Profiles of Grad Students & Postdocs in 3CPG labs
Clark Laboratory (joint with John Fitzpatrick's lab at the Cornell Lab of Ornithology)
I obtained my undergraduate degree in biochemistry. When I started college, I was primarily interested in chemistry and worked in a number of different chemistry labs. Then an ornithology class reawakened my childhood dream to become a field biologist, and my growing interest in evolutionary biology led me to join an avian evolutionary genetics lab. My honors thesis project focused on population genetics of the regulatory regions of genes involved in the response to bacterial infection. Since coming to Cornell, I have had the opportunity to learn genomic and bioinformatic approaches that have greatly expanded the scope of my research. My current research interests include evolutionary and population genetics, conservation genomics, and ornithology.
I'm interested in characterizing the genetic basis of fitness-related traits and in elucidating the evolutionary dynamics of declining populations in the wild. My research combines modern genomic technologies with a long-term demographic study of the federally threatened Florida Scrub-Jay. I have used next-generation sequencing to build genomic resources for this species. By combining genomic data with the available pedigree and demographic data, my goals are to identify regions of the genome associated with fitness-related traits and to investigate the relative roles of fundamental evolutionary processes on genome-wide dynamics of neutral and adaptive variation. In addition, I am developing bioinformatic methods for analyzing next-generation data for non-model organisms.
I am interested in studying bacterial natural products, such as antibiotics and anticancer compounds, in a systematic, genome-based framework. The main source of natural products in bacteria is a genus called Streptomyces. During my time at Cornell I was studying the population genetics of Streptomyces. The main goal of this work was to determine the main population genetic parameters for one study population, and to determine criteria for species delineation in Streptomyces, if such a designation was appropriate at all. This led to an interest in species definitions overall, which I pursued with some theoretical work and simulations. The nature of this research has also forced me to gain programming skills, something which I now very much enjoy.
My current research builds upon the population genetic and evolutionary work I performed as a grad student. I am now working as an IGB fellow at the University of Illinois at Urbana-Champaign, creating a systematic framework for studying natural product biosynthetic gene cluster diversity. This work is creating new natural product discovery opportunities, allowing us to use correlations between large genomic and mass spectrometric data sets to identify novel potential drugs, even if they are missed by phenotypic screens with crude microbial extracts. Natural products exist because they have bioactivity of some sort, so simply identifying which compounds are in these potential drug classes is an important first step. I am also working to understand the ecology of streptomycetes, from habitat preferences to the total diversity contained within the genus.
Ley and Clark Laboratory
The first time I was exposed to computer programming was at the age of twelve. It took no more that a few lines of code to convince me of the powers and possibilities that computers held. While I was pursuing a degree in computer science, I had several experiences in experimental biology labs ranging from molecular biology to tissue engineering that led me to become interested in a career that combined experimental biology with computer science. When I was faced with finding an interdisciplinary graduate program that could leverage my combined interests I found that Cornell was a great fit. The faculty research is diverse, collaboration is encouraged, and I have the freedom and support to pursue my research interests. Soon after starting my graduate career at Cornell, I was given the opportunity to work on a collaborative project that combines my background in computer science, previous work developing software to characterize and analyze microbial datasets, and my interest in human genetics.
The goal of my current research project is to investigate whether there is a genetic component to the variation of the human gut microbiome, and to identify specific loci in the human genome that are responsible. The composition of the gut microbiota differs markedly among individuals, and constitutes a target for novel therapies, however the development of therapeutics will require a deeper understanding of the factors that shape the microbiota, including age, diet, host physiology and health, and host genotype. To better understand the role of host genotype in modulating microbial community composition, we are conducting a genome-wide association study using fecal samples from monozygotic (MZ) and dizygotic (DZ) twins pairs that have been studied in depth by the United Kingdom’s Adult Twin Registry (TwinsUK). Results from this analysis will reveal candidate genes and pathways for future mechanistic investigations.
Working at the intersection of genetic epidemiology and computational statistics, I am interested in developing statistical methods that elucidate the molecular mechanisms underlying complex traits. This challenging interdisciplinary work also overlaps with population, evolutionary and medical genetics. I have enjoyed the collaborative environment at Cornell University where I have had to opportunity to interact with many people at the interface of these broad subfields of biology.
