BoostMe accurately predicts DNA methylation values in whole-genome bisulfite sequencing of multiple human tissues

Abstract Background Bisulfite sequencing is widely employed to study the role of DNA methylation in disease; however, the data suffer from biases due to coverage depth variability. Imputation of methylation values at low-coverage sites may mitigate these biases while also identifying important genomic features associated with predictive power. Results Here we describe BoostMe, a method for imputing low-quality DNA methylation estimates within whole-genome bisulfite sequencing (WGBS) data. BoostMe uses a gradient boosting algorithm, XGBoost, and leverages information from multiple samples for prediction. We find that BoostMe outperforms existing algorithms in speed and accuracy when applied to WGBS of human tissues. Furthermore, we show that imputation improves concordance between WGBS and the MethylationEPIC array at low WGBS depth, suggesting improved WGBS accuracy after imputation. Conclusions Our findings support the use of BoostMe as a preprocessing step for WGBS analysis.https://deepblue.lib.umich.edu/bitstream/2027.42/143848/1/12864_2018_Article_4766.pd

Genetic Architecture of Skewed X Inactivation in the Laboratory Mouse

X chromosome inactivation (XCI) is the mammalian mechanism of dosage compensation that balances X-linked gene expression between the sexes. Early during female development, each cell of the embryo proper independently inactivates one of its two parental X-chromosomes. In mice, the choice of which X chromosome is inactivated is affected by the genotype of a cis-acting locus, the X-chromosome controlling element (Xce). Xce has been localized to a 1.9 Mb interval within the X-inactivation center (Xic), yet its molecular identity and mechanism of action remain unknown. We combined genotype and sequence data for mouse stocks with detailed phenotyping of ten inbred strains and with the development of a statistical model that incorporates phenotyping data from multiple sources to disentangle sources of XCI phenotypic variance in natural female populations on X inactivation. We have reduced the Xce candidate 10-fold to a 176 kb region located approximately 500 kb proximal to Xist. We propose that structural variation in this interval explains the presence of multiple functional Xce alleles in the genus Mus. We have identified a new allele, Xcee present in Mus musculus and a possible sixth functional allele in Mus spicilegus. We have also confirmed a parent-of-origin effect on X inactivation choice and provide evidence that maternal inheritance magnifies the skewing associated with strong Xce alleles. Based on the phylogenetic analysis of 155 laboratory strains and wild mice we conclude that Xcea is either a derived allele that arose concurrently with the domestication of fancy mice but prior the derivation of most classical inbred strains or a rare allele in the wild. Furthermore, we have found that despite the presence of multiple haplotypes in the wild Mus musculus domesticus has only one functional Xce allele, Xceb. Lastly, we conclude that each mouse taxa examined has a different functional Xce allele

Genetic regulatory signatures underlying islet gene expression and type 2 diabetes

The majority of genetic variants associated with type 2 diabetes (T2D) are located outside of genes in noncoding regions that may regulate gene expression in disease-relevant tissues, like pancreatic islets. Here, we present the largest integrated analysis to date of high-resolution, high-throughput human islet molecular profiling data to characterize the genome (DNA), epigenome (DNA packaging), and transcriptome (gene expression). We find that T2D genetic variants are enriched in regions of the genome where transcription Regulatory Factor X (RFX) is predicted to bind in an islet-specific manner. Genetic variants that increase T2D risk are predicted to disrupt RFX binding, providing a molecular mechanism to explain how the genome can influence the epigenome, modulating gene expression and ultimately T2D risk

Integrative analysis of gene expression, DNA methylation, physiological traits, and genetic variation in human skeletal muscle

We integrate comeasured gene expression and DNA methylation (DNAme) in 265 human skeletal muscle biopsies from the FUSION study with >7 million genetic variants and eight physiological traits: height, waist, weight, waist-hip ratio, body mass index, fasting serum insulin, fasting plasma glucose, and type 2 diabetes. We find hundreds of genes and DNAme sites associated with fasting insulin, waist, and body mass index, as well as thousands of DNAme sites associated with gene expression (eQTM). We find that controlling for heterogeneity in tissue/muscle fiber type reduces the number of physiological trait associations, and that long-range eQTMs (>1 Mb) are reduced when controlling for tissue/muscle fiber type or latent factors. We map genetic regulators (quantitative trait loci; QTLs) of expression (eQTLs) and DNAme (mQTLs). Using Mendelian randomization (MR) and mediation techniques, we leverage these genetic maps to predict 213 causal relationships between expression and DNAme, approximately two-thirds of which predict methylation to causally influence expression. We use MR to integrate FUSION mQTLs, FUSION eQTLs, and GTEx eQTLs for 48 tissues with genetic associations for 534 diseases and quantitative traits. We identify hundreds of genes and thousands of DNAme sites that may drive the reported disease/quantitative trait genetic associations. We identify 300 gene expression MR associations that are present in both FUSION and GTEx skeletal muscle and that show stronger evidence of MR association in skeletal muscle than other tissues, which may partially reflect differences in power across tissues. As one example, we find that increased RXRA muscle expression may decrease lean tissue mass.Peer reviewe

Coexistent ARID1A–PIK3CA mutations promote ovarian clear-cell tumorigenesis through pro-tumorigenic inflammatory cytokine signalling

