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Indiana University Bloomington

Department of Biology

Faculty & Research

Faculty Profile

Matthew Hahn

Photo of Matthew Hahn
Professor of Biology and Informatics

IU Affiliations
School of Informatics

Contact Information
By telephone: 812-856-7001/6-7016(lab)
JH 249B / JH 249 (lab)

Hahn Lab website


Evolution, Ecology & Behavior
Research Areas
  • Evolution
  • Genomics and Bioinformatics

Ph.D., Duke University, 2003
Postdoctoral Fellow, University of California, Davis, 2003-2005


Alfred P. Sloan Foundation Research Fellow, 2010-2012

Research Description

Overview. Our work focuses broadly on computational evolutionary genomics—using the terabytes of available genomic data to ask questions about organismal function and evolution, as well as developing the computational and statistical tools necessary for genome-scale analyses.  The research examines genomic variation both within and between species to study the roles of natural selection and genetic drift in molecular evolution.  Although most of our empirical work has been on systems such as humans, flies, and mosquitoes, students can work on topics and organisms that appeal to them. The main research topics of the lab include:

The evolution of transcriptional regulation. Changes in the timing, level, and location of gene expression have been implicated in many phenotypic differences between individuals and species.  Using both DNA sequence and gene expression data, we can address the origin of variation in gene expression and the evolutionary forces that affect this variation.  Our work on the origin of transcriptional variation within humans has revealed multiple instances of the creation and maintenance of novel transcription factor binding sites in human history.  Natural selection appears to act locally to drive new variants to fixation in different human sub-populations.  We have also examined the creation of such binding sites throughout whole genomes, and have found that many are removed by natural selection to avoid inappropriate binding by transcription factors.  In ongoing work using Affymetrix microarrays, we are studying the relationship between sequence polymorphism and transcriptional variation in the fruitfly, Drosophila melanogaster.

The evolution of gene families.  Comparison of whole genomes has revealed large and frequent changes in the size of gene families.  Comparative genomic analyses allow us to identify large-scale patterns of change in gene families and to make inferences regarding the role of natural selection in gene gain and loss.  To make these analyses possible, we have developed a stochastic birth-and-death model for gene family evolution.  This model allows for parameter estimation, inference of rates and magnitude of change, and a test for the action of adaptive natural selection in gene family diversification.  Application of this method to data from multiple whole genomes of mammals and flies is revealing remarkable patterns of gene family contraction and expansion.

Human population genomics.  The interaction between human demographic history (such as the migration out of Africa) and ongoing natural selection creates complex patterns of polymorphism and linkage disequilibrium.  Our recent work on both regulatory and coding variation in humans has used large numbers of loci from across the genome to tease apart the effects of these potentially confounded forces.  The development and application of coalescent methods to this data has revealed instances of natural selection throughout humans (at the ABO blood-type locus) and in single populations (at the F7 clotting factor locus).  The use of hundreds of loci currently being sequenced in multiple populations will allow for an even more fine-scale investigation of natural selection across the human genome.

Divergence in genetic networks.  Proteins do not evolve in isolation, but rather as components of complex genetic networks.  Therefore, a protein’s position in a network may indicate how central it is to cellular function, and hence how constrained it is evolutionarily.  We have examined the protein-protein interaction networks in yeast, worm, and fly, and have found that proteins with a more central position in all three networks—regardless of the number of direct interactors—evolve more slowly and are more likely to be essential for survival.  By studying various types of genetic networks in a number of different genomes, we can begin to understand the determinants of sequence evolution—and therefore of phenotypic evolution.

Select Publications
Schrider, D.R. and M.W. Hahn (2010) Lower linkage disequilibrium at CNVs is due to both recurrent mutation and transposing duplications. Molecular Biology and Evolution. 27:103-111.  [article]
Han, M.V., J.P. Demuth, C.L. McGrath, C. Casola, and M.W. Hahn (2009) Adaptive evolution of young gene duplicates in mammals. Genome Research. 19:859-867.
Li, Y., J.C. Costello, A.K. Holloway, and M.W. Hahn (2008) "Reverse ecology" and the power of population genomics. Evolution. 62:2984-2994.  [article]
Hahn, M.W. (2008) Toward a selection theory of molecular evolution. Evolution. 62:255-265.
Hahn, M.W., J.P. Demuth, and S.-G. Han (2007) Accelerated rate of gene gain and loss in primates. Genetics. 177:1941-1949.
Demuth, J.P., T. De Bie, J. Stajich, N. Cristianini, and M.W. Hahn (2006) The evolution of mammalian gene families. PLoS ONE. 1:e85.  [article]
Hahn, M.W., T. De Bie, J.E. Stajich, C. Nguyen, and N. Cristianini (2005) Estimating the tempo and mode of gene family evolution from comparative genomic data. Genome Research. 15:1153-1160
Hahn M.W., M.V. Rockman, N. Soranzo, D.B. Goldstein, G.A. Wray (2004) Population genetic and phylogenetic evidence for positive selection on regulatory mutations at the Factor VII locus in humans. Genetics. 167:867-877.
Hahn M.W., J.E. Stajich, G.A. Wray (2003) The effects of selection against spurious transcription factor binding sites. Molecular Biology and Evolution 20, 901-906.
Hahn M.W., M.D. Rausher, C.W. Cunningham (2002) Distinguishing between selection and population expansion in an experimental lineage of bacteriophage T7. Genetics 161, 11-20.

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