Updated on 2022/09/26

写真a

 
ZENG, Chao
 
Affiliation
Faculty of Science and Engineering, Waseda Research Institute for Science and Engineering
Job title
Junior Researcher(Assistant Professor)
Homepage URL
https://zengchao.me

Concurrent Post

  • Faculty of Science and Engineering   School of Advanced Science and Engineering

Education

  • 2013.04
    -
    2016.03

    The University of Tokyo   Graduate School of Frontier Sciences   Department of Computational Biology and Medical Sciences  

  • 2011.04
    -
    2013.03

    Kyoto University   Graduate School of Informatics   Department of Intelligence Science and Technology  

Degree

  • The University of Tokyo   Ph.D. (Science)

  • 京都大学   修士（情報学）

Research Experience

  • 2021.04
    -
    Now

    Waseda University

  • 2018.11
    -
    2021.03

    National Institute of Advanced Industrial Science and Technology (AIST)   AIST-Waseda University Computational Bio Big-Data Open Innovation Laboratory (CBBD-OIL)   Postdoctoral Researcher

  • 2018.05
    -
    2018.10

    Waseda University   Waseda Research Institute for Science and Engineering   Research Associate

  • 2016.12
    -
    2018.04

    National Institute of Advanced Industrial Science and Technology (AIST)   AIST-Waseda University Computational Bio Big-Data Open Innovation laboratory (CBBD-OIL)   Technical Staff

  • 2016.04
    -
    2016.11

    The University of Tokyo   Graduate School of Frontier Sciences   Project Researcher

Professional Memberships

  • 　
    　
    　

    THE RNA SOCIETY OF JAPAN

  • 　
    　
    　

    JAPANESE SOCIETY FOR BIOINFORMATICS

  • 　
    　
    　

    THE MOLECULAR BIOLOGY SOCIETY OF JAPAN

 

Research Areas

  • Life, health and medical informatics

Research Interests

  • lncRNA

Papers

  • Bioinformatics Approaches for Determining the Functional Impact of Repetitive Elements on Non-coding RNAs (in press)

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

    Methods in Molecular Biology   2509  2022  [Refereed]  [Invited]

    Authorship：Lead author, Corresponding author

    DOI

  • Impact of human gene annotations on RNA-seq differential expression analysis

    Yu Hamaguchi, Chao Zeng, Michiaki Hamada

    BMC Genomics   22   730  2021.10  [Refereed]

  • Binding patterns of RNA-binding proteins to repeat-derived RNA sequences reveal putative functional RNA elements

    Masahiro Onoguchi, Chao Zeng, Ayako Matsumaru, Michiaki Hamada

    NAR Genomics and Bioinformatics   3 ( 3 )  2021.07  [Refereed]

    　View Summary

    <jats:title>Abstract</jats:title>
    <jats:p>Recent reports have revealed that repeat-derived sequences embedded in introns or long noncoding RNAs (lncRNAs) are targets of RNA-binding proteins (RBPs) and contribute to biological processes such as RNA splicing or transcriptional regulation. These findings suggest that repeat-derived RNAs are important as scaffolds of RBPs and functional elements. However, the overall functional sequences of the repeat-derived RNAs are not fully understood. Here, we show the putative functional repeat-derived RNAs by analyzing the binding patterns of RBPs based on ENCODE eCLIP data. We mapped all eCLIP reads to repeat sequences and observed that 10.75 % and 7.04 % of reads on average were enriched (at least 2-fold over control) in the repeats in K562 and HepG2 cells, respectively. Using these data, we predicted functional RNA elements on the sense and antisense strands of long interspersed element 1 (LINE1) sequences. Furthermore, we found several new sets of RBPs on fragments derived from other transposable element (TE) families. Some of these fragments show specific and stable secondary structures and are found to be inserted into the introns of genes or lncRNAs. These results suggest that the repeat-derived RNA sequences are strong candidates for the functional RNA elements of endogenous noncoding RNAs.</jats:p>

    DOI

  • Long Non-Coding RNA CRNDE Is Involved in Resistance to EGFR Tyrosine Kinase Inhibitor in EGFR-Mutant Lung Cancer via eIF4A3/MUC1/EGFR Signaling

