Identification of the Bile Acid Transporter Slco1a6 as a Candidate Gene That Broadly Affects Gene Expression in Mouse Pancreatic Islets

Genetic Analysis of Obesity-Induced Diabetic Nephropathy in BTBR Mice

Diabetic nephropathy (DN) is the leading cause of end-stage renal disease in the U.S. and has a significant impact on human suffering. Leptin-deficient BTBR (BTBRob/ob) mice develop hallmark features of obesity-induced DN, whereas leptin-deficient C57BL/6J (B6ob/ob) mice do not. To identify genetic loci that underlie this strain difference, we constructed an F2 intercross between BTBRob/ob and B6ob/ob mice. We isolated kidneys from 460 F2 mice and histologically scored them for percent mesangial matrix and glomerular volume (∼50 glomeruli per mouse), yielding ∼45,000 distinct measures in total. The same histological measurements were made in kidneys from B6 and BTBR mice, either lean or obese (Lepob/ob), at 4 and 10 weeks of age, allowing us to assess the contribution of strain, age, and obesity to glomerular pathology. All F2 mice were genotyped for ∼5,000 single nucleotide polymorphisms (SNPs), ∼2,000 of which were polymorphic between B6 and BTBR, enabling us to identify a quantitative trait locus (QTL) on chromosome 7, with a peak at ∼30 Mbp, for percent mesangial matrix, glomerular volume, and mesangial volume. The podocyte-specific gene nephrin (Nphs1) is physically located at the QTL and contains high-impact SNPs in BTBR, including several missense variants within the extracellular immunoglobulin-like domains.

ARTICLE HIGHLIGHTS

What the BTBR/J mouse has taught us about diabetes and diabetic complications

Human and mouse genetics have delivered numerous diabetogenic loci, but it is mainly through the use of animal models that the pathophysiological basis for their contribution to diabetes has been investigated. More than 20 years ago, we serendipidously identified a mouse strain that could serve as a model of obesity-prone type 2 diabetes, the BTBR (Black and Tan Brachyury) mouse (BTBR T+ Itpr3tf/J, 2018) carrying the Lepob mutation. We went on to discover that the BTBR-Lepob mouse is an excellent model of diabetic nephropathy and is now widely used by nephrologists in academia and the pharmaceutical industry. In this review, we describe the motivation for developing this animal model, the many genes identified and the insights about diabetes and diabetes complications derived from >100 studies conducted in this remarkable animal model.

Analysis of a genetic region affecting mouse body weight

Genetic factors affect an individual's risk of developing obesity, but in most cases each genetic variant has a small effect. Discovery of genes that regulate obesity may provide clues about its underlying biological processes and point to new ways the disease can be treated. Preclinical animal models facilitate genetic discovery in obesity because environmental factors can be better controlled compared with the human population. We studied inbred mouse strains to identify novel genes affecting obesity and glucose metabolism. BTBR T+ Itpr3^tf/J (BTBR) mice are fatter and more glucose intolerant than C57BL/6J (B6) mice. Prior genetic studies of these strains identified an obesity locus on chromosome 2. Using congenic mice, we found that obesity was affected by a ∼316 kb region, with only two known genes, pyruvate dehydrogenase kinase 1 (Pdk1) and integrin α 6 (Itga6). Both genes had mutations affecting their amino acid sequence and reducing mRNA levels. Both genes have known functions that could modulate obesity, lipid metabolism, insulin secretion, and/or glucose homeostasis. We hypothesized that genetic variation in or near Pdk1 or Itga6 causing reduced Pdk1 and Itga6 expression would promote obesity and impaired glucose tolerance. We used knockout mice lacking Pdk1 or Itga6 fed an obesigenic diet to test this hypothesis. Under the conditions we studied, we were unable to detect an individual contribution of either Pdk1 or Itga6 to body weight. During our studies, with conditions outside our control, we were unable to reproduce some of our previous body weight data. However, we identified a previously unknown role for Pdk1 in cardiac cholesterol metabolism providing the basis for future investigations. The studies described in this paper highlight the importance and the challenge using physiological outcomes to study obesity genes in mice.

