TY  - JOUR
A1  - Smith, Douglas R.
A1  - Quinlan, Aaron R.
A1  - Peckham, Heather E.
A1  - Makowsky, Kathryn
A1  - Tao, Wei
A1  - Woolf, Betty
A1  - Shen, Lei
A1  - Donahue, William F.
A1  - Tusneem, Nadeem
A1  - Stromberg, Michael P.
A1  - Stewart, Donald A.
A1  - Zhang, Lu
A1  - Ranade, Swati S.
A1  - Warner, Jason B.
A1  - Lee, Clarence C.
A1  - Coleman, Brittney E.
A1  - Zhang, Zheng
A1  - McLaughlin, Stephen F.
A1  - Malek, Joel A.
A1  - Sorenson, Jon M.
A1  - Blanchard, Alan P.
A1  - Chapman, Jarrod
A1  - Hillman, David
A1  - Chen, Feng
A1  - Rokhsar, Daniel S.
A1  - McKernan, Kevin J.
A1  - Jeffries, Thomas W.
A1  - Marth, Gabor T.
A1  - Richardson, Paul M.
T1  - Rapid whole-genome mutational profiling using next-generation sequencing technologies
Y1  - 2008/10/01 
JF  - Genome Research 
JO  - Genome Research 
SP  - 1638 
EP  - 1642 
DO  - 10.1101/gr.077776.108 
VL  - 18 
IS  - 10 
UR  - http://genome.cshlp.org/content/18/10/1638.abstract 
N2  - Forward genetic mutational studies, adaptive evolution, and phenotypic screening are powerful tools for creating new variant organisms with desirable traits. However, mutations generated in the process cannot be easily identified with traditional genetic tools. We show that new high-throughput, massively parallel sequencing technologies can completely and accurately characterize a mutant genome relative to a previously sequenced parental (reference) strain. We studied a mutant strain of Pichia stipitis, a yeast capable of converting xylose to ethanol. This unusually efficient mutant strain was developed through repeated rounds of chemical mutagenesis, strain selection, transformation, and genetic manipulation over a period of seven years. We resequenced this strain on three different sequencing platforms. Surprisingly, we found fewer than a dozen mutations in open reading frames. All three sequencing technologies were able to identify each single nucleotide mutation given at least 10–15-fold nominal sequence coverage. Our results show that detecting mutations in evolved and engineered organisms is rapid and cost-effective at the whole-genome level using new sequencing technologies. Identification of specific mutations in strains with altered phenotypes will add insight into specific gene functions and guide further metabolic engineering efforts. 
ER  -