Our group publishes papers presenting new methodologies, describing the results of studies that use our software, and reviewing current topics in the field of Bioinformatics. Scroll down or click here for a complete list of papers produced by our lab. Since 2013, we write blog posts summarizing new research papers and review articles:
GWAS
- Fine Mapping Causal Variants and Allelic Heterogeneity
- Widespread Allelic Heterogeneity in Complex Traits
- Selection in Europeans on Fatty Acid Desaturases Associated with Dietary Changes
- Incorporating prior information into association studies
- Characterization of Expression Quantitative Trait Loci in Pedigrees from Colombia and Costa Rica Ascertained for Bipolar Disorder
- Simultaneous modeling of disease status and clinical phenotypes to increase power in GWAS
- Efficient and accurate multiple-phenotype regression method for high dimensional data considering population structure
- Review Article: Population Structure in Genetic Studies: Confounding Factors and Mixed Models
- Colocalization of GWAS and eQTL Signals Detects Target Genes
- Chromosome conformation elucidates regulatory relationships in developing human brain
Mouse Genetics
- Review Article: The Hybrid Mouse Diversity Panel
- Genes, Environments and Meta-Analysis
- Review Article: Mixed Models and Population Structure
- Identifying Genes Involved in Blood Cell Traits
- Genes, Diet, and Body Weight (in Mice)
- Review Article: Mouse Genetics
Population Structure
- Efficient and accurate multiple-phenotype regression method for high dimensional data considering population structure
- Review Article: Population Structure in Genetic Studies: Confounding Factors and Mixed Models
- Accounting for Population Structure in Gene-by-Environment Interactions in Genome-Wide Association Studies Using Mixed Models
- Multiple testing correction in linear mixed models
- Identification of causal genes for complex traits (CAVIAR-gene)
- Accurate viral population assembly from ultra-deep sequencing data
- GRAT: Speeding up Expression Quantitative Trail Loci (eQTL) Studies
- Correcting Population Structure using Mixed Models Webcast
- Mixed models can correct for population structure for genomic regions under selection
Review Articles
- Review Article: Population Structure in Genetic Studies: Confounding Factors and Mixed Models
- Review Article: The Hybrid Mouse Diversity Panel
- Review Article: GWAS and Missing Heritability
- Review Article: Mixed Models and Population Structure
- Review Article: Mouse Genetics
Publications
Allele Specific Expression Association Priors Association Study Methods Causal Inference Causal Inference Biology Confounding Expression QTLs Fine Mapping Genes By Environment genome-wide association studies Haplotype Phasing Haplotyping from Sequences Heritability HMDP Imputation Meta-Analysis Mixed Models Motif Finding Mouse Genetics Multiple Phenotypes Multiple Testing Pedigree Inference Population Genetics Population Structure Methods Rare Variants RNA sequencing RNAseq Sequence Assembly Sequencing with Pools Structural Variation
2015 |
Rau, Christoph D; Parks, Brian; Wang, Yibin; Eskin, Eleazar; Simecek, Petr; Churchill, Gary A; Lusis, Aldons J High Density Genotypes of Inbred Mouse Strains: Improved Power and Precision of Association Mapping. Journal Article G3 (Bethesda), 5 (10), pp. 2021-6, 2015, ISSN: 2160-1836. Abstract | Links | BibTeX | Tags: HMDP, Mouse Genetics @article{Rau:G3:2015b, title = {High Density Genotypes of Inbred Mouse Strains: Improved Power and Precision of Association Mapping.}, author = { Christoph D. Rau and Brian Parks and Yibin Wang and Eleazar Eskin and Petr Simecek and Gary A. Churchill and Aldons J. Lusis}, url = {http://dx.doi.org/10.1534/g3.115.020784}, issn = {2160-1836}, year = {2015}, date = {2015-01-01}, journal = {G3 (Bethesda)}, volume = {5}, number = {10}, pages = {2021-6}, address = {United States}, abstract = {Human genome-wide association studies (GWAS) have identified thousands of loci associated with disease phenotypes. GWAS studies have also become feasible using rodent models and these have some important advantages over human studies including controlled environment, access to tissues for molecular profiling, reproducible genotypes and a wide array of techniques for experimental validation. Association mapping with common mouse inbred strains generally requires one hundred or more strains to achieve sufficient power and mapping resolution; in contrast, sample sizes for human studies are typically one or more orders of magnitude greater than this. To enable well-powered studies in mice, we have generated high-density genotypes for ~175 inbred strains of mice using the Mouse Diversity Array. These new data increase marker density by 1.9-fold, have reduced missing data rates, and provide more accurate identification of heterozygous regions compared to previous genotype data. We report the discovery of new loci from previously reported association mapping studies using the new genotype data. The data are freely available for download and web-based tools provide easy access for association mapping and viewing of the underlying intensity data for individual loci}, keywords = {HMDP, Mouse Genetics}, pubstate = {published}, tppubtype = {article} } Human genome-wide association studies (GWAS) have identified thousands of loci associated with disease phenotypes. GWAS studies have also become feasible using rodent models and these have some important advantages over human studies including controlled environment, access to tissues for molecular profiling, reproducible genotypes and a wide array of techniques for experimental validation. Association mapping with common mouse inbred strains generally requires one hundred or more strains to achieve sufficient power and mapping resolution; in contrast, sample sizes for human studies are typically one or more orders of magnitude greater than this. To enable well-powered studies in mice, we have generated high-density genotypes for ~175 inbred strains of mice using the Mouse Diversity Array. These new data increase marker density by 1.9-fold, have reduced missing data rates, and provide more accurate identification of heterozygous regions compared to previous genotype data. We report the discovery of new loci from previously reported association mapping studies using the new genotype data. The data are freely available for download and web-based tools provide easy access for association mapping and viewing of the underlying intensity data for individual loci |
