Genetic and environmental control of host-gut microbiota interactions.

Genetics provides a potentially powerful approach to dissect host-gut microbiota interactions. Toward this end, we profiled gut microbiota using 16s rRNA gene sequencing in a panel of 110 diverse inbred strains of mice. This panel has previously been studied for a wide range of metabolic traits and can be used for high-resolution association mapping. Using a SNP-based approach with a linear mixed model, we estimated the heritability of microbiota composition. We conclude that, in a controlled environment, the genetic background accounts for a substantial fraction of abundance of most common microbiota. The mice were previously studied for response to a high-fat, high-sucrose diet, and we hypothesized that the dietary response was determined in part by gut microbiota composition. We tested this using a cross-fostering strategy in which a strain showing a modest response, SWR, was seeded with microbiota from a strain showing a strong response, A×B19. Consistent with a role of microbiota in dietary response, the cross-fostered SWR pups exhibited a significantly increased response in weight gain. To examine specific microbiota contributing to the response, we identified various genera whose abundance correlated with dietary response. Among these, we chose Akkermansia muciniphila, a common anaerobe previously associated with metabolic effects. When administered to strain A×B19 by gavage, the dietary response was significantly blunted for obesity, plasma lipids, and insulin resistance. In an effort to further understand host-microbiota interactions, we mapped loci controlling microbiota composition and prioritized candidate genes. Our publicly available data provide a resource for future studies.

Allele-specific expression and eQTL analysis in mouse adipose tissue.

BACKGROUND: The simplest definition of cis-eQTLs versus trans, refers to genetic variants that affect expression in an allele specific manner, with implications on underlying mechanism. Yet, due to technical limitations of expression microarrays, the vast majority of eQTL studies performed in the last decade used a genomic distance based definition as a surrogate for cis, therefore exploring local rather than cis-eQTLs. RESULTS: In this study we use RNAseq to explore allele specific expression (ASE) in adipose tissue of male and female F1 mice, produced from reciprocal crosses of C57BL/6J and DBA/2J strains. Comparison of the identified cis-eQTLs, to local-eQTLs, that were obtained from adipose tissue expression in two previous population based studies in our laboratory, yields poor overlap between the two mapping approaches, while both local-eQTL studies show highly concordant results. Specifically, local-eQTL studies show ~60% overlap between themselves, while only 15-20% of local-eQTLs are identified as cis by ASE, and less than 50% of ASE genes are recovered in local-eQTL studies. Utilizing recently published ENCODE data, we also find that ASE genes show significant bias for SNPs prevalence in DNase I hypersensitive sites that is ASE direction specific. CONCLUSIONS: We suggest a new approach to analysis of allele specific expression that is more sensitive and accurate than the commonly used fisher or chi-square statistics. Our analysis indicates that technical differences between the cis and local-eQTL approaches, such as differences in genomic background or sex specificity, account for relatively small fraction of the discrepancy. Therefore, we suggest that the differences between two eQTL mapping approaches may facilitate sorting of SNP-eQTL interactions into true cis and trans, and that a considerable portion of local-eQTL may actually represent trans interactions.

ABCC6 localizes to the mitochondria-associated membrane.

RATIONALE: Mutations of the orphan transporter ABCC6 (ATP-binding cassette, subfamily C, member 6) cause the connective tissue disorder pseudoxanthoma elasticum. ABCC6 was thought to be located on the plasma membrane of liver and kidney cells. OBJECTIVE: Mouse systems genetics and bioinformatics suggested that ABCC6 deficiency affects mitochondrial gene expression. We therefore tested whether ABCC6 associates with mitochondria. METHODS AND RESULTS: We found ABCC6 in crude mitochondrial fractions and subsequently pinpointed its localization to the purified mitochondria-associated membrane fraction. Cell-surface biotinylation in hepatocytes confirmed that ABCC6 is intracellular. Abcc6-knockout mice demonstrated mitochondrial abnormalities and decreased respiration reserve capacity. CONCLUSIONS: Our finding that ABCC6 localizes to the mitochondria-associated membrane has implications for its mechanism of action in normal and diseased states.

