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Computational approaches and challenges for identification and annotation of non-coding RNAs using RNA-Seq

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Abstract

Significant innovations in next-generation sequencing techniques and bioinformatics tools have impacted our appreciation and understanding of RNA. Practical RNASeq applications have evolved in conjunction with sequence technology and bioinformatic tool advances. In this review, we explained various computational resources, tools, and bioinformatics analyses advancement for small and large non-coding RNAs. These include non-coding RNAs (ncRNAs) such as piwi, micro, circular, and long ncRNAs. In addition, this article discusses future challenges, single-cell level sequencing for non-coding RNAs, and advantages of using long-read sequencing to annotate lncRNAs.

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Acknowledgements

The authors would like to acknowledge the authors of various tools discussed here in the article.

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Authors and Affiliations

  1. Institute of Microbial Technology, Council of Scientific and Industrial Research, Chandigarh, India

    Kiran Dindhoria

  2. Department of Dermatology, Columbia University Irving Medical Center, New York, NY, USA

    Isha Monga

  3. Graduate school of Medicine, University of Wollongong, Wollongong, Australia

    Amarinder Singh Thind

  4. Illawarra Health and Medical Research Institute, Wollongong, Australia

    Amarinder Singh Thind

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  1. Kiran Dindhoria
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  2. Isha Monga
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  3. Amarinder Singh Thind
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K.D, I.M, and A.S.T wrote, edited, and reviewed the original review article; KD prepared the figure and table.

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Correspondence to Amarinder Singh Thind.

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Dindhoria, K., Monga, I. & Thind, A.S. Computational approaches and challenges for identification and annotation of non-coding RNAs using RNA-Seq. Funct Integr Genomics 22, 1105–1112 (2022). https://doi.org/10.1007/s10142-022-00915-y

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