The overarching goal of my research unfolds over three aims: (i) evaluating circRNAs and their predicted impact on transcriptional regulatory networks in cell-specific RNAseq data; (ii) developing a novel solution for de novo detection of full length circRNAs as well as in silico validation of selected circRNA junctions using assembly; and (iii) application of these assembly based detection and validation workflows, and integrating existing tools, to systematically identify and characterize circRNAs in functionally distinct human brain regions. To this end, I have developed novel bioinformatics workflows that are applicable to non-polyA selected RNAseq datasets and can be used to characterize circRNA expression across various sample types and diseases. Further, I establish a reference dataset of circRNA expression profiles and regulatory networks in a brain region-specific manner. This resource along with existing databases such as circBase will be invaluable in advancing circRNA research as well as improving our understanding of their role in transcriptional regulation and various neurological conditions.
Recent epigenetic association studies have identified a new gene, ANK1, in the pathogenesis of Alzheimer’s disease (AD). Although strong associations were observed, brain homogenates were used to generate the data, introducing complications because of the range of cell types analyzed. In order to address the issue of cellular heterogeneity in homogenate samples we isolated microglial, astrocytes and neurons by laser capture microdissection from CA1 of hippocampus in the same individuals with a clinical and pathological diagnosis of AD and matched control cases. Using this unique RNAseq data set, we show that in the hippocampus, ANK1 is significantly (p<0.0001) up-regulated 4-fold in AD microglia, but not in neurons or astrocytes from the same individuals. These data provide evidence that microglia are the source of ANK1 differential expression previously identified in homogenate samples in AD.