Computing siRNA and piRNA overlap signatures

Methods Mol Biol. 2014;1173:135-46. doi: 10.1007/978-1-4939-0931-5_12.


High-throughput sequencing approaches opened the possibility to precisely map full populations of small RNAs to the genomic loci from which they originate. A bioinformatic approach revealed a strong tendency of sense and antisense piRNAs to overlap with each other over ten nucleotides and had a major role in understanding the mechanisms of piRNA biogenesis. Using similar approaches, it is possible to detect a tendency of sense and antisense siRNAs to overlap over 19 nucleotides. Thus, the so-called overlap signature which describes the tendency of small RNA to map in a specific way relative to each other has become the approach of choice to identify and characterize specific classes of small RNAs. Although simple in essence, the bioinformatic methods used for this approach are not easily accessible to biologists. Here we provide a python software that can be run on most of desktop or laptop computers to compute small RNA signatures from files of sequencing read alignments. Moreover, we describe and illustrate step by step two different algorithms at the core of the software and which were previously used in a number of works.

MeSH terms

  • Algorithms
  • Base Sequence
  • High-Throughput Nucleotide Sequencing* / methods
  • RNA, Small Interfering / genetics*
  • Software*


  • RNA, Small Interfering