The Integration of Data from Different Long-Read Sequencing Platforms Enhances Proteoform Characterization in Arabidopsis

Abstract

The increasing availability of massive omics data requires improving the quality of reference databases and their annotations. The combination of full-length isoform sequencing (Iso-Seq) with short-read transcriptomics and proteomics has been successfully used for increasing proteoform characterization, which is a main ongoing goal in biology. However, the potential of including Oxford Nanopore Technologies Direct RNA Sequencing (ONT-DRS) data has not been explored. In this paper, we analyzed the impact of combining Iso-Seq- and ONT-DRS-derived data on the identification of proteoforms in Arabidopsis MS proteomics data. To this end, we selected a proteomics dataset corresponding to senescent leaves and we performed protein searches using three different protein databases: AtRTD2 and AtRTD3, built from the homonymous transcriptomes, regarded as the most complete and up-to-date available for the species; and a custom hybrid database combining AtRTD3 with publicly available ONT-DRS transcriptomics data generated from Arabidopsis leaves. Our results show that the inclusion and combination of long-read sequencing data from Iso-Seq and ONT-DRS into a proteogenomic workflow enhances proteoform characterization and discovery in bottom-up proteomics studies. This represents a great opportunity to further investigate biological systems at an unprecedented scale, although it brings challenges to current protein searching algorithms.

Postmortem Muscle Proteome Characteristics of Silver Carp (Hypophthalmichthys molitrix): Insights from Full-Length Transcriptome and Deep 4D Label-Free Proteomic

“…The integration of transcriptomics data from different longread sequencing platforms into a proteomics study can enhance proteome characterization. 33,34 Accordingly, the predictions of the coding sequence (CDS) from FL transcripts can provide longer, more complete, and accurate protein sequences, which is helpful to enhance the accuracy and reliability of MS/MS identification. Therefore, the first objective of the present study was to provide an advanced FL transcriptome database of postmortem silver carp dorsal muscles to date by using PacBio long-read high-throughput sequencing technology.…”

“…Moreover, the merit of long-read sequencing can also be confirmed in proteogenomic analysis. The integration of transcriptomics data from different long-read sequencing platforms into a proteomics study can enhance proteome characterization. , Accordingly, the predictions of the coding sequence (CDS) from FL transcripts can provide longer, more complete, and accurate protein sequences, which is helpful to enhance the accuracy and reliability of MS/MS identification.…”