Dataset Information

Missing proteins identified from the haploid cell lines: HAP1 and KBM-7

ABSTRACT: Chromosome-centric Human Proteomic Project (C-HPP) aims at identifying and characterizing protein products encoded from all protein-coding genes of human chromosomes. As evident in the recent nature papers, it is possible that those missing proteins may be low abundant in many cell types or expressed only in a few cell types. In order to identify missing proteins, we focused on extensively unexplored cell lines(HAP1, KBM-7).

INSTRUMENT(S): LTQ Orbitrap Velos

ORGANISM(S): Homo Sapiens (ncbitaxon:9606)

SUBMITTER: Min-Sik Kim

PROVIDER: MSV000083952 | MassIVE | Mon Jun 10 14:13:00 BST 2019

SECONDARY ACCESSION(S): PXD006614

REPOSITORIES: MassIVE

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Publications

Proteogenomic Analysis to Identify Missing Proteins from Haploid Cell Lines.

Lee Seung-Eun SE Song JongKeon J Bösl Korbinian K Müller André C AC Vitko Dijana D Bennett Keiryn L KL Superti-Furga Giulio G Pandey Akhilesh A Kandasamy Richard K RK Kim Min-Sik MS

Proteomics 20180401 8

Chromosome-centric Human Proteome Project aims at identifying and characterizing protein products encoded from all human protein-coding genes. As of early 2017, 19 837 protein-coding genes have been annotated in the neXtProt database including 2691 missing proteins that have never been identified by mass spectrometry. Missing proteins may be low abundant in many cell types or expressed only in a few cell types in human body such as sperms in testis. In this study, we performed expression proteom ...[more]

PMID: 29474001

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Project description:Droplet based 3’ single-cell RNA-sequencing (scRNA-seq) methods have proved transformational in characterizing cellular diversity and generating valuable hypotheses throughout biology1,2. Here we outline a common problem with 3’ scRNA-seq datasets where genes that have been documented to be expressed with other methods, are either completely missing or are dramatically under-represented thereby compromising discovery of cell types, states and genetic mechanisms. We show that this problem stems from three main sources of sequencing read loss: (1) reads mapping immediately 3’ to known gene boundaries due to poor 3’ UTR annotation; (2) intronic reads stemming from unannotated exons or pre-mRNA; (3) discarded reads due to gene overlaps3. Each of these issues impacts detection of thousands of genes even in well characterized mouse and human genomes rendering downstream analysis either partially or fully blind to their expression. We outline a simple three step solution to recover the missing gene expression data that entails compiling a basic pre-mRNA reference to retrieve intronic reads4, resolving gene collision derived read loss through removal of readthrough and premature start transcripts, and redefining 3’ gene boundaries to capture false intergenic reads. We demonstrate with mouse brain and human peripheral blood datasets that this approach dramatically increases the amount of sequencing data included in downstream analysis revealing 20 - 50% more genes per cell and incorporates 15-20% more sequencing reads than with standard solutions5. These improvements reveal previously missing biologically relevant cell types, states and marker genes in the mouse brain and human blood profiling data. Finally, we provide simple algorithmic implementation of these solutions that can be deployed to both thoroughly as well as poorly annotated genomes. Our results demonstrate that optimizing the sequencing read mapping step can significantly improve the analysis resolution as well as biological insight from scRNA-seq. Moreover, this approach warrants a fresh look at preceding analyses of this popular and scalable cellular profiling technology.

Dataset Information

Missing proteins identified from the haploid cell lines: HAP1 and KBM-7

Publications

Proteogenomic Analysis to Identify Missing Proteins from Haploid Cell Lines.

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