July 28, 2015–Dr. Liang Sun’s recent successful dissertation defense marked an important milestone, both for him and for the Bioinformatics Graduate program.
Dr. Sun is the first student to graduate from the Bioinformatics & Systems Biology PhD Program, which was launched in Fall 2012.
His dissertation, performed under the supervision of Dr. Carl Schmidt, Professor of Animal and Food Sciences, was focused on understanding the molecular mechanisms underlying heat stress.
Heat-related stress causes massive economic losses for the US livestock industries and is one of the greatest challenges to poultry production worldwide. However, heat regulation is a complicated process and its exact molecular mechanism is not fully understood.
Dr. Sun used RNA-Seq to identify heat stress responsive genes in the male white-leghorn chicken hepatocellular (LMH) cell line. This created a large gene list – 812 to be exact. To understand and interpret how these genes may play a role in the heat stress response, Dr. Sun turned to bioinformatics tools.
One approach to understanding the underlying biology of large gene lists is to group the responsive genes to knowledge bases such as pathways. However, existing popular pathway databases, such as KEGG and Reactome, do not have the complete chicken pathway data.
Dr. Sun expanded on the approach used by Reactome, a popular human centric metabolic and signaling pathway database that relies on orthology between genomic sequences to predict pathways in other species. He did this by using orthology information based on transcriptome data to annotate chicken pathways (Gallus Gallus Reactome Plus) and he created a web-based chicken pathway analysis and visualization tool.
Another approach for interpreting large gene datasets is to associate genes and informative terms (iTerm) that are obtained from the biomedical literature using the eGIFT text-mining system. However, examining large lists of iTerm and gene pairs is a daunting task. To assist with this task, Dr. Sun developed WebGIVI, an interactive web-based visualization tool to explore gene:iTerm pairs.
Using these newly developed bioinformatics tools, Dr. Sun was able to perform a transcriptome analysis of heat stressed LMH cells and further our understanding of molecular mechanisms underlying stress response in chickens.
In addition to his research success, Dr. Sun also served as the Secretary for the Bioinformatics Student Association (BiSA).
“We’re very proud of Dr. Sun’s achievements. He is a model student for the program, excelled not only in his academic pursuit, but also as a student leader,” said Dr. Cathy Wu, director of the Center for Bioinformatics and Computational Biology and graduate director of the PhD program.
Given the success of Dr. Sun’s PhD studies, it is no surprise that Dr. Liang has already been offered and accepted a position to work with the Samuel Roberts Noble Foundation as a Bioinformatics Analyst & Programmer in the Computing Services Department of the Administrative Division.
About the Program
The PhD in Bioinformatics and Systems Biology is offered as a university-wide interdisciplinary graduate program with scientific curriculum that builds upon the research and educational strength from departments across the Colleges of Engineering (CoE), Arts & Sciences (CAS), Agriculture & Natural Resources (CANR), and Earth, Ocean & Environment (CEOE). The Center for Bioinformatics and Computational Biology (CBCB) administers the PhD program and coordinates with the individual Departments involved in the program.
The program aims to train the next-generation of researchers and professionals who will play a key role in multi- and interdisciplinary teams, bridging life sciences and computational sciences. Students receive training in experimental, computational and mathematical disciplines through their coursework and research. Students who complete this degree will be able to generate and analyze experimental data for biomedical research, as well as develop physical or computational models of the molecular components that drive the behavior of the biological system.