Non-coding genome functions in diabetes

2015 ◽  
Vol 56 (1) ◽  
pp. R1-R20 ◽  
Author(s):  
Inês Cebola ◽  
Lorenzo Pasquali
Keyword(s):  
Gene Regulation ◽  
Sequence Variation ◽  
High Throughput Sequencing ◽  
Association Studies ◽  
Cell Types ◽  
Regulatory Elements ◽  
Genome Wide Association Studies ◽  
Coding Regions ◽  
Pancreatic Progenitors ◽  
Functional Variants

Most of the genetic variation associated with diabetes, through genome-wide association studies, does not reside in protein-coding regions, making the identification of functional variants and their eventual translation to the clinic challenging. In recent years, high-throughput sequencing-based methods have enabled genome-scale high-resolution epigenomic profiling in a variety of human tissues, allowing the exploration of the human genome outside of the well-studied coding regions. These experiments unmasked tens of thousands of regulatory elements across several cell types, including diabetes-relevant tissues, providing new insights into their mechanisms of gene regulation. Regulatory landscapes are highly dynamic and cell-type specific and, being sensitive to DNA sequence variation, can vary with individual genomes. The scientific community is now in place to exploit the regulatory maps of tissues central to diabetes etiology, such as pancreatic progenitors and adult islets. This giant leap forward in the understanding of pancreatic gene regulation is revolutionizing our capacity to discriminate between functional and non-functional non-coding variants, opening opportunities to uncover regulatory links between sequence variation and diabetes susceptibility. In this review, we focus on the non-coding regulatory landscape of the pancreatic endocrine cells and provide an overview of the recent developments in this field.

scholarly journals EpiRegio: analysis and retrieval of regulatory elements linked to genes

2020 ◽  
Vol 48 (W1) ◽  
pp. W193-W199 ◽  
Author(s):  
Nina Baumgarten ◽  
Dennis Hecker ◽  
Sivarajan Karunanithi ◽  
Florian Schmidt ◽  
Markus List ◽  
...  
Keyword(s):  
Gene Expression ◽  
Target Genes ◽  
Association Studies ◽  
Web Server ◽  
Cell Types ◽  
Regulatory Elements ◽  
Chromatin Accessibility ◽  
Genome Wide Association Studies ◽  
Coding Regions ◽  
Genomic Regions

Abstract A current challenge in genomics is to interpret non-coding regions and their role in transcriptional regulation of possibly distant target genes. Genome-wide association studies show that a large part of genomic variants are found in those non-coding regions, but their mechanisms of gene regulation are often unknown. An additional challenge is to reliably identify the target genes of the regulatory regions, which is an essential step in understanding their impact on gene expression. Here we present the EpiRegio web server, a resource of regulatory elements (REMs). REMs are genomic regions that exhibit variations in their chromatin accessibility profile associated with changes in expression of their target genes. EpiRegio incorporates both epigenomic and gene expression data for various human primary cell types and tissues, providing an integrated view of REMs in the genome. Our web server allows the analysis of genes and their associated REMs, including the REM’s activity and its estimated cell type-specific contribution to its target gene’s expression. Further, it is possible to explore genomic regions for their regulatory potential, investigate overlapping REMs and by that the dissection of regions of large epigenomic complexity. EpiRegio allows programmatic access through a REST API and is freely available at https://epiregio.de/.

scholarly journals Analysis of putative cis-regulatory elements regulating blood pressure variation

2020 ◽  
Vol 29 (11) ◽  
pp. 1922-1932
Author(s):  
Priyanka Nandakumar ◽  
Dongwon Lee ◽  
Thomas J Hoffmann ◽  
Georg B Ehret ◽  
Dan Arking ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Association Studies ◽  
Specific Effect ◽  
Cell Types ◽  
Regulatory Elements ◽  
Open Chromatin ◽  
Genome Wide Association Studies ◽  
Cell Type ◽  
Functional Scores ◽  
Cell Type Specific

Abstract Hundreds of loci have been associated with blood pressure (BP) traits from many genome-wide association studies. We identified an enrichment of these loci in aorta and tibial artery expression quantitative trait loci in our previous work in ~100 000 Genetic Epidemiology Research on Aging study participants. In the present study, we sought to fine-map known loci and identify novel genes by determining putative regulatory regions for these and other tissues relevant to BP. We constructed maps of putative cis-regulatory elements (CREs) using publicly available open chromatin data for the heart, aorta and tibial arteries, and multiple kidney cell types. Variants within these regions may be evaluated quantitatively for their tissue- or cell-type-specific regulatory impact using deltaSVM functional scores, as described in our previous work. We aggregate variants within these putative CREs within 50 Kb of the start or end of ‘expressed’ genes in these tissues or cell types using public expression data and use deltaSVM scores as weights in the group-wise sequence kernel association test to identify candidates. We test for association with both BP traits and expression within these tissues or cell types of interest and identify the candidates MTHFR, C10orf32, CSK, NOV, ULK4, SDCCAG8, SCAMP5, RPP25, HDGFRP3, VPS37B and PPCDC. Additionally, we examined two known QT interval genes, SCN5A and NOS1AP, in the Atherosclerosis Risk in Communities Study, as a positive control, and observed the expected heart-specific effect. Thus, our method identifies variants and genes for further functional testing using tissue- or cell-type-specific putative regulatory information.

