Evolutionary Genomics @ Columbia University
We are a group of scientists with a common interest in the genetic basis of variation within and between species.
Work in our groups spans the fields of phylogenetics, epigenetics, functional genomics, population and quantitative genetics, human genetics, neurogenetics, animal behavior, experimental evolution, and comparative and evolutionary genomics.
People and interests
To what extent are adaptive evolutionary paths “predictable”? What factors limit the rate of adaptive evolution? We address these fundamental questions at a variety of scales, from the dissection of repeated adaptations in single proteins to the characterization of changes in gene regulatory networks underlying complex phenotypes.
Zuckerman Mind Brain Behavior Institute
Ecology, Evolution and Environmental Biology
The diversity of animal behavior is fascinating, yet we know little about how behavior evolves. Our research occupies a niche at the intersection of genomics and neuroscience; we leverage natural variation in behavior in multiple vertebrates to uncover fundamental principles about the evolution of behavior and function of the brain, with an emphasis on behaviors that are significant in nature and of great relevance to humans.
The lab focuses on the ecology and evolution of plant-gene-environment interactions, often working with Arabidopsis thaliana. We are part of a multi-campus effort to phenotype a comprehensive mutant library in Arabidopsis, examining what proportion and what types of mutations alter whole-plant phenotypes. As a lab at Barnard, we prioritize undergraduate research, and integrating research with teaching.
Ecology, Evolution and Environmental Biology
Why is hybridization more common in some taxonomic groups? How does it affect rates of speciation and genome organization? And how can we properly reconstruct evolutionary history in the presence of horizontal gene transfer? We combine fieldwork and experimentation with computational genomics and comparative methods to investigate these questions in plants within an ecological and evolutionary context.
Biochemistry and Molecular Biophysics
We study the evolutionary genomics of microbial eukaryotes with complex genome architectures. We use both functional genomic experiments that manipulate chromosome structure and comparative genomics to understand differences in chromosome organization, epigenetic marks, and DNA sequence. The model organisms we use have two nuclei, which also permits comparative genomics within a single cell: one genome gives rise to the other during programmed genome reorganization, and we study how this system arose by transposon coevolution.
Barnard Computational Biology
There is a clear link between bacterial metabolism and antibiotic efficacy, but we know surprisingly little about how bacterial metabolism contributes to the evolution of antibiotic resistance. Our lab studies how metabolic genes and networks influence vertical and horizontal evolution of drug resistance, using a combination of experimental evolution, genomics, and mathematical modeling. By understanding how resistance spreads in dynamic bacterial populations, our goal is to develop novel therapeutic strategies to curb the rise of resistant pathogens.
How is it best to measure, describe and quantify differences between individual DNA sequences? How does sequence variation affect biological processes? How can we use it to understand and influence human disease? All these questions pose complex analytical challenges, with direct impact on medical research.
We are interested in the genetic and evolutionary mechanisms that give rise to heritable variation among humans and across species. Our research combines genomic data analysis, statistical modeling, and some data collection. Currently, we are primarily focused on understanding adaptation in humans and the evolution of mutation and recombination among vertebrates.
The amount of high throughput data in biological and clinical systems—from next-generation sequencing experiments to electronic health records—is increasing dramatically, allowing for the development of a quantitative understanding of these complex systems. Our lab is an interdisciplinary team interested in developing mathematical and computational tools to extract useful biological information from large data sets.
Ecology, Evolution and Environmental Biology
We take an integrative approach to understand why complex animal societies form and how organisms cope with environmental change through studies that combine behavior, ecology and evolution with those of the underlying molecular and neuroendocrine mechanisms. We work on a variety of organisms, including insects, crustaceans, and birds in both the lab and field, including in Asia, Africa, Central America, the Caribbean, and North America.
We study the evolutionary processes that give rise to genetic and phenotypic differences between individuals, populations and closely related species. To these ends, we use mathematical models to better understand these processes, and statistical analyses to identify their footprints in data and make inferences about them. Our current work focuses primarily on the evolutionary causes of adaptation and disease, but we also study a variety of other topics.
