학술논문

Alternative cleavage and polyadenylation of genes associated with protein turnover and mitochondrial function are deregulated in Parkinson’s, Alzheimer’s and ALS disease
Document Type
article
Source
BMC Medical Genomics, Vol 12, Iss 1, Pp 1-14 (2019)
Subject
Alternative polyadenylation
Neurodegenerative disease
Internal medicine
RC31-1245
Genetics
QH426-470
Language
English
ISSN
1755-8794
Abstract
Abstract Background Transcriptome wide changes have been assessed extensively during the progression of neurodegenerative diseases. Alternative polyadenylation (APA) occurs in over 70% of human protein coding genes and it has recently been recognised as a critical regulator of gene expression during disease. However, the effect of APA in the context of neurodegenerative diseases, to date, has not been widely investigated. Dynamic Analysis of Alternative Polyadenylation from RNA-seq (DaPars) is a method by Xia and colleagues [Nat Commun. 5:5274, 2014] to investigate APA using standard RNA-seq data. Here, we employed this method to interrogate APA using publicly available RNA-seq data from Alzheimer’s disease (AD), Parkinson’s disease (PD) and Amyotrophic Lateral Sclerosis (ALS) patients and matched healthy individuals. Results For all three diseases, we found that APA profile changes were limited to a relative small number of genes suggesting that APA is not globally deregulated in neurodegenerative disease. However, for each disease phenotype we identified a subgroup of genes that showed disease-specific deregulation of APA. Whilst the affected genes differ between the RNA-seq datasets, in each cohort we identified an overrepresentation of genes that are associated with protein turnover pathways and mitochondrial function. Conclusions Our findings, while drawn from a relatively small sample size, suggest that deregulation of APA may play a significant role in neurodegeneration by altering the expression of genes including UBR1 and OGDHL in AD, LONP1 in PD and UCHL1 in ALS. This report thus provides important novel insights into how APA can shape neurodegenerative disease characteristic transcriptomes.