Post-3CPG Scholar Fellowships/Positions: Postdoctoral Research Associate, Fred Hutchinson Cancer Research Center, Advisor: Dr. Charles Kooperberg, 2011-2012; Senior Fellow, University of Washington Department of Genome Sciences, Advisor: Dr. Su-In Lee, 2012-Present
I am fascinated by how unexpected phenomena arise within biological systems and specifically how genetics plays a role in these phenomena. As an undergraduate I studied biochemistry and did research on the evolution of multivariate heritable variation. As a graduate student, Cornell provided a unique setting in terms of the excellent and collegial population geneticists and computational biologists working together on a multitude of research areas in association mapping and population genetics. It was the perfect place to combine mathematical modeling and population biology. I was fortunate to work with Dr. Jason Mezey along with other labs at Cornell, including the Siepel lab, to apply novel machine learning methods and statistical models to elucidate sparse relationships between population level genetic variation and phenotype. I was also involved with two initiatives at Cornell, the Center for Population Genetics and the Center for Vertebrate Genomics, both of which provide invaluable resources within the Cornell community in terms of fostering collaborations and supporting innovative research.
My primary research interest is to develop novel statistical methodologies that enforce sparsity constraints when inferring population level genetic associations. Through work at Cornell and as a postdoctoral research associate I have shown that adding stringent constraints on the sparsity of a statistical model can increase a practitioner's power to detect novel genetic associations with phenotype. More importantly, this increase in power does not have to come at the cost of a proportionate increase in the number of false positives, the primary concern of most genetic association studies. I have demonstrated the advantage of these sparse modelling approaches in genome-wide association studies in human, as well as in constructing sparse genetic networks for both obesity in a mouse F2 cross and gene expression in a Saccharomyces cerevisiae cross. Currently, I am extending these approaches to apply to high dimensional genetic data underlying Alzheimer's disease, Acute Myeloid Leukemia, and Ovarian Cancer.
Masters: Concepcion University, M.S. Microbiology, 2007
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.
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.
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.
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.
I was lucky to spend much of my youth out in the natural world fostering a fascination in how it all worked. When finally given the chance to conduct research, I focused on questions on an ecological scale regarding the role of animal learning in predator-prey interactions and ecological adaptations in invasive and insipient species. This work solidified my appreciation for the ecological factors driving evolution, but I became interested in the evolution occurring at the molecular level underlying the ecological patterns I was observing. I pursued graduate work at Cornell to learn population genomic methods and 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.
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 complex ecology and population structure make this system a potentially fertile opportunity to study the genomic manifestations of natural selection related to recent ecological shifts as well as complex demography involving on-going speciation and historical size shifts. I used 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.
Barbash and Clark labs
Since undergrad, I have had the opportunity to work in many labs with greatly differing focuses, that included Developmental Neurobiology, Evo-Devo, and clinical Psychiatry. As a result I have developed varied interest. However, for my graduate work, I decided to focus on evolutionary genetics as it presents a multifaceted interface between theoretical, quantitative, functional, and experimental studies. The co-supervision by Daniel Barbash and Andy Clark has allowed me to explore many approaches for my projects. Specifically, the expertise in Genomics of the Clark lab and the Genetics of the Barbash lab are highly complementary, and has been instrumental in my progress and development through my Ph.D.
I am exploring the diversity of the vast quantities of heterochromatic repetitive sequences in animal genomes, using Drosophila as a model. While abundances of inactive transposable elements and satellite DNA in the heterochromatin are often characterized to be neutral, many lines of evidence have raised the possibility that their quantity can have substantial influence on the host genome. I am developing a computational approach to identify de novo and quantify satellite DNA from whole genome sequences. Precise quantifications will allow me to assess the variation of these sequences between Drosophila strains as well as the divergence between species. From this, I plan to infer the mechanism underlying the previously observed rapid evolution of repetitive sequences and heterochromatic landscape. Additionally, I plan to extend the program to ChIP-Seq data to estimate the quantitative relationship between proteins associated with repressive chromatin (e.g. HP1) and repetitive sequences and to determine the influence such interaction can have on chromatin state and gene expression at unlinked loci and genome-wide.
Ever since my days as an undergraduate I have had a keen interest in parasitology. My research as a graduate student provided me opportunity to cultivate this interest, particularly towards understanding the role of parasites and pathogens in shaping host population genetic diversity. I was thrilled to be offered a postdoctoral position at Cornell that allows me to continue research within the field of immunogenetics and host-pathogen interactions, utilizing cutting-edge next-generation sequencing techniques. I am thoroughly enjoying the chance to interact with so many world-class researchers working at the forefront of genomics and bioinformatics.
