Two Drosophila heteroneura males fighting for a female. (Squeeze the window to make it visible at the right bottom corner.)
Koichiro Tamura, PhD
Director, Researh Center for Genomics and Bioinformatics
Professor, Department of Biological Sciences
Tokyo Metropolitan University
Adaptative evolution of a tropical fruit fly species to temperate climate
The distribution of Drosophila albomicans
was limited in tropics in Southeast Asia until the mid-1980. Since then, however, the distribution has been extended toward the north to west Japan to date. In our study, we found that the cold tolerance of this species has been improved in the Japanese population with a higher response to cold acclimation. This suggests that improved cold tolerance is attributable to gene expression changes in response to the cold acclimation. Using RNA-seq method, we found many candidate genes responsible for the improvement of cold tolerance. We are trying to identify the causative genes among these genes by artificially modifying gene expression using the GAL4/UAS system in D. melanogaster
. [Ref. 1
Genetic mechanisms of neo-sex chromosome evolution in a fruit fly species
has giant X and Y chromosomes named neo-X and neo-Y chromosomes, which originated by fusions of the canonical X and Y chromosomes, respectively, and autosomes corresponding to the third chromosomes in its sister species, D. nasuta
. As a result, a large part of the genome has become meiotic-recombination-free. What is the merit of these neo-sex chromosomes? This is a mystery as the meiotic recombination is believed to be evolutionarily advantageous. We are studying to solve this issue. [Ref. 2
Theoretical study for molecular evolution and molecular phylogenetics
Evolutionary changes of genomic DNA sequences are an ultimate driving force of organismal evolutions. Therefore, it is important to study how DNA sequences change during the evolutionary period for a deep understanding of the evolution of genomes and organisms as well as performing accurate inferring phylogenetic trees and estimating divergence times. We are studying the molecular evolution of genes and genomes, using mathematical modeling, computer simulations, and real data analyses. A special focus is on developing methods for molecular evolutionary and phylogenetic analyses. The current project is to estimate divergence times in a phylogenetic tree in case of unequal evolutionary rates among lineages. [Ref. 3
The phylogenetic tree of zinc finger protein genes from human and mouse, showing extreme evolutionary rate heterogeneity among genes and lineages (A), is successfully time-aligned by the RelTime method (B). x1: human ZFX, x2: mouse ZFX, y1: human ZFY, y2: mouse ZFY.
Development of Molecular Evolutionary Genetics Analyses software
With its theoretical basis firmly established in molecular evolutionary and population genetics, the comparative DNA and protein sequence analyses play a central role in reconstructing the evolutionary histories of species and multigene families, estimating rates of molecular evolution, and inferring the nature and extent of selective forces shaping the evolution of genes and genomes. As a response to the demand for easy-to-use computer programs for such analyses, we have produced Molecular Evolutionary Genetics Analysis (MEGA) software, with its focus on facilitating the exploration and analysis of DNA and protein sequence variations from an evolutionary perspective. [Ref. 5
Bioinformatics for Drosophila species identification
The identification of Drosophila
species requires high expertise and thus not an easy practice for ordinary researchers. To facilitate this task, we took a bioinformatics approach, focusing on the pattern of wing vein, which is one of the important key characters in traditional taxonomy. Measuring the distances between crossing points of wing veins, we succeeded to identify each species from sixteen Drosophila
species commonly observed around Tokyo area. [Ref. 6
- Moriguchi N, Uchiyama K, Miyagi R, Moritsuka E, Takahashi A, Tamura K, Tsumura Y, Teshima KM, Tachida H, Kusumi J (2019) Inferring the demographic history of Japanese cedar, Cryptomeria japonica, using amplicon sequencing. Heredity 123:371–383.
- Tao Q, Tamura K, Battistuzzi FU, Kumar S (2019) A machine learning method for detecting autocorrelation of evolutionary rates in large phylogenies. Mol. Biol. Evol. 36:811–824.
- Battistuzzi FU, Tao Q, Jones L, Tamura K, Kumar S (2018) RelTime relaxes the strict molecular clock throughout the phylogeny. Genome Biol. Evol. 10:1631-1636 2.
- Patel R, Scheinfeldt LB, Sanderford MD, Lanham TR, Tamura K, Platt A, Glicksberg BS, Xu K, Dudley JT, Kumar S (2018) Adaptive landscape of protein variation in human exomes. Mol. Biol. Evol. 35:2015-2025.
- Kumar S, Stecher G, Li M, Knyaz C, Tamura K (2018) MEGA X: molecular evolutionary genetics analysis across computing platforms. Mol. Biol. Evol. 35:1547-1549.
