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  • 1
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    Comment on "Widespread RNA and DNA sequence differences in the human transcriptome" (2012)
    American Association for the Advancement of Science (AAAS)
    Details
    Publication Date: 2012-03-17
    Description: Li et al. (Research Articles, 1 July 2011, p. 53; published online 19 May 2011) reported more than 10,000 mismatches between messenger RNA and DNA sequences from the same individuals, which they attributed to previously unrecognized mechanisms of gene regulation. We found that at least 88% of these sequence mismatches can likely be explained by technical artifacts such as errors in mapping sequencing reads to a reference genome, sequencing errors, and genetic variation.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Pickrell, Joseph K -- Gilad, Yoav -- Pritchard, Jonathan K -- GM077959/GM/NIGMS NIH HHS/ -- MH084703/MH/NIMH NIH HHS/ -- New York, N.Y. -- Science. 2012 Mar 16;335(6074):1302; author reply 1302. doi: 10.1126/science.1210484.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA. pickrell@uchicago.edu〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/22422963" target="_blank"〉PubMed〈/a〉
    Keywords: DNA/*genetics ; *Genetic Variation ; *Genome, Human ; Humans ; RNA, Messenger/*genetics
    Print ISSN: 0036-8075
    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Computer Science , Medicine , Natural Sciences in General , Physics
    Published by American Association for the Advancement of Science (AAAS)
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  • 2
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    Primate transcript and protein expression levels evolve under compensatory selection pressures (2013)
    American Association for the Advancement of Science (AAAS)
    Details
    Publication Date: 2013-10-19
    Description: Changes in gene regulation have likely played an important role in the evolution of primates. Differences in messenger RNA (mRNA) expression levels across primates have often been documented; however, it is not yet known to what extent measurements of divergence in mRNA levels reflect divergence in protein expression levels, which are probably more important in determining phenotypic differences. We used high-resolution, quantitative mass spectrometry to collect protein expression measurements from human, chimpanzee, and rhesus macaque lymphoblastoid cell lines and compared them to transcript expression data from the same samples. We found dozens of genes with significant expression differences between species at the mRNA level yet little or no difference in protein expression. Overall, our data suggest that protein expression levels evolve under stronger evolutionary constraint than mRNA levels.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3994702/" target="_blank"〉〈img src="https://static.pubmed.gov/portal/portal3rc.fcgi/4089621/img/3977009" border="0"〉〈/a〉   〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3994702/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Khan, Zia -- Ford, Michael J -- Cusanovich, Darren A -- Mitrano, Amy -- Pritchard, Jonathan K -- Gilad, Yoav -- F32HG006972/HG/NHGRI NIH HHS/ -- GM077959/GM/NIGMS NIH HHS/ -- R01 GM077959/GM/NIGMS NIH HHS/ -- Howard Hughes Medical Institute/ -- New York, N.Y. -- Science. 2013 Nov 29;342(6162):1100-4. doi: 10.1126/science.1242379. Epub 2013 Oct 17.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/24136357" target="_blank"〉PubMed〈/a〉
    Keywords: Animals ; *Evolution, Molecular ; *Gene Expression Regulation ; Humans ; Macaca mulatta/*genetics ; Pan troglodytes/*genetics ; Protein Biosynthesis/*genetics ; RNA, Messenger/*biosynthesis/genetics ; *Selection, Genetic ; Species Specificity ; *Transcription, Genetic
    Print ISSN: 0036-8075
    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Computer Science , Medicine , Natural Sciences in General , Physics
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  • 3
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    Identification of genetic variants that affect histone modifications in human cells (2013)
    American Association for the Advancement of Science (AAAS)
    Details
    Publication Date: 2013-10-19
