Date of Award

Spring 2020

Document Type

Thesis

Degree Name

Master of Science (MS)

Department

Bioinformatics

First Advisor

Petrella, Lisa N.

Second Advisor

Bansal, Naveen

Third Advisor

Maadooliat, Mehdi

Abstract

Quantitative analysis is very important for researchers to understand the molecular physiology underlying differential gene expression. High-throughput mRNA sequencing (RNA-seq) has become a standard method, which can be used in a wide variety of species and biological conditions to discover new genes and transcripts or measure levels transcript expression. The nematode Caenorhabditis elegans is an important model for the study of germ cell biology. For this thesis, RNA-Seq was performed on dissected germlines of Caenorhabditis elegans that were grown at either 20°C (ideal conditions) or 27°C (stress conditions) from two wildtype strains: JU1171 (thermotolerant) and LKC34 (thermosensitive). The goals of this research were to uncover four expression patterns that are different between these two strains under two different temperature conditions, which could potentially underlie the phenotypic difference when Caenorhabditis elegans are stressed. I performed and compared five different RNA-Seq pipelines, which include Cuffdiff, DESeq2, edgeR, limma, DESeq, starting with 16 raw sequencing fastq files, including experimental design, quality control, read alignment, expression quantification, differential gene expression, and enrichment analysis. My research resulted in both differential expression data and analyzed patterns of differentially expressed genes. I also did the enrichment analysis on the functions of genes under each pattern to uncover the different expression patterns between the two strains and two temperatures. From the result, we predict that increased apoptosis at elevated temperatures is protective for fertility. In the end, I discussed the drawbacks in the analysis that can be improved and mentioned additional analysis which can be added to the outcomes in the future.

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