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.