Zhou, Xiaoying; Crow, Amanda L; Hartiala, Jaana; Spindler, Tassja J; Ghazalpour, Anatole; Barsky, Lora W; Bennett, Brian J; Parks, Brian W; Eskin, Eleazar; Jain, Rajan; Epstein, Jonathan A; Lusis, Aldons J; Adams, Gregor B; Allayee, Hooman The Genetic Landscape of Hematopoietic Stem Cell Frequency in Mice. Journal Article Stem Cell Reports, 5 (1), pp. 125-38, 2015, ISSN: 2213-6711. Abstract | Links | BibTeX | Tags: HMDP @article{Zhou:StemCellReports:2015b, title = {The Genetic Landscape of Hematopoietic Stem Cell Frequency in Mice.}, author = { Xiaoying Zhou and Amanda L. Crow and Jaana Hartiala and Tassja J. Spindler and Anatole Ghazalpour and Lora W. Barsky and Brian J. Bennett and Brian W. Parks and Eleazar Eskin and Rajan Jain and Jonathan A. Epstein and Aldons J. Lusis and Gregor B. Adams and Hooman Allayee}, url = {http://dx.doi.org/10.1016/j.stemcr.2015.05.008}, issn = {2213-6711}, year = {2015}, date = {2015-01-01}, journal = {Stem Cell Reports}, volume = {5}, number = {1}, pages = {125-38}, address = {United States}, abstract = {Prior efforts to identify regulators of hematopoietic stem cell physiology have relied mainly on candidate gene approaches with genetically modified mice. Here we used a genome-wide association study (GWAS) strategy with the hybrid mouse diversity panel to identify the genetic determinants of hematopoietic stem/progenitor cell (HSPC) frequency. Among 108 strains, we observed 120- to 300-fold variation in three HSPC populations. A GWAS analysis identified several loci that were significantly associated with HSPC frequency, including a locus on chromosome 5 harboring the homeodomain-only protein gene (Hopx). Hopx previously had been implicated in cardiac development but was not known to influence HSPC biology. Analysis of the HSPC pool in Hopx(-/-) mice demonstrated significantly reduced cell frequencies and impaired engraftment in competitive repopulation assays, thus providing functional validation of this positional candidate gene. These results demonstrate the power of GWAS in mice to identify genetic determinants of the hematopoietic system}, keywords = {HMDP}, pubstate = {published}, tppubtype = {article} } Prior efforts to identify regulators of hematopoietic stem cell physiology have relied mainly on candidate gene approaches with genetically modified mice. Here we used a genome-wide association study (GWAS) strategy with the hybrid mouse diversity panel to identify the genetic determinants of hematopoietic stem/progenitor cell (HSPC) frequency. Among 108 strains, we observed 120- to 300-fold variation in three HSPC populations. A GWAS analysis identified several loci that were significantly associated with HSPC frequency, including a locus on chromosome 5 harboring the homeodomain-only protein gene (Hopx). Hopx previously had been implicated in cardiac development but was not known to influence HSPC biology. Analysis of the HSPC pool in Hopx(-/-) mice demonstrated significantly reduced cell frequencies and impaired engraftment in competitive repopulation assays, thus providing functional validation of this positional candidate gene. These results demonstrate the power of GWAS in mice to identify genetic determinants of the hematopoietic system |
Bennett, Brian J; Davis, Richard C; Civelek, Mete; Orozco, Luz; Wu, Judy; Qi, Hannah; Pan, Calvin; Packard, René Sevag R; Eskin, Eleazar; Yan, Mujing; Kirchgessner, Todd; Wang, Zeneng; Li, Xinmin; Gregory, Jill C; Hazen, Stanley L; Gargalovic, Peter S; JLusis, Aldons Genetic Architecture of Atherosclerosis in Mice: A Systems Genetics Analysis of Common Inbred Strains. Journal Article PLoS Genet, 11 (12), pp. e1005711, 2015, ISSN: 1553-7404. Abstract | Links | BibTeX | Tags: atherosclerosis, genome-wide association studies, HMDP @article{Bennett:PlosGenet:2015, title = {Genetic Architecture of Atherosclerosis in Mice: A Systems Genetics Analysis of Common Inbred Strains.}, author = {Brian J. Bennett and Richard C. Davis and Mete Civelek and Luz Orozco and Judy Wu and Hannah Qi and Calvin Pan and René R. Sevag Packard and Eleazar Eskin and Mujing Yan and Todd Kirchgessner and Zeneng Wang and Xinmin Li and Jill C. Gregory and Stanley L. Hazen and Peter S. Gargalovic and Aldons JLusis}, url = {http://dx.doi.org/10.1371/journal.pgen.1005711}, issn = {1553-7404}, year = {2015}, date = {2015-01-01}, journal = {PLoS Genet}, volume = {11}, number = {12}, pages = {e1005711}, address = {United States}, abstract = {Common forms of atherosclerosis involve multiple genetic and environmental factors. While human genome-wide association studies have identified numerous loci contributing to coronary artery disease and its risk factors, these studies are unable to control environmental factors or examine detailed molecular traits in relevant tissues. We now report a study of natural variations contributing to atherosclerosis and related traits in over 100 inbred strains of mice from the Hybrid Mouse Diversity Panel (HMDP). The mice were made hyperlipidemic by transgenic expression of human apolipoprotein E-Leiden (APOE-Leiden) and human cholesteryl ester transfer protein (CETP). The mice were examined for lesion size and morphology as well as plasma lipid, insulin and glucose levels, and blood cell profiles. A subset of mice was studied for plasma levels of metabolites and cytokines. We also measured global transcript levels in aorta and liver. Finally, the uptake of acetylated LDL by macrophages from HMDP mice was quantitatively examined. Loci contributing to the traits were mapped using association analysis, and relationships among traits were examined using correlation and statistical modeling. A number of conclusions emerged. First, relationships among atherosclerosis and the risk factors in mice resemble those found in humans. Second, a number of trait-loci were identified, including some overlapping with previous human and mouse studies. Third, gene expression data enabled enrichment analysis of pathways contributing to atherosclerosis and prioritization of candidate genes at associated loci in both mice and humans. Fourth, the data provided a number of mechanistic inferences; for example, we detected no association between macrophage uptake of acetylated LDL and atherosclerosis. Fifth, broad sense heritability for atherosclerosis was much larger than narrow sense heritability, indicating an important role for gene-by-gene interactions. Sixth, stepwise linear regression showed that the combined variations in plasma metabolites, including LDL/VLDL-cholesterol, trimethylamine N-oxide (TMAO), arginine, glucose and insulin, account for approximately 30 to 40% of the variation in atherosclerotic lesion area. Overall, our data provide a rich resource for studies of complex interactions underlying atherosclerosis}, keywords = {atherosclerosis, genome-wide association studies, HMDP}, pubstate = {published}, tppubtype = {article} } Common forms of atherosclerosis involve multiple genetic and environmental factors. While human genome-wide association studies have identified numerous loci contributing to coronary artery disease and its risk factors, these studies are unable to control environmental factors or examine detailed molecular traits in relevant tissues. We now report a study of natural variations contributing to atherosclerosis and related traits in over 100 inbred strains of mice from the Hybrid Mouse Diversity Panel (HMDP). The mice were made hyperlipidemic by transgenic expression of human apolipoprotein E-Leiden (APOE-Leiden) and human cholesteryl ester transfer protein (CETP). The mice were examined for lesion size and morphology as well as plasma lipid, insulin and glucose levels, and blood cell profiles. A subset of mice was studied