Kaikki aineistot
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To investigate whether alterations in mitochondrial metabolism affect longevity in Drosophila melanogaster, we studied lifespan in various single gene mutants, using inbred and outbred genetic backgrounds. As positive controls we included the two most intensively studied mutants of Indy, which encodes a Drosophila Krebs cycle intermediate transporter. It has been reported that flies heterozygous for these Indy mutations, which lie outside the coding region, show almost a doubling of lifespan. We report that only one of the two mutants lowers mRNA levels, implying that the lifespan extension observed is not attributable to the Indy mutations themselves. Moreover, neither Indy mutation extended lifespan in female flies in any genetic background tested. In the original genetic background, only the Indy mutation associated with altered RNA expression extended lifespan in male flies. However, this effect was abolished by backcrossing into standard outbred genetic backgrounds, and was associated with an unidentified locus on the X chromosome. The original Indy line with long-lived males is infected by the cytoplasmic symbiont Wolbachia, and the longevity of Indy males disappeared after tetracycline clearance of this endosymbiont. These findings underscore the critical importance of standardisation of genetic background and of cytoplasm in genetic studies of lifespan, and show that the lifespan extension previously claimed for Indy mutants was entirely attributable to confounding variation from these two sources. In addition, we saw no effects on lifespan of expression knockdown of the Indy orthologues nac-2 and nac-3 in the nematode Caenorhabditis elegans.
Abstract Transcriptomic imputation approaches combine eQTL reference panels with large-scale genotype data in order to test associations between disease and gene expression. These genic associations could elucidate signals in complex genome-wide association study (GWAS) loci and may disentangle the role of different tissues in disease development. We used the largest eQTL reference panel for the dorso-lateral prefrontal cortex (DLPFC) to create a set of gene expression predictors and demonstrate their utility. We applied DLPFC and 12 GTEx-brain predictors to 40,299 schizophrenia cases and 65,264 matched controls for a large transcriptomic imputation study of schizophrenia. We identified 413 genic associations across 13 brain regions. Stepwise conditioning identified 67 non-MHC genes, of which 14 did not fall within previous GWAS loci. We identified 36 significantly enriched pathways, including hexosaminidase-A deficiency, and multiple porphyric disorder pathways. We investigated developmental expression patterns among the 67 non-MHC genes and identified specific groups of pre- and postnatal expression.