Scalable continuous culture-based approaches for understanding evolution and cancer

dc.contributor.advisorDunham, Maitreya J
dc.contributor.authorMiller, Aaron W.
dc.date.accessioned2016-04-06T16:31:57Z
dc.date.issued2016-04-06
dc.date.submitted2016-03
dc.descriptionThesis (Ph.D.)--University of Washington, 2016-03
dc.description.abstractUnderstanding the genetic basis of adaptation in evolution is an area of research that has the potential to characterize the forces that have shaped the evolution of all life. For much of history, it was far easier to see evolution’s effect than its genetic cause; however, modern sequencing methods are for the first time making it possible to comprehensively characterize the genetic basis of evolution. As such, there is a renaissance for experimental microbial evolution, as researchers attempt to characterize the genetic basis of adaptation in a given environment. However, controlling the environment is an ongoing challenge in the field. Use of continuous culture is an ideal way to control the environment in which microbes are grown and to provide an invariant selection over time. One disadvantage of continuous cultures is that they are generally carried out in low throughput, thus limiting what we can learn from them. The focus of my dissertation has been the marriage of multiplexed continuous cultures that I developed in graduate school with selection and sequencing techniques to allow for a more comprehensive view of the genetic basis of adaptation in Saccharomyces cerevisiae. Additionally, I have developed a new continuous culture-based method for multiplexed determination of mutation rate, which I have applied to the study of mismatch repair genes relevant to Lynch syndrome risk in humans.
dc.embargo.lift2018-03-27T16:31:57Z
dc.embargo.termsRestrict to UW for 2 years -- then make Open Access
dc.format.mimetypeapplication/pdf
dc.identifier.otherMiller_washington_0250E_15462.pdf
dc.identifier.urihttp://hdl.handle.net/1773/35591
dc.language.isoen_US
dc.subjectBioinformatics; Cancer; Evolution; Genetics; Genomics; Technology
dc.subject.otherGenetics
dc.subject.otherBioinformatics
dc.subject.otherBiology
dc.subject.othergenetics
dc.titleScalable continuous culture-based approaches for understanding evolution and cancer
dc.typeThesis

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