My research interests are broadly focused on pathogen-host interactions and co-evolution. I have a specific interest in how parasites and other pathogens influence host evolution, genetic diversity, and structuring in host populations, particularly with regards to immunogenetics. At Cornell, my research currently focuses on characterizing, via next-generation transcriptome sequencing, the immunogenetic responses of multiple species of frogs to infection with the amphibian-killing fungus Batrachochytrium dendrobatidis (Bd). Frog species vary greatly in their susceptibility to chytridiomycosis, the disease caused by the fungal pathogen. My ultimate aim is to generate cross-species comparative analyses of gene expression changes in response to Bd infection, with the hope to identify specific immunogenetic markers key to the resistance of chytridiomycosis.
Current: Assistant Professor of Genetics, College of the Holy Cross, Worcester, MA, August 2013- present
I have been fascinated by genetics ever since I took two classes in the field during high school. In college, I also became interested in reproduction and molecular evolution when I began doing research on a fertilization protein in a marine mollusk. I found it fascinating to learn how interactions between specific male and female proteins mediate the reproductive success of each sex. I continued studying this topic in grad school, where I became seduced by the availability of genetic and genomic tools for Drosophila. These tools make flies an excellent model system for studying internal fertilization. For my dissertation, I used proteomic and evolutionary methods to characterize the set of seminal fluid proteins that male flies transfer to females at mating; these proteins regulate fertility and manipulate female post-mating behavior. I came to Cornell to study how individual seminal proteins function. I was attracted by Cornell’s strengths in both experimental and computational biology and the opportunities to collaborate with other labs interested in evolutionary genomics.
As a postdoc, I have studied a small network of male seminal proteins that act in the female fly to control her behavior after mating. I started by using comparative genomics to identify male and female reproductive proteins that show patterns of correlated evolution with the known network proteins; this work was in collaboration with Nathan Clark (Aquadro Lab). Using RNAi, I then tested these proteins for involvement in the network and found five new network members: three male and two female. Loss of any of these proteins severely reduces fertility. I used molecular genetics to identify the steps in the network at which these new proteins act and found that where these proteins fit into the network was consistent with their strongest signatures of correlated evolution. My results suggest that patterns of coevolution can be used prospectively to predict new members of protein networks. In the future, I plan to continue characterizing the molecular interactions between network proteins and to use correlated evolution to identify sperm proteins that function in this pathway.
What is the impact of natural genetic variation on phenotypes? I have approached this question from many different angles, which has led me from the fresh air of field trips to aromatic molecular biology reagents, from the dark rooms of confocal microscopes to the bright screens of computer programming. During my PhD (Montpellier, France), I tried to elucidate whether the diversity of karyotypic variants in Mus musculus domesticus is evolutionary noise or if it is linked to differences in phenotype and adaptation. In my post-doc at the Medical Research Council (Edinburgh, UK), I tested the hypothesis of an adaptive organization of the chromosomes in the nucleus. I also spent 6 years in Barcelona (Spain), working on a wide range of genomic projects revolving around structural variation in the genomes of human and great apes. Coming to Cornell, I discovered a rich and collaborative environment where I received exceptional support to develop a new and very exciting project: deciphering the genetic component of complex diseases.
My current research focuses on the explosive human demographic expansion. During the last 10,000 years, the human population has grown from a few million to 7 billion individuals. My aim is to understand how natural selection and recent population growth have interacted to shape the extant genetic variation observed in humans. In particular, I am interested in understanding how this process has affected the architecture of complex diseases. Theoretical population genetics predicts a series of genetic modifications associated with rapid population expansions. Starting from these expectations and using simulations, I formulate predictions regarding the characteristics of disease-causing variants in humans. Analyzing sequencing data, I additionally test these predictions empirically. I have also taken advantage of sequencing data to refine current models of recent human demographic history.
Sipel Computational Genomics Laboratory
3CPG Scholar: 2012- 2013
I am a computer scientist in training, devoting most of my research to developing and applying new computational methods for evolutionary analysis. I was introduced to evolutionary biology during my graduate studies at the Techion, when I worked on the problem of efficiently reconstructing reliable phylogenies from DNA sequence data. My graduate work focused on the mathematical aspects of this classic problem, and it made me realize how valuable rigorous computational methods are in recovering evolutionary histories. I joined Siepel lab in September 2009 and since then the focus of my research has shifted toward applied genomics and population genetics. The interaction with the population genetics community at Cornell has played a central role in shaping my research by exposing me to some of the most exciting and challenging problems currently faced by the field.
