<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kim-Hellmuth, Sarah</style></author><author><style face="normal" font="default" size="100%">Aguet, François</style></author><author><style face="normal" font="default" size="100%">Oliva, Meritxell</style></author><author><style face="normal" font="default" size="100%">Muñoz-Aguirre, Manuel</style></author><author><style face="normal" font="default" size="100%">Kasela, Silva</style></author><author><style face="normal" font="default" size="100%">Wucher, Valentin</style></author><author><style face="normal" font="default" size="100%">Castel, Stephane E</style></author><author><style face="normal" font="default" size="100%">Hamel, Andrew R</style></author><author><style face="normal" font="default" size="100%">Viñuela, Ana</style></author><author><style face="normal" font="default" size="100%">Roberts, Amy L</style></author><author><style face="normal" font="default" size="100%">Mangul, Serghei</style></author><author><style face="normal" font="default" size="100%">Wen, Xiaoquan</style></author><author><style face="normal" font="default" size="100%">Wang, Gao</style></author><author><style face="normal" font="default" size="100%">Barbeira, Alvaro N</style></author><author><style face="normal" font="default" size="100%">Garrido-Martín, Diego</style></author><author><style face="normal" font="default" size="100%">Nadel, Brian B</style></author><author><style face="normal" font="default" size="100%">Zou, Yuxin</style></author><author><style face="normal" font="default" size="100%">Bonazzola, Rodrigo</style></author><author><style face="normal" font="default" size="100%">Quan, Jie</style></author><author><style face="normal" font="default" size="100%">Brown, Andrew</style></author><author><style face="normal" font="default" size="100%">Martinez-Perez, Angel</style></author><author><style face="normal" font="default" size="100%">Soria, José Manuel</style></author><author><style face="normal" font="default" size="100%">Getz, Gad</style></author><author><style face="normal" font="default" size="100%">Dermitzakis, Emmanouil T</style></author><author><style face="normal" font="default" size="100%">Small, Kerrin S</style></author><author><style face="normal" font="default" size="100%">Stephens, Matthew</style></author><author><style face="normal" font="default" size="100%">Xi, Hualin S</style></author><author><style face="normal" font="default" size="100%">Im, Hae Kyung</style></author><author><style face="normal" font="default" size="100%">Guigo, Roderic</style></author><author><style face="normal" font="default" size="100%">Segrè, Ayellet V</style></author><author><style face="normal" font="default" size="100%">Stranger, Barbara E</style></author><author><style face="normal" font="default" size="100%">Ardlie, Kristin G</style></author><author><style face="normal" font="default" size="100%">Lappalainen, Tuuli</style></author></authors><translated-authors><author><style face="normal" font="default" size="100%">GTEx Consortium</style></author></translated-authors></contributors><titles><title><style face="normal" font="default" size="100%">Cell type-specific genetic regulation of gene expression across human tissues.</style></title><secondary-title><style face="normal" font="default" size="100%">Science</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Science</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Cells</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Regulation</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Organ Specificity</style></keyword><keyword><style  face="normal" font="default" size="100%">Quantitative Trait Loci</style></keyword><keyword><style  face="normal" font="default" size="100%">RNA, Long Noncoding</style></keyword><keyword><style  face="normal" font="default" size="100%">Transcriptome</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2020 09 11</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">369</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;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.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">6509</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/32913075?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><translated-authors><author><style face="normal" font="default" size="100%">GTEx Consortium</style></author></translated-authors></contributors><titles><title><style face="normal" font="default" size="100%">The GTEx Consortium atlas of genetic regulatory effects across human tissues.</style></title><secondary-title><style face="normal" font="default" size="100%">Science</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Science</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Datasets as Topic</style></keyword><keyword><style  face="normal" font="default" size="100%">Disease</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Regulation</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome-Wide Association Study</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Organ Specificity</style></keyword><keyword><style  face="normal" font="default" size="100%">Quantitative Trait Loci</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Analysis, RNA</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2020 09 11</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">369</style></volume><pages><style face="normal" font="default" size="100%">1318-1330</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;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.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">6509</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/32913098?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Oliva, Meritxell</style></author><author><style face="normal" font="default" size="100%">Muñoz-Aguirre, Manuel</style></author><author><style face="normal" font="default" size="100%">Kim-Hellmuth, Sarah</style></author><author><style face="normal" font="default" size="100%">Wucher, Valentin</style></author><author><style face="normal" font="default" size="100%">Gewirtz, Ariel D H</style></author><author><style face="normal" font="default" size="100%">Cotter, Daniel J</style></author><author><style face="normal" font="default" size="100%">Parsana, Princy</style></author><author><style face="normal" font="default" size="100%">Kasela, Silva</style></author><author><style face="normal" font="default" size="100%">Balliu, Brunilda</style></author><author><style face="normal" font="default" size="100%">Viñuela, Ana</style></author><author><style face="normal" font="default" size="100%">Castel, Stephane E</style></author><author><style face="normal" font="default" size="100%">Mohammadi, Pejman</style></author><author><style face="normal" font="default" size="100%">Aguet, François</style></author><author><style face="normal" font="default" size="100%">Zou, Yuxin</style></author><author><style face="normal" font="default" size="100%">Khramtsova, Ekaterina A</style></author><author><style face="normal" font="default" size="100%">Skol, Andrew D</style></author><author><style face="normal" font="default" size="100%">Garrido-Martín, Diego</style></author><author><style face="normal" font="default" size="100%">Reverter, Ferran</style></author><author><style face="normal" font="default" size="100%">Brown, Andrew</style></author><author><style face="normal" font="default" size="100%">Evans, Patrick</style></author><author><style face="normal" font="default" size="100%">Gamazon, Eric R</style></author><author><style face="normal" font="default" size="100%">Payne, Anthony</style></author><author><style face="normal" font="default" size="100%">Bonazzola, Rodrigo</style></author><author><style face="normal" font="default" size="100%">Barbeira, Alvaro N</style></author><author><style face="normal" font="default" size="100%">Hamel, Andrew R</style></author><author><style face="normal" font="default" size="100%">Martinez-Perez, Angel</style></author><author><style face="normal" font="default" size="100%">Soria, José Manuel</style></author><author><style face="normal" font="default" size="100%">Pierce, Brandon L</style></author><author><style face="normal" font="default" size="100%">Stephens, Matthew</style></author><author><style face="normal" font="default" size="100%">Eskin, Eleazar</style></author><author><style face="normal" font="default" size="100%">Dermitzakis, Emmanouil T</style></author><author><style face="normal" font="default" size="100%">Segrè, Ayellet V</style></author><author><style face="normal" font="default" size="100%">Im, Hae Kyung</style></author><author><style face="normal" font="default" size="100%">Engelhardt, Barbara E</style></author><author><style face="normal" font="default" size="100%">Ardlie, Kristin G</style></author><author><style face="normal" font="default" size="100%">Montgomery, Stephen B</style></author><author><style face="normal" font="default" size="100%">Battle, Alexis J</style></author><author><style face="normal" font="default" size="100%">Lappalainen, Tuuli</style></author><author><style face="normal" font="default" size="100%">Guigo, Roderic</style></author><author><style face="normal" font="default" size="100%">Stranger, Barbara E</style></author></authors><translated-authors><author><style face="normal" font="default" size="100%">GTEx Consortium</style></author></translated-authors></contributors><titles><title><style face="normal" font="default" size="100%">The impact of sex on gene expression across human tissues.</style></title><secondary-title><style face="normal" font="default" size="100%">Science</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Science</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Chromosomes, Human, X</style></keyword><keyword><style  face="normal" font="default" size="100%">Disease</style></keyword><keyword><style  face="normal" font="default" size="100%">Epigenesis, Genetic</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Regulation</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Variation</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome-Wide Association Study</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Organ Specificity</style></keyword><keyword><style  face="normal" font="default" size="100%">Promoter Regions, Genetic</style></keyword><keyword><style  face="normal" font="default" size="100%">Quantitative Trait Loci</style></keyword><keyword><style  face="normal" font="default" size="100%">Sex Characteristics</style></keyword><keyword><style  face="normal" font="default" size="100%">Sex Factors</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2020 09 11</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">369</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;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.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">6509</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/32913072?