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  • 1
    Online Resource
    Online Resource
    Genetic regulatory signatures underlying islet gene expression and type 2 diabetes
    Proceedings of the National Academy of Sciences ; 2017
    In:  Proceedings of the National Academy of Sciences Vol. 114, No. 9 ( 2017-02-28), p. 2301-2306
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 114, No. 9 ( 2017-02-28), p. 2301-2306
    Abstract: Genome-wide association studies (GWAS) have identified 〉 100 independent SNPs that modulate the risk of type 2 diabetes (T2D) and related traits. However, the pathogenic mechanisms of most of these SNPs remain elusive. Here, we examined genomic, epigenomic, and transcriptomic profiles in human pancreatic islets to understand the links between genetic variation, chromatin landscape, and gene expression in the context of T2D. We first integrated genome and transcriptome variation across 112 islet samples to produce dense cis -expression quantitative trait loci ( cis -eQTL) maps. Additional integration with chromatin-state maps for islets and other diverse tissue types revealed that cis -eQTLs for islet-specific genes are specifically and significantly enriched in islet stretch enhancers. High-resolution chromatin accessibility profiling using assay for transposase-accessible chromatin sequencing (ATAC-seq) in two islet samples enabled us to identify specific transcription factor (TF) footprints embedded in active regulatory elements, which are highly enriched for islet cis -eQTL. Aggregate allelic bias signatures in TF footprints enabled us de novo to reconstruct TF binding affinities genetically, which support the high-quality nature of the TF footprint predictions. Interestingly, we found that T2D GWAS loci were strikingly and specifically enriched in islet Regulatory Factor X (RFX) footprints. Remarkably, within and across independent loci, T2D risk alleles that overlap with RFX footprints uniformly disrupt the RFX motifs at high-information content positions. Together, these results suggest that common regulatory variations have shaped islet TF footprints and the transcriptome and that a confluent RFX regulatory grammar plays a significant role in the genetic component of T2D predisposition.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.1621192114
    RVK:
    TA 1000
    RVK:
    WA 15000
    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2017
    detail.hit.zdb_id: 209104-5
    detail.hit.zdb_id: 1461794-8
    SSG: 11
    SSG: 12
    Location Call Number Limitation Availability
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  • 2
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    Online Resource
    Integrative analysis of gene expression, DNA methylation, physiological traits, and genetic variation in human skeletal muscle
    Proceedings of the National Academy of Sciences ; 2019
    In:  Proceedings of the National Academy of Sciences Vol. 116, No. 22 ( 2019-05-28), p. 10883-10888
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 116, No. 22 ( 2019-05-28), p. 10883-10888
    Abstract: 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.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.1814263116
    RVK:
    TA 1000
    RVK:
    WA 15000
    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2019
    detail.hit.zdb_id: 209104-5
    detail.hit.zdb_id: 1461794-8
    SSG: 11
    SSG: 12
    Location Call Number Limitation Availability
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  • 3
    Online Resource
    Online Resource
    Chromatin stretch enhancer states drive cell-specific gene regulation and harbor human disease risk variants
    Proceedings of the National Academy of Sciences ; 2013
    In:  Proceedings of the National Academy of Sciences Vol. 110, No. 44 ( 2013-10-29), p. 17921-17926
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 110, No. 44 ( 2013-10-29), p. 17921-17926
    Abstract: Chromatin-based functional genomic analyses and genomewide association studies (GWASs) together implicate enhancers as critical elements influencing gene expression and risk for common diseases. Here, we performed systematic chromatin and transcriptome profiling in human pancreatic islets. Integrated analysis of islet data with those from nine cell types identified specific and significant enrichment of type 2 diabetes and related quantitative trait GWAS variants in islet enhancers. Our integrated chromatin maps reveal that most enhancers are short (median = 0.8 kb). Each cell type also contains a substantial number of more extended (≥3 kb) enhancers. Interestingly, these stretch enhancers are often tissue-specific and overlap locus control regions, suggesting that they are important chromatin regulatory beacons. Indeed, we show that ( i ) tissue specificity of enhancers and nearby gene expression increase with enhancer length; ( ii ) neighborhoods containing stretch enhancers are enriched for important cell type–specific genes; and ( iii ) GWAS variants associated with traits relevant to a particular cell type are more enriched in stretch enhancers compared with short enhancers. Reporter constructs containing stretch enhancer sequences exhibited tissue-specific activity in cell culture experiments and in transgenic mice. These results suggest that stretch enhancers are critical chromatin elements for coordinating cell type–specific regulatory programs and that sequence variation in stretch enhancers affects risk of major common human diseases.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.1317023110
    RVK:
    TA 1000
    RVK:
    WA 15000
    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2013
    detail.hit.zdb_id: 209104-5
    detail.hit.zdb_id: 1461794-8
    SSG: 11
    SSG: 12
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
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