Date :

 February 10-11, 2003

Place :

 The First Meeting Room, 5F, Institute of Physics, Academia Sinica (Taipei)

Schedule :

February 10

10:00-10:50

Growth of microbial genomes by short segmental duplications and the RNA world
Professor H. C. Lee (Dept. of Physics & Dept. Life Sciences, National Central Univ.)
Abstract
We show that analyses of frequencies of word occurrence of microbial genomes considered as texts of their four nucleotides reveal telling footprints of the early evolution of the genomes. The frequencies of word occurrence of the genomes are expected to obey Poisson distributions. Yet for words less than nine letters the average distribution for complete microbial genomes has a width many times the width of a Poisson distribution. We interpret this phenomenon as follows: the genome is a large system that possesses the statistical characteristics of a much smaller "andom'' system, and certain textual statistical properties of genomes we now see are remnants of those of their ancestral genomes, which were much shorter than the genomes are now. This interpretation suggests a simple biologically plausible model for the growth of genomes: the genome first grows randomly to an initial length much shorter than its final length, of the order of one thousand nucleotides (1k nt), thereafter mainly grows by random segmental duplication. We show that using duplicated segments averaging around 25 nt, the model sequences generated possess statistical properties characteristic of present day genomes. Both the initial length and the duplicated segment length support an RNA world at the time duplication began. Random segmental duplication would greatly enhance the ability of a genome to use its hard-to-acquire codes repeatedly, and a genome that practiced it would have evolved enormously faster than those that did not.

11:00-11:50

Hemagglutinin sequence clusters and the antigenic evolution of influenza A virus
Dr. Jonathan Dushoff (Dept Ecol & Evolutionary Biology, Princeton University)
Abstract
Continual mutations to the hemagglutinin gene of influenza A virus generate novel antigenic strains that cause annual epidemics. Our group has used cluster analysis to study the structure and tempo of hemagglutinin evolution over the past two decades. We found a critical length scale, in amino-acid space, at which hemagglutinin sequences aggregate into clusters, and investigated the spatio-temporal distribution of these clusters. We also investigated the relationship between cluster structure and the primary antibody-combining regions of the hemagglutinin protein.

Drift evolution, seasonality and influenza mortality
Dr. Jonathan Dushoff (Dept Ecol & Evolutionary Biology, Princeton University)
Abstract
The spread of an infectious disease is an essentially stochastic process, and simulation models show that such stochasticity can have large effects even in large populations. The case of influenza is further complicated by the stochastic process of 'drift' evolution: mutations that change the way the virus looks to the immune system. I will discuss efforts to understand inluenza evolution and epidemiology, and the processes that lead to its unusual evolutionary pattern.

14:30-15:20

Dating the monocot-dicot divergence and the origin of core eudicots using whole  chloroplast genomes
Dr. Shu-Miaw Chaw (Inst. of Botany, Academia Sinica)
Abstract
We estimated the date of the monocot–dicot split and the origin of core eudicots using a large chloroplast (cp) genomic dataset. Sixty-one protein-coding genes (>39,000 bps) common to the twelve whole cp genomes of land plants were concatenated and analyzed. Three known split events were used as calibration points and for cross references. Both the method based on the assumption of a constant rate and the Li-Tanimura unequal rate method were used to estimate divergence times. The phylogenetic analyses indicated that nonsynonymous substitution rates of cp genomes are heterogeneous among the angiosperm, seed plant, and tracheophyte lineages. For this reason, the constant rate method gives overestimates for the divergence date between monocots and dicots and for the divergence of core eudicots, especially when fast evolving monocots are included. In contrast, the Li-Tanimura method gives estimates that better reflect the known evolutionary sequence of tracheophyte lineages and are in line with known fossil records. Combining estimates calibrated by two known fossil nodes and the Li-Tanimura method, we propose that the monocot lineage branched off from dicots 140–150 Myr ago (late Jurassic–early Cretaceous), at least 50 Myr younger than previous estimates based on the molecular clock hypothesis, and that the core eudicots diverged 100–115 Myr ago (Albian–Aptian of Cretaceous). These estimates indicate that both the monocot–dicot divergence and the core eudicot’s age are older than their respective fossil records.

Solvable evolution model with parallel mutation-selection scheme and Fisher theorem
Dr. David Saakian (Yerevan Institute of Physics)
Abstract
Based on the connection between an biological evolution model with a parallel mutation-selection scheme and a quantum spin model, we derive analytic expressions for the relaxation periods from some general initial genome configurations to the fittest configuration in the evolution model whose fitness function has a single peak. We find that in stationary state, after relaxation, all individuals in the population are located in the optimal genome and it's closest neighboring genome configurations, which resembles Fisher's Fundamental Theorem of Natural Selection. Thus the concentration around the fittest configuration is more efficient in the parallel scheme than in the connected mutation-selection scheme, e.g. the Eigen model.

16:40-17:30

Statistical Physics on Life
Professor N. Ito (Dept. of Applied Physics, Univ. of Tokyo)
Abstract
The success of the biophysics and biotechnology revealed the nanomachine aspect of life. Now we can share the picture that the biological system is also a kind of machine obeying a deterministic dynamical rule, like a solar system. But, as we physicists know, the statistical treatment is more suitable even to the deterministic systems when the degree of freedom is not very small. In this talk, the studies on statistical behavior of life are reviewed. It will include the problem on life-time of individuals and species.

February 11

10:00-10:50

Beyond Thermodynamics Towards Hydrodynamics
Professor N. Ito (Dept. of Applied Physics, Univ. of Tokyo)
Abstract
Main issue of statistical mechanics has been to predict the thermodynamic behavior of many particle systems, and it is now practically achieved with the use of computer. Of course, there remain many difficult problems, for example, quantum and random systems, but we can predict many interesting properties including the phases and transitions of basic systems like Ising and simple particle systems simulationally. Now it seems to be the time to go beyond the thermal equilibrium state. The first step will be the dynamical behaviors of macroscopic materials. Especially, the hydrodynamic behavior is promising. In this talk, some results of nonequilibrium particle-dynamics simulations are introduced.

Lunch

Simple model of diversifying ecosystem
Mr. Takashi Shimada (Dept. of Applied Physics, Univ. of Tokyo)
Abstract
Enduring studies on fossil and field data have provided us hints of the property of large ecosystem in the evolutional time span. Although many models and scenarios were proposed, those arguments tend to focus on a certain aspect. Furthermore, the mechanism of diversification is ignored while theoretical studies predict that large and complex system is generally unstable. ?In this talk we propose a new model of population dynamics in which the interactions between species have a size-free form. In addition to the equations of motion, simple rules for random mutation and deterministic extinction are introduced. In this model, although most of the new species fail to survive, some succeed in adapting. As a result the system shows spontaneous growth to diverse structure. ?Furthermore, our model reproduces the distribution of the life span of species evaluated from paleontological data. Other statistical properties in our model such as the distribution of extinction size also show good agreements with ones of fossil data.