YEAST EXPERIMENTAL EVOLUTION
We study the molecular basis of evolution. Our goal is to understand how phenotypic selection drives genotypic change. We work with the yeast, Saccharomyces cerevisiae, the same yeast that is used to bake bread and brew beer. Using this simple but powerful genetic system we study evolution in real-time in our laboratory. Our work lies at the intersection of evolutionary biology, molecular biology, and quantitative genetics. Below are three examples of ongoing research in our lab:
Eukaryotic genomes contain thousands of genes organized into complex and interconnected genetic interaction networks. Identifying genetic interactions that arise during experimental evolution is important because (i) a global understanding of genetic interaction networks, and how network perturbations affect cellular function, is crucial to preventing and treating human disease, and (ii) genetic interactions impose constraints on evolution by permitting (or prohibiting) subsequent evolutionary change. We are developing high-throughput methods to quantify the fitness effects of hundreds of mutations from our laboratory-evolved populations, both individually and in combination with each other. We have demonstrated that both genetic hitchhiking (luck) and genetic interactions play a significant role in determining which mutations ultimately succeed and fail. By studying evolution in hundreds of replicate populations, we hope to learn how initial steps along an evolutionary path constrain future evolution.
PLOIDY AND EVOLUTION
Ploidy varies considerably in the natural world from bacteria that are mostly haploid to some plants that can exist as decaploid. Furthermore, all sexual organisms alternate between ploidy states through gamete fusion and meiosis. The budding yeast, Saccharomyces cerevisiae, can be stably propagated asexually in both haploid and diploid states, providing an ideal system for studying the effect of ploidy on adaptation. In principle, how ploidy impacts adaptation depends largely on assumptions regarding the dominance of new beneficial mutations. Both theory and experimental work support the notion that haploids adapt faster than diploids, presumably due to access to recessive beneficial mutations. Curiously, however, many laboratory-evolving haploid populations undergo whole-genome duplication events yielding populations of diploid yeast. We are using experimental evolution to study the causes and consequences of ploidy changes during evolution. One immediate effect is that diploids accumulate recessive deleterious mutations which can be revealed by traditional tetrad dissections.
Nearly all genomes contain genetic parasites that replicate selfishly, often at a cost to the host genome. Evolutionary arms races between selfish genetic elements and their hosts drive speciation events and have contributed to the origin of sex and the evolution of sex chromosomes. All genomes, including the human genome, exhibit clear signatures of past intragenomic conflicts. Yet our understanding of intragenomic conflict is limited in that few systems exist to study the mechanisms by which evolution resolves these conflicts. We are leveraging experimental evolution to study various types of genetic conflict in yeast, including sexual conflict, gene drive, and the selfish intracellular “Killer” virus. The yeast Killer virus is an encapsulated double-stranded RNA virus that encodes both a Killer toxin and its corresponding immunity component. An infected host secretes the toxin, which kills non-Killer-containing cells. A Killer+ strain produces a zone of inhibition by impeding the growth of a sensitive lawn (left). An evolved strain that has lost the Killer virus no longer produces the zone of inhibition (right).
Fisher KJ, Buskirk SW, Vignogna RC, Marad DM, Lang GI. 2018. Adaptive genome duplication affects patterns of molecular evolution in Saccharomyces cerevisiae. PLoS Genetics. May 25;14(5):e1007396. doi: 10.1371/journal.pgen.1007396.
Marad DM, Buskirk SW, Lang GI. 2018. Altered access to beneficial mutations slows adaptation and biases fixed mutations in diploids. Nature Ecology & Evolution. May;2(5):882-889. doi: 10.1038/s41559-018-0503-9. Epub 2018 Mar 26.
Lang GI. 2018. Measuring mutation rates using the Luria-Delbrück fluctuation assay. Methods Mol Biol. 1672:21-31. Epub 2017 Oct 17.
Buskirk SW, Peace RE, Lang GI. 2017. Hitchhiking and epistasis give rise to cohort dynamics in adapting populations. PNAS. Jul 18. pii: 201702314.
Fisher KJ and Lang GI. 2016. Invited Review, Experimental evolution in fungi: An untapped resource. Fungal Genetics and Biology. Sep;94:88-94. Epub Jun 30.
Frenkel EM, McDonald MJ, Van Dyken JD, Kosheleva K, Lang GI, and Desai MM. 2015. Crowded growth leads to the spontaneous evolution of semistable coexistence in laboratory yeast populations. Proc Natl Acad Sci U S A Aug 3. pii: 201506184.
Lang GI, and Desai MM. 2014. Invited Review Article: The spectrum of adaptive mutations in experimental evolution. Genomics. Dec;104(6 Pt A):412-6. doi: 10.1016/j.ygeno.2014.09.011. Epub 2014 Sep 28.
Lang GI, Rice DP, Hickman MJ, Sodergren E, Weinstock GM, Botstein D, and Desai MM. 2013. Pervasive genetic hitchhiking and clonal interference in forty evolving yeast populations. Nature, Aug 29;500(7464):571-4.
Lang GI, Parsons L, and Gammie A. 2013. Mutation rates, spectra, and genome-wide distribution of spontaneous mutations in mismatch repair deficient yeast. G3, Sep 4;3(9):1453-65.
Lang GI, Botstein D, and Desai MM. 2011. Genetic variation and the fate of beneficial mutations in asexual populations. Genetics. Jul;188(3):647-61.
Lang GI, Murray AW. 2011. Mutation rates across budding yeast Chromosome VI are correlated with replication timing. Genome Biology and Evolution. 3:799-811.
Lang GI, and Botstein D. 2011. A test of the coordinated expression hypothesis for the origin and maintenance of the GAL cluster in yeast. PLoS ONE. Sep 22; 10.1371/journal.pone.0025290.
Lang GI, Murray AW, and Botstein D. 2009. The cost of gene expression underlies a fitness trade-off in yeast. Proc Natl Acad Sci U S A. Apr 7;106(14):5755-60.
Lang GI, Murray AW. 2008. Estimating the per-base-pair mutation rate in the yeast Saccharomyces cerevisiae. Genetics. Jan;178(1):67-82.
Hepfer CE, Arnold-Croop S, Fogell H, Steudel KG, Moon M, Roff A, Zaikoski S, Rickman A, Komsisky K,Harbaugh DL, Lang GI, Keil RL. 2005. DEG1, encoding the tRNA:pseudouridine synthase Pus3p, impacts HOT1-stimulated recombination in Saccharomyces cerevisiae. Mol Genet Genomics. Dec;274(5):528-38.
PhD, Infectious Diseases, University of Georgia
BS, Biochemistry and Molecular Biology, Pennsylvania State University
Ph.D., Biochemistry and Molecular Biology, SUNY Upstate Medical University
National Technical University of Athens, Greece
MS Biology, Long Island University, C.W. Post
BS Biology, Long Island University, C.W. Post
BS Biology, Ursinus College
BS Biochemistry and Molecular Biology, DeSales University
Jasper Jeffrey, Class of 2019
Alecia Rokes, Class of 2019