My lab is interested in evolutionary genomics in the cancer setting. We develop and apply methods motivated by population genetics approaches to understand aspects of tumor evolution, particularly tumor heterogeneity and its consequences for treatment. In this world, the individuals are cells; we have recently been working on methods for molecularly annotating tumors in three+ dimensions by exploiting microscopy methods such as STPT and merFISH.
Biochemistry and Molecular Biophysics
We use laboratory experimental evolution to study how cells adapt to the challenges imposed by severe changes to the external environment. Genetic, genomic, and physiological characterization of adapted cells is revealing how perturbations to signaling and regulatory networks enable cells to rapidly adapt to novel or extreme environments. We also utilize comparative sequence analysis to infer the presence and functional roles of transcriptional and post-transcriptional regulatory elements.
Upcoming Joint Group Meetings
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Past Joint Group Meetings
|11-Jun-2019 noon||Fairchild 800||Jan-Niklas Runge (Bendesky, CU) / Jeffrey Vedanayagam (Eric Lai, MSKCC)|
|14-May-2019 noon||Fairchild 800||Sandra Hoffberg (Eaton, CU) / Arbel Harpak (Przeworski, CU)|
|2-Apr-2019 noon||Fairchild 800||Sarah Kocher (Kocher, Princeton) / Young Mi-Kwon (Bendesky/Kelley, CU)|
|12-Mar-2019 noon||Fairchild 800||Bluma Lesch (Lesch, Yale) / Jie (Pe'er, CU)|
|5-Feb-2019 noon||Fairchild 800||Shana Caro (Rubenstein, CU) / Zack Fuller (Przeworski, CU)|
|5-Dec-2018 noon||FAIRCH-800||Lindy McBride (McBride, Princeton) / Laura Hayward (Sella, CU)|
|7-Nov-2018 noon||FAIRCH-800||Saeed Tavazoie (Tavazoie, CU) / Kristin Lee (Przeworski, CU)|
|3-Oct-2018 noon||FAIRCH-800||Nick Tatonetti (Tatonetti, CU) / Juan Patino (Rabadan, CU)|
|5-Sep-2018 noon||FAIRCH-800||Christina Zakas (Rockman, NYU) / Jason Munshi-South (Munshi-South, Fordham)|
|6-Jun-2018 noon||FAIRCH-1000||Rafik Neme (Landweber) / Li Zhao (Zhao, Rockefeller)|
|4-Apr-2018 noon||FAIRCH-800||Erik Ladewig (Rabadan) / Yifei Huang (Siepel, CSHL)|
|7-Mar-2018 noon||FAIRCH-800||Luke Noble (Rockman, NYU) / Ioan Filip (Rabadan)|
|7-Feb-2018 noon||FAIRCH-800||Patrick Reilly (Andolfatto) / Molly Przeworski (Przeworski)|
|6-Dec-2017 noon||FAIRCH-800||Tyler Joseph (Pe'er) / Natalie Wagner (Bendesky)|
|1-Nov-2017 noon||FAIRCH-800||Deren Eaton (Eaton) / Zach Baker (Przeworski)|
|4-Oct-2017 noon||FAIRCH-800||Solomon Chak (Rubenstein) / Jeremy Berg (Sella)|
2019/20 Evolutionary Biology Courses
|BIOL UN3560||Evolution in the Age of Genomics||Guy Sella, Peter Andolfatto||Fall|
|EEEB GR6110||Fundamentals of Evolution||Deren Eaton, Joel L Cracraft||Fall|
|EEEB UN1010||Human Origins and Evolution||Jill Shapiro||Fall|
|G4017||Deep Sequencing||Yufeng Shen, Peter Sims, Chaolin Zhang||Basic knowledge in molecular biology, probability, and statistics||Fall|
|BIOL GR6570||Readings in Human Genetics||Molly Przeworski, Guy Sella||Spring|
|UN3220||Evolution of Human Growth and Development||Spring|
|GU4055||Principles and Applications of Modern DNA Sequencing Technologies||Andres Bendesky, Deren Eaton||Introductory Biology, or the instructor's permission||Spring|
|W6560||Human Evolutionary Genetics||Molly Przeworski, Guy Sella||Undergraduate course in genetics. Familiarity with basic concepts in probability and statistics||Spring|
|COMS4761||Introduction to Computational Genomics||Itsik Pe'er||The student is expected to be an independent programmer||Spring|
BIOL UN3560 Evolution in the Age of Genomics
This course introduces basic concepts in evolutionary biology, from speciation to natural selection. While the lectures incorporate a historical perspective, the main goal of the class is to familiarize students with topics and tools of evolutionary genetics as practiced today, in the era of genomics. Thus, the focus will be on evidence from molecular evolution and genetics and exercises will assume a basic background in genetics. Examples will be drawn from across the tree of life, but with a primary focus on humans.
