2024/12/07 更新

写真a

フクナガ ツカサ
福永 津嵩
所属
附属機関・学校 高等研究所
職名
准教授(任期付)
学位
博士(科学) ( 東京大学 )

経歴

  • 2023年04月
    -
    継続中

    早稲田大学   高等研究所   准教授

  • 2021年04月
    -
    2023年03月

    早稲田大学   高等研究所   講師

  • 2017年10月
    -
    2021年03月

    早稲田大学   理工学術院総合研究所   招聘研究員

  • 2017年10月
    -
    2021年03月

    東京大学   情報理工学系研究科コンピュータ科学専攻   助教

  • 2018年02月
    -
    2019年03月

    大阪大学   医学系研究科   招聘研究員

  • 2016年04月
    -
    2017年09月

    日本学術振興会   特別研究員(PD)

  • 2016年04月
    -
    2017年09月

    早稲田大学   理工学術院   特別研究員

▼全件表示

学歴

  • 2011年04月
    -
    2016年03月

    東京大学大学院   新領域創成科学研究科   メディカル情報生命専攻  

  • 2007年04月
    -
    2011年03月

    東京大学   理学部   生物情報科学科  

委員歴

  • 2024年04月
    -
    継続中

    IPSJ Transactions on Bioinformatics  編集委員

  • 2024年04月
    -
    継続中

    日本バイオインフォマティクス学会  幹事

  • 2024年04月
    -
    継続中

    日本バイオインフォマティクス学会  理事

  • 2023年07月
    -
    継続中

    Frontiers in Bioinformatics  Review Editor

  • 2023年04月
    -
    継続中

    情報処理学会  バイオ情報学研究会運営委員

  • 2021年03月
    -
    継続中

    Frontiers in Genetics  Review Editor

  • 2021年04月
    -
    2023年03月

    日本バイオインフォマティクス学会  理事

▼全件表示

所属学協会

  •  
     
     

    日本バイオインフォマティクス学会

  •  
     
     

    日本植物生理学会

  •  
     
     

    日本ゲノム微生物学会

  •  
     
     

    情報処理学会

  •  
     
     

    日本RNA学会

研究分野

  • システムゲノム科学 / ゲノム生物学 / 生命、健康、医療情報学

研究キーワード

  • シアノバクテリア

  • 比較ゲノム解析

  • 表現型

  • 遺伝子機能推定

  • ゲノム進化

  • データマイニング

  • 機械学習

  • RNA二次構造

  • バイオインフォマティクス

▼全件表示

受賞

  • Oxford journals-JSBi Prize

    2024年08月   日本バイオインフォマティクス学会   RNA構造解析/比較ゲノム解析による機能未知遺伝子の機能推定  

  • 優秀口頭発表賞

    2021年   第十回生命医薬情報学連合大会   The inverse Potts model improves accuracy of phylogenetic profiling  

    受賞者: 福永津嵩, 岩崎渉

  • ポスター賞

    2020年   第九回生命医薬情報学連合大会   統計的有意性を担保可能な系列パターンマイニングに基づく配列モチーフ検出ソフトウェアの開発  

    受賞者: 毛利公一, 尾崎遼, 福永津嵩

  • ポスター賞

    2016年   第五回生命医薬情報学連合大会   RIblast: A high-speed RNA-RNA interaction prediction system for comprehensive lncRNA interactome analysis.  

    受賞者: 福永津嵩, 浜田道昭

 

論文

  • Phylogenetic Profiling Analysis of the Phycobilisome Revealed a Novel State-Transition Regulator Gene in Synechocystis sp. PCC 6803.

    Tsukasa Fukunaga, Takako Ogawa, Wataru Iwasaki, Kintake Sonoike

    Plant & cell physiology    2024年07月  [国内誌]

     概要を見る

    Phycobilisomes play a crucial role in the light-harvesting mechanisms of cyanobacteria, red algae, and glaucophytes, but the molecular mechanism of their regulation is largely unknown. In the cyanobacterium, Synechocystis sp. PCC 6803, we identified a gene, slr0244, as a phycobilisome-related gene using phylogenetic profiling analysis, a method to predict gene function based on comparative genomics. To investigate the physiological function of the slr0244 gene, we characterize the slr0244 mutants spectroscopically. The disruption of the slr0244 gene impaired state transition, a process by which the distribution of light energy absorbed by the phycobilisomes between two photosystems was regulated in response to the changes in light conditions. The Slr0244 protein seems to act somewhere at or downstream of the sensing step of the redox state of the plastoquinone pool in the process of state transition. These findings, together with the past report of the interaction of this gene product with thioredoxin or glutaredoxin, suggest that the slr0244 gene is a novel state-transition regulator that integrates the redox signal of plastoquinone pools with that of photosystem I-reducing side. The protein has two USP (universal stress protein) motifs in tandem. The second motif has two conserved cysteine residues found in USPs of other cyanobacteria and land plants. These redox-type USPs with conserved cysteines may function as redox regulators in various photosynthetic organisms. Our study also showed the efficacy of the phylogenetic profiling analysis in predicting the function of cyanobacterial genes that have not been annotated so far.

    DOI PubMed

  • DeepRaccess: high-speed RNA accessibility prediction using deep learning

    Kaisei Hara, Natsuki Iwano, Tsukasa Fukunaga, Michiaki Hamada

    Frontiers in Bioinformatics   3  2023年10月  [査読有り]

    担当区分:責任著者

     概要を見る

    RNA accessibility is a useful RNA secondary structural feature for predicting RNA-RNA interactions and translation efficiency in prokaryotes. However, conventional accessibility calculation tools, such as Raccess, are computationally expensive and require considerable computational time to perform transcriptome-scale analysis. In this study, we developed DeepRaccess, which predicts RNA accessibility based on deep learning methods. DeepRaccess was trained to take artificial RNA sequences as input and to predict the accessibility of these sequences as calculated by Raccess. Simulation and empirical dataset analyses showed that the accessibility predicted by DeepRaccess was highly correlated with the accessibility calculated by Raccess. In addition, we confirmed that DeepRaccess could predict protein abundance in E.coli with moderate accuracy from the sequences around the start codon. We also demonstrated that DeepRaccess achieved tens to hundreds of times software speed-up in a GPU environment. The source codes and the trained models of DeepRaccess are freely available at https://github.com/hmdlab/DeepRaccess.

