Harnessing natural variation to identify cis regulators of sex-biased gene expression in a multi-strain mouse liver model.

Sex differences in gene expression are widespread in the liver, where many autosomal factors act in tandem with growth hormone signaling to regulate individual variability of sex differences in liver metabolism and disease. Here, we compare hepatic transcriptomic and epigenetic profiles of mouse strains C57BL/6J and CAST/EiJ, representing two subspecies separated by 0.5-1 million years of evolution, to elucidate the actions of genetic factors regulating liver sex differences. We identify 144 protein coding genes and 78 lncRNAs showing strain-conserved sex bias; many have gene ontologies relevant to liver function, are more highly liver-specific and show greater sex bias, and are more proximally regulated than genes whose sex bias is strain-dependent. The strain-conserved genes include key growth hormone-dependent transcriptional regulators of liver sex bias; however, three other transcription factors, Trim24, Tox, and Zfp809, lose their sex-biased expression in CAST/EiJ mouse liver. To elucidate the observed strain specificities in expression, we characterized the strain-dependence of sex-biased chromatin opening and enhancer marks at cis regulatory elements (CREs) within expression quantitative trait loci (eQTL) regulating liver sex-biased genes. Strikingly, 208 of 286 eQTLs with strain-specific, sex-differential effects on expression were associated with a complete gain, loss, or reversal of the sex differences in expression between strains. Moreover, 166 of the 286 eQTLs were linked to the strain-dependent gain or loss of localized sex-biased CREs. Remarkably, a subset of these CREs apparently lacked strain-specific genetic variants yet showed coordinated, strain-dependent sex-biased epigenetic regulation. Thus, we directly link hundreds of strain-specific genetic variants to the high variability in CRE activity and expression of sex-biased genes and uncover underlying genetically-determined epigenetic states controlling liver sex bias in genetically diverse mouse populations.

Genetic factors contributing to extensive variability of sex-specific hepatic gene expression in Diversity Outbred mice.

Sex-specific transcription characterizes hundreds of genes in mouse liver, many implicated in sex-differential drug and lipid metabolism and disease susceptibility. While the regulation of liver sex differences by growth hormone-activated STAT5 is well established, little is known about autosomal genetic factors regulating the sex-specific liver transcriptome. Here we show, using genotyping and expression data from a large population of Diversity Outbred mice, that genetic factors work in tandem with growth hormone to control the individual variability of hundreds of sex-biased genes, including many long non-coding RNA genes. Significant associations between single nucleotide polymorphisms and sex-specific gene expression were identified as expression quantitative trait loci (eQTLs), many of which showed strong sex-dependent associations. Remarkably, autosomal genetic modifiers of sex-specific genes were found to account for more than 200 instances of gain or loss of sex-specificity across eight Diversity Outbred mouse founder strains. Sex-biased STAT5 binding sites and open chromatin regions with strain-specific variants were significantly enriched at eQTL regions regulating correspondingly sex-specific genes, supporting the proposed functional regulatory nature of the eQTL regions identified. Binding of the male-biased, growth hormone-regulated repressor BCL6 was most highly enriched at trans-eQTL regions controlling female-specific genes. Co-regulated gene clusters defined by overlapping eQTLs included sets of highly correlated genes from different chromosomes, further supporting trans-eQTL action. These findings elucidate how an unexpectedly large number of autosomal factors work in tandem with growth hormone signaling pathways to regulate the individual variability associated with sex differences in liver metabolism and disease.

Long non-coding RNA Gm15441 attenuates hepatic inflammasome activation in response to PPARA agonism and fasting.

Exploring the molecular mechanisms that prevent inflammation during caloric restriction may yield promising therapeutic targets. During fasting, activation of the nuclear receptor peroxisome proliferator-activated receptor α (PPARα) promotes the utilization of lipids as an energy source. Herein, we show that ligand activation of PPARα directly upregulates the long non-coding RNA gene Gm15441 through PPARα binding sites within its promoter. Gm15441 expression suppresses its antisense transcript, encoding thioredoxin interacting protein (TXNIP). This, in turn, decreases TXNIP-stimulated NLR family pyrin domain containing 3 (NLRP3) inflammasome activation, caspase-1 (CASP1) cleavage, and proinflammatory interleukin 1ß (IL1B) maturation. Gm15441-null mice were developed and shown to be more susceptible to NLRP3 inflammasome activation and to exhibit elevated CASP1 and IL1B cleavage in response to PPARα agonism and fasting. These findings provide evidence for a mechanism by which PPARα attenuates hepatic inflammasome activation in response to metabolic stress through induction of lncRNA Gm15441.