scholarly journals Chronic lymphocytic leukemia (CLL) risk is mediated by multiple enhancer variants within CLL risk loci

2020 ◽  
Vol 29 (16) ◽  
pp. 2761-2774
Author(s):  
Huihuang Yan ◽  
Shulan Tian ◽  
Geffen Kleinstern ◽  
Zhiquan Wang ◽  
Jeong-Heon Lee ◽  
...  
Keyword(s):  
Chronic Lymphocytic Leukemia ◽  
Immune Cell ◽  
Association Studies ◽  
Cell Types ◽  
Lymphocytic Leukemia ◽  
Type I ◽  
Genome Wide Association Studies ◽  
Gene Promoters ◽  
Functional Variants ◽  
Increased Risk

Abstract Chronic lymphocytic leukemia (CLL) is the most common adult leukemia in Western countries. It has a strong genetic basis, showing a ~ 8-fold increased risk of CLL in first-degree relatives. Genome-wide association studies (GWAS) have identified 41 risk variants across 41 loci. However, for a majority of the loci, the functional variants and the mechanisms underlying their causal roles remain undefined. Here, we examined the genetic and epigenetic features associated with 12 index variants, along with any correlated (r2 ≥ 0.5) variants, at the CLL risk loci located outside of gene promoters. Based on publicly available ChIP-seq and chromatin accessibility data as well as our own ChIP-seq data from CLL patients, we identified six candidate functional variants at six loci and at least two candidate functional variants at each of the remaining six loci. The functional variants are predominantly located within enhancers or super-enhancers, including bi-directionally transcribed enhancers, which are often restricted to immune cell types. Furthermore, we found that, at 78% of the functional variants, the alternative alleles altered the transcription factor binding motifs or histone modifications, indicating the involvement of these variants in the change of local chromatin state. Finally, the enhancers carrying functional variants physically interacted with genes enriched in the type I interferon signaling pathway, apoptosis, or TP53 network that are known to play key roles in CLL. These results support the regulatory roles for inherited noncoding variants in the pathogenesis of CLL.

scholarly journals Using regulatory genomics data to interpret the function of disease variants and prioritise genes from expression studies

F1000Research ◽  
2018 ◽  
Vol 7 ◽  
pp. 121 ◽  
Author(s):  
Enrico Ferrero
Keyword(s):  
Gene Expression ◽  
Large Scale ◽  
Association Studies ◽  
Cell Types ◽  
Regulatory Elements ◽  
New Drugs ◽  
Genome Wide Association Studies ◽  
Functional Interpretation ◽  
Expression Studies ◽  
Regulatory Genomics

The identification of therapeutic targets is a critical step in the research and developement of new drugs, with several drug discovery programmes failing because of a weak linkage between target and disease. Genome-wide association studies and large-scale gene expression experiments are providing insights into the biology of several common and complex diseases, but the complexity of transcriptional regulation mechanisms often limit our understanding of how genetic variation can influence changes in gene expression. Several initiatives in the field of regulatory genomics are aiming to close this gap by systematically identifying and cataloguing regulatory elements such as promoters and enhacers across different tissues and cell types. In this Bioconductor workflow, we will explore how different types of regulatory genomic data can be used for the functional interpretation of disease-associated variants and for the prioritisation of gene lists from gene expression experiments.

scholarly journals Addiction-associated genetic variants implicate brain cell type- and region-specific cis-regulatory elements in addiction neurobiology

2020 ◽  
Author(s):  
Chaitanya Srinivasan ◽  
BaDoi N. Phan ◽  
Alyssa J. Lawler ◽  
Easwaran Ramamurthy ◽  
Michael Kleyman ◽  
...  
Keyword(s):  
Genetic Variants ◽  
Cell Types ◽  
Regulatory Elements ◽  
Brain Regions ◽  
Open Chromatin ◽  
Genome Wide Association Studies ◽  
Cell Type ◽  
Coding Regions ◽  
Cell Type Specific ◽  
The Impact

