UNDERSTANDING GENOME-WIDE GENE REGULATION IN PROKARYOTES USING OMICS DATA

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Seyedi Tabari, S. E. (2016). UNDERSTANDING GENOME-WIDE GENE REGULATION IN PROKARYOTES USING OMICS DATA. Unc Charlotte Electronic Theses And Dissertations.
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Abstract

Gene annotation is a critical step for understanding functions of genomes and host organisms. However, accurately annotating thousands of sequenced genomes can be a challenging task. Further, although gene transcriptional regulation is crucial for many important biological functions of cells, our understanding of the complexity of this process in even prokaryotes is still limited. This dissertation addressed both of these problems. First, we developed a fast and scalable tool, PorthoMCL for annotating gene functions through identifying orthologous genes in a large number of prokaryotic genomes. Using this tool, we have predicted orthologous genes in the thousands of sequenced prokaryotic genomes for public use. Second, we systematically investigated the complexity of transcriptomes in E. coli K12 in response to a variety of environmental changes. By adopting a model for alternate splicing isoforms in eukaryotes, we revealed that ~22% of operons exhibited different forms of transcriptional units. i.e., alternative operon utilizations, and ~36% operons displayed varying transcriptional levels of their genes, i.e., dynamic operon utilizations, at different growth phases and culture conditions. Moreover, by simultaneously profiling directional transcriptomes and proteomes of E. coli K12 cells, we found that a varying portion of genes had antisense RNA (asRNAs) transcription in a growth phase- and culture condition-dependent manner. The detected asRNAs were generally short and overlapped the previously identified asRNAs. Intriguingly, the correlation between genes’ protein levels and mRNA levels was disrupted by increased relative expression levels of asRNA to mRNA, suggesting that asRNA may play an important role in gene expressional regulation.

Details
Author

Seyedi Tabari, Seyed Ehsan

Title

UNDERSTANDING GENOME-WIDE GENE REGULATION IN PROKARYOTES USING OMICS DATA

Physical Description

1 online resource (101 pages) : PDF

Date

2016

Degree Granting Institution

University of North Carolina at Charlotte

Abstract

Gene annotation is a critical step for understanding functions of genomes and host organisms. However, accurately annotating thousands of sequenced genomes can be a challenging task. Further, although gene transcriptional regulation is crucial for many important biological functions of cells, our understanding of the complexity of this process in even prokaryotes is still limited. This dissertation addressed both of these problems. First, we developed a fast and scalable tool, PorthoMCL for annotating gene functions through identifying orthologous genes in a large number of prokaryotic genomes. Using this tool, we have predicted orthologous genes in the thousands of sequenced prokaryotic genomes for public use. Second, we systematically investigated the complexity of transcriptomes in E. coli K12 in response to a variety of environmental changes. By adopting a model for alternate splicing isoforms in eukaryotes, we revealed that ~22% of operons exhibited different forms of transcriptional units. i.e., alternative operon utilizations, and ~36% operons displayed varying transcriptional levels of their genes, i.e., dynamic operon utilizations, at different growth phases and culture conditions. Moreover, by simultaneously profiling directional transcriptomes and proteomes of E. coli K12 cells, we found that a varying portion of genes had antisense RNA (asRNAs) transcription in a growth phase- and culture condition-dependent manner. The detected asRNAs were generally short and overlapped the previously identified asRNAs. Intriguingly, the correlation between genes’ protein levels and mRNA levels was disrupted by increased relative expression levels of asRNA to mRNA, suggesting that asRNA may play an important role in gene expressional regulation.

Genre

doctoral dissertations

Subjects--Topics

Bioinformatics
Information science
Biometry

Degree

Ph.D.

Subject Area

Bioinformatics

Advisor(s)

Su, Zhengchang

Committee Members

Fodor, Anthony
Guo, Jun-tao
Shi, Xinghua
Song, Bao-Hua

Degree Note

Thesis (Ph.D.)--University of North Carolina at Charlotte, 2016.

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Rights Holder Information

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Identifier

SeyediTabari_uncc_0694D_11219

Permalink

http://hdl.handle.net/20.500.13093/etd:64