Dataset Information

D283 MED, a cell line derived from peritoneal metastatic medulloblastoma — a good choice for missing protein discovery

ABSTRACT: Our goal is the identification of more and more missing proteins from cancer cell lines. This project focuses on D283 med and U-118mg cell lines which contribute to 12 missing protein identification.

INSTRUMENT(S): Orbitrap Fusion Lumos

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

SUBMITTER: Siqi Liu

PROVIDER: MSV000087678 | MassIVE | Mon Jun 21 23:47:00 BST 2021

SECONDARY ACCESSION(S): PXD021482

REPOSITORIES: MassIVE

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Publications

D283 Med, a Cell Line Derived from Peritoneal Metastatic Medulloblastoma: A Good Choice for Missing Protein Discovery.

Zhang Yuanliang Y Zhang Keren K Bu Fanyu F Hao Piliang P Yang Huanming H Liu Siqi S Ren Yan Y

Journal of proteome research 20201119 12

Since the Chromosome-Centric Human Proteome Project (C-HPP) was launched in 2010, many techniques have been adopted for the discovery of missing proteins (MPs). Because of these efforts, only 1481 MPs remained as of July 2020; however, by relying only on technique optimization, researchers have reached a bottleneck in MP discovery. Protein expression is tissue- or cell-type-dependent. The tissues of the human testis and brain have been reported to harbor a large number of tissue-specific genes a ...[more]

PMID: 33210925

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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

D283 MED, a cell line derived from peritoneal metastatic medulloblastoma — a good choice for missing protein discovery

Publications

D283 Med, a Cell Line Derived from Peritoneal Metastatic Medulloblastoma: A Good Choice for Missing Protein Discovery.

Similar Datasets

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