Bulletin of the American Physical Society
APS March Meeting 2017
Volume 62, Number 4
Monday–Friday, March 13–17, 2017; New Orleans, Louisiana
Session C5: Evolutionary Dynamics of GenomesFocus
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Sponsoring Units: DBIO Chair: Benjamin Greenbaum, Icahn School of Medicine, Mount Sinai Room: 264 |
Monday, March 13, 2017 2:30PM - 3:06PM |
C5.00001: Theory of microbial genome evolution Invited Speaker: Eugene Koonin Bacteria and archaea have small genomes tightly packed with protein-coding genes. This compactness is commonly perceived as evidence of adaptive genome streamlining caused by strong purifying selection in large microbial populations. In such populations, even the small cost incurred by nonfunctional DNA because of extra energy and time expenditure is thought to be sufficient for this extra genetic material to be eliminated by selection. However, contrary to the predictions of this model, there exists a consistent, positive correlation between the strength of selection at the protein sequence level, measured as the ratio of nonsynonymous to synonymous substitution rates, and microbial genome size. By fitting the genome size distributions in multiple groups of prokaryotes to predictions of mathematical models of population evolution, we show that only models in which acquisition of additional genes is, on average, slightly beneficial yield a good fit to genomic data. Thus, the number of genes in prokaryotic genomes seems to reflect the equilibrium between the benefit of additional genes that diminishes as the genome grows and deletion bias. New genes acquired by microbial genomes, on average, appear to be adaptive. Evolution of bacterial and archaeal genomes involves extensive horizontal gene transfer and gene loss. Many microbes have open pangenomes, where each newly sequenced genome contains more than 10{\%} `ORFans', genes without detectable homologues in other species. A simple, steady-state evolutionary model reveals two sharply distinct classes of microbial genes, one of which (ORFans) is characterized by effectively instantaneous gene replacement, whereas the other consists of genes with finite, distributed replacement rates. These findings imply a conservative estimate of at least a billion distinct genes in the prokaryotic genomic universe. [Preview Abstract] |
Monday, March 13, 2017 3:06PM - 3:18PM |
C5.00002: Statistical Physics of Population Genetics in the Low Population Size Limit Gurinder Atwal The understanding of evolutionary processes lends itself naturally to theory and computation, and the entire field of population genetics has benefited greatly from the influx of methods from applied mathematics for decades. However, in spite of all this effort, there are a number of key dynamical models of evolution that have resisted analytical treatment. In addition, modern DNA sequencing technologies have magnified the amount of genetic data available, revealing an excess of rare genetic variants in human genomes, challenging the predictions of conventional theory. Here I will show that methods from statistical physics can be used to model the distribution of genetic variants, incorporating selection and spatial degrees of freedom. In particular, a functional path-integral formulation of the Wright-Fisher process maps exactly to the dynamics of a particle in an effective potential, beyond the mean field approximation. In the small population size limit, the dynamics are dominated by instanton-like solutions which determine the probability of fixation in short timescales. These results are directly relevant for understanding the unusual genetic variant distribution at moving frontiers of populations. [Preview Abstract] |
Monday, March 13, 2017 3:18PM - 3:30PM |
C5.00003: Genome-Wide Motif Statistics are Shaped by DNA Binding Proteins over Evolutionary Time Scales Long Qian, Edo Kussell The composition of genomes with respect to short DNA motifs impacts the ability of DNA binding proteins to locate and bind their target sites. Since nonfunctional DNA binding can be detrimental to cellular functions and ultimately to organismal fitness, organisms could benefit from reducing the number of nonfunctional binding sites genome wide. Using in vitro measurements of binding affinities for a large collection of DNA binding proteins, in multiple species, we detect a significant global avoidance of weak binding sites in genomes. The underlying evolutionary process leaves a distinct genomic hallmark in that similar words have correlated frequencies, which we detect in all species across domains of life. We hypothesize that natural selection against weak binding sites contributes to this process, and using an evolutionary model we show that the strength of selection needed to maintain global word compositions is on the order of point mutation rates. Alternative contributions may come from interference of protein-DNA binding with replication and mutational repair processes, which operates with similar rates. We conclude that genome-wide word compositions have been molded by DNA binding proteins through tiny evolutionary steps over timescales spanning millions of generations. [Preview Abstract] |
Monday, March 13, 2017 3:30PM - 3:42PM |
C5.00004: Mutational jackpot events generate effective frequency-dependent selection in adapting populations Oskar Hallatschek The site-frequency spectrum is one the most easily measurable quantities that characterize the genetic diversity of a population. While most neutral models predict that site frequency spectra should decay with increasing frequency, a high-frequency uptick has been reported in many populations. Anomalies in the high-frequency tail are particularly unsettling because the highest frequencies can be measured with greatest accuracy. Here, we show that an uptick in the spectrum of neutral mutations generally arises when mutant frequencies are dominated by rare jackpot events, mutational events with large descendant numbers. This leads to an effective pattern of frequency-dependent selection (or unstable internal equilibrium at one half frequency) that causes an accumulation of high-frequency polymorphic sites. We reproduce the known uptick occurring for recurrent hitchhiking (genetic draft) as well as rapid adaptation, and (in the future) generalize the shape of the high-frequency tail to other scenarios that are dominated by jackpot events, such as frequent range expansions. We also tackle (in the future) the inverse approach to use the high-frequency uptick for learning about the tail of the offspring number distribution. Positively selected alleles need to surpass, typically, an u [Preview Abstract] |
