Browsing by Author "Winter DJ"
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- ItemLow base-substitution mutation rate in the germline genome of the ciliate Tetrahymena thermophila(Oxford University Press, 2016) Long H; Winter DJ; Chang AY-C; Sung W; Wu SH; Balboa M; Azevedo RBR; Cartwright RA; Lynch M; Zufall RAMutation is the ultimate source of all genetic variation and is, therefore, central to evolutionary change. Previous work on Paramecium tetraurelia found an unusually low germline base-substitution mutation rate in this ciliate. Here, we tested the generality of this result among ciliates using Tetrahymena thermophila. We sequenced the genomes of 10 lines of T. thermophila that had each undergone approximately 1,000 generations of mutation accumulation (MA). We applied an existing mutation-calling pipeline and developed a new probabilistic mutation detection approach that directly models the design of an MA experiment and accommodates the noise introduced by mismapped reads. Our probabilistic mutation-calling method provides a straightforward way of estimating the number of sites at which a mutation could have been called if one was present, providing the denominator for our mutation rate calculations. From these methods, we find that T. thermophila has a germline base-substitution mutation rate of 7.61 × 10 − 12 per-site, per cell division, which is consistent with the low base-substitution mutation rate in P. tetraurelia. Over the course of the evolution experiment, genomic exclusion lines derived from the MA lines experienced a fitness decline that cannot be accounted for by germline base-substitution mutations alone, suggesting that other genetic or epigenetic factors must be involved. Because selection can only operate to reduce mutation rates based upon the "visible" mutational load, asexual reproduction with a transcriptionally silent germline may allow ciliates to evolve extremely low germline mutation rates.
- ItemRentrez: An R package for the NCBI eUtils API(The R Foundation for Statistical Computing, 2017-12) Winter DJThe USA National Center for Biotechnology Information (NCBI) is one of the world's most important sources of biological information. NCBI databases like PubMed and GenBank contain millions of records describing bibliographic, genetic, genomic, and medical data. Here I present rentrez, a package which provides an R interface to 50 NCBI databases. The package is well-documented, contains an extensive suite of unit tests and has an active user base. The programmatic interface to the NCBI provided by rentrez allows researchers to query databases and download or import particular records into R sessions for subsequent analysis. The complete nature of the package, its extensive test-suite and the fact the package implements the NCBI's usage policies all make rentrez a powerful aid to developers of new packages that perform more specific tasks.