Predicting causal variants affecting expression by using whole-genome sequencing and RNA-seq from multiple human tissues

Brown, Andrew Anand; Viñuela, Ana; Delaneau, Olivier; Spector, Tim D.; Small, Kerrin S.; Dermitzakis, Emmanouil T.

doi:10.1038/ng.3979

Cited by 98 publications

(85 citation statements)

References 57 publications

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“…However, even within a cell or tissue type, such data are often mutually discordant: one study examining six epigenomic datasets in K562 cells found that 49% of functional regulators did not overlap any of the six annotation sets, and another 40% only overlapped one of the six (11). Similarly, the Roadmap Epigenomics Consortium (12) inferred cell type-specific regulatory elements using chromatin marks, but only a minority of GWAS SNPs overlap these elements (except in blood) (13). Therefore, epigenomic data alone are inadequate for predicting functional regulatory variants in a given cell type.…”

Section: Challenges In Predicting a Variant's Functional Consequencesmentioning

confidence: 99%

The Oft-Overlooked Massively Parallel Reporter Assay: Where, When, and Which Psychiatric Genetic Variants are Functional?

Mulvey¹,

Lagunas²,

Dougherty³

2020

Preprint

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Neuropsychiatric phenotypes have been long known to be influenced by heritable risk factors. The past decade of genetic studies have confirmed this directly, revealing specific common and rare genetic variants enriched in disease cohorts. However, the early hope for these studies-that only a small set of genes would be responsible for a given disorder-proved false. The picture that has emerged is far more complex: a given disorder may be influenced by myriad coding and noncoding variants of small effect size, and/or by rare but severe variants of large effect size, many de novo.Noncoding genomic sequences harbor a large portion of these variants, the molecular functions of which cannot usually be inferred from sequence alone. This creates a substantial barrier to understanding the higher-order molecular and biological systems underlying disease risk. Fortunately, a proliferation of genetic technologies-namely, scalable oligonucleotide synthesis, high-throughput RNA sequencing, CRISPR, and CRISPR derivatives-have opened novel avenues to experimentally identify biologically significant variants en masse. These advances have yielded an especially versatile technique adaptable to large-scale functional assays of variation in both untranscribed and untranslated regulatory features: Massively Parallel Reporter Assays (MPRAs). MPRAs are powerful molecular genetic tools that can be used to screen tens of thousands of predefined sequences for functional effects in a single experiment. This approach has several ideal features for psychiatric genetics, but remains underutilized in the field to date. To emphasize the opportunities MPRA holds for dissecting psychiatric polygenicity, we review here its applications in the literature, discuss its ability to test several biological variables implicated in psychiatric disorders, illustrate this flexibility with a proof-of-principle, in vivo cell-type specific implementation of the assay, and envision future outcomes of applying MPRA to both computational and experimental neurogenetics.

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Section: Challenges In Predicting a Variant's Functional Consequencesmentioning

confidence: 99%

The Oft-Overlooked Massively Parallel Reporter Assay: Where, When, and Which Psychiatric Genetic Variants are Functional?

Mulvey¹,

Lagunas²,

Dougherty³

2020

Preprint

View full text Add to dashboard Cite

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“…To discover multiple independent eQTLs, we applied a stepwise regression procedure as described in Brown et al 75 . Briefly, we started from the set of eGenes discovered in the first pass of association analysis (FDR < 1%).…”

Section: Rnaseq Quality Assessment and Data Normalizationmentioning

confidence: 99%

Influence of genetic variants on gene expression in human pancreatic islets – implications for type 2 diabetes

Viñuela

Varshney

Bunt

et al. 2019

Preprint

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Most signals detected by genome-wide association studies map to non-coding sequence and their tissue-specific effects influence transcriptional regulation. However, many key tissues and cell-types required for appropriate functional inference are absent from large-scale resources such as ENCODE and GTEx. We explored the relationship between genetic variants influencing predisposition to type 2 diabetes (T2D) and related glycemic traits, and human pancreatic islet transcription using RNA-Seq and genotyping data from 420 islet donors. We find: (a) eQTLs have a variable replication rate across the 44 GTEx tissues (<73%), indicating that our study captured islet-specific cis-eQTL signals; (b) islet eQTL signals show marked overlap with islet epigenome annotation, though eQTL effect size is reduced in the stretch enhancers most strongly implicated in GWAS signal location; (c) selective enrichment of islet eQTL overlap with the subset of T2D variants implicated in islet dysfunction; and (d) colocalization between islet eQTLs and variants influencing T2D or related glycemic traits, delivering candidate effector transcripts at 23 loci, including DGKB and TCF7L2. Our findings illustrate the advantages of performing functional and regulatory studies in tissues of greatest disease-relevance while expanding our mechanistic insights into complex traits association loci activity with an expanded list of putative transcripts implicated in T2D development.

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“…An association with species-specific OCRs and expression changes would support that the state changes are biologically relevant. To measure association with expression changes, we compared to known human adipose expression quantitative trait loci (eQTL) (18).…”

Section: Species-specific Ocr States Correlate With Cis-regulatory DImentioning

confidence: 99%

Comparative analyses of chromatin landscape in white adipose tissue suggest humans may have less beigeing potential than other primates

Swain-Lenz

Berrío

Safi

et al. 2019

Preprint

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Humans carry a much larger percentage of body fat than other primates. Despite the central role of adipose tissue in metabolism, little is known about the evolution of white adipose tissue in primates. Phenotypic divergence is often caused by genetic divergence in cis-regulatory regions. We examined the cis-regulatory landscape of fat during human origins by performing comparative analyses of chromatin accessibility in human and chimpanzee adipose tissue using macaque as an outgroup. We find that many cis-regulatory regions that are specifically closed in humans are under positive selection, located near genes involved with lipid metabolism, and contain a short sequence motif involved in the beigeing of fat, the process in which white adipocytes are transdifferentiated into beige adipocytes. While the primary role of white adipocytes is to store lipids, beige adipocytes are thermogeneic. The collective closing of many putative regulatory regions associated with beiging of fat suggests an adaptive mechanism that increases body fat in humans.

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Predicting causal variants affecting expression by using whole-genome sequencing and RNA-seq from multiple human tissues

Cited by 98 publications

References 57 publications

The Oft-Overlooked Massively Parallel Reporter Assay: Where, When, and Which Psychiatric Genetic Variants are Functional?

The Oft-Overlooked Massively Parallel Reporter Assay: Where, When, and Which Psychiatric Genetic Variants are Functional?

Influence of genetic variants on gene expression in human pancreatic islets – implications for type 2 diabetes

Comparative analyses of chromatin landscape in white adipose tissue suggest humans may have less beigeing potential than other primates

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