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Abstract
BackgroundGenome-wide surveys have detected cis-acting quantitative trait loci altering levels of RNA transcripts (RNA-eQTLs) by associating SNV alleles to transcript levels. However, the sensitivity and specificity of detection of cis- expression quantitative trait loci (eQTLs) by genetic approaches, reliant as it is on measurements of transcript levels in recombinant inbred strains or offspring from arranged crosses, is unknown, as is their relationship to QTL’s for complex phenotypes.ResultsWe used transcriptome-wide differential allele expression (DAE) to detect cis-eQTLs in forebrain and kidney from reciprocal crosses between three mouse inbred strains, 129S1/SvlmJ, DBA/2J, and CAST/EiJ and C57BL/6 J. Two of these crosses were previously characterized for cis-eQTLs and QTLs for various complex phenotypes by genetic analysis of recombinant inbred (RI) strains. 5.4 %, 1.9 % and 1.5 % of genes assayed in forebrain of B6/129SF1, B6/DBAF1, and B6/CASTF1 mice, respectively, showed differential allelic expression, indicative of cis-acting alleles at these genes. Moreover, the majority of DAE QTLs were observed to be tissue-specific with only a small fraction showing cis-effects in both tissues. Comparing DAE QTLs in F1 mice to cis-eQTLs previously mapped in RI strains we observed that many of the cis-eQTLs were not confirmed by DAE. Additionally several novel DAE-QTLs not identified as cis-eQTLs were identified suggesting that there are differences in sensitivity and specificity for QTL detection between the two methodologies. Strain specific DAE QTLs in B6/DBAF1 mice were located in excess at candidate genes for alcohol use disorders, seizures, and angiogenesis previously implicated by genetic linkage in C57BL/6J × DBA/2JF2 mice or BXD RI strains.ConclusionsVia a survey for differential allele expression in F1 mice, a substantial proportion of genes were found to have alleles altering expression in cis-acting fashion. Comparing forebrain and kidney, many or most of these alleles were tissue-specific in action. The identification of strain specific DAE QTLs, can assist in assessment of candidate genes located within the large intervals associated with trait QTLs.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-2922-9) contains supplementary material, which is available to authorized users.
Highlights
Genome-wide surveys have detected cis-acting quantitative trait loci altering levels of RNA transcripts (RNA-expression quantitative trait loci (eQTL)) by associating single nucleotide variants (SNV) alleles to transcript levels
Genome-wide identification of differential allele expression (DAE) QTLs in forebrain and kidney of F1 mice by RNA-Seq Reciprocal crosses were made between C57BL/6J (B6) and three other inbred strains: 129S1/SvlmJ (129S), DBA/2J (DBA), and CAST/EiJ (CAST)
Strain-specific alleles were validated through exome sequencing of the parental mouse strains and by comparison to the Sanger mouse genome resource (The VCF file 20111102-snps-all.annotated.vcf.gz was downloaded from ftp://ftp-mouse.sanger.ac.uk/ REL-1105) to ensure that only genuine SNVs were interrogated (Additional file 1: Table S2)
Summary
Genome-wide surveys have detected cis-acting quantitative trait loci altering levels of RNA transcripts (RNA-eQTLs) by associating SNV alleles to transcript levels. The sensitivity and specificity of detection of cis- expression quantitative trait loci (eQTLs) by genetic approaches, reliant as it is on measurements of transcript levels in recombinant inbred strains or offspring from arranged crosses, is unknown, as is their relationship to QTL’s for complex phenotypes. Cis-regulatory elements modulating transcript expression are usually located nearby or within genes, but at the minimum are on the same chromosome. Genetic variations in cis-regulatory elements located anywhere upstream, downstream, within introns, and as well as in the 5’ and 3’ un-translated regions of genes, and even at considerable distances from genes, can alter transcription, mRNA stability, mRNA processing efficiency, or mRNA isoform expression [2]. The importance of genomic elements that regulate gene expression was highlighted in a series of studies arising from the ENCODE project, suggesting that a significant proportion of the human genome might regulate gene expression [3]
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