scholarly journals Distant regulatory effects of genetic variation in multiple human tissues

2016 ◽  
Author(s):  
Brian Jo ◽  
Yuan He ◽  
Benjamin J. Strober ◽  
Princy Parsana ◽  
François Aguet ◽  
...  
Keyword(s):  
Genetic Variation ◽  
Complex Traits ◽  
Disease Risk ◽  
Tissue Expression ◽  
Human Tissues ◽  
Sequencing Data ◽  
Cellular Mechanisms ◽  
Regulation Of Expression ◽  
Tissue Specific ◽  
Project Data

AbstractUnderstanding the genetics of gene regulation provides information on the cellular mechanisms through which genetic variation influences complex traits. Expression quantitative trait loci, or eQTLs, are enriched for polymorphisms that have been found to be associated with disease risk. While most analyses of human data has focused on regulation of expression by nearby variants (cis-eQTLs), distal or trans-eQTLs may have broader effects on the transcriptome and important phenotypic consequences, necessitating a comprehensive study of the effects of genetic variants on distal gene transcription levels. In this work, we identify trans-eQTLs in the Genotype Tissue Expression (GTEx) project data1, consisting of 449 individuals with RNA-sequencing data across 44 tissue types. We find 81 genes with a trans-eQTL in at least one tissue, and we demonstrate that trans-eQTLs are more likely than cis-eQTLs to have effects specific to a single tissue. We evaluate the genomic and functional properties of trans-eQTL variants, identifying strong enrichment in enhancer elements and Piwi-interacting RNA clusters. Finally, we describe three tissue-specific regulatory loci underlying relevant disease associations: 9q22 in thyroid that has a role in thyroid cancer, 5q31 in skeletal muscle, and a previously reported master regulator near KLF14 in adipose. These analyses provide a comprehensive characterization of trans-eQTLs across human tissues, which contribute to an improved understanding of the tissue-specific cellular mechanisms of regulatory genetic variation.

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 Tissue-specific sex differences in human gene expression

2019 ◽  
Vol 28 (17) ◽  
pp. 2976-2986 ◽  
Author(s):  
Irfahan Kassam ◽  
Yang Wu ◽  
Jian Yang ◽  
Peter M Visscher ◽  
Allan F McRae
Keyword(s):  
Gene Expression ◽  
Sex Differences ◽  
Complex Traits ◽  
Tissue Expression ◽  
Regulatory Elements ◽  
Tissue Specific ◽  
Significance Threshold ◽  
Expression Of Genes ◽  
Causal Variants ◽  
Similar Distance

Abstract Despite extensive sex differences in human complex traits and disease, the male and female genomes differ only in the sex chromosomes. This implies that most sex-differentiated traits are the result of differences in the expression of genes that are common to both sexes. While sex differences in gene expression have been observed in a range of different tissues, the biological mechanisms for tissue-specific sex differences (TSSDs) in gene expression are not well understood. A total of 30 640 autosomal and 1021 X-linked transcripts were tested for heterogeneity in sex difference effect sizes in n = 617 individuals across 40 tissue types in Genotype–Tissue Expression (GTEx). This identified 65 autosomal and 66 X-linked TSSD transcripts (corresponding to unique genes) at a stringent significance threshold. Results for X-linked TSSD transcripts showed mainly concordant direction of sex differences across tissues and replicate previous findings. Autosomal TSSD transcripts had mainly discordant direction of sex differences across tissues. The top cis-expression quantitative trait loci (eQTLs) across tissues for autosomal TSSD transcripts are located a similar distance away from the nearest androgen and estrogen binding motifs and the nearest enhancer, as compared to cis-eQTLs for transcripts with stable sex differences in gene expression across tissue types. Enhancer regions that overlap top cis-eQTLs for TSSD transcripts, however, were found to be more dispersed across tissues. These observations suggest that androgen and estrogen regulatory elements in a cis region may play a common role in sex differences in gene expression, but TSSD in gene expression may additionally be due to causal variants located in tissue-specific enhancer regions.

