bims-micpro Biomed News
on Discovery and characterization of microproteins
Issue of 2020‒10‒25
two papers selected by
Thomas Martinez
Salk Institute for Biological Studies


  1. Cancer Cell Int. 2020 ;20 506
    Ye M, Zhang J, Wei M, Liu B, Dong K.
      Increasing evidence has indicated that long noncoding RNAs (lncRNAs) play various important roles in the development of cancers. The widespread applications of ribosome profiling and ribosome nascent chain complex sequencing revealed that some short open reading frames of lncRNAs have micropeptide-coding potential. The resulting micropeptides have been shown to participate in N6-methyladenosine modification, tumor angiogenesis, cancer metabolism, and signal transduction. This review summarizes current information regarding the reported roles of lncRNA-encoded micropeptides in cancer, and explores the potential clinical value of these micropeptides in the development of anti-cancer drugs and prognostic tumor biomarkers.
    Keywords:  Cancer; Coding potential; Micropeptide; Open reading frame; lncRNA
    DOI:  https://doi.org/10.1186/s12935-020-01589-x
  2. Nucleic Acids Res. 2020 Oct 19. pii: gkaa823. [Epub ahead of print]
    Huang W, Ling Y, Zhang S, Xia Q, Cao R, Fan X, Fang Z, Wang Z, Zhang G.
      TransCirc (https://www.biosino.org/transcirc/) is a specialized database that provide comprehensive evidences supporting the translation potential of circular RNAs (circRNAs). This database was generated by integrating various direct and indirect evidences to predict coding potential of each human circRNA and the putative translation products. Seven types of evidences for circRNA translation were included: (i) ribosome/polysome binding evidences supporting the occupancy of ribosomes onto circRNAs; (ii) experimentally mapped translation initiation sites on circRNAs; (iii) internal ribosome entry site on circRNAs; (iv) published N-6-methyladenosine modification data in circRNA that promote translation initiation; (v) lengths of the circRNA specific open reading frames; (vi) sequence composition scores from a machine learning prediction of all potential open reading frames; (vii) mass spectrometry data that directly support the circRNA encoded peptides across back-splice junctions. TransCirc provides a user-friendly searching/browsing interface and independent lines of evidences to predicte how likely a circRNA can be translated. In addition, several flexible tools have been developed to aid retrieval and analysis of the data. TransCirc can serve as an important resource for investigating the translation capacity of circRNAs and the potential circRNA-encoded peptides, and can be expanded to include new evidences or additional species in the future.
    DOI:  https://doi.org/10.1093/nar/gkaa823