Genetic mapping of microbial and host traits reveals production of immunomodulatory lipids by Akkermansia muciniphila in the murine gut

The molecular bases of how host genetic variation impacts the gut microbiome remain largely unknown. Here we used a genetically diverse mouse population and applied systems genetics strategies to identify interactions between host and microbe phenotypes including microbial functions, using faecal metagenomics, small intestinal transcripts and caecal lipids that influence microbe-host dynamics. Quantitative trait locus (QTL) mapping identified murine genomic regions associated with variations in bacterial taxa; bacterial functions including motility, sporulation and lipopolysaccharide production and levels of bacterial- and host-derived lipids. We found overlapping QTL for the abundance of Akkermansia muciniphila and caecal levels of ornithine lipids. Follow-up in vitro and in vivo studies revealed that A. muciniphila is a major source of these lipids in the gut, provided evidence that ornithine lipids have immunomodulatory effects and identified intestinal transcripts co-regulated with these traits including Atf3, which encodes for a transcription factor that plays vital roles in modulating metabolism and immunity. Collectively, these results suggest that ornithine lipids are potentially important for A. muciniphila-host interactions and support the role of host genetics as a determinant of responses to gut microbes.

Tissue context determines the penetrance of regulatory DNA variation

Functional assessment of disease-associated sequence variation at non-coding regulatory elements is complicated by their high degree of context sensitivity to both the local chromatin and nuclear environments. Allelic profiling of DNA accessibility across individuals has shown that only a select minority of sequence variation affects transcription factor (TF) occupancy, yet low sequence diversity in human populations means that no experimental assessment is available for the majority of disease-associated variants. Here we describe high-resolution in vivo maps of allelic DNA accessibility in liver, kidney, lung and B cells from 5 increasingly diverged strains of F1 hybrid mice. The high density of heterozygous sites in these hybrids enables precise quantification of effect size and cell-type specificity for hundreds of thousands of variants throughout the mouse genome. We show that chromatin-altering variants delineate characteristic sensitivity profiles for hundreds of TF motifs. We develop a compendium of TF-specific sensitivity profiles accounting for genomic context effects. Finally, we link maps of allelic accessibility to allelic transcript levels in the same samples. This work provides a foundation for quantitative prediction of cell-type specific effects of non-coding variation on TF activity, which will facilitate both fine-mapping and systems-level analyses of common disease-associated variation in human genomes.

Molecular and evolutionary processes generating variation in gene expression

Heritable variation in gene expression is common within and between species. This variation arises from mutations that alter the form or function of molecular gene regulatory networks that are then filtered by natural selection. High-throughput methods for introducing mutations and characterizing their cis- and trans-regulatory effects on gene expression (particularly, transcription) are revealing how different molecular mechanisms generate regulatory variation, and studies comparing these mutational effects with variation seen in the wild are teasing apart the role of neutral and non-neutral evolutionary processes. This integration of molecular and evolutionary biology allows us to understand how the variation in gene expression we see today came to be and to predict how it is most likely to evolve in the future.

Identification of putative regulatory regions and transcription factors associated with intramuscular fat content traits

Background

Integration of high throughput DNA genotyping and RNA-sequencing data allows for the identification of genomic regions that control gene expression, known as expression quantitative trait loci (eQTL), on a whole genome scale. Intramuscular fat (IMF) content and carcass composition play important roles in metabolic and physiological processes in mammals because they influence insulin sensitivity and consequently prevalence of metabolic diseases such as obesity and type 2 diabetes. However, limited information is available on the genetic variants and mechanisms associated with IMF deposition in mammals. Thus, our hypothesis was that eQTL analyses could identify putative regulatory regions and transcription factors (TFs) associated with intramuscular fat (IMF) content traits.

