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Related Concept Videos

Proteomics01:33

Proteomics

8.4K
A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term...
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SMAP is a pipeline for sample matching in proteogenomics.

Ling Li1, Mingming Niu2, Alyssa Erickson1

  • 1Department of Biology, University of North Dakota, Grand Forks, ND, 58202, USA.

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|February 9, 2022
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Sample mix-ups in proteogenomics studies are common. A new pipeline, Sample Matching in Proteogenomics (SMAP), uses mass spectrometry data to verify sample identity, ensuring accurate human disease research.

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Area of Science:

  • Genomics and Proteomics
  • Human Disease Research
  • Bioinformatics

Background:

  • Proteogenomics integrates genomics and proteomics for deeper human disease understanding.
  • Sample mix-ups are a significant challenge in complex proteogenomics workflows.
  • Ensuring data integrity is crucial for reliable research findings.

Purpose of the Study:

  • To develop and validate a computational pipeline for verifying sample identity in proteogenomics.
  • To address the pervasive issue of sample mix-up in large-scale studies.
  • To enhance the accuracy and reliability of proteogenomic data analysis.

Main Methods:

  • Developed Sample Matching in Proteogenomics (SMAP) pipeline.
  • Inferred sample-specific protein-coding variants from quantitative mass spectrometry (MS) data.
  • Aligned proteomic and genomic samples using two discriminant scores.

Main Results:

  • SMAP accurately matches proteomic and genomic samples with ≥20% genotype data.
  • Applied to the PsychENCODE BrainGVEX dataset, SMAP corrected 54 samples (19%).
  • Corrections were validated using ribosome profiling and ATAC-seq data.

Conclusions:

  • SMAP is an effective tool for sample verification in large-scale MS-based proteogenomics.
  • The pipeline ensures data integrity, crucial for advancing human disease research.
  • SMAP is publicly available, facilitating its adoption in the scientific community.