    Satoshi Takahashi, Rintaro Noro, Masahiro Seike, Chao Zeng, Masaru Matsumoto, Akiko Yoshikawa, Shinji Nakamichi, Teppei Sugano, Mariko Hirao, Kuniko Matsuda, Michiaki Hamada, Akihiko Gemma

    International Journal of Molecular Sciences   22 ( 8 ) 4005 - 4005  2021.04  [Refereed]  [International journal]

    　View Summary

    (1) Background: Acquired resistance to epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) is an intractable problem for many clinical oncologists. The mechanisms of resistance to EGFR-TKIs are complex. Long non-coding RNAs (lncRNAs) may play an important role in cancer development and metastasis. However, the biological process between lncRNAs and drug resistance to EGFR-mutated lung cancer remains largely unknown. (2) Methods: Osimertinib- and afatinib-resistant EGFR-mutated lung cancer cells were established using a stepwise method. A microarray analysis of non-coding and coding RNAs was performed using parental and resistant EGFR-mutant non-small cell lung cancer (NSCLC) cells and evaluated by bioinformatics analysis through medical-industrial collaboration. (3) Results: Colorectal neoplasia differentially expressed (CRNDE) and DiGeorge syndrome critical region gene 5 (DGCR5) lncRNAs were highly expressed in EGFR-TKI-resistant cells by microarray analysis. RNA-protein binding analysis revealed eukaryotic translation initiation factor 4A3 (eIF4A3) bound in an overlapping manner to CRNDE and DGCR5. The CRNDE downregulates the expression of eIF4A3, mucin 1 (MUC1), and phospho-EGFR. Inhibition of CRNDE activated the eIF4A3/MUC1/EGFR signaling pathway and apoptotic activity, and restored sensitivity to EGFR-TKIs. (4) Conclusions: The results showed that CRNDE is associated with the development of resistance to EGFR-TKIs. CRNDE may be a novel therapeutic target to conquer EGFR-mutant NSCLC.

    DOI PubMed

  • Association analysis of repetitive elements and R-loop formation across species

      12 ( 3 )  2021.01  [Refereed]

    Authorship：Lead author, Corresponding author

  • Detection and Characterization of Ribosome-Associated Long Noncoding RNAs

    Chao Zeng, Michiaki Hamada

    Methods in Molecular Biology   2254   179 - 194  2021  [Refereed]  [Invited]  [International journal]

    　View Summary

    Ribosome profiling shows potential for studying the function of long noncoding RNAs (lncRNAs). We introduce a bioinformatics pipeline for detecting ribosome-associated lncRNAs (ribo-lncRNAs) from ribosome profiling data. Further, we describe a machine-learning approach for the characterization of ribo-lncRNAs based on their sequence features. Scripts for ribo-lncRNA analysis can be accessed at ( https://ribolnc.hamadalab.com/ ).

    DOI PubMed

  • RNA-Seq Analysis Reveals Localization-Associated Alternative Splicing across 13 Cell Lines

    Chao Zeng, Michiaki Hamada

    Genes   11 ( 7 ) 820  2020.07  [Refereed]  [International journal]

    Authorship：Lead author, Corresponding author

    　View Summary

    Alternative splicing, a ubiquitous phenomenon in eukaryotes, is a regulatory mechanism for the biological diversity of individual genes. Most studies have focused on the effects of alternative splicing for protein synthesis. However, the transcriptome-wide influence of alternative splicing on RNA subcellular localization has rarely been studied. By analyzing RNA-seq data obtained from subcellular fractions across 13 human cell lines, we identified 8720 switching genes between the cytoplasm and the nucleus. Consistent with previous reports, intron retention was observed to be enriched in the nuclear transcript variants. Interestingly, we found that short and structurally stable introns were positively correlated with nuclear localization. Motif analysis reveals that fourteen RNA-binding protein (RBPs) are prone to be preferentially bound with such introns. To our knowledge, this is the first transcriptome-wide study to analyze and evaluate the effect of alternative splicing on RNA subcellular localization. Our findings reveal that alternative splicing plays a promising role in regulating RNA subcellular localization.