    Description: Histone modifications are important markers of function and chromatin state, yet the DNA sequence elements that direct them to specific genomic locations are poorly understood. Here, we identify hundreds of quantitative trait loci, genome-wide, that affect histone modification or RNA polymerase II (Pol II) occupancy in Yoruba lymphoblastoid cell lines (LCLs). In many cases, the same variant is associated with quantitative changes in multiple histone marks and Pol II, as well as in deoxyribonuclease I sensitivity and nucleosome positioning. Transcription factor binding site polymorphisms are correlated overall with differences in local histone modification, and we identify specific transcription factors whose binding leads to histone modification in LCLs. Furthermore, variants that affect chromatin at distal regulatory sites frequently also direct changes in chromatin and gene expression at associated promoters.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3947669/" target="_blank"〉〈img src="https://static.pubmed.gov/portal/portal3rc.fcgi/4089621/img/3977009" border="0"〉〈/a〉   〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3947669/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉McVicker, Graham -- van de Geijn, Bryce -- Degner, Jacob F -- Cain, Carolyn E -- Banovich, Nicholas E -- Raj, Anil -- Lewellen, Noah -- Myrthil, Marsha -- Gilad, Yoav -- Pritchard, Jonathan K -- GM007197/GM/NIGMS NIH HHS/ -- HG006123/HG/NHGRI NIH HHS/ -- HG007036/HG/NHGRI NIH HHS/ -- MH084703/MH/NIMH NIH HHS/ -- R01 HG006123/HG/NHGRI NIH HHS/ -- R01 MH084703/MH/NIMH NIH HHS/ -- T32 GM007197/GM/NIGMS NIH HHS/ -- U01 HG007036/HG/NHGRI NIH HHS/ -- Howard Hughes Medical Institute/ -- New York, N.Y. -- Science. 2013 Nov 8;342(6159):747-9. doi: 10.1126/science.1242429. Epub 2013 Oct 17.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/24136359" target="_blank"〉PubMed〈/a〉
    Keywords: Binding Sites/genetics ; Cell Line, Tumor ; Cells/metabolism ; Chromatin/chemistry/genetics/metabolism ; *Gene Expression Regulation ; *Genetic Variation ; Genome, Human ; Histones/chemistry/genetics/*metabolism ; Humans ; Polymorphism, Genetic ; Promoter Regions, Genetic ; Protein Processing, Post-Translational/*genetics ; Quantitative Trait Loci ; RNA Polymerase II/chemistry/*metabolism ; Transcription Factors/genetics/*metabolism
    Print ISSN: 0036-8075
    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Computer Science , Medicine , Natural Sciences in General , Physics
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  • 4
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    Genomic variation. Impact of regulatory variation from RNA to protein (2015)
    American Association for the Advancement of Science (AAAS)
    Details
    Publication Date: 2015-02-07
    Description: The phenotypic consequences of expression quantitative trait loci (eQTLs) are presumably due to their effects on protein expression levels. Yet the impact of genetic variation, including eQTLs, on protein levels remains poorly understood. To address this, we mapped genetic variants that are associated with eQTLs, ribosome occupancy (rQTLs), or protein abundance (pQTLs). We found that most QTLs are associated with transcript expression levels, with consequent effects on ribosome and protein levels. However, eQTLs tend to have significantly reduced effect sizes on protein levels, which suggests that their potential impact on downstream phenotypes is often attenuated or buffered. Additionally, we identified a class of cis QTLs that affect protein abundance with little or no effect on messenger RNA or ribosome levels, which suggests that they may arise from differences in posttranslational regulation.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4507520/" target="_blank"〉〈img src="https://static.pubmed.gov/portal/portal3rc.fcgi/4089621/img/3977009" border="0"〉〈/a〉   〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4507520/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Battle, Alexis -- Khan, Zia -- Wang, Sidney H -- Mitrano, Amy -- Ford, Michael J -- Pritchard, Jonathan K -- Gilad, Yoav -- F32 HG006972/HG/NHGRI NIH HHS/ -- F32HG006972/HG/NHGRI NIH HHS/ -- GM077959/GM/NIGMS NIH HHS/ -- HG007036/HG/NHGRI NIH HHS/ -- MH084703/MH/NIMH NIH HHS/ -- R01 GM077959/GM/NIGMS NIH HHS/ -- R01 MH084703/MH/NIMH NIH HHS/ -- U01 HG007036/HG/NHGRI NIH HHS/ -- Howard Hughes Medical Institute/ -- New York, N.Y. -- Science. 2015 Feb 6;347(6222):664-7. doi: 10.1126/science.1260793. Epub 2014 Dec 18.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Department of Genetics, Stanford University, Stanford, CA 94305, USA. Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA. ; Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA. ; MS Bioworks, LLC, 3950 Varsity Drive, Ann Arbor, MI 48108, USA. ; Department of Genetics, Stanford University, Stanford, CA 94305, USA. Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA. Department of Biology, Stanford University, Stanford, CA 94305, USA. pritch@stanford.edu gilad@uchicago.edu. ; Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA. pritch@stanford.edu gilad@uchicago.edu.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/25657249" target="_blank"〉PubMed〈/a〉
    Keywords: 3' Flanking Region ; 5' Flanking Region ; Cell Line ; Exons ; *Gene Expression Regulation ; *Genetic Variation ; Humans ; Phenotype ; Protein Biosynthesis/*genetics ; *Quantitative Trait Loci ; RNA, Messenger/*genetics ; Ribosomes/metabolism ; *Transcription, Genetic
