Discovering Novel Bacterial Small RNA by RNA-seq Analysis Toolkit ANNOgesic

Chin-Hsien Tai; Deborah Hinton; Sung-Huan Yu

doi:10.1007/978-1-0716-3565-0_4

Discovering Novel Bacterial Small RNA by RNA-seq Analysis Toolkit ANNOgesic

Methods Mol Biol. 2024:2741:35-69. doi: 10.1007/978-1-0716-3565-0_4.

Authors

Chin-Hsien Tai¹, Deborah Hinton², Sung-Huan Yu^{3

4}

Affiliations

¹ Laboratory of Molecular Biology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
² Gene Expression and Regulation Section, Laboratory of Biochemistry and Genetics, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, USA.
³ Institute of Precision Medicine, National Sun Yat-sen University, Kaohsiung, Taiwan. silasysh@g-mail.nsysu.edu.tw.
⁴ School of Medicine, College of Medicine, National Sun Yat-sen University, Kaohsiung, Taiwan. silasysh@g-mail.nsysu.edu.tw.

PMID: 38217648
DOI: 10.1007/978-1-0716-3565-0_4

Abstract

ANNOgesic is an RNA-seq analysis pipeline that can detect sRNAs and many other genomic features in bacteria and archaea. In addition to listing sRNA candidates, ANNOgesic also generates various formats of data files for visual examination and downstream experimental design. Based on validations from previous studies, the sRNA predictions are accurate and reliable. In this chapter, we outline the sRNA detection algorithm, important parameters used, step-by-step execution, and data interpretation with a B. pertussis study as an example. Following those procedures, novel sRNA can be revealed by ANNOgesic.

Keywords: ANNOgesic; Computational predictions; RNA-seq; Small RNAs; genome annotation.

MeSH terms

Computational Biology / methods
Gene Expression Regulation, Bacterial
Genome, Bacterial
Genomics
RNA, Bacterial* / genetics
RNA, Small Untranslated* / genetics
RNA-Seq
Sequence Analysis, RNA / methods

Substances

RNA, Bacterial
RNA, Small Untranslated