Variations in DNA elucidate molecular networks that cause disease.

Identifying variations in DNA that increase susceptibility to disease is one of the primary aims of genetic studies using a forward genetics approach. However, identification of disease-susceptibility genes by means of such studies provides limited functional information on how genes lead to disease. In fact, in most cases there is an absence of functional information altogether, preventing a definitive identification of the susceptibility gene or genes. Here we develop an alternative to the classic forward genetics approach for dissecting complex disease traits where, instead of identifying susceptibility genes directly affected by variations in DNA, we identify gene networks that are perturbed by susceptibility loci and that in turn lead to disease. Application of this method to liver and adipose gene expression data generated from a segregating mouse population results in the identification of a macrophage-enriched network supported as having a causal relationship with disease traits associated with metabolic syndrome. Three genes in this network, lipoprotein lipase (Lpl), lactamase beta (Lactb) and protein phosphatase 1-like (Ppm1l), are validated as previously unknown obesity genes, strengthening the association between this network and metabolic disease traits. Our analysis provides direct experimental support that complex traits such as obesity are emergent properties of molecular networks that are modulated by complex genetic loci and environmental factors.

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.

Integrating genotypic and expression data in a segregating mouse population to identify 5-lipoxygenase as a susceptibility gene for obesity and bone traits.

Forward genetic approaches to identify genes involved in complex traits such as common human diseases have met with limited success. Fine mapping of linkage regions and validation of positional candidates are time-consuming and not always successful. Here we detail a hybrid procedure to map loci involved in complex traits that leverages the strengths of forward and reverse genetic approaches. By integrating genotypic and expression data in a segregating mouse population, we show how clusters of expression quantitative trait loci linking to regions of the genome accurately reflect the underlying perturbation to the transcriptional network induced by DNA variations in genes that control the complex traits. By matching patterns of gene expression in a segregating population with expression responses induced by single-gene perturbation experiments, we show how genes controlling clusters of expression and clinical quantitative trait loci can be mapped directly. We demonstrate the utility of this approach by identifying 5-lipoxygenase as underlying previously identified quantitative trait loci in an F(2) cross between strains C57BL/6J and DBA/2J and showing that it has pleiotropic effects on body fat, lipid levels and bone density.

An integrative genomics approach to infer causal associations between gene expression and disease.

A key goal of biomedical research is to elucidate the complex network of gene interactions underlying complex traits such as common human diseases. Here we detail a multistep procedure for identifying potential key drivers of complex traits that integrates DNA-variation and gene-expression data with other complex trait data in segregating mouse populations. Ordering gene expression traits relative to one another and relative to other complex traits is achieved by systematically testing whether variations in DNA that lead to variations in relative transcript abundances statistically support an independent, causative or reactive function relative to the complex traits under consideration. We show that this approach can predict transcriptional responses to single gene-perturbation experiments using gene-expression data in the context of a segregating mouse population. We also demonstrate the utility of this approach by identifying and experimentally validating the involvement of three new genes in susceptibility to obesity.

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.

Upstream transcription factor 1 influences plasma lipid and metabolic traits in mice.

Upstream transcription factor 1 (USF1) has been associated with familial combined hyperlipidemia, the metabolic syndrome, and related conditions, but the mechanisms involved are unknown. In this study, we report validation of Usf1 as a causal gene of cholesterol homeostasis, insulin sensitivity and body composition in mouse models using several complementary approaches and identify associated pathways and gene expression network modules. Over-expression of human USF1 in both transgenic mice and mice with transient liver-specific over-expression influenced metabolic trait phenotypes, including obesity, total cholesterol level, LDL/VLDL cholesterol and glucose/insulin ratio. Additional analyses of trait and hepatic gene expression data from an F2 population derived from C57BL/6J and C3H/HeJ strains in which there is a naturally occurring variation in Usf1 expression supported a causal role for Usf1 for relevant metabolic traits. Gene network and pathway analyses of the liver gene expression signatures in the F2 population and the hepatic over-expression model suggested the involvement of Usf1 in immune responses and metabolism, including an Igfbp2-centered module. In all three mouse model settings, notable sex specificity was observed, consistent with human studies showing differences in association with USF1 gene polymorphisms between sexes.