Results

We performed an integrative eQTL study in skeletal muscle to identify putative regulatory regions and factors associated with intramuscular fat content traits. Data obtained from skeletal muscle samples of 192 animals was used for association analysis between 461,466 SNPs and the transcription level of 11,808 genes. This yielded 1268 cis- and 10,334 trans-eQTLs, among which we identified nine hotspot regions that each affected the expression of > 119 genes. These putative regulatory regions overlapped with previously identified QTLs for IMF content. Three of the hotspots respectively harbored the transcription factors USF1, EGR4 and RUNX1T1, which are known to play important roles in lipid metabolism. From co-expression network analysis, we further identified modules significantly correlated with IMF content and associated with relevant processes such as fatty acid metabolism, carbohydrate metabolism and lipid metabolism.

Conclusion

This study provides novel insights into the link between genotype and IMF content as evident from the expression level. It thereby identifies genomic regions of particular importance and associated regulatory factors. These new findings provide new knowledge about the biological processes associated with genetic variants and mechanisms associated with IMF deposition in mammals.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-4871-y) contains supplementary material, which is available to authorized users.

Genetic Drivers of Pancreatic Islet Function

The majority of gene loci that have been associated with type 2 diabetes play a role in pancreatic islet function. To evaluate the role of islet gene expression in the etiology of diabetes, we sensitized a genetically diverse mouse population with a Western diet high in fat (45% kcal) and sucrose (34%) and carried out genome-wide association mapping of diabetes-related phenotypes. We quantified mRNA abundance in the islets and identified 18,820 expression QTL. We applied mediation analysis to identify candidate causal driver genes at loci that affect the abundance of numerous transcripts. These include two genes previously associated with monogenic diabetes (PDX1 and HNF4A), as well as three genes with nominal association with diabetes-related traits in humans (FAM83E, IL6ST, and SAT2). We grouped transcripts into gene modules and mapped regulatory loci for modules enriched with transcripts specific for α-cells, and another specific for δ-cells. However, no single module enriched for β-cell-specific transcripts, suggesting heterogeneity of gene expression patterns within the β-cell population. A module enriched in transcripts associated with branched-chain amino acid metabolism was the most strongly correlated with physiological traits that reflect insulin resistance. Although the mice in this study were not overtly diabetic, the analysis of pancreatic islet gene expression under dietary-induced stress enabled us to identify correlated variation in groups of genes that are functionally linked to diabetes-associated physiological traits. Our analysis suggests an expected degree of concordance between diabetes-associated loci in the mouse and those found in human populations, and demonstrates how the mouse can provide evidence to support nominal associations found in human genome-wide association mapping.

Genetics of metabolic syndrome: potential clues from wild-derived inbred mouse strains

The metabolic syndrome (MetS) is a complex constellation of metabolic abnormalities including obesity, abnormal glucose metabolism, dyslipidemia, and elevated blood pressure that together substantially increase risk for cardiovascular disease and Type 2 diabetes. Both genetic and environmental factors contribute to the development of MetS, but this process is still far from understood. Human studies have revealed only part of the underlying basis. Studies in mice offer many strengths that can complement human studies to help elucidate the etiology and pathophysiology of MetS. Here we review the ways mice can contribute to MetS research. In particular, we focus on the information that can be obtained from studies of the inbred strains, with specific focus on the phenotypes of the wild-derived inbred strains. These are newly derived inbred strains that were created from wild-caught mice. They contain substantial genetic variation that is not present in the classical inbred strains, have phenotypes of relevance for MetS, and various mouse strain resources have been created to facilitate the mining of this new genetic variation. Thus studies using wild-derived inbred strains hold great promise for increasing our understanding of MetS.