for plasma levels of metabolites and cytokines. We also measured global transcript levels in aorta and liver. Finally, the uptake of acetylated LDL by macrophages from HMDP mice was quantitatively examined. Loci contributing to the traits were mapped using association analysis, and relationships among traits were examined using correlation and statistical modeling. A number of conclusions emerged. First, relationships among atherosclerosis and the risk factors in mice resemble those found in humans. Second, a number of trait-loci were identified, including some overlapping with previous human and mouse studies. Third, gene expression data enabled enrichment analysis of pathways contributing to atherosclerosis and prioritization of candidate genes at associated loci in both mice and humans. Fourth, the data provided a number of mechanistic inferences; for example, we detected no association between macrophage uptake of acetylated LDL and atherosclerosis. Fifth, broad sense heritability for atherosclerosis was much larger than narrow sense heritability, indicating an important role for gene-by-gene interactions. Sixth, stepwise linear regression showed that the combined variations in plasma metabolites, including LDL/VLDL-cholesterol, trimethylamine N-oxide (TMAO), arginine, glucose and insulin, account for approximately 30 to 40% of the variation in atherosclerotic lesion area. Overall, our data provide a rich resource for studies of complex interactions underlying atherosclerosis |
2014 |
Ohmen, Jeffrey; Kang, Eun Yong ; Li, Xin ; Joo, Jong Wha ; Hormozdiari, Farhad ; Zheng, Qing Yin ; Davis, Richard C; Lusis, Aldons J; Eskin, Eleazar ; Friedman, Rick A Genome-Wide Association Study for Age-Related Hearing Loss (AHL) in the Mouse: A Meta-Analysis. Journal Article J Assoc Res Otolaryngol, 15 (3), pp. 335-52, 2014, ISSN: 1438-7573. Abstract | Links | BibTeX | Tags: HMDP, Meta-Analysis, Mouse Genetics @article{Ohmen:JAssocResOtolaryngol:2014, title = {Genome-Wide Association Study for Age-Related Hearing Loss (AHL) in the Mouse: A Meta-Analysis.}, author = { Jeffrey Ohmen and Eun Yong Kang and Xin Li and Jong Wha Joo and Farhad Hormozdiari and Qing Yin Zheng and Richard C. Davis and Aldons J. Lusis and Eleazar Eskin and Rick A. Friedman}, url = {http://dx.doi.org/10.1007/s10162-014-0443-2}, issn = {1438-7573}, year = {2014}, date = {2014-01-01}, journal = {J Assoc Res Otolaryngol}, volume = {15}, number = {3}, pages = {335-52}, address = {United States}, abstract = {Age-related hearing loss (AHL) is characterized by a symmetric sensorineural hearing loss primarily in high frequencies and individuals have different levels of susceptibility to AHL. Heritability studies have shown that the sources of this variance are both genetic and environmental, with approximately half of the variance attributable to hereditary factors as reported by Huag and Tang (Eur Arch Otorhinolaryngol 267(8):1179-1191, 2010). Only a limited number of large-scale association studies for AHL have been undertaken in humans, to date. An alternate and complementary approach to these human studies is through the use of mouse models. Advantages of mouse models include that the environment can be more carefully controlled, measurements can be replicated in genetically identical animals, and the proportion of the variability explained by genetic variation is increased. Complex traits in mouse strains have been shown to have higher heritability and genetic loci often have stronger effects on the trait compared to humans. Motivated by these advantages, we have performed the first genome-wide association study of its kind in the mouse by combining several data sets in a meta-analysis to identify loci associated with age-related hearing loss. We identified five genome-wide significant loci (<10(-6)). One of these loci confirmed a previously identified locus (ahl8) on distal chromosome 11 and greatly narrowed the candidate region. Specifically, the most significant associated SNP is located 450udotkb upstream of Fscn2. These data confirm the utility of this approach and provide new high-resolution mapping information about variation within the mouse genome associated with hearing loss}, keywords = {HMDP, Meta-Analysis, Mouse Genetics}, pubstate = {published}, tppubtype = {article} } Age-related hearing loss (AHL) is characterized by a symmetric sensorineural hearing loss primarily in high frequencies and individuals have different levels of susceptibility to AHL. Heritability studies have shown that the sources of this variance are both genetic and environmental, with approximately half of the variance attributable to hereditary factors as reported by Huag and Tang (Eur Arch Otorhinolaryngol 267(8):1179-1191, 2010). Only a limited number of large-scale association studies for AHL have been undertaken in humans, to date. An alternate and complementary approach to these human studies is through the use of mouse models. Advantages of mouse models include that the environment can be more carefully controlled, measurements can be replicated in genetically identical animals, and the proportion of the variability explained by genetic variation is increased. Complex traits in mouse strains have been shown to have higher heritability and genetic loci often have stronger effects on the trait compared to humans. Motivated by these advantages, we have performed the first genome-wide association study of its kind in the mouse by combining several data sets in a meta-analysis to identify loci associated with age-related hearing loss. We identified five genome-wide significant loci (<10(-6)). One of these loci confirmed a previously identified locus (ahl8) on distal chromosome 11 and greatly narrowed the candidate region. Specifically, the most significant associated SNP is located 450udotkb upstream of Fscn2. These data confirm the utility of this approach and provide new high-resolution mapping information about variation within the mouse genome associated with hearing loss |
2013 |
Parks, Brian W; Nam, Elizabeth ; Org, Elin ; Kostem, Emrah ; Norheim, Frode ; Hui, Simon T; Pan, Calvin ; Civelek, Mete ; Rau, Christoph D; Bennett, Brian J; Mehrabian, Margarete ; Ursell, Luke K; He, Aiqing ; Castellani, Lawrence W; Zinker, Bradley ; Kirby, Mark ; Drake, Thomas A; Drevon, Christian A; Knight, Rob ; Gargalovic, Peter ; Kirchgessner, Todd ; Eskin, Eleazar ; Lusis, Aldons J Genetic control of obesity and gut microbiota composition in response to high-fat, high-sucrose diet in mice. Journal Article Cell Metab, 17 (1), pp. 141-52, 2013, ISSN: 1932-7420. Abstract | Links | BibTeX | Tags: HMDP, Mouse Genetics @article{Parks:CellMetab:2013, title = {Genetic control of obesity and gut microbiota composition in response to high-fat, high-sucrose diet in mice.