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Trans-species Transcriptomic Comparison of in vitro and in vivo Neural Cells

Posted on:2016-08-31Degree:M.SType:Thesis
University:Rochester Institute of TechnologyCandidate:LoVerso, PeterFull Text:PDF
GTID:2474390017484228Subject:Bioinformatics
Abstract/Summary:PDF Full Text Request
RNAseq has recently evolved into a powerful tool for the analysis and comparison of different cell types within and across organisms, and allows for accurate, reproducible measurements of the transcriptome of these cells. Here, RNA from three different neural cells types (oligodendrocyte progenitor cells, neurons, and astrocytes) in rats (R. norvegicus ) are grown in vitro then sequenced and aligned to the rn5 genome assembly. Furthermore, RNA from two different human ( H. sapiens) neural cell types (neurons and astrocytes) grown in vitro were also sequenced and aligned to the hg38 assembly. An in vivo dataset of RNAseq reads was identified from literature, containing data for all three cell types in mice. These reads were aligned to the mm10 genome assembly, the annotation of which was then converted into its orthologous coordinates for rnor5 and hg38. The expression of all data was then quantified in terms of the mouse annotation, normalized, and compared to determine differences in expression.;Differential gene expression and pathway analysis across these data have identified a number of pathways and genes which are significantly differently expressed and enriched in in vivo cells as compared to in vitro, as well as specific differences between cell types, showing that especially when targeting certain diseases in vitro cells should not be used as a drop-in replacement for in vivo. Similarities and differences were also observed between this RNA-seq data and the microarray data presented in previous in vitro/in vivo studies involving the same cell types and species. These data are presented and discussed along with the first comprehensive protocol for comparing RNAseq data between species.
Keywords/Search Tags:Cell, Vitro, Vivo, Data, Neural
PDF Full Text Request
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