EEEB GR6110 Fundamentals of Evolution
Lectures cover principal topics in evolutionary biology including genetics, genome organization, population and quantitative genetics, the history of evolutionary theory, systematics, speciation and species concepts, co-evolution, and biogeography.
EEEB UN1010 Human Origins and Evolution
This is an introductory course in human evolution. Building on a foundation of evolutionary theory, students explore primate behavioral morphology and then trace the last 65 million years of primate evolution from the earliest Paleocene forms to the fossil remains of earliest humans and human relatives. Along with Behavioral Biology of the Living Primates this serves as a core required class for the EBHS program.
G4017 Deep Sequencing
Next-generation sequencing (NGS) has become ubiquitous in biomedical research with numerous applications. This course, which has been offered for three consecutive years, will provide an in-depth introduction to principles of modern sequencing, key computational algorithms and statistical models, and applications in disease genetics, cancer, and fundamental biology. It will cover genome, exome, and transcriptome sequencing approaches. Emphasis will be placed on understanding the interplay between experimental design, data acquisition, and data analysis so that students can apply these powerful tools in their own research.
GU4055 Principles and Applications of Modern DNA Sequencing Technologies
Genome sequencing, the technology used to translate DNA into data, is now a fundamental tool in biological and biomedical research, and is expected to revolutionize many related fields and industries in coming years as the technology becomes faster, smaller, and less expensive. Learning to use and interpret genomic information, however, remains challenging for many students, as it requires synthesizing knowledge from a range of disciplines, including genetics, molecular biology, and bioinformatics. Although genomics is of broad interest to many fields—such as ecology, evolutionary biology, genetics, medicine, and computer science—students in these areas often lack sufficient background training to take a genomics course. This course bridges this gap, by teaching skills in modern genomic technologies that will allow students to innovate and effectively apply these tools in novel applications across disciplines. To achieve this, we implement an active learning approach to emphasize genomics as a data science, and use this organizing principle to structure the course around computational exercises, lab-based activities using state-of-the-art sequencing instruments, case studies, and field work. Together, this approach will introduce students to the principles of genomics by allowing them to generate, analyze, and interpret data hands-on while using the most cutting-edge genomic technologies of today in a stimulating and engaging learning experience.
W6560 Human Evolutionary Genetics
The course brings together population genetics theory, empirical studies and genetic models of disease to provide an integrated perspective on the evolutionary forces that shape human variation and in particular disease risk. Our goals are to provide you with a basic toolbox with which to approach human variation data and in parallel, to expose you to cutting-edge research and to the forefront of knowledge in human population genetics. To this end, the course includes in-depth discussions of classic papers in these fields coupled with recent findings employing new technologies and approaches.
COMS4761 Introduction to Computational Genomics
Technology for obtaining DNA sequences have been consistently improving faster than Moore's law. This has opened a wealth of computational challenges in weaving the heaps of straw of DNA sequence data into gold of biological insight. The class serves as an introduction to computational genomics, explaining the basic challenges and teaching the general computer-science tools to tackle them. This course is intended to introduce students of both computational and bio-medical skill sets to current quantitative understanding of genomics and prepare them to computational research or industrial development in the field.