bims-micpro 2022-10-09 papers

Issue of 2022‒10‒09
two papers selected by
Thomas Farid Martínez
University of California, Irvine

Genomics Proteomics Bioinformatics. 2022 Sep 29. pii: S1672-0229(22)00124-3. [Epub ahead of print]

Newfound Coding Potential of Transcripts Unveils Missing Members of Human Protein Communities.

Sébastien Leblanc, Marie A Brunet, Jean-François Jacques, Amina M Lekehal, Andréa Duclos, Alexia Tremblay, Alexis Bruggeman-Gascon, Sondos Samandi, Mylène Brunelle, Alan A Cohen, Michelle S Scott, Xavier Roucou.

Recent proteogenomic approaches have led to the discovery that regions of the transcriptome previously annotated as non-coding regions [i.e., untranslated regions (UTRs), open reading frames overlapping annotated coding sequences in a different reading frame, and non-coding RNAs] frequently encode proteins (termed alternative proteins). This suggests that previously identified protein-protein interaction networks are partially incomplete since alternative proteins are not present in conventional protein databases. Here we used the proteogenomic resource OpenProt and a combined spectrum- and peptide-centric analysis for the re-analysis of a high-throughput human network proteomics dataset thereby revealing the presence of 261 alternative proteins in the network. We found 19 genes encoding both an annotated (reference) and an alternative protein interacting with each other. Of the 117 alternative proteins encoded by pseudogenes, 38 are direct interactors of reference proteins encoded by their respective parental gene. Finally, we experimentally validate several interactions involving alternative proteins. These data improve the blueprints of the human protein-protein interaction network and suggest functional roles for hundreds of alternative proteins.

Keywords: Affinity purification mass spectrometry; Alternative proteins; Protein network; Protein–protein interactions; Pseudogenes

DOI: https://doi.org/10.1016/j.gpb.2022.09.008

Plant Methods. 2022 Oct 04. 18(1): 115

A custom library construction method for super-resolution ribosome profiling in Arabidopsis.

Hsin-Yen Larry Wu, Polly Yingshan Hsu.

BACKGROUND: Ribosome profiling, also known as Ribo-seq, is a powerful technique to study genome-wide mRNA translation. It reveals the precise positions and quantification of ribosomes on mRNAs through deep sequencing of ribosome footprints. We previously optimized the resolution of this technique in plants. However, several key reagents in our original method have been discontinued, and thus, there is an urgent need to establish an alternative protocol.RESULTS: Here we describe a step-by-step protocol that combines our optimized ribosome footprinting in plants with available custom library construction methods established in yeast and bacteria. We tested this protocol in 7-day-old Arabidopsis seedlings and evaluated the quality of the sequencing data regarding ribosome footprint length, mapped genomic features, and the periodic properties corresponding to actively translating ribosomes through open resource bioinformatic tools. We successfully generated high-quality Ribo-seq data comparable with our original method.
CONCLUSIONS: We established a custom library construction method for super-resolution Ribo-seq in Arabidopsis. The experimental protocol and bioinformatic pipeline should be readily applicable to other plant tissues and species.

Keywords: 3-nt periodicity; Ribo-seq; Ribosome footprint; Ribosome profiling; Translatome

DOI: https://doi.org/10.1186/s13007-022-00947-2