My current research explores the effects of genetic drift and natural selection on patterns of variation in current day genomes. I am interested in two problems in particular: (1) inferring the demographic history of populations and closely related species using sequence data in neutrally evolving genomic loci, and (2) detecting and interpreting signatures of natural selection in the genome using within-species polymorphism and cross-species sequence divergence. I develop computational methods that address these problems by analyzing collections of complete genome sequences generated by high throughput technologies. My work combines examination of unresolved questions in genomics and population genetics by direct data analysis, with development of methods and software that can be used by a broad community of investigators. My goal is to help realize the great potential of vast genomic data sets in shedding light on some of the most challenging and long-standing riddles faced by the field of evolutionary biology.
The Tree of Life forms an interconnected web of genes, populations, species, and ecosystems. I am fascinated by how these levels of biodiversity interact and affect evolution. My graduate training with Dr. David Hillis prepared me to use phylogenetics as a tool for hypothesis-testing. I used Bayesian statistics to demonstrate that clams in the genus Corbicula have an unusual form of asexuality as the result of rare hybridization, not convergent selection on novel mutations. I came to Cornell to work with Dr. Bryan Danforth on bee phylogenomics. Bees are an excellent system to examine the genetics of adaptation, because species have independently evolved complex behaviors. Thus, I can examine evolutionary correlations among traits such as social behavior, diet, pathogen defense, and chemical detoxification. My research can inform us about evolutionary processes, but also has applications to native bee health and conservation.
I plan to study the impact of taxon and gene sampling on comparative and phylogenomic inference using a combination of biological and simulated data. Systematic error - statistical inaccuracy due to inadequate models of evolution - can be caused by incomplete and biased sampling. I seek to identify conditions that lead to systematic error and to develop methods for countering these problems. I will apply these methods to examine genome evolution in bees, but my results will be generalizable to research across a broad spectrum of disciplines.
Current: Assistant Professor, Department of Biology, University of Houston (2013 - present)
Although my Ph.D. is in Ecology and Evolutionary Biology, I was fortunate as a graduate student to participate in a fellowship program that included students from across campus 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. Both within and between departments, 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.
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.
My interest in vertebrate evolution and behavior is longstanding and probably began when I took my first biology class in middle school. As an undergraduate, I conducted research in a molecular laboratory for two and a half years. This first experience with molecular genetics was so remarkable that I decided to apply the variety of techniques I learned to vertebrate systems during my graduate career. I investigated the composition of male salamander courtship pheromones and candidate receptors in females, as well as conducted behavioral assays to test female behavioral responses to pheromones. I was drawn to Cornell by my interest in the amphibian disease dynamics currently occurring in Central America and the fact that Cornell has the facilities and computational power to investigate evolutionary questions at large scales.
Most broadly, my research goals are to use evolutionary genetics and genomics to better understand selection and adaptation in natural populations. My postdoctoral research focused on the impact of emerging diseases on amphibian host genetics in Central America. Specifically, I used a combination of molecular and transcriptomic approaches to investigate how pathogen introduction shapes immune gene variation and population structure. By studying temporal and spatially varying samples, I was able to compare native and exposed hosts of multiple species. I also performed high-throughput sequencing of transcriptomes from exposed and unexposed animals to obtain global estimates of genetic diversity from both neutral and adaptive loci. The long term objectives of this project are to characterize the genetic determinants of resistance and susceptibility to a novel threat to amphibian biodiversity.
Current: Senior scientist at Sage Bionetworks developing models of cancer and enabling open source science through the development of a Biomedical Commons
I have always been a tinkerer - as a child, to my parents chagrin, I got myself in trouble by disassembling everything including the motor on our lawn mower. Teaching me the valuable lesson that assembly is not always as easy as disassembly. By going into physics, I continued in this vein of trying to learn from disassembly, by approaching science from a reductionist perspective. Always having an interest in biologically motivated physics I learned this valuable lesson again in graduate school when introduced to genomics and systems biology where the models constitutes the assembly of many parts instead of disassembly. This change of direction lead to a postdoc position at Cornell where I had the fortune to work with trio of professors: Jason Mezey, Andy Clark and Ron Crystal. With them I worked both on models of disease and models of admixture.
