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Review

Review on the Computational Genome Annotation of Sequences Obtained by Next-Generation Sequencing

Department of Information and Communication Engineering, Myongji University, Yongin-si 17058, Gyeonggi-do, Korea
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Author to whom correspondence should be addressed.
Biology 2020, 9(9), 295; https://doi.org/10.3390/biology9090295
Received: 21 August 2020 / Revised: 13 September 2020 / Accepted: 16 September 2020 / Published: 18 September 2020
(This article belongs to the Special Issue Computational Biology)
Due to the development of high-throughput sequencing technologies, computational genome annotation of sequences has become one of the principal research area in computational biology. First, we reviewed comparative annotation tools and pipelines for both annotations of structures and functions, which enable us to comprehend gene functions and their genome evolution. Second, we compared genome annotation tools that utilize homology-based and ab initio methods depending on the similarity of sequences or the lack of evidences. Third, we explored visualization tools that aid the annotation process and stressed the need for the quality control of annotations and re-annotations, because misannotations may happen due to experimental errors or missed genes by preceding technologies. Finally, we highlighted how emerging technologies can be used in future annotations.
Next-Generation Sequencing (NGS) has made it easier to obtain genome-wide sequence data and it has shifted the research focus into genome annotation. The challenging tasks involved in annotation rely on the currently available tools and techniques to decode the information contained in nucleotide sequences. This information will improve our understanding of general aspects of life and evolution and improve our ability to diagnose genetic disorders. Here, we present a summary of both structural and functional annotations, as well as the associated comparative annotation tools and pipelines. We highlight visualization tools that immensely aid the annotation process and the contributions of the scientific community to the annotation. Further, we discuss quality-control practices and the need for re-annotation, and highlight the future of annotation. View Full-Text
Keywords: structural annotation; functional annotation; ab initio annotation; homology-based annotation structural annotation; functional annotation; ab initio annotation; homology-based annotation
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MDPI and ACS Style

Ejigu, G.F.; Jung, J. Review on the Computational Genome Annotation of Sequences Obtained by Next-Generation Sequencing. Biology 2020, 9, 295. https://doi.org/10.3390/biology9090295

AMA Style

Ejigu GF, Jung J. Review on the Computational Genome Annotation of Sequences Obtained by Next-Generation Sequencing. Biology. 2020; 9(9):295. https://doi.org/10.3390/biology9090295

Chicago/Turabian Style

Ejigu, Girum F., and Jaehee Jung. 2020. "Review on the Computational Genome Annotation of Sequences Obtained by Next-Generation Sequencing" Biology 9, no. 9: 295. https://doi.org/10.3390/biology9090295

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