Variation in histone configurations correlates with gene expression across nine inbred strains of mice.

The diversity outbred (DO) mice and their inbred founders are widely used models of human disease. However, although the genetic diversity of these mice has been well documented, their epigenetic diversity has not. Epigenetic modifications, such as histone modifications and DNA methylation, are important regulators of gene expression, and as such are a critical mechanistic link between genotype and phenotype. Therefore, creating a map of epigenetic modifications in the DO mice and their founders is an important step toward understanding mechanisms of gene regulation and the link to disease in this widely used resource. To this end, we performed a strain survey of epigenetic modifications in hepatocytes of the DO founders. We surveyed four histone modifications (H3K4me1, H3K4me3, H3K27me3, and H3K27ac), and DNA methylation. We used ChromHMM to identify 14 chromatin states, each of which represented a distinct combination of the four histone modifications. We found that the epigenetic landscape was highly variable across the DO founders and was associated with variation in gene expression across strains. We found that epigenetic state imputed into a population of DO mice recapitulated the association with gene expression seen in the founders suggesting that both histone modifications and DNA methylation are highly heritable mechanisms of gene expression regulation. We illustrate how DO gene expression can be aligned with inbred epigenetic states to identify putative cis-regulatory regions. Finally, we provide a data resource that documents strain-specific variation in chromatin state and DNA methylation in hepatocytes across nine widely used strains of laboratory mice

Modeling islet enhancers using deep learning identifies candidate causal variants at loci associated with T2D and glycemic traits.

Genetic association studies have identified hundreds of independent signals associated with type 2 diabetes (T2D) and related traits. Despite these successes, the identification of specific causal variants underlying a genetic association signal remains challenging. In this study, we describe a deep learning (DL) method to analyze the impact of sequence variants on enhancers. Focusing on pancreatic islets, a T2D relevant tissue, we show that our model learns islet-specific transcription factor (TF) regulatory patterns and can be used to prioritize candidate causal variants. At 101 genetic signals associated with T2D and related glycemic traits where multiple variants occur in linkage disequilibrium, our method nominates a single causal variant for each association signal, including three variants previously shown to alter reporter activity in islet-relevant cell types. For another signal associated with blood glucose levels, we biochemically test all candidate causal variants from statistical fine-mapping using a pancreatic islet beta cell line and show biochemical evidence of allelic effects on TF binding for the model-prioritized variant. To aid in future research, we publicly distribute our model and islet enhancer perturbation scores across ~67 million genetic variants. We anticipate that DL methods like the one presented in this study will enhance the prioritization of candidate causal variants for functional studies

RCAN1 knockout and overexpression recapitulate an ensemble of rest-activity and circadian disruptions characteristic of Down syndrome, Alzheimer's disease, and normative aging

Regulator of calcineurin 1 (RCAN1) is overexpressed in Down syndrome (DS), but RCAN1 levels are also increased in Alzheimer&rsquo;s disease (AD) and normal aging. AD is highly comorbid among individuals with DS and is characterized in part by progressive neurodegeneration that resembles accelerated aging. Importantly, abnormal RCAN1 levels have been demonstrated to promote memory deficits and pathophysiology that appear symptomatic of DS, AD, and aging. Anomalous diurnal rest-activity patterns and circadian rhythm disruptions are also common in DS, AD, and aging and have been implicated in facilitating age-related cognitive decline and AD progression. However, no prior studies have assessed whether RCAN1 dysregulation may also promote the age-associated alteration of rest-activity profiles and circadian rhythms, which could in turn contribute to neurodegeneration in DS, AD, and aging. &nbsp;</p

CYP2A6 metabolism in the development of smoking behaviors in young adults

Cytochrome P450 2A6 (CYP2A6) encodes the enzyme responsible for the majority of nicotine metabolism. Previous studies support that slow metabolizers smoke fewer cigarettes once nicotine dependent but provide conflicting results on the role of CYP2A6 in the development of dependence. By focusing on the critical period of young adulthood, this study examines the relationship of CYP2A6 variation and smoking milestones. A total of 1209 European American young adults enrolled in the Collaborative Study on the Genetics of Alcoholism were genotyped for CYP2A6 variants to calculate a previously well-validated metric that estimates nicotine metabolism. This metric was not associated with the transition from never smoking to smoking initiation nor with the transition from initiation to daily smoking (P > 0.4). But among young adults who had become daily smokers (n = 506), decreased metabolism was associated with increased risk of nicotine dependence (P = 0.03) (defined as Fagerström Test for Nicotine Dependence score ≥4). This finding was replicated in the Collaborative Genetic Study of Nicotine Dependence with 335 young adult daily smokers (P = 0.02). Secondary meta-analysis indicated that slow metabolizers had a 53 percent increased odds (OR = 1.53, 95 percent CI 1.11-2.11, P = 0.009) of developing nicotine dependence compared with normal metabolizers. Furthermore, secondary analyses examining four-level response of time to first cigarette after waking (>60, 31-60, 6-30, ≤5 minutes) demonstrated a robust effect of the metabolism metric in Collaborative Study on the Genetics of Alcoholism (P = 0.03) and Collaborative Genetic Study of Nicotine Dependence (P = 0.004), illustrating the important role of this measure of dependence. These findings highlight the complex role of CYP2A6 variation across different developmental stages of smoking behaviors

Erratum: Sequence data and association statistics from 12,940 type 2 diabetes cases and controls.

This corrects the article DOI: 10.1038/sdata.2017.179

Essential Role for miR-196a in Brown Adipogenesis of White Fat Progenitor Cells

Brown adipocytes can differentiate from white fat progenitor cells in mice exposed to cold or β3-adrenergic stimulation, and this process is regulated by a microRNA that regulates the expression of Hoxc8, a master regulator of brown adipogenesis

An in vivo cis-Regulatory Screen at the Type 2 Diabetes Associated TCF7L2 Locus Identifies Multiple Tissue-Specific Enhancers

Genome-wide association studies (GWAS) have repeatedly shown an association between non-coding variants in the TCF7L2 locus and risk for type 2 diabetes (T2D), implicating a role for cis-regulatory variation within this locus in disease etiology. Supporting this hypothesis, we previously localized complex regulatory activity to the TCF7L2 T2D-associated interval using an in vivo bacterial artificial chromosome (BAC) enhancer-trapping reporter strategy. To follow-up on this broad initial survey of the TCF7L2 regulatory landscape, we performed a fine-mapping enhancer scan using in vivo mouse transgenic reporter assays. We functionally interrogated approximately 50% of the sequences within the T2D-associated interval, utilizing sequence conservation within this 92-kb interval to determine the regulatory potential of all evolutionary conserved sequences that exhibited conservation to the non-eutherian mammal opossum. Included in this study was a detailed functional interrogation of sequences spanning both protective and risk alleles of single nucleotide polymorphism (SNP) rs7903146, which has exhibited allele-specific enhancer function in pancreatic beta cells. Using these assays, we identified nine segments regulating various aspects of the TCF7L2 expression profile and that constitute nearly 70% of the sequences tested. These results highlight the regulatory complexity of this interval and support the notion that a TCF7L2 cis-regulatory disruption leads to T2D predisposition