ALBERT

Description: Transcriptional regulation and posttranscriptional processing underlie many cellular and organismal phenotypes. We used RNA sequence data generated by Genotype-Tissue Expression (GTEx) project to investigate the patterns of transcriptome variation across individuals and tissues. Tissues exhibit characteristic transcriptional signatures that show stability in postmortem samples. These signatures are dominated by a relatively small number of genes-which is most clearly seen in blood-though few are exclusive to a particular tissue and vary more across tissues than individuals. Genes exhibiting high interindividual expression variation include disease candidates associated with sex, ethnicity, and age. Primary transcription is the major driver of cellular specificity, with splicing playing mostly a complementary role; except for the brain, which exhibits a more divergent splicing program. Variation in splicing, despite its stochasticity, may play in contrast a comparatively greater role in defining individual phenotypes.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4547472/" 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/PMC4547472/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Mele, Marta -- Ferreira, Pedro G -- Reverter, Ferran -- DeLuca, David S -- Monlong, Jean -- Sammeth, Michael -- Young, Taylor R -- Goldmann, Jakob M -- Pervouchine, Dmitri D -- Sullivan, Timothy J -- Johnson, Rory -- Segre, Ayellet V -- Djebali, Sarah -- Niarchou, Anastasia -- GTEx Consortium -- Wright, Fred A -- Lappalainen, Tuuli -- Calvo, Miquel -- Getz, Gad -- Dermitzakis, Emmanouil T -- Ardlie, Kristin G -- Guigo, Roderic -- HHSN261200800001E/PHS HHS/ -- HHSN268201000029C/HL/NHLBI NIH HHS/ -- HHSN268201000029C/PHS HHS/ -- R01 DA006227-17/DA/NIDA NIH HHS/ -- R01 MH090936/MH/NIMH NIH HHS/ -- R01 MH090941/MH/NIMH NIH HHS/ -- New York, N.Y. -- Science. 2015 May 8;348(6235):660-5. doi: 10.1126/science.aaa0355.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Center for Genomic Regulation (CRG), Barcelona, Catalonia, Spain. Harvard Department of stem cell and regenerative biology, Harvard University, Cambridge, MA, USA. ; Center for Genomic Regulation (CRG), Barcelona, Catalonia, Spain. Department of Genetic Medicine and Development, University of Geneva, Geneva, Switzerland. Institute for Genetics and Genomics in Geneva (iGE3), University of Geneva, Geneva, Switzerland. Swiss Institute of Bioinformatics, Geneva, Switzerland. ; Center for Genomic Regulation (CRG), Barcelona, Catalonia, Spain. Facultat de Biologia, Universitat de Barcelona (UB), Barcelona, Catalonia, Spain. Universitat Pompeu Fabra (UPF), Barcelona, Catalonia, Spain. ; Broad Institute of MIT and Harvard, Cambridge, MA, USA. ; Center for Genomic Regulation (CRG), Barcelona, Catalonia, Spain. Universitat Pompeu Fabra (UPF), Barcelona, Catalonia, Spain. McGill University, Montreal, Canada. ; Center for Genomic Regulation (CRG), Barcelona, Catalonia, Spain. Universitat Pompeu Fabra (UPF), Barcelona, Catalonia, Spain. National Institute for Scientific Computing (LNCC), Petropolis, Rio de Janeiro, Brazil. ; Center for Genomic Regulation (CRG), Barcelona, Catalonia, Spain. Universitat Pompeu Fabra (UPF), Barcelona, Catalonia, Spain. Radboud University, Nijmegen, Netherlands. ; Center for Genomic Regulation (CRG), Barcelona, Catalonia, Spain. Universitat Pompeu Fabra (UPF), Barcelona, Catalonia, Spain. Faculty of Bioengineering and Bioinformatics, Moscow State University, Leninskie Gory 1-73, 119992 Moscow, Russia. ; Center for Genomic Regulation (CRG), Barcelona, Catalonia, Spain. Universitat Pompeu Fabra (UPF), Barcelona, Catalonia, Spain. ; Department of Genetic Medicine and Development, University of Geneva, Geneva, Switzerland. Institute for Genetics and Genomics in Geneva (iGE3), University of Geneva, Geneva, Switzerland. Swiss Institute of Bioinformatics, Geneva, Switzerland. ; Center for Genomic Regulation (CRG), Barcelona, Catalonia, Spain. Harvard Department of stem cell and regenerative biology, Harvard