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Reflections on Schrödinger's Reflections on Schrödinger’s “What is life?” Nick Barton “What is life?” - Trinity College Dublin, 1943 - contrasts deterministic with statistical laws - heredity must be based on a stable “aperiodic crystal” - X-rays induce mutations, implying a small target Schrödinger’s ideas had little direct influence, yet drew many Into molecular biology. Contrast molecular with evolutionary biology Does life depend on general principles, independent of details? Judson, 1979 The Eighth Day of Creation Barton et al. 2007, Evolution Watson & Crick, 1953: structure of DNA 1953-1962: - DNA-> RNA-> protein - genetic code (Crick…Nirenberg) - gene regulation (Jacob, Monod) - protein structure (Perutz, Kendrew) Ingenious arguments failed to decipher the code - e.g. Gamow’s argument from DNA structure Extraordinary technical developments - yet few fundamental advances in 50 years? Evolutionary biology: a synthesis between Darwin and Mendel Darwin, 1859, Origin of species Mendel, 1866 Evolution was widely accepted, yet natural selection was not Rediscovery of Mendel’s work in 1900 led to bitter disputes Eventually, population genetics led to the evolutionary synthesis Population genetics: - sophisticated theory, based on simple genetics - little data on natural variation - showed that even weak selection can be effective (t ~ 1/s) Discovery of abundant molecular variation in 1966: - largely explained by neutral theory - shift to statistical inference Now, an abundance of DNA sequence …. General principles: - diffusion of genes through space - the coalescent process - quantitative genetics Diffusion of genes across a hybrid zone in Podisma pedestris A. majus pseudomajus A. m. striatum SNPs across the Planoles transect Individual (West to East) Flavia Sulf Locus (ordered) Rosea Eluta cp ROS ELUTA The coalescent process: - rate of coalescence of lineages ~ 1/2N - with constant population size, coalescence times ~ exp(-t/2N) - distribution of coalescence times across the genome -> N(t) Li & Durbin, 2011 infer N(t) for humans: What can we really infer about ancestral populations ? Quantitative genetics: Fisher (1918) - VP = VG+VE = VA+VD+VAA+VAD … VE - variance components can be estimated - variance components are insensitive to selection - the infinitesimal model Given sequence data, why not just find the genes ? Wood et al., Nature 2014: human height ~250,000 people -> 700 variants explain 20% of variance In practice, we cannot account for most of the variance: - how can we use sequence data ? Genomic selection improves the efficiency of artificial selection, assuming the infinitesimal model How can we best understand organisms? - even complete information may not be enough - complex traits may evolve via subtle changes at many sites How much can we know? IST Austria Institute of Science and Technology • PhD granting research institution dedicated to basic research in biology, neuroscience, computer science, math, physics and interdisciplinary areas • Located on the outskirts of Vienna; working language is English • 35 research groups from 40 countries; will grow to 90 groups by 2026 IST Austria invites applications for: • Student interns (apply by February 15, 2016 for summer 2016) • PhD students (apply by January 15, 2016 for September 2016 start date) • Postdocs (search by group leader or ISTFELLOW program) • Assistant professors (tenure track) and professors (tenured) (upcoming call November 2, 2015) www.ist.ac.at .
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