}, author = { Brian W. Parks and Elizabeth Nam and Elin Org and Emrah Kostem and Frode Norheim and Simon T. Hui and Calvin Pan and Mete Civelek and Christoph D. Rau and Brian J. Bennett and Margarete Mehrabian and Luke K. Ursell and Aiqing He and Lawrence W. Castellani and Bradley Zinker and Mark Kirby and Thomas A. Drake and Christian A. Drevon and Rob Knight and Peter Gargalovic and Todd Kirchgessner and Eleazar Eskin and Aldons J. Lusis}, url = {http://dx.doi.org/10.1016/j.cmet.2012.12.007}, issn = {1932-7420}, year = {2013}, date = {2013-01-01}, journal = {Cell Metab}, volume = {17}, number = {1}, pages = {141-52}, address = {United States}, organization = {Department of Medicine/Division of Cardiology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA. Electronic address: bparks@mednet.ucla.edu.}, abstract = {Obesity is a highly heritable disease driven by complex interactions between genetic and environmental factors. Human genome-wide association studies (GWAS) have identified a number of loci contributing to obesity; however, a major limitation of these studies is the inability to assess environmental interactions common to obesity. Using a systems genetics approach, we measured obesity traits, global gene expression, and gut microbiota composition in response to a high-fat/high-sucrose (HF/HS) diet of more than 100 inbred strains of mice. Here we show that HF/HS feeding promotes robust, strain-specific changes in obesity that are not accounted for by food intake and provide evidence for a genetically determined set point for obesity. GWAS analysis identified 11 genome-wide significant loci associated with obesity traits, several of which overlap with loci identified in human studies. We also show strong relationships between genotype and gut microbiota plasticity during HF/HS feeding and identify gut microbial phylotypes associated with obesity}, keywords = {HMDP, Mouse Genetics}, pubstate = {published}, tppubtype = {article} } Obesity is a highly heritable disease driven by complex interactions between genetic and environmental factors. Human genome-wide association studies (GWAS) have identified a number of loci contributing to obesity; however, a major limitation of these studies is the inability to assess environmental interactions common to obesity. Using a systems genetics approach, we measured obesity traits, global gene expression, and gut microbiota composition in response to a high-fat/high-sucrose (HF/HS) diet of more than 100 inbred strains of mice. Here we show that HF/HS feeding promotes robust, strain-specific changes in obesity that are not accounted for by food intake and provide evidence for a genetically determined set point for obesity. GWAS analysis identified 11 genome-wide significant loci associated with obesity traits, several of which overlap with loci identified in human studies. We also show strong relationships between genotype and gut microbiota plasticity during HF/HS feeding and identify gut microbial phylotypes associated with obesity |
Davis, Richard C; van Nas, Atila ; Bennett, Brian ; Orozco, Luz ; Pan, Calvin ; Rau, Christoph D; Eskin, Eleazar ; Lusis, Aldons J Genome-wide association mapping of blood cell traits in mice. Journal Article Mamm Genome, 2013, ISSN: 1432-1777. Abstract | Links | BibTeX | Tags: HMDP, Mouse Genetics @article{Davis:MammGenome:2013, title = {Genome-wide association mapping of blood cell traits in mice.}, author = { Richard C. Davis and Atila van Nas and Brian Bennett and Luz Orozco and Calvin Pan and Christoph D. Rau and Eleazar Eskin and Aldons J. Lusis}, url = {http://dx.doi.org/10.1007/s00335-013-9448-0}, issn = {1432-1777}, year = {2013}, date = {2013-01-01}, journal = {Mamm Genome}, organization = {Department of Medicine/Division of Cardiology, David Geffen School of Medicine, University of California, Los Angeles, CA, USA.}, abstract = {Genetic variations in blood cell parameters can impact clinical traits. We report here the mapping of blood cell traits in a panel of 100 inbred strains of mice of the Hybrid Mouse Diversity Panel (HMDP) using genome-wide association (GWA). We replicated a locus previously identified in using linkage analysis in several genetic crosses for mean corpuscular volume (MCV) and a number of other red blood cell traits on distal chromosome 7. Our peak for SNP association to MCV occurred in a linkage disequilibrium (LD) block spanning from 109.38 to 111.75Mb that includes Hbb-b1, the likely causal gene. Altogether, we identified five loci controlling red blood cell traits (on chromosomes 1, 7, 11, 12, and 16), and four of these correspond to loci for red blood cell traits reported in a recent human GWA study. For white blood cells, including granulocytes, monocytes, and lymphocytes, a total of six significant loci were identified on chromosomes 1, 6, 8, 11, 12, and 15. An average of ten candidate genes were found at each locus and those were prioritized by examining functional variants in the HMDP such as missense and expression variants. These results provide intermediate phenotypes and candidate loci for genetic studies of atherosclerosis and cancer as well as inflammatory and immune disorders in mice}, keywords = {HMDP, Mouse Genetics}, pubstate = {published}, tppubtype = {article} } Genetic variations in blood cell parameters can impact clinical traits. We report here the mapping of blood cell traits in a panel of 100 inbred strains of mice of the Hybrid Mouse Diversity Panel (HMDP) using genome-wide association (GWA). We replicated a locus previously identified in using linkage analysis in several genetic crosses for mean corpuscular volume (MCV) and a number of other red blood cell traits on distal chromosome 7. Our peak for SNP association to MCV occurred in a linkage disequilibrium (LD) block spanning from 109.38 to 111.75Mb that includes Hbb-b1, the likely causal gene. Altogether, we identified five loci controlling red blood cell traits (on chromosomes 1, 7, 11, 12, and 16), and four of these correspond to loci for red blood cell traits reported in a recent human GWA study. For white blood cells, including granulocytes, monocytes, and lymphocytes, a total of six significant loci were identified on chromosomes 1, 6, 8, 11, 12, and 15. An average of ten candidate genes were found at each locus and those were prioritized by examining functional variants in the HMDP such as missense and expression variants. These results provide intermediate phenotypes and candidate loci for genetic studies of atherosclerosis and cancer as well as inflammatory and immune disorders in mice |
2012 |