Nat1 Deficiency Is Associated with Mitochondrial Dysfunction and Exercise Intolerance in Mice

We recently identified human N-acetyltransferase 2 (NAT2) as an insulin resistance (IR) gene. Here, we examine the cellular mechanism linking NAT2 to IR and find that Nat1 (mouse ortholog of NAT2) is co-regulated with key mitochondrial genes. RNAi-mediated silencing of Nat1 led to mitochondrial dysfunction characterized by increased intracellular reactive oxygen species and mitochondrial fragmentation as well as decreased mitochondrial membrane potential, biogenesis, mass, cellular respiration, and ATP generation. These effects were consistent in 3T3-L1 adipocytes, C2C12 myoblasts, and in tissues from Nat1-deficient mice, including white adipose tissue, heart, and skeletal muscle. Nat1-deficient mice had changes in plasma metabolites and lipids consistent with a decreased ability to utilize fats for energy and a decrease in basal metabolic rate and exercise capacity without altered thermogenesis. Collectively, our results suggest that Nat1 deficiency results in mitochondrial dysfunction, which may constitute a mechanistic link between this gene and IR.

The Transcription Factor Nfatc2 Regulates β-Cell Proliferation and Genes Associated with Type 2 Diabetes in Mouse and Human Islets

Human genome-wide association studies (GWAS) have shown that genetic variation at >130 gene loci is associated with type 2 diabetes (T2D). We asked if the expression of the candidate T2D-associated genes within these loci is regulated by a common locus in pancreatic islets. Using an obese F2 mouse intercross segregating for T2D, we show that the expression of ~40% of the T2D-associated genes is linked to a broad region on mouse chromosome (Chr) 2. As all but 9 of these genes are not physically located on Chr 2, linkage to Chr 2 suggests a genomic factor(s) located on Chr 2 regulates their expression in trans. The transcription factor Nfatc2 is physically located on Chr 2 and its expression demonstrates cis linkage; i.e., its expression maps to itself. When conditioned on the expression of Nfatc2, linkage for the T2D-associated genes was greatly diminished, supporting Nfatc2 as a driver of their expression. Plasma insulin also showed linkage to the same broad region on Chr 2. Overexpression of a constitutively active (ca) form of Nfatc2 induced β-cell proliferation in mouse and human islets, and transcriptionally regulated more than half of the T2D-associated genes. Overexpression of either ca-Nfatc2 or ca-Nfatc1 in mouse islets enhanced insulin secretion, whereas only ca-Nfatc2 was able to promote β-cell proliferation, suggesting distinct molecular pathways mediating insulin secretion vs. β-cell proliferation are regulated by NFAT. Our results suggest that many of the T2D-associated genes are downstream transcriptional targets of NFAT, and may act coordinately in a pathway through which NFAT regulates β-cell proliferation in both mouse and human islets.

Genome-wide association studies (GWAS) and linkage studies provide a powerful way to establish a causal connection between a gene locus and a physiological or pathophysiological phenotype. We wondered if candidate genes associated with type 2 diabetes in human populations, in addition to being causal for the disease, could also be intermediate traits in a pathway leading to disease. In addition, we wished to know if there were any regulatory loci that could coordinately drive the expression of these genes in pancreatic islets and thus complete a pathway; i.e. Driver → GWAS candidate expression → type 2 diabetes. Using data from a mouse intercross between a diabetes-susceptible and a diabetes-resistant mouse strain, we found that the expression of ~40% of >130 candidate GWAS genes genetically mapped to a hot spot on mouse chromosome 2. Using a variety of statistical methods, we identified the transcription factor Nfatc2 as the candidate driver. Follow-up experiments showed that overexpression of Nfatc2 does indeed affect the expression of the GWAS genes and regulates β-cell proliferation and insulin secretion. The work shows that in addition to being causal, GWAS candidate genes can be intermediate traits in a pathway leading to disease. Model organisms can be used to explore these novel causal pathways.

