Peter LoVerso

Abstract

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.

Library of Congress Subject Headings

Neurons--Research; Astrocytes--Research; Nucleotide sequence; Genetic transcription

Publication Date

4-30-2015

Document Type

Thesis

Student Type

Graduate

Degree Name

Bioinformatics (MS)

Department, Program, or Center

Thomas H. Gosnell School of Life Sciences (COS)

Advisor

Feng Cui

Advisor/Committee Member

Gary R. Skuse

Advisor/Committee Member

Gregory Babbitt

Comments

Physical copy available from RIT's Wallace Library at QP625.N89 L68 2015

2017 MS Thesis Honorable Mention Award recipient

Campus

RIT – Main Campus

Plan Codes

BIOINFO-MS

Download

Share

COinS