Geographical variation in soil bacterial community structure in 26 tropical forests in Southeast Asia (Malaysia, Indonesia and Singapore) and two temperate forests in Japan was investigated to elucidate the environmental factors and mechanisms that influence biogeography of soil bacterial diversity and composition. Despite substantial environmental differences, bacterial phyla were represented in similar proportions, with Acidobacteria and Proteobacteria the dominant phyla in all forests except one mangrove forest in Sarawak, although highly significant heterogeneity in frequency of individual phyla was detected among forests. In contrast, species diversity (α-diversity) differed to a much greater extent, being nearly six-fold higher in the mangrove forest (Chao1 index = 6,862) than in forests in Singapore and Sarawak (~1,250). In addition, natural mixed dipterocarp forests had lower species diversity than acacia and oil palm plantations, indicating that aboveground tree composition does not influence soil bacterial diversity. Shannon and Chao1 indices were correlated positively, implying that skewed operational taxonomic unit (OTU) distribution was associated with the abundance of overall and rare (singleton) OTUs. No OTUs were represented in all 28 forests, and forest-specific OTUs accounted for over 70% of all detected OTUs. Forests that were geographically adjacent and/or of the same forest type had similar bacterial species composition, and a positive correlation was detected between species divergence (β-diversity) and direct distance between forests. Both α- and β-diversities were correlated with soil pH. These results suggest that soil bacterial communities in different forests evolve largely independently of each other and that soil bacterial communities adapt to their local environment, modulated by bacterial dispersal (distance effect) and forest type. Therefore, we conclude that the biogeography of soil bacteria communities described here is non-random, reflecting the influences of contemporary environmental factors and evolutionary history.

Seed awning is one of the important traits for successful propagation in wild rice. During the domestication of rice by ancient humans, plants with awnless seeds may have been selected because long awns hindered collection and handling activities. To investigate domestication of awnless rice, QTL analysis for seed awning was first carried out using backcross recombinant inbred lines between Oryza sativa Nipponbare (recurrent parent) and O. rufipogon W630 (donor parent). Two strong QTLs were detected in the same regions as known major seed-awning loci, An-1 and RAE2. Subsequent causal mutation surveying and fine mapping confirmed that O. rufipogon W630 has functional alleles at both loci. The gene effects and interactions at these loci were examined using two backcross populations with reciprocal genetic backgrounds of O. sativa Nipponbare and O. rufipogon W630. As awn length in wild rice varied among seeds even in the same plant, awn length was measured based on spikelet position. In the genetic background of cultivated rice, the wild alleles at An-1 and RAE2 had awning effects, and plants having both wild homozygous alleles produced awns whose length was about 70% of those of the wild parent. On the other hand, in the genetic background of wild rice, the substitution of cultivated alleles at An-1 and RAE2 contributed little to awn length reduction. These results indicate that the domestication process of awnless seeds was complicated because many genes are involved in awn formation in wild rice.

Sequences homologous to organellar DNA that have been integrated into nuclear genomes are referred to as nuclear mitochondrial DNAs (NUMTs) and nuclear plastid DNAs (NUPTs). NUMTs in nine plant species were analyzed to reveal the integration patterns and possible factors involved. The cumulative lengths of NUMTs in two-thirds of species analyzed were greater than those of NUPTs observed in a previous study. The age distribution of NUMTs was similar to that of NUPTs, suggesting similar mechanisms for integration and degradation of both NUPTs and NUMTs. Nuclear genome size and the cumulative length of NUMTs showed a significant positive correlation for older but not younger NUMTs. The same correlation was also found between nuclear genome size and older NUPTs in 17 species. These results suggested that genome size is a key factor to determine the cumulative length of relatively older NUPTs/NUMTs. Although the factor(s) determining the cumulative length of younger NUPTs/NUMTs is unclear, these sequences may be more deleterious, which could explain the different manner of determining the cumulative length of younger NUPTs/NUMTs in nuclear genomes. In addition, a relationship between the cumulative length of integrated NUMTs and complexity of mitochondrial genomes (i.e., the number of repeats) was found. The results indicate that the structural complexity of both NUMTs and their original mitochondrial sequences affects integration and degradation processes.

All members of the order Trypanosomatida known to date are parasites that are most likely descendants of a free-living ancestor. Trypanosomatids are an excellent model to assess the transition from a free-living to a parasitic lifestyle, because a large amount of experimental data has been accumulated for well-studied members that are harmful to humans and livestock (Trypanosoma spp. and Leishmania spp.). However, recent advances in our understanding of the diversity of trypanosomatids and their close relatives (i.e., members of the class Kinetoplastea) have suggested that the change in lifestyle took place multiple times independently from that which gave rise to the extant trypanosomatid parasites. In the current study, transcriptomic data of two parasitic kinetoplastids belonging to orders other than Trypanosomatida, namely Azumiobodo hoyamushi (Neobodonida) and Trypanoplasma borreli (Parabodonida), were generated. We re-examined the transition from a free-living to a parasitic lifestyle in the evolution of kinetoplastids by combining (i) the relationship among the five orders in Kinetoplastea and (ii) that among free-living and parasitic species within the individual orders. The former relationship was inferred from a large-scale multigene alignment including the newly generated data from Azumiobodo and Trypanoplasma, as well as the data from another parasitic kinetoplastid, Perkinsela sp., deposited in GenBank; and the latter was inferred from a taxon-rich small subunit ribosomal DNA alignment. Finally, we discuss the potential value of parasitic kinetoplastids identified in Parabodonida and Neobodonida for studying the evolutionary process that turned a free-living species into a parasite.

Unsupervised data mining capable of extracting a wide range of knowledge from big data without prior knowledge or particular models is a timely application in the era of big sequence data accumulation in genome research. By handling oligonucleotide compositions as high-dimensional data, we have previously modified the conventional self-organizing map (SOM) for genome informatics and established BLSOM, which can analyze more than ten million sequences simultaneously. Here, we develop BLSOM specialized for tRNA genes (tDNAs) that can cluster (self-organize) more than one million microbial tDNAs according to their cognate amino acid solely depending on tetra- and pentanucleotide compositions. This unsupervised clustering can reveal combinatorial oligonucleotide motifs that are responsible for the amino acid-dependent clustering, as well as other functionally and structurally important consensus motifs, which have been evolutionarily conserved. BLSOM is also useful for identifying tDNAs as phylogenetic markers for special phylotypes. When we constructed BLSOM with ‘species-unknown’ tDNAs from metagenomic sequences plus ‘species-known’ microbial tDNAs, a large portion of metagenomic tDNAs self-organized with species-known tDNAs, yielding information on microbial communities in environmental samples. BLSOM can also enhance accuracy in the tDNA database obtained from big sequence data. This unsupervised data mining should become important for studying numerous functionally unclear RNAs obtained from a wide range of organisms.

Population size is one of the main factors that determine the amount of DNA polymorphism. We examined a model under which the population size changed linearly. Because of the simplicity of this model, we could analytically obtain the expectation of nucleotide diversity, E(π), and the expectation of the amount of DNA polymorphism, E(θ), based on the number of segregating sites. The results suggest that E(π) is larger than E(θ) when the population size decreased and that E(π) is smaller than E(θ) when the population size increased. The expected time to the most recent common ancestor could also be obtained under this model.