- Tamura K, Tao Q, Kumar S (2018) Theoretical foundation of the RelTime method for estimating divergence times from variable evolutionary rates. Mol. Biol. Evol. 35:1770-1782
- Noyszewski AK，Liu YC，Tamura K，Smith AG. (2017) Polymorphism and structure of style–specific arabinogalactan proteins as determinants of pollen tube growth in Nicotiana. BMC Evol. Biol. 17:186.
- Loh SYM，Ogawa Y，Kawana S，Tamura K，Lee HK. (2017) Semi-automated quantitative Drosophila wings measurements. BMC Bioinformatics 18:319.
- Fraimout A, Debat V, Fellous S, Hufbauer RA, Foucaud J, Pudlo P, Marin J-M, Price DK, Cattel J, Chen X, Deprá M, Duyck PF, Guedot C, Kenis M, Kimura MT, Loeb G, Loiseau A, Martinez-Sañudo I, Pascual M, Richmond MP, Shearer P, Singh N, Tamura K, Xuéreb A, Zhang J, Estoup A. (2017) Deciphering the routes of invasion of Drosophila suzukii by means of ABC random forest. Mol. Biol. Evol. 34:980-996.
- Mello B, Tao Q, Tamura K, Kumar S. (2017) Fast and accurate estimates of divergence times from big data. Mol. Biol. Evol. 34:45-50.
- Kumar S, Stecher, G, Tamura K. (2016) MEGA7: Molecular Evolutionary Genetics Analysis Version 7.0 for Bigger Datasets. Mol. Biol. Evol. 33:1870-1874.
- Satomura K, Tamura K. (2016) Ancient male recombination shaped genetic diversity of neo-Y chromosome in Drosophila albomicans. Mol. Biol. Evol. 33:367-374.
- Liu L, Tamura K, Sanderford M, Gray VE, Kumar S. A (2016) Molecular Evolutionary Reference for the Human Variome. Mol. Biol. Evol. 33:245-254.
- Ohta S, Seto Y, Tamura K, Ishikawa Y, Matsuo T. (2015) Comprehensive identification of odorant-binding protein genes in the seed fly, Delia platura (Diptera: Anthomyiidae). Applied Entomology and Zoology 50:457-463.
- Filipski A, Tamura K, Billing-Ross P, Murillo O, Kumar S. (2015) Phylogenetic placement of metagenomic reads using the minimum evolution principle. BMC Genomics 16:1-9.
- Filipski A, Murillo O, Freydenzon A, Tamura K, Kumar S. (2014) Prospects for building large timetrees using molecular data with incomplete gene coverage among species. Mol. Biol. Evol. 31:2542-2550.
- Takezaki N, Nei M, Tamura K. (2014) POPTREEW: Web version of POPTREE for constructing population trees from allele frequency data and computing some other quantities. Mol. Biol. Evol. 31:1622-1624.
- Stecher G, Liu L, Sanderford M, Peterson P, Tamura K, Kumar S. (2014) MEGA-MD: Molecular Evolutionary Genetics Analysis software with mutational diagnosis of amino acid variation. Bioinformatics 30:1305-1307.
- Ohta S, Seto Y, Tamura K, Ishikawa Y, Matsuo T. (2014) Identification of odorant-binding protein genes expressed in the antennae and the legs of the onion fly, Delia antiqua (Diptera: Anthomyiidae). Appl. Entomol. Zool. 49:89-95.
- Isobe K, Takahashi A, Tamura K. (2013) Cold tolerance and metabolic rate increased by cold acclimation in Drosophila albomicans from natural populations. Genes Genet. Syst. 88:289-300.
- Tamura K, Stecher G, Peterson D, Filipski A, Kumar S. (2013) MEGA6: Molecular Evolutionary Genetics Analysis version 6.0. Mol Biol. Evol. 30:2725-2729.
- Seto Y, Tamura K. (2013) Extensive Differences in Antifungal Immune Response in Two Drosophila Species Revealed by Comparative Transcriptome Analysis. Int. J. Genomics 2013:Article ID 542139.
- Tamura K, Battistuzzi FU, Billing-Ross P, Kumar S. (2012) Estimating Divergence Times in Large Molecular Phylogenies. Proc. Nat. Acad. Sci. USA 109:19333-19338.
- Kumar S, Stecher G, Peterson D, Tamura K. (2012) MEGA-CC: Computing Core of Molecular Evolutionary Genetics Analysis program for automated and iterative data analysis. Bioinformatics 28: 2685-2686.
- Kumar S, Filipski AJ, Battistuzzi FU, Kosakovsky Pond SL, Tamura K. (2012) Statistics and Truth in Phylogenomics. Mol Biol. Evol. 29:457-472.