    DOI PubMed

  • Identifying sequence features that drive ribosomal association for lncRNA.

    Chao Zeng, Michiaki Hamada

    BMC genomics   19 ( Suppl 10 ) 906 - 906  2018.12  [Refereed]  [International journal]

    　View Summary

    BACKGROUND: With the increasing number of annotated long noncoding RNAs (lncRNAs) from the genome, researchers are continually updating their understanding of lncRNAs. Recently, thousands of lncRNAs have been reported to be associated with ribosomes in mammals. However, their biological functions or mechanisms are still unclear. RESULTS: In this study, we tried to investigate the sequence features involved in the ribosomal association of lncRNA. We have extracted ninety-nine sequence features corresponding to different biological mechanisms (i.e., RNA splicing, putative ORF, k-mer frequency, RNA modification, RNA secondary structure, and repeat element). An [Formula: see text]-regularized logistic regression model was applied to screen these features. Finally, we obtained fifteen and nine important features for the ribosomal association of human and mouse lncRNAs, respectively. CONCLUSION: To our knowledge, this is the first study to characterize ribosome-associated lncRNAs and ribosome-free lncRNAs from the perspective of sequence features. These sequence features that were identified in this study may shed light on the biological mechanism of the ribosomal association and provide important clues for functional analysis of lncRNAs.

    DOI PubMed

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

    Chao Zeng, Tsukasa Fukunaga, Michiaki Hamada

    BMC Genomics   19 ( 414 )  2018.05  [Refereed]

    Authorship：Lead author, Corresponding author

  • Obstacle Avoidance and Path Planning Based on S-Type Double-Arc Insertion Method

    Xiao-tong Hu, Chao Zeng

    2010 International Conference on Computational Intelligence and Software Engineering    2010.09  [Refereed]

    Authorship：Corresponding author

    DOI

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Misc

Awards

  • Research Award for Joint Conference of Informatics In Biology, Medicine and Pharmacology

    2017.07   Japanese Society for Bioinformatics (JSBi)  

    Winner： Chao Zeng

Research Projects

  • Identification of repetitive elements involving genome regulation

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research Grant-in-Aid for Early-Career Scientists

    Project Year :

    2022.04
    -
    2025.03
     

  • RNA品質管理機構によるイントロン-エクソン化RNA生成と癌維持機構への関与

    日本学術振興会  科学研究費助成事業 挑戦的研究(萌芽)

    Project Year :

    2021.07
    -
    2023.03
     

    谷上 賢瑞

  • Identification and characterization of lncRNAs involved in genetic compensation

    日本学術振興会  科学研究費助成事業 若手研究

    Project Year :

    2020.04
    -
    2022.03
     

    曽 超

Presentations

  • Bioinformatic approaches for understanding RNA reincarnation

    Chao Zeng, Masahiro Onoguchi, Michiaki Hamada

    第43回日本分子生物学会 

    Presentation date： 2020.12

    Event date：
    2020.12
    　
    　

  • Identification and characterisation of ribosome-associated lncRNAs in human and mouse

    Chao Zeng, Michiaki Hamada

    RNA bioinformatics 

    Presentation date： 2019.09

  • Identifying sequence features that drive ribosomal association for lncRNA

    Chao Zeng, Michiaki Hamada

    The 29th International Conference on Genome Informatics(GIW2018) 

    Presentation date： 2018.12

  • A comprehensive analysis of the effects of alternative splicing on RNA localization in human

    Chao Zeng, Michiaki Hamada

    第7回生命医薬情報学連合大会(IIBMP2018) 

    Presentation date： 2018.09

  • Integrative analysis of multiple ribosome profiling datasets reveals widespread lncRNA-ribosome interaction in mammals

    Chao Zeng, Michiaki Hamada

    第6回生命医薬情報学連合大会(IIBMP2017) 

    Presentation date： 2017.09

  • Mapping and Aligning PacBio RNA-seq Data

    Chao Zeng, Hiroaki Iwata, Natsuhiro Ichinose, Tetsushi Yada, Osamu Gotoh

    The Asian Young Researchers Conference on Computational and Omics Biology (AYRCOB) 

    Presentation date： 2012.12

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