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ENCODE Expands with $30M in New Projects, Data Centers

NEW YORK (GenomeWeb News) – The National Human Genome Research Institute has awarded $30.3 million in new grants to expand its Encyclopedia of DNA Elements (ENCODE) project, a long-term effort to catalog all of the functional gene regulatory networks in the human genome.

The ENCODE effort recently made headlines with the publication early this month of dozens of papers from research that found that around 80 percent of human genome sequences have biological functions, which may have negated for good the concept of 'junk' DNA.

"These grants build on the momentum of recently published ENCODE findings in which researchers provided a highly detailed and global view of the human genome," Elise Feingold, program director for ENCODE in NHGRI's Division of Extramural Research, said in a statement.

"We have already made tremendous progress, but much work remains to complete the catalog of functional elements. These grants, awarded over a four-year period, will allow us to build on those results and take the next significant steps in deepening our understanding of the entire human genome."

The new round of ENCODE awards will expand studies of functional elements to "a considerably larger number of human cells and tissue, and a deeper set of data types," NHGRI said.

The awards also will fund more efforts to analyze the mouse genome in order to enhance its use for studying a range of tissues that are difficult to study in humans.

In addition, the funding will create a data coordinating center and a data analysis center with the goal of making it easier for the scientific community to use the ENCODE data and improving those data sets and making them more useful for the human biology and disease research communities.

The new awards will fund seven ENCODE Production Centers.

Bradley Bernstein at the Broad Institute will lead efforts to catalog chromatin structure in human cells by mapping histone modifications that may affect cellular function and the proteins that direct those modifications.

A group led by Thomas Gingeras at Cold Spring Harbor Laboratory will identify protein-coding and non-protein-coding RNA transcripts in human cells using high-throughput sequencing.

Brenton Graveley's lab at the University of Connecticut Health Center will analyze human RNA transcripts to identify protein-binding sites and to study their functions, a project that represents ENCODE's first production-scale effort to map protein-binding sites in RNA.

Richard Myers at the HudsonAlpha Institute for Biotechnology will head efforts to identify transcription factor binding sites in the human genome, RNA transcripts in human and mouse cells, and DNA methylation sites in the human genome.

Ludwig Institute for Cancer Research scientist Bing Ren will oversee a group seeking to identify DNA methylation sites in the mouse and human genome.

Michael Snyder's group at Stanford University will identify transcription factor binding sites in the human genome, and his group will work with Myers' groups at HudsonAlpha to map binding sites for more than 1,500 transcription factors in the human genome.

John Stamatoyannopoulos at the University of Washington will lead a team to map chromatin structure in the human and mouse genomes, using the DNase I enzyme to identify the location of genomic regulatory elements.

The ENCODE Data Coordination Center will be led by Michael Cherry at Stanford University. His group will work with the data production centers to collect, organize, and store ENCODE data and to provide the research community with access to those data.

The ENCODE Data Analysis Center will be run by Zhiping Weng of the University of Massachusetts Medical School. Weng's team will work with the investigators at the data production centers to perform integrated analyses of the ENCODE data, and to make it easier for the research community to use this knowledge in their human disease studies.

The new ENCODE Computational Analysis awards will fund six grants.

Peter Bickel at The University of California, Berkeley will run a group seeking to develop statistical and computational methods to reduce the complexity of the ENCODE data and to enable comparisons involving many data sets at one time.

David Gifford at Massachusetts Institute of Technology will lead efforts to develop computational approaches to identify regulatory elements, and to study how components within regulatory elements function together.

University of Wisconsin investigator Sunduz Keles will head a team that will develop statistical methods and software to identify regulatory elements in the human genome, with a particular focus on sequences that are repeated at several locations.

Memorial Sloan-Kettering Cancer Center investigator Robert Klein will oversee a group seeking to develop computational approaches to identify cell types and genetic changes that are involved in human disease.

Jonathan Pritchard's team at the University of Chicago will develop computational approaches to determine how changes in DNA sequence lead to changes in gene expression.

University of California, Los Angeles investigator Xinshu Xiao will head a team seeking to identify genetic differences that alter RNA processing.

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