scholarly journals Cell-type specific eQTL of primary melanocytes facilitates identification of melanoma susceptibility genes

2017 ◽  
Author(s):  
Tongwu Zhang ◽  
Jiyeon Choi ◽  
Michael A. Kovacs ◽  
Jianxin Shi ◽  
Mai Xu ◽  
...  

ABSTRACTMost expression quantitative trait loci (eQTL) studies to date have been performed in heterogeneous tissues as opposed to specific cell types. To better understand the cell-type specific regulatory landscape of human melanocytes, which give rise to melanoma but account for <5% of typical human skin biopsies, we performed an eQTL analysis in primary melanocyte cultures from 106 newborn males. We identified 597,335 cis-eQTL SNPs prior to LD-pruning and 4,997 eGenes (FDR<0.05), which are higher numbers than in any GTEx tissue type with a similar sample size. Melanocyte eQTLs differed considerably from those identified in the 44 GTEx tissues, including skin. Over a third of melanocyte eGenes, including key genes in melanin synthesis pathways, were not observed to be eGenes in two types of GTEx skin tissues or TCGA melanoma samples. The melanocyte dataset also identified cell-type specific trans-eQTLs with a pigmentation-associated SNP for four genes, likely through its cis-regulation of IRF4, encoding a transcription factor implicated in human pigmentation phenotypes. Melanocyte eQTLs are enriched in cis-regulatory signatures found in melanocytes as well as melanoma-associated variants identified through genome-wide association studies (GWAS). Co-localization of melanoma GWAS variants and eQTLs from melanocyte and skin eQTL datasets identified candidate melanoma susceptibility genes for six known GWAS loci including unique genes identified by the melanocyte dataset. Further, a transcriptome-wide association study using published melanoma GWAS data uncovered four new loci, where imputed expression levels of five genes (ZFP90, HEBP1, MSC, CBWD1, and RP11-383H13.1) were associated with melanoma at genome-wide significant P-values. Our data highlight the utility of lineage-specific eQTL resources for annotating GWAS findings and present a robust database for genomic research of melanoma risk and melanocyte biology.

2015 ◽  
Author(s):  
Hilary Kiyo Finucane ◽  
Brendan Bulik-Sullivan ◽  
Alexander Gusev ◽  
Gosia Trynka ◽  
Yakir Reshef ◽  
...  

Recent work has demonstrated that some functional categories of the genome contribute disproportionately to the heritability of complex diseases. Here, we analyze a broad set of functional elements, including cell-type-specific elements, to estimate their polygenic contributions to heritability in genome-wide association studies (GWAS) of 17 complex diseases and traits spanning a total of 1.3 million phenotype measurements. To enable this analysis, we introduce a new method for partitioning heritability from GWAS summary statistics while controlling for linked markers. This new method is computationally tractable at very large sample sizes, and leverages genome-wide information. Our results include a large enrichment of heritability in conserved regions across many traits; a very large immunological disease-specific enrichment of heritability in FANTOM5 enhancers; and many cell-type-specific enrichments including significant enrichment of central nervous system cell types in body mass index, age at menarche, educational attainment, and smoking behavior. These results demonstrate that GWAS can aid in understanding the biological basis of disease and provide direction for functional follow-up.


2021 ◽  
Author(s):  
Rujin Wang ◽  
Danyu Lin ◽  
Yuchao Jiang

More than a decade of genome-wide association studies (GWASs) have identified genetic risk variants that are significantly associated with complex traits. Emerging evidence suggests that the function of trait-associated variants likely acts in a tissue- or cell-type-specific fashion. Yet, it remains challenging to prioritize trait-relevant tissues or cell types to elucidate disease etiology. Here, we present EPIC (cEll tyPe enrIChment), a statistical framework that relates large-scale GWAS summary statistics to cell-type-specific omics measurements from single-cell sequencing. We derive powerful gene-level test statistics for common and rare variants, separately and jointly, and adopt generalized least squares to prioritize trait-relevant tissues or cell types while accounting for the correlation structures both within and between genes. Using enrichment of loci associated with four lipid traits in the liver and enrichment of loci associated with three neurological disorders in the brain as ground truths, we show that EPIC outperforms existing methods. We extend our framework to single-cell transcriptomic data and identify cell types underlying type 2 diabetes and schizophrenia. The enrichment is replicated using independent GWAS and single-cell datasets and further validated using PubMed search and existing bulk case-control testing results.


