smORFer

smORFer detects small open reading frames (smORFs) encoding proteins of 50 amino acids or fewer in prokaryotic genomes by integrating genome sequencing, ribosome profiling (Ribo-Seq), and translation initiation stalling sequencing (TIS-seq) to empirically annotate translated smORFs.


Key Features:

  • smORF detection: Identifies smORFs encoding proteins of 50 amino acids or fewer in prokaryotic genomes.
  • Data integration: Integrates genome sequencing, ribosome profiling (Ribo-Seq), and translation initiation stalling sequencing (TIS-seq).
  • RPF-based mapping: Uses ribosome-protected fragments (RPFs) from Ribo-Seq to precisely locate actively translated ORFs on mRNA.
  • Initiation site identification: Leverages TIS-seq, which blocks ribosomes at the start codon, to sequence protected fragments and identify translation initiation sites.
  • Sequence and translation pattern analysis: Considers structural features of genetic sequences and in-frame translation patterns to evaluate candidate smORFs.
  • Fourier transform scoring: Applies a Fourier transform to convert sequence and translation parameters into a measurable score for selecting putative smORFs.
  • Prokaryotic genome challenges addressed: Accounts for polycistronic messages, overlapping ORFs, leaderless translation, and non-canonical initiation sites.

Scientific Applications:

  • Coding sequence annotation: Empirical annotation of coding sequences, specifically smORFs, in prokaryotic genomes.
  • Translation initiation mapping: Precise identification of translation initiation sites using TIS-seq and Ribo-Seq data.
  • Discovery of non-canonical translation: Detection of leaderless translation and non-canonical initiation events in prokaryotes.
  • Functional small protein studies: Enabling discovery and study of small proteins implicated in physiological processes.

Methodology:

Integrates genome sequencing, Ribo-Seq (RPF mapping), and TIS-seq (ribosome stalling at start codons); analyzes structural sequence features and in-frame translation patterns; and employs a Fourier transform to convert parameters into a score for selecting putative smORFs.

Topics

Details

License:
Not licensed
Cost:
Free of charge
Tool Type:
command-line tool
Operating Systems:
Linux
Programming Languages:
R, Shell, Perl
Added:
10/14/2021
Last Updated:
10/15/2021

Operations

Publications

Bartholomäus A, Kolte B, Mustafayeva A, Goebel I, Fuchs S, Benndorf D, Engelmann S, Ignatova Z. smORFer: a modular algorithm to detect small ORFs in prokaryotes. Nucleic Acids Research. 2021;49(15):e89-e89. doi:10.1093/nar/gkab477. PMID:34125903. PMCID:PMC8421149.

PMID: 34125903
PMCID: PMC8421149
Funding: - Deutsche Forschungsgemeinschaft: GRK PROCOMPAS, IG 73/16-1

Documentation