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Abstract
Post-mortem tissues samples are a key resource for investigating patterns of gene expression. However, the processes triggered by death and the post-mortem interval (PMI) can significantly alter physiologically normal RNA levels. We investigate the impact of PMI on gene expression using data from multiple tissues of post-mortem donors obtained from the GTEx project. We find that many genes change expression over relatively short PMIs in a tissue-specific manner, but this potentially confounding effect in a biological analysis can be minimized by taking into account appropriate covariates. By comparing ante- and post-mortem blood samples, we identify the cascade of transcriptional events triggered by death of the organism. These events do not appear to simply reflect stochastic variation resulting from mRNA degradation, but active and ongoing regulation of transcription. Finally, we develop a model to predict the time since death from the analysis of the transcriptome of a few readily accessible tissues.
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1 Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal; Institute of Molecular Pathology and Immunology, University of Porto, Porto, Portugal
2 Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, Barcelona, Catalonia, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Catalonia, Spain; Institut Hospital del Mar d’Investigacions Mediques (IMIM), Barcelona, Catalonia, Spain; Departament d’Estadística i Investigació Operativa, Universitat Politècnica de Catalunya, Barcelona, Catalonia, Spain
3 Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, Barcelona, Catalonia, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Catalonia, Spain; Institut Hospital del Mar d’Investigacions Mediques (IMIM), Barcelona, Catalonia, Spain; Universitat de Barcelona, Barcelona, Catalonia, Spain
4 Institute of Biophysics Carlos Chagas Filho (IBCCF), Federal University of Rio de Janeiro (UFRJ), Rio de Janeiro, Brazil
5 Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal; Institute of Molecular Pathology and Immunology, University of Porto, Porto, Portugal; European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Cambridge, UK
6 Department of Bioinformatics, Igenomix S.A, Valencia, Spain
7 Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, Barcelona, Catalonia, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Catalonia, Spain; Institut Hospital del Mar d’Investigacions Mediques (IMIM), Barcelona, Catalonia, Spain
8 Clinical Bioinformatics Area, Fundación Progreso y Salud (FPS), Hospital Virgen del Rocio, Sevilla, Spain
9 Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, Barcelona, Catalonia, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Catalonia, Spain; Institut Hospital del Mar d’Investigacions Mediques (IMIM), Barcelona, Catalonia, Spain; Skolkovo Institute of Science and Technology, Skolkovo, Moscow Region, Russia
10 Chromatin and Gene expression Lab, Gene Regulation, Stem Cells and Cancer Program, Centre de Regulació Genòmica (CRG), The Barcelona Institute of Science and Technology, PRBB, Barcelona, Spain
11 The Broad Institute of MIT and Harvard, Cambridge, MA, USA
12 Department of Bioinformatics, Igenomix S.A, Valencia, Spain; Clinical Bioinformatics Area, Fundación Progreso y Salud (FPS), Hospital Virgen del Rocio, Sevilla, Spain; Functional Genomics Node (INB), FPS, Hospital Virgen del Rocio, Sevilla, Spain; Bioinformatics in Rare Diseases (BiER), Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), FPS, Hospital Virgen del Rocio, Sevilla, Spain