Classification of Long Noncoding RNAs by k-mer Content

Jessime M Kirk; Daniel Sprague; J Mauro Calabrese

doi:10.1007/978-1-0716-1158-6_4

Classification of Long Noncoding RNAs by k-mer Content

Methods Mol Biol. 2021:2254:41-60. doi: 10.1007/978-1-0716-1158-6_4.

Authors

Jessime M Kirk^{1

2

3

4}, Daniel Sprague^{1

3

5

6}, J Mauro Calabrese^{7

8

9

10}

Affiliations

¹ Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
² Curriculum in Bioinformatics and Computational Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
³ Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
⁴ Invitae Corporation, San Francisco, CA, USA.
⁵ Curriculum in Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
⁶ Flagship Pioneering, Boston, MA, USA.
⁷ Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. jmcalabr@med.unc.edu.
⁸ Curriculum in Bioinformatics and Computational Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. jmcalabr@med.unc.edu.
⁹ Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. jmcalabr@med.unc.edu.
¹⁰ Curriculum in Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. jmcalabr@med.unc.edu.

Abstract

K-mer based comparisons have emerged as powerful complements to BLAST-like alignment algorithms, particularly when the sequences being compared lack direct evolutionary relationships. In this chapter, we describe methods to compare k-mer content between groups of long noncoding RNAs (lncRNAs), to identify communities of lncRNAs with related k-mer contents, to identify the enrichment of protein-binding motifs in lncRNAs, and to scan for domains of related k-mer contents in lncRNAs. Our step-by-step instructions are complemented by Python code deposited in Github. Though our chapter focuses on lncRNAs, the methods we describe could be applied to any set of nucleic acid sequences.

Keywords: Communities; Domain; LncRNA; Long noncoding RNA; Louvain algorithm; Networks; Protein-binding motif; Sequence alignment; Unsupervised clustering; k-mer.

MeSH terms

Algorithms
Cluster Analysis
Computational Biology / methods*
Nucleotide Motifs / genetics
Protein Binding
RNA, Long Noncoding / classification*
RNA, Long Noncoding / genetics*

Substances

RNA, Long Noncoding

Grants and funding

R01 GM121806/GM/NIGMS NIH HHS/United States