Bennett, Brian J; Orozco, Luz ; Kostem, Emrah ; Erbilgin, Ayca ; Dallinga, Marchien ; Neuhaus, Isaac ; Guan, Bo ; Wang, Xuping ; Eskin, Eleazar ; Lusis, Aldons J High-Resolution Association Mapping of Atherosclerosis Loci in Mice. Journal Article Arterioscler Thromb Vasc Biol, 2012, ISSN: 1524-4636. Abstract | Links | BibTeX | Tags: HMDP, Mouse Genetics @article{Bennett:ArteriosclerThrombVascBiol:2012, title = {High-Resolution Association Mapping of Atherosclerosis Loci in Mice.}, author = { Brian J. Bennett and Luz Orozco and Emrah Kostem and Ayca Erbilgin and Marchien Dallinga and Isaac Neuhaus and Bo Guan and Xuping Wang and Eleazar Eskin and Aldons J. Lusis}, url = {http://dx.doi.org/10.1161/ATVBAHA.112.253864}, issn = {1524-4636}, year = {2012}, date = {2012-01-01}, journal = {Arterioscler Thromb Vasc Biol}, organization = {Department of Genetics, University of North Carolina, Chapel Hill, NC.}, abstract = {OBJECTIVE: The purpose of this study was to fine map previously identified quantitative trait loci affecting atherosclerosis in mice using association analysis. METHODS AND RESULTS: We recently showed that high-resolution association analysis using common inbred strains of mice is feasible if corrected for population structure. To use this approach for atherosclerosis, which requires a sensitizing mutation, we bred human apolipoprotein B-100 transgenic mice with 22 different inbred strains to produce F1 heterozygotes. Mice carrying the dominant transgene were tested for association with high-density single nucleotide polymorphism maps. Here, we focus on high-resolution mapping of the previously described atherosclerosis 30 locus on chromosome 1. Compared with the previous linkage analysis, association improved the resolution of the atherosclerosis 30 locus by more than an order of magnitude. Using expression quantitative trait locus analysis, we identified one of the genes in the region, desmin, as a strong candidate. CONCLUSIONS: Our high-resolution mapping approach accurately identifies and fine maps known atherosclerosis quantitative trait loci. These results suggest that high-resolution genome-wide association analysis for atherosclerosis is feasible in mice.}, keywords = {HMDP, Mouse Genetics}, pubstate = {published}, tppubtype = {article} } OBJECTIVE: The purpose of this study was to fine map previously identified quantitative trait loci affecting atherosclerosis in mice using association analysis. METHODS AND RESULTS: We recently showed that high-resolution association analysis using common inbred strains of mice is feasible if corrected for population structure. To use this approach for atherosclerosis, which requires a sensitizing mutation, we bred human apolipoprotein B-100 transgenic mice with 22 different inbred strains to produce F1 heterozygotes. Mice carrying the dominant transgene were tested for association with high-density single nucleotide polymorphism maps. Here, we focus on high-resolution mapping of the previously described atherosclerosis 30 locus on chromosome 1. Compared with the previous linkage analysis, association improved the resolution of the atherosclerosis 30 locus by more than an order of magnitude. Using expression quantitative trait locus analysis, we identified one of the genes in the region, desmin, as a strong candidate. CONCLUSIONS: Our high-resolution mapping approach accurately identifies and fine maps known atherosclerosis quantitative trait loci. These results suggest that high-resolution genome-wide association analysis for atherosclerosis is feasible in mice. |
Ghazalpour, Anatole; Rau, Christoph D; Farber, Charles R; Bennett, Brian J; Orozco, Luz D; van Nas, Atila; Pan, Calvin; Allayee, Hooman; Beaven, Simon W; Civelek, Mete; Davis, Richard C; Drake, Thomas A; Friedman, Rick A; Furlotte, Nick; Hui, Simon T; Jentsch, David J; Kostem, Emrah; Kang, Hyun Min; Kang, Eun Yong; Joo, Jong Wha; Korshunov, Vyacheslav A; Laughlin, Rick E; Martin, Lisa J; Ohmen, Jeffrey D; Parks, Brian W; Pellegrini, Matteo; Reue, Karen; Smith, Desmond J; Tetradis, Sotirios; Wang, Jessica; Wang, Yibin; N, James Hybrid mouse diversity panel: a panel of inbred mouse strains suitable for analysis of complex genetic traits. Journal Article Mamm Genome, 2012, ISSN: 1432-1777. Abstract | Links | BibTeX | Tags: HMDP, Mouse Genetics @article{Ghazalpour:MammGenome:2012, title = {Hybrid mouse diversity panel: a panel of inbred mouse strains suitable for analysis of complex genetic traits.}, author = {Anatole Ghazalpour and Christoph D Rau and Charles R Farber and Brian J Bennett and Luz D Orozco and Atila van Nas and Calvin Pan and Hooman Allayee and Simon W Beaven and Mete Civelek and Richard C Davis and Thomas A Drake and Rick A Friedman and Nick Furlotte and Simon T Hui and J David Jentsch and Emrah Kostem and Hyun Min Kang and Eun Yong Kang and Jong Wha Joo and Vyacheslav A Korshunov and Rick E Laughlin and Lisa J Martin and Jeffrey D Ohmen and Brian W Parks and Matteo Pellegrini and Karen Reue and Desmond J Smith and Sotirios Tetradis and Jessica Wang and Yibin Wang and James N}, url = {http://dx.doi.org/10.1007/s00335-012-9411-5}, issn = {1432-1777}, year = {2012}, date = {2012-01-01}, journal = {Mamm Genome}, organization = {Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA, USA.}, abstract = {We have developed an association-based approach using classical inbred strains of mice in which we correct for population structure, which is very extensive in mice, using an efficient mixed-model algorithm. Our approach includes inbred parental strains as well as recombinant inbred strains in order to capture loci with effect sizes typical of complex traits in mice (in the range of 5% of total trait variance). Over the last few years, we have typed the hybrid mouse diversity panel (HMDP) strains for a variety of clinical traits as well as intermediate phenotypes and have shown that the HMDP has sufficient power to map genes for highly complex traits with resolution that is in most cases less than a megabase. In this essay, we review our experience with the HMDP, describe various ongoing projects, and discuss how the HMDP may fit into the larger picture of common diseases and different approaches.}, keywords = {HMDP, Mouse Genetics}, pubstate = {published}, tppubtype = {article} } We have developed an association-based approach using classical inbred strains of mice in which we correct for population structure, which is very extensive in mice, using an efficient mixed-model algorithm. Our approach includes inbred parental strains as well as recombinant inbred strains in order to capture loci with effect sizes typical of complex traits in mice (in the range of 5% of total trait variance). Over the last few years, we have typed the hybrid mouse diversity panel (HMDP) strains for a variety of clinical traits as well as intermediate phenotypes and have shown that the HMDP has sufficient power to map genes for highly complex traits with resolution that is in most cases less than a megabase. In this essay, we review our experience with the HMDP, describe various ongoing projects, and discuss how the HMDP may fit into the larger picture of common diseases and different approaches. |
