NEW YORK (GenomeWeb) – The National Human Genome Research Institute today announced it has awarded $28.3 million in grants to decipher the underlying mechanisms that turn genes on and off.
Five new awards, part of the Genomics of Gene Regulation (GGR) program started in 2013, were given to study gene networks and pathways in different systems in the body.
The grants have been awarded to Memorial Sloan Kettering Cancer Center, which received $3.2 million to study mechanisms of immune system activity during inflammation in mice; Duke University, which got $5.9 million to characterize how human lung epithelial cells respond to anti-inflammatory drugs called glucocorticoids; the University of Massachusetts Medical School, which was granted $6.1 million for the study of dendritic cells in the immune system; Stanford University, which received $7.1 million to study the maturation and development of keratinocyte skin cells; and the University of California, Los Angeles, which was awarded $6 million to study macrophage response to bacterial pathogens.
"The GGR program aims to develop new ways for understanding how the genes and switches in the genome fit together as networks. Such knowledge is important for defining the role of genomic differences in human health and disease," said Mike Pazin, a program director in the Functional Analysis Program in NHGRI's Division of Genome Sciences.
Numerous studies have suggested that variation in genomic regions outside of the protein-coding regions can play a role in disease. Such regions likely contain gene-control elements that are altered by this variation and may increase the risk for a disease.
"Knowing the interconnections of these regulatory elements is critical for understanding the genomic basis of disease," Pazin said. "We do not have a good way to predict whether particular regulatory elements are turning genes off or activating them, or whether these elements make genes responsive to a condition, such as infection. We expect these new projects will develop better methods to answer these types of questions using genomic data."