2023 PCGC/CDDRC Fellows

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Andrew Blair, Ph.D. Candidate

University of California San Francisco 

Andrew Blair is a Biological and Medical Informatics Ph.D. candidate at UC San Francisco and a trainee in the Impact of Genomic Variation on Function (IGVF). His research interest is deciphering the regulatory role of genomic elements in human cardiac development and disease. Before starting his Ph.D., he received an M.S. in Bioinformatics from UC Santa Cruz, supporting the California Institute of Regenerative Medicine’s Heart of Cell team. Following his M.S., he worked as a Genomic Analyst for the Gladstone Cardiovascular Disease Institute and Genentech. His current research with Dr. Nadav Ahituv focuses on building congenital heart disease (CHD) candidate regulatory element models for experimental characterization and functionalization.


Multi-omic Modeling of Candidate Regulatory Elements to Decipher Congenital Heart Disease

Variants in gene regulatory elements are a significant cause of congenital heart disease (CHD). However, associating variants in candidate regulatory elements (CREs) to CHD is challenging to identify and characterize. Using the CDDRC multi-omics and PCGC dbGAP/TOPMeD data in the BioData Catalyst ecosystem, along with an ensemble of deep learning model predictions, I will develop spatiotemporal networks for cardiac cell-type-specific CREs. This network will allow users to link CHD-associated CREs to target gene regulatory domains, including which time point and in vitro system or organism to best model CHD. Using predictions prioritized by the network, over 50,000 CHD-associated CREs will be functionally evaluated via massively parallel reporter assays (MPRA) in cardiac progenitors, primitive cardiomyocytes, and atrial and ventricular cardiomyocytes, allowing me to improve the networks’ predictions. This work will provide a user, data-driven “report card” from our catalog of functionally characterized CHD-associated CREs, supporting the design of future functional testing and providing a framework to refine our understanding of CHD further.

Jonathan Klonowski, Ph.D. Candidate

Cecilia W. Lo Laboratory, University of Pittsburgh School of Medicine

Jonathan Klonowski is the son of Polish immigrants who grew up on the west side of Chicago and obtained his B.S. from the University of Illinois at Chicago. As a scientific nomad, Jonathan has received training in many biological disciplines including biochemistry, molecular biology, cell biology, virology and developmental biology. Pursuing his PhD at the University of Pittsburgh, School of Medicine’s Integrative Systems Biology program, Jonathan is currently utilizing a combination of genetics, computational biology and bioinformatics to understand the genetic etiology of congenital heart disease.


Role of Nonsense-Mediated mRNA Decay (NMD) Escaping Variants in the Pathogenesis of Congenital Heart Disease.

Premature termination codon (PTC) causing mutations represent a large fraction of clinically relevant pathogenic genomic variation. Typically, PTCs generate transcripts degraded by nonsense-mediated mRNA decay (NMD), causing loss-of-function (LOF) allele. However, PTC containing transcripts can escape NMD, possibly resulting in dominant negative or gain-of-function (DNGOF).  Ability to systematically identify PTC-causing variants predicted to escape NMD will make it possible to investigate the potential role of DNGOF variants in human disease. Herein, we will develop Dockstore software for annotating sequencing data at scale, implementing established and experimentally validated rules for NMD escape. Using this, we will recover predicted NMD escaping variants (pNEVs) among Pediatric Cardiac Genomics Consortium (PCGC) congenital heart disease (CHD) patients to assess their role in CHD pathogenesis. Functional impact will be discerned by cross-species analysis of pNEVs from mutations recovered from mouse mutagenesis screens.

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Jing Li, Ph.D.

Institute of Biosciences and Technology (IBT), Texas A&M University Health Science Center

Jing Li is a postdoctoral researcher at the Institute of Biosciences and Technology (IBT), Texas A&M University Health Science Center. He received a Ph.D. in Biomedical Engineering from Purdue University before starting the position at IBT. His previous work resulted in several publications including topics in single cell discrete, mechano-dynamic models that focused on intracellular cytoskeletal dynamics during cell morphogenesis. The modeling components include cytoskeletal proteins such as actin filaments and microtubules. He has been proactively pursing research with the goal of developing multiscale model for single and collective cell dynamics, which also requires integrative data analysis across various spatiotemporal scales. He is currently committed to single cell spatial transcriptomics study which involves the development of an innovative mapping technique to understand patterning of cardiac progenitor cells during early embryonic stages in mice. He has started serving as a steering committee member at the Gulf Coast Consortia (GCC), for the GCC Single Cell Omics Scholars Program.


