Author:
Smith Douglas R.,Quinlan Aaron R.,Peckham Heather E.,Makowsky Kathryn,Tao Wei,Woolf Betty,Shen Lei,Donahue William F.,Tusneem Nadeem,Stromberg Michael P.,Stewart Donald A.,Zhang Lu,Ranade Swati S.,Warner Jason B.,Lee Clarence C.,Coleman Brittney E.,Zhang Zheng,McLaughlin Stephen F.,Malek Joel A.,Sorenson Jon M.,Blanchard Alan P.,Chapman Jarrod,Hillman David,Chen Feng,Rokhsar Daniel S.,McKernan Kevin J.,Jeffries Thomas W.,Marth Gabor T.,Richardson Paul M.
Abstract
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.
Publisher
Cold Spring Harbor Laboratory
Subject
Genetics(clinical),Genetics
Cited by
222 articles.
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