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 Genetic Architecture of Complex Traits and Disease Risk Predictors

2020 ◽  
Author(s):  
Soke Yuen Yong ◽  
Timothy G. Raben ◽  
Louis Lello ◽  
Stephen D.H. Hsu
Keyword(s):  
Genetic Variants ◽  
Complex Traits ◽  
Genetic Architecture ◽  
Disease Risk ◽  
Sequencing Data ◽  
Exome Data ◽  
Coding Regions ◽  
Disease Risks ◽  
Risk Predictors ◽  
Complex Human Traits

AbstractGenomic prediction of complex human traits (e.g., height, cognitive ability, bone density) and disease risks (e.g., breast cancer, diabetes, heart disease, atrial fibrillation) has advanced considerably in recent years. Predictors have been constructed using penalized algorithms that favor sparsity: i.e., which use as few genetic variants as possible. We analyze the specific genetic variants (SNPs) utilized in these predictors, which can vary from dozens to as many as thirty thousand. We find that the fraction of SNPs in or near genic regions varies widely by phenotype. For the majority of disease conditions studied, a large amount of the variance is accounted for by SNPs outside of coding regions. The state of these SNPs cannot be determined from exome-sequencing data. This suggests that exome data alone will miss much of the heritability for these traits – i.e., existing PRS cannot be computed from exome data alone. We also study the fraction of SNPs and of variance that is in common between pairs of predictors. The DNA regions used in disease risk predictors so far constructed seem to be largely disjoint (with a few interesting exceptions), suggesting that individual genetic disease risks are largely uncorrelated. It seems possible in theory for an individual to be a low-risk outlier in all conditions simultaneously.

scholarly journals An integrated personal and population-based Egyptian genome reference

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Inken Wohlers ◽  
Axel Künstner ◽  
Matthias Munz ◽  
Michael Olbrich ◽  
Anke Fähnrich ◽  
...  
Keyword(s):  
Genetic Variation ◽  
De Novo ◽  
Disease Risk ◽  
Population Based ◽  
European Ancestry ◽  
Whole Genome Sequencing Data ◽  
Sequencing Data ◽  
Human Genomes ◽  
Genome Wide ◽  
Polygenic Scores

Abstract A small number of de novo assembled human genomes have been reported to date, and few have been complemented with population-based genetic variation, which is particularly important for North Africa, a region underrepresented in current genome-wide references. Here, we combine long- and short-read whole-genome sequencing data with recent assembly approaches into a de novo assembly of an Egyptian genome. The assembly demonstrates well-balanced quality metrics and is complemented with variant phasing via linked reads into haploblocks, which we associate with gene expression changes in blood. To construct an Egyptian genome reference, we identify genome-wide genetic variation within a cohort of 110 Egyptian individuals. We show that differences in allele frequencies and linkage disequilibrium between Egyptians and Europeans may compromise the transferability of European ancestry-based genetic disease risk and polygenic scores, substantiating the need for multi-ethnic genome references. Thus, the Egyptian genome reference will be a valuable resource for precision medicine.

scholarly journals Incomplete annotation has a disproportionate impact on our understanding of Mendelian and complex neurogenetic disorders

2020 ◽  
Vol 6 (24) ◽  
pp. eaay8299 ◽  
Author(s):  
David Zhang ◽  
Sebastian Guelfi ◽  
Sonia Garcia-Ruiz ◽  
Beatrice Costa ◽  
Regina H. Reynolds ◽  
...  
Keyword(s):  
Human Gene ◽  
Gene Annotation ◽  
Tissue Expression ◽  
Mendelian Inheritance ◽  
Disease Genes ◽  
Human Tissues ◽  
Sequencing Data ◽  
Protein Coding ◽  
Neurogenetic Disorders ◽  
Different Tissues

