MIT Computational Biology Group
Our work focuses on the computational foundations of genomics,
developing algorithmic, statistical, and machine learning methods to
interpret the functional elements encoded in the human genome,
reconstruct the regulatory circuits they define, and understand their
evolutionary mechanisms.
We work in a highly interdisciplinary environment at the interface
of Computer Science and Biology. Since its inception, our lab has
eagerly engaged in collaborative research partnerships with biological
and experimental collaborators, facilitated by our affiliation with
the Broad Institute and the Computational and Systems Biology
initiative (CSBi) at MIT, our participation in the ENCODE and
modENCODE consortia, and by several other ongoing collaborations at
MIT, Harvard, and the Harvard Medical School affiliated hospitals.
Our research focuses on the following major questions,
central to our understanding of biological systems:
- Genome Interpretation:
We have developed comparative genomics methods which can directly discover diverse functional genomic elements based on their characteristic patterns of evolutionary change across related species. These "evolutionary signatures" are dictated by precise functional constraints unique to each class of functional elements, thus enabling their genome-wide discovery. We have used such signatures in the human, fly, and yeast genomes to recognize protein-coding genes and exons, RNA genes and structures, microRNAs and their targets, and diverse classes of regulatory elements. This has resulted in many surprising findings and new insights, including extensive stop-codon read-through in adult brain proteins, novel types of RNA structures involved in post-transcriptional and translational regulation, miRNA targeting in protein-coding regions, functionality of both arms of a miRNA hairpin, and both sense and anti-sense miRNAs, and the discovery of a new class of long intergenic non-coding RNAs.
More on: Genome Interpretation -
Protein-coding Genes -
Non-coding RNAs
Gene regulation:
We have also developed computational methods to study the cellular circuitry of genomes, which directs gene expression levels in response to environmental and developmental stimuli. Our work has resulted in global maps of regulatory elements in yeast and animal genomes, and their role in specifying pre- and post-transcriptional gene regulatory networks. Combining comparative genomics with experimental datasets, we have studied condition-specific and tissue-specific activation networks, and revealed new insights on activation and silencing of developmental genes, and post-transcriptional targeting by miRNA genes.
Read more on:
Chromatin -
Regulatory Motifs -
Biological Networks
Epigenomics:
With the recent availability of genome-wide maps of histone modifications, we have developed new methods for the systematic discovery of recurrent combinations of chromatin marks, or "chromatin signatures," which we found to be associated with very specific types of functional elements, including diverse classes of enhancers, promoters, and insulators. We have used these signatures to discover new elements, including novel non-coding RNA genes, and to systematically study the dynamics of chromatin state across tissues and during development, and to discover the sequence elements and grammars governing those changes. We are currently also exploring the role of small non-coding RNAs in the establishment, maintenance, and targeting of chromatin state.
More on: Epigenetics -
Small RNAs
Small RNAs:
e aim to decipher the combinatorial control of
gene expression and cell fate specification, and understand the
dynamic reconfiguration of genetic sub-networks in changing
environmental conditions
Epigenomics: we study the combinations, dynamics and logic of
chromatin marks in multiple cell types in fly and human, to
understand their role in development and differentiation.
- Evolutionary genomics: we aim to understanding the emergence of
new functions, reconfiguration of regulatory motifs, and the
coordinated evolution of functionally interconnected cellular
components.
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- Genome evolution: We have also developed methods to study systematic differences between the species compared, and uncovered important evolutionary mechanisms for the emergence of new functions. Our work provided definitive proof of an ancestral whole-genome duplication in yeast, which led to a complete doubling of the gene count, and was rapidly followed by massive gene loss, asymmetric divergence, and new gene functions. To further understand the evolutionary processes leading to new functions, we developed a phylogenomic framework for studying gene family evolution in the context of complete genomes, revealing two largely independent evolutionary forces, dictating gene- and species-specific mutation rates. De-coupling these two rates also allowed us to develop the first machine-learning approach to phylogeny, resulting in drastically higher accuracies than any existing phylogenetic method.
More on: Evolution - Phylogenomics.
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We are located on the 8th floor of MIT Stata Center, a truly unique
building that stretches the imagination, and home of the Computer
Science and Artificial Intelligence Lab (CSAIL). We are just across
Main Street from the Broad Institute, which boasts a unique
collaborative environment for genomics, and we have weekly meetings
in both institutions.
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Positions Available
Spotlight: RecombSat09 - RECOMB Regulatory Genomics, Systems Biology, DREAM4
Selected Publications
See also: Full list - Grouped - Google Scholar - Pubmed
- The modENCODE Project: Unlocking the secrets of the genome.
Celniker, Dillon, Gerstein, Gunsalus, Henikoff, Karpen, Kellis, Lai, Lieb, MacAlpine, Micklem, Piano, Snyder, Stein, White, Waterston; modENCODE Consortium.
Nature. 2009 Jun 18;459(7249):927-30.
- Evolution of pathogenicity and sexual reproduction in eight Candida genomes.
Butler, Rasmussen, Lin, Santos, et al, Birren, Kellis, Cuomo.
Nature. 2009 Jun 4;459(7247):657-62.
- Histone modifications at human enhancers reflect global cell-type-specific gene expression.
Heintzman, Hon, Hawkins, Kheradpour, Stark, et al, Crawford, Kellis, Ren.
Nature. 2009 May 7;459(7243):108-12. Epub 2009 Mar 18.
- Chromatin signature reveals over a thousand highly conserved large non-coding RNAs in mammals
Guttman, Amit, Garber, French, Lin, et al, Bernstein, Kellis, Regev, Rinn, Lander
Nature, Feb 1, 2009
- Discovery of functional elements in 12 Drosophila genomes using evolutionary signatures
Stark, Lin, Kheradpour, Pedersen, Parts, Carlson, Crosby, Rasmussen, Roy, Deoras, Ruby, Brennecke, FlyBase curators, Berkeley Drosophila Genome Project, Hodges, et al, Pachter, Kent, Haussler, Lai, Bartel, Hannon, Kaufman, Eisen, Clark, Smith, Celniker, Gelbart, Kellis
Nature, 2007 Nov 8; 450:203-218, 14 pages
- Systematic discovery of regulatory motifs in human promoters and 3' UTRs by comparison of several mammals
Xiaohui Xie, Jun Lu, EJ. Kulbokas, Todd Golub, Vamsi Mootha, Kerstin Lindblad-Toh, Eric Lander, Manolis Kellis
Nature 2005 Feb 27, doi:10.1038/nature03441
- Proof and evolutionary analysis of ancient genome duplication in the yeast Saccharomyces cerevisiae
Manolis Kellis, Bruce Birren, Eric Lander
Nature 2004 Apr 8; 428 pp. 617-24
- Transcriptional regulatory code of a eukaryotic genome
Chris Harbison et al.
Nature 2004 Sep 2; 431 pp. 99-104
- Sequencing and comparison of yeast species to identify genes and regulatory motifs
Manolis Kellis, Nick Patterson, Matt Endrizzi, Bruce Birren, Eric Lander
Nature 2003 May 15; 423 pp. 241-254
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