Charles R. Farber

A high-resolution association mapping panel for the dissection of complex traits in mice.

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.

An Integration of Genome-Wide Association Study and Gene Expression Profiling to Prioritize the Discovery of Novel Susceptibility Loci for Osteoporosis-Related Traits

Osteoporosis is a complex disorder and commonly leads to fractures in elderly persons. Genome-wide association studies (GWAS) have become an unbiased approach to identify variations in the genome that potentially affect health. However, the genetic variants identified so far only explain a small proportion of the heritability for complex traits. Due to the modest genetic effect size and inadequate power, true association signals may not be revealed based on a stringent genome-wide significance threshold. Here, we take advantage of SNP and transcript arrays and integrate GWAS and expression signature profiling relevant to the skeletal system in cellular and animal models to prioritize the discovery of novel candidate genes for osteoporosis-related traits, including bone mineral density (BMD) at the lumbar spine (LS) and femoral neck (FN), as well as geometric indices of the hip (femoral neck-shaft angle, NSA; femoral neck length, NL; and narrow-neck width, NW). A two-stage meta-analysis of GWAS from 7,633 Caucasian women and 3,657 men, revealed three novel loci associated with osteoporosis-related traits, including chromosome 1p13.2 (RAP1A, p = 3.6×10−8), 2q11.2 (TBC1D8), and 18q11.2 (OSBPL1A), and confirmed a previously reported region near TNFRSF11B/OPG gene. We also prioritized 16 suggestive genome-wide significant candidate genes based on their potential involvement in skeletal metabolism. Among them, 3 candidate genes were associated with BMD in women. Notably, 2 out of these 3 genes (GPR177, p = 2.6×10−13; SOX6, p = 6.4×10−10) associated with BMD in women have been successfully replicated in a large-scale meta-analysis of BMD, but none of the non-prioritized candidates (associated with BMD) did. Our results support the concept of our prioritization strategy. In the absence of direct biological support for identified genes, we highlighted the efficiency of subsequent functional characterization using publicly available expression profiling relevant to the skeletal system in cellular or whole animal models to prioritize candidate genes for further functional validation.

Mouse Genome-Wide Association and Systems Genetics Identify Asxl2 As a Regulator of Bone Mineral Density and Osteoclastogenesis

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.

Glucagon Regulates Hepatic Kisspeptin to Impair Insulin Secretion

Early in the pathogenesis of type 2 diabetes mellitus (T2DM), dysregulated glucagon secretion from pancreatic α cells occurs prior to impaired glucose-stimulated insulin secretion (GSIS) from β cells. However, whether hyperglucagonemia is causally linked to β cell dysfunction remains unclear. Here we show that glucagon stimulates via cAMP-PKA-CREB signaling hepatic production of the neuropeptide kisspeptin1, which acts on β cells to suppress GSIS. Synthetic kisspeptin suppresses GSIS in vivo in mice and from isolated islets in a kisspeptin1 receptor-dependent manner. Kisspeptin1 is increased in livers and in serum from humans with T2DM and from mouse models of diabetes mellitus. Importantly, liver Kiss1 knockdown in hyperglucagonemic, glucose-intolerant, high-fat-diet fed, and Lepr(db/db) mice augments GSIS and improves glucose tolerance. These observations indicate a hormonal circuit between the liver and the endocrine pancreas in glycemia regulation and suggest in T2DM a sequential link between hyperglucagonemia via hepatic kisspeptin1 to impaired insulin secretion.

Gene networks associated with conditional fear in mice identified using a systems genetics approach

BackgroundOur 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.ResultsA 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.ConclusionApplication of our multi-faceted mapping strategy permits an increasingly detailed characterization of the genetic networks underlying behavior.

An integrative genetics approach to identify candidate genes regulating BMD: combining linkage, gene expression, and association.

Numerous quantitative trait loci (QTLs) affecting bone traits have been identified in the mouse; however, few of the underlying genes have been discovered. To improve the process of transitioning from QTL to gene, we describe an integrative genetics approach, which combines linkage analysis, expression QTL (eQTL) mapping, causality modeling, and genetic association in outbred mice. In C57BL/6J × C3H/HeJ (BXH) F2 mice, nine QTLs regulating femoral BMD were identified. To select candidate genes from within each QTL region, microarray gene expression profiles from individual F2 mice were used to identify 148 genes whose expression was correlated with BMD and regulated by local eQTLs. Many of the genes that were the most highly correlated with BMD have been previously shown to modulate bone mass or skeletal development. Candidates were further prioritized by determining whether their expression was predicted to underlie variation in BMD. Using network edge orienting (NEO), a causality modeling algorithm, 18 of the 148 candidates were predicted to be causally related to differences in BMD. To fine‐map QTLs, markers in outbred MF1 mice were tested for association with BMD. Three chromosome 11 SNPs were identified that were associated with BMD within the Bmd11 QTL. Finally, our approach provides strong support for Wnt9a, Rasd1, or both underlying Bmd11. Integration of multiple genetic and genomic data sets can substantially improve the efficiency of QTL fine‐mapping and candidate gene identification.

