The New Frontier of Functional Genomics: From Chromatin Architecture and Noncoding RNAs to Therapeutic Targets

Common diseases are complex, multifactorial disorders whose pathogenesis is influenced by the interplay of genetic predisposition and environmental factors. Genome-wide association studies have interrogated genetic polymorphisms across genomes of individuals to test associations between genotype and susceptibility to specific disorders, providing insights into the genetic architecture of several complex disorders. However, genetic variants associated with the susceptibility to common diseases are often located in noncoding regions of the genome, such as tissue-specific enhancers or long noncoding RNAs, suggesting that regulatory elements might play a relevant role in human diseases. Enhancers are cis-regulatory genomic sequences that act in concert with promoters to regulate gene expression in a precise spatiotemporal manner. They can be located at a considerable distance from their cognate target promoters, increasing the difficulty of their identification. Genomes are organized in domains of chromatin folding, namely topologically associating domains (TADs). Identification of enhancer–promoter interactions within TADs has revealed principles of cell-type specificity across several organisms and tissues. The vast majority of mammalian genomes are pervasively transcribed, accounting for a previously unappreciated complexity of the noncoding RNA fraction. Particularly, long noncoding RNAs have emerged as key players for the establishment of chromatin architecture and regulation of gene expression. In this perspective, we describe the new advances in the fields of transcriptomics and genome organization, focusing on the role of noncoding genomic variants in the predisposition of common diseases. Finally, we propose a new framework for the identification of the next generation of pharmacological targets for common human diseases.

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Genetic regulatory signatures underlying islet gene expression and type 2 diabetes

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1621192114 ◽

2017 ◽

Vol 114 (9) ◽

pp. 2301-2306 ◽

Cited By ~ 110

Author(s):

Arushi Varshney ◽

Laura J. Scott ◽

Ryan P. Welch ◽

Michael R. Erdos ◽

Peter S. Chines ◽

...

Keyword(s):

Gene Expression ◽

Type 2 Diabetes ◽

De Novo ◽

Association Studies ◽

Regulatory Elements ◽

Chromatin Accessibility ◽

Genome Wide Association Studies ◽

Factor X ◽

Risk Alleles

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.

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

F1000Research ◽

10.12688/f1000research.13577.1 ◽

2018 ◽

Vol 7 ◽

pp. 121 ◽

Cited By ~ 1

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.

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EpiRegio: analysis and retrieval of regulatory elements linked to genes

Nucleic Acids Research ◽

10.1093/nar/gkaa382 ◽

2020 ◽

Vol 48 (W1) ◽

pp. W193-W199 ◽

Cited By ~ 4

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/.

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

Scientific Reports ◽

10.1038/s41598-019-51864-9 ◽

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.

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Integration of Alzheimer’s disease genetics and myeloid genomics reveals novel disease risk mechanisms

10.1101/694281 ◽

2019 ◽

Cited By ~ 12

Author(s):

Gloriia Novikova ◽

Manav Kapoor ◽

Julia TCW ◽

Edsel M. Abud ◽

Anastasia G. Efthymiou ◽

...

Keyword(s):

Gene Expression ◽

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Gene Expression Regulation ◽

Disease Risk ◽

Association Studies ◽

Regulatory Elements ◽

Genome Wide Association Studies ◽

Functional Variants ◽

Analytical Approaches

AbstractGenome-wide association studies (GWAS) have identified more than thirty loci associated with Alzheimer’s disease (AD), but the causal variants, regulatory elements, genes and pathways remain largely unknown thus impeding a mechanistic understanding of AD pathogenesis. Previously, we showed that AD risk alleles are enriched in myeloid-specific epigenomic annotations. Here, we show that they are specifically enriched in active enhancers of monocytes, macrophages and microglia. We integrated AD GWAS signals with myeloid epigenomic and transcriptomic datasets using novel analytical approaches to link myeloid enhancer activity to target gene expression regulation and AD risk modification. We nominate candidate AD risk enhancers and identify their target causal genes (including AP4E1, AP4M1, APBB3, BIN1, CD2AP, MS4A4A, MS4A6A, PILRA, RABEP1, SPI1, SPPL2A, TP53INP1, ZKSCAN1, and ZYX) in sixteen loci. Fine-mapping of these enhancers nominates candidate functional variants that likely modify disease susceptibility by regulating causal gene expression in myeloid cells. In the MS4A locus we identified a single candidate functional variant and validated it experimentally in human induced pluripotent stem cell (hiPSC)-derived microglia. Combined, these results strongly implicate dysfunction of the myeloid endolysosomal system in the etiology of AD.