I am motivated by building better data-driven models of biology and disease. I work primarily on developing mathematical approaches for extracting genomic phenotypes and disease signals from system level biological data. When focusing on disease - primarily chronic obstructive pulmonary disease and cancer - I believe these models should be built with the goal of benefitting patients.
Angela C. Poole
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.
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.
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.
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.
My evolutionary interest began as an undergraduate at Oregon State, where I spent three years working in Stevan Arnold's group studying aspects of sexual selection. After graduating, I headed for the University of Chicago to delve deeper into molecular evolution and population genetics with Manyuan Long's group. There I carried out research on the evolution/population genetics of new genes and gene families. At the time, Drosophila's chemosensory system was beginning to be deciphered at the molecular and neurological levels. It became clear to me that these findings were setting the groundwork for rich evolutionary questions to be asked. With this in mind, I went to Andy Clark's group at Cornell with the aim of broadening my population genomic background, and to begging to ask questions of the population differentiation in D. melanogaster, especially the chemosensory-related loci. I have since joined the neurogenetics group of Richard Benton's lab at the University of Lausanne to learn experimental approaches to studying the function and evolution of the Drosophila chemosensory systems.
The general research themes that I pursue have to do with population genomics, chemosensory variation, and gene family evolution. An ultimate goal is to be able to combine these avenues in order to understand the physiological differences and evolutionary forces behind the varying capacity organisms have to make sense of - and exploit - their chemical environment. To do this, I am using neurogenetic techniques to follow up on sensory-related loci that have been identified as evolving under positive selection, or that are otherwise differentiated between species or populations. I am also working with Benton Lab members carrying behavioral and physiological experiments in Drosophila larva to understand the function of particular taste receptors and taste neurons. By expanding our understanding of what these proteins and neurons do in D. melanogaster, we will then be able to ask how these proteins and neural circuits evolve between species.
For as long as I can remember I have been intensely interested in the natural world, and the diversity of life that surrounds us. As an undergraduate I began to explore my interests on an academic scale through projects investigating the impacts of beech bark disease on forest biodiversity and source-sink dynamics of an endangered toad population. As a graduate student I began to use molecular tools to better understand the generation and maintenance of biodiversity, primarily through studying hybridization and speciation in avian systems. I decided to pursue a postdoc at Cornell for two reasons. The Cornell Lab of Ornithology is a world-renowned institution where I knew my interests in avian hybridization and speciation could expand and develop. Additionally, the study of evolutionary genomics at Cornell is cutting edge and highly collaborative, involving a multitude of distinguished faculty and initiatives such as the Cornell Center for Comparative and Population Genomics. I wanted to be a member of that community, to learn from its members, and to contribute wherever possible.
I am interested in understanding how biodiversity is generated and maintained. I am particularly interested in using hybrid zones as windows on the evolutionary process to understand, at a genomic scale, what maintains species barriers and how genomes that have differentiated in isolation interact upon secondary contact and hybridization. At Cornell I have pursued this avenue of research by studying hybridization between black-capped and Carolina chickadees, which occurs along a zone of contact that stretches from New Jersey to Texas. Using a long term transect and temporal genomic sampling I am investigating how selection and genomic introgression vary temporally. Additionally, I am investigating the relationship of hybrid zone movement to climate warming using genomic and citizen science data. I will also bring a transcriptomic approach to the chickadee system in an effort to better understand what happens when divergent genomes interact. All of these avenues of inquiry will benefit from collaboration with, and mentorship from, members of the Cornell Center for Comparative and Population Genomics.
Evolution was the topic that lured me into the study of biology early in my college career, and evolution remains my primary interest and motivator in my career to this day. Although I grew up in “urban” Alaska, I spent a lot of time outdoors at my family’s wilderness cabin and have always pondered questions about why certain organisms are the way they are. As an undergraduate I discovered evolution by natural selection as a satisfying and compelling explanation that gets to the root of my “why?” questions. I joined a research lab led by John Wingfield at the University of Washington and participated in two field seasons studying songbird behavior in the Alaskan Arctic near the town of Barrow. After college I spent two years working in a human genetics laboratory led by Charles Laird before beginning graduate school. For my Ph.D. research with Ben Kerr, also at the University of Washington, I studied adaptation to ultraviolet radiation exposure among populations of the freshwater microcrustacean Daphnia melanica inhabiting small subalpine ponds in the Olympic Mountains of western Washington. From there I moved to Cornell with a postdoctoral fellowship from the NSF, working with Nelson Hairston in the Department of Ecology and Evolutionary Biology.