    DOI

  • Neat1 lncRNA organizes the inflammatory gene expressions in the dorsal root ganglion in neuropathic pain caused by nerve injury

    Motoyo Maruyama, Atsushi Sakai, Tsukasa Fukunaga, Yoshitaka Miyagawa, Takashi Okada, Michiaki Hamada, Hidenori Suzuki

    Frontiers in Immunology   14  2023年08月  [査読有り]

     概要を見る

    Primary sensory neurons regulate inflammatory processes in innervated regions through neuro-immune communication. However, how their immune-modulating functions are regulated in concert remains largely unknown. Here, we show that Neat1 long non-coding RNA (lncRNA) organizes the proinflammatory gene expressions in the dorsal root ganglion (DRG) in chronic intractable neuropathic pain in rats. Neat1 was abundantly expressed in the DRG and was upregulated after peripheral nerve injury. Neat1 overexpression in primary sensory neurons caused mechanical and thermal hypersensitivity, whereas its knockdown alleviated neuropathic pain. Bioinformatics analysis of comprehensive transcriptome changes indicated the inflammatory response was the most relevant function of genes upregulated through Neat1. Consistent with this, upregulation of proinflammatory genes in the DRG following nerve injury was suppressed by Neat1 knockdown. Expression changes of these proinflammatory genes were regulated through Neat1-mRNA interaction-dependent and -independent mechanisms. Notably, Neat1 increased proinflammatory genes by stabilizing its interacting mRNAs in neuropathic pain. Finally, Neat1 in primary sensory neurons contributed to spinal inflammatory processes that mediated peripheral neuropathic pain. These findings demonstrate that Neat1 lncRNA is a key regulator of neuro-immune communication in neuropathic pain.

    DOI

  • Bioinformatics approaches for unveiling virus-host interactions.

    Hitoshi Iuchi, Junna Kawasaki, Kento Kubo, Tsukasa Fukunaga, Koki Hokao, Gentaro Yokoyama, Akiko Ichinose, Kanta Suga, Michiaki Hamada

    Computational and structural biotechnology journal   21   1774 - 1784  2023年  [査読有り]  [国際誌]

     概要を見る

    The coronavirus disease-2019 (COVID-19) pandemic has elucidated major limitations in the capacity of medical and research institutions to appropriately manage emerging infectious diseases. We can improve our understanding of infectious diseases by unveiling virus-host interactions through host range prediction and protein-protein interaction prediction. Although many algorithms have been developed to predict virus-host interactions, numerous issues remain to be solved, and the entire network remains veiled. In this review, we comprehensively surveyed algorithms used to predict virus-host interactions. We also discuss the current challenges, such as dataset biases toward highly pathogenic viruses, and the potential solutions. The complete prediction of virus-host interactions remains difficult; however, bioinformatics can contribute to progress in research on infectious diseases and human health.

    DOI PubMed

  • Web Services for RNA-RNA Interaction Prediction

    Tsukasa Fukunaga, Junichi Iwakiri, Michiaki Hamada

    Methods in molecular biology (Clifton, N.J.)   2586   175 - 195  2023年

    担当区分:筆頭著者

     概要を見る

    Non-coding RNAs have various biological functions such as translational regulation, and RNA-RNA interactions play essential roles in the mechanisms of action of these RNAs. Therefore, RNA-RNA interaction prediction is an important problem in bioinformatics, and many tools have been developed for the computational prediction of RNA-RNA interactions. In addition to the development of novel algorithms with high accuracy, the development and maintenance of web services is essential for enhancing usability by experimental biologists. In this review, we survey web services for RNA-RNA interaction predictions and introduce how to use primary web services. We present various prediction tools, including general interaction prediction tools, prediction tools for specific RNA classes, and RNA-RNA interaction-based RNA design tools. Additionally, we discuss the future perspectives of the development of RNA-RNA interaction prediction tools and the sustainability of web services.

    DOI PubMed

  • Fast RNA-RNA Interaction Prediction Methods for Interaction Analysis of Transcriptome-Scale Large Datasets

    Tsukasa Fukunaga, Michiaki Hamada

    Methods in molecular biology (Clifton, N.J.)   2586   163 - 173  2023年

    担当区分:筆頭著者

     概要を見る

    The computational prediction of RNA-RNA interactions has long been studied in RNA informatics. Most of the existing approaches focused on the interaction prediction of short RNAs in small datasets. However, in recent years, two fast prediction methods, RIsearch2 and RIblast, have been developed to predict transcriptome-scale interactions or long RNA interactions. The key idea of the software acceleration of these tools was the integration of a seed-and-extend method, which is used in fast sequence alignment tools, into RNA-RNA interaction prediction. As a result, the two software programs were ten to a thousand times faster than the existing tools; because of this acceleration, detection of genome-wide microRNA target sites or interaction partners of function-unknown long noncoding RNAs has become possible. In this review, we describe the basic concept of the algorithm, its applications, and the future perspectives of the fast RNA-RNA interaction prediction tools.

    DOI PubMed

  • LinAliFold and CentroidLinAliFold: fast RNA consensus secondary structure prediction for aligned sequences using beam search methods

    Tsukasa Fukunaga, Michiaki Hamada

    Bioinformatics Advances   2 ( 1 )  2022年10月  [査読有り]

    担当区分:筆頭著者, 責任著者

     概要を見る

    Abstract

    Motivation

    RNA consensus secondary structure prediction from aligned sequences is a powerful approach for improving the secondary structure prediction accuracy. However, because the computational complexities of conventional prediction tools scale with the cube of the alignment lengths, their application to long RNA sequences, such as viral RNAs or long non-coding RNAs, requires significant computational time.

    Results

    In this study, we developed LinAliFold and CentroidLinAliFold, fast RNA consensus secondary structure prediction tools based on minimum free energy and maximum expected accuracy principles, respectively. We achieved software acceleration using beam search methods that were successfully used for fast secondary structure prediction from a single RNA sequence. Benchmark analyses showed that LinAliFold and CentroidLinAliFold were much faster than the existing methods while preserving the prediction accuracy. As an empirical application, we predicted the consensus secondary structure of coronaviruses with approximately 30 000 nt in 5 and 79 min by LinAliFold and CentroidLinAliFold, respectively. We confirmed that the predicted consensus secondary structure of coronaviruses was consistent with the experimental results.

    Availability and implementation

    The source codes of LinAliFold and CentroidLinAliFold are freely available at https://github.com/fukunagatsu/LinAliFold-CentroidLinAliFold.

    Supplementary information

    Supplementary data are available at Bioinformatics Advances online.

    DOI

  • Mirage 2.0: fast and memory-efficient reconstruction of gene-content evolution considering heterogeneous evolutionary patterns among gene families.

    Tsukasa Fukunaga, Wataru Iwasaki

    Bioinformatics (Oxford, England)    2022年06月  [査読有り]  [国際誌]

    担当区分:筆頭著者, 責任著者

     概要を見る

    SUMMARY: We present Mirage 2.0, which accurately estimates gene-content evolutionary history by considering heterogeneous evolutionary patterns among gene families. Notably, we introduce a deterministic pattern mixture (DPM) model, which makes Mirage substantially faster and more memory-efficient to be applicable to large datasets with thousands of genomes. AVAILABILITY: The source code is freely available at https://github.com/fukunagatsu/Mirage. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

    DOI PubMed

  • Inverse Potts model improves accuracy of phylogenetic profiling.