Hybrid mouse diversity panel: a panel of inbred mouse strains suitable for analysis of complex genetic traits.

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.

Abcc6 deficiency causes increased infarct size and apoptosis in a mouse cardiac ischemia-reperfusion model.

OBJECTIVE: ABCC6 genetic deficiency underlies pseudoxanthoma elasticum (PXE) in humans, characterized by ectopic calcification, and early cardiac disease. The spectrum of PXE has been noted in Abcc6-deficient mice, including dystrophic cardiac calcification. We tested the role of Abcc6 in response to cardiac ischemia-reperfusion (I/R) injury. METHODS AND RESULTS: To determine the role of Abcc6 in cardioprotection, we induced ischemic injury in mice in vivo by occluding the left anterior descending artery (30 minutes) followed by reperfusion (48 hours). Infarct size was increased in Abcc6-deficient mice compared with wild-type controls. Additionally, an Abcc6 transgene significantly reduced infarct size on the background of a naturally occurring Abcc6 deficiency. There were no differences in cardiac calcification following I/R, but increased cardiac apoptosis was noted in Abcc6-deficient mice. Previous studies have implicated the bone morphogenetic protein (BMP) signaling pathway in directing calcification, and here we showed that the BMP responsive transcription factors pSmad1/5/8 were increased in hearts of Abcc6 mice. Consistent with this finding, BMP4 and BMP9 were increased and activin receptor-like kinase-2 and endoglin were downregulated in cardiac extracts from Abcc6-deficient mice versus controls. CONCLUSIONS: These data identify Abcc6 as a novel modulator of cardiac myocyte survival after I/R. This cardioprotective mechanism may involve inhibition of the BMP signaling pathway, which modulates apoptosis.

Mapping the genetic architecture of gene expression in human liver.

Genetic variants that are associated with common human diseases do not lead directly to disease, but instead act on intermediate, molecular phenotypes that in turn induce changes in higher-order disease traits. Therefore, identifying the molecular phenotypes that vary in response to changes in DNA and that also associate with changes in disease traits has the potential to provide the functional information required to not only identify and validate the susceptibility genes that are directly affected by changes in DNA, but also to understand the molecular networks in which such genes operate and how changes in these networks lead to changes in disease traits. Toward that end, we profiled more than 39,000 transcripts and we genotyped 782,476 unique single nucleotide polymorphisms (SNPs) in more than 400 human liver samples to characterize the genetic architecture of gene expression in the human liver, a metabolically active tissue that is important in a number of common human diseases, including obesity, diabetes, and atherosclerosis. This genome-wide association study of gene expression resulted in the detection of more than 6,000 associations between SNP genotypes and liver gene expression traits, where many of the corresponding genes identified have already been implicated in a number of human diseases. The utility of these data for elucidating the causes of common human diseases is demonstrated by integrating them with genotypic and expression data from other human and mouse populations. This provides much-needed functional support for the candidate susceptibility genes being identified at a growing number of genetic loci that have been identified as key drivers of disease from genome-wide association studies of disease. By using an integrative genomics approach, we highlight how the gene RPS26 and not ERBB3 is supported by our data as the most likely susceptibility gene for a novel type 1 diabetes locus recently identified in a large-scale, genome-wide association study. We also identify SORT1 and CELSR2 as candidate susceptibility genes for a locus recently associated with coronary artery disease and plasma low-density lipoprotein cholesterol levels in the process.

High-resolution mapping of gene expression using association in an outbred mouse stock.

