Using INFERNO to Infer the Molecular Mechanisms Underlying Noncoding Genetic Associations

2020 ◽  
pp. 73-91
Author(s):  
Alexandre Amlie-Wolf ◽  
Pavel P. Kuksa ◽  
Chien-Yueh Lee ◽  
Elisabeth Mlynarski ◽  
Yuk Yee Leung ◽  
...  
Keyword(s):  
Molecular Mechanisms ◽  
Genetic Associations

scholarly journals The fog of genetics: Known unknowns and unknown unknowns in the genetics of complex traits and diseases

2019 ◽  
Author(s):  
João Pedro de Magalhães ◽  
Jingwei Wang
Keyword(s):  
Genetic Variability ◽  
Genetic Variants ◽  
Genetic Information ◽  
Complex Traits ◽  
Drug Targets ◽  
Molecular Mechanisms ◽  
Genetic Associations ◽  
Missing Heritability ◽  
Genome Space ◽  
Known Unknowns

AbstractAssociating genetic variants with phenotypes is not only important to understand the underlying biology but also to identify potential drug targets for treating diseases. It is widely accepted that for most complex traits many associations remain to be discovered, the so-called “missing heritability.” Yet missing heritability can be estimated, it is a known unknown, and we argue is only a fraction of the unknowns in genetics. The majority of possible genetic variants in the genome space are either too rare to be detected or even entirely absent from populations, and therefore do not contribute to estimates of phenotypic or genetic variability. We call these unknown unknowns in genetics the “fog of genetics.” Using data from the 1000 Genomes Project we then show that larger genes with greater genetic diversity are more likely to be associated with human traits, demonstrating that genetic associations are biased towards particular types of genes and that the genetic information we are lacking about traits and diseases is potentially immense. Our results and model have multiple implications for how genetic variability is perceived to influence complex traits, provide insights on molecular mechanisms of disease and for drug discovery efforts based on genetic information.

scholarly journals The GTEx Consortium atlas of genetic regulatory effects across human tissues

Science ◽  
2020 ◽  
Vol 369 (6509) ◽  
pp. 1318-1330 ◽  
Author(s):  
Keyword(s):  
Complex Traits ◽  
Molecular Mechanisms ◽  
Tissue Expression ◽  
Genetic Effects ◽  
Regulatory Mechanisms ◽  
Human Tissues ◽  
Genetic Associations ◽  
Key Factor ◽  
Regulatory Effects ◽  
Almost All

The Genotype-Tissue Expression (GTEx) project was established to characterize genetic effects on the transcriptome across human tissues and to link these regulatory mechanisms to trait and disease associations. Here, we present analyses of the version 8 data, examining 15,201 RNA-sequencing samples from 49 tissues of 838 postmortem donors. We comprehensively characterize genetic associations for gene expression and splicing in cis and trans, showing that regulatory associations are found for almost all genes, and describe the underlying molecular mechanisms and their contribution to allelic heterogeneity and pleiotropy of complex traits. Leveraging the large diversity of tissues, we provide insights into the tissue specificity of genetic effects and show that cell type composition is a key factor in understanding gene regulatory mechanisms in human tissues.

scholarly journals Challenges and progress in interpretation of non-coding genetic variants associated with human disease

2017 ◽  
Vol 242 (13) ◽  
pp. 1325-1334 ◽  
Author(s):  
Yizhou Zhu ◽  
Cagdas Tazearslan ◽  
Yousin Suh
Keyword(s):  
Molecular Mechanisms ◽  
Target Genes ◽  
Disease Risk ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genetic Associations ◽  
Functional Interpretation ◽  
Genome Wide ◽  
Coding Variants

Genome-wide association studies have shown that the far majority of disease-associated variants reside in the non-coding regions of the genome, suggesting that gene regulatory changes contribute to disease risk. To identify truly causal non-coding variants and their affected target genes remains challenging but is a critical step to translate the genetic associations to molecular mechanisms and ultimately clinical applications. Here we review genomic/epigenomic resources and in silico tools that can be used to identify causal non-coding variants and experimental strategies to validate their functionalities. Impact statement Most signals from genome-wide association studies (GWASs) map to the non-coding genome, and functional interpretation of these associations remained challenging. We reviewed recent progress in methodologies of studying the non-coding genome and argued that no single approach allows one to effectively identify the causal regulatory variants from GWAS results. By illustrating the advantages and limitations of each method, our review potentially provided a guideline for taking a combinatorial approach to accurately predict, prioritize, and eventually experimentally validate the causal variants.

