bioRxivImmunologyPreprint
Shared Transcriptomic Signatures of Inflammaging Among Diverse Strains of Drosophila melanogaster
Abstract
BackgroundA prominent hallmark of aging is inflammaging--the increased expression of innate immune genes without identifiable infection. Model organisms with shorter lifespans, such as the fruit fly, provide an essential platform for probing the mechanisms of inflammaging. Multiple groups have reported that, like mammalian models, old flies have significantly higher levels of expression of anti-microbial peptide genes. However, whether some of these genes--or any others--can serve as reliable markers for assessing and comparing inflammaging in different strains remains unclear. Methods and ResultsWe compared RNA-Seq datasets generated by different groups. Although the fly strains used in these studies differ significantly, we found that they share a core group of genes with strong aging-associated expression. In addition to anti-microbial peptide genes, we identified other genes that have prominently increased expression in old flies, especially SPH93. We further showed that machine learning models can be used to predict the "inflammatory age" of the fruit fly. ConclusionA core group of genes may serve as markers for studying inflammaging in Drosophila. RNA-Seq profiles, in combination with machine-learning models, can be applied to measure the acceleration or deceleration of inflammaging.
- organism: Drosophila
- assay: bulk RNA-seq
- research focus: cell type annotation
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: machine learning (classical)
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