Deletion of histone deacetylase 3 in adult beta cells improves glucose tolerance via increased insulin secretion

Objective

Histone deacetylases are epigenetic regulators known to control gene transcription in various tissues. A member of this family, histone deacetylase 3 (HDAC3), has been shown to regulate metabolic genes. Cell culture studies with HDAC-specific inhibitors and siRNA suggest that HDAC3 plays a role in pancreatic β-cell function, but a recent genetic study in mice has been contradictory. Here we address the functional role of HDAC3 in β-cells of adult mice.

Methods

An HDAC3 β-cell specific knockout was generated in adult MIP-CreERT transgenic mice using the Cre-loxP system. Induction of HDAC3 deletion was initiated at 8 weeks of age with administration of tamoxifen in corn oil (2 mg/day for 5 days). Mice were assayed for glucose tolerance, glucose-stimulated insulin secretion, and islet function 2 weeks after induction of the knockout. Transcriptional functions of HDAC3 were assessed by ChIP-seq as well as RNA-seq comparing control and β-cell knockout islets.

Results

HDAC3 β-cell specific knockout (HDAC3βKO) did not increase total pancreatic insulin content or β-cell mass. However, HDAC3βKO mice demonstrated markedly improved glucose tolerance. This improved glucose metabolism coincided with increased basal and glucose-stimulated insulin secretion in vivo as well as in isolated islets. Cistromic and transcriptomic analyses of pancreatic islets revealed that HDAC3 regulates multiple genes that contribute to glucose-stimulated insulin secretion.

Conclusions

HDAC3 plays an important role in regulating insulin secretion in vivo, and therapeutic intervention may improve glucose homeostasis.

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HDAC3 ablation in adult mouse β-cells improves glucose tolerance.

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Improved glucose tolerance is due to increased insulin secretion.

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HDAC3 targets multiple genes involved in potentiating insulin secretion.

Hypothalamic transcriptomes of 99 mouse strains reveal trans eQTL hotspots, splicing QTLs and novel non-coding genes

Previous studies had shown that the integration of genome wide expression profiles, in metabolic tissues, with genetic and phenotypic variance, provided valuable insight into the underlying molecular mechanisms. We used RNA-Seq to characterize hypothalamic transcriptome in 99 inbred strains of mice from the Hybrid Mouse Diversity Panel (HMDP), a reference resource population for cardiovascular and metabolic traits. We report numerous novel transcripts supported by proteomic analyses, as well as novel non coding RNAs. High resolution genetic mapping of transcript levels in HMDP, reveals both local and trans expression Quantitative Trait Loci (eQTLs) demonstrating 2 trans eQTL 'hotspots' associated with expression of hundreds of genes. We also report thousands of alternative splicing events regulated by genetic variants. Finally, comparison with about 150 metabolic and cardiovascular traits revealed many highly significant associations. Our data provide a rich resource for understanding the many physiologic functions mediated by the hypothalamus and their genetic regulation.

DOI:http://dx.doi.org/10.7554/eLife.15614.001

Metabolism is a term that describes all the chemical reactions that are involved in keeping a living organism alive. Diseases related to metabolism – such as obesity, heart disease and diabetes – are a major health problem in the Western world. The causes of these diseases are complex and include both environmental factors, such as diet and exercise, and genetics. Indeed, many genetic variants that contribute to obesity have been uncovered in both humans and mice. However, it is only dimly understood how these genetic variants affect the underlying networks of interacting genes that cause metabolic disorders.

Measuring gene activity or expression, and tracing how genetic instructions are carried from DNA into RNA and proteins, can reliably identify groups of genes that correlate with metabolic traits in specific organs. This strategy was successfully used in previous studies to reveal new information about abnormalities linked to obesity in specific tissues such as the liver and fat tissues. It was also shown that this approach might suggest new molecules that could be targeted to treat metabolic disorders.

A brain region called the hypothalamus is key to the control of metabolism, including feeding behavior and obesity. Hasin-Brumshtein et al. set out to explore gene expression in the hypothalamus of 99 different strains of mice, in the hope that the data will help identify new connections between gene expression and metabolism.