    Tsukasa Fukunaga, Wataru Iwasaki

    Bioinformatics (Oxford, England)    2022年01月  [査読有り]  [国際誌]

    担当区分:筆頭著者, 責任著者

     概要を見る

    MOTIVATION: Phylogenetic profiling is a powerful computational method for revealing the functions of function-unknown genes. Although conventional similarity metrics in phylogenetic profiling achieved high prediction accuracy, they have two estimation biases: an evolutionary bias and a spurious correlation bias. While previous studies reduced the evolutionary bias by considering a phylogenetic tree, few studies have analyzed the spurious correlation bias. RESULTS: To reduce the spurious correlation bias, we developed metrics based on the inverse Potts model (IPM) for phylogenetic profiling. We also developed a metric based on both the IPM and a phylogenetic tree. In an empirical dataset analysis, we demonstrated that these IPM-based metrics improved the prediction performance of phylogenetic profiling. In addition, we found that the integration of several metrics, including the IPM-based metrics, had superior performance to a single metric. AVAILABILITY: The source code is freely available at https://github.com/fukunagatsu/Ipm. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

    DOI PubMed

  • Bioinformatics Approaches for Determining the Functional Impact of Repetitive Elements on Non-coding RNAs.

    Chao Zeng, Atsushi Takeda, Kotaro Sekine, Naoki Osato, Tsukasa Fukunaga, Michiaki Hamada

    Methods in molecular biology (Clifton, N.J.)   2509   315 - 340  2022年  [国際誌]

     概要を見る

    With a large number of annotated non-coding RNAs (ncRNAs), repetitive sequences are found to constitute functional components (termed as repetitive elements) in ncRNAs that perform specific biological functions. Bioinformatics analysis is a powerful tool for improving our understanding of the role of repetitive elements in ncRNAs. This chapter summarizes recent findings that reveal the role of repetitive elements in ncRNAs. Furthermore, relevant bioinformatics approaches are systematically reviewed, which promises to provide valuable resources for studying the functional impact of repetitive elements on ncRNAs.

    DOI PubMed

  • Mirage: Estimation of ancestral gene-copy numbers by considering different evolutionary patterns among gene families

    Tsukasa Fukunaga, Wataru Iwasaki

    Bioinformatics Advances    2021年07月  [査読有り]

    担当区分:筆頭著者, 責任著者

     概要を見る

    <title>Abstract</title>
    <sec>
    <title>Motivation</title>
    Reconstruction of gene copy number evolution is an essential approach for understanding how complex biological systems have been organized. Although various models have been proposed for gene copy number evolution, existing evolutionary models have not appropriately addressed the fact that different gene families can have very different gene gain/loss rates.


    </sec>
    <sec>
    <title>Results</title>
    In this study, we developed Mirage (MIxtuRe model for Ancestral Genome Estimation), which allows different gene families to have flexible gene gain/loss rates. Mirage can use three models for formulating heterogeneous evolution among gene families: the discretized Γ model, PDF model, and PM model. Simulation analysis showed that Mirage can accurately estimate heterogeneous gene gain/loss rates and reconstruct gene content evolutionary history. Application to empirical datasets demonstrated that the PM model fits genome data from various taxonomic groups better than the other heterogeneous models. Using Mirage, we revealed that metabolic function-related gene families displayed frequent gene gains and losses in all taxa investigated.


    </sec>
    <sec>
    <title>Availability</title>
    The source code of Mirage is freely available at https://github.com/fukunagatsu/Mirage.


    </sec>
    <sec>
    <title>Supplementary information</title>
    Supplementary data are available at Bioinformatics Advances online.


    </sec>

    DOI

  • Umibato: estimation of time-varying microbial interaction using continuous-time regression hidden Markov model.

    Shion Hosoda, Tsukasa Fukunaga, Michiaki Hamada

    Bioinformatics (Oxford, England)   37 ( Suppl_1 ) i16-i24  2021年07月  [査読有り]  [国際誌]

     概要を見る

    MOTIVATION: Accumulating evidence has highlighted the importance of microbial interaction networks. Methods have been developed for estimating microbial interaction networks, of which the generalized Lotka-Volterra equation (gLVE)-based method can estimate a directed interaction network. The previous gLVE-based method for estimating microbial interaction networks did not consider time-varying interactions. RESULTS: In this study, we developed unsupervised learning-based microbial interaction inference method using Bayesian estimation (Umibato), a method for estimating time-varying microbial interactions. The Umibato algorithm comprises Gaussian process regression (GPR) and a new Bayesian probabilistic model, the continuous-time regression hidden Markov model (CTRHMM). Growth rates are estimated by GPR, and interaction networks are estimated by CTRHMM. CTRHMM can estimate time-varying interaction networks using interaction states, which are defined as hidden variables. Umibato outperformed the existing methods on synthetic datasets. In addition, it yielded reasonable estimations in experiments on a mouse gut microbiota dataset, thus providing novel insights into the relationship between consumed diets and the gut microbiota. AVAILABILITY AND IMPLEMENTATION: The C++ and python source codes of the Umibato software are available at https://github.com/shion-h/Umibato. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

    DOI PubMed

  • Representation learning applications in biological sequence analysis.

    Hitoshi Iuchi, Taro Matsutani, Keisuke Yamada, Natsuki Iwano, Shunsuke Sumi, Shion Hosoda, Shitao Zhao, Tsukasa Fukunaga, Michiaki Hamada

    Computational and structural biotechnology journal   19   3198 - 3208  2021年  [査読有り]  [国際誌]

     概要を見る

    Although remarkable advances have been reported in high-throughput sequencing, the ability to aptly analyze a substantial amount of rapidly generated biological (DNA/RNA/protein) sequencing data remains a critical hurdle. To tackle this issue, the application of natural language processing (NLP) to biological sequence analysis has received increased attention. In this method, biological sequences are regarded as sentences while the single nucleic acids/amino acids or k-mers in these sequences represent the words. Embedding is an essential step in NLP, which performs the conversion of these words into vectors. Specifically, representation learning is an approach used for this transformation process, which can be applied to biological sequences. Vectorized biological sequences can then be applied for function and structure estimation, or as input for other probabilistic models. Considering the importance and growing trend for the application of representation learning to biological research, in the present study, we have reviewed the existing knowledge in representation learning for biological sequence analysis.

    DOI PubMed

  • Novel metric for hyperbolic phylogenetic tree embeddings.

    Hirotaka Matsumoto, Takahiro Mimori, Tsukasa Fukunaga

    Biology methods & protocols   6 ( 1 ) bpab006  2021年  [査読有り]  [国際誌]

     概要を見る

    Advances in experimental technologies, such as DNA sequencing, have opened up new avenues for the applications of phylogenetic methods to various fields beyond their traditional application in evolutionary investigations, extending to the fields of development, differentiation, cancer genomics, and immunogenomics. Thus, the importance of phylogenetic methods is increasingly being recognized, and the development of a novel phylogenetic approach can contribute to several areas of research. Recently, the use of hyperbolic geometry has attracted attention in artificial intelligence research. Hyperbolic space can better represent a hierarchical structure compared to Euclidean space, and can therefore be useful for describing and analyzing a phylogenetic tree. In this study, we developed a novel metric that considers the characteristics of a phylogenetic tree for representation in hyperbolic space. We compared the performance of the proposed hyperbolic embeddings, general hyperbolic embeddings, and Euclidean embeddings, and confirmed that our method could be used to more precisely reconstruct evolutionary distance. We also demonstrate that our approach is useful for predicting the nearest-neighbor node in a partial phylogenetic tree with missing nodes. Furthermore, we proposed a novel approach based on our metric to integrate multiple trees for analyzing tree nodes or imputing missing distances. This study highlights the utility of adopting a geometric approach for further advancing the applications of phylogenetic methods.