One of my current research interests is the consequences that evolutionary change within a single species can have for an entire ecological community. In collaboration with Brian Lazzaro, Nelson Hairston and others, I have begun a project at the Cornell Experimental Ponds in which we are manipulating nutrient supply as a driver of natural selection, and tracking both ecological dynamics (such as the timing of annual events like the spring phytoplankton bloom and the midsummer clear water phase) and the evolutionary response of the dominant primary consumer, Daphnia pulicaria. We aim to evaluate the importance of Daphnia evolutionary change within a single growing season in determining ecological dynamics and ecosystem properties of the aquatic environment. In order to track changes in Daphnia genotype frequencies with fine temporal resolution (weekly samples throughout each four-month growing season) in 32 different experimental units, we must develop a method whereby we can infer genotype frequencies from pooled, population-level samples, rather than by genotyping individual animals. In service of this goal, I am developing a novel population-genomic methodology, beginning with computer simulations, in which I use an expectation-maximizing algorithm to infer haplotype frequencies from pooled DNA samples of known haplotypes. Following the development of the statistical and bioinformatic method, I will test the method on real DNA samples from defined pools of Daphnia genotypes assembled in the laboratory, using an Illumina sequencing platform to generate data on single-nucleotide polymorphisms (SNPs). The method I plan to develop will be not only useful to our specific project, but also more generally applicable to any situation in which researchers would like to infer genotype or haplotype frequencies from population-level pools of DNA.
Whole-genome sequencing of ancient and archaic humans has transformed the way we can study human evolution and prehistory. The lowering cost of sequencing technology has gotten many headlines, but making effective use of these new data requires new methods, and opens up new opportunities to examine hypotheses that were previously impossible to test. I have pursued training in anthropology because of the focus of this field on the holistic nature of human evolution, which I consider essential to the understanding of human variation. That perspective helps me to test hypotheses with empirical data from human genetics. I am especially motivated to understand how genes work together in order to disentangle how complex traits in human populations today were shaped by past cultural and demographic changes. I came to Cornell for the opportunity to deepen my computational skills and work in a highly collaborative environment. So far, the opportunity to work and interact with the many talented scientists in the population genetics and evolution community at Cornell has enriched my research and led me to approach my work from many new angles.
My research aims are: (1) To use ancient DNA to understand the evolution of ancient populations, including the Neandertals, Denisovans and pre-Holocene modern humans. (2) To understand the evolutionary mechanisms that influenced complex traits underlying human health. (3) To understand the role of recent human demographic and cultural change, such as changes in human demographic growth and changes in subsistence and settlement patterns. At Cornell, I’m focusing on using existing datasets generated from the Neandertal genome project to understand how Neandertal ancestry contributes to variation in modern human health outcomes, and to understand what this variation reflects about Neandertal evolution and phenotypes.
My interest in how evolution, development, and genomics affect morphological diversity began with an introduction to the Hox genes during an undergraduate evolution course. I was fortunate to obtain an undergraduate summer research scholarship at the Field Museum of Natural History in Chicago to work in the Kearney lab, which focused on understanding the evolutionary origin of snakes from a morphological perspective. My doctoral work in the Moczek lab at Indiana University expanded my approaches with molecular, functional, and even morphometric measurement techniques to understand the evolution and development of a diverse morphological trait: beetle horns. I have spent the last few years engaged as a postdoctoral associate at Yale University in the Monteiro lab, studying the evolution and genomic basis of diverse butterfly wing patterns. In the Reed lab at Cornell, I plan to merge my broad morphological and molecular toolkit with cutting-edge genomic and computational methods to build a synergistic approach toward my original interest in the evolution and development of phenotypic diversity.
My research focuses on uncovering the complex regulation machinery that produces diverse wing patterns during development to understand the origins of morphological diversity in butterflies and other animals with complex novel traits. My proposed research in the Reed lab will use Heliconius butterflies as a model system to focus on the evolution of co-option, or the evolutionary redeployment of gene expression in novel tissues during development. These butterflies have fascinating wing patterns and well-documented adaptive variation. My goal is to describe the molecular basis of how genes are co-opted or how co-option affects downstream regulatory networks, by utilizing functional genomic methods such as ChIP-seq, DNase-seq, and RNA-seq. To do this, I will focus on the transcription factor gene, optix, which has undergone multiple recent co-option events in the Heliconius lineage. I will characterize changes in number, sequence, location, and type of cis-regulatory elements that underlie the co-option of optix from ancestral roles in scale morphology to a novel role in red pigmentation patterning during development.
