The effects of death and post-mortem cold ischemia on human tissue transcriptomes

• Type: Article in International Scientific Journal
• Date: 2018

Authors

Ferreira, PG (Author) Other; Munoz Aguirre, M (Author) Other; Reverter, F (Author) Other; Sa Godinho, CPS (Author) Other; Sousa, A (Author) Other; Amadoz, A (Author) Other; Sodaei, R (Author) Other; Hidalgo, MR (Author) Other; Pervouchine, D (Author) Other; Carbonell Caballero, J (Author) Other; Nurtdinov, R (Author) Other; Breschi, A (Author) Other; Amador, R (Author) Other; Oliveira, P (Author) Other; Cubuk, C (Author) Other; Curado, J (Author) Other; Aguet, F (Author) Other; Oliveira C (Author) FMUP; Dopazo, J (Author) Other; Sammeth, M (Author) Other; Ardlie, KG (Author) Other; Guigo, R (Author) Other

Journal

Title: Nature Communications

Vol. 9 No. 1

ISSN: 2041-1723

Publisher: Springer Nature

Indexing

ISI Web of Knowledge - 167 Citations

Scopus - 178 Citations

Scientific classification

CORDIS: Natural sciences > Biological sciences > Biology > Computational biology ; Technological sciences > Engineering > Computer engineering

FOS: Natural sciences > Computer and information sciences ; Natural sciences > Biological sciences

Other information

Authenticus ID: P-00N-MK1

DOI: 10.1038/s41467-017-02772-x

Abstract (EN): 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 postmortem 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.

Language: English

Type (Professor's evaluation): Dissemination

No. of pages: 15