Functional variants in hematopoietic transcription factor footprints and their roles in the risk of immune system diseases

Kubota, Naoto; Suyama, Mikita

doi:10.1101/2021.03.22.436360

Cited by 3 publications

(3 citation statements)

References 65 publications

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“…For instance, it is known that GTEx tissue eVariants are enriched in cis-regulatory elements (CREs) in relevant cell types, and eVariants with higher posterior causal probabilities are more likely to fall into tissue-matched DHSs (31). Thus, when investigating eQTL mechanisms, researchers can choose to focus on eVariants that fall into CREs, DHSs, and transcription factor binding sites in the relevant cell types (6,8,151). For environmental and immune response eQTLs, researchers may narrow their scope further by focusing on eVariants in genomic annotations for treatment-responsive transcription factors, such as STAT and IRF transcription factors, and on immune response eQTLs in dendritic cells (144).…”

Section: Using Context Specificity To Inform Expression Quantitative ...mentioning

confidence: 99%

Functional Characterization of Genetic Variant Effects on Expression

Flynn

Lappalainen

2022

Annu. Rev. Biomed. Data Sci.

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Thousands of common genetic variants in the human population have been associated with disease risk and phenotypic variation by genome-wide association studies (GWAS). However, the majority of GWAS variants fall into noncoding regions of the genome, complicating our understanding of their regulatory functions, and few molecular mechanisms of GWAS variant effects have been clearly elucidated. Here, we set out to review genetic variant effects, focusing on expression quantitative trait loci (eQTLs), including their utility in interpreting GWAS variant mechanisms. We discuss the interrelated challenges and opportunities for eQTL analysis, covering determining causal variants, elucidating molecular mechanisms of action, and understanding context variability. Addressing these questions can enable better functional characterization of disease-associated loci and provide insights into fundamental biological questions of the noncoding genetic regulatory code and its control of gene expression.

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Section: Using Context Specificity To Inform Expression Quantitative ...mentioning

confidence: 99%

Functional Characterization of Genetic Variant Effects on Expression

Flynn

Lappalainen

2022

Annu. Rev. Biomed. Data Sci.

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“…The first obstacle lies in identifying the causal variant(s) of a locus from the typically numerous associated variants in high linkage disequilibrium (LD). Putatively functional variants can be pinpointed by statistical fine-mapping approaches, complemented with genomic annotations such as regions of open chromatin, TF binding sites predicted by motifs, or allele-specific binding of TF ChIP-seq data [5,[16][17][18][19]. However, these annotations suffer from both low specificity and low sensitivity.…”

Section: Introductionmentioning

confidence: 99%

Transcription factor regulation of eQTL activity across individuals and tissues

et al. 2022

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Tens of thousands of genetic variants associated with gene expression (cis-eQTLs) have been discovered in the human population. These eQTLs are active in various tissues and contexts, but the molecular mechanisms of eQTL variability are poorly understood, hindering our understanding of genetic regulation across biological contexts. Since many eQTLs are believed to act by altering transcription factor (TF) binding affinity, we hypothesized that analyzing eQTL effect size as a function of TF level may allow discovery of mechanisms of eQTL variability. Using GTEx Consortium eQTL data from 49 tissues, we analyzed the interaction between eQTL effect size and TF level across tissues and across individuals within specific tissues and generated a list of 10,098 TF-eQTL interactions across 2,136 genes that are supported by at least two lines of evidence. These TF-eQTLs were enriched for various TF binding measures, supporting with orthogonal evidence that these eQTLs are regulated by the implicated TFs. We also found that our TF-eQTLs tend to overlap genes with gene-by-environment regulatory effects and to colocalize with GWAS loci, implying that our approach can help to elucidate mechanisms of context-specificity and trait associations. Finally, we highlight an interesting example of IKZF1 TF regulation of an APBB1IP gene eQTL that colocalizes with a GWAS signal for blood cell traits. Together, our findings provide candidate TF mechanisms for a large number of eQTLs and offer a generalizable approach for researchers to discover TF regulators of genetic variant effects in additional QTL datasets.

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Section: Introductionmentioning

confidence: 99%

Transcription factor regulation of eQTL activity across individuals and tissues

Flynn

Tsu

Kasela

et al. 2021

Preprint

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Tens of thousands of genetic variants associated with gene expression ( cis -eQTLs) have been discovered in the human population. These eQTLs are active in various tissues and contexts, but the molecular mechanisms of eQTL variability are poorly understood, hindering our understanding of genetic regulation across biological contexts. Since many eQTLs are believed to act by altering transcription factor (TF) binding affinity, we hypothesized that analyzing eQTL effect size as a function of TF level may allow discovery of mechanisms of eQTL variability. Using GTEx Consortium eQTL data from 49 tissues, we analyzed the interaction between eQTL effect size and TF level across tissues and across individuals within specific tissues and generated a list of 6,262 TF-eQTL interactions across 1,598 genes that are supported by at least two lines of evidence. These TF-eQTLs were enriched for various TF binding measures, supporting with orthogonal evidence that these eQTLs are regulated by the implicated TFs. We also found that our TF-eQTLs tend to overlap genes with gene-by-environment regulatory effects and to colocalize with GWAS loci, implying that our approach can help to elucidate mechanisms of context-specificity and trait associations. Finally, we highlight an interesting example of IKZF1 TF regulation of an APBB1IP gene eQTL that colocalizes with a GWAS signal for blood cell traits. Together, our findings provide candidate TF mechanisms for a large number of eQTLs and offer a generalizable approach for researchers to discover TF regulators of genetic variant effects in additional QTL datasets.

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Functional variants in hematopoietic transcription factor footprints and their roles in the risk of immune system diseases

Cited by 3 publications

References 65 publications

Functional Characterization of Genetic Variant Effects on Expression

Functional Characterization of Genetic Variant Effects on Expression

Transcription factor regulation of eQTL activity across individuals and tissues

Transcription factor regulation of eQTL activity across individuals and tissues

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