I did my undergraduate studies at the University of Toronto where I was fortunate to work in two evolutionary biology labs. I analyzed the genome-wide distribution of polymorphism and recombination in Caenorabditis briggsae in the Asher Cutter Lab, and the molecular evolution of rhodopsin genes in teleost fishes in the Belinda Chang Lab. I came to the Field of Genetics, Genomics and Development at Cornell in August 2010 where I joined the Aquadro lab and have focused on using next generation sequencing technology and data to understand the patterns and processes shaping genome evolution of Drosophila and one of its endosymbiotic bacteria, Wolbachia pipientis. I’ve benefited from the interaction I have had with both 3CPG faculty and fellow graduate students and postdocs, and they have been very helpful in helping me figure out the challenges that have arisen in my projects.
The 3CPG scholarship will help me in the final stages of my dissertation research involving two related areas of research. The first area involves studies of the evolution of germline stem cell regulating genes across the genus Drosophila. Previous studies have extensively studied the rapid evolution of “downstream” reproductive genes (seminal fluid proteins and gamete recognition proteins). The earliest stages of reproduction involving germline stem cell maintenance and initial differentiation have received much less attention. I am generating as well as using newly available comparative and population genomic datasets of multiple species of Drosophila in order to understand the evolutionary forces shaping the molecular and functional evolution of the germline stem cell regulatory system. I am also investigating the evolution of other stem cell regulatory systems (i.e. neural stem cell) in order to understand the general patterns of evolution and forces occurring in genes with stem cell regulatory functions.
My second research project involves the genomic analysis of the insect endosymbiont Wolbachia pipientis. This bacteria infects probably three-quarters of all insects, and can cause significant manipulation of reproduction in these species. I have investigated the evolutionary history of the infection of several species of Drosophila by W. pipentis, with a particular focus on the widespread Asian species Drosophila ananassae. This species is of particular interest in that not only are many populations infected intracellularly by this endosymbiont, but many individuals also have the whole bacterial genome integrated into the host eukaryotic genome. I am using population genomic approaches to understand the evolutionary history and dynamics of the integration event and characterize the genomic and functional properties of the integrated bacterial genome in the host.
My work focuses on understanding the genetic basis and evolution of complex traits. I am particularly interested in the interplay between genetic and environmental variation in shaping phenotypic differences between individuals. My research centers on understanding the context-dependency of allelic effects on phenotypic variation. I address this question in light of gene-gene interactions (epistasis), genotype-by-environment interactions, and evolution (e.g. do particular alleles have different effects, or function, in different ecological or genomic environments, and how are these effects mediated?). I focus on different levels of biological organization and across different scales, ranging from variation emerging within a population to variation between populations, to differences between recently diverged species.
I started my undergraduate studies in Toulouse, France at the University Paul Sabatier where I majored in Ecology. I then crossed the Atlantic to go to the University of Illinois at Urbana-Champaign where I completed a master’s in the Department of Natural Resources and Environmental Sciences, with Drs Ken Paige and Kim Hughes. I began my doctoral studies in 2006 under Trudy Mackay and Eric Stone at North Carolina State University. My dissertation was centered around the development of experimental and analytical approaches aimed at understanding the genetic basis of complex traits in Drosophila melanogaster. I later received a fellowship from the Harvard Society of Fellows where I have been since 2011.
Using the 3CpG fellowship, I will pursue a project aimed at understanding the genomic impacts of hybridization between species to determine if introgression between species is both a source of adaptive alleles and a driver of reproductive isolation. The recently diverged species Drosophila simulans and D. sechellia have remarkable ecologies: D. sechellia evolved to exploit the toxic “noni” fruit of Morinda citrifolia and acquired several physiological and morphological adaptations associated with using this host. In contrast, D. simulans is a broad generalist that is normally highly sensitive to noni toxins. I am studying recent collections from a hybrid zone in the Seychelles, where D. simulans exists in sympatry with D. sechellia. Remarkably, several D. simulans populations (“neo-sim”) in this zone have evolved resistance to noni and contain genomic regions from both parental species. "Neo-sim" appears to be partially but strongly reproductively isolated from both parental species. This project will determine the relationship between the genetics of the ecological adaptation to noni and reproductive isolation in neo-sim. I hope this project will provide unique insight into the genetic interrelationship between adaptation and speciation and test a possible mechanism for their co-origination in a hybrid zone.
