Tesfaye B. Mersha, PhD

Bio

My career in genetics and research began with an interest in understanding the interplay between biology and the environmental conditions that contribute to disease. Over time, I’ve broadened my research interests to include genomics, genetic ancestry, racial disparities, personalized medicine and bioinformatics. One of my areas of expertise is multi-omics (genomics, epigenomics, transcriptomics, microbiome, proteomics and metabolomics). For more than 10 years, I’ve worked to integrate multi-omics with statistical genetics and bioinformatics methods to uncover the molecular architecture of medical conditions, such as asthma and asthma-related allergic diseases. My Lab performs a variety of computational and applied data analysis projects, including the development of statistical and genome informatics tools that enable multiethnic admixture, genome-wide association and omics integration studies of biomedical traits. Our goal is to develop an in-depth understanding of the intricate interactions between genomic variations and environmental exposure in the etiology of complex diseases — and then translate these findings into clinical practice through collaborations with clinicians. Some of our previous and ongoing research efforts include: • Using admixture mapping to localize asthma liability genes in admixed populations • Studying the interaction of asthma risk variants and environmental exposures that shape racial disparities • Identifying genetic/regulatory networks to recognize potential functional variants associated with asthma and atopic dermatitis using whole transcriptome RNA-seq profiling • Investigating the role of microbiome and epigenome on asthma pathogenesis among immigrants • Multi-omics integration using deep learning and other machine learning algorithms. My Lab is composed of a diverse and collaborative group of experts from various fields, including biostatisticians, bioinformaticians and wet lab researchers. We work closely together to tackle complex scientific questions with a focus on multi-omics approaches to understand the environmental and genetic factors that contribute to complex diseases