HomeResearchIntramural ResearchResearch Branches at NHGRIGenome Technology Branch Margulies Lab

Elliott Margulies, Ph.D. Investigator Genome Informatics Section B.S. Rutgers University, 1995 Ph.D. University of Michigan Medical School, 2001 (301) 594-9210 (301) 480-3520 elliott@nhgri.nih.gov 5625 Fishers Ln Room 5N-01N, MSC 9400 Rockville, MD 20892-9400 Selected Publications

Dr. Margulies develops bioinformatics approaches for identifying and characterizing regions of the human genome that are evolutionarily conserved across multiple species. The conservation of these sequences over millions of years of evolution is strong evidence that they play important roles in biology, such as coding for genes or functioning as regulatory elements. He has played an important role in advancing the goals of the NISC Comparative Sequencing Program over the past several years.

Dr. Margulies' group utilizes both high-performance computational analyses and laboratory-based high-throughput genomic methods to decipher the genetic information that confers biological function. Indeed, many functions encoded within the genome are likely yet to be discovered; however, uncovering these basic biological phenomena is essential for understanding human development and disease. A major component of Dr. Margulies' research program involves developing and implementing analytical methods for detecting evolutionarily conserved sequences and determining their functional significance. As more vertebrate genomes are sequenced, the evolutionary depth of sequence data sets allows Dr. Margulies to refine algorithms that can detect different kinds of conserved sequences, such as those present only in a subset of species (e.g., primates or certain lineages of mammals).

To better understand the relationship between evolutionary sequence constraint and the functional elements encoded in the human genome, Dr. Margulies is developing approaches to characterize conserved sequences. Through his participation in the ENCODE consortium, he is examining the patterns of overlap between constrained sequences and specific genomic functions, such as RNA transcription, chromatin accessibility, or DNA-protein interactions. The results emanating from this work not only highlight the functional significance of evolutionarily conserved sequences, but they also point to new approaches for assessing sequence conservation.

Toward that end, Dr. Margulies is also developing new methods for detecting cross-species conservation that take into account the important role the three-dimensional chromatin structure of DNA plays in genome function. Two approaches are currently being pursued. The first involves looking at structural conservation, as it has been shown that different DNA sequence patterns can produce similar three-dimensional structures. Using this information, Dr. Margulies is analyzing the structural similarity of orthologous genomic regions from different species. The second approach involves evaluating functional conservation across different species. Using multi-species sequence alignments as a framework, specific functions (e.g., the binding of certain protein) can be found that occur in the same relative position in multiple species. In some cases, these sequences are quite different among species, yet they confer similar function. By analyzing these sequences more carefully, Dr. Margulies hopes to uncover how the genome can encode function in ways other than through its primary sequence.

In addition to these computational-based projects, Dr. Margulies is developing comprehensive high-throughput methods to assay large regions of the genome for transcriptional regulatory activity. He eventually hopes to expand these methods so that an entire genome can be assayed at once. By coupling the data generated in the laboratory with the various computational methods, his group hopes to create synergistic, multidisciplinary approaches for revealing the myriad functions encoded in the human genome.

Finally, Dr. Margulies plans to establish computational and experimental tools to analyze the data that will be produced by the next generation of DNA sequencing technologies. These new sequencing platforms will generate several orders of magnitude more data than current DNA sequencing technologies can, at greatly reduced costs. They will therefore be of great interest to smaller, investigator-driven research programs and potentially to clinical laboratories.

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Last Updated: August 1, 2008