Omics evidence: single nucleotide variants transