Profiles of Grad Students & Postdocs in 3CPG labs
Graduate Students
Andrea Moreno Switt
Wiedmann Laboratory
Food Science
From: Concepcion, Chile
Undergraduate: Concepcion University, Chile. Veterinary Doctor, 2001
Masters: Concepcion University, Chile. M.S. Microbiology, 2007
Statement
I am a Ph.D. candidate in Food Science with concentration in Food Microbiology. I was born and went to school in Chile. There I received a Veterinary Doctor and a M.S. in Microbiology from Concepcion University. My research interests include food safety, zoonosis, antimicrobial resistance, and food safety issues in international trade. I chose Cornell for their people, culture, resources, diversity, and prestige. At Cornell I have found all the opportunities that I need to learn and develop to my full potential. I am attracted to comparative genomics because it provides important tools for understanding the evolution and spread of foodborne pathogens. Using comparative genomics will help to reduce food contamination and zoonotic diseases.
Research
The focus of my research is the foodborne pathogen Salmonella enterica. This pathogen is the leading cause of deaths and hospitalizations due to foodborne illness. Salmonella is very diverse and mobile elements (e.g., plasmids, phages, transposons) are important drivers of Salmonella evolution. The goals of my research are to understand the roles of free-living phages in the ecology and distribution of Salmonella serotypes, and to analyze mobile elements inserted in the chromosome to elucidate how these elements are related with the emergence of new pathogenic strains. To accomplish these goals I use comparative genomics and phylogenetic analysis to analyze more than 100 Salmonella and phages that we have collected and sequenced.
Jaaved Mohammed
Siepel Laboratory (joint with Dr. Eric Lai’s lab at Memorial Sloan-Kettering Cancer Center)
Computational Biology
From: Trinidad and Tobago
Undergraduate: The University of Florida, Gainesville, FL. B.S. Mathematics and Computer Science, 2005.
Statement
As a youth, I dreamed about having a career working with computers. However, growing up on the island of Trinidad, computers were non-existent at home and at school. When I was given the opportunity to live and study in the US, I jumped at the opportunity to pursue my dream. Even though my undergraduate experience and first job in industry were quite fulfilling, I still felt there were more important questions to be answered, so I decided to pursue graduate school. Of all the interdisciplinary fields I was exposed to, computational biology seemed the best fit. Most of my interest in the area of genomics stemmed from the popular media. The human genome had just been sequenced and the potential of the data was vast. The Tri-Institutional Training Program in Computational Biology and Medicine allowed me to explore work in genomics done in several research labs, however it was the strengths of the Department of Biological Statistics and Computational Biology and its grounded commitment and contribution to the field which motivated me to join the lab of Dr. Adam Siepel.
Research
My goals within genomics have converged to the study of microRNA (miRNA) evolution. Using methods from comparative genomics guided by principles of molecular evolution, I am investigating micro- and macro-patterns of miRNA evolution within Drosophila. These include topics such as deciphering the conservation signatures within the miRNA hairpin or understanding the importance of miRNA gene fluctuation across the species tree. Several key observations of miRNA evolution have already been published and these facts have unequivocally enhanced our understanding of miRNA function. However, with the introduction of high-throughput RNA sequencing and enhances in molecular methods, the field of miRNA biology continues to uncover new species of miRNA genes, which are located in more esoteric genomic arrangements, are newly-evolved, and are maturated via distinct biogenesis mechanisms. A deeper understanding of the evolutionary signatures unique to these new classes remains to be explored as part of my thesis work. It is with hope that whatever features which are uncovered within Drosophila will be similar to miRNAs in other eukaryotes.
Jacob E. Crawford
Lazzaro Laboratory
Entomology
From: Baltimore, MD
Undergraduate: Georgetown University, Washington, D.C. B.S. Biology, 2003.
Statement
I am interested in the evolutionary processes that generate, shape, and maintain the variation observed in natural systems. Prior to arriving at Cornell, I focused on variation on an ecological scale through studies of life history evolution of an invasive and rapidly evolving container-breeding mosquito, and ecological studies of the phenotypic manifestations of insipient speciation in African malaria mosquitoes. As a graduate student at Cornell, I shifted my focus to evolution at the molecular level, using population genomic methods to test hypotheses related to adaptation and the complex ecology of African malaria mosquitoes. I found the population genomic approach to be especially appealing because it allowed me to probe both short and long-term evolutionary patterns through comparisons to well developed evolutionary models. As the home to many experts in the field of population genomics, Cornell offers a rich environment for learning both population genomics theory and methods, making it an ideal choice for my graduate work.
Research
The goal of my graduate research is to understand the short and long-term evolutionary forces shaping patterns of genetic variation across the genomes of Anopheles mosquito vectors of human malaria. The close biological association with the parasite and the complex population structure and history make this system a potentially fertile opportunity to study the genomic manifestations of pathogen-related natural selection as well as complex demography involving on-going speciation and historical size shifts. I use population genetic theory to test hypotheses of demography and selection, through applications to both intra- and inter-species genomic datasets. I am also interested in the prospects of using next-generation sequencing in non-model population genomic studies and use computational simulations to understand potential biases and shifts in statistical power under a variety of experimental structures involving next-generation sequencing.
