@article {99, title = {Cell type-specific genetic regulation of gene expression across human tissues.}, journal = {Science}, volume = {369}, year = {2020}, month = {2020 09 11}, abstract = {

The Genotype-Tissue Expression (GTEx) project has identified expression and splicing quantitative trait loci in cis (QTLs) for the majority of genes across a wide range of human tissues. However, the functional characterization of these QTLs has been limited by the heterogeneous cellular composition of GTEx tissue samples. We mapped interactions between computational estimates of cell type abundance and genotype to identify cell type-interaction QTLs for seven cell types and show that cell type-interaction expression QTLs (eQTLs) provide finer resolution to tissue specificity than bulk tissue cis-eQTLs. Analyses of genetic associations with 87 complex traits show a contribution from cell type-interaction QTLs and enables the discovery of hundreds of previously unidentified colocalized loci that are masked in bulk tissue.

}, keywords = {Cells, Gene Expression Regulation, Humans, Organ Specificity, Quantitative Trait Loci, RNA, Long Noncoding, Transcriptome}, issn = {1095-9203}, doi = {10.1126/science.aaz8528}, author = {Kim-Hellmuth, Sarah and Aguet, Fran{\c c}ois and Oliva, Meritxell and Mu{\~n}oz-Aguirre, Manuel and Kasela, Silva and Wucher, Valentin and Castel, Stephane E and Hamel, Andrew R and Vi{\~n}uela, Ana and Roberts, Amy L and Mangul, Serghei and Wen, Xiaoquan and Wang, Gao and Barbeira, Alvaro N and Garrido-Mart{\'\i}n, Diego and Nadel, Brian B and Zou, Yuxin and Bonazzola, Rodrigo and Quan, Jie and Brown, Andrew and Martinez-Perez, Angel and Soria, Jos{\'e} Manuel and Getz, Gad and Dermitzakis, Emmanouil T and Small, Kerrin S and Stephens, Matthew and Xi, Hualin S and Im, Hae Kyung and Guigo, Roderic and Segr{\`e}, Ayellet V and Stranger, Barbara E and Ardlie, Kristin G and Lappalainen, Tuuli} } @article {100, title = {Determinants of telomere length across human tissues.}, journal = {Science}, volume = {369}, year = {2020}, month = {2020 09 11}, abstract = {

Telomere shortening is a hallmark of aging. Telomere length (TL) in blood cells has been studied extensively as a biomarker of human aging and disease; however, little is known regarding variability in TL in nonblood, disease-relevant tissue types. Here, we characterize variability in TLs from 6391 tissue samples, representing >20 tissue types and 952 individuals from the Genotype-Tissue Expression (GTEx) project. We describe differences across tissue types, positive correlation among tissue types, and associations with age and ancestry. We show that genetic variation affects TL in multiple tissue types and that TL may mediate the effect of age on gene expression. Our results provide the foundational knowledge regarding TL in healthy tissues that is needed to interpret epidemiological studies of TL and human health.

}, keywords = {Aging, Genetic Markers, Genetic Variation, Humans, Organ Specificity, Telomere, Telomere Homeostasis, Telomere Shortening}, issn = {1095-9203}, doi = {10.1126/science.aaz6876}, author = {Demanelis, Kathryn and Jasmine, Farzana and Chen, Lin S and Chernoff, Meytal and Tong, Lin and Delgado, Dayana and Zhang, Chenan and Shinkle, Justin and Sabarinathan, Mekala and Lin, Hannah and Ramirez, Eduardo and Oliva, Meritxell and Kim-Hellmuth, Sarah and Stranger, Barbara E and Lai, Tsung-Po and Aviv, Abraham and Ardlie, Kristin G and Aguet, Fran{\c c}ois and Ahsan, Habibul and Doherty, Jennifer A and Kibriya, Muhammad G and Pierce, Brandon L} } @article {97, title = {The GTEx Consortium atlas of genetic regulatory effects across human tissues.}, journal = {Science}, volume = {369}, year = {2020}, month = {2020 09 11}, pages = {1318-1330}, abstract = {

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.