2021 ◽  
pp. gr.275723.121
Author(s):  
Jill E Moore ◽  
Xiao-Ou Zhang ◽  
Shaimae I Elhajjajy ◽  
Kaili Fan ◽  
Henry E Pratt ◽  
...  

Accurate transcription start site (TSS) annotations are essential for understanding transcriptional regulation and its role in human disease. Gene collections such as GENCODE contain annotations for tens of thousands of TSSs, but not all of these annotations are experimentally validated, nor do they contain information on cell type-specific usage. Therefore, we sought to generate a collection of experimentally validated TSSs by integrating RNA Annotation and Mapping of Promoters for the Analysis of Gene Expression (RAMPAGE) data from 115 cell and tissue types, which resulted in a collection of approximately 50 thousand representative RAMPAGE peaks. These peaks were primarily proximal to GENCODE-annotated TSSs and were concordant with other transcription assays. Because RAMPAGE uses paired-end reads, we were then able to connect peaks to transcripts by analyzing the genomic positions of the 3' ends of read mates. Using this paired-end information, we classified the vast majority (37 thousand) of our RAMPAGE peaks as verified TSSs, updating TSS annotations for 20% of GENCODE genes. We also found that these updated TSS annotations were supported by epigenomic and other transcriptomic datasets. To demonstrate the utility of this RAMPAGE rPeak collection, we intersected it with the NHGRI/EBI genome-wide association studies (GWAS) catalog and identified new candidate GWAS genes. Overall, our work demonstrates the importance of integrating experimental data to further refine TSS annotations and provides a valuable resource for the biological community.


2021 ◽  
Author(s):  
Tongwu Zhang ◽  
Jiyeon Choi ◽  
Ramile Dilshat ◽  
Berglind Ósk Einarsdóttir ◽  
Michael A Kovacs ◽  
...  

AbstractWhile expression quantitative trait loci (eQTL) have been powerful in identifying susceptibility genes from genome-wide association studies (GWAS) findings, most trait-associated loci are not explained by eQTL alone. Alternative QTLs including DNA methylation QTL (meQTL) are emerging, but cell-type-specific meQTL using cells of disease origin has been lacking. Here we established an meQTL dataset using primary melanocytes from 106 individuals and identified 1,497,502 significant cis-meQTLs. Multi-QTL colocalization using meQTL, eQTL, and mRNA splice-junction QTL from the same individuals together with imputed methylome-wide and transcriptome-wide association studies identified susceptibility genes at 63% of melanoma GWAS loci. Among three molecular QTLs, meQTLs were the single largest contributor. To compare melanocyte meQTLs with those from malignant melanomas, we performed meQTL analysis on skin cutaneous melanomas from The Cancer Genome Atlas (n = 444). A substantial proportion of meQTL probes (45.9%) in primary melanocytes are preserved in melanomas, while a smaller fraction of eQTL genes is preserved (12.7%). Integration of melanocyte multi-QTL and melanoma meQTL identified candidate susceptibility genes at 72% of melanoma GWAS loci. Beyond GWAS annotation, meQTL-eQTL colocalization in melanocytes suggested that 841 unique genes potentially share a causal variant with a nearby methylation probe in melanocytes. Finally, melanocyte trans-meQTL identified a hotspot for rs12203592, a cis-eQTL of a transcription factor, IRF4, with 131 candidate target CpGs. Motif enrichment and IRF4 ChIPseq analysis demonstrated that these target CpGs are enriched in IRF4 binding sites, suggesting an IRF4-mediated regulatory network. Our study highlights the utility of cell-type-specific meQTL.


2021 ◽  
Vol 41 (1) ◽  
Author(s):  
Kyuto Sonehara ◽  
Yukinori Okada

AbstractGenome-wide association studies have identified numerous disease-susceptibility genes. As knowledge of gene–disease associations accumulates, it is becoming increasingly important to translate this knowledge into clinical practice. This challenge involves finding effective drug targets and estimating their potential side effects, which often results in failure of promising clinical trials. Here, we review recent advances and future perspectives in genetics-led drug discovery, with a focus on drug repurposing, Mendelian randomization, and the use of multifaceted omics data.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jamie W. Robinson ◽  
Richard M. Martin ◽  
Spiridon Tsavachidis ◽  
Amy E. Howell ◽  
Caroline L. Relton ◽  
...  