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

F1000Research ◽

10.12688/f1000research.13577.2 ◽

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 diseases, but the complexity of transcriptional regulation mechanisms often limits 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.

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Enhancer variants associated with Alzheimer’s disease affect gene expression via chromatin looping

10.1101/426312 ◽

2018 ◽

Author(s):

Masataka Kikuchi ◽

Norikazu Hara ◽

Mai Hasegawa ◽

Akinori Miyashita ◽

Ryozo Kuwano ◽

...

Keyword(s):

Gene Expression ◽

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Association Studies ◽

Regulatory Elements ◽

Regulation Of Transcription ◽

Genome Wide Association Studies ◽

Expression Levels ◽

Chromatin Loops ◽

Affect Gene Expression

AbstractBackground:Genome-wide association studies (GWASs) have identified single-nucleotide polymorphisms (SNPs) that may be genetic factors underlying Alzheimer’s disease (AD). However, how these AD-associated SNPs (AD SNPs) contribute to the pathogenesis of this disease is poorly understood because most of them are located in non-coding regions, such as introns and intergenic regions. Previous studies reported that some disease-associated SNPs affect regulatory elements including enhancers. We hypothesized that non-coding AD SNPs are located in enhancers and affect gene expression levels via chromatin loops.Results:We examined enhancer locations that were predicted in 127 human tissues or cell types, including ten brain tissues, and identified chromatin-chromatin interactions by Hi-C experiments. We report the following findings: (1) nearly 30% of non-coding AD SNPs are located in enhancers; (2) expression quantitative trait locus (eQTL) genes affected by non-coding AD SNPs within enhancers are associated with amyloid beta clearance, synaptic transmission, and immune responses; (3) 95% of the AD SNPs located in enhancers co-localize with their eQTL genes in topologically associating domains suggesting that regulation may occur through chromatin higher-order structures; (4) rs1476679 spatially contacts the promoters of eQTL genes via CTCF-CTCF interactions; (5) the effect of other AD SNPs such as rs7364180 is likely to be, at least in part, indirect through regulation of transcription factors that in turn regulate AD associated genes.Conclusion:Our results suggest that non-coding AD SNPs may affect the function of enhancers thereby influencing the expression levels of surrounding or distant genes via chromatin loops. This result may explain how some non-coding AD SNPs contribute to AD pathogenesis.

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Integration of Alzheimer’s disease genetics and myeloid genomics identifies disease risk regulatory elements and genes

Nature Communications ◽

10.1038/s41467-021-21823-y ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Gloriia Novikova ◽

Manav Kapoor ◽

Julia TCW ◽

Edsel M. Abud ◽

Anastasia G. Efthymiou ◽

...

Keyword(s):

Gene Expression ◽

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Disease Risk ◽

Association Studies ◽

Regulatory Elements ◽

Genome Wide Association Studies ◽

Risk Alleles ◽

Functional Variants ◽

Analytical Approaches

AbstractGenome-wide association studies (GWAS) have identified more than 40 loci associated with Alzheimer’s disease (AD), but the causal variants, regulatory elements, genes and pathways remain largely unknown, impeding a mechanistic understanding of AD pathogenesis. Previously, we showed that AD risk alleles are enriched in myeloid-specific epigenomic annotations. Here, we show that they are specifically enriched in active enhancers of monocytes, macrophages and microglia. We integrated AD GWAS with myeloid epigenomic and transcriptomic datasets using analytical approaches to link myeloid enhancer activity to target gene expression regulation and AD risk modification. We identify AD risk enhancers and nominate candidate causal genes among their likely targets (including AP4E1, AP4M1, APBB3, BIN1, MS4A4A, MS4A6A, PILRA, RABEP1, SPI1, TP53INP1, and ZYX) in twenty loci. Fine-mapping of these enhancers nominates candidate functional variants that likely modify AD risk by regulating gene expression in myeloid cells. In the MS4A locus we identified a single candidate functional variant and validated it in human induced pluripotent stem cell (hiPSC)-derived microglia and brain. Taken together, this study integrates AD GWAS with multiple myeloid genomic datasets to investigate the mechanisms of AD risk alleles and nominates candidate functional variants, regulatory elements and genes that likely modulate disease susceptibility.

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