Post Docs
Erin Kelleher
Barbash Laboratory
From: Mclean, VA
Undergraduate: University of Virginia, Charlottesville, VA. B.S. Biology, B.A. Archaeology, 2003
PhD: University of Arizona, Tucson, AZ. Ecology and Evolutionary Biology, 2009
Statement
As a graduate student, I was fortunate to participate in a fellowship program that included students with interests in functional, computational, and evolutionary genomics. This interdisciplinary environment exposed me to the breadth of genomic approaches and motivated me to better integrate them with my own research interests. I decided to pursue a post-doc at Cornell both out of a specific interest in working with my mentor, Daniel Barbash, but also because of the intellectually and technologically rich environment, particularly for those with interests in evolutionary genomics. Cornell is highly collaborative, with initiatives such as the Cornell Center for Population Genomics and Vertebrate Genomics serving to support and enrich these collaborations. Furthermore, as a community the Cornell Life Sciences operates on the forefront of existing technology, investing in cutting edge instrumentation and computational resources.
Research
I am broadly interested in intragenomic coevolution, the process through which different components of the same genome influence each other’s evolutionary history. At Cornell, my research focuses on the piRNA pathway, a small RNA silencing pathway that regulates the selfish propagation of transposable elements in metazoan germlines. In the fruit-fly Drosophila, many piRNA proteins are known to evolve rapidly, a pattern that may reflect their adaptation to the dynamic pool of transposable elements inhabiting the genome. The goal of my research is to better understand both the functional consequences of adaptive protein evolution in the piRNA pathway, and the selective forces that underlie this process. I have used next generation sequencing of small RNA and mRNA pools in two species of Drosophila and their interspecific hybrids to describe interspecific divergence in piRNA pathway function. I furthermore am applying these approaches to transgenic D. melanogster harboring piRNA proteins from other Drosophila species to understand how individual piRNA proteins have changed in function.
Angela C. Poole
Ley Laboratory
From: Baton Rouge, LA
Undergraduate: California Institute of Technology, Pasadena, CA. B.S. Engineering and Applied Sciences, 1999.
PhD: University of Washington, Seattle, WA. Genome Sciences, 2010.
Statement
Hailing from one of the fattest states in the Union, I have always had a keen interest in factors contributing to the growing obesity epidemic. After college, I worked as a research associate, analyzing the effects of host genotype on macronutrient preference using a mouse model. At the time, I definitely never considered the involvement of gut microbial symbionts in obesity or other metabolic disorders. During graduate school, I read about exciting genomics research being done on the microscopic populations on and within our own bodies, known as microbiomes, and interestingly, the correlation of gut microbiome composition with obesity. Upon learning that a dynamic new investigator at the forefront of this field was at Cornell, I quickly applied to do a postdoc with her.
Research
My main research interest is the effect of host genotype on microbiomes, the microbes inhabiting the host and their combined genomes. At present, I am investigating how the copy number of AMY1, the gene encoding the amylase enzyme, which breaks down starch, correlates with gut and oral microbiome composition. AMY1 gene copy number is variable in human populations and appears to have been shaped by selection: historically agricultural populations have a higher gene copy number of AMY1 on average than traditional hunter-gatherer populations, which typically consume less starch. Amylase is also encoded by a number of microbes found in the human gut. I am comparing the microbiomes of people with high or low AMY1 copy number. Using 454 pyrosequencing on PCR amplicons from the hypervariable regions of the 16S rRNA genes, I will determine and compare gut microbiome compositions and elucidate differences in their capacity to break down starch. My goal is to use this knowledge to devise strategies for manipulating the gut microbiome to treat or prevent metabolic disorders such as type 2 diabetes and obesity.
Matthew Rasmussen
Siepel Laboratory
From: Eden Prairie, MN
Undergraduate: University of Minnesota, Minneapolis, MN. B.S. Math and Computer Science, 2004.
PhD: Massachusetts Institute of Technology, Cambridge, MA. Computer Science.
Statement
I have always been interested in computers and programming. When I was younger, I used teach myself math so I could write more realistic computer games. Later in college, I learned about the Human Genome Project and how computation was playing a major role in this new emerging science. Intrigued, I got involved in several early research opportunities and decided to make evolutionary genomics the focus of my Ph.D. These days, I find myself hooked on learning more about genomes and evolution, and I have found that my background in algorithms and computation has applications in almost every part of the field. Cornell has provided an exciting environment to continue my research. I have had the opportunity to meet many talented people and the chance to work on lots of interesting problems and data.
Research
I am interested in developing new computational methods for several problems within phylogenetics and population genetics. I am particularly focused on new ways of modeling evolutionary history that are computationally efficient while still properly capturing the complexities of DNA evolving within populations. At Cornell, I have worked on efficient algorithms for inferring the Ancestral Recombination Graph (ARG), a data structure representing population history that is central to several active areas of research, such as demography, selection, and association mapping. Using a more principled model for evolutionary history may provide greater power in distinguishing positive and negative selection as well as increased power for association mapping. Previously, I have also developed models for how incomplete lineage sorting can interact with genomic duplications and deletions, then studied the implications of this effect on estimating duplication-loss rates, orthology, and paralogy.