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Gravitropic Signal Transduction: A Systems Approach to Gene Discovery

Shen, Kaiyu
http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1387467697

Abstract Details

2014, Doctor of Philosophy (PhD), Ohio University, Molecular and Cellular Biology (Arts and Sciences).
Gravity is an important stimulus for plants. Gravitropism, the plants' response to gravity, can be divided into three phases: gravity perception, signal transduction and response. Various theories have been proposed to explain the process of gravitropism, yet more genes are needed to elucidate the mechanism of gravitropic signal transduction. A transcriptome analysis, in combination with the Gravity Persistent Signal treatment, was performed to specifically study the genes involved in signal transduction. Analysis generated a list of 318 transcripts that were differentially expressed in plants that were reoriented with respect to gravity as compared to vertical controls. Based on the expression profiles and gene function annotations, five transcription factors, WRKY18, WRKY26, WRKY33, BT2 and ATAIB, were selected for further study. In addition to the standard analysis of differentially expressed genes, a systems approach was adopted to uncover more gravity related genes. A semi-supervised learning method was developed to find additional novel genes. This learning method took a set of 32 known gravity genes from the literature as well as a collection of heterogeneous annotation features, such as existing protein-protein interactions, and co-expression profiles. The learning classifier predicted a list of 50 genes that are functionally related to gravity signal transduction. Based on this list of genes, an interaction network was predicted based two complementary approaches: a dynamic Bayesian network and a time-lagged correlation coefficient. To increase confidence in the predication, genes/interactions that appeared in both networks were selected. This 'intersected' network provided 20 hub and bottleneck genes, fourteen of which had not been previously identified as involved in gravitropism. Such an approach provides a framework to extend current research in a more comprehensive manner, and serves a complementary to the traditional mutant/gene discovery model.
Sarah Wyatt, Dr. (Advisor)
Allan Showalter, Dr. (Committee Chair)
Lonnie Welch, Dr. (Committee Member)
Frank Horodyski, Dr. (Committee Member)
167 p.
Biology; Computer Science
Systems Biology; Semi-supervised machine learning; Gravitropism; Transcriptome analysis; Biological network

Recommended Citations

Citations

  • Shen, K. (2014). Gravitropic Signal Transduction: A Systems Approach to Gene Discovery [Doctoral dissertation, Ohio University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1387467697

    APA Style (7th edition)

  • Shen, Kaiyu. Gravitropic Signal Transduction: A Systems Approach to Gene Discovery. 2014. Ohio University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1387467697.

    MLA Style (8th edition)

  • Shen, Kaiyu. "Gravitropic Signal Transduction: A Systems Approach to Gene Discovery." Doctoral dissertation, Ohio University, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1387467697

    Chicago Manual of Style (17th edition)

ohiou1387467697
928
© 2013, all rights reserved.
This open access ETD is published by Ohio University and OhioLINK.