Characterize the transcriptional and epigenetic networks that control FRT TRM identity. Our phenotypic characterization has revealed a significant heterogeneity among the TRM populations. We hypothesize that FRT TRM are transcriptionally diverse and their transcriptional heterogeneity is driven by differential chromatin accessibility.

Primary tumors shed circulating tumor cells (CTCs) into the bloodstream that metastasize preferentially to distant organs, resulting in 90% of cancer related fatalities. For example, estrogen receptor positive (ER+) breast cancers exhibit high rates of metastasis to bone, with decreased rates to liver and lung.

One of the most important challenge in biological science today is to elucidate the extent to which complex experiments, which measure hundreds of thousands of variables, can be analyzed to generate consistent and global signal when repeated, to identify local signal related to tissues, cancer types or population structure. Importantly, we must include the intrinsic diversity of variation across different studies and control for technical confounders as part of this task.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of coronavirus disease 19 (COVID-19). Spike protein is the primary antigenic target for COVID vaccines and interfering with the interface between RBD (Receptor Binding Domain) of spike and ACE2 is the mechanism of action for the majority of existing therapeutic antibodies, indicating the importance of RBD and its binding to the cellular receptor for controlling SARS-CoV-2. It is unclear whether there are any intrinsic cellular proteins that inhibit viral entry of SARS-CoV-2.

Dr. Sohini Ramachandran will develop new computational and analytical methodologies to identify risk alleles for leukemia that differ in incidence across ethnic groups and genders, and apply these methods to genome wide association studies. Analyses of X-linked factors offer new insights into human genomic variation.

While infection biology has largely focused on studying the immune response to a single infection, it is becoming increasingly clear that many infections involve more than one pathogen.

Nonlinear genetic effects have been proposed as key contributors to missing heritability – the proportion of heritability is a trait that is not explained by the top associated additive variants in genome-wide association (GWA) studies. To this end, probabilistic machine learning approaches have been shown to be useful tools that exhibit great performance gains in genomic selection-based analyses.

Fungal pathogens exhibit considerable genetic plasticity, with both microvariation and chromosome-level rearrangements frequently enabling adaptation to host and environmental pressures.  Several genera of fungi are important human pathogens, with invasive fungal infections responsible for the death of approximately 1.5 to 2 million people worldwide each year. Candida species are the most prominent cause of invasive fungal disease in the US, with the major protagonist being Candida albicans.

Gene regulatory mechanisms are critical for proper cellular and protein function, and modern molecular biology has linked numerous pathologies to dysregulation of these processes. Although modification of the genome to correct pathogenic mutations is a promising therapeutic approach, these efforts cannot be successful without knowledge of the underlying biochemistry of protein machinery such as CRISPR-Cas9 (Cas9).