Kiyoshi Asai

Bio: Kiyoshi Asai is an academic researcher from University of Tokyo. The author has contributed to research in topics: Hidden Markov model & Nucleic acid secondary structure. The author has an hindex of 46, co-authored 192 publications receiving 10456 citations. Previous affiliations of Kiyoshi Asai include National Institute of Advanced Industrial Science and Technology & Nara Institute of Science and Technology.

Genomic sequence of the pathogenic and allergenic filamentous fungus Aspergillus fumigatus

Abstract: Aspergillus fumigatus is exceptional among microorganisms in being both a primary and opportunistic pathogen as well as a major allergen. Its conidia production is prolific, and so human respiratory tract exposure is almost constant. A. fumigatus is isolated from human habitats and vegetable compost heaps. In immunocompromised individuals, the incidence of invasive infection can be as high as 50% and the mortality rate is often about 50% (ref. 2). The interaction of A. fumigatus and other airborne fungi with the immune system is increasingly linked to severe asthma and sinusitis. Although the burden of invasive disease caused by A. fumigatus is substantial, the basic biology of the organism is mostly obscure. Here we show the complete 29.4-megabase genome sequence of the clinical isolate Af293, which consists of eight chromosomes containing 9,926 predicted genes. Microarray analysis revealed temperature-dependent expression of distinct sets of genes, as well as 700 A. fumigatus genes not present or significantly diverged in the closely related sexual species Neosartorya fischeri, many of which may have roles in the pathogenicity phenotype. The Af293 genome sequence provides an unparalleled resource for the future understanding of this remarkable fungus.

Sequencing of Aspergillus nidulans and comparative analysis with A. fumigatus and A. oryzae

Abstract: The aspergilli comprise a diverse group of filamentous fungi spanning over 200 million years of evolution. Here we report the genome sequence of the model organism Aspergillus nidulans, and a comparative study with Aspergillus fumigatus, a serious human pathogen, and Aspergillus oryzae, used in the production of sake, miso and soy sauce. Our analysis of genome structure provided a quantitative evaluation of forces driving long-term eukaryotic genome evolution. It also led to an experimentally validated model of mating-type locus evolution, suggesting the potential for sexual reproduction in A. fumigatus and A. oryzae. Our analysis of sequence conservation revealed over 5,000 non-coding regions actively conserved across all three species. Within these regions, we identified potential functional elements including a previously uncharacterized TPP riboswitch and motifs suggesting regulation in filamentous fungi by Puf family genes. We further obtained comparative and experimental evidence indicating widespread translational regulation by upstream open reading frames. These results enhance our understanding of these widely studied fungi as well as provide new insight into eukaryotic genome evolution and gene regulation.

Genome sequencing and analysis of Aspergillus oryzae

Abstract: The genome of Aspergillus oryzae, a fungus important for the production of traditional fermented foods and beverages in Japan, has been sequenced. The ability to secrete large amounts of proteins and the development of a transformation system have facilitated the use of A. oryzae in modern biotechnology. Although both A. oryzae and Aspergillus flavus belong to the section Flavi of the subgenus Circumdati of Aspergillus, A. oryzae, unlike A. flavus, does not produce aflatoxin, and its long history of use in the food industry has proved its safety. Here we show that the 37-megabase (Mb) genome of A. oryzae contains 12,074 genes and is expanded by 7-9 Mb in comparison with the genomes of Aspergillus nidulans and Aspergillus fumigatus. Comparison of the three aspergilli species revealed the presence of syntenic blocks and A. oryzae-specific blocks (lacking synteny with A. nidulans and A. fumigatus) in a mosaic manner throughout the genome of A. oryzae. The blocks of A. oryzae-specific sequence are enriched for genes involved in metabolism, particularly those for the synthesis of secondary metabolites. Specific expansion of genes for secretory hydrolytic enzymes, amino acid metabolism and amino acid/sugar uptake transporters supports the idea that A. oryzae is an ideal microorganism for fermentation.

Drosophila endogenous small RNAs bind to Argonaute 2 in somatic cells

Abstract: RNA silencing is a conserved mechanism in which small RNAs trigger various forms of sequence-specific gene silencing by guiding Argonaute complexes to target RNAs by means of base pairing. RNA silencing is thought to have evolved as a form of nucleic-acid-based immunity to inactivate viruses and transposable elements. Although the activity of transposable elements in animals has been thought largely to be restricted to the germ line, recent studies have shown that they may also actively transpose in somatic cells, creating somatic mosaicism in animals. In the Drosophila germ line, Piwi-interacting RNAs arise from repetitive intergenic elements including retrotransposons by a Dicer-independent pathway and function through the Piwi subfamily of Argonautes to ensure silencing of retrotransposons. Here we show that, in cultured Drosophila S2 cells, Argonaute 2 (AGO2), an AGO subfamily member of Argonautes, associates with endogenous small RNAs of 20-22 nucleotides in length, which we have collectively named endogenous short interfering RNAs (esiRNAs). esiRNAs can be divided into two groups: one that mainly corresponds to a subset of retrotransposons, and the other that arises from stem-loop structures. esiRNAs are produced in a Dicer-2-dependent manner from distinctive genomic loci, are modified at their 3' ends and can direct AGO2 to cleave target RNAs. Mutations in Dicer-2 caused an increase in retrotransposon transcripts. Together, our findings indicate that different types of small RNAs and Argonautes are used to repress retrotransposons in germline and somatic cells in Drosophila.

The Physics of the B Factories

Abstract: This work is on the Physics of the B Factories. Part A of this book contains a brief description of the SLAC and KEK B Factories as well as their detectors, BaBar and Belle, and data taking related issues. Part B discusses tools and methods used by the experiments in order to obtain results. The results themselves can be found in Part C.

MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability

Abstract: We report a major update of the MAFFT multiple sequence alignment program. This version has several new features, including options for adding unaligned sequences into an existing alignment, adjustment of direction in nucleotide alignment, constrained alignment and parallel processing, which were implemented after the previous major update. This report shows actual examples to explain how these features work, alone and in combination. Some examples incorrectly aligned by MAFFT are also shown to clarify its limitations. We discuss how to avoid misalignments, and our ongoing efforts to overcome such limitations.

Minimap2: pairwise alignment for nucleotide sequences

Abstract: Motivation Recent advances in sequencing technologies promise ultra-long reads of ∼100 kb in average, full-length mRNA or cDNA reads in high throughput and genomic contigs over 100 Mb in length. Existing alignment programs are unable or inefficient to process such data at scale, which presses for the development of new alignment algorithms. Results Minimap2 is a general-purpose alignment program to map DNA or long mRNA sequences against a large reference database. It works with accurate short reads of ≥100 bp in length, ≥1 kb genomic reads at error rate ∼15%, full-length noisy Direct RNA or cDNA reads and assembly contigs or closely related full chromosomes of hundreds of megabases in length. Minimap2 does split-read alignment, employs concave gap cost for long insertions and deletions and introduces new heuristics to reduce spurious alignments. It is 3-4 times as fast as mainstream short-read mappers at comparable accuracy, and is ≥30 times faster than long-read genomic or cDNA mappers at higher accuracy, surpassing most aligners specialized in one type of alignment. Availability and implementation https://github.com/lh3/minimap2. Supplementary information Supplementary data are available at Bioinformatics online.

Kernel Methods for Pattern Analysis

Abstract: Kernel methods provide a powerful and unified framework for pattern discovery, motivating algorithms that can act on general types of data (e.g. strings, vectors or text) and look for general types of relations (e.g. rankings, classifications, regressions, clusters). The application areas range from neural networks and pattern recognition to machine learning and data mining. This book, developed from lectures and tutorials, fulfils two major roles: firstly it provides practitioners with a large toolkit of algorithms, kernels and solutions ready to use for standard pattern discovery problems in fields such as bioinformatics, text analysis, image analysis. Secondly it provides an easy introduction for students and researchers to the growing field of kernel-based pattern analysis, demonstrating with examples how to handcraft an algorithm or a kernel for a new specific application, and covering all the necessary conceptual and mathematical tools to do so.

Predicting effective microRNA target sites in mammalian mRNAs

Abstract: Proteins are built by using the information contained in molecules of messenger RNA (mRNA). Cells have several ways of controlling the amounts of different proteins they make. For example, a so-called ‘microRNA’ molecule can bind to an mRNA molecule to cause it to be more rapidly degraded and less efficiently used, thereby reducing the amount of protein built from that mRNA. Indeed, microRNAs are thought to help control the amount of protein made from most human genes, and biologists are working to predict the amount of control imparted by each microRNA on each of its mRNA targets. All RNA molecules are made up of a sequence of bases, each commonly known by a single letter—‘A’, ‘U’, ‘C’ or ‘G’. These bases can each pair up with one specific other base—‘A’ pairs with ‘U’, and ‘C’ pairs with ‘G’. To direct the repression of an mRNA molecule, a region of the microRNA known as a ‘seed’ binds to a complementary sequence in the target mRNA. ‘Canonical sites’ are regions in the mRNA that contain the exact sequence of partner bases for the bases in the microRNA seed. Some canonical sites are more effective at mRNA control than others. ‘Non-canonical sites’ also exist in which the pairing between the microRNA seed and mRNA does not completely match. Previous work has suggested that many non-canonical sites can also control mRNA degradation and usage. Agarwal et al. first used large experimental datasets from many sources to investigate microRNA activity in more detail. As expected, when mRNAs had canonical sites that matched the microRNA, mRNA levels and usage tended to drop. However, no effect was observed when the mRNAs only had recently identified non-canonical sites. This suggests that microRNAs primarily bind to canonical sites to control protein production. Based on these results, Agarwal et al. further developed a statistical model that predicts the effects of microRNAs binding to canonical sites. The updated model considers 14 different features of the microRNA, microRNA site, or mRNA—including the mRNA sequence around the site—to predict which sites within mRNAs are most effectively targeted by microRNAs. Tests showed that Agarwal et al.'s model was as good as experimental approaches at identifying the effective target sites, and was better than existing computational models. The model has been used to power the latest version of a freely available resource called TargetScan, and so could prove a valuable resource for researchers investigating the many important roles of microRNAs in controlling protein production.

Profile hidden Markov models.

Abstract: Summary : The recent literature on profile hidden Markov model (profile HMM) methods and software is reviewed. Profile HMMs turn a multiple sequence alignment into a position-specific scoring system suitable for searching databases for remotely homologous sequences. Profile HMM analyses complement standard pairwise comparison methods for large-scale sequence analysis. Several software implementations and two large libraries of profile HMMs of common protein domains are available, HMM methods performed comparably to threading methods in the CASP2 structure prediction exercise. Contact: eddy@genetics.wustl.edu.