MicroRNA-93 Controls Perfusion Recovery After Hindlimb Ischemia by Modulating Expression of Multiple Genes in the Cell Cycle Pathway

Background— MicroRNAs are key regulators of gene expression in response to injury, but there is limited knowledge of their role in ischemia-induced angiogenesis, such as in peripheral arterial disease. Here, we used an unbiased strategy and took advantage of different phenotypic outcomes that follow surgically induced hindlimb ischemia between inbred mouse strains to identify key microRNAs involved in perfusion recovery from hindlimb ischemia. Methods and Results— From comparative microRNA profiling between inbred mouse strains that display profound differences in their extent of perfusion recovery after hindlimb ischemia, we found that the mouse strain with higher levels of microRNA-93 (miR-93) in hindlimb muscle before ischemia and the greater ability to upregulate miR-93 in response to ischemia had better perfusion recovery. In vitro, overexpression of miR-93 attenuated hypoxia-induced apoptosis in both endothelial and skeletal muscle cells and enhanced proliferation in both cell types. In addition, miR-93 overexpression enhanced endothelial cell tube formation. In vivo, miR-93 overexpression enhanced capillary density and perfusion recovery from hindlimb ischemia, and antagomirs to miR-93 attenuated perfusion recovery. Both in vitro and in vivo modulation of miR-93 resulted in alterations in the expression of >1 cell cycle pathway gene in 2 different cell types. Conclusions— Our data indicate that miR-93 enhances perfusion recovery from hindlimb ischemia by modulation of multiple genes that coordinate the functional pathways of cell proliferation and apoptosis. Thus, miR-93 is a strong potential target for pharmacological modulation to promote angiogenesis in ischemic tissue.

Hippocampal gene expression analysis highlights Ly6a/Sca-1 as candidate gene for previously mapped novelty induced behaviors in mice.

In this study, we show that the covariance between behavior and gene expression in the brain can help further unravel the determinants of neurobehavioral traits. Previously, a QTL for novelty induced motor activity levels was identified on murine chromosome 15 using consomic strains. With the goal of narrowing down the linked region and possibly identifying the gene underlying the quantitative trait, gene expression data from this F2-population was collected and used for expression QTL analysis. While genetic variation in these mice was limited to chromosome 15, eQTL analysis of gene expression showed strong cis-effects as well as trans-effects elsewhere in the genome. Using weighted gene co-expression network analysis, we were able to identify modules of co-expressed genes related to novelty induced motor activity levels. In eQTL analyses, the expression of Ly6a (a.k.a. Sca-1) was found to be cis-regulated by chromosome 15. Ly6a also surfaced in a group of genes resulting from the network analysis that was correlated with behavior. Behavioral analysis of Ly6a knock-out mice revealed reduced novelty induced motor activity levels when compared to wild type controls, confirming functional importance of Ly6a in this behavior, possibly through regulating other genes in a pathway. This study shows that gene expression profiling can be used to narrow down a previously identified behavioral QTL in mice, providing support for Ly6a as a candidate gene for functional involvement in novelty responsiveness.

Wnt-Lrp5 Signaling Regulates Fatty Acid Metabolism in the Osteoblast

ABSTRACT The Wnt coreceptors Lrp5 and Lrp6 are essential for normal postnatal bone accrual and osteoblast function. In this study, we identify a previously unrecognized skeletal function unique to Lrp5 that enables osteoblasts to oxidize fatty acids. Mice lacking the Lrp5 coreceptor specifically in osteoblasts and osteocytes exhibit the expected reductions in postnatal bone mass but also exhibit an increase in body fat with corresponding reductions in energy expenditure. Conversely, mice expressing a high bone mass mutant Lrp5 allele are leaner with reduced plasma triglyceride and free fatty acid levels. In this context, Wnt-initiated signals downstream of Lrp5, but not the closely related Lrp6 coreceptor, regulate the activation of β-catenin and thereby induce the expression of key enzymes required for fatty acid β-oxidation. These results suggest that Wnt-Lrp5 signaling regulates basic cellular activities beyond those associated with fate specification and differentiation in bone and that the skeleton influences global energy homeostasis via mechanisms independent of osteocalcin and glucose metabolism.

Epigenome-Wide Association of Liver Methylation Patterns and Complex Metabolic Traits in Mice

Heritable epigenetic factors can contribute to complex disease etiology. Here we examine the contribution of DNA methylation to complex traits that are precursors to heart disease, diabetes, and osteoporosis. We profiled DNA methylation in the liver using bisulfite sequencing in 90 mouse inbred strains, genome-wide expression levels, proteomics, metabolomics, and 68 clinical traits and performed epigenome-wide association studies (EWAS). We found associations with numerous clinical traits including bone density, insulin resistance, expression, and protein and metabolite levels. A large proportion of associations were unique to EWAS and were not identified using GWAS. Methylation levels were regulated by genetics largely in cis, but we also found evidence of trans regulation, and we demonstrate that genetic variation in the methionine synthase reductase gene Mtrr affects methylation of hundreds of CpGs throughout the genome. Our results indicate that natural variation in methylation levels contributes to the etiology of complex clinical traits.