Calabrese, Gina; Bennett, Brian J; Orozco, Luz ; Kang, Hyun M; Eskin, Eleazar ; Dombret, Carlos ; Backer, Olivier De ; Lusis, Aldons J; Farber, Charles R Systems genetic analysis of osteoblast-lineage cells. Journal Article PLoS Genet, 8 (12), pp. e1003150, 2012, ISSN: 1553-7404. Abstract | Links | BibTeX | Tags: HMDP, Mouse Genetics @article{Calabrese:PlosGenet:2012, title = {Systems genetic analysis of osteoblast-lineage cells.}, author = { Gina Calabrese and Brian J. Bennett and Luz Orozco and Hyun M. Kang and Eleazar Eskin and Carlos Dombret and Olivier De Backer and Aldons J. Lusis and Charles R. Farber}, url = {http://dx.doi.org/10.1371/journal.pgen.1003150}, issn = {1553-7404}, year = {2012}, date = {2012-01-01}, journal = {PLoS Genet}, volume = {8}, number = {12}, pages = {e1003150}, address = {United States}, organization = {Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, United States of America.}, abstract = {The osteoblast-lineage consists of cells at various stages of maturation that are essential for skeletal development, growth, and maintenance. Over the past decade, many of the signaling cascades that regulate this lineage have been elucidated; however, little is known of the networks that coordinate, modulate, and transmit these signals. Here, we identify a gene network specific to the osteoblast-lineage through the reconstruction of a bone co-expression network using microarray profiles collected on 96 Hybrid Mouse Diversity Panel (HMDP) inbred strains. Of the 21 modules that comprised the bone network, module 9 (M9) contained genes that were highly correlated with prototypical osteoblast maker genes and were more highly expressed in osteoblasts relative to other bone cells. In addition, the M9 contained many of the key genes that define the osteoblast-lineage, which together suggested that it was specific to this lineage. To use the M9 to identify novel osteoblast genes and highlight its biological relevance, we knocked-down the expression of its two most connected "hub" genes, Maged1 and Pard6g. Their perturbation altered both osteoblast proliferation and differentiation. Furthermore, we demonstrated the mice deficient in Maged1 had decreased bone mineral density (BMD). It was also discovered that a local expression quantitative trait locus (eQTL) regulating the Wnt signaling antagonist Sfrp1 was a key driver of the M9. We also show that the M9 is associated with BMD in the HMDP and is enriched for genes implicated in the regulation of human BMD through genome-wide association studies. In conclusion, we have identified a physiologically relevant gene network and used it to discover novel genes and regulatory mechanisms involved in the function of osteoblast-lineage cells. Our results highlight the power of harnessing natural genetic variation to generate co-expression networks that can be used to gain insight into the function of specific cell-types}, keywords = {HMDP, Mouse Genetics}, pubstate = {published}, tppubtype = {article} } The osteoblast-lineage consists of cells at various stages of maturation that are essential for skeletal development, growth, and maintenance. Over the past decade, many of the signaling cascades that regulate this lineage have been elucidated; however, little is known of the networks that coordinate, modulate, and transmit these signals. Here, we identify a gene network specific to the osteoblast-lineage through the reconstruction of a bone co-expression network using microarray profiles collected on 96 Hybrid Mouse Diversity Panel (HMDP) inbred strains. Of the 21 modules that comprised the bone network, module 9 (M9) contained genes that were highly correlated with prototypical osteoblast maker genes and were more highly expressed in osteoblasts relative to other bone cells. In addition, the M9 contained many of the key genes that define the osteoblast-lineage, which together suggested that it was specific to this lineage. To use the M9 to identify novel osteoblast genes and highlight its biological relevance, we knocked-down the expression of its two most connected "hub" genes, Maged1 and Pard6g. Their perturbation altered both osteoblast proliferation and differentiation. Furthermore, we demonstrated the mice deficient in Maged1 had decreased bone mineral density (BMD). It was also discovered that a local expression quantitative trait locus (eQTL) regulating the Wnt signaling antagonist Sfrp1 was a key driver of the M9. We also show that the M9 is associated with BMD in the HMDP and is enriched for genes implicated in the regulation of human BMD through genome-wide association studies. In conclusion, we have identified a physiologically relevant gene network and used it to discover novel genes and regulatory mechanisms involved in the function of osteoblast-lineage cells. Our results highlight the power of harnessing natural genetic variation to generate co-expression networks that can be used to gain insight into the function of specific cell-types |
2011 |
Ghazalpour, Anatole; Bennett, Brian; Petyuk, Vladislav A; Orozco, Luz; Hagopian, Raffi; Mungrue, Imran N; Farber, Charles R; Sinsheimer, Janet; Kang, Hyun M; Furlotte, Nicholas; Park, Christopher C; Wen, Ping-Zi; Brewer, Heather; Weitz, Karl; Camp, David G; Pan, Calvin; Yordanova, Roumyana; Neuhaus, Isaac; Tilford, Charles; Siemers, Nathan; Gargalovic, Peter; Eskin, Eleazar; Kirchgessner, Todd; Smith, Desmond J; Smith, Richard D; Lusis, Aldons J Comparative analysis of proteome and transcriptome variation in mouse. Journal Article PLoS Genet, 7 (6), pp. e1001393, 2011, ISSN: 1553-7404. Abstract | Links | BibTeX | Tags: HMDP, Mouse Genetics @article{Ghazalpour:PlosGenet:2011, title = {Comparative analysis of proteome and transcriptome variation in mouse.}, author = {Anatole Ghazalpour and Brian Bennett and Vladislav A Petyuk and Luz Orozco and Raffi Hagopian and Imran N Mungrue and Charles R Farber and Janet Sinsheimer and Hyun M Kang and Nicholas Furlotte and Christopher C Park and Ping-Zi Wen and Heather Brewer and Karl Weitz and David G Camp and Calvin Pan and Roumyana Yordanova and Isaac Neuhaus and Charles Tilford and Nathan Siemers and Peter Gargalovic and Eleazar Eskin and Todd Kirchgessner and Desmond J Smith and Richard D Smith and Aldons J Lusis}, url = {http://dx.doi.org/10.1371/journal.pgen.1001393}, issn = {1553-7404}, year = {2011}, date = {2011-01-01}, journal = {PLoS Genet}, volume = {7}, number = {6}, pages = {e1001393}, address = {United States}, organization = {Department of Medicine/Division of Cardiology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, United States of America.}, abstract = {The relationships between the levels of transcripts and the levels of the proteins they encode have not been examined comprehensively in mammals, although previous work in plants and yeast suggest a surprisingly modest correlation. We have examined this issue using a genetic approach in which natural variations were used to perturb both transcript levels and protein levels among inbred strains of mice. We quantified over 5,000 peptides and over 22,000 transcripts in livers of 97 inbred and recombinant inbred strains and focused on the 7,185 most heritable transcripts and 486 most reliable proteins. The transcript levels were quantified by microarray analysis in three replicates and the proteins were quantified by Liquid Chromatography-Mass Spectrometry using O(18)-reference-based isotope labeling approach. We show that the levels of transcripts and proteins correlate significantly for only about half of the genes tested, with an average correlation of 0.27, and the correlations of transcripts and proteins varied depending on the cellular location and biological function of the gene. We examined technical and biological factors that could contribute to the modest correlation. For example, differential splicing clearly affects the analyses for certain genes; but, based on deep sequencing, this does not substantially contribute to the overall estimate of the correlation. We also employed genome-wide association analyses to map loci controlling both transcript and protein levels. Surprisingly, little overlap was observed between the protein- and transcript-mapped loci. We have typed numerous clinically relevant traits among the strains, including adiposity, lipoprotein levels, and tissue parameters. Using correlation analysis, we found that a low number of clinical trait relationships are preserved between the protein and mRNA gene products and that the majority of such relationships are specific to either the protein levels or transcript levels. Surprisingly, transcript levels were more strongly correlated with clinical traits than protein levels. In light of the widespread use of high-throughput technologies in both clinical and basic research, the results presented have practical as well as basic implications.