معرفی
Heath Blackmon is an Associate Professor and Associate Department Head of Graduate Studies in the Department of Biology at Texas A&M University. He leads the Blackmon Lab, focusing on genome evolution, sex chromosome dynamics, and methodological advancements in quantitative genetics and phylogenetics. His research integrates theoretical population genetics, bioinformatics, and molecular cytogenetics, with a particular emphasis on beetle model systems.
Blackmon holds a Ph.D. in Quantitative Biology from the University of Texas at Arlington (2015) and a B.S. in Environmental Science from Oregon State University (2010, Summa Cum Laude). He is affiliated with professional organizations including the Genetics Society of America and the Society for the Study of Evolution.
His research interests center on two core themes: (1) genome evolution, including sex chromosome differentiation and structural genomic changes, and (2) development of computational tools and databases to enhance genetic and phylogenetic analyses. Notable contributions include the Fragile Y Hypothesis, explaining Y chromosome persistence in beetles, and the Tree of Sex Database, a curated resource for insect karyotype data. Recent work explores epistatic effects in genetic architecture and the evolutionary drivers of chromosome number variation in insects and mammals.
Blackmon’s publications reflect interdisciplinary approaches, spanning genomic studies of beetles and birds, methodological innovations in bioinformatics (e.g., the Polly R package), and analyses of evolutionary mechanisms such as drift and natural selection. His lab’s work bridges basic research and applied tools, with implications for understanding genome evolution across diverse taxa.
His academic contributions include leadership roles in graduate training and collaborative projects on topics like chromosome evolution in social insects and the genomic basis of trait divergence in plants. The Blackmon Lab’s research is supported by federal grants and leverages both experimental and computational methodologies.
