bims-micpro Biomed News
on Discovery and characterization of microproteins
Issue of 2022‒03‒13
three papers selected by
Thomas Farid Martínez
University of California, Irvine

  1. 3 Biotech. 2022 Mar;12(3): 76
      Gene prediction is a laborious and time-consuming task. The advancement of sequencing technologies and bioinformatics tools, coupled with accelerated rate of ribosome profiling and mass spectrometry development, have made identification of small open reading frames (sORFs) (< 100 codons) in various plant genomes possible. The past 50 years have seen sORFs being isolated from many organisms. However, to date, a comprehensive sORF annotation pipeline is as yet unavailable, hence, addressed in our review. Here, we also provide current information on classification and functions of plant sORFs and their potential applications in crop improvement programs.
    Keywords:  Hormone-like peptides; SEP; Small open reading frame; Small peptide; sORFs
  2. J Proteome Res. 2022 Mar 07.
      Advanced analytic techniques, such as ribosome profiling and mass spectrometry, as well as improved bioinformatics technology, have promoted the field of genome annotation forward and have identified thousands of likely coding short open reading frames (sORFs) in the human genome. The discovery of sORFs and their products allows us to realize that the complexity of the human genome is far greater than previously assumed. Here, we provide a review of human micropeptides encoded by various transcripts such as mitochondrial rRNAs, long noncoding RNAs, circular RNAs, upstream of mRNAs, and so on.
    Keywords:  human genome; micropeptides; sORFs
  3. J Vis Exp. 2022 Feb 18.
      Identification of open reading frames (ORFs), especially those encoding small peptides and being actively translated under specific physiological contexts, is critical for comprehensive annotations of context-dependent translatomes. Ribosome profiling, a technique for detecting the binding locations and densities of translating ribosomes on RNA, offers an avenue to rapidly discover where translation is occurring at the genome-wide scale. However, it is not a trivial task in bioinformatics to efficiently and comprehensively identify the translating ORFs for ribosome profiling. Described here is an easy-to-use package, named RiboCode, designed to search for actively translating ORFs of any size from distorted and ambiguous signals in ribosome profiling data. Taking our previously published dataset as an example, this article provides step-by-step instructions for the entire RiboCode pipeline, from preprocessing of the raw data to interpretation of the final output result files. Furthermore, for evaluating the translation rates of the annotated ORFs, procedures for visualization and quantification of ribosome densities on each ORF are also described in detail. In summary, the present article is a useful and timely instruction for the research fields related to translation, small ORFs, and peptides.