}, keywords = {HMDP, Mouse Genetics}, pubstate = {published}, tppubtype = {article} } The relationships between the levels of transcripts and the levels of the proteins they encode have not been examined comprehensively in mammals, although previous work in plants and yeast suggest a surprisingly modest correlation. We have examined this issue using a genetic approach in which natural variations were used to perturb both transcript levels and protein levels among inbred strains of mice. We quantified over 5,000 peptides and over 22,000 transcripts in livers of 97 inbred and recombinant inbred strains and focused on the 7,185 most heritable transcripts and 486 most reliable proteins. The transcript levels were quantified by microarray analysis in three replicates and the proteins were quantified by Liquid Chromatography-Mass Spectrometry using O(18)-reference-based isotope labeling approach. We show that the levels of transcripts and proteins correlate significantly for only about half of the genes tested, with an average correlation of 0.27, and the correlations of transcripts and proteins varied depending on the cellular location and biological function of the gene. We examined technical and biological factors that could contribute to the modest correlation. For example, differential splicing clearly affects the analyses for certain genes; but, based on deep sequencing, this does not substantially contribute to the overall estimate of the correlation. We also employed genome-wide association analyses to map loci controlling both transcript and protein levels. Surprisingly, little overlap was observed between the protein- and transcript-mapped loci. We have typed numerous clinically relevant traits among the strains, including adiposity, lipoprotein levels, and tissue parameters. Using correlation analysis, we found that a low number of clinical trait relationships are preserved between the protein and mRNA gene products and that the majority of such relationships are specific to either the protein levels or transcript levels. Surprisingly, transcript levels were more strongly correlated with clinical traits than protein levels. In light of the widespread use of high-throughput technologies in both clinical and basic research, the results presented have practical as well as basic implications. |
Park, Christopher C; Gale, Greg D; de Jong, Simone ; Ghazalpour, Anatole ; Bennett, Brian J; Farber, Charles R; Langfelder, Peter ; Lin, Andy ; Khan, Arshad H; Eskin, Eleazar ; Horvath, Steve ; Lusis, Aldons J; Ophoff, Roel A; Smith, Desmond J Gene networks associated with conditional fear in mice identified using a systems genetics approach. Journal Article BMC Syst Biol, 5 , pp. 43, 2011, ISSN: 1752-0509. Abstract | Links | BibTeX | Tags: HMDP, Mouse Genetics @article{Park:BmcSystBiol:2011, title = {Gene networks associated with conditional fear in mice identified using a systems genetics approach.}, author = { Christopher C. Park and Greg D. Gale and Simone de Jong and Anatole Ghazalpour and Brian J. Bennett and Charles R. Farber and Peter Langfelder and Andy Lin and Arshad H. Khan and Eleazar Eskin and Steve Horvath and Aldons J. Lusis and Roel A. Ophoff and Desmond J. Smith}, url = {http://dx.doi.org/10.1186/1752-0509-5-43}, issn = {1752-0509}, year = {2011}, date = {2011-01-01}, journal = {BMC Syst Biol}, volume = {5}, pages = {43}, address = {England}, organization = {Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA. DSmith@mednet.ucla.edu.}, abstract = {UNLABELLED: ABSTRACT: BACKGROUND: Our understanding of the genetic basis of learning and memory remains shrouded in mystery. To explore the genetic networks governing the biology of conditional fear, we used a systems genetics approach to analyze a hybrid mouse diversity panel (HMDP) with high mapping resolution. RESULTS: A total of 27 behavioral quantitative trait loci were mapped with a false discovery rate of 5%. By integrating fear phenotypes, transcript profiling data from hippocampus and striatum and also genotype information, two gene co-expression networks correlated with context-dependent immobility were identified. We prioritized the key markers and genes in these pathways using intramodular connectivity measures and structural equation modeling. Highly connected genes in the context fear modules included Psmd6, Ube2a and Usp33, suggesting an important role for ubiquitination in learning and memory. In addition, we surveyed the architecture of brain transcript regulation and demonstrated preservation of gene co-expression modules in hippocampus and striatum, while also highlighting important differences. Rps15a, Kif3a, Stard7, 6330503K22RIK, and Plvap were among the individual genes whose transcript abundance were strongly associated with fear phenotypes. CONCLUSION: Application of our multi-faceted mapping strategy permits an increasingly detailed characterization of the genetic networks underlying behavior.}, keywords = {HMDP, Mouse Genetics}, pubstate = {published}, tppubtype = {article} } UNLABELLED: ABSTRACT: BACKGROUND: Our understanding of the genetic basis of learning and memory remains shrouded in mystery. To explore the genetic networks governing the biology of conditional fear, we used a systems genetics approach to analyze a hybrid mouse diversity panel (HMDP) with high mapping resolution. RESULTS: A total of 27 behavioral quantitative trait loci were mapped with a false discovery rate of 5%. By integrating fear phenotypes, transcript profiling data from hippocampus and striatum and also genotype information, two gene co-expression networks correlated with context-dependent immobility were identified. We prioritized the key markers and genes in these pathways using intramodular connectivity measures and structural equation modeling. Highly connected genes in the context fear modules included Psmd6, Ube2a and Usp33, suggesting an important role for ubiquitination in learning and memory. In addition, we surveyed the architecture of brain transcript regulation and demonstrated preservation of gene co-expression modules in hippocampus and striatum, while also highlighting important differences. Rps15a, Kif3a, Stard7, 6330503K22RIK, and Plvap were among the individual genes whose transcript abundance were strongly associated with fear phenotypes. CONCLUSION: Application of our multi-faceted mapping strategy permits an increasingly detailed characterization of the genetic networks underlying behavior. |