    Print ISSN: 0036-8075
    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Computer Science , Medicine , Natural Sciences in General , Physics
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  • 5
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    RNA splicing is a primary link between genetic variation and disease (2016)
    American Association for the Advancement of Science (AAAS)
    Details
    Publication Date: 2016-04-30
    Description: Noncoding variants play a central role in the genetics of complex traits, but we still lack a full understanding of the molecular pathways through which they act. We quantified the contribution of cis-acting genetic effects at all major stages of gene regulation from chromatin to proteins, in Yoruba lymphoblastoid cell lines (LCLs). About ~65% of expression quantitative trait loci (eQTLs) have primary effects on chromatin, whereas the remaining eQTLs are enriched in transcribed regions. Using a novel method, we also detected 2893 splicing QTLs, most of which have little or no effect on gene-level expression. These splicing QTLs are major contributors to complex traits, roughly on a par with variants that affect gene expression levels. Our study provides a comprehensive view of the mechanisms linking genetic variation to variation in human gene regulation.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Li, Yang I -- van de Geijn, Bryce -- Raj, Anil -- Knowles, David A -- Petti, Allegra A -- Golan, David -- Gilad, Yoav -- Pritchard, Jonathan K -- R01MH084703/MH/NIMH NIH HHS/ -- R01MH101825/MH/NIMH NIH HHS/ -- U01HG007036/HG/NHGRI NIH HHS/ -- U54CA149145/CA/NCI NIH HHS/ -- Howard Hughes Medical Institute/ -- New York, N.Y. -- Science. 2016 Apr 29;352(6285):600-4. doi: 10.1126/science.aad9417. Epub 2016 Apr 28.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Department of Genetics, Stanford University, Stanford, CA, USA. ; Department of Human Genetics, University of Chicago, Chicago, IL, USA. ; Department of Computer Science, Stanford University, Stanford, CA, USA. Department of Radiology, Stanford University, Stanford, CA, USA. ; Genome Institute, Washington University in St. Louis, St. Louis, MO, USA. ; Department of Human Genetics, University of Chicago, Chicago, IL, USA. gilad@uchicago.edu pritch@stanford.edu. ; Department of Genetics, Stanford University, Stanford, CA, USA. Department of Biology, Stanford University, Stanford, CA, USA. Howard Hughes Medical Institute, Stanford University, Stanford, CA, USA. gilad@uchicago.edu pritch@stanford.edu.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/27126046" target="_blank"〉PubMed〈/a〉
    Keywords: Cell Line ; Chromatin/metabolism ; *Gene Expression Regulation ; *Genetic Variation ; Genome-Wide Association Study ; Humans ; Immune System Diseases/*genetics ; Lymphocytes/immunology ; Phenotype ; Polymorphism, Single Nucleotide ; *Quantitative Trait Loci ; RNA Splicing/*genetics
    Print ISSN: 0036-8075
    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Computer Science , Medicine , Natural Sciences in General , Physics
    Published by American Association for the Advancement of Science (AAAS)
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  • 6
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    Dynamic genetic regulation of gene expression during cellular differentiation (2019)
    American Association for the Advancement of Science (AAAS)
    In: Science
    Details
    Publication Date: 2019
    Description: 〈p〉Genetic regulation of gene expression is dynamic, as transcription can change during cell differentiation and across cell types. We mapped expression quantitative trait loci (eQTLs) throughout differentiation to elucidate the dynamics of genetic effects on cell type–specific gene expression. We generated time-series RNA sequencing data, capturing 16 time points during the differentiation of induced pluripotent stem cells to cardiomyocytes, in 19 human cell lines. We identified hundreds of dynamic eQTLs that change over time, with enrichment in enhancers of relevant cell types. We also found nonlinear dynamic eQTLs, which affect only intermediate stages of differentiation and cannot be found by using data from mature tissues. These fleeting genetic associations with gene regulation may explain some of the components of complex traits and disease. We highlight one example of a nonlinear eQTL that is associated with body mass index.〈/p〉
    Print ISSN: 0036-8075
    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Computer Science , Medicine , Natural Sciences in General , Physics
    Published by American Association for the Advancement of Science (AAAS)
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