    DOI PubMed

  • MotiMul: A significant discriminative sequence motif discovery algorithm with multiple testing correction

    Koichi Mori, Haruka Ozaki, Tsukasa Fukunaga

    Proceedings - 2020 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2020     186 - 193  2020年12月  [査読有り]

    担当区分:最終著者, 責任著者

     概要を見る

    Sequence motifs play essential roles in intermolecular interactions such as DNA-protein interactions. The discovery of novel sequence motifs is therefore crucial for revealing gene functions. Various bioinformatics tools have been developed for finding sequence motifs, but until now there has been no software based on statistical hypothesis testing with statistically sound multiple testing correction. Existing software therefore could not control for the type-l error rates. This is because, in the sequence motif discovery problem, conventional multiple testing correction methods produce very low statistical power due to overly-strict correction. We developed MotiMul, which comprehensively finds significant sequence motifs using statistically sound multiple testing correction. Our key idea is the application of Tarone's correction, which improves the statistical power of the hypothesis test by ignoring hypotheses that never become statistically significant. For the efficient enumeration of the significant sequence motifs, we integrated a variant of the PrefixSpan algorithm with Tarone's correction. Simulation and empirical dataset analysis showed that MotiMul is a powerful method for finding biologically meaningful sequence motifs. The source code of MotiMul is freely available at https://github.com/ko-ichimo-ri/MotiMul.

    DOI

  • Revealing the microbial assemblage structure in the human gut microbiome using latent Dirichlet allocation

    Shion Hosoda, Suguru Nishijima, Tsukasa Fukunaga, Masahira Hattori, Michiaki Hamada

    Microbiome   8 ( 1 ) 95 - 95  2020年06月  [査読有り]  [国際誌]

     概要を見る

    Background: The human gut microbiome has been suggested to affect human health and thus has received considerable attention. To clarify the structure of the human gut microbiome, clustering methods are frequently applied to human gut taxonomic profiles. Enterotypes, i.e., clusters of individuals with similar microbiome composition, are well-studied and characterized. However, only a few detailed studies on assemblages, i.e., clusters of co-occurring bacterial taxa, have been conducted. Particularly, the relationship between the enterotype and assemblage is not well-understood. Results: In this study, we detected gut microbiome assemblages using a latent Dirichlet allocation (LDA) method. We applied LDA to a large-scale human gut metagenome dataset and found that a 4-assemblage LDA model could represent relationships between enterotypes and assemblages with high interpretability. This model indicated that each individual tends to have several assemblages, three of which corresponded to the three classically recognized enterotypes. Conversely, the fourth assemblage corresponded to no enterotypes and emerged in all enterotypes. Interestingly, the dominant genera of this assemblage (Clostridium, Eubacterium, Faecalibacterium, Roseburia, Coprococcus, and Butyrivibrio) included butyrate-producing species such as Faecalibacterium prausnitzii. Indeed, the fourth assemblage significantly positively correlated with three butyrate-producing functions. Conclusions: We conducted an assemblage analysis on a large-scale human gut metagenome dataset using LDA. The present study revealed that there is an enterotype-independent assemblage. [MediaObject not available: see fulltext.]

    DOI PubMed

  • Logicome profiler: Exhaustive detection of statistically significant logic relationships from comparative omics data

    Tsukasa Fukunaga, Wataru Iwasaki

    PLoS ONE   15 ( 5 ) e0232106  2020年05月  [査読有り]  [国際誌]

    担当区分:筆頭著者, 責任著者

     概要を見る

    Logic relationship analysis is a data mining method that comprehensively detects item triplets that satisfy logic relationships from a binary matrix dataset, such as an ortholog table in comparative genomics. Thanks to recent technological advancements, many binary matrix datasets are now being produced in genomics, transcriptomics, epigenomics, metagenomics, and many other fields for comparative purposes. However, regardless of presumed interpretability and importance of logic relationships, existing data mining methods are not based on the framework of statistical hypothesis testing. That means, the type-1 and type-2 error rates are neither controlled nor estimated. Here, we developed Logicome Profiler, which exhaustively detects statistically significant triplet logic relationships from a binary matrix dataset (Logicome means ome of logics). To test all item triplets in a dataset while avoiding false positives, Logicome Profiler adjusts a significance level by the Bonferroni or Benjamini-Yekutieli method for the multiple testing correction. Its application to an ocean metagenomic dataset showed that Logicome Profiler can effectively detect statistically significant triplet logic relationships among environmental microbes and genes, which include those among urea transporter, urease, and photosynthesis-related genes. Beyond omics data analysis, Logicome Profiler is applicable to various binary matrix datasets in general for finding significant triplet logic relationships. The source code is available at https://github.com/fukunagatsu/LogicomeProfiler.

    DOI PubMed

  • Targeting the TR4 nuclear receptor-mediated lncTASR/AXL signaling with tretinoin increases the sunitinib sensitivity to better suppress the RCC progression

    Hangchuan Shi, Yin Sun, Miao He, Xiong Yang, Michiaki Hamada, Tsukasa Fukunaga, Xiaoping Zhang, Chawnshang Chang

    Oncogene   39 ( 3 ) 530 - 545  2020年01月  [査読有り]  [国際誌]

     概要を見る

    Renal cell carcinoma (RCC) is one of the most lethal urological tumors. Using sunitinib to improve the survival has become the first-line therapy for metastatic RCC patients. However, the occurrence of sunitinib resistance in the clinical application has curtailed its efficacy. Here we found TR4 nuclear receptor might alter the sunitinib resistance to RCC via altering the TR4/lncTASR/AXL signaling. Mechanism dissection revealed that TR4 could modulate lncTASR (ENST00000600671.1) expression via transcriptional regulation, which might then increase AXL protein expression via enhancing the stability of AXL mRNA to increase the sunitinib resistance in RCC. Human clinical surveys also linked the expression of TR4, lncTASR, and AXL to the RCC survival, and results from multiple RCC cell lines revealed that targeting this newly identified TR4-mediated signaling with small molecules, including tretinoin, metformin, or TR4-shRNAs, all led to increase the sunitinib sensitivity to better suppress the RCC progression, and our preclinical study using the in vivo mouse model further proved tretinoin had a better synergistic effect to increase sunitinib sensitivity to suppress RCC progression. Future successful clinical trials may help in the development of a novel therapy to better suppress the RCC progression.

