Computational Genomics Reveal Insights into the Biology of Non-model Organisms
On Thursday, April 18, 2024, the University of Houston Hewlett Packard Enterprise Data Science Institute hosted an online lecture titled "Computational Genomics Reveal Insights into the Biology of Non-model Organisms." Richard Meisel from UH's Department of Biology and Biochemistry presented his research on applying genomic methods to non-traditional study organisms. Meisel highlighted how recent technological advancements have made genomic analysis more accessible across various biological fields.
The lecture focused on projects from Meisel's lab, a key example being their work on the house fly, Musca domestica, which possesses a complex sex determination system. Meisel’s team used advanced sequencing technologies and computational methods to assemble a high-quality genome for the house fly. This improved genome assembly allowed them to investigate the genetic basis of sex determination in this species, revealing variations in the male-determining chromosomes across different populations. The research uncovered how environmental factors, particularly temperature, play a role in the distribution of different male-determining chromosomes.
Another significant aspect of the talk was the demonstration of how computational genomics can bridge the gap between model and non-model organisms. Meisel’s team used data from the well-studied fruit fly, Drosophila melanogaster, to inform experiments on the house fly, leading to the identification of genes involved in mating behavior.
Throughout the presentation, Meisel emphasized the importance of integrating various approaches, including computational genomics, organismal experiments and comparative studies between model and non-model organisms. This multifaceted strategy allows researchers to address fundamental questions in biology from both mechanistic and evolutionary perspectives. Meisel highlighted the technical challenges of genomic assembly, such as dealing with repetitive DNA sequences. Long-read sequencing technologies and novel computational approaches have helped overcome these obstacles.
Richard Meisel, Ph.D. completed his postdoctoral training in the Department of Molecular Biology and Genetics at Cornell University. The Meisel lab uses lab experiments, genomic data and molecular biology techniques to study a broad range of questions in evolutionary biology. The research addresses how environmental variation and sex differences influence genetic and phenotypic diversity within populations and between species. Meisel’s lecture is part of an ongoing series hosted by the UH Hewlett Packard Enterprise Data Science Institute, aimed at showcasing cutting-edge research that leverages high-performance computing resources for scientific discovery.