Quantitative trait locus (QTL) analysis is a powerful tool for mapping genes for complex traits in mice, but its utility is limited by poor resolution. A promising mapping approach is association analysis in outbred stocks or different inbred strains. As a proof of concept for the association approach, we applied whole-genome association analysis to hepatic gene expression traits in an outbred mouse population, the MF1 stock, and replicated expression QTL (eQTL) identified in previous studies of F2 intercross mice. We found that the mapping resolution of these eQTL was significantly greater in the outbred population. Through an example, we also showed how this precise mapping can be used to resolve previously identified loci (in intercross studies), which affect many different transcript levels (known as eQTL "hotspots"), into distinct regions. Our results also highlight the importance of correcting for population structure in whole-genome association studies in the outbred stock.

Identification of pathways for atherosclerosis in mice: integration of quantitative trait locus analysis and global gene expression data.

We report a combined genetic and genomic analysis of atherosclerosis in a cross between the strains C3H/HeJ and C57BL/6J on a hyperlipidemic apolipoprotein E-null background. We incorporated sex and sex-by-genotype interactions into our model selection procedure to identify 10 quantitative trait loci for lesion size, revealing a level of complexity greater than previously thought. Of the known risk factors for atherosclerosis, plasma triglyceride levels and plasma glucose to insulin ratios were particularly strongly, but negatively, associated with lesion size. We performed expression array analysis for 23,574 transcripts of the livers and adipose tissues of all 334 F2 mice and identified more than 10,000 expression quantitative trait loci that either mapped to the gene encoding the transcript, implying cis regulation, or to a separate locus, implying trans-regulation. The gene expression data allowed us to identify candidate genes that mapped to the atherosclerosis quantitative trait loci and for which the expression was regulated in cis. Genes highly correlated with lesions were enriched in certain known pathways involved in lesion development, including cholesterol metabolism, mitochondrial oxidative phosphorylation, and inflammation. Thus, global gene expression in peripheral tissues can reflect the systemic perturbations that contribute to atherosclerosis.

Genetic and genomic analysis of a fat mass trait with complex inheritance reveals marked sex specificity.

The integration of expression profiling with linkage analysis has increasingly been used to identify genes underlying complex phenotypes. The effects of gender on the regulation of many physiological traits are well documented; however, "genetical genomic" analyses have not yet addressed the degree to which their conclusions are affected by sex. We constructed and densely genotyped a large F2 intercross derived from the inbred mouse strains C57BL/6J and C3H/HeJ on an apolipoprotein E null (ApoE-/-) background. This BXH.ApoE-/- population recapitulates several "metabolic syndrome" phenotypes. The cross consists of 334 animals of both sexes, allowing us to specifically test for the dependence of linkage on sex. We detected several thousand liver gene expression quantitative trait loci, a significant proportion of which are sex-biased. We used these analyses to dissect the genetics of gonadal fat mass, a complex trait with sex-specific regulation. We present evidence for a remarkably high degree of sex-dependence on both the cis and trans regulation of gene expression. We demonstrate how these analyses can be applied to the study of the genetics underlying gonadal fat mass, a complex trait showing significantly female-biased heritability. These data have implications on the potential effects of sex on the genetic regulation of other complex traits.

Integrating genetic and network analysis to characterize genes related to mouse weight.

Systems biology approaches that are based on the genetics of gene expression have been fruitful in identifying genetic regulatory loci related to complex traits. We use microarray and genetic marker data from an F2 mouse intercross to examine the large-scale organization of the gene co-expression network in liver, and annotate several gene modules in terms of 22 physiological traits. We identify chromosomal loci (referred to as module quantitative trait loci, mQTL) that perturb the modules and describe a novel approach that integrates network properties with genetic marker information to model gene/trait relationships. Specifically, using the mQTL and the intramodular connectivity of a body weight-related module, we describe which factors determine the relationship between gene expression profiles and weight. Our approach results in the identification of genetic targets that influence gene modules (pathways) that are related to the clinical phenotypes of interest.

