, 52(6), 1139-1149. https://doi.org/10.1194/jlr.M009175

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; Kathiresan, Sekar; Paigen, Beverly; Korstanje, Ron.

In: Journal of Lipid Research, Vol. 52, No. 6, 01.06.2011, p. 1139-1149.

Research output: Contribution to journalArticle

Leduc, MS, Lyons, M, Darvishi, K, Walsh, K, Sheehan, S, Amend, S, Cox, A, Orho-Melander, M, Kathiresan, S, Paigen, B & Korstanje, R 2011, 'The mouse QTL map helps interpret human genome-wide association studies for HDL cholesterol', Journal of Lipid Research, vol. 52, no. 6, pp. 1139-1149. https://doi.org/10.1194/jlr.M009175
Leduc, Magalie S. ; Lyons, Malcolm ; Darvishi, Katayoon ; Walsh, Kenneth ; Sheehan, Susan ; Amend, Sarah ; Cox, Allison ; Orho-Melander, Marju ; Kathiresan, Sekar ; Paigen, Beverly ; Korstanje, Ron. / The mouse QTL map helps interpret human genome-wide association studies for HDL cholesterol. In: Journal of Lipid Research. 2011 ; Vol. 52, No. 6. pp. 1139-1149.
@article{5b162c4fa9984485b237aa3dd0096575,
title = "The mouse QTL map helps interpret human genome-wide association studies for HDL cholesterol",
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.",
keywords = "Comparative genomics, Genomics, High density lipoprotein, Mouse model, Quantitative trait loci",
author = "Leduc, {Magalie S.} and Malcolm Lyons and Katayoon Darvishi and Kenneth Walsh and Susan Sheehan and Sarah Amend and Allison Cox and Marju Orho-Melander and Sekar Kathiresan and Beverly Paigen and Ron Korstanje",
year = "2011",
month = "6",
day = "1",
doi = "10.1194/jlr.M009175",
language = "English (US)",
volume = "52",
pages = "1139--1149",
journal = "Journal of Lipid Research",
issn = "0022-2275",
publisher = "American Society for Biochemistry and Molecular Biology Inc.",
number = "6",

}

TY - JOUR

T1 - The mouse QTL map helps interpret human genome-wide association studies for HDL cholesterol

AU - Leduc, Magalie S.

AU - Lyons, Malcolm

AU - Darvishi, Katayoon

AU - Walsh, Kenneth

AU - Sheehan, Susan

AU - Amend, Sarah

AU - Cox, Allison

AU - Orho-Melander, Marju

AU - Kathiresan, Sekar

AU - Paigen, Beverly

AU - Korstanje, Ron

PY - 2011/6/1

Y1 - 2011/6/1

N2 - 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.

AB - 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.

KW - Comparative genomics

KW - Genomics

KW - High density lipoprotein

KW - Mouse model

KW - Quantitative trait loci

UR - http://www.scopus.com/inward/record.url?scp=79955982125&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=79955982125&partnerID=8YFLogxK

U2 - 10.1194/jlr.M009175

DO - 10.1194/jlr.M009175

M3 - Article

C2 - 21444760

AN - SCOPUS:79955982125

VL - 52

SP - 1139

EP - 1149

JO - Journal of Lipid Research

JF - Journal of Lipid Research

SN - 0022-2275

IS - 6

ER -