Growing evidence suggests that human gene annotation remains incomplete; however, it is unclear how this affects different tissues and our understanding of different disorders. Here, we detect previously unannotated transcription from Genotype-Tissue Expression RNA sequencing data across 41 human tissues. We connect this unannotated transcription to known genes, confirming that human gene annotation remains incomplete, even among well-studied genes including 63% of the Online Mendelian Inheritance in Man–morbid catalog and 317 neurodegeneration-associated genes. We find the greatest abundance of unannotated transcription in brain and genes highly expressed in brain are more likely to be reannotated. We explore examples of reannotated disease genes, such as SNCA, for which we experimentally validate a previously unidentified, brain-specific, potentially protein-coding exon. We release all tissue-specific transcriptomes through vizER: http://rytenlab.com/browser/app/vizER. We anticipate that this resource will facilitate more accurate genetic analysis, with the greatest impact on our understanding of Mendelian and complex neurogenetic disorders.

scholarly journals Local genetic effects on gene expression across 44 human tissues

2016 ◽  
Author(s):  
François Aguet ◽  
Andrew A. Brown ◽  
Stephane E. Castel ◽  
Joe R. Davis ◽  
Pejman Mohammadi ◽  
...  
Keyword(s):  
Gene Expression ◽  
Complex Traits ◽  
Large Scale ◽  
Genetic Diseases ◽  
Tissue Expression ◽  
Specific Expression ◽  
Tissue Specific ◽  
Regulatory Variation ◽  
Functional Variants ◽  
Trait Locus

AbstractExpression quantitative trait locus (eQTL) mapping provides a powerful means to identify functional variants influencing gene expression and disease pathogenesis. We report the identification of cis-eQTLs from 7,051 post-mortem samples representing 44 tissues and 449 individuals as part of the Genotype-Tissue Expression (GTEx) project. We find a cis-eQTL for 88% of all annotated protein-coding genes, with one-third having multiple independent effects. We identify numerous tissue-specific cis-eQTLs, highlighting the unique functional impact of regulatory variation in diverse tissues. By integrating large-scale functional genomics data and state-of-the-art fine-mapping algorithms, we identify multiple features predictive of tissue-specific and shared regulatory effects. We improve estimates of cis-eQTL sharing and effect sizes using allele specific expression across tissues. Finally, we demonstrate the utility of this large compendium of cis-eQTLs for understanding the tissue-specific etiology of complex traits, including coronary artery disease. The GTEx project provides an exceptional resource that has improved our understanding of gene regulation across tissues and the role of regulatory variation in human genetic diseases.

scholarly journals Adhesion GPCR GPR56 Expression Profiling in Human Tissues

Cells ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 3557
Author(s):  
Fyn Kaiser ◽  
Markus Morawski ◽  
Knut Krohn ◽  
Nada Rayes ◽  
Cheng-Chih Hsiao ◽  
...  
Keyword(s):  
Specific Binding ◽  
Tissue Expression ◽  
Adult Brain ◽  
Human Tissues ◽  
Sequencing Data ◽  
Physiological Processes ◽  
Pepsinogen A ◽  
The Central Nervous System ◽  
Functional Relevance ◽  
Adhesion Gpcr

Despite the immense functional relevance of GPR56 (gene ADGRG1) in highly diverse (patho)physiological processes such as tumorigenesis, immune regulation, and brain development, little is known about its exact tissue localization. Here, we validated antibodies for GPR56-specific binding using cells with tagged GPR56 or eliminated ADGRG1 in immunotechniques. Using the most suitable antibody, we then established the human GPR56 tissue expression profile. Overall, ADGRG1 RNA-sequencing data of human tissues and GPR56 protein expression correlate very well. In the adult brain especially, microglia are GPR56-positive. Outside the central nervous system, GPR56 is frequently expressed in cuboidal or highly prismatic secreting epithelia. High ADGRG1 mRNA, present in the thyroid, kidney, and placenta is related to elevated GPR56 in thyrocytes, kidney tubules, and the syncytiotrophoblast, respectively. GPR56 often appears in association with secreted proteins such as pepsinogen A in gastric chief cells and insulin in islet β-cells. In summary, GPR56 shows a broad, not cell-type restricted expression in humans.