scholarly journals Genetic associations at regulatory phenotypes improve fine-mapping of causal variants for twelve immune-mediated diseases

2020 ◽  
Author(s):  
Kousik Kundu ◽  
Alice L. Mann ◽  
Manuel Tardaguila ◽  
Stephen Watt ◽  
Hannes Ponstingl ◽  
...  
Keyword(s):  
Fine Mapping ◽  
Molecular Mechanisms ◽  
Immune Cell ◽  
Meta Analysis ◽  
Cell Types ◽  
Genetic Associations ◽  
Sequencing Data ◽  
Immune Mediated ◽  
Causal Genes ◽  
Causal Variants

AbstractThe identification of causal genetic variants for common diseases improves understanding of disease biology. Here we use data from the BLUEPRINT project to identify regulatory quantitative trait loci (QTL) for three primary human immune cell types and use these to fine-map putative causal variants for twelve immune-mediated diseases. We identify 340 unique, non major histocompatibility complex (MHC) disease loci that colocalise with high (>98%) posterior probability with regulatory QTLs, and apply Bayesian frameworks to fine-map associations at each locus. We show that fine-mapping applied to regulatory QTLs yields smaller credible set sizes and higher posterior probabilities for candidate causal variants compared to disease summary statistics. We also describe a systematic under-representation of insertion/deletion (INDEL) polymorphisms in credible sets derived from publicly available disease meta-analysis when compared to QTLs based on genome-sequencing data. Overall, our findings suggest that fine-mapping applied to disease-colocalising regulatory QTLs can enhance the discovery of putative causal disease variants and provide insights into the underlying causal genes and molecular mechanisms.

scholarly journals The GTEx Consortium atlas of genetic regulatory effects across human tissues

2019 ◽  
Author(s):  
François Aguet ◽  
Alvaro N Barbeira ◽  
Rodrigo Bonazzola ◽  
Andrew Brown ◽  
Stephane E Castel ◽  
...  
Keyword(s):  
Complex Traits ◽  
Molecular Mechanisms ◽  
Tissue Expression ◽  
Genetic Effects ◽  
Regulatory Mechanisms ◽  
Human Tissues ◽  
Genetic Associations ◽  
Key Factor ◽  
Regulatory Effects ◽  
Almost All

AbstractThe Genotype-Tissue Expression (GTEx) project was established to characterize genetic effects on the transcriptome across human tissues, and to link these regulatory mechanisms to trait and disease associations. Here, we present analyses of the v8 data, based on 17,382 RNA-sequencing samples from 54 tissues of 948 post-mortem donors. We comprehensively characterize genetic associations for gene expression and splicing incisandtrans, showing that regulatory associations are found for almost all genes, and describe the underlying molecular mechanisms and their contribution to allelic heterogeneity and pleiotropy of complex traits. Leveraging the large diversity of tissues, we provide insights into the tissue-specificity of genetic effects, and show that cell type composition is a key factor in understanding gene regulatory mechanisms in human tissues.

scholarly journals Dissecting molecular regulatory mechanisms underlying noncoding susceptibility SNPs associated with 19 autoimmune diseases using multi-omics integrative analysis

2019 ◽  
Author(s):  
Xiao-Feng Chen ◽  
Min-Rui Guo ◽  
Yuan-Yuan Duan ◽  
Feng Jiang ◽  
Hao Wu ◽  
...  
Keyword(s):  
Autoimmune Diseases ◽  
Long Range ◽  
Drug Targets ◽  
Molecular Mechanisms ◽  
Target Genes ◽  
Immune Cell ◽  
Drug Application ◽  
Chromatin Interaction ◽  
Genetic Associations ◽  
Functional Variants

