AtoI RNA editing does not change with age in the

Authors: Andrew P Holmes Shona H Wood Brian J Merry João Pedro de Magalhães

Publish Date: 2013/05/26

Volume: 14, Issue: 4, Pages: 395-400

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Abstract

RNA editing is a posttranscriptional process which results in base substitution modifications to RNA It is an important process in generating protein diversity through amino acid substitution and the modulation of splicing events Previous studies have suggested a link between genespecific reductions in adenosine to inosine RNA editing and aging in the human brain Here we demonstrate that changes in RNA editing observed in humans with age are not observed during aging in healthy rats Furthermore we identify a conserved editing site in rats in Cog3 We propose that either agerelated changes in RNA editing are specific to primates or humans or that they are the manifestation of disease pathology Since rodents are often used as model organisms for studying aging these findings demonstrate the importance of understanding speciesspecific differences in RNA biology during agingAdenosine to inosine AtoI RNA editing is a posttranscriptional process that alters the sequences of RNA molecules The adenosine deaminases ADAR and ADARB1 convert specific adenosine residues on RNA to inosine bases During translation sequencing and splicing inosine is recognized as guanosine Therefore AtoI RNA editing has important implications in altering specific amino acids miRNA targeting and in the modulation of alternative splicing Nishikura 2010Targets of AtoI RNA editing are often genes involved in neurotransmission in the central nervous system CNS although editing is known to occur in other tissues Changes in AtoI RNA editing have been implicated in the development of cancer inside and outside the CNS Cenci et al 2008 Galeano et al 2010 Paz et al 2007 Shah et al 2009 and in various neurodegenerative diseases such as dyschromatosis symmetrica hereditaria DSH amyotrophic lateral sclerosis ALS Alzheimer’s disease and Huntington’s disease In addition the process has implications in epilepsy depression schizophrenia and is associated with a greater risk of suicide Akbarian et al 1995 Farajollahi and Maas 2010 Maas et al 2006 More recently it was identified that single nucleotide polymorphisms in ADARB1 and ADARB2 are associated with extreme longevity in humans Sebastiani et al 2009 Furthermore it was recently observed that editing of the p53inducible Cyfip2 Cytoplasmic FMR1 interacting protein 2 significantly declines with age in human cerebral cortex However editing of Gabra3 Gammaaminobutyric acid A receptor subunit alpha 3 was found not to decline with age in humans This suggests that RNA editing efficiency may be linked to aging in a genespecific manner Nicholas et al 2010Humans are known to have far more targets of AtoI RNA editing than rodents due to the spread of Alu repeats during human evolution Neeman et al 2006 However there are several known targets of AtoI RNA editing that are conserved from rodents to humans Levanon et al 2005 The brown rat Rattus norvegicus is a wellestablished model species for studying aging and has been used in neurological research for many years The brown rat is held as a model for mammalian behavioral and neurodegenerative studies Jacob 1999 Wood et al 2013 Comparative approaches are essential to fully understand aging hence it is crucial to establish differences between humans and rodents to assess their importance to inform about human aging Functional alterations through RNA editing or other means may also contribute to species differences in aging Since studies linking RNA editing to aging have only been reported in humans this study aimed to investigate whether the effect of age on RNA editing efficacy is conserved in the brown ratRat tissues used in this study were supplied from a previous experiment Merry et al 2008 All animal husbandry procedures undertaken in this study were carried out in accordance with the provisions of the United Kingdom Animals Scientific Procedures Act 1986 Male BN rats SubstrainBN/SsNOlaHSD were obtained from Harlan UK at 21–28 days of age and maintained under barrier conditions on a 12 h light 12 h dark cycle 0800–2000 The health status of the rats was monitored at regular intervals through the screening of sentinel animals All rats were fed ad libitum and sacrificed at 6 12 and 28 months of age None of the animals exhibited any signs of pathology when sacrificed Each age group had six rats from which brain samples were taken flash frozen and stored at −80 °CRNA was extracted from cerebral cortex of rats using the RNeasy lipid tissue kit Qiagen The quality of the extracted RNA was assessed using the Agilent 2100 Bioanalyzer all RNA integrity numbers RINs were above 80 indicating that the RNA had minimal degradation For RNA extraction from brain tissue RIN 8 represents a high quality threshold Bettscheider et al 2011 The samples were pooled in pairs leaving 3 samples per age group Ribosomal RNA was removed from the pooled samples using the Eukaryote Ribominus Kit Invitrogen and confirmed with the Agilent 2100 BioanalyzerRNAseq data was generated by SOLiD sequencing Applied Biosystems from these samples in a previous study Wood et al 2013 The RNAseq results from the SOLiD system were output as color space FASTA and quality files These were converted into FASTQ format using a Python script from Galaxy http//maing2bxpsuedu/ The FASTQ files were mapped to the Ensembl release 65 rat reference genome RGSC 34 assembly May 2010 gene build using Bowtie Langmead et al 2009 and settings appropriate to SOLiD data For each sample ~336 million reads were generated range 295–398 million reads On average 167 million reads per sample were mapped to the reference genome range 138–214 million reads ~50  of reads generated were mapped All data have been submitted to GEO under the accession GSE34272 Wood et al 2013 A mismatch analysis was performed on the aligned reads using Bambino in order to generate candidate editing sites Edmonson et al 2011 These candidates were selected using custom Python scripts for AG mismatches within exons in genes on the positive strand and TC mismatches on the negative strand Results were narrowed by selecting for nonsynonymous mismatches and for those with a high number of read counts Selected candidate targets were reverse transcribed using MMLV reverse transcriptase Invitrogen and amplified by PCR using rTaq TaKaRa Editing levels were then analyzed by Sanger sequencing using the 3730 DNA Analyzer Applied Biosystems and quantifications were calculated by peak height analysis Eggington et al 2011

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