N-terminal Proteomics Assisted Profiling of the Unexplored Translation Initiation Landscape in Arabidopsis thaliana

Abstract

Proteogenomics is an emerging research field yet lacking a uniform method of analysis. Proteogenomic studies in which N-terminal proteomics and ribosome profiling are combined, suggest that a high number of protein start sites are currently missing in genome annotations. We constructed a proteogenomic pipeline specific for the analysis of N-terminal proteomics data, with the aim of discovering novel translational start sites outside annotated protein coding regions. In summary, unidentified MS/MS spectra were matched to a specific N-terminal peptide library encompassing protein N termini encoded in the Arabidopsis thaliana genome. After a stringent false discovery rate filtering, 117 protein N termini compliant with N-terminal methionine excision specificity and indicative of translation initiation were found. These include N-terminal protein extensions and translation from transposable elements and pseudogenes. Gene prediction provided supporting protein-coding models for approximately half of the protein N termini. Besides the prediction of functional domains (partially) contained within the newly predicted ORFs, further supporting evidence of translation was found in the recently released Araport11 genome re-annotation of Arabidopsis and computational translations of sequences stored in public repositories. Most interestingly, complementary evidence by ribosome profiling was found for 23 protein N termini. Finally, by analyzing protein N-terminal peptides, an in silico analysis demonstrates the applicability of our N-terminal proteogenomics strategy in revealing protein-coding potential in species with well- and poorly-annotated genomes.

N‐terminomics reveals control of Arabidopsis seed storage proteins and proteases by the Arg/N‐end rule pathway

“…Quantitative proteomics techniques, in particular N-terminome analysis (Huesgen & Overall, 2012;Tsiatsiani et al, 2012), offer an opportunity to analyse the N-end rule in this way: enrichment of N-terminal peptides not only simplifies the proteome but also provides information about protein cleavage events that can be used to identify and validate potential N-end rule substrates (Kleifeld et al, 2010(Kleifeld et al, , 2011. The N-terminome is also a useful resource for protein annotation (Hartmann & Armengaud, 2014;Lange et al, 2014;Willems et al, 2017). Previously, we achieved efficient enrichment of Nt peptides from roots of Arg/N-end rule mutants, using terminal amine isotopic labelling of substrates (TAILS) coupled with dimethyl labelling (Zhang et al, 2015).…”

Recognition of the polycistronic nature of human genes is critical to understanding the genotype-phenotype relationship

“…With the implementation of large-scale proteogenomics and ribosome profiling studies for smORF detection, their discovery is becoming less serendipitous Delcourt et al 2017;Willems et al 2017). One of the first and most striking examples is that of the apelin (APELA smORF), 58 amino acids (aa), shown to bind apelin receptors (Pauli et al 2014).…”

“…Evidence can be inferred from large-scale detection methods, either at the DNA (conservation signatures), the translation (ribosome profiling), or the protein level (mass spectrometry). And even though there is no perfect detection method for alternative proteins, one should be cognizant of each technique's strengths and pitfalls and strive to use and adapt them to better detect the entire proteomic landscape of a cell or tissue (Boekhorst et al 2011;Aspden et al 2014;Calviello et al 2016;Hellens et al 2016;Ma et al 2016;Pueyo et al 2016a;Delcourt et al 2017;Hsu and Benfey 2017;Willems et al 2017 Evidence at the genomic level An indirect but potentially powerful piece of evidence of a protein's expression is its conservation signature. Conservation signatures are already used to distinguish functional ORFs in current ORF prediction algorithms .…”

“…Recently, the development of new techniques or the optimization of existing ones has allowed for large-scale detection of alternative proteins and a more in-depth view of a cell proteomic landscape (Boekhorst et al 2011;Aspden et al 2014;Calviello et al 2016;Hellens et al 2016;Ma et al 2016;Pueyo et al 2016a;Delcourt et al 2017;Hsu and Benfey 2017;Willems et al 2017). Three detection methods-ribosome profiling, proteogenomics, and conservation signatures-have been used to identify likely translated and functional alternative ORFs, as further discussed later in this review.…”

Integration of large-scale multi-omic datasets: A protein-centric view

“…Another study used a specific proteomic approach that enriched for the N-terminal ends of proteins that are often missed in both RNA sequencing and proteomics experiments. Examining the plant Arabidopsis, integration of Nterminal proteomics with transcript data and information on ribosome-mRNA interactions identified 117 novel translation start sites outside the annotated protein regions [36*]. …”