Our laboratory studies molecular evolution and information biology. Through our research, we are trying to figure out some profound issues in molecular evolution by newly developed methods with large amount of data such as genomic data.
We study the evolution of life, with the aim of clarifying genetic lineages and other phenomena, by using various types of molecular information (like DNA sequences) to study present day organisms. This kind of research can also be used to study groups of organisms that cannot be analyzed by existing evolution research techniques based on morphological comparisons. For example, the fossil information concerning the initial evolutionary processes of bacteria and eukaryotes is limited, and it is difficult to predict their genetic lineages using morphological comparisons. However, their relationships can be inferred using molecular information. Since phenomena such as genomic duplication, genetic sequence transposition, and horizontal gene migration caused by symbiosis can be inferred from vestiges left in genomes, one can find how various phenomena have affected the organism’s evolution or diversification.
Orphan genes are detected by homology search as genes which do not have any homologs in other organisms. In other words, orphan genes are species or lineage specific genes. Orphan genes are always detected from any genomes, so it may play a rule in evolution. We are developing the method to find the origin of orphan gene.
Convergent evolution of the body shape has often occurred through the adaptation of organisms to the environment. However, convergent evolution on the amino acid level are rarely reported. Therefore, we are trying to detect novel convergent proteins using large amount of protein data, and to estimate the influence of convergent gene to the evolution of species.
We are developing a software to detect gene gain and gene loss event on a lineage, and estimate the functions of the gene. Using the software, we hope to understand the contribution of gene-gain and gene-loss to the adaptation to environment through the evolution.
Recently, large amount of sequence data of gene is available by high throughput sequencer. Therefore, we examined the robustness of the method to construct the phylogenetic tree using large amount of genes by simulation tests.