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Yin, Jiani</style></author><author><style face="normal" font="default" size="100%">Chun, Chun-An</style></author><author><style face="normal" font="default" size="100%">Zavadenko, Nikolay N</style></author><author><style face="normal" font="default" size="100%">Pechatnikova, Natalia L</style></author><author><style face="normal" font="default" size="100%">Naumova, Oxana Yu</style></author><author><style face="normal" font="default" size="100%">Doddapaneni, Harsha V</style></author><author><style face="normal" font="default" size="100%">Hu, Jianhong</style></author><author><style face="normal" font="default" size="100%">Muzny, Donna M</style></author><author><style face="normal" font="default" size="100%">Schaaf, Christian P</style></author><author><style face="normal" font="default" size="100%">Grigorenko, Elena L</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Next Generation Sequencing of 134 Children with Autism Spectrum Disorder and Regression.</style></title><secondary-title><style face="normal" font="default" size="100%">Genes (Basel)</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Genes (Basel)</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Autism Spectrum Disorder</style></keyword><keyword><style  face="normal" font="default" size="100%">Child</style></keyword><keyword><style  face="normal" font="default" size="100%">Child, Preschool</style></keyword><keyword><style  face="normal" font="default" size="100%">Cohort Studies</style></keyword><keyword><style  face="normal" font="default" size="100%">Disease Progression</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Regulation</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Markers</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Predisposition to Disease</style></keyword><keyword><style  face="normal" font="default" size="100%">High-Throughput Nucleotide Sequencing</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Infant</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Mutation</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2020 07 25</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">11</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Approximately 30% of individuals with autism spectrum disorder (ASD) experience developmental regression, the etiology of which remains largely unknown. We performed a complete literature search and identified 47 genes that had been implicated in such cases. We sequenced these genes in a preselected cohort of 134 individuals with regressive autism. In total, 16 variants in 12 genes with evidence supportive of pathogenicity were identified. They were classified as variants of uncertain significance based on ACMG standards and guidelines. Among these were recurring variants in  and , variants in genes that were linked to syndromic forms of ASD (, , , , , and ), and variants in the form of oligogenic heterozygosity (, , and ).&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">8</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/32722525?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Sajuthi, Satria P</style></author><author><style face="normal" font="default" size="100%">DeFord, Peter</style></author><author><style face="normal" font="default" size="100%">Li, Yingchun</style></author><author><style face="normal" font="default" size="100%">Jackson, Nathan D</style></author><author><style face="normal" font="default" size="100%">Montgomery, Michael T</style></author><author><style face="normal" font="default" size="100%">Everman, Jamie L</style></author><author><style face="normal" font="default" size="100%">Rios, Cydney L</style></author><author><style face="normal" font="default" size="100%">Pruesse, Elmar</style></author><author><style face="normal" font="default" size="100%">Nolin, James D</style></author><author><style face="normal" font="default" size="100%">Plender, Elizabeth G</style></author><author><style face="normal" font="default" size="100%">Wechsler, Michael E</style></author><author><style face="normal" font="default" size="100%">Mak, Angel C Y</style></author><author><style face="normal" font="default" size="100%">Eng, Celeste</style></author><author><style face="normal" font="default" size="100%">Salazar, Sandra</style></author><author><style face="normal" font="default" size="100%">Medina, Vivian</style></author><author><style face="normal" font="default" size="100%">Wohlford, Eric M</style></author><author><style face="normal" font="default" size="100%">Huntsman, Scott</style></author><author><style face="normal" font="default" size="100%">Nickerson, Deborah A</style></author><author><style face="normal" font="default" size="100%">Germer, Soren</style></author><author><style face="normal" font="default" size="100%">Zody, Michael C</style></author><author><style face="normal" font="default" size="100%">Abecasis, Gonçalo</style></author><author><style face="normal" font="default" size="100%">Kang, Hyun Min</style></author><author><style face="normal" font="default" size="100%">Rice, Kenneth M</style></author><author><style face="normal" font="default" size="100%">Kumar, Rajesh</style></author><author><style face="normal" font="default" size="100%">Oh, Sam</style></author><author><style face="normal" font="default" size="100%">Rodriguez-Santana, Jose</style></author><author><style face="normal" font="default" size="100%">Burchard, Esteban G</style></author><author><style face="normal" font="default" size="100%">Seibold, Max A</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Type 2 and interferon inflammation regulate SARS-CoV-2 entry factor expression in the airway epithelium.