The aim of our research is to understand phenotypic evolution by studying the processes by which the genetic networks that underlie complex traits produce variation in those traits and diverge through time. A major feature of many regulatory networks is their robustness (Masel & Siegal 2009). That is, they are tolerant of both environmental and genetic perturbations. Our lab uses a variety of approaches to understand the causes and evolutionary consequences of this robustness. We also study cases where variability (or the lack of robustness) appears to be advantageous. Such cases include so-called bet-hedging mechanisms, whereby a population maximizes its long-term success in an uncertain environment by maintaining subpopulations that thrive under different conditions (Levy et al. 2012). Our work spans two model organisms, yeast and flies, as well as theoretical work involving computational simulations and, more recently, analysis of human data from genome-wide association studies.

One major experimental focus in our lab is on directly identifying and characterizing genes that contribute to robustness of many traits. We have screened the genome of the budding yeast, Saccharomyces cerevisiae, for genes whose deletion increases the variation in the morphologies of individual, genetically identical cells (i.e., the genes normally contribute to robustness against fluctuations in the external or internal cellular environment). Yeast is advantageous for this work because of its wealth of genetic and genomic resources, and because it lends itself to high-throughput analyses. Hundreds of nonessential yeast genes increase morphological variation when deleted, and these genes tend to be highly connected in cellular networks (Levy & Siegal 2008). An even greater proportion of essential genes contribute to robustness against environmental fluctuations (Bauer et al. 2015). We are also testing whether the same mechanisms that buffer environmental fluctuations also buffer the effects of mutations. A longstanding hypothesis in the field has been that the two types of buffering should be linked mechanistically, but we have refuted this connection in the case of the chromatin protein H2A.Z (Richardson et al. 2013). Indeed, our current work supports the view that other genes previously thought to confer greater robustness to mutations might not actually do so (Siegal & Leu 2014).
Another major experimental focus has been on the process of sexual differentiation in Drosophila melanogaster and related flies. Sexual differentiation is a powerful model system for studying the evolution of development because many aspects of sexual morphology, physiology and behavior differ between closely related species, thereby enabling high resolution comparative analysis. Despite this rapid divergence, sexual traits are highly robust within species and indeed are often diagnostic of species. We are using genomic and genetic approaches to identify and characterize regulatory pathways involved in genital development and function in D. melanogaster (e.g., Chatterjee et al. 2011 and Schnakenberg et al. 2011). In current work we are studying how a major perturbation of sexual differentiation impacts variation of sex-related phenotypes within and between fly strains.
A third major experimental focus is on our recent discovery of a putative bet-hedging system in S. cerevisiae using a high-throughput, microscopy-based growth assay that we developed (Levy et al. 2012). Individual yeast cells show a large amount of variation in growth rate, and these differences are transiently heritable. Slower-growing cells are naturally outcompeted by faster-growing cells when conditions are benign, but are better able to survive acute stress. Different strains of yeast differ in their growth-rate distributions, suggesting that ecological pressures might shape bet-hedging strategies in nature (Ziv et al. 2013). We are currently working on trying to understand the molecular mechanism underlying heterogeneity in growth rate and stress resistance.

Our research is funded by NIH National Institute of General Medical Sciences MIRA award 1R35GM118170 (“Genetic and Nongenetic Variation in Complex Traits“).