GCAT-SEEKquence The Genome Consortium for Active Teaching NextGen Sequencing Group NextGen Sequencing Request Form Complete fields below, save file with your last name at the beginning of the filename (e.g. newman-GCAT-SEEK Sequence request form.pdf) and email to Vincent Buonaccorsi <BUONACCORSI@juniata.edu> A. Contact Information 1. Name: Dr. Lisa Scheifele 2. Department: Biology 3. Institution: Loyola University Maryland 4. Phone Number: 410-617-2316 5. Email Address lzscheifele@loyola.edu B. Project Information 1. Title: Resequencing of Saccharomyces cerevisiae strains following lab evolution 2. Category: Small eukaryotic genome resequencing 3. Total amount of sequence requested: 420 Mbp per genome for up to 4 genomes 4. Preferred technology: Illumina or Solid 5. Do you have funds for a partial run next Spring? No C. Describe the background, hypotheses and specific aims (500 words max) Yeast cells serve as an ideal model system in which to identify the genomic changes that underlie evolution as the rapid generation time of yeast cells enables hundreds of generations of evolution within reasonably short time periods. In addition, yeast can be easily cultured in chemostat apparatuses, which enable evolution under highly defined and constant conditions. Genomic analyses have identified chromosomal changes in evolved yeast cells, including recurrent genome rearrangements in evolved yeast clones (Dunham et al. 2002). While microarray analysis using high-density arrays has enabled us to map many of these large-scale chromosomal changes (Gresham et al. 2006), these microarray studies are rapidly being supplemented by resequencing of evolved yeast strains. Sequencing offers additional the benefits of identifying adaptive point mutations, mapping balanced chromosome translocations, and fine mapping of the breakpoints of chromosome rearrangements (Araya et al. 2010). Many chromosome rearrangements have been mapped by microarray comparative genome hybridization, and these rearrangements recur during evolution in medium that is limited for a single nutrient (Dunham et al. 2002; Gresham et al. 2008). While the use of single nutrient limitation makes it easier to identify those genomic changes that are most likely to be adaptive, these conditions are highly artificial. To achieve evolution under conditions that are more relevant to yeast cells in wild environments, we have evolved yeast cells in chemostats that are limited for multiple nutrients, beginning with concurrent glucose and sulfur limitation. In addition to wild-type yeast cells we have also evolved a unique isogenic series of retrotransposon overdose (RO) strains that contain an elevated number of retrotransposons dispersed throughout the genome (Scheifele et al. 2009). Because many of the chromosome rearrangements that are present in evolved yeast cells are mediated by unequal recombination between retrotransposons we predicted that these strains would be poised to undergo rearrangement and would therefore achieve a greater number of chromosome rearrangements. When we evolve these RO yeast cells under single nutrient limitation, we observe the same chromosome changes have been previously described in wild-type cells: amplification of the SUL1 sulfur transporter following sulfur limitation and amplification of the hexose transporters HXT6 and HXT7 or amplification of chromosome 14L following glucose limitation (Scheifele et al, manuscript submitted). We obtain different results, however, when these RO strains are evolved in medium limiting for both glucose and sulfur. Some evolved cells contain amplifications of both the glucose and sulfur transporters, but other evolved clones contain no detectable chromosome changes despite the increased fitness of these evolved clones in the medium that is limited for glucose and sulfur (Scheifele et al, manuscript submitted). These results suggest that there are genomic changes that underlie adaptation to these conditions that remain to be identified and for which the resolution of microarray-based mapping technologies are insufficient. We therefore propose to use next-generation resequencing of these evolved RO clones to map the point mutations, chromosome rearrangements and retrotransposition events that are present in the evolved clones. D. Describe the methods [sample prep, calculation of amount of sequence required, analysis plan] We have recently used Illumina sequencing to obtain the complete genome sequence for four of the unevolved RO strains from 10 micrograms of yeast DNA. In collaboration with Dr. Sarah Wheelan, a bioinformaticist at Johns Hopkins, we are currently analyzing this data to identify genome changes in unevolved RO strains and to map the position of all retrotransposons. This pilot project was intended to provide reference unevolved RO genomes against which we can compare our evolved strains. We now have four RO strains that have been evolved in medium that was limiting for both glucose and sulfur but which do not contain detectable genome rearrangements. By obtaining the sequence of these four strains, we can identify mutations that enable adaptation to more complex and physiologically relevant environmental conditions. We will sequence 10 micrograms of genomic DNA from each of the four evolved clones, and samples could be ready at any time. The barcoded libraries from each of the four strains could be combined in a single lane for sequencing using paired end reads. The yeast genome is 14 Mbp, so 30-fold coverage would correspond to 420 Mbp, and sequencing all four strains would require 1.68 Gbp of sequence. E. Describe the role and number of undergraduates involved in the project, and how they would benefit. I am introducing a senior seminar in Genomics (12 students) during the fall semester 2012 in which students will analyze the whole-genome sequence data that we recently obtained for 4 unevolved RO yeast strains using tools such as NextGENe or the Broad Institute’s Integrated Genomics Viewer. This will be a writing intensive course where students will write a research paper that incorporates their analysis. My hope is to obtain additional sequencing data in the spring of 2013 (of the evolved RO strains) that students could then analyze in the fall 2013 genomics course. I also anticipate that this project will benefit the research students in my laboratory (average of 2-4 per year). They will not only participate in the preparation of genomic DNA for sequencing and analysis of the sequencing data, but they will also use traditional yeast genetics tools to test whether the genome changes that we identify by sequencing confer a fitness advantage when introduced into unevolved cells. F. I agree to administer the GCAT-SEEK pre- and post-activity assessment test for students and to complete the faculty post-utilization survey. __X_ yes, ____ no G. References Araya, C. L., Payen, C., Dunham, M. J., and Fields, S. 2010. Whole-genome sequencing of a laboratory-evolved yeast strain. BMC Genomics 11: 88. Dunham, M. J., Badrane, H., Ferea, T., Adams, J., Brown, P. O., Rosenzweig, F., and Botstein, D. 2002. Characteristic genome rearrangements in experimental evolution of Saccharomyces cerevisiae. Proc. Natl. Acad. Sci. U. S. A. 99: 16144-16149. Gresham, D., Desai, M. M., Tucker, C. M., Jenq, H. T., Pai, D. A., Ward, A., DeSevo, C. G., Botstein, D., and Dunham, M. J. 2008. The repertoire and dynamics of evolutionary adaptations to controlled nutrient-limited environments in yeast. PLoS Genet. 4: e1000303. Gresham, D., Ruderfer, D. M., Pratt, S. C., Schacherer, J., Dunham, M. J., Botstein, D., and Kruglyak, L. 2006. Genome-wide detection of polymorphisms at nucleotide resolution with a single DNA microarray. Science 311: 1932-1936. Scheifele, L. Z., Cost, G. J., Zupancic, M. L., Caputo, E. M., and Boeke, J. D. 2009. Retrotransposon overdose and genome integrity. Proc. Natl. Acad. Sci. U. S. A. 106: 13927-13932.