scholarly journals Genetic variation and microRNA targeting of A-to-I RNA editing fine tune human tissue transcriptomes

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Eddie Park ◽  
Yan Jiang ◽  
Lili Hao ◽  
Jingyi Hui ◽  
Yi Xing
Keyword(s):  
Genetic Variation ◽  
Quantitative Trait Loci ◽  
Rna Editing ◽  
Quantitative Trait ◽  
Complex Traits ◽  
Expression Profiles ◽  
Phenotypic Variability ◽  
Tissue Specific ◽  
Specific Manner ◽  
Trait Loci

Abstract Background A-to-I RNA editing diversifies the transcriptome and has multiple downstream functional effects. Genetic variation contributes to RNA editing variability between individuals and has the potential to impact phenotypic variability. Results We analyze matched genetic and transcriptomic data in 49 tissues across 437 individuals to identify RNA editing events that are associated with genetic variation. Using an RNA editing quantitative trait loci (edQTL) mapping approach, we identify 3117 unique RNA editing events associated with a cis genetic polymorphism. Fourteen percent of these edQTL events are also associated with genetic variation in their gene expression. A subset of these events are associated with genome-wide association study signals of complex traits or diseases. We determine that tissue-specific levels of ADAR and ADARB1 are able to explain a subset of tissue-specific edQTL events. We find that certain microRNAs are able to differentiate between the edited and unedited isoforms of their targets. Furthermore, microRNAs can generate an expression quantitative trait loci (eQTL) signal from an edQTL locus by microRNA-mediated transcript degradation in an editing-specific manner. By integrative analyses of edQTL, eQTL, and microRNA expression profiles, we computationally discover and experimentally validate edQTL-microRNA pairs for which the microRNA may generate an eQTL signal from an edQTL locus in a tissue-specific manner. Conclusions Our work suggests a mechanism in which RNA editing variability can influence the phenotypes of complex traits and diseases by altering the stability and steady-state level of critical RNA molecules.

Epigenomic Profiling and Single-Nucleus-RNA-Seq Reveal Cis-Regulatory Elements in Human Retina, Macula and RPE and Non-Coding Genetic Variation

2018 ◽  
Author(s):  
Timothy J. Cherry ◽  
Marty G. Yang ◽  
David A. Harmin ◽  
Peter Tao ◽  
Andrew E. Timms ◽  
...  
Keyword(s):  
Gene Expression ◽  
Genetic Variation ◽  
Complex Traits ◽  
Retinal Pigment ◽  
Regulatory Elements ◽  
Human Vision ◽  
Specific Gene ◽  
Tissue Specific ◽  
Complex Disorders ◽  
Regulatory Variation

ABSTRACTCis-regulatory elements (CREs) orchestrate the dynamic and diverse transcriptional programs that assemble the human central nervous system (CNS) during development and maintain its function throughout life. Genetic variation within CREs plays a central role in phenotypic variation in complex traits including the risk of developing disease. However, the cellular complexity of the human brain has largely precluded the identification of functional regulatory variation within the human CNS. We took advantage of the retina, a well-characterized region of the CNS with reduced cellular heterogeneity, to establish a roadmap for characterizing regulatory variation in the human CNS. This comprehensive resource of tissue-specific regulatory elements, transcription factor binding, and gene expression programs in three regions of the human visual system (retina, macula, retinal pigment epithelium/choroid) reveals features of regulatory element evolution that shape tissue-specific gene expression programs and defines the regulatory elements with the potential to contribute to mendelian and complex disorders of human vision.

Sign in / Sign up

Export Citation Format

Share Document