    DOI PubMed

  • Discovering novel mutation signatures by latent Dirichlet allocation with variational Bayes inference

    Taro Matsutani, Yuki Ueno, Tsukasa Fukunaga, Michiaki Hamada

    Bioinformatics   35 ( 22 ) 4543 - 4552  2019年11月  [査読有り]  [国際誌]

     概要を見る

    A cancer genome includes many mutations derived from various mutagens and mutational processes, leading to specific mutation patterns. It is known that each mutational process leads to characteristic mutations, and when a mutational process has preferences for mutations, this situation is called a 'mutation signature.' Identification of mutation signatures is an important task for elucidation of carcinogenic mechanisms. In previous studies, analyses with statistical approaches (e.g. non-negative matrix factorization and latent Dirichlet allocation) revealed a number of mutation signatures. Nonetheless, strictly speaking, these existing approaches employ an ad hoc method or incorrect approximation to estimate the number of mutation signatures, and the whole picture of mutation signatures is unclear. Results: In this study, we present a novel method for estimating the number of mutation signatures- latent Dirichlet allocation with variational Bayes inference (VB-LDA)-where variational lower bounds are utilized for finding a plausible number of mutation patterns. In addition, we performed cluster analyses for estimated mutation signatures to extract novel mutation signatures that appear in multiple primary lesions. In a simulation with artificial data, we confirmed that our method estimated the correct number of mutation signatures. Furthermore, applying our method in combination with clustering procedures for real mutation data revealed many interesting mutation signatures that have not been previously reported.

    DOI PubMed

  • Lncrrisearch: A web server for lncRNA-RNA interaction prediction integrated with tissue-specific expression and subcellular localization data

    Tsukasa Fukunaga, Junichi Iwakiri, Yukiteru Ono, Michiaki Hamada

    Frontiers in Genetics   10 ( MAY ) 462 - 462  2019年  [査読有り]  [国際誌]

    担当区分:筆頭著者

     概要を見る

    Long non-coding RNAs (lncRNAs) play critical roles in various biological processes, but the function of the majority of lncRNAs is still unclear. One approach for estimating a function of a lncRNA is the identification of its interaction target because functions of lncRNAs are expressed through interaction with other biomolecules in quite a few cases. In this paper, we developed “LncRRIsearch,” which is a web server for comprehensive prediction of human and mouse lncRNA-lncRNA and lncRNA-mRNA interaction. The prediction was conducted using RIblast, which is a fast and accurate RNA-RNA interaction prediction tool. Users can investigate interaction target RNAs of a particular lncRNA through a web interface. In addition, we integrated tissue-specific expression and subcellular localization data for the lncRNAs with the web server. These data enable users to examine tissue-specific or subcellular localized lncRNA interactions. LncRRIsearch is publicly accessible at http://rtools.cbrc.jp/LncRRIsearch/.

    DOI PubMed

  • A Novel Method for Assessing the Statistical Significance of RNA-RNA Interactions Between Two Long RNAs

    Tsukasa Fukunaga, Michiaki Hamada

    Journal of Computational Biology   25 ( 9 ) 976 - 986  2018年09月  [査読有り]  [国際誌]

    担当区分:筆頭著者, 責任著者

     概要を見る

    RNA-RNA interactions are key mechanisms through which noncoding RNA (ncRNA) regions exert biological functions. Computational prediction of RNA-RNA interactions is an essential method for detecting novel RNA-RNA interactions because their comprehensive detection by biological experimentation is still quite difficult. Many RNA-RNA interaction prediction tools have been developed, but they tend to produce many false positives. Accordingly, assessment of the statistical significance of computationally predicted interactions is an important task. However, there is no method to evaluate the statistical significance of RNA-RNA interactions that is applicable to interactions between two long RNA sequences. We developed a method to calculate the p-value for the minimal interaction energy between two long RNA sequences. The developed method depends on the fact that minimum interaction energies of RNA-RNA interactions between long RNAs follow a Gumbel distribution when repeat sequences in RNAs are masked. To show the usefulness of the developed method, we applied it to whole human 5′-untranslated region (UTR) and 3′-UTR sequences to detect novel 5′-UTR-3′-UTR interactions. We thus identified two significant 5′-UTR-3′-UTR interactions. Specifically, the human small proline-rich repeat protein 3 shows conserved 5′-UTR-3′-UTR interactions with some nucleotide variations preserving base pairings among primates. Our developed method enables us to detect statistically significant RNA-RNA interactions between long RNAs such as long ncRNAs. Statistical significance estimates help in identification of interactions for experimental validation and provide novel insights into the function of ncRNA regions.

    DOI PubMed

  • Computational approaches for alternative and transient secondary structures of ribonucleic acids

    Tsukasa Fukunaga, Michiaki Hamada

    Briefings in Functional Genomics   18 ( 3 ) 182 - 191  2018年06月  [査読有り]  [国際誌]

    担当区分:筆頭著者

     概要を見る

    Transient and alternative structures of ribonucleic acids (RNAs) play essential roles in various regulatory processes, such as translation regulation in living cells. Because experimental analyses for RNA structures are difficult and time-consuming, computational approaches based on RNA secondary structures are promising. In this article, we review computational methods for detecting and analyzing transient/alternative secondary structures of RNAs, including static approaches based on probabilistic distributions of RNA secondary structures and dynamic approaches such as kinetic folding and folding pathway predictions.

    DOI PubMed

  • MitoFish and mifish pipeline: A mitochondrial genome database of fish with an analysis pipeline for environmental DNA metabarcoding

    Yukuto Sato, Masaki Miya, Tsukasa Fukunaga, Tetsuya Sado, Wataru Iwasaki

    Molecular Biology and Evolution   35 ( 6 ) 1553 - 1555  2018年06月  [査読有り]

     概要を見る

    Fish mitochondrial genome (mitogenome) data form a fundamental basis for revealing vertebrate evolution and hydrosphere ecology. Here, we report recent functional updates of MitoFish, which is a database of fish mitogenomes with a precise annotation pipeline MitoAnnotator. Most importantly, we describe implementation of MiFish pipeline for metabarcoding analysis of fish mitochondrial environmental DNA, which is a fast-emerging and powerful technology in fish studies. MitoFish, MitoAnnotator, and MiFish pipeline constitute a key platform for studies of fish evolution, ecology, and conservation, and are freely available at http://mitofish.aori.u-Tokyo.ac.jp/ (last accessed April 7th, 2018).

