The NIH established the Grand Opportunities “GO” grants program as part of the Recovery act to support high yield, short-term projects that address large, specific biomedical and bio-behavioral research endeavors. Two CCGS faculty members recently received these highly competitive stimulus grants.
Morgan Giddings and Co-PI Xian Chen were awarded $1.6M from the NHGRI to generate and analyze proteomic datasets for annotation of ENCODE human cell lines. ENCODE is a consortium spearheaded by NHGRI to produce a comprehensive map of functional elements in the human genome. The Giddings lab will further proteogenomic mapping efforts by using advanced mass spectrometry methods to generate large-scale proteomic datasets using the same ENCODE cell lines used for transcription mapping. A community accessible database will be constructed to store and manage the datasets which will be mapped to human genome drafts on a UCSC genome browser track. As the ENCODE project scales up, these advances to existing mapping technologies will further ENCODE efforts to identify the subset of transcripts that encode proteins.
With his GO award, Pat Sullivan proposes experiments aimed at discovering DNA and RNA biomarkers for major depressive disorder (MDD) by developing a comprehensive understanding of the genomics of transcription in normal and affected twins. This work is essential to developing a more complete understanding of the biological basis of MDD, a common complex trait associated with considerable morbidity, mortality, and personal/societal cost. The 2-year grant from the NIMH provides $3.3M in funding to achieve two aims. First, they will conduct an eQTL study of mono- and dizygotic twin pairs. Genome-wide SNPs and CNVs will be assayed as well as genome-wide methylation, miRNA, exon splicing, and nucleosome occupancy. RNA-seq will be also be conducted on a subset of samples. Comprehensive analyses will determine the genetic architecture and genome-wide associations for every transcript to provide a detailed catalog of the architecture of transcription. The second aim will capitalize on the results from Aim 1 and a large MDD study with repeated clinical and biological assessments to identify biomarkers for MDD.