Yasunori Osana

Whole-Genome Tiling Array Analysis of Mycobacterium leprae RNA Reveals High Expression of Pseudogenes and Noncoding Regions

Whole-genome sequence analysis of Mycobacterium leprae has revealed a limited number of protein-coding genes, with half of the genome composed of pseudogenes and noncoding regions. We previously showed that some M. leprae pseudogenes are transcribed at high levels and that their expression levels change following infection. In order to clarify the RNA expression profile of the M. leprae genome, a tiling array in which overlapping 60-mer probes cover the entire 3.3-Mbp genome was designed. The array was hybridized with M. leprae RNA from the SHR/NCrj-rnu nude rat, and the results were compared to results from an open reading frame array and confirmed by reverse transcription-PCR. RNA expression was detected from genes, pseudogenes, and noncoding regions. The signal intensities obtained from noncoding regions were higher than those from pseudogenes. Expressed noncoding regions include the M. leprae unique repetitive sequence RLEP and other sequences without any homology to known functional noncoding RNAs. Although the biological functions of RNA transcribed from M. leprae pseudogenes and noncoding regions are not known, RNA expression analysis will provide insights into the bacteriological significance of the species. In addition, our study suggests that M. leprae will be a useful model organism for the study of the molecular mechanism underlying the creation of pseudogenes and the role of microRNAs derived from noncoding regions.

Stochastic Simulation for Biochemical Reactions on FPGA

Biological cell simulations generally require high-powered computer resources. A reconfigurable system is a possible solution to the problem as an alternative approach against PC/WS clusters. A stochastic simulation algorithm proposed by Gillespie is implemented on a reconfigurable platform called ReCSiP, and the performance is evaluated. The implemented Lotka system outperforms the software implementation on AthlonXP2800+ by 105.13 times.

Accurate identification of orthologous segments among multiple genomes

MOTIVATION The accurate detection of orthologous segments (also referred to as syntenic segments) plays a key role in comparative genomics, as it is useful for inferring genome rearrangement scenarios and computing whole-genome alignments. Although a number of algorithms for detecting orthologous segments have been proposed, none of them contain a framework for optimizing their parameter values. METHODS In the present study, we propose an algorithm, named OSfinder (Orthologous Segment finder), which uses a novel scoring scheme based on stochastic models. OSfinder takes as input the positions of short homologous regions (also referred to as anchors) and explicitly discriminates orthologous anchors from non-orthologous anchors by using Markov chain models which represent respective geometric distributions of lengths of orthologous and non-orthologous anchors. Such stochastic modeling makes it possible to optimize parameter values by maximizing the likelihood of the input dataset, and to automate the setting of the optimal parameter values. RESULTS We validated the accuracies of orthology-mapping algorithms on the basis of their consistency with the orthology annotation of genes. Our evaluation tests using mammalian and bacterial genomes demonstrated that OSfinder shows higher accuracy than previous algorithms. AVAILABILITY The OSfinder software was implemented as a C++ program. The software is freely available at http://osfinder.dna.bio.keio.ac.jp under the GNU General Public License. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.

Murasaki: A Fast, Parallelizable Algorithm to Find Anchors from Multiple Genomes

Background With the number of available genome sequences increasing rapidly, the magnitude of sequence data required for multiple-genome analyses is a challenging problem. When large-scale rearrangements break the collinearity of gene orders among genomes, genome comparison algorithms must first identify sets of short well-conserved sequences present in each genome, termed anchors. Previously, anchor identification among multiple genomes has been achieved using pairwise alignment tools like BLASTZ through progressive alignment tools like TBA, but the computational requirements for sequence comparisons of multiple genomes quickly becomes a limiting factor as the number and scale of genomes grows. Methodology/Principal Findings Our algorithm, named Murasaki, makes it possible to identify anchors within multiple large sequences on the scale of several hundred megabases in few minutes using a single CPU. Two advanced features of Murasaki are (1) adaptive hash function generation, which enables efficient use of arbitrary mismatch patterns (spaced seeds) and therefore the comparison of multiple mammalian genomes in a practical amount of computation time, and (2) parallelizable execution that decreases the required wall-clock and CPU times. Murasaki can perform a sensitive anchoring of eight mammalian genomes (human, chimp, rhesus, orangutan, mouse, rat, dog, and cow) in 21 hours CPU time (42 minutes wall time). This is the first single-pass in-core anchoring of multiple mammalian genomes. We evaluated Murasaki by comparing it with the genome alignment programs BLASTZ and TBA. We show that Murasaki can anchor multiple genomes in near linear time, compared to the quadratic time requirements of BLASTZ and TBA, while improving overall accuracy. Conclusions/Significance Murasaki provides an open source platform to take advantage of long patterns, cluster computing, and novel hash algorithms to produce accurate anchors across multiple genomes with computational efficiency significantly greater than existing methods. Murasaki is available under GPL at http://murasaki.sourceforge.net.

FPGA Implementation of a Data-Driven Stochastic Biochemical Simulator with the Next Reaction Method

This paper introduces a scalable FPGA implementation of a stochastic simulation algorithm (SSA) called the next reaction method. There are some hardware approaches of SSAs that obtained high-throughput on reconfigurable devices such as FPGAs, but these works lacked in scalability. The design of this work can accommodate to the increasing size of target biochemical models, or to make use of increasing capacity of FPGAs. Interconnection network between arithmetic circuits and multiple simulation circuits aims to perform a data-driven multi-threading simulation. Approximately 8 times speedup was obtained compared to an execution on Xeon 2.80 GHz.

Exploiting memory hierarchy for a Computational Fluid Dynamics accelerator on FPGAs

Computational fluid dynamics (CFD) is an important tool for aeronautical engineers. Instead of expensive super-computers or clusters, using custom pipelines built on FPGAs is expected to be a cost effective solution to accelerate CFD. The problem is that to keep the pipeline busy is difficult because of the memory bandwidth. To deal with this problem, an effective memory access method using block-RAMs is implemented based on a careful survey about memory access pattern. This work is targetting on two major subroutines in UPACS, a CFD software package. As a result, the amount of data transfer is reduced about 40%. This shows 46-170 fold speed-up is expected by several Virtex-4 FPGAs compared to Itanium2 processor.

The design of scalable stochastic biochemical simulator on FPGA

Biochemical simulations including whole-cell models require high performance computing systems. Reconfigurable systems are expected to be an alternative solution for conventional methods by PC clusters or vector computers. This paper shows the implementation of a stochastic biochemical simulation algorithm called Next Reaction Method for Virtex-II PRO. As the result of benchmarking with a small reaction system, the FPGA-based simulator outperforms the software implementation on Xeon 2.40 GHz by 17.1 times

Efficient scheduling of rate law functions for ODE-based multimodel biochemical simulation on an FPGA

A reconfigurable biochemical simulator by solving ordinary differential equations has received attention as a personal high speed environment for biochemical researchers. For efficient use of the reconfigurable hardware, static scheduling of high-throughput arithmetic pipeline structures is essential. This paper shows and compares some scheduling alternatives, and analyzes the tradeoffs between performance and hardware amount. Through the evaluation, it is shown that the sharing first scheduling reduces the hardware cost by 33.8% in average, with the up to 11.5% throughput degradation. Effects of sharing of rate law functions are also analyzed.

Implementation and evaluation of an arithmetic pipeline on FLOPS-2D: multi-FPGA system

UPACS (Unified Platform for Aerospace Computational Simulation) is one of the practical CFD (Computational Fluid Dynamics) packages supporting various selectability. A custom machine for efficient execution of MUSCL; a core functions of UPACS is implemented on FLOPS-2D (Flexibly Linkable Object for Programmable System); multi-FPGA reconfigurable system. The deep and complicated pipeline structure generated from MUSCL dataflow is divided and optimized into two FPGA boards by using a tuning tool called RER. With optimization of the order of operations and pipeline structure, about 60% utilization of the pipeline is achieved even by using serial links between two boards. The execution time is 6.16-23.19 times faster than that of the software on 2.66 GHz Intel Core 2 Duo processor.

Comparison of the terrestrial cyanobacterium Leptolyngbya sp. NIES-2104 and the freshwater Leptolyngbya boryana PCC 6306 genomes

The cyanobacterial genus Leptolyngbya is widely distributed throughout terrestrial environments and freshwater. Because environmental factors, such as oxygen level, available water content, and light intensity, vary between soil surface and water bodies, terrestrial Leptolyngbya should have genomic differences with freshwater species to adapt to a land habitat. To study the genomic features of Leptolyngbya species, we determined the complete genome sequence of the terrestrial strain Leptolyngbya sp. NIES-2104 and compared it with that of the near-complete sequence of the freshwater Leptolyngbya boryana PCC 6306. The greatest differences between these two strains were the presence or absence of a nitrogen fixation gene cluster for anaerobic nitrogen fixation and several genes for tetrapyrrole synthesis, which can operate under micro-oxic conditions. These differences might reflect differences in oxygen levels where these strains live. Both strains have the genes for trehalose biosynthesis, but only Leptolyngbya sp. NIES-2104 has genetic capacity to produce a mycosporine-like amino acid, mycosporine-glycine. Mycosporine-glycine has an antioxidant action, which may contribute to adaptation to terrestrial conditions. These features of the genomes yielded additional insights into the classification and physiological characteristics of these strains.