University, Cambridge, MA, USA. Department of Genetic Medicine and Development, University of Geneva, Geneva, Switzerland. Institute for Genetics and Genomics in Geneva (iGE3), University of Geneva, Geneva, Switzerland. Swiss Institute of Bioinformatics, Geneva, Switzerland. Facultat de Biologia, Universitat de Barcelona (UB), Barcelona, Catalonia, Spain. Universitat Pompeu Fabra (UPF), Barcelona, Catalonia, Spain. Broad Institute of MIT and Harvard, Cambridge, MA, USA. McGill University, Montreal, Canada. National Institute for Scientific Computing (LNCC), Petropolis, Rio de Janeiro, Brazil. Radboud University, Nijmegen, Netherlands. Faculty of Bioengineering and Bioinformatics, Moscow State University, Leninskie Gory 1-73, 119992 Moscow, Russia. North Carolina State University, Raleigh, NC, USA. New York Genome Center, New York, NY, USA. Department of Systems Biology, Columbia University, New York, NY, USA. Cancer Center and Department of Pathology, Massachusetts General Hospital, Boston, MA 02114, USA. Institut Hospital del Mar d'Investigacions Mediques (IMIM), Barcelona, Catalonia, Spain. Joint CRG-Barcelona Super Computing Center (BSC)-Institut de Recerca Biomedica (IRB) Program in Computational Biology, Barcelona, Catalonia, Spain. ; North Carolina State University, Raleigh, NC, USA. ; Department of Genetic Medicine and Development, University of Geneva, Geneva, Switzerland. Institute for Genetics and Genomics in Geneva (iGE3), University of Geneva, Geneva, Switzerland. Swiss Institute of Bioinformatics, Geneva, Switzerland. New York Genome Center, New York, NY, USA. Department of Systems Biology, Columbia University, New York, NY, USA. ; Facultat de Biologia, Universitat de Barcelona (UB), Barcelona, Catalonia, Spain. ; Broad Institute of MIT and Harvard, Cambridge, MA, USA. Cancer Center and Department of Pathology, Massachusetts General Hospital, Boston, MA 02114, USA. ; Broad Institute of MIT and Harvard, Cambridge, MA, USA. kardlie@broadinstitute.org roderic.guigo@crg.cat. ; Center for Genomic Regulation (CRG), Barcelona, Catalonia, Spain. Universitat Pompeu Fabra (UPF), Barcelona, Catalonia, Spain. Institut Hospital del Mar d'Investigacions Mediques (IMIM), Barcelona, Catalonia, Spain. Joint CRG-Barcelona Super Computing Center (BSC)-Institut de Recerca Biomedica (IRB) Program in Computational Biology, Barcelona, Catalonia, Spain. kardlie@broadinstitute.org roderic.guigo@crg.cat.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/25954002" target="_blank"〉PubMed〈/a〉

Description: The development of rhythmicity is foundational to communicative and social behaviours in humans and many other species, and mechanisms of synchrony could be conserved across species. The goal of the current paper is to explore evolutionary hypotheses linking vocal learning and beat synchronization through genomic approaches, testing the prediction that genetic underpinnings of birdsong also contribute to the aetiology of human interactions with musical beat structure. We combined state-of-the-art-genomic datasets that account for underlying polygenicity of these traits: birdsong genome-wide transcriptomics linked to singing in zebra finches, and a human genome-wide association study of beat synchronization. Results of competitive gene set analysis revealed that the genetic architecture of human beat synchronization is significantly enriched for birdsong genes expressed in songbird Area X (a key nucleus for vocal learning, and homologous to human basal ganglia). These findings complement ethological and neural evidence of the relationship between vocal learning and beat synchronization, supporting a framework of some degree of common genomic substrates underlying rhythm-related behaviours in two clades, humans and songbirds (the largest evolutionary radiation of vocal learners). Future cross-species approaches investigating the genetic underpinnings of beat synchronization in a broad evolutionary context are discussed. This article is part of the theme issue ‘Synchrony and rhythm interaction: from the brain to behavioural ecology’.