Who is this really?
Gentle Reader, I presume thou wilt be very inquisitive to know what antic or personate actor this is, that so insolently intrudes upon this common theatre to the world’s view…
- Robert Burton, The Anatomy of Melancholy (1621)
Welcome to Gene Logic. Your host is Michael A. White, PhD, a biochemist/systems biologist/geneticist/genomicist currently working as a postdoctoral researcher in the Department of Genetics and the Center for Genome Sciences & Systems Biology at the Washington University in St. Louis School of Medicine.
The obsession that keeps me going is this: I want to know how living behavior arises as a consequence of the interactions of non-living parts.
More specifically, I want to understand how genes make decisions. Genes make decisions? Yes - the fundamental problem faced by a gene is to read the state of the world and figure out whether it should be expressed. Your body is comprised of intricate arrangements of many different types of cells, despite the fact that most of your ten trillion cells have exactly the same genome. This is possible only because genes make decisions. Genes make their decisions using associated stretches of regulatory DNA. My goal is to understand how regulatory DNA encodes the information to make correct decisions.
Read about my research below. My CV is here. Grab your favorite brew and join me for conversation at the Finch and Pea, especially if you like science poetry or science fiction. Read my weekly contribution to Pacific Standard. Check out what we’re up to in the Cohen lab. See what I’m reading over at the stack. Follow my latest findings on genes, books, science fiction, and whatever else. My tweets are @genologos. Contact me via Gmail: email@example.com
For the aficionados, a more technical overview of my research interests:
Genome Technologies and Biophysical Models to Understand How DNA Encodes Cis-Regulatory Information
A major function of the genome is to carry the information that directs gene expression, yet we do not understand how this information is physically encoded. Cracking the genetic code for amino acids was a crucial achievement, enabling us to predict the molecular effects of DNA sequence changes within protein-coding genes. We lack a similar ability to interpret sequence changes in regulatory DNA, because we do not understand how primary DNA sequence determines the transcriptional specificity of enhancers and promoters, and we do not understand how regulatory DNA distinguishes itself from the vast excess of non-functional DNA within large eukaryotic genomes. The short, degenerate binding motifs for individual transcription factors (TFs) do not, by themselves, account for the specificity of cis-regulation in large genomes, and the contribution made by other sources of specificity such as chromatin context, nucleosome positioning, combinatorial TF binding, and DNA structural features, is poorly understood. Of the hundreds of thousands of cis-regulatory elements predicted by the ENCODE consortium and others, only a small fraction have been assayed for function, which limits our power to identify the primary sequence features that define genuinely functional regulatory elements from spurious sites.
I approach this problem both experimentally and computationally. Since the current bottleneck in genomic studies of gene regulation is functional validation of predicted cis-regulatory elements, I use a new, massively parallel reporter gene assay to simultaneously test the function of thousands of predicted elements.
I use my experimental results to parameterize thermodynamic models of gene regulation, which attempt to explain gene regulation by modeling the interaction energies between transcription factors and DNA, and between different transcription factors. To complete the cycle of experiment-modeling-validation, I use synthetic biology to explicitly test the importance of particular DNA sequence features that are predicted by the model to define a functional cis-regulatory site. These sequence features include the position and orientation of binding motifs, nucleosome positioning signals, and sequences that distort DNA shape.
By traversing cycles of model building and model testing, I aim to understand how multiple sources of cis-regulatory specificity determine gene expression patterns, and improve our ability to interpret the regulatory potential of non-coding DNA, which is currently a major limiting point in our efforts to understand the influence of genetic variation on human health.