Our goal is to identify components of human nuclear RNA pathways implicated in devastating genetic diseases and cancers. To achieve this goal, we developed novel genetic screening approaches that enabled identification of human pathways acting on nuclear long non-coding RNAs. We are currently employing these approaches to conduct forward genetic screening of pathways that regulate three disease-associated nuclear lncRNAs: MALAT1, MEN-beta and KSHV PAN. Identification of components of these pathways will provide a list of potential targets for the treatment of cancer, developmental, and viral disorders.

There are an estimated 7-10 thousand known rare diseases affecting 300-400 million individuals worldwide. Approximately 80% of these have a genetic etiology. However, despite increasing availability of whole genome sequencing and other ‘omics’ technologies, rare disease diagnostic rates are unacceptably low and time to diagnosis is typically measured in years. Our goal is to alleviate the burden experienced by patients with rare diseases by accelerating rare disease research, increasing diagnostic rates, and reducing time to diagnosis. To achieve these goals, our research focuses on the development of artificial intelligence (AI) capabilities that combine structured biological knowledge with multiomic and phenotypic patient data to discover associations between phenotypes and rare variants, predict in-silico variant pathogenicity, and enable clinical decision support tools to help clinicians diagnose rare genetic disorders.

Many individuals living today are admixed, with genetic variation coming from multiple ancestral sources. Past interactions between populations can shape the genetic variants present in modern people, but how exactly allele frequencies are impacted by admixture is understudied. In this project, we will leverage demographic simulations of admixture to identify selection occurring in ancient populations over time. This work will first survey ancient Europe, where the demographic history of populations are well-known and sampled ancient individuals are abundant, to demonstrate that this method can help detect selection in ancient populations. We will also examine ancient American populations and how Indigenous ancestry was impacted by the effects of European colonization, which included admixture with European and African populations.

The gene-regulatory mechanisms controlling mitochondrial biogenesis during early development stages are not well-understood, leading to difficulties in predicting pediatric cardiomyopathies due to mitochondrial dysfunction. Our long-term goal is to understand the relationship between transcriptional regulation and metabolism in the cardiovascular system. Research conducted in our laboratory revealed that GATA4 binds to regulatory DNA regions to regulate the expression of PPARGC1A (encoding PGC-1α), which serves as an important regulator of mitochondrial biogenesis and maturation. We also demonstrated that overexpression of GATA4 can rescue mitochondrial function and biogenesis in cardiomyocytes that were impaired from cancer drug exposure; and repression of GATA4 decreased mitochondrial respiration in cardiomyocytes. Our central hypothesis is that GATA4 is involved in mitochondrial biogenesis via regulation of PPARGC1A during early cardiac development. In the proposed study, we will combine a scaffold-free 3D-cardiac organoid method with CRISPR/dCas9-interference approaches as a novel system, so as to investigate the relationship between dynamic alterations in metabolic profiles and GATA4-mediated regulatory networks during early cardiac differentiation. This study will fill the gaps in our understanding of early-onset cardiac defects from the metabolic dysregulation due to dysfunction of GATA4, and it will also improve therapeutic intervention for pediatric cardiomyopathies from metabolic disorders.

Flame retardants (FRs) are a ubiquitous group of chemicals used in furniture, car seats, and children’s products and can leach into indoor dust, resulting in chronic exposures. Epidemiological and experimental evidence shows that developmental FR exposures result in short- and long-term adverse health outcomes, but the knowledge gap remains- what targets do they attack and how do they drive adverse outcomes? Using zebrafish, our preliminary data on a brominated FR, tetrabromobisphenol A (TBBPA) shows that TBBPA exposures during early developmental windows (cleavage, blastula, early gastrula) results in developmental delays and gene-level disruption. These developmental windows encompass maternal to zygotic transition (MZT) and zygotic genome activation (ZGA), when maternally loaded mRNA degrade, and zygotic genome is activated. The overarching goal of this project is to understand the diversity of TBBPA-induced alterations in histone modifications and chromatin remodeling- key regulatory factors driving genome activation. Leveraging embryonic zebrafish as a model and a combination of ChIP, ATAC and metabolic RNA sequencing, this project will fill knowledge gaps on how environmental toxicants target early developmental events such as MZT and ZGA that set stage for plutipotency.

Alzheimer’s disease (AD) research presents novel, complex data-analytic challenges. Many large-scale brain neuroimaging studies have been conducted in the context of AD; however, the high-resolution, complex domain and complicated spatial structure of brain images are not amenable to analysis by conventional statistical methods. In addition, recent advances in high-throughput genotyping give rise to the emerging “imaging genetics” discipline, which focuses on exploring the genetic influence on structural and functional imaging variations. This project will develop new statistical methods to quantify 2D neuroimages, and assess the contribution of genetic and environmental factors to variation in brain morphology and relationship to AD susceptibility. The methods we develop will be applicable to AD as well as other precision medicine research involving imaging genetics studies.