</style></title><secondary-title><style face="normal" font="default" size="100%">Nat Commun</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Nat Commun</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Angiotensin-Converting Enzyme 2</style></keyword><keyword><style  face="normal" font="default" size="100%">Betacoronavirus</style></keyword><keyword><style  face="normal" font="default" size="100%">Child</style></keyword><keyword><style  face="normal" font="default" size="100%">Coronavirus Infections</style></keyword><keyword><style  face="normal" font="default" size="100%">COVID-19</style></keyword><keyword><style  face="normal" font="default" size="100%">Epithelial Cells</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Profiling</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Regulation</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Variation</style></keyword><keyword><style  face="normal" font="default" size="100%">Host-Pathogen Interactions</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Inflammation</style></keyword><keyword><style  face="normal" font="default" size="100%">Interferons</style></keyword><keyword><style  face="normal" font="default" size="100%">Interleukin-13</style></keyword><keyword><style  face="normal" font="default" size="100%">Middle Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Nasal Mucosa</style></keyword><keyword><style  face="normal" font="default" size="100%">Pandemics</style></keyword><keyword><style  face="normal" font="default" size="100%">Peptidyl-Dipeptidase A</style></keyword><keyword><style  face="normal" font="default" size="100%">Pneumonia, Viral</style></keyword><keyword><style  face="normal" font="default" size="100%">SARS-CoV-2</style></keyword><keyword><style  face="normal" font="default" size="100%">Serine Endopeptidases</style></keyword><keyword><style  face="normal" font="default" size="100%">Virus Internalization</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2020 10 12</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">11</style></volume><pages><style face="normal" font="default" size="100%">5139</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Coronavirus disease 2019 (COVID-19) is caused by SARS-CoV-2, an emerging virus that utilizes host proteins ACE2 and TMPRSS2 as entry factors. Understanding the factors affecting the pattern and levels of expression of these genes is important for deeper understanding of SARS-CoV-2 tropism and pathogenesis. Here we explore the role of genetics and co-expression networks in regulating these genes in the airway, through the analysis of nasal airway transcriptome data from 695 children. We identify expression quantitative trait loci for both ACE2 and TMPRSS2, that vary in frequency across world populations. We find TMPRSS2 is part of a mucus secretory network, highly upregulated by type 2 (T2) inflammation through the action of interleukin-13, and that the interferon response to respiratory viruses highly upregulates ACE2 expression. IL-13 and virus infection mediated effects on ACE2 expression were also observed at the protein level in the airway epithelium. Finally, we define airway responses to common coronavirus infections in children, finding that these infections generate host responses similar to other viral species, including upregulation of IL6 and ACE2. Our results reveal possible mechanisms influencing SARS-CoV-2 infectivity and COVID-19 clinical outcomes.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/33046696?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Battle, Alexis</style></author><author><style face="normal" font="default" size="100%">Brown, Christopher D</style></author><author><style face="normal" font="default" size="100%">Engelhardt, Barbara E</style></author><author><style face="normal" font="default" size="100%">Montgomery, Stephen B</style></author></authors><translated-authors><author><style face="normal" font="default" size="100%">GTEx Consortium</style></author><author><style face="normal" font="default" size="100%">Laboratory, Data Analysis &amp;Coordinating Center (LDACC)—Analysis Working Group</style></author><author><style face="normal" font="default" size="100%">Statistical Methods groups—Analysis Working Group</style></author><author><style face="normal" font="default" size="100%">Enhancing GTEx (eGTEx) groups</style></author><author><style face="normal" font="default" size="100%">NIH Common Fund</style></author><author><style face="normal" font="default" size="100%">NIH/NCI</style></author><author><style face="normal" font="default" size="100%">NIH/NHGRI</style></author><author><style face="normal" font="default" size="100%">NIH/NIMH</style></author><author><style face="normal" font="default" size="100%">NIH/NIDA</style></author><author><style face="normal" font="default" size="100%">Biospecimen Collection Source Site—NDRI</style></author><author><style face="normal" font="default" size="100%">Biospecimen Collection Source Site—RPCI</style></author><author><style face="normal" font="default" size="100%">Biospecimen Core Resource—VARI</style></author><author><style face="normal" font="default" size="100%">Brain Bank Repository—University of Miami Brain Endowment Bank</style></author><author><style face="normal" font="default" size="100%">Leidos Biomedical—Project Management</style></author><author><style face="normal" font="default" size="100%">ELSI Study</style></author><author><style face="normal" font="default" size="100%">Genome Browser Data Integration &amp;Visualization—EBI</style></author><author><style face="normal" font="default" size="100%">Genome Browser Data Integration &amp;Visualization—UCSC Genomics Institute, University of California Santa Cruz</style></author><author><style face="normal" font="default" size="100%">Lead analysts:</style></author><author><style face="normal" font="default" size="100%">Laboratory, Data Analysis &amp;Coordinating Center (LDACC):</style></author><author><style face="normal" font="default" size="100%">NIH program management:</style></author><author><style face="normal" font="default" size="100%">Biospecimen collection:</style></author><author><style face="normal" font="default" size="100%">Pathology:</style></author><author><style face="normal" font="default" size="100%">eQTL manuscript working group:</style></author></translated-authors></contributors><titles><title><style face="normal" font="default" size="100%">Genetic effects on gene expression across human tissues.