This approach showed that thousands of new and known genes are expressed in the mouse hypothalamus, some of which coded for proteins, and some of which did not. Hasin-Brumshtein et al. uncovered two genetic variants that controlled the expression of hundreds of other genes. Further analysis then revealed thousands of genetic variants that regulated the expression of, and type of RNA (so-called "spliceforms") produced from neighboring genes. Also, the expression of many individual genes showed significant similarities with about 150 metabolic measurements that had been evaluated previously in the mice.

This new dataset is a unique resource that can be coupled with different approaches to test existing ideas and develop new ones about the role of particular genes or genetic mechanisms in obesity. Future studies will likely focus on new genes that show strong associations with attributes that are relevant to metabolic disorders, such as insulin levels, weight and fat mass.

DOI:http://dx.doi.org/10.7554/eLife.15614.002

The Hybrid Mouse Diversity Panel: a resource for systems genetics analyses of metabolic and cardiovascular traits

The Hybrid Mouse Diversity Panel (HMDP) is a collection of approximately 100 well-characterized inbred strains of mice that can be used to analyze the genetic and environmental factors underlying complex traits. While not nearly as powerful for mapping genetic loci contributing to the traits as human genome-wide association studies, it has some important advantages. First, environmental factors can be controlled. Second, relevant tissues are accessible for global molecular phenotyping. Finally, because inbred strains are renewable, results from separate studies can be integrated. Thus far, the HMDP has been studied for traits relevant to obesity, diabetes, atherosclerosis, osteoporosis, heart failure, immune regulation, fatty liver disease, and host-gut microbiota interactions. High-throughput technologies have been used to examine the genomes, epigenomes, transcriptomes, proteomes, metabolomes, and microbiomes of the mice under various environmental conditions. All of the published data are available and can be readily used to formulate hypotheses about genes, pathways and interactions.

High-resolution genetic localization of a modifying locus affecting disease severity in the juvenile cystic kidneys (jck) mouse model of polycystic kidney disease

We have previously demonstrated that a locus on proximal Chr 4 modifies disease severity in the juvenile cystic kidney (jck) mouse, a model of polycystic kidney disease (PKD) that carries a mutation of the Nek8 serine-threonine kinase. In this study, we used QTL analysis of independently constructed B6.D2 congenic lines to confirm this and showed that this locus has a highly significant effect. We constructed sub-congenic lines to more specifically localize the modifier and have determined it resides in a 3.2 Mb interval containing 28 genes. These include Invs and Anks6, which are both excellent candidates for the modifier as mutations in these genes result in PKD and both genes are known to genetically and physically interact with Nek8. However, examination of strain-specific DNA sequence and kidney expression did not reveal clear differences that might implicate either gene as a modifier of PKD severity. The fact that our high-resolution analysis did not yield an unambiguous result highlights the challenge of establishing the causality of strain-specific variants as genetic modifiers, and suggests that alternative strategies be considered.

The Dissection of Expression Quantitative Trait Locus Hotspots

Studies of the genetic loci that contribute to variation in gene expression frequently identify loci with broad effects on gene expression: expression quantitative trait locus hotspots. We describe a set of exploratory graphical methods as well as a formal likelihood-based test for assessing whether a given hotspot is due to one or multiple polymorphisms. We first look at the pattern of effects of the locus on the expression traits that map to the locus: the direction of the effects and the degree of dominance. A second technique is to focus on the individuals that exhibit no recombination event in the region, apply dimensionality reduction (e.g., with linear discriminant analysis), and compare the phenotype distribution in the nonrecombinant individuals to that in the recombinant individuals: if the recombinant individuals display a different expression pattern than the nonrecombinant individuals, this indicates the presence of multiple causal polymorphisms. In the formal likelihood-based test, we compare a two-locus model, with each expression trait affected by one or the other locus, to a single-locus model. We apply our methods to a large mouse intercross with gene expression microarray data on six tissues.