Hirohisa Kishino, Ph.D.

Professor emeritus, University of Tokyo

Visiting researcher, AI/Data Science Social Implementation Laboratory, Chuo University

Email: kishino@g.ecc.u-tokyo.ac.jp; khirohisa001v@g.chuo-u.ac.jp

Current Research Interests and Collaborations

Evolutionary rates and divergence times:

Rates and times are two fundamental quantities in evolutionary study. When molecular evolution is neutral, the evolutionary rate is constant as far as the mutation rate and the generation time remains constant. The rate of molecular evolution can vary due to the change of the functional constraints, mutation rates and generation lengths. Jeff Thorne and I expressed the variability of the evolutionary rate as a stochastic process and developed a Bayesian hierarchical model to estimate the evolutionary rates and the divergence times. The estimated pattern of the evolutionary rates gives us a clue on the driving force causing the rate change. The functional constraints vary among genes whereas the change of the mutation rates and generation lengths affects on all loci in the genomes equally. Therefore, analysis of multiple loci makes it possible to identify the one out of the above candidate causes. The information on the distribution of divergence times may also be used to measure the phylogenetic diversity and skew of species composition.

Adaptive evolution of virus and protein structure:

In collaboration with Teruaki Watabe, we try to estimate the evolution of genotypes behind the adaptive evolution of phenotypes. Molecular mechanism behind the evolution of phenotypes is decomposed into the evolution of the protein structure and evolution of the expression level. RNA virus has a relatively simple “life cycle” with a few key components, one of which is the spike proteins bound to the receptors of the host cells. A viral population escapes from the attacks of antibodies by changing the microstructure in the binding region of the spike protein to the antibody. Because the binding region to the antibody is close to or even overlaps the binding region to the receptors of the host cells, the escape from the antibodies is accompanied with the reduced ability of binding to the host cells. Therefore, the strengths of the binding abilities of these two types determine the fitness. By integrating sequence information and structural information, we identify the region under diversifying selection and predict the fate of mutations.

Population structure and adaptation measured by genomics and transcriptomics:

Geographical and environmental barriers and human activities affect the distribution and dynamics of a population. Shuichi Kitada and I have long studied the effects of marine stock enhancement programs by survey sampling approach and population genetics methodology. The environmental stress and the intended or unintended selection of farming and conservation activities may affect the physiological process of the marine organisms. We are trying to understand it through a graphical modeling of gene expression profiles.

With full thanks to my collaborators:

I thank my friends for collaboration of statistical modeling and analysis in various fields such as agronomy, community ecology, psychology, medicine, and behavioral science.