Ovarian clear-cell carcinoma (OCCC) is an aggressive form of ovarian cancer with high ARID1A mutation rates. Here we present a mutant mouse model of OCCC. We find that ARID1A inactivation is not sufficient for tumor formation, but requires concurrent activation of the phosphoinositide 3-kinase catalytic subunit, PIK3CA. Remarkably, the mice develop highly penetrant tumors with OCCC-like histopathology, culminating in hemorrhagic ascites and a median survival period of 7.5 weeks. Therapeutic treatment with the pan-PI3K inhibitor, BKM120, prolongs mouse survival by inhibiting tumor cell growth. Cross-species gene expression comparisons support a role for IL-6 inflammatory cytokine signaling in OCCC pathogenesis. We further show that ARID1A and PIK3CA mutations cooperate to promote tumor growth through sustained IL-6 overproduction. Our findings establish an epistatic relationship between SWI/SNF chromatin remodeling and PI3K pathway mutations in OCCC and demonstrate that these pathways converge on pro-tumorigenic cytokine signaling. We propose that ARID1A protects against inflammation-driven tumorigenesis

Molecular Evolutionary Trends and Feeding Ecology Diversification in the Hemiptera, Anchored by the Milkweed Bug Genome

Background: The Hemiptera (aphids, cicadas, and true bugs) are a key insect order, with high diversity for feeding ecology and excellent experimental tractability for molecular genetics. Building upon recent sequencing of hemipteran pests such as phloem-feeding aphids and blood-feeding bed bugs, we present the genome sequence and comparative analyses centered on the milkweed bug Oncopeltus fasciatus, a seed feeder of the family Lygaeidae. Results: The 926-Mb Oncopeltus genome is well represented by the current assembly and official gene set. We use our genomic and RNA-seq data not only to characterize the protein-coding gene repertoire and perform isoform-specific RNAi, but also to elucidate patterns of molecular evolution and physiology. We find ongoing, lineage-specific expansion and diversification of repressive C2H2 zinc finger proteins. The discovery of intron gain and turnover specific to the Hemiptera also prompted the evaluation of lineage and genome size as predictors of gene structure evolution. Furthermore, we identify enzymatic gains and losses that correlate with feeding biology, particularly for reductions associated with derived, fluid nutrition feeding. Conclusions: With the milkweed bug, we now have a critical mass of sequenced species for a hemimetabolous insect order and close outgroup to the Holometabola, substantially improving the diversity of insect genomics. We thereby define commonalities among the Hemiptera and delve into how hemipteran genomes reflect distinct feeding ecologies. Given Oncopeltus’s strength as an experimental model, these new sequence resources bolster the foundation for molecular research and highlight technical considerations for the analysis of medium-sized invertebrate genomes

The genetic regulatory signature of type 2 diabetes in human skeletal muscle

Type 2 diabetes (T2D) results from the combined effects of genetic and environmental factors on multiple tissues over time. Of the 4100 variants associated with T2D and related traits in genome-wide association studies (GWAS), >90% occur in non-coding regions, suggesting a strong regulatory component to T2D risk. Here to understand how T2D status, metabolic traits and genetic variation influence gene expression, we analyse skeletal muscle biopsies from 271 well-phenotyped Finnish participants with glucose tolerance ranging from normal to newly diagnosed T2D. We perform high-depth strand-specific mRNA-sequencing and dense genotyping. Computational integration of these data with epigenome data, including ATAC-seq on skeletal muscle, and transcriptome data across diverse tissues reveals that the tissue-specific genetic regulatory architecture of skeletal muscle is highly enriched in muscle stretch/super enhancers, including some that overlap T2D GWAS variants. In one such example, T2D risk alleles residing in a muscle stretch/super enhancer are linked to increased expression and alternative splicing of muscle-specific isoforms of ANK1.Peer reviewe

Molecular evolutionary trends and feeding ecology diversification in the Hemiptera, anchored by the milkweed bug genome.

BACKGROUND: The Hemiptera (aphids, cicadas, and true bugs) are a key insect order, with high diversity for feeding ecology and excellent experimental tractability for molecular genetics. Building upon recent sequencing of hemipteran pests such as phloem-feeding aphids and blood-feeding bed bugs, we present the genome sequence and comparative analyses centered on the milkweed bug Oncopeltus fasciatus, a seed feeder of the family Lygaeidae. RESULTS: The 926-Mb Oncopeltus genome is well represented by the current assembly and official gene set. We use our genomic and RNA-seq data not only to characterize the protein-coding gene repertoire and perform isoform-specific RNAi, but also to elucidate patterns of molecular evolution and physiology. We find ongoing, lineage-specific expansion and diversification of repressive C2H2 zinc finger proteins. The discovery of intron gain and turnover specific to the Hemiptera also prompted the evaluation of lineage and genome size as predictors of gene structure evolution. Furthermore, we identify enzymatic gains and losses that correlate with feeding biology, particularly for reductions associated with derived, fluid nutrition feeding. CONCLUSIONS: With the milkweed bug, we now have a critical mass of sequenced species for a hemimetabolous insect order and close outgroup to the Holometabola, substantially improving the diversity of insect genomics. We thereby define commonalities among the Hemiptera and delve into how hemipteran genomes reflect distinct feeding ecologies. Given Oncopeltus's strength as an experimental model, these new sequence resources bolster the foundation for molecular research and highlight technical considerations for the analysis of medium-sized invertebrate genomes