}, keywords = {Datasets as Topic, Disease, Female, Gene Expression Regulation, Genome-Wide Association Study, Humans, Male, Organ Specificity, Quantitative Trait Loci, Sequence Analysis, RNA}, issn = {1095-9203}, doi = {10.1126/science.aaz1776} } @article {102, title = {The impact of sex on gene expression across human tissues.}, journal = {Science}, volume = {369}, year = {2020}, month = {2020 09 11}, abstract = {

Many complex human phenotypes exhibit sex-differentiated characteristics. However, the molecular mechanisms underlying these differences remain largely unknown. We generated a catalog of sex differences in gene expression and in the genetic regulation of gene expression across 44 human tissue sources surveyed by the Genotype-Tissue Expression project (GTEx, v8 release). We demonstrate that sex influences gene expression levels and cellular composition of tissue samples across the human body. A total of 37\% of all genes exhibit sex-biased expression in at least one tissue. We identify cis expression quantitative trait loci (eQTLs) with sex-differentiated effects and characterize their cellular origin. By integrating sex-biased eQTLs with genome-wide association study data, we identify 58 gene-trait associations that are driven by genetic regulation of gene expression in a single sex. These findings provide an extensive characterization of sex differences in the human transcriptome and its genetic regulation.

}, keywords = {Chromosomes, Human, X, Disease, Epigenesis, Genetic, Female, Gene Expression, Gene Expression Regulation, Genetic Variation, Genome-Wide Association Study, Humans, Male, Organ Specificity, Promoter Regions, Genetic, Quantitative Trait Loci, Sex Characteristics, Sex Factors}, issn = {1095-9203}, doi = {10.1126/science.aba3066}, author = {Oliva, Meritxell and Mu{\~n}oz-Aguirre, Manuel and Kim-Hellmuth, Sarah and Wucher, Valentin and Gewirtz, Ariel D H and Cotter, Daniel J and Parsana, Princy and Kasela, Silva and Balliu, Brunilda and Vi{\~n}uela, Ana and Castel, Stephane E and Mohammadi, Pejman and Aguet, Fran{\c c}ois and Zou, Yuxin and Khramtsova, Ekaterina A and Skol, Andrew D and Garrido-Mart{\'\i}n, Diego and Reverter, Ferran and Brown, Andrew and Evans, Patrick and Gamazon, Eric R and Payne, Anthony and Bonazzola, Rodrigo and Barbeira, Alvaro N and Hamel, Andrew R and Martinez-Perez, Angel and Soria, Jos{\'e} Manuel and Pierce, Brandon L and Stephens, Matthew and Eskin, Eleazar and Dermitzakis, Emmanouil T and Segr{\`e}, Ayellet V and Im, Hae Kyung and Engelhardt, Barbara E and Ardlie, Kristin G and Montgomery, Stephen B and Battle, Alexis J and Lappalainen, Tuuli and Guigo, Roderic and Stranger, Barbara E} } @article {101, title = {Transcriptomic signatures across human tissues identify functional rare genetic variation.}, journal = {Science}, volume = {369}, year = {2020}, month = {2020 09 11}, abstract = {

Rare genetic variants are abundant across the human genome, and identifying their function and phenotypic impact is a major challenge. Measuring aberrant gene expression has aided in identifying functional, large-effect rare variants (RVs). Here, we expanded detection of genetically driven transcriptome abnormalities by analyzing gene expression, allele-specific expression, and alternative splicing from multitissue RNA-sequencing data, and demonstrate that each signal informs unique classes of RVs. We developed Watershed, a probabilistic model that integrates multiple genomic and transcriptomic signals to predict variant function, validated these predictions in additional cohorts and through experimental assays, and used them to assess RVs in the UK Biobank, the Million Veterans Program, and the Jackson Heart Study. Our results link thousands of RVs to diverse molecular effects and provide evidence to associate RVs affecting the transcriptome with human traits.

