Whole Transcriptome RNA-Seq Reveals Drivers of Pathological Dysfunction in a Transgenic Model of Alzheimer’s Disease

Abstract

Alzheimer’s disease (AD) affects more than 55 million people worldwide, yet current theories cannot fully explain its aetiology. Accordingly, gene expression profiling has been used to provide a holistic view of the biology underpinning AD. Focusing primarily on protein-coding genes, such approaches have highlighted a critical involvement of microglia-related inflammatory processes. Simultaneous investigation of transcriptional regulators and noncoding RNA (ncRNA) can offer further insight into AD biology and inform the development of disease-modifying therapies. We previously described a method for whole transcriptome sampling to simultaneously investigate protein-coding genes and ncRNA. Here, we use this technique to explore transcriptional changes in a murine model of AD (15-month-old APP/PS1 mice). We confirmed the extensive involvement of microglia-associated genes and gene networks, consistent with literature. We also report a wealth of differentially-expressed non-coding RNA — including microRNA, long non-coding RNA, small nuclear and small nucleolar RNA, and pseudogenes — many of which have been overlooked previously. Transcription factor analysis determined that six transcription factors likely regulate gene expression changes in this model ( Irf8 , Junb , c-Fos , Lmo2 , Runx1 , and Nfe2l2 ). We then utilised validated miRNA-target interactions, finding 60 interactions between 15 miRNA and 42 mRNA (messenger RNA) with largely consistent directionality. Furthermore, we found that eight transcription factors ( Clock , Lmo2 , Runx1 , Nfe2l2 , Egr2 , c-Fos , Junb , and Nr4a1 ) are likely responsible for the regulation of miRNA expression. Taken together, these data indicate a complex interplay of coding and non-coding RNA, driven by a small number of specific transcription factors, contributing to transcriptional changes in 15-month-old APP/PS1 mice.

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