This action funds an NSF Postdoctoral Research Fellowship for FY 2010. The fellowship supports a research and training plan entitled "Evolution of the Saccharomyces cerevisiae genetic interaction network" for Janna Fierst. The host institution for this research is University of Oregon, and the sponsoring scientist is Patrick Phillips.
A central problem in biology concerns defining how genetic information and molecular processes are integrated to produce an organism. This requires understanding how selection, genetic drift and mutation shape the evolution of the genotype-phenotype map. Genomics and systems biological studies are rapidly producing data on the mechanisms underlying the genetic system. Most evolutionary theory, however, was developed before the advent of molecular genetics and the discovery that genes commonly interact in networks. Without additional theory to take such interactions into account, these data cannot be understood in an evolutionary framework and we cannot identify meaningful patterns. This project uses data on genetic interactions and gene expression in the Saccharomyces cerevisiae synthetic lethal genetic interaction network to build a theoretical model of network evolution. This model is being used to analyze the influence of selection, drift and mutation on network changes that are observed between two different strains of S. cerevisiae and the related yeast Schizosaccharomyces pombe.
Specific training goals include increasing bioinformatics and computational skills, and gaining familiarity with publicly available genomic and systems biological datasets. The broader impacts include creating a public database integrating gene expression and genetic interactions in S. cerevisiae, distributing a network evolution model, and training undergraduates in bioinformatics and computational biology through the University of Oregon summer program for undergraduate research (SPUR). The results expand evolutionary genetics theory and provide a theoretical framework in which genomic and systems biological patterns can be associated with evolutionary processes.
Research Findings: My main research projects at the conclusion of my fellowship are: 1) bioinformatic analysis of gene expression variation and genetic interactions in yeast; 2) developing machine learning techniques to identify dynamical relationships in biological networks; 3) modeling biological network evolution and developing methods to measure potential network evolution; and 4) genome and transcriptome data analysis and visualization in Caenorhabditis remanei. 1) We have mapped expression variation across genes, cells, populations and closely related species and found a negative correlation between these measures of variation and variance in genetic interactions. The mechanism of expression variation appears to be the relative probability of nucleosome occupancy. While this is a finding that has been published in previous work, this is the first time these patterns have been related to quantitative, genome-wide interaction distributions. We published these findings in the December issue of Genome Biology and Evolution. 2) We have identified a computational modeling structure common in artificial intelligence and machine learning that is also used in computational simulations of biological networks. We are using this machine learning structure as the framework for computational methods identifying dynamical relationships in biological networks, and are preparing a manuscript reviewing the history of computational models used in biological network modeling, neural network modeling and machine learning. 3) We were able to identify several control theory measures that describe the evolutionary potential of a biological network, and to study how the control structure of a biological network changes as the network evolves. 4) We have assembled a preliminary genome and transcriptome for one inbred laboratory strain of Caenorhabditis remanei, and are assembling a preliminary genome for a second inbred strain. We are currently preparing these results for publication. Activities: I attended the University of Oregon Center for Ecology and Evolutionary Biology retreat in the fall, and presented my dissertation research at a department seminar in early November. I audited Introduction to Scientific Computing at the University of Oregon in Fall 2010. I was selected for a travel grant to participate in the NSF Pan-American Studies Institute 'Scientific Computing in the Americas: the challenge of massive parallelism' organized through Boston University. I traveled to Valparaiso, Chile in January for this workshop and participated in lectures, lab sections and tutorials on scientific computing. In September 2011 I traveled to Lubeck, Germany to participate in the Workshop on Systems Biology and present my initial fellowship findings on gene interactions in yeast. In November 2011 I presented my initial fellowship findings at the Western Society for Naturalists meeting in Vancouver, Washington. In the spring of 2012 I took an online class on Machine Learning through Coursera. I advised two groups of computer science students through the University of Oregon Computational Sciences class. This class involves lectures and assignments on parallel computing paired with a guided parallel computing research project. I designed two research projects, one using parallel computing to accelerate biological network modeling and one using GPU parallel computing in machine learning techniques modeling biological data. I advised one undergraduate and one masters student in the first group and three undergraduates and one PhD student in the second group. The students worked independently and as a group, and we met weekly to read and discuss primary literature, discuss progress and research design and findings. In April 2012 I presented my Caenorhabditis remanei genome assembly at the Cold Spring Harbor Caenorhabditid meetings. In the summer of 2012 I began advising a group of four undergraduate students. They are working on a project documenting recent speciation in Caenorhabditid worms and I have been meeting monthly with the students to read and discuss primary literature, and to discuss research design, progress and findings. In the fall of 2012 I advised a PhD student on a network modeling project. Training and Development: Over the past 2 years I have developed my research skills in a number of ways. I have developed my computational skills through classes, workshops and research projects utilizing scientific computing and parallel computing. I have developed my bioinformatics skills by participating in workshops and research projects utilizing bioinformatics methods and scientific computing. I have participated in weekly lab meetings and paper discussions that have allowed me to develop my critical thinking and analysis, and verbal presentation skills. My professional development has been helped through these meetings, and by co-authoring grants and publications with my advisor. This has allowed me to develop my skills in planning and executing research projects. I have developed my mentoring skills through advising several student projects ranging from empirically-based undergraduate research to computational science projects involving masters and PhD students. I have advised a number of students in both biology and computer science, including students from traditionally underrepresented groups like women and people of color. These students have continued in both research and science and engineering careers.