The DOI matches its Crossref record; 55 of the 55 references it cites were found in a registry or an index.
A high-resolution association mapping panel for the dissection of complex traits in mice
Open accessAbstract
Systems genetics relies on common genetic variants to elucidate biologic networks contributing to complex disease-related phenotypes. Mice are ideal model organisms for such approaches, but linkage analysis has been only modestly successful due to low mapping resolution. Association analysis in mice has the potential of much better resolution, but it is confounded by population structure and inadequate power to map traits that explain less than 10% of the variance, typical of mouse quantitative trait loci (QTL). We report a novel strategy for association mapping that combines classic inbred strains for mapping resolution and recombinant inbred strains for mapping power. Using a mixed model algorithm to correct for population structure, we validate the approach by mapping over 2500 cis-expression QTL with a resolution an order of magnitude narrower than traditional QTL analysis. We also report the fine mapping of metabolic traits such as plasma lipids. This resource, termed the Hybrid Mouse Diversity Panel, makes possible the integration of multiple data sets and should prove useful for systems-based approaches to complex traits and studies of gene-by-environment interactions.
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Citations
Cites
A haplotype map of the human genome
The International HapMap Consortium (2005) · Nature · doi:10.1038/nature04226 · Cited by 5,858
Efficient Control of Population Structure in Model Organism Association Mapping
Kang, H. M., Zaitlen, N. A., Wade, C. M., Kirby, A., Heckerman, D., Daly, M. J., & Eskin, E. (2008) · Genetics · doi:10.1534/genetics.107.080101 · Cited by 1,835
Self-citationEfficiency and power in genetic association studies
de Bakker, P. I. W., Yelensky, R., Pe'er, I., Gabriel, S. B., Daly, M. J., & Altshuler, D. (2005) · Nature Genetics · doi:10.1038/ng1669 · Cited by 1,688
Newly identified loci that influence lipid concentrations and risk of coronary artery disease
Willer, C. J., Sanna, S., Jackson, A. U., Scuteri, A., Bonnycastle, L. L., Clarke, R., Heath, S. C., Timpson, N. J., Najjar, S. S., Stringham, H. M., et al. (2008) · Nature Genetics · doi:10.1038/ng.76 · Cited by 1,585
Genetics of gene expression surveyed in maize, mouse and man
Schadt, E. E., Monks, S. A., Drake, T. A., Lusis, A. J., Che, N., Colinayo, V., Ruff, T. G., Milligan, S. B., Lamb, J. R., Cavet, G., et al. (2003) · Nature · doi:10.1038/nature01434 · Cited by 1,503
Self-citationGenetic Mapping in Human Disease
Altshuler, D., Daly, M. J., & Lander, E. S. (2008) · Science · doi:10.1126/science.1156409 · Cited by 1,452
Genetics of gene expression and its effect on disease
Emilsson, V., Thorleifsson, G., Zhang, B., Leonardson, A. S., Zink, F., Zhu, J., Carlson, S., Helgason, A., Walters, G. B., Gunnarsdottir, S., et al. (2008) · Nature · doi:10.1038/nature06758 · Cited by 1,296
The Collaborative Cross, a community resource for the genetic analysis of complex traits
The Complex Trait Consortium (2004) · Nature Genetics · doi:10.1038/ng1104-1133 · Cited by 1,113
Multiple Rare Alleles Contribute to Low Plasma Levels of HDL Cholesterol
Cohen, J. C., Kiss, R. S., Pertsemlidis, A., Marcel, Y. L., McPherson, R., & Hobbs, H. H. (2004) · Science · doi:10.1126/science.1099870 · Cited by 1,108
An integrative genomics approach to infer causal associations between gene expression and disease
Schadt, E. E., Lamb, J., Yang, X., Zhu, J., Edwards, S., GuhaThakurta, D., Sieberts, S. K., Monks, S., Reitman, M., Zhang, C., et al. (2005) · Nature Genetics · doi:10.1038/ng1589 · Cited by 1,043
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Cited by
Genome-wide efficient mixed-model analysis for association studies
Zhou, X., & Stephens, M. (2012) · Nature Genetics · doi:10.1038/ng.2310 · Cited by 3,627
“For the HMDP data, the potential gain in power from the exact calculations appears considerable, and this is confirmed by simulations (Supplementary Fig.”
MethodInfluentialMouse genomic variation and its effect on phenotypes and gene regulation.
Keane, T. M., Goodstadt, L., Danecek, P., White, M. A., Wong, K., Yalcin, B., Heger, A., Agam, A., Slater, G., Goodson, M., et al. (2011) · Nature · doi:10.1038/nature10413 · Cited by 1,580
Self-citationBennett, B. J., Vallim, T. Q. D. A., Wang, Z., Shih, D. M., Meng, Y., Gregory, J., Allayee, H., Lee, R., Graham, M., Crooke, R., et al. (2013) · Cell Metabolism · doi:10.1016/j.cmet.2012.12.011 · Cited by 1,070
Self-citationEfficient multivariate linear mixed model algorithms for genome-wide association studies
Zhou, X., & Stephens, M. (2014) · Nature Methods · doi:10.1038/nmeth.2848 · Cited by 841
Comparative analysis of proteome and transcriptome variation in mouse
Ghazalpour, A., Bennett, B., Petyuk, V. A., Orozco, L., Hagopian, R., Mungrue, I. N., Farber, C. R., Sinsheimer, J., Kang, H. M., Furlotte, N., et al. (2011) · PLoS Genetics · doi:10.1371/journal.pgen.1001393 · Cited by 624
“Livers from the 97 strains were quantitatively analyzed for global transcript levels using the Affymetrix HT-MG430A platform and for protein levels using LC-MS employing AMT tag approach for identification and (16)O/(18)O labeling for quantification [12,15].”
MethodResultInfluentialSelf-citation
Metadata
- Authors
- Bennett, B. J., Farber, C. R., Orozco, L., Min Kang, H., Ghazalpour, A., Siemers, N., Neubauer, M., Neuhaus, I., Yordanova, R., Guan, B., Truong, A., Yang, W.-P., He, A., Kayne, P., Gargalovic, P., Kirchgessner, T., Pan, C., Castellani, L. W., Kostem, E., Furlotte, N., Drake, T. A., Eskin, E., & Lusis, A. J.
- Venue
- Genome Research
- Publisher
- Cold Spring Harbor Laboratory
- Published
- 2010-01-06
- Volume
- 20
- Issue
- 2
- Pages
- 281-290
- ISSN
- 1088-9051 (ISSN-L)
- OpenAlex
- W2158534900
- Cited by
- 317
- References
- 55
- Type
- posted content
- Language
- en
- Open access
- bronze
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- Bennett, B. J., Farber, C. R., Orozco, L., Min Kang, H., Ghazalpour, A., Siemers, N., Neubauer, M., Neuhaus, I., Yordanova, R., Guan, B., Truong, A., Yang, W.-P., He, A., Kayne, P., Gargalovic, P., Kirchgessner, T., Pan, C., Castellani, L. W., Kostem, E., . . . Lusis, A. J. (2010). A high-resolution association mapping panel for the dissection of complex traits in mice. Genome Research. https://doi.org/10.1101/gr.099234.109
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