ABSTRACTRecent large genome-wide association studies (GWAS) have identified multiple confident risk loci linked to addiction-associated behavioral traits. Genetic variants linked to addiction-associated traits lie largely in non-coding regions of the genome, likely disrupting cis-regulatory element (CRE) function. CREs tend to be highly cell type-specific and may contribute to the functional development of the neural circuits underlying addiction. Yet, a systematic approach for predicting the impact of risk variants on the CREs of specific cell populations is lacking. To dissect the cell types and brain regions underlying addiction-associated traits, we applied LD score regression to compare GWAS to genomic regions collected from human and mouse assays for open chromatin, which is associated with CRE activity. We found enrichment of addiction-associated variants in putative regulatory elements marked by open chromatin in neuronal (NeuN+) nuclei collected from multiple prefrontal cortical areas and striatal regions known to play major roles in reward and addiction. To further dissect the cell type-specific basis of addiction-associated traits, we also identified enrichments in human orthologs of open chromatin regions of mouse neuron subtypes: cortical excitatory, PV, D1, and D2. Lastly, we developed machine learning models from mouse cell type-specific regions of open chromatin to further dissect human NeuN+ open chromatin regions into cortical excitatory or striatal D1 and D2 neurons and predict the functional impact of addiction-associated genetic variants. Our results suggest that different neuron subtypes within the reward system play distinct roles in the variety of traits that contribute to addiction.Significance StatementOur study on cell types and brain regions contributing to heritability of addiction-associated traits suggests that the conserved non-coding regions within cortical excitatory and striatal medium spiny neurons contribute to genetic predisposition for nicotine, alcohol, and cannabis use behaviors. This computational framework can flexibly integrate epigenomic data across species to screen for putative causal variants in a cell type- and tissue-specific manner across numerous complex traits.

scholarly journals Non-coding DNA in IBD: from sequence variation in DNA regulatory elements to novel therapeutic potential

Gut ◽  
2019 ◽  
Vol 68 (5) ◽  
pp. 928-941 ◽  
Author(s):  
Claartje Aleid Meddens ◽  
Amy Catharina Johanna van der List ◽  
Edward Eelco Salomon Nieuwenhuis ◽  
Michal Mokry
Keyword(s):  
Therapeutic Potential ◽  
Association Studies ◽  
Cell Types ◽  
Regulatory Elements ◽  
Genome Wide Association Studies ◽  
Enhancer Activity ◽  
Protein Coding ◽  
Dna Regulatory Elements ◽  
Coding Variants ◽  
Novel Therapeutic

Genome-wide association studies have identified over 200 loci associated with IBD. We and others have recently shown that, in addition to variants in protein-coding genes, the majority of the associated loci are related to DNA regulatory elements (DREs). These findings add a dimension to the already complex genetic background of IBD. In this review we summarise the existing evidence on the role of DREs in IBD. We discuss how epigenetic research can be used in candidate gene approaches that take non-coding variants into account and can help to pinpoint the essential pathways and cell types in the pathogenesis of IBD. Despite the increased level of genetic complexity, these findings can contribute to novel therapeutic options that target transcription factor binding and enhancer activity. Finally, we summarise the future directions and challenges of this emerging field.

scholarly journals Multiple functional variants in long-range enhancer elements contribute to the risk of SNP rs965513 in thyroid cancer

2015 ◽  
Vol 112 (19) ◽  
pp. 6128-6133 ◽  
Author(s):  
Huiling He ◽  
Wei Li ◽  
Sandya Liyanarachchi ◽  
Mukund Srinivas ◽  
Yanqiang Wang ◽  
...  
Keyword(s):  
Thyroid Cancer ◽  
Long Range ◽  
Molecular Mechanisms ◽  
Association Studies ◽  
Linkage Disequilibrium Block ◽  
Thyroid Tissue ◽  
Regulatory Elements ◽  
Genome Wide Association Studies ◽  
Papillary Thyroid ◽  
Functional Variants

The [A] allele of SNP rs965513 in 9q22 has been consistently shown to be highly associated with increased papillary thyroid cancer (PTC) risk with an odds ratio of ∼1.8 as determined by genome-wide association studies, yet the molecular mechanisms remain poorly understood. Previously, we noted that the expression of two genes in the region, forkhead box E1 (FOXE1) and PTC susceptibility candidate 2 (PTCSC2), is regulated by rs965513 in unaffected thyroid tissue, but the underlying mechanisms were not elucidated. Here, we fine-mapped the 9q22 region in PTC and controls and detected an ∼33-kb linkage disequilibrium block (containing the lead SNP rs965513) that significantly associates with PTC risk. Chromatin characteristics and regulatory element signatures in this block disclosed at least three regulatory elements functioning as enhancers. These enhancers harbor at least four SNPs (rs7864322, rs12352658, rs7847449, and rs10759944) that serve as functional variants. The variant genotypes are associated with differential enhancer activities and/or transcription factor binding activities. Using the chromosome conformation capture methodology, long-range looping interactions of these elements with the promoter region shared by FOXE1 and PTCSC2 in a human papillary thyroid carcinoma cell line (KTC-1) and unaffected thyroid tissue were found. Our results suggest that multiple variants coinherited with the lead SNP and located in long-range enhancers are involved in the transcriptional regulation of FOXE1 and PTCSC2 expression. These results explain the mechanism by which the risk allele of rs965513 predisposes to thyroid cancer.