AbstractGenome-wide association studies (GWAS) have discovered 27 loci associated with glioma risk. Whether these loci are causally implicated in glioma risk, and how risk differs across tissues, has yet to be systematically explored. We integrated multi-tissue expression quantitative trait loci (eQTLs) and glioma GWAS data using a combined Mendelian randomisation (MR) and colocalisation approach. We investigated how genetically predicted gene expression affects risk across tissue type (brain, estimated effective n = 1194 and whole blood, n = 31,684) and glioma subtype (all glioma (7400 cases, 8257 controls) glioblastoma (GBM, 3112 cases) and non-GBM gliomas (2411 cases)). We also leveraged tissue-specific eQTLs collected from 13 brain tissues (n = 114 to 209). The MR and colocalisation results suggested that genetically predicted increased gene expression of 12 genes were associated with glioma, GBM and/or non-GBM risk, three of which are novel glioma susceptibility genes (RETREG2/FAM134A, FAM178B and MVB12B/FAM125B). The effect of gene expression appears to be relatively consistent across glioma subtype diagnoses. Examining how risk differed across 13 brain tissues highlighted five candidate tissues (cerebellum, cortex, and the putamen, nucleus accumbens and caudate basal ganglia) and four previously implicated genes (JAK1, STMN3, PICK1 and EGFR). These analyses identified robust causal evidence for 12 genes and glioma risk, three of which are novel. The correlation of MR estimates in brain and blood are consistently low which suggested that tissue specificity needs to be carefully considered for glioma. Our results have implicated genes yet to be associated with glioma susceptibility and provided insight into putatively causal pathways for glioma risk.


2020 ◽  
Vol 29 (11) ◽  
pp. 1922-1932
Author(s):  
Priyanka Nandakumar ◽  
Dongwon Lee ◽  
Thomas J Hoffmann ◽  
Georg B Ehret ◽  
Dan Arking ◽  
...  

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.


2019 ◽  
Vol 116 (37) ◽  
pp. 18710-18716 ◽  
Author(s):  
Ana Milhinhos ◽  
Francisco Vera-Sirera ◽  
Noel Blanco-Touriñán ◽  
Cristina Mari-Carmona ◽  
Àngela Carrió-Seguí ◽  
...  

In plants, secondary growth results in radial expansion of stems and roots, generating large amounts of biomass in the form of wood. Using genome-wide association studies (GWAS)-guided reverse genetics inArabidopsis thaliana, we discoveredSOBIR1/EVR, previously known to control plant immunoresponses and abscission, as a regulator of secondary growth. We present anatomical, genetic, and molecular evidence indicating that SOBIR1/EVR prevents the precocious differentiation of xylem fiber, a key cell type for wood development. SOBIR1/EVR acts through a mechanism that involves BREVIPEDICELLUS (BP) and ERECTA (ER), 2 proteins previously known to regulate xylem fiber development. We demonstrate that BP bindsSOBIR1/EVRpromoter and thatSOBIR1/EVRexpression is enhanced inbpmutants, suggesting a direct, negative regulation of BP overSOBIR1/EVRexpression. We show that SOBIR1/EVR physically interacts with ER and that defects caused by thesobir1/evrmutation are aggravated by mutatingER, indicating that SOBIR1/EVR and ERECTA act together in the control of the precocious formation of xylem fiber development.


2019 ◽  
Vol 29 (3) ◽  
pp. 513-516 ◽  
Author(s):  
Megan C. Roberts ◽  
Muin J. Khoury ◽  
George A. Mensah

Polygenic risk scores (PRS) are an emerging precision medicine tool based on multiple gene variants that, taken alone, have weak associations with disease risks, but collec­tively may enhance disease predictive value in the population. However, the benefit of PRS may not be equal among non-European populations, as they are under-represented in genome-wide association studies (GWAS) that serve as the basis for PRS develop­ment. In this perspective, we discuss a path forward, which includes: 1) inclusion of underrepresented populations in PRS research; 2) global efforts to build capacity for genomic research; 3) equitable imple­mentation of these tools in clinical practice; and 4) traditional public health approaches to reduce risk of adverse health outcomes as an important component to precision health. As precision medicine is imple­mented in clinical care, researchers must ensure that advances from PRS research will benefit all.Ethn Dis.2019;29(3):513-516; doi:10.18865/ed.29.3.513.


Sign in / Sign up

Export Citation Format

Share Document