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SCIENCE CHINA Life Sciences, Volume 63 , Issue 7 : 986-995(2020) https://doi.org/10.1007/s11427-019-1677-8

Understanding the proteome encoded by “non-coding RNAs”: new insights into human genome

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  • ReceivedNov 29, 2019
  • AcceptedMar 12, 2020
  • PublishedApr 20, 2020

Abstract

A great number of non-coding RNAs (ncRNAs) account for the majority of the genome. The translation of these ncRNAs has been noted but seriously underestimated due to both technological and theoretical limitations. Based on the development of ribosome profiling (Ribo-seq), full length translating RNA analysis (RNC-seq) and mass spectrometry technology, more and more ncRNAs are being found to be translated in different organism, and some of them can produce functional peptides. While recently, not only individual new functional proteins, but also a new proteome have been experimentally discovered to be encoded by endogenous lncRNAs and circRNAs. These new proteins are of biological significance, suggesting the connection of the translation of ncRNAs to human physiology and diseases. Therefore, an in-depth and systematic understanding of the coding capabilities of ncRNAs is necessary for basic biology and medicine. In this review, we summarize the advances in the field of discovering this new proteome, i.e. “ncRNA-coded” proteins.


Funded by

the National Key Research and Development Program(2017YFA0505100,2017YFA0505001,2018YFC0910202)

the National Natural and Science Foundation of China(81372135,to,TW;,81322028,31300649,to,GZ;,31570828,31770888,to,Q.Y.H.)


Acknowledgment

This work was supported by the National Key Research and Development Program (2017YFA0505100, 2017YFA0505001, 2018YFC0910202) and the National Natural and Science Foundation of China (81372135 to TW; 81322028 and 31300649 to GZ; 31570828 and 31770888 to Q.Y.H.).


Interest statement

The author(s) declare that they have no conflict of interest.


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  • Figure 1

    The difference between RNC-seq and Ribo-seq. A, Schematic workflow of RNC-seq and Ribo-seq. B, RNC-seq with long reads can eliminate the small RNA fragment contaminants but Ribo-seq cannot. C and D, RNC-seq’s advantages in detecting splice junctions. E, RNC-seq’s advantages in detecting translating circRNAs.

  • Figure 2

    Hypothesis of new protein origin.

  • Table 1   Table 1 Commonly used human genome annotation databases based on algorithmic modelling and classification

    Databases name

    Website

    Algorithm

    RefSeq

    https://www.ncbi.nlm.nih.gov/genome/?term=human

    Splign

    UniProtKB/Swiss-Pro

    https://www.uniprot.org/

    Sequence similarity and homology

    Ensembl

    http://www.ensembl.org/info/data/ftp/index.html

    Havana(VEGA)

    NONCODE

    http://www.noncode.org/

    BLAST, CNCI

  • Table 2   Table 2 Typical features of PE1 protein-coding genes, new protein-coding genes and non-coding genes

    Typical features

    Gene class

    PE1 protein-coding genes

    New protein-coding genes

    Non-coding genes

    RNA length

    Longer

    Shorter

    Shorter

    ORF length

    Longer

    Shorter

    /

    Exon count

    More

    Fewer

    Fewer

    ORF exon count

    Multiple exons

    Mostly single exon

    /

    Expression level

    Higher

    Lower

    Lower

    Isoelectric point (protein)

    Lower

    Higher

    /

    Amino acid compositions

    Normal

    More positively charged, less negatively charged

    /

    Stability (protein)

    More stable

    Less stable

    /

    Evolutionary conservation

    Conserved

    Poorly conserved

    Poorly conserved

  • Table 3   Table 3 Functions of human new proteins

    Gene name

    Protein length (aa)

    Function

    Literature

    linear lncRNA

    ESRG

    105

    A novel biomarker for intracranial germinoma and embryonal carcinoma

    (Wanggou et al., 2012)

    LINC00961

    90

    Regulates mTORC1 and muscle regeneration

    (Matsumoto et al., 2017)

    NOBODY

    68

    Involved in mRNA processing and negatively regulates P-body association

    (D’Lima et al., 2017)

    Minion

    84

    Controls cell fusion and muscle formation

    (Zhang et al., 2017)

    HOXB-AS3

    53

    Suppresses colon cancer growth

    (Huang et al., 2017)

    LINC00116

    56

    A mitochondrial that enhances fatty acid β-Oxidation

    (Makarewich et al., 2018)

    CASIMO1

    83

    Controls cell proliferation and interacts with squalene epoxidase modulating lipid droplet formation

    (Polycarpou-Schwarz et al., 2018)

    UBAP1-AST6

    NCBP2-AS2

    117

    99

    Promote cell proliferation and clone formation

    Suppresses oncogenic signaling in hepatocellular carcinoma cells

    (Lu et al., 2019)

    (Xu et al., 2019)

    circRNA

     

    circ-ZNF609

    251

    Functions in myogenesis

    (Legnini et al., 2017)

    circ-SHPRH

    146

    Suppresses glioma tumorigenesis

    (Zhang et al., 2018a)

    LINC-PINT

    87

    Suppresses oncogenic transcriptional elongation in glioblastoma

    (Zhang et al., 2018b)

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