Mapping, genetic isolation, and characterization of genetic loci that determine resistance to atherosclerosis in C3H mice.

OBJECTIVE: C3H/HeJ (C3H) mice are extremely resistant to atherosclerosis. To identify the genetic factors involved in lesion initiation, we studied a cross between C3H and the susceptible strain C57BL/6J (B6) on a hyperlipidemic (apolipoprotein E-null) background. METHODS AND RESULTS: Whereas a previous cross in mice fed a Western diet for 16 weeks revealed a very complex inheritance pattern with many significant lesion QTLs, the present cross, on a chow diet, revealed a single major locus on chromosome 9 (lod=5.0, Ath29*), and a suggestive locus on chromosome 4 (lod=2.6, Ath8). QTLs for plasma HDL, total cholesterol, and triglyceride levels were found on chromosome 1 over the ApoA2 gene. Neither of the lesion QTLs were associated with differences in plasma lipid levels or other systemic risk factors, consistent with the concept that genetic factors affecting cellular functions of the vessel wall are important determinants of atherosclerosis susceptibility. We generated a congenic strain for Ath29 and confirmed its contribution to lesion development. Toll-like receptor 4 (Tlr4), the lipopolysaccharide (LPS) receptor, is located in the Ath8 region and is known to be defective in C3H/HeJ mice. We constructed a congenic strain carrying a normal Tlr4 gene on the C3H Apoe-null background and found that the defective Tlr4 does not contribute significantly to lesion resistance during early lesion development. CONCLUSIONS: We identified one major QTL on chromosome 9, Ath29, for early lesion development in the BXH ApoE(-/-) cross fed on a chow diet and confirmed its contribution in congenic mice. We have also determined that Tlr4 on the C3H ApoE(-/-) background does not contribute to early lesion development. *Ath29 is referred to as Ath22 in Su et al 2006.

A system for sharing routine surgical pathology specimens across institutions: the Shared Pathology Informatics Network.

This report presents an overview for pathologists of the development and potential applications of a novel Web enabled system allowing indexing and retrieval of pathology specimens across multiple institutions. The system was developed through the National Cancer Institute's Shared Pathology Informatics Network program with the goal of creating a prototype system to find existing pathology specimens derived from routine surgical and autopsy procedures ("paraffin blocks") that may be relevant to cancer research. To reach this goal, a number of challenges needed to be met. A central aspect was the development of an informatics system that supported Web-based searching while retaining local control of data. Additional aspects included the development of an eXtensible Markup Language schema, representation of tissue specimen annotation, methods for deidentifying pathology reports, tools for autocoding critical data from these reports using the Unified Medical Language System, and hierarchies of confidentiality and consent that met or exceeded federal requirements. The prototype system supported Web-based querying of millions of pathology reports from 6 participating institutions across the country in a matter of seconds to minutes and the ability of bona fide researchers to identify and potentially to request specific paraffin blocks from the participating institutions. With the addition of associated clinical and outcome information, this system could vastly expand the pool of annotated tissues available for cancer research as well as other diseases.

Sex differences and hormonal effects on gut microbiota composition in mice.

We previously reported quantitation of gut microbiota in a panel of 89 different inbred strains of mice, and we now examine the question of sex differences in microbiota composition. When the total population of 689 mice was examined together, several taxa exhibited significant differences in abundance between sexes but a larger number of differences were observed at the single strain level, suggesting that sex differences can be obscured by host genetics and environmental factors. We also examined a subset of mice on chow and high fat diets and observed sex-by-diet interactions. We further investigated the sex differences using gonadectomized and hormone treated mice from 3 different inbred strains. Principal coordinate analysis with unweighted UniFrac distances revealed very clear effects of gonadectomy and hormone replacement on microbiota composition in all 3 strains. Moreover, bile acid analyses showed gender-specific differences as well as effects of gonodectomy, providing one possible mechanism mediating sex differences in microbiota composition.