Genes in the human genome are interconnected within biological pathways or networks (e.g., signaling cascades, protein complexes, metabolic reactions, etc…), and not independent of each other. Therefore, it is intuitive that groups of interconnected genes are co-expressed or co-regulated within a specific cell or tissue. Our research program employs machine learning approaches for multivariate analysis of ‘omics data (e.g., genomics, transcriptomics, epigenomics, etc.) to determine novel connections among genes and gene products. Moreover, we integrate these pan-omics datasets along with environmental exposures information to better understand mechanisms of gene regulation, gene-gene and gene-environment interactions. Finally, our focus on gene networks and environmental modifiers have revealed novel biological processes underlying multifactorial traits and diseases such as drug response outcomes, asthma and chronic obstructive pulmonary disease.

“Omics” platforms now provide valuable approaches for comparing metabolite profiles and gene expression patterns from stress-sensitive and stress-adapted genomes, studies that can lead to greater mechanistic understanding of biological processes underlying stress tolerance.  Our research focuses upon the extremophyte, Eutrema salsugineum (aka Thellungiella salsuginea), a close relative of Arabidopsis thaliana yet a plant species far more tolerant of extremes in temperature, water deficits, soil salinity, and nutrient deficiencies.  Transcriptomes and metabolite profiles prepared from E. salsugineum plants subjected to stress treatments in growth cabinets have been compared to profiles from plants collected in the challenging conditions of its native semi-arid, sub-Arctic habitat in the Yukon, Canada.  These comparative genomics approaches reveal a rich diversity in novel coping strategies, some well exemplified in processes of osmotic adjustment and nutrient deficiencies.

Various factors lead a cell to initiate genetically encoded forms of programmed cell death (PCD). PCD occurs as part of normal cellular processes such as homeostasis, aging, and development as well as in pathological situations such as ischemic events and Parkinson’s disease. In addition, a variety of stressors including chemicals (i.e., heavy metals), physical changes (i.e., temperature) as well as cellular damage (i.e., DNA damage) can induce PCD. Deficiencies in PCD are linked to other types of pathologies such as cancer. Ability to regulate PCD would thus have tremendous therapeutic applications. In my work, the yeast, Saccharomyces cerevisiae, was used to characterize novel negative regulators of PCD that were previously identified by screening a human heart cDNA expression library in yeast cells undergoing PCD in response to the expression of a pro-apoptotic murine Bax cDNA. My work focused on characterizing four of these human putative anti-apoptotic cDNA sequences, namely lactate dehydrogenase B (LDHB), thyroid cancer–1 (TC-1), 14-3-3β/α (YWHAB) and human ferritin (FTH1). Using spot assay and cell viability assays, I was able to show that these cDNA sequences prevent cell death due to multiple stresses including copper. In order to further examine the functions of anti-apoptotic genes in yeast, we challenged yeast heterologously expressing 14-3-3β/α with multiple stresses. My studies showed that iron and copper activate two different pathways that cross-talk in order to activate the appropriate stress specific response.

​Human genomics is currently undergoing a shift whereby the majority of whole exomes and genomes will soon be coming from clinical, rather than research, settings. If we can successfully harness this global wealth of genomic data, researchers could have a virtual cohort of >60 million individuals available for study by 2025. However, technical and regulatory barriers and the existence of ‘data silos’ continue to prevent clinicians and researchers from deriving maximal benefit from data sources. The Global Alliance for Genomics and Health (GA4GH), formed in 2013, is an international not-for-profit consortium aiming to provide solutions for effective and responsible sharing of genomic and health-related data. The GA4GH community comprises >500 leading institutions around the world working in health care, research, life sciences and information technology, and patient advocacy. Through the development of technical standards and the harmonization of policy approaches, GA4GH strives to facilitate sharing that will advance genomic discovery and human health. This presentation will introduce the audience to GA4GH and its activities, discuss challenges and opportunities in genomic data sharing, and highlight current initiatives that are already demonstrating the value of sharing data (including the Matchmaker Exchange, the BRCA Exchange, and the Beacon Network).