    DOI PubMed

  • Identification and analysis of ribosome-associated lncRNAs using ribosome profiling data

    Chao Zeng, Tsukasa Fukunaga, Michiaki Hamada

    BMC Genomics   19 ( 1 ) 414 - 414  2018年05月  [査読有り]  [国際誌]

     概要を見る

    Background: Although the number of discovered long non-coding RNAs (lncRNAs) has increased dramatically, their biological roles have not been established. Many recent studies have used ribosome profiling data to assess the protein-coding capacity of lncRNAs. However, very little work has been done to identify ribosome-associated lncRNAs, here defined as lncRNAs interacting with ribosomes related to protein synthesis as well as other unclear biological functions. Results: On average, 39.17% of expressed lncRNAs were observed to interact with ribosomes in human and 48.16% in mouse. We developed the ribosomal association index (RAI), which quantifies the evidence for ribosomal associability of lncRNAs over various tissues and cell types, to catalog 691 and 409 lncRNAs that are robustly associated with ribosomes in human and mouse, respectively. Moreover, we identified 78 and 42 lncRNAs with a high probability of coding peptides in human and mouse, respectively. Compared with ribosome-free lncRNAs, ribosome-associated lncRNAs were observed to be more likely to be located in the cytoplasm and more sensitive to nonsense-mediated decay. Conclusion: Our results suggest that RAI can be used as an integrative and evidence-based tool for distinguishing between ribosome-associated and free lncRNAs, providing a valuable resource for the study of lncRNA functions.

    DOI PubMed

  • Solar-panel and parasol strategies shape the proteorhodopsin distribution pattern in marine Flavobacteriia

    Yohei Kumagai, Susumu Yoshizawa, Yu Nakajima, Mai Watanabe, Tsukasa Fukunaga, Yoshitoshi Ogura, Tetsuya Hayashi, Kenshiro Oshima, Masahira Hattori, Masahiko Ikeuchi, Kazuhiro Kogure, Edward F. Delong, Wataru Iwasaki

    ISME Journal   12 ( 5 ) 1329 - 1343  2018年05月  [査読有り]  [国際誌]

     概要を見る

    Proteorhodopsin (PR) is a light-driven proton pump that is found in diverse bacteria and archaea species, and is widespread in marine microbial ecosystems. To date, many studies have suggested the advantage of PR for microorganisms in sunlit environments. The ecophysiological significance of PR is still not fully understood however, including the drivers of PR gene gain, retention, and loss in different marine microbial species. To explore this question we sequenced 21 marine Flavobacteriia genomes of polyphyletic origin, which encompassed both PR-possessing as well as PR-lacking strains. Here, we show that the possession or alternatively the lack of PR genes reflects one of two fundamental adaptive strategies in marine bacteria. Specifically, while PR-possessing bacteria utilize light energy ("solar-panel strategy"), PR-lacking bacteria exclusively possess UV-screening pigment synthesis genes to avoid UV damage and would adapt to microaerobic environment ("parasol strategy"), which also helps explain why PR-possessing bacteria have smaller genomes than those of PR-lacking bacteria. Collectively, our results highlight the different strategies of dealing with light, DNA repair, and oxygen availability that relate to the presence or absence of PR phototrophy.

    DOI PubMed

  • RIblast: an ultrafast RNA-RNA interaction prediction system based on a seed-and-extension approach

    Tsukasa Fukunaga, Michiaki Hamada

    Bioinformatics (Oxford, England)   33 ( 17 ) 2666 - 2674  2017年09月  [査読有り]  [国際誌]

    担当区分:筆頭著者, 責任著者

     概要を見る

    Motivation: LncRNAs play important roles in various biological processes. Although more than 58 000 human lncRNA genes have been discovered, most known lncRNAs are still poorly characterized. One approach to understanding the functions of lncRNAs is the detection of the interacting RNA target of each lncRNA. Because experimental detections of comprehensive lncRNA-RNA interactions are difficult, computational prediction of lncRNA-RNA interactions is an indispensable technique. However, the high computational costs of existing RNA-RNA interaction prediction tools prevent their application to large-scale lncRNA datasets.

    DOI PubMed

  • Inactivity periods and postural change speed can explain atypical postural change patterns of Caenorhabditis elegans mutants

    Tsukasa Fukunaga, Wataru Iwasaki

    BMC Bioinformatics   18 ( 1 ) 46  2017年01月  [査読有り]

    担当区分:筆頭著者, 責任著者

     概要を見る

    Background: With rapid advances in genome sequencing and editing technologies, systematic and quantitative analysis of animal behavior is expected to be another key to facilitating data-driven behavioral genetics. The nematode Caenorhabditis elegans is a model organism in this field. Several video-tracking systems are available for automatically recording behavioral data for the nematode, but computational methods for analyzing these data are still under development. Results: In this study, we applied the Gaussian mixture model-based binning method to time-series postural data for 322 C. elegans strains. We revealed that the occurrence patterns of the postural states and the transition patterns among these states have a relationship as expected, and such a relationship must be taken into account to identify strains with atypical behaviors that are different from those of wild type. Based on this observation, we identified several strains that exhibit atypical transition patterns that cannot be fully explained by their occurrence patterns of postural states. Surprisingly, we found that two simple factors-overall acceleration of postural movement and elimination of inactivity periods-explained the behavioral characteristics of strains with very atypical transition patterns; therefore, computational analysis of animal behavior must be accompanied by evaluation of the effects of these simple factors. Finally, we found that the npr-1 and npr-3 mutants have similar behavioral patterns that were not predictable by sequence homology, proving that our data-driven approach can reveal the functions of genes that have not yet been characterized. Conclusion: We propose that elimination of inactivity periods and overall acceleration of postural change speed can explain behavioral phenotypes of strains with very atypical postural transition patterns. Our methods and results constitute guidelines for effectively finding strains that show "truly" interesting behaviors and systematically uncovering novel gene functions by bioimage-informatic approaches.

    DOI PubMed

  • Rtools: a web server for various secondary structural analyses on single RNA sequences

    Michiaki Hamada, Yukiteru Ono, Hisanori Kiryu, Kengo Sato, Yuki Kato, Tsukasa Fukunaga, Ryota Mori, Kiyoshi Asai

    Nucleic acids research   44 ( W1 ) W302 - W307  2016年07月  [査読有り]

     概要を見る

    The secondary structures, as well as the nucleotide sequences, are the important features of RNA molecules to characterize their functions. According to the thermodynamic model, however, the probability of any secondary structure is very small. As a consequence, any tool to predict the secondary structures of RNAs has limited accuracy. On the other hand, there are a few tools to compensate the imperfect predictions by calculating and visualizing the secondary structural information from RNA sequences. It is desirable to obtain the rich information from those tools through a friendly interface. We implemented a web server of the tools to predict secondary structures and to calculate various structural features based on the energy models of secondary structures. By just giving an RNA sequence to the web server, the user can get the different types of solutions of the secondary structures, the marginal probabilities such as base-paring probabilities, loop probabilities and accessibilities of the local bases, the energy changes by arbitrary base mutations as well as the measures for validations of the predicted secondary structures. The web server is available at http://rtools.cbrc.jp, which integrates software tools, CentroidFold, CentroidHomfold, IPKnot, CapR, Raccess, Rchange and RintD.