</style></title><secondary-title><style face="normal" font="default" size="100%">Nature</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Nature</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Alleles</style></keyword><keyword><style  face="normal" font="default" size="100%">Chromosomes, Human</style></keyword><keyword><style  face="normal" font="default" size="100%">Disease</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Profiling</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Regulation</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Variation</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome, Human</style></keyword><keyword><style  face="normal" font="default" size="100%">Genotype</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Organ Specificity</style></keyword><keyword><style  face="normal" font="default" size="100%">Quantitative Trait Loci</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2017</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2017 Oct 11</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">550</style></volume><pages><style face="normal" font="default" size="100%">204-213</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;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.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">7675</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/29022597?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kim-Hellmuth, Sarah</style></author><author><style face="normal" font="default" size="100%">Bechheim, Matthias</style></author><author><style face="normal" font="default" size="100%">Pütz, Benno</style></author><author><style face="normal" font="default" size="100%">Mohammadi, Pejman</style></author><author><style face="normal" font="default" size="100%">Nédélec, Yohann</style></author><author><style face="normal" font="default" size="100%">Giangreco, Nicholas</style></author><author><style face="normal" font="default" size="100%">Becker, Jessica</style></author><author><style face="normal" font="default" size="100%">Kaiser, Vera</style></author><author><style face="normal" font="default" size="100%">Fricker, Nadine</style></author><author><style face="normal" font="default" size="100%">Beier, Esther</style></author><author><style face="normal" font="default" size="100%">Boor, Peter</style></author><author><style face="normal" font="default" size="100%">Castel, Stephane E</style></author><author><style face="normal" font="default" size="100%">Nöthen, Markus M</style></author><author><style face="normal" font="default" size="100%">Barreiro, Luis B</style></author><author><style face="normal" font="default" size="100%">Pickrell, Joseph K</style></author><author><style face="normal" font="default" size="100%">Müller-Myhsok, Bertram</style></author><author><style face="normal" font="default" size="100%">Lappalainen, Tuuli</style></author><author><style face="normal" font="default" size="100%">Schumacher, Johannes</style></author><author><style face="normal" font="default" size="100%">Hornung, Veit</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Genetic regulatory effects modified by immune activation contribute to autoimmune disease associations.</style></title><secondary-title><style face="normal" font="default" size="100%">Nat Commun</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Nat Commun</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Acetylmuramyl-Alanyl-Isoglutamine</style></keyword><keyword><style  face="normal" font="default" size="100%">Adjuvants, Immunologic</style></keyword><keyword><style  face="normal" font="default" size="100%">Adolescent</style></keyword><keyword><style  face="normal" font="default" size="100%">Adult</style></keyword><keyword><style  face="normal" font="default" size="100%">Autoimmune Diseases</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Profiling</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Regulation</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Predisposition to Disease</style></keyword><keyword><style  face="normal" font="default" size="100%">Healthy Volunteers</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Indicators and Reagents</style></keyword><keyword><style  face="normal" font="default" size="100%">Lipids</style></keyword><keyword><style  face="normal" font="default" size="100%">Lipopolysaccharides</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Monocytes</style></keyword><keyword><style  face="normal" font="default" size="100%">Quantitative Trait Loci</style></keyword><keyword><style  face="normal" font="default" size="100%">Regulatory Sequences, Nucleic Acid</style></keyword><keyword><style  face="normal" font="default" size="100%">RNA, Double-Stranded</style></keyword><keyword><style  face="normal" font="default" size="100%">RNA, Messenger</style></keyword><keyword><style  face="normal" font="default" size="100%">Young Adult</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2017</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2017 Aug 16</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">8</style></volume><pages><style face="normal" font="default" size="100%">266</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The immune system plays a major role in human health and disease, and understanding genetic causes of interindividual variability of immune responses is vital. Here, we isolate monocytes from 134 genotyped individuals, stimulate these cells with three defined microbe-associated molecular patterns (LPS, MDP, and 5'-ppp-dsRNA), and profile the transcriptomes at three time points. Mapping expression quantitative trait loci (eQTL), we identify 417 response eQTLs (reQTLs) with varying effects between conditions. We characterize the dynamics of genetic regulation on early and late immune response and observe an enrichment of reQTLs in distal cis-regulatory elements. In addition, reQTLs are enriched for recent positive selection with an evolutionary trend towards enhanced immune response. Finally, we uncover reQTL effects in multiple GWAS loci and show a stronger enrichment for response than constant eQTLs in GWAS signals of several autoimmune diseases. This demonstrates the importance of infectious stimuli in modifying genetic predisposition to disease.Insight into the genetic influence on the immune response is important for the understanding of interindividual variability in human pathologies. Here, the authors generate transcriptome data from human blood monocytes stimulated with various immune stimuli and provide a time-resolved response eQTL map.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/28814792?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Chiang, Colby</style></author><author><style face="normal" font="default" size="100%">Scott, Alexandra J</style></author><author><style face="normal" font="default" size="100%">Davis, Joe R</style></author><author><style face="normal" font="default" size="100%">Tsang, Emily K</style></author><author><style face="normal" font="default" size="100%">Li, Xin</style></author><author><style face="normal" font="default" size="100%">Kim, Yungil</style></author><author><style face="normal" font="default" size="100%">Hadzic, Tarik</style></author><author><style face="normal" font="default" size="100%">Damani, Farhan N</style></author><author><style face="normal" font="default" size="100%">Ganel, Liron</style></author><author><style face="normal" font="default" size="100%">Montgomery, Stephen B</style></author><author><style face="normal" font="default" size="100%">Battle, Alexis</style></author><author><style face="normal" font="default" size="100%">Conrad, Donald F</style></author><author><style face="normal" font="default" size="100%">Hall, Ira M</style></author></authors><translated-authors><author><style face="normal" font="default" size="100%">GTEx Consortium</style></author></translated-authors></contributors><titles><title><style face="normal" font="default" size="100%">The impact of structural variation on human gene expression.</style></title><secondary-title><style face="normal" font="default" size="100%">Nat Genet</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Nat Genet</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Algorithms</style></keyword><keyword><style  face="normal" font="default" size="100%">Chromosome Mapping</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Regulation</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Variation</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome, Human</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome-Wide Association Study</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">INDEL Mutation</style></keyword><keyword><style  face="normal" font="default" size="100%">Linear Models</style></keyword><keyword><style  face="normal" font="default" size="100%">Polymorphism, Single Nucleotide</style></keyword><keyword><style  face="normal" font="default" size="100%">Quantitative Trait Loci</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Analysis, DNA</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2017</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2017 May</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">49</style></volume><pages><style face="normal" font="default" size="100%">692-699</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Structural variants (SVs) are an important source of human genetic diversity, but their contribution to traits, disease and gene regulation remains unclear. We mapped cis expression quantitative trait loci (eQTLs) in 13 tissues via joint analysis of SVs, single-nucleotide variants (SNVs) and short insertion/deletion (indel) variants from deep whole-genome sequencing (WGS). We estimated that SVs are causal at 3.5-6.8% of eQTLs-a substantially higher fraction than prior estimates-and that expression-altering SVs have larger effect sizes than do SNVs and indels. We identified 789 putative causal SVs predicted to directly alter gene expression: most (88.3%) were noncoding variants enriched at enhancers and other regulatory elements, and 52 were linked to genome-wide association study loci. We observed a notable abundance of rare high-impact SVs associated with aberrant expression of nearby genes. These results suggest that comprehensive WGS-based SV analyses will increase the power of common- and rare-variant association studies.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">5</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/28369037?dopt=Abstract</style></custom1></record></records></xml>