Monday, March 13, 2017 3:42PM - 3:54PM |
C5.00005: Minimal-assumption inference from population-genomic data Daniel Weissman, Oskar Hallatschek Samples of multiple complete genome sequences contain vast amounts of information about the evolutionary history of populations, much of it in the associations among polymorphisms at different loci. Current methods that take advantage of this linkage information rely on models of recombination and coalescence, limiting the sample sizes and populations that they can analyze. We introduce a method, Minimal-Assumption Genomic Inference of Coalescence (MAGIC), that reconstructs key features of the evolutionary history, including the distribution of coalescence times, by integrating information across genomic length scales without using an explicit model of recombination, demography or selection. Using simulated data, we show that MAGIC's performance is comparable to PSMC' on single diploid samples generated with standard coalescent and recombination models. More importantly, MAGIC can also analyze arbitrarily large samples and is robust to changes in the coalescent and recombination processes. Using MAGIC, we show that the inferred coalescence time histories of samples of multiple human genomes exhibit inconsistencies with a description in terms of an effective population size based on single-genome data. [Preview Abstract] |
Monday, March 13, 2017 3:54PM - 4:06PM |
C5.00006: Diffusion and Selection in Many-Allele Range Expansions Bryan Weinstein, Maxim Lavrentovich, Wolfram M\"obius, Andrew Murray, David Nelson We experimentally and numerically investigate the evolutionary dynamics of four competing strains of \textit{E. coli} with differing growth rates in a range expansion. We model the population as a one-dimensional line of annihilating and coalescing random walkers with deterministic biases due to selection. We compare experimental measurements of the average fraction, two-point correlation functions, and relative annihilation and coalescence rates to simulation by matching a set of dimensionless parameters that collapses the dynamics of the competing strains. The model reasonably predicts our experimental population dynamics. We find that our domain boundaries fluctuate superdiffusively per length expanded $L$ as $L^{1.66\pm0.05}$. Our work acts as a starting point to describe the dynamics of clonal interference in spatially structured populations when multiple mutations have arisen conferring different selective advantages to subsets of a population. [Preview Abstract] |
Monday, March 13, 2017 4:06PM - 4:42PM |
C5.00007: How do prokaryotic genomes evolve? Invited Speaker: Erik Nimwegen |
Monday, March 13, 2017 4:42PM - 4:54PM |
C5.00008: Coalescence of genetic lineages in range expansions with obstacles and superdiffusive sector boundaries Daniel Beller, David Nelson In models of biological range expansions with simple diffusive wandering of both lineages and genetic boundaries in homogeneous space, it is straightforward to calculate the time since common ancestry for pairs of individuals at the front. However, model microbial systems such as E. coli show superdiffusive lateral wandering of genetic sector boundaries, due to roughening of the front with time, and this behavior drastically changes the coalescence of genetic lineages. Using stepping-stone simulations, we compute the distribution of backwards times to coalescence in range expansions with front roughening in the KPZ universality class. Genetic lineages are in this case superdiffusive as well, resulting in an exceptionally high concentration of coalescence events in the recent past. We then introduce heterogeneities in the form of obstacles (viewed spatially) or catastrophes of finite extent (viewed spatiotemporally). We discuss the scar-like signatures left by these obstacles/catastrophes in the distribution of coalescence times for individuals at the front, and associated measurable genetic properties of the population. [Preview Abstract] |
Monday, March 13, 2017 4:54PM - 5:06PM |
C5.00009: Mechanical function of proteins constrains sequence space to a low dimension: a simple physical model. Tsvi Tlusty, Albert Libchaber, Jean-Pierre Eckmann DNA genes are mapped to 3D arrangements of amino acids that make functional proteins. We will discuss this back-and-forth mapping, between the many-body physics within the protein and evolutionary forces acting on the gene. To look into the geometry of the map, we introduce a simple physical model in which proteins are treated as amino acid networks that adapt their connectivity to evolve a specific mechanical mode. Such large-scale conformational changes -- where big chunks of the protein move with respect to each other -- are known to be central to the function of many proteins. We will discuss how the collective physical interaction within the proteins projects the high-dimensional sequence space onto a low-dimensional space of mechanical modes: most of the gene records random evolution, while only a small non-random fraction is constrained by the biophysical function. Spectral analysis reveals a strong signature of the protein's structure and function within correlation `ripples' that appear in the space of DNA sequences. These findings propose a testable basic principle of the protein as amorphous matter whose dynamics encode the evolutionary learning process. [1] Tlusty, Libchaber {\&} Eckmann, \textit{Physical model of the sequence-to-function map of proteins} (arXiv:1608.03145). [Preview Abstract] |
Monday, March 13, 2017 5:06PM - 5:18PM |
C5.00010: The population dynamics of bacteria, phage and RM Systems. Calin Guet, Bruce Levin, Maros Pleska Viruses drive and mediate bacterial evolution as parasites and vectors of horizontal gene transfer, respectively. Temperate bacteriophages, defined by the ability to lysogenize a fraction of hosts and to transmit horizontally as well as vertically in the form of prophages, frequently carry genes that increase fitness or contribute to bacterial pathogenicity. Restriction-modification (RM) systems, which are widely diverse and ubiquitous among bacteria, can prevent infections leading to lysis, but their effect on lysogeny is not clear. We show that RM systems prevent lytic and lysogenic infections to the same extent and therefore represent a molecular barrier to prophage acquisition. Surprisingly, we find that this negative effect can be overcome and even reversed at the population level, as a consequence of dynamic interactions between viruses, hosts and RM systems. Thus the population dynamics of bacteria carrying RM systems impacts bacterial genome-wide evolution. . [Preview Abstract] |
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