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Saunders Genetics LectureAdd to your list(s) Download to your calendar using vCal
If you have a question about this talk, please contact Charlotte Groocock. This will be the first of a prestigious series of lectures held in commemoration of the life and work of Edith Rebecca (Becky) Saunders who made major contributions to the understanding of genetics and heredity at the beginning of the 20th century. Saunders entered Newnham College in 1884, continued her postgraduate research as a Bathurst student from 1888 to 1889, and later became the director of the Balfour Biological Laboratory for Women in 1899. She was Director of Studies for Natural Sciences at Newnham between 1918 and 1925 and President of the Genetical Society from 1936-1938. The Saunders Genetics Lectures will celebrate the best contemporary research in Genetics today, with invited speakers being selected on the basis of their contribution to research that resonates with the activities of the Department of Genetics and more widely across the School of Biological Sciences. We are delighted to welcome Professor Richard Lenski from Michigan State University as our inaugural speaker for the 2018 Saunders Genetics Lecture to deliver a talk on Dynamics of Phenotypic and Genomic Evolution in a Long-Term Experiment with E. coli. For further information about Richard and his research please visit http://myxo.css.msu.edu/ Abstract: Evolution is an on-going process, one that can be studied experimentally in organisms with rapid generations. We have maintained 12 populations of Escherichia coli in a simple environment for over 65,000 generations. The aims of this experiment are to characterise the tempo and mode of evolution, and to examine the repeatability of phenotypic and genomic changes. We have quantified the dynamics of adaptation by natural selection, documented many cases of parallel evolution, observed changes in the underlying mutation rate, and seen the appearance of a novel metabolic function that transcends the usual definition of E. coli as a species. We have sequenced hundreds of complete genomes to find the mutations in time-series of samples from the populations. These genomic data provide insights into the dynamic coupling of phenotypic and genotypic evolution during periods of optimisation and innovation.
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