Recent Advances in Genome Editing and Bioinformatics: Addressing Challenges in Genome Editing Implementation and Genome Sequencing

被引:0
作者
Bono, Hidemasa [1 ,2 ,3 ]
机构
[1] Hiroshima Univ, Grad Sch Integrated Sci Life, 3-10-23 Kagamiyama, Higashihiroshima 7390046, Japan
[2] Hiroshima Univ, Sch Sci, Dept Biol Sci, 3-10-23 Kagamiyama, Higashihiroshima 7390046, Japan
[3] Hiroshima Univ, Genome Editing Innovat Ctr, 3-10-23 Kagamiyama, Higashihiroshima 7390046, Japan
基金
日本科学技术振兴机构;
关键词
genome editing; next-generation sequencers; genome sequencing; bioinformatics; bibliome; transcriptome; meta-analysis; pathway; database; FUNCTIONAL ANNOTATION; RNA-SEQ; GENERATION; EXPRESSION; BASE;
D O I
10.3390/ijms26073442
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Genome-editing technology has advanced significantly since the 2020 Nobel Prize in Chemistry was awarded for the development of clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated protein 9 (Cas9). While CRISPR-Cas9 has become widely used in academic research, its social implementation has lagged due to unresolved patent disputes and slower progress in gene function analysis. To address this, new approaches bypassing direct gene function analysis are needed, with bioinformatics and next-generation sequencing (NGS) playing crucial roles. NGS is essential for sequencing the genome of target species, but challenges such as data quality, genome heterogeneity, ploidy, and small individual sizes persist. Despite these issues, advancements in sequencing technologies, like PacBio high-fidelity (HiFi) long reads and high-throughput chromosome conformation capture (Hi-C), have improved genome sequencing. Bioinformatics contributes to genome editing through off-target prediction and target gene selection, both of which require accurate genome sequence information. In this review, I will give updates on the development of genome editing and bioinformatics technologies with a focus on the rapid progress in genome sequencing.
引用
收藏
页数:18
相关论文
共 57 条
[1]   WikiPathways 2024: next generation pathway database [J].
Agrawal, Ayushi ;
Balci, Hasan ;
Hanspers, Kristina ;
Coort, Susan L. ;
Martens, Marvin ;
Slenter, Denise N. ;
Ehrhart, Friederike ;
Digles, Daniela ;
Waagmeester, Andra ;
Wassink, Isabel ;
Abbassi-Daloii, Tooba ;
Lopes, Elisson N. ;
Iyer, Aishwarya ;
Acosta, Javier Millan ;
Willighagen, Lars G. ;
Nishida, Kozo ;
Riutta, Anders ;
Basaric, Helena ;
Evelo, Chris T. ;
Willighagen, Egon L. ;
Kutmon, Martina ;
Pico, Alexander R. .
NUCLEIC ACIDS RESEARCH, 2023, 52 (D1) :D679-D689
[2]  
[Anonymous], 2004, Bioinformatics: Sequence and Genome Analysis
[3]   Search-and-replace genome editing without double-strand breaks or donor DNA [J].
Anzalone, Andrew V. ;
Randolph, Peyton B. ;
Davis, Jessie R. ;
Sousa, Alexander A. ;
Koblan, Luke W. ;
Levy, Jonathan M. ;
Chen, Peter J. ;
Wilson, Christopher ;
Newby, Gregory A. ;
Raguram, Aditya ;
Liu, David R. .
NATURE, 2019, 576 (7785) :149-+
[4]   Gene Ontology: tool for the unification of biology [J].
Ashburner, M ;
Ball, CA ;
Blake, JA ;
Botstein, D ;
Butler, H ;
Cherry, JM ;
Davis, AP ;
Dolinski, K ;
Dwight, SS ;
Eppig, JT ;
Harris, MA ;
Hill, DP ;
Issel-Tarver, L ;
Kasarskis, A ;
Lewis, S ;
Matese, JC ;
Richardson, JE ;
Ringwald, M ;
Rubin, GM ;
Sherlock, G .
NATURE GENETICS, 2000, 25 (01) :25-29
[5]  
Barbosa Sebastian, 2020, Wellcome Open Res, V5, P244, DOI 10.12688/wellcomeopenres.16260.2
[6]   Systematic Functional Annotation Workflow for Insects [J].
Bono, Hidemasa ;
Sakamoto, Takuma ;
Kasukawa, Takeya ;
Tabunoki, Hiroko .
INSECTS, 2022, 13 (07)
[7]   Meta-Analysis of Oxidative Transcriptomes in Insects [J].
Bono, Hidemasa .
ANTIOXIDANTS, 2021, 10 (03) :1-12
[8]   Meta-Analysis of Hypoxic Transcriptomes from Public Databases [J].
Bono, Hidemasa ;
Hirota, Kiichi .
BIOMEDICINES, 2020, 8 (01)
[9]   Haplotype-resolved de novo assembly using phased assembly graphs with hifiasm [J].
Cheng, Haoyu ;
Concepcion, Gregory T. ;
Feng, Xiaowen ;
Zhang, Haowen ;
Li, Heng .
NATURE METHODS, 2021, 18 (02) :170-+
[10]   Accurate proteome-wide missense variant effect prediction with AlphaMissense [J].
Cheng, Jun ;
Novati, Guido ;
Pan, Joshua ;
Bycroft, Clare ;
Zemgulyte, Akvile ;
Applebaum, Taylor ;
Pritzel, Alexander ;
Wong, Lai Hong ;
Zielinski, Michal ;
Sargeant, Tobias ;
Schneider, Rosalia G. ;
Senior, Andrew W. ;
Jumper, John ;
Hassabis, Demis ;
Kohli, Pushmeet ;
Avsec, Ziga .
SCIENCE, 2023, 381 (6664) :1303-+