}, keywords = {Genetic Variation, Genome, Human, Humans, Multifactorial Inheritance, Organ Specificity, Transcriptome}, issn = {1095-9203}, doi = {10.1126/science.aaz5900}, author = {Ferraro, Nicole M and Strober, Benjamin J and Einson, Jonah and Abell, Nathan S and Aguet, Fran{\c c}ois and Barbeira, Alvaro N and Brandt, Margot and Bucan, Maja and Castel, Stephane E and Davis, Joe R and Greenwald, Emily and Hess, Gaelen T and Hilliard, Austin T and Kember, Rachel L and Kotis, Bence and Park, YoSon and Peloso, Gina and Ramdas, Shweta and Scott, Alexandra J and Smail, Craig and Tsang, Emily K and Zekavat, Seyedeh M and Ziosi, Marcello and Ardlie, Kristin G and Assimes, Themistocles L and Bassik, Michael C and Brown, Christopher D and Correa, Adolfo and Hall, Ira and Im, Hae Kyung and Li, Xin and Natarajan, Pradeep and Lappalainen, Tuuli and Mohammadi, Pejman and Montgomery, Stephen B and Battle, Alexis} } @article {24, title = {cTag-PAPERCLIP Reveals Alternative Polyadenylation Promotes Cell-Type Specific Protein Diversity and Shifts Araf Isoforms with Microglia Activation.}, journal = {Neuron}, volume = {95}, year = {2017}, month = {2017 Sep 13}, pages = {1334-1349.e5}, abstract = {

Alternative polyadenylation (APA) is increasingly recognized to regulate gene expression across different cell types, but obtaining APA maps from individual cell types typically requires prior purification, a stressful procedure that can itself alter cellular states. Here, we describe a new platform, cTag-PAPERCLIP,~that generates APA profiles from single cell populations in intact tissues; cTag-PAPERCLIP requires no tissue dissociation and preserves transcripts in native states. Applying cTag-PAPERCLIP to profile four major cell types in the mouse brain revealed common APA preferences between excitatory and inhibitory neurons distinct from astrocytes~and microglia, regulated in part by neuron-specific~RNA-binding proteins NOVA2 and PTBP2. We further~identified a role of APA in switching Araf protein isoforms during microglia activation, impacting production of downstream inflammatory cytokines. Our results demonstrate the broad applicability of cTag-PAPERCLIP and a previously undiscovered role of APA in contributing to protein diversity between different cell types and cellular states within the brain.

}, keywords = {Animals, Antigens, Neoplasm, Astrocytes, Brain, Cells, Cultured, Female, Humans, Male, Mice, Microglia, Nerve Tissue Proteins, Neuro-Oncological Ventral Antigen, Neurons, Organ Specificity, Polyadenylation, Polypyrimidine Tract-Binding Protein, Protein Isoforms, Protein Serine-Threonine Kinases, RNA-Binding Proteins}, issn = {1097-4199}, doi = {10.1016/j.neuron.2017.08.024}, author = {Hwang, Hun-Way and Saito, Yuhki and Park, Christopher Y and Blach{\`e}re, Nathalie E and Tajima, Yoko and Fak, John J and Zucker-Scharff, Ilana and Darnell, Robert B} } @article {32, title = {Genetic effects on gene expression across human tissues.}, journal = {Nature}, volume = {550}, year = {2017}, month = {2017 Oct 11}, pages = {204-213}, abstract = {

Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression levels across individuals and diverse tissues of the human body, many of which are not easily accessible. Here we describe genetic effects on gene expression levels across 44 human tissues. We find that local genetic variation affects gene expression levels for the majority of genes, and we further identify inter-chromosomal genetic effects for 93 genes and 112 loci. On the basis of the identified genetic effects, we characterize patterns of tissue specificity, compare local and distal effects, and evaluate the functional properties of the genetic effects. We also demonstrate that multi-tissue, multi-individual data can be used to identify genes and pathways affected by human disease-associated variation, enabling a mechanistic interpretation of gene regulation and the genetic basis of disease.

}, keywords = {Alleles, Chromosomes, Human, Disease, Female, Gene Expression Profiling, Gene Expression Regulation, Genetic Variation, Genome, Human, Genotype, Humans, Male, Organ Specificity, Quantitative Trait Loci}, issn = {1476-4687}, doi = {10.1038/nature24277}, author = {Battle, Alexis and Brown, Christopher D and Engelhardt, Barbara E and Montgomery, Stephen B} }