Farber, Charles R; Bennett, Brian J; Orozco, Luz; Zou, Wei; Lira, Ana; Kostem, Emrah; Kang, Hyun Min; Furlotte, Nicholas; Berberyan, Ani; Ghazalpour, Anatole; Suwanwela, Jaijam; Drake, Thomas A; Eskin, Eleazar; Wang, Tian Q; Teitelbaum, Steven L; Lusis, Aldons J Mouse genome-wide association and systems genetics identify asxl2 as a regulator of bone mineral density and osteoclastogenesis. Journal Article PLoS Genet, 7 (4), pp. e1002038, 2011, ISSN: 1553-7404. Abstract | Links | BibTeX | Tags: HMDP, Mouse Genetics @article{Farber:PlosGenet:2011, title = {Mouse genome-wide association and systems genetics identify asxl2 as a regulator of bone mineral density and osteoclastogenesis.}, author = {Charles R Farber and Brian J Bennett and Luz Orozco and Wei Zou and Ana Lira and Emrah Kostem and Hyun Min Kang and Nicholas Furlotte and Ani Berberyan and Anatole Ghazalpour and Jaijam Suwanwela and Thomas A Drake and Eleazar Eskin and Q Tian Wang and Steven L Teitelbaum and Aldons J Lusis}, url = {http://dx.doi.org/10.1371/journal.pgen.1002038}, issn = {1553-7404}, year = {2011}, date = {2011-01-01}, journal = {PLoS Genet}, volume = {7}, number = {4}, pages = {e1002038}, address = {United States}, organization = {Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, United States of America.}, abstract = {Significant advances have been made in the discovery of genes affecting bone mineral density (BMD); however, our understanding of its genetic basis remains incomplete. In the current study, genome-wide association (GWA) and co-expression network analysis were used in the recently described Hybrid Mouse Diversity Panel (HMDP) to identify and functionally characterize novel BMD genes. In the HMDP, a GWA of total body, spinal, and femoral BMD revealed four significant associations (-log10P>5.39) affecting at least one BMD trait on chromosomes (Chrs.) 7, 11, 12, and 17. The associations implicated a total of 163 genes with each association harboring between 14 and 112 genes. This list was reduced to 26 functional candidates by identifying those genes that were regulated by local eQTL in bone or harbored potentially functional non-synonymous (NS) SNPs. This analysis revealed that the most significant BMD SNP on Chr. 12 was a NS SNP in the additional sex combs like-2 (Asxl2) gene that was predicted to be functional. The involvement of Asxl2 in the regulation of bone mass was confirmed by the observation that Asxl2 knockout mice had reduced BMD. To begin to unravel the mechanism through which Asxl2 influenced BMD, a gene co-expression network was created using cortical bone gene expression microarray data from the HMDP strains. Asxl2 was identified as a member of a co-expression module enriched for genes involved in the differentiation of myeloid cells. In bone, osteoclasts are bone-resorbing cells of myeloid origin, suggesting that Asxl2 may play a role in osteoclast differentiation. In agreement, the knockdown of Asxl2 in bone marrow macrophages impaired their ability to form osteoclasts. This study identifies a new regulator of BMD and osteoclastogenesis and highlights the power of GWA and systems genetics in the mouse for dissecting complex genetic traits.}, keywords = {HMDP, Mouse Genetics}, pubstate = {published}, tppubtype = {article} } Significant advances have been made in the discovery of genes affecting bone mineral density (BMD); however, our understanding of its genetic basis remains incomplete. In the current study, genome-wide association (GWA) and co-expression network analysis were used in the recently described Hybrid Mouse Diversity Panel (HMDP) to identify and functionally characterize novel BMD genes. In the HMDP, a GWA of total body, spinal, and femoral BMD revealed four significant associations (-log10P>5.39) affecting at least one BMD trait on chromosomes (Chrs.) 7, 11, 12, and 17. The associations implicated a total of 163 genes with each association harboring between 14 and 112 genes. This list was reduced to 26 functional candidates by identifying those genes that were regulated by local eQTL in bone or harbored potentially functional non-synonymous (NS) SNPs. This analysis revealed that the most significant BMD SNP on Chr. 12 was a NS SNP in the additional sex combs like-2 (Asxl2) gene that was predicted to be functional. The involvement of Asxl2 in the regulation of bone mass was confirmed by the observation that Asxl2 knockout mice had reduced BMD. To begin to unravel the mechanism through which Asxl2 influenced BMD, a gene co-expression network was created using cortical bone gene expression microarray data from the HMDP strains. Asxl2 was identified as a member of a co-expression module enriched for genes involved in the differentiation of myeloid cells. In bone, osteoclasts are bone-resorbing cells of myeloid origin, suggesting that Asxl2 may play a role in osteoclast differentiation. In agreement, the knockdown of Asxl2 in bone marrow macrophages impaired their ability to form osteoclasts. This study identifies a new regulator of BMD and osteoclastogenesis and highlights the power of GWA and systems genetics in the mouse for dissecting complex genetic traits. |
2010 |
Bennett, Brian J; Farber, Charles R; Orozco, Luz; Kang, Hyun Min; Ghazalpour, Anatole; Siemers, Nathan; Neubauer, Michael; Neuhaus, Isaac; Yordanova, Roumyana; Guan, Bo; Truong, Amy; Yang, Wen-Pin; He, Aiqing; Kayne, Paul; Gargalovic, Peter; Kirchgessner, Todd; Pan, Calvin; Castellani, Lawrence W; Kostem, Emrah; Furlotte, Nicholas; Drake, Thomas A; Eskin, Eleazar; Lusis, Aldons J A high-resolution association mapping panel for the dissection of complex traits in mice. Journal Article Genome Res, 20 (2), pp. 281-90, 2010, ISSN: 1549-5469. Abstract | Links | BibTeX | Tags: HMDP, Mouse Genetics @article{Bennett:GenomeRes:2010, title = {A high-resolution association mapping panel for the dissection of complex traits in mice.}, author = {Brian J Bennett and Charles R Farber and Luz Orozco and Hyun Min Kang and Anatole Ghazalpour and Nathan Siemers and Michael Neubauer and Isaac Neuhaus and Roumyana Yordanova and Bo Guan and Amy Truong and Wen-Pin Yang and Aiqing He and Paul Kayne and Peter Gargalovic and Todd Kirchgessner and Calvin Pan and Lawrence W Castellani and Emrah Kostem and Nicholas Furlotte and Thomas A Drake and Eleazar Eskin and Aldons J Lusis}, url = {http://dx.doi.org/10.1101/gr.099234.109}, issn = {1549-5469}, year = {2010}, date = {2010-01-01}, journal = {Genome Res}, volume = {20}, number = {2}, pages = {281-90}, address = {United States}, organization = {Department of Medicine/Division of Cardiology, David Geffen School of Medicine, University of California, Los Angeles California 90095, USA;}, abstract = {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.}, keywords = {HMDP, Mouse Genetics}, pubstate = {published}, tppubtype = {article} } 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. |