AbstractThe genome-wide association studies (GWAS) have identified hundreds of susceptibility loci associated with autoimmune diseases. However, over 90% of risk variants are located in the noncoding regions, leading to great challenges in deciphering the underlying causal functional variants/genes and biological mechanisms. Previous studies focused on developing new scoring method to prioritize functional/disease-relevant variants. However, they principally incorporated annotation data across all cells/tissues while omitted the cell-specific or context-specific regulation. Moreover, limited analyses were performed to dissect the detailed molecular regulatory circuits linking functional GWAS variants to disease etiology. Here we devised a new analysis frame that incorporate hundreds of immune cell-specific multi-omics data to prioritize functional noncoding susceptibility SNPs with gene targets and further dissect their downstream molecular mechanisms and clinical applications for 19 autoimmune diseases. Most prioritized SNPs have genetic associations with transcription factors (TFs) binding, histone modification or chromatin accessibility, indicating their allelic regulatory roles on target genes. Their target genes were significantly enriched in immunologically related pathways and other immunologically related functions. We also detected long-range regulation on 90.7% of target genes including 132 ones exclusively regulated by distal SNPs (eg, CD28, IL2RA), which involves several potential key TFs (eg, CTCF), suggesting the important roles of long-range chromatin interaction in autoimmune diseases. Moreover, we identified hundreds of known or predicted druggable genes, and predicted some new potential drug targets for several autoimmune diseases, including two genes (NFKB1, SH2B3) with known drug indications on other diseases, highlighting their potential drug repurposing opportunities. In summary, our analyses may provide unique resource for future functional follow-up and drug application on autoimmune diseases, which are freely available at http://fngwas.online/.Author SummaryAutoimmune diseases are groups of complex immune system disorders with high prevalence rates and high heritabilities. Previous studies have unraveled thousands of SNPs associated with different autoimmune diseases. However, it remains largely unknown on the molecular mechanisms underlying these genetic associations. Striking, over 90% of risk SNPs are located in the noncoding region. By leveraging multiple immune cell-specific multi-omics data across genomic, epigenetic, transcriptomic and 3D chromatin interaction information, we systematically analyzed the functional variants/genes and biological mechanisms underlying genetic association on 19 autoimmune diseases. We found that most functional SNPs may affect target gene expression through altering transcription factors (TFs) binding, histone modification or chromatin accessibility. Most target genes had known immunological functions. We detected prevailing long-range chromatin interaction linking distal functional SNPs to target genes. We also identified many known drug targets and predicted some new drug target genes for several autoimmune diseases, suggesting their potential clinical applications. All analysis results and tools are available online, which may provide unique resource for future functional follow-up and drug application. Our study may help reduce the gap between traditional genetic findings and biological mechanistically exploration of disease etiologies as well as clinical drug development.

scholarly journals Type I Interferon and the Spectrum of Susceptibility to Viral Infection and Autoimmune Disease: A Shared Genomic Signature

2021 ◽  
Vol 12 ◽  
Author(s):  
Jamie A. Sugrue ◽  
Nollaig M. Bourke ◽  
Cliona O’Farrelly
Keyword(s):  
Autoimmune Disease ◽  
Viral Infection ◽  
Lupus Erythematosus ◽  
Molecular Mechanisms ◽  
Type I Interferons ◽  
Type I ◽  
Nucleotide Polymorphisms ◽  
Genetic Associations ◽  
Signalling Molecules ◽  
Resistance To Viral Infection

Type I interferons (IFN-I) and their cognate receptor, the IFNAR1/2 heterodimer, are critical components of the innate immune system in humans. They have been widely explored in the context of viral infection and autoimmune disease where they play key roles in protection against infection or shaping disease pathogenesis. A false dichotomy has emerged in the study of IFN-I where interferons are thought of as either beneficial or pathogenic. This ‘good or bad’ viewpoint excludes more nuanced interpretations of IFN-I biology - for example, it is known that IFN-I is associated with the development of systemic lupus erythematosus, yet is also protective in the context of infectious diseases and contributes to resistance to viral infection. Studies have suggested that a shared transcriptomic signature underpins both potential resistance to viral infection and susceptibility to autoimmune disease. This seems to be particularly evident in females, who exhibit increased viral resistance and increased susceptibility to autoimmune disease. The molecular mechanisms behind such a signature and the role of sex in its determination have yet to be precisely defined. From a genomic perspective, several single nucleotide polymorphisms (SNPs) in the IFN-I pathway have been associated with both infectious and autoimmune disease. While overlap between infection and autoimmunity has been described in the incidence of these SNPs, it has been overlooked in work and discussion to date. Here, we discuss the possible contributions of IFN-Is to the pathogenesis of infectious and autoimmune diseases. We comment on genetic associations between common SNPs in IFN-I or their signalling molecules that point towards roles in protection against viral infection and susceptibility to autoimmunity and propose that a shared transcriptomic and genomic immunological signature may underlie resistance to viral infection and susceptibility to autoimmunity in humans. We believe that defining shared transcriptomic and genomic immunological signatures underlying resistance to viral infection and autoimmunity in humans will reveal new therapeutic targets and improved vaccine strategies, particularly in females.

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