Monday, October 21, 2019 - 4:00pm to 4:50pm
Gilfillan Auditorium

Speaker Information

David Hendrix
Associate Professor
Department of Biochemistry and Biophysics, and
School of Electrical Engineering and Computer Science


The circadian system is a regulatory network hub that temporally coordinates molecular, cellular and physiological processes. Circadian coordination of neural functions contributes to healthy aging, and the expression of hundreds of genes change in a daily pattern due to circadian regulation. To understand age-related changes in rhythmically expressed genes, we performed around-the-clock RNA-seq and small RNA-seq in the heads of 5-day-old (young) and 55-day-old (old) flies. In this study, we present an analysis of obtained data. Our methods build upon Fourier-based detection of changes in rhythmic expression, and can also detect rhythmic bursts of expression that are not detected with other Fourier-based approaches. Although the net level of rhythmicity remains constant after aging, we observe a "rewiring" of the circadian system. First, we observe changes in the core clock genes, such as the expression of period, which exhibits an increase in the amplitude of mRNA expression and a reduction in protein expression. We observe several stress-response genes, late life cyclers (LLCs), that gain rhythmicity during aging. We also present some preliminary data on oscillatory expression of genes in humans. The computational analysis and data we present will shed new light on the widespread shifts in gene regulation and metabolic pathways to cope with the changing cellular environment during aging. This talk will also provide the much of the biological background needed to understand the analysis.

Speaker Bio

David Hendrix got his Bachelor's degrees in Applied Mathematics and Physics at Georgia Tech. He went on to get his PhD in physics at UC Berkeley, while focusing research on computational and statistical genomics. He went on to do postdocs at Berkeley and MIT in computational biology. 

The Hendrix Lab at Oregon State University employs a broad range of computational approaches, from machine learning to data mining, to investigate questions concerning RNA and DNA. We seek to use computational biology and bioinformatics to analyze RNA sequence and structure, and to uncover new mechanisms of gene regulation, as well as validate known biology.