scholarly journals Rare variants in non-coding regulatory regions of the genome that affect gene expression in systemic lupus erythematosus

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Sarah A. Jones ◽  
Stuart Cantsilieris ◽  
Huapeng Fan ◽  
Qiang Cheng ◽  
Brendan E. Russ ◽  
...  
Keyword(s):  
Gene Expression ◽  
Systemic Lupus Erythematosus ◽  
Lupus Erythematosus ◽  
Association Studies ◽  
Regulatory Elements ◽  
Genome Wide Association Studies ◽  
Systemic Lupus ◽  
High Resolution Melt ◽  
Functional Variants ◽  
Reporter Assays

Abstract Personalized medicine approaches are increasingly sought for diseases with a heritable component. Systemic lupus erythematosus (SLE) is the prototypic autoimmune disease resulting from loss of immunologic tolerance, but the genetic basis of SLE remains incompletely understood. Genome wide association studies (GWAS) identify regions associated with disease, based on common single nucleotide polymorphisms (SNPs) within them, but these SNPs may simply be markers in linkage disequilibrium with other, causative mutations. Here we use an hierarchical screening approach for prediction and testing of true functional variants within regions identified in GWAS; this involved bioinformatic identification of putative regulatory elements within close proximity to SLE SNPs, screening those regions for potentially causative mutations by high resolution melt analysis, and functional validation using reporter assays. Using this approach, we screened 15 SLE associated loci in 143 SLE patients, identifying 7 new variants including 5 SNPs and 2 insertions. Reporter assays revealed that the 5 SNPs were functional, altering enhancer activity. One novel variant was linked to the relatively well characterized rs9888739 SNP at the ITGAM locus, and may explain some of the SLE heritability at this site. Our study demonstrates that non-coding regulatory elements can contain private sequence variants affecting gene expression, which may explain part of the heritability of SLE.

scholarly journals Functional Annotation of Putative Regulatory Elements at Cancer Susceptibility Loci

2014 ◽  
Vol 13s2 ◽  
pp. CIN.S13789
Author(s):  
Stephanie A. Rosse ◽  
Paul L. Auer ◽  
Christopher S. Carlson
Keyword(s):  
Cancer Susceptibility ◽  
Association Studies ◽  
Regulatory Elements ◽  
Genome Wide Association Studies ◽  
Genetic Associations ◽  
Functional Polymorphisms ◽  
Functional Variants ◽  
Genome Wide ◽  
Regulatory Variant ◽  
Causal Variants

Most cancer-associated genetic variants identified from genome-wide association studies (GWAS) do not obviously change protein structure, leading to the hypothesis that the associations are attributable to regulatory polymorphisms. Translating genetic associations into mechanistic insights can be facilitated by knowledge of the causal regulatory variant (or variants) responsible for the statistical signal. Experimental validation of candidate functional variants is onerous, making bioinformatic approaches necessary to prioritize candidates for laboratory analysis. Thus, a systematic approach for recognizing functional (and, therefore, likely causal) variants in noncoding regions is an important step toward interpreting cancer risk loci. This review provides a detailed introduction to current regulatory variant annotations, followed by an overview of how to leverage these resources to prioritize candidate functional polymorphisms in regulatory regions.

scholarly journals Modeling regulatory network topology improves genome-wide analyses of complex human traits

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Xiang Zhu ◽  
Zhana Duren ◽  
Wing Hung Wong
Keyword(s):  
Network Topology ◽  
Complex Traits ◽  
Regulatory Networks ◽  
Association Studies ◽  
Biological Significance ◽  
Cell Types ◽  
Genome Wide Association Studies ◽  
Coding Regions ◽  
Genome Wide ◽  
Complex Human Traits

AbstractGenome-wide association studies (GWAS) have cataloged many significant associations between genetic variants and complex traits. However, most of these findings have unclear biological significance, because they often have small effects and occur in non-coding regions. Integration of GWAS with gene regulatory networks addresses both issues by aggregating weak genetic signals within regulatory programs. Here we develop a Bayesian framework that integrates GWAS summary statistics with regulatory networks to infer genetic enrichments and associations simultaneously. Our method improves upon existing approaches by explicitly modeling network topology to assess enrichments, and by automatically leveraging enrichments to identify associations. Applying this method to 18 human traits and 38 regulatory networks shows that genetic signals of complex traits are often enriched in interconnections specific to trait-relevant cell types or tissues. Prioritizing variants within enriched networks identifies known and previously undescribed trait-associated genes revealing biological and therapeutic insights.

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