I have been fortunate in my education to have the opportunity to experience biological research across many disciplines. During my undergraduate career I became interested in Evolutionary Genetics through working with Dr. Sarah Tishkoff. It was then that I learned how examining sequence variation within and between populations could help us to understand the underlying evolutionary history of populations. I would later work as a technician at the Fox Chase Cancer Center in a lab studying stem cell biology in Drosophila. Under the tutelage of Dr. Alana O’Reilly I learned confocal microscopy, biochemistry, fly genetics, and a myriad of other useful techniques for studying biology in a model organism. I realized that evolutionary and functional genetics were two distinct research approaches that could be used to answer fundamental biological questions, and I applied to Cornell’s Genetics, Genomics and Development program with the goal of unifying these two interests.
I am currently investigating how Germline Stem Cells are maintained in Drosophila. There are a number of genes required for the normal maintenance of these cells, many of which have undergone adaptive evolution within the genus. Of particular interest to me is the role that these genes play in preventing selfish transposable elements (TEs) from mobilizing in the germline. Some of them function by maintaining TE-dense genomic regions as “silent” heterochromatic sites, while others function via the piRNA pathway to eliminate TE transcripts. This work gets at the so-called “arms race” between transposable elements and host response.
I am generally interested in the origins and maintenance of species diversity. My past and current projects investigate a variety of factors that contribute to this diversity, from spatial and mechanical isolation, through life history evolution and reproductive ecology to behavioral ecology and communication. I explore these phenomena using both empirical and theoretical approaches. I have predominantly worked with insects in my field research, with a special emphasis on dragonflies and damselflies (Insecta: Odonata). I have also utilized ‘virtual’ organisms, studying computer-generated populations under selection by human ‘predators’.
As an undergraduate in the Ecology, Ethology and Evolution program at the University of Illinois I pursued courses focusing on evolutionary ecology, aquatic invertebrate ecology and entomology; I also gained research experience working in the stream ecology lab of Ed Herricks. My M.S. thesis project, with Paul Jepson and Judi Li at Oregon State University, explored the diversity of life history strategies present in dragonflies and damselflies in riverine wetlands. These wetlands are a major component of the riverine ecosystems of the Willamettte Valley in Oregon, where I performed my research, and understanding how organisms have adapted to these plentiful, but at times challenging, habitats are key to habitat conservation efforts in the region. My PhD work with Tom Sherratt at Carleton University in Ottawa, Ontario focused on the evolution of warning signaling and mimicry; Tom and I also worked with colleagues on a project investigating territorial behavior, sex ratio distortion and species diversification in the endemic Nesobasis damselflies in Fiji. In postdoctoral research with Adolfo Cordero at the University of Vigo in Spain, I combined my knowledge of behavior, damselfly life history and signal evolution to explore the wing color diversification in the Neotropical genus Polythore, which shows elaborate wing coloration, and which may be under sexual selection as well as selection by predators to resemble co-occcuring toxic butterflies. I have also recently collaborated with Jessica Ware at Rutgers University and other colleagues looking into speciation, biogeography and population genetic structure of the ‘petaltail’ dragonfly (Odonata: Petaluridae) a relict group that first diversified along the coasts of the supercontinent Pangaea.
Using the 3CPG fellowship, I will work with Bob Reed on a project investigating the regulatory targets of the Ultrabithorax (Ubx) Hox gene in dragonflies. The role of Ubx in insect hindwing specification is a textbook example of how an individual transcription factor can drive differentiation of entire body segments. Presumably, over evolutionary history, the evolution of body plan diversity in insects was in part attributable to Ubx regulation evolving over time to permit individuation of the third thoracic segment. Ubx is one of the most famous stories in evo-devo, yet it is still a story based largely on presumption. To date, data on Ubx expression has come from lab model insects with highly differentiated segments. To truly characterize the role of Ubx in the evolution of segmental diversification we need to look at its function in insects representing more primitive and transitional states. Dragonflies have only very slightly differentiated thoracic segments, and would be an excellent place to begin delving into the tale of how Ubx facilitated the diversification of insect wings. This project will provide unique insight into the nature of wing evolution in dragonflies and damselflies (underpinning a number of ongoing projects on odonate genomics) and will allow for comparative analysis of Ubx expression and hindwing diversification across a number of insect orders.