Multi-omic Modeling of Candidate Regulatory Elements to Decipher Congenital Heart Disease

Congenital heart defects (CHD) arise upon dysregulation of highly synchronized, chronological sequence of proliferation and differentiation of cardiac progenitor cells (CPCs). The CPCs are present in both the first and second heart field (SHF). As the SHF contributes entirely to the outflow tract, mutations in the SHF-related genes lead to major arterial pole defects which account for one third of congenital heart defects in newborn children. Understanding the cellular behavior and the underlying molecular mechanisms are of vital importance, not only for early detection but also for precise therapy in a timely manner. Leveraging the PCGC, CDDRC and our SHF single cell RNA-seq datasets, we aim to develop a comprehensive metric for quantitative analysis of SHF cell’s migratory level and epithelial to mesenchymal (EMT) transitional status. Further, we will perform spatiotemporal analysis to identify and validate specific patterns of genes and genotypes associated with SHF-derived CHD as seen in the PCGC and CDDRC databases.

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Archana Rai, Ph.D.

University of Texas Health Science Center, Houston

Archana Rai is a postdoctoral research fellow in the Department of Epidemiology, Human Genetics and Environmental Sciences at University of Texas Health Science Center, Houston. Her research interest is to understand the genetic etiology of congenital heart disease by utilizing a combination of genetics and computational biology and establishing genotype-phenotype correlation in patients with congential heart disease. Before starting her career as a postdoctoral research fellow, she received Ph.D. degree in medical genetics from India. Currently, she is working with Dr. Zeynep Coban Akdemir and interested in extending her approach to congenital heart defects by using a digenic/oligogenic approach. Her current research focuses on understanding the complex genetics of congenital cardiac laterality defects using a digenic/oligogenic model.


Genomic Rare Variant Mechanisms for Congenital Cardiac Laterality Defect: A Digenic/oligogenic Approach

Laterality defects are defined by perturbations in the usual left-right (LR) asymmetry of organs in the body. They involve a spectrum of disorders that range from cardiac D-transposition of the great arteries to complex conditions including situs inversus totalis and heterotaxy, reflecting extensive anatomic heterogeneity. The genetic underpinnings of laterality defects are complex, and the rarity, together with the phenotypic heterogeneity of these defects, challenge the elucidation of complete disease models. Several recent studies suggest that digenic/oligogenic inheritance models may contribute to the complex genetics of these defects. Herein, we will use a digenic/oligogenic analysis approach on exomes/genomes for the identification of contributing variants among laterality cases in data from the 3 congenital heart disease cohorts: 1) Baylor College of Medicine-Genomics Research to Elucidate the Genetics of Rare Diseases (BCM-GREGoR; N=141), Pediatric Cardiac Genomics Consortium (PCGC; N=520) and Gabriella Miller Kids First Pediatric Research program (Kids First; N=228) cohorts. The findings may contribute to the complex genetics of laterality defects.

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Richa Naveed Ahamed, Ph.D.

College of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences (MBRU), Dubai, UAE

Richa is a Postdoctoral researcher at the College of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences (MBRU), Dubai, UAE. She completed Ph.D. in Bioinformatics at SASTRA University, India post which she received the JSPS Postdoctoral fellowship. She carried out her first postdoc research at the Tokyo University of Agriculture and Technology (TUAT), Japan. During this period her research work focused on insilco protein structural analysis using machine learning and molecular dynamics. Currently she is working in a lab co-led by Dr. Bakhrom Berdiev and Dr. Mohammed Uddin. Here she has delved into genomics, with a particular focus on single-cell transcriptomics. In one of her works she has uncovered the molecular convergence of clinically relevant mutations associated with the etiology of Brugada Syndrome. She takes pleasure in exploring different kinds of omics data, leveraging existing tools, and innovating novel applications, to understand complex biological problems. She is particularly interested in investigating rare diseases using a multi-omic approach.


Consanguinity and the genetic architecture of CHD

Although CHD predominates in children, our understanding of the underlying genetic factors remains limited. A significant increase in CHD rates is associated with consanguinity. Offspring from related parents are about 2.0-2.5 times more at risk of having autosomal recessive congenital anomalies than unrelated parents. However, the recessive inheritance of CHD is not completely understood. Here, my goal is to identify the relationship between consanguinity and CHD using the multi-omics datasets available through PCGC, CDDRC, GEO and other resources. I will identify the type of CHD significantly associated with consanguineous families and explore the genomics and cellular diversity in consanguineous populations highlighting the known and novel variants. I hope that the proposed study will provide new insights into CHD cellular and genomic architecture, as well as build the foundation for identifying therapeutic targets.