    DOI PubMed

  • GroupTracker: Video tracking system for multiple animals under severe occlusion

    Tsukasa Fukunaga, Shoko Kubota, Shoji Oda, Wataru Iwasaki

    Computational Biology and Chemistry   57   39 - 45  2015年12月  [査読有り]

    担当区分:筆頭著者, 責任著者

     概要を見る

    Quantitative analysis of behaviors shown by interacting multiple animals can provide a key for revealing high-order functions of their nervous systems. To resolve these complex behaviors, a video tracking system that preserves individual identity even under severe overlap in positions, i.e., occlusion, is needed. We developed GroupTracker, a multiple animal tracking system that accurately tracks individuals even under severe occlusion. As maximum likelihood estimation of Gaussian mixture model whose components can severely overlap is theoretically an ill-posed problem, we devised an expectation-maximization scheme with additional constraints on the eigenvalues of the covariance matrix of the mixture components. Our system was shown to accurately track multiple medaka (Oryzias latipes) which freely swim around in three dimensions and frequently overlap each other. As an accurate multiple animal tracking system, GroupTracker will contribute to revealing unexplored structures and patterns behind animal interactions. The Java source code of GroupTracker is available at https://sites.google.com/site/fukunagatsu/software/group-tracker.

    DOI PubMed J-GLOBAL

  • MiFish, a set of universal PCR primers for metabarcoding environmental DNA from fishes: detection of more than 230 subtropical marine species

    M. Miya, M. Miya, Y. Sato, Y. Sato, T. Fukunaga, T. Sado, T. Sado, J. Y. Poulsen, J. Y. Poulsen, J. Y. Poulsen, K. Sato, T. Minamoto, T. Minamoto, S. Yamamoto, S. Yamamoto, H. Yamanaka, H. Yamanaka, H. Araki, H. Araki, M. Kondoh, M. Kondoh, W. Iwasaki, W. Iwasaki, W. Iwasaki

    Royal Society Open Science   2 ( 7 )  2015年07月  [査読有り]

     概要を見る

    © 2015 The Authors. We developed a set of universal PCR primers (MiFish-U/E) for metabarcoding environmental DNA (eDNA) from fishes. Primers were designed using aligned whole mitochondrial genome (mitogenome) sequences from 880 species, supplemented by partial mitogenome sequences from 160 elasmobranchs (sharks and rays). The primers target a hypervariable region of the 12S rRNA gene (163–185 bp), which contains sufficient information to identify fishes to taxonomic family, genus and species except for some closely related congeners. To test versatility of the primers across a diverse range of fishes, we sampled eDNA from four tanks in the Okinawa Churaumi Aquarium with known species compositions, prepared dual-indexed libraries and performed paired-end sequencing of the region using high-throughput next-generation sequencing technologies. Out of the 180 marine fish species contained in the four tanks with reference sequences in a custom database, we detected 168 species (93.3%) distributed across 59 families and 123 genera. These fishes are not only taxonomically diverse, ranging from sharks and rays to higher teleosts, but are also greatly varied in their ecology, including both pelagic and benthic species living in shallow coastal to deep waters. We also sampled natural seawaters around coral reefs near the aquarium and detected 93 fish species using this approach. Of the 93 species, 64 were not detected in the four aquarium tanks, rendering the total number of species detected to 232 (from 70 families and 152 genera). The metabarcoding approach presented here is non-invasive, more efficient, more cost-effective and more sensitive than the traditional survey methods. It has the potential to serve as an alternative (or complementary) tool for biodiversity monitoring that revolutionizes natural resource management and ecological studies of fish communities on larger spatial and temporal scales.

    DOI

  • MiFish, a set of universal PCR primers for metabarcoding environmental DNA from fishes: Detection of more than 230 subtropical marine species

    M. Miya, Y. Sato, T. Fukunaga, T. Sado, J. Y. Poulsen, K. Sato, T. Minamoto, S. Yamamoto, H. Yamanaka, H. Araki, M. Kondoh, W. Iwasaki

    Royal Society Open Science   2 ( 7 ) 150088  2015年07月  [査読有り]

     概要を見る

    We developed a set of universal PCR primers (MiFish-U/E) for metabarcoding environmental DNA (eDNA) from fishes. Primers were designed using aligned whole mitochondrial genome (mitogenome) sequences from 880 species, supplemented by partial mitogenome sequences from 160 elasmobranchs (sharks and rays). The primers target a hypervariable region of the 12S rRNA gene (163–185 bp), which contains sufficient information to identify fishes to taxonomic family, genus and species except for some closely related congeners. To test versatility of the primers across a diverse range of fishes, we sampled eDNA from four tanks in the Okinawa Churaumi Aquarium with known species compositions, prepared dual-indexed libraries and performed paired-end sequencing of the region using high-throughput next-generation sequencing technologies. Out of the 180 marine fish species contained in the four tanks with reference sequences in a custom database, we detected 168 species (93.3%) distributed across 59 families and 123 genera. These fishes are not only taxonomically diverse, ranging from sharks and rays to higher teleosts, but are also greatly varied in their ecology, including both pelagic and benthic species living in shallow coastal to deep waters. We also sampled natural seawaters around coral reefs near the aquarium and detected 93 fish species using this approach. Of the 93 species, 64 were not detected in the four aquarium tanks, rendering the total number of species detected to 232 (from 70 families and 152 genera). The metabarcoding approach presented here is non-invasive, more efficient, more cost-effective and more sensitive than the traditional survey methods. It has the potential to serve as an alternative (or complementary) tool for biodiversity monitoring that revolutionizes natural resource management and ecological studies of fish communities on larger spatial and temporal scales.

    DOI PubMed

  • Capr: Revealing structural specificities of rna-binding protein target recognition using clip-seq data

    Tsukasa Fukunaga, Haruka Ozaki, Goro Terai, Kiyoshi Asai, Wataru Iwasaki, Hisanori Kiryu

    Genome Biology   15 ( 1 ) R16  2014年  [査読有り]

    担当区分:筆頭著者, 責任著者

     概要を見る

    RNA-binding proteins (RBPs) bind to their target RNA molecules by recognizing specific RNA sequences and structural contexts. The development of CLIP-seq and related protocols has made it possible to exhaustively identify RNA fragments that bind to RBPs. However, no efficient bioinformatics method exists to reveal the structural specificities of RBP-RNA interactions using these data. We present CapR, an efficient algorithm that calculates the probability that each RNA base position is located within each secondary structural context. Using CapR, we demonstrate that several RBPs bind to their target RNA molecules under specific structural contexts.