Sex-Biased lncRNAs Inversely Correlate With Sex-Opposite Gene Coexpression Networks in Diversity Outbred Mouse Liver.

Sex differences in liver gene expression are determined by pituitary growth hormone secretion patterns, which regulate sex-dependent liver transcription factors and establish sex-specific chromatin states. Hypophysectomy (hypox) identifies two major classes of liver sex-biased genes, defined by their sex-dependent positive or negative responses to pituitary hormone ablation. However, the mechanisms that underlie each hypox-response class are unknown. We sought to discover candidate, regulatory, long noncoding RNAs (lncRNAs) controlling responsiveness to hypox. We characterized gene structures and expression patterns for 15,558 mouse liver-expressed lncRNAs, including many sex-specific lncRNAs regulated during postnatal development or subject to circadian regulation. Using the high natural allelic variance of Diversity Outbred (DO) mice, we discovered tightly coexpressed clusters of sex-specific protein-coding genes (gene modules) in male and female DO liver. Remarkably, many gene modules were strongly enriched for sex-specific genes within a single hypox-response class, indicating that the genetic heterogeneity of DO mice encompasses responsiveness to hypox. Moreover, several distant gene modules were enriched for gene subsets of the same hypox-response class, highlighting the complex regulation of hypox-responsiveness. Finally, we identified eight sex-specific lncRNAs with strong negative regulatory potential, as indicated by their strong negative correlation of expression across DO mouse livers with that of protein-coding gene modules enriched for genes of the opposite sex bias and inverse hypox-response class. These findings reveal an important role for genetic factors in regulating responsiveness to hypox, and present testable hypotheses for the roles of sex-biased liver lncRNAs in controlling the sex-bias of liver gene expression.

Sex-Differential Responses of Tumor Promotion-Associated Genes and Dysregulation of Novel Long Noncoding RNAs in Constitutive Androstane Receptor-Activated Mouse Liver.

Xenobiotic agonists of constitutive androstane receptor (CAR) induce many hepatic drug metabolizing enzymes, but following prolonged exposure, promote hepatocellular carcinoma, most notably in male mouse liver. Here, we used nuclear RNA-seq to characterize global changes in the mouse liver transcriptome following exposure to the CAR-specific agonist ligand 1,4-bis-[2-(3,5-dichloropyridyloxy)]benzene (TCPOBOP), including changes in novel long noncoding RNAs that may contribute to xenobiotic-induced pathophysiology. Protein-coding genes dysregulated by 3 h TCPOBOP exposure were strongly enriched in KEGG pathways of xenobiotic and drug metabolism, with stronger and more extensive gene responses observed in female than male liver. After 27 h TCPOBOP exposure, the number of responsive genes increased >8-fold in males, where the top enriched pathways and their upstream regulators expanded to include factors implicated in cell cycle dysregulation and hepatocellular carcinoma progression (cyclin-D1, oncogenes E2f, Yap, Rb, Myc, and proto-oncogenes ß-catenin, FoxM1, FoxO1, all predicted to be activated by TCPOBOP in male but not female liver; and tumor suppressors p21 and p53, both predicted to be inhibited). Upstream regulators uniquely associated with 3 h TCPOBOP-exposed females include TNF/NFkB pathway members, which negatively regulate CAR-dependent proliferative responses and may contribute to the relative resistance of female liver to TCPOBOP-induced tumor promotion. These responses may be modified by the many long noncoding liver RNAs we show are dysregulated by TCPOBOP or pregnane-X-receptor agonist exposure, including lncRNAs proximal to CAR target genes Cyp2b10, Por, and Alas1. These data provide a comprehensive view of the CAR-regulated transcriptome and give insight into the mechanism of sex-biased susceptibility to CAR-dependent mouse liver tumorigenesis.

Hepatic Long Intergenic Noncoding RNAs: High Promoter Conservation and Dynamic, Sex-Dependent Transcriptional Regulation by Growth Hormone.

Long intergenic noncoding RNAs (lincRNAs) are increasingly recognized as key chromatin regulators, yet few studies have characterized lincRNAs in a single tissue under diverse conditions. Here, we analyzed 45 mouse liver RNA sequencing (RNA-Seq) data sets collected under diverse conditions to systematically characterize 4,961 liver lincRNAs, 59% of them novel, with regard to gene structures, species conservation, chromatin accessibility, transcription factor binding, and epigenetic states. To investigate the potential for functionality, we focused on the responses of the liver lincRNAs to growth hormone stimulation, which imparts clinically relevant sex differences to hepatic metabolism and liver disease susceptibility. Sex-biased expression characterized 247 liver lincRNAs, with many being nuclear RNA enriched and regulated by growth hormone. The sex-biased lincRNA genes are enriched for nearby and correspondingly sex-biased accessible chromatin regions, as well as sex-biased binding sites for growth hormone-regulated transcriptional activators (STAT5, hepatocyte nuclear factor 6 [HNF6], FOXA1, and FOXA2) and transcriptional repressors (CUX2 and BCL6). Repression of female-specific lincRNAs in male liver, but not that of male-specific lincRNAs in female liver, was associated with enrichment of H3K27me3-associated inactive states and poised (bivalent) enhancer states. Strikingly, we found that liver-specific lincRNA gene promoters are more highly species conserved and have a significantly higher frequency of proximal binding by liver transcription factors than liver-specific protein-coding gene promoters. Orthologs for many liver lincRNAs were identified in one or more supraprimates, including two rat lincRNAs showing the same growth hormone-regulated, sex-biased expression as their mouse counterparts. This integrative analysis of liver lincRNA chromatin states, transcription factor occupancy, and growth hormone regulation provides novel insights into the expression of sex-specific lincRNAs and their potential for regulation of sex differences in liver physiology and disease.

Genomic models of short-term exposure accurately predict long-term chemical carcinogenicity and identify putative mechanisms of action.

BACKGROUND: Despite an overall decrease in incidence of and mortality from cancer, about 40% of Americans will be diagnosed with the disease in their lifetime, and around 20% will die of it. Current approaches to test carcinogenic chemicals adopt the 2-year rodent bioassay, which is costly and time-consuming. As a result, fewer than 2% of the chemicals on the market have actually been tested. However, evidence accumulated to date suggests that gene expression profiles from model organisms exposed to chemical compounds reflect underlying mechanisms of action, and that these toxicogenomic models could be used in the prediction of chemical carcinogenicity. RESULTS: In this study, we used a rat-based microarray dataset from the NTP DrugMatrix Database to test the ability of toxicogenomics to model carcinogenicity. We analyzed 1,221 gene-expression profiles obtained from rats treated with 127 well-characterized compounds, including genotoxic and non-genotoxic carcinogens. We built a classifier that predicts a chemical's carcinogenic potential with an AUC of 0.78, and validated it on an independent dataset from the Japanese Toxicogenomics Project consisting of 2,065 profiles from 72 compounds. Finally, we identified differentially expressed genes associated with chemical carcinogenesis, and developed novel data-driven approaches for the molecular characterization of the response to chemical stressors. CONCLUSION: Here, we validate a toxicogenomic approach to predict carcinogenicity and provide strong evidence that, with a larger set of compounds, we should be able to improve the sensitivity and specificity of the predictions. We found that the prediction of carcinogenicity is tissue-dependent and that the results also confirm and expand upon previous studies implicating DNA damage, the peroxisome proliferator-activated receptor, the aryl hydrocarbon receptor, and regenerative pathology in the response to carcinogen exposure.

Robust consensus clustering for identification of expressed genes linked to malignancy of human colorectal carcinoma.

Previous studies have been conducted in gene expression profiling to identify groups of genes that characterize the colorectal carcinoma disease. Despite the success of previous attempts to identify groups of genes in the progression of the colorectal carcinoma disease, their methods either require subjective interpretation of the number of clusters, or lack stability during different runs of the algorithms. All of which limits the usefulness of these methods. In this study, we propose an enhanced algorithm that provides stability and robustness in identifying differentially expressed genes in an expression profile analysis. Our proposed algorithm uses multiple clustering algorithms under the consensus clustering framework. The results of the experiment show that the robustness of our method provides a consistent structure of clusters, similar to the structure found in the previous study. Furthermore, our algorithm outperforms any single clustering algorithms in terms of the cluster quality score.