    DOI PubMed J-GLOBAL

  • Mitofish and mitoannotator: A mitochondrial genome database of fish with an accurate and automatic annotation pipeline

    Wataru Iwasaki, Tsukasa Fukunaga, Ryota Isagozawa, Koichiro Yamada, Yasunobu Maeda, Takashi P. Satoh, Tetsuya Sado, Kohji Mabuchi, Hirohiko Takeshima, Masaki Miya, Mutsumi Nishida

    Molecular Biology and Evolution   30 ( 11 ) 2531 - 2540  2013年11月  [査読有り]

     概要を見る

    Mitofish is a database of fish mitochondrial genomes (mitogenomes) that includes powerful and precise de novo annotations for mitogenome sequences. Fish occupy an important position in the evolution of vertebrates and the ecology of the hydrosphere, and mitogenomic sequence data have served as a rich source of information for resolving fish phylogenies and identifying new fish species. The importance of a mitogenomic database continues to grow at a rapid pace as massive amounts of mitogenomic data are generated with the advent of new sequencing technologies. A severe bottleneck seems likely to occur with regard to mitogenome annotation because of the overwhelming pace of data accumulation and the intrinsic difficulties in annotating sequences with degenerating transfer RNA structures, divergent start/stop codons of the coding elements, and the overlapping of adjacent elements. To ease this data backlog, we developed an annotation pipeline named MitoAnnotator. MitoAnnotator automatically annotates a fish mitogenome with a high degree of accuracy in approximately 5 min; thus, it is readily applicable to data sets of dozens of sequences. MitoFish also contains re-annotations of previously sequenced fish mitogenomes, enabling researchers to refer to them when they find annotations that are likely to be erroneous or while conducting comparative mitogenomic analyses. For users who need more information on the taxonomy, habitats, phenotypes, or life cycles of fish, MitoFish provides links to related databases. MitoFish and MitoAnnotator are freely available at http://mitofish.aori.u-tokyo.ac.jp/ (last accessed August 28, 2013); all of the data can be batch downloaded, and the annotation pipeline can be used via a web interface. © The Author 2013.

    DOI PubMed

  • Evolutionary Origin of the Scombridae (Tunas and Mackerels): Members of a Paleogene Adaptive Radiation with 14 Other Pelagic Fish Families

    Masaki Miya, Matt Friedman, Takashi P. Satoh, Hirohiko Takeshima, Tetsuya Sado, Wataru Iwasaki, Yusuke Yamanoue, Masanori Nakatani, Kohji Mabuchi, Jun G. Inoue, Jan Yde Poulsen, Tsukasa Fukunaga, Yukuto Sato, Mutsumi Nishida

    PLoS ONE   8 ( 9 ) e73535  2013年09月  [査読有り]

     概要を見る

    Uncertainties surrounding the evolutionary origin of the epipelagic fish family Scombridae (tunas and mackerels) are symptomatic of the difficulties in resolving suprafamilial relationships within Percomorpha, a hyperdiverse teleost radiation that contains approximately 17,000 species placed in 13 ill-defined orders and 269 families. Here we find that scombrids share a common ancestry with 14 families based on (i) bioinformatic analyses using partial mitochondrial and nuclear gene sequences from all percomorphs deposited in GenBank (10,733 sequences) and (ii) subsequent mitogenomic analysis based on 57 species from those targeted 15 families and 67 outgroup taxa. Morphological heterogeneity among these 15 families is so extraordinary that they have been placed in six different perciform suborders. However, members of the 15 families are either coastal or oceanic pelagic in their ecology with diverse modes of life, suggesting that they represent a previously undetected adaptive radiation in the pelagic realm. Time-calibrated phylogenies imply that scombrids originated from a deep-ocean ancestor and began to radiate after the end-Cretaceous when large predatory epipelagic fishes were selective victims of the Cretaceous-Paleogene mass extinction. We name this clade of open-ocean fishes containing Scombridae "Pelagia" in reference to the common habitat preference that links the 15 families. © 2013 Miya et al.

    DOI PubMed J-GLOBAL

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書籍等出版物

  • バイオインフォマティクスのための生命科学入門 (バイオインフォマティクスシリーズ 1)

    福永 津嵩(著), 岩切 淳一(著), 浜田 道昭(監修)( 担当: 共著)

    コロナ社  2022年07月 ISBN: 4339027316

    ASIN

講演・口頭発表等

  • RNA構造解析/比較ゲノム解析による機能未知遺伝子の機能推定

    福永津嵩  [招待有り]

    京都大学医生物学研究所 「物理学・情報科学と生物学」研究会  

    発表年月: 2024年07月

  • フィコビリソームの系統プロファイル解析により明らかになった新規ステート遷移制御遺伝子

    福永津嵩  [招待有り]

    2023年度ラン藻ゲノム交流会  

    発表年月: 2023年07月

  • 高性能系統プロファイル法による機能未知遺伝子の機能推定

    福永 津嵩

    第11回生命医薬情報学連合大会  

    発表年月: 2022年09月

  • 次世代のRNA情報学を基盤としたトランスクリプトーム解析

    福永 津嵩, 浜田 道昭

    早稲田大学 BINDS発現機能インシリコ融合ユニットキックオフシンポジウム  

    発表年月: 2022年06月

  • The inverse Potts model improves accuracy of phylogenetic profiling

    福永津嵩, 岩崎渉

    第10回生命医薬情報学連合大会  

    発表年月: 2021年09月

  • 遺伝子獲得/欠失速度の不均一性を考慮したゲノム進化史再構築

    福永津嵩, 岩崎渉

    日本進化学会第23回東京大会  

    発表年月: 2021年08月

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共同研究・競争的資金等の研究課題

  • 深層学習を用いたRNA二次構造情報解析の高速化

    日本学術振興会  科学研究費助成事業

    研究期間:

    2023年04月
    -
    2026年03月
     

    福永 津嵩

  • 大規模メタゲノムデータを用いた高精度機能未知遺伝子推定手法の開発

    日本学術振興会  科学研究費助成事業 新学術領域研究(研究領域提案型)

    研究期間:

    2022年04月
    -
    2024年03月
     

    福永 津嵩

  • リピート要素のde novo発見に基づく長鎖ノンコーディングRNAの機能の解明

    日本学術振興会  科学研究費助成事業 基盤研究(A)

    研究期間:

    2020年04月
    -
    2023年03月
     

    浜田 道昭, 小野口 真広, 福永 津嵩

  • 逆イジングモデル法に基づく機能未知な微生物遺伝子の機能推定

    日本学術振興会  科学研究費助成事業 新学術領域研究(研究領域提案型)

    研究期間:

    2020年04月
    -
    2022年03月
     

    福永 津嵩

  • 統計的論理関係解析法に基づく機能未知遺伝子の機能推定

    日本学術振興会  科学研究費助成事業 若手研究

    研究期間:

    2019年04月
    -
    2022年03月
     

    福永 津嵩

  • lncRNA-mRNAの相互作用ネットワークに基づくlncRNAの機能推定

    日本学術振興会  科研費 (新学術領域研究) 「ノンコーディングRNAネオタクソノミ」公募研究

    研究期間:

    2017年04月
    -
    2019年03月
     

    福永 津嵩

  • Computational Ethologyで解き明かす動物の群れ形成メカニズム

    日本学術振興会  科研費 (特別研究員奨励費)

    研究期間:

    2016年04月
    -
    2019年03月
     

    福永 津嵩

  • 定量的動画データ解析から迫るメダカの社会性行動

    日本学術振興会  科研費(特別研究員奨励費)

    研究期間:

    2015年04月
    -
    2016年03月
     

    福永 津嵩

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現在担当している科目

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他学部・他研究科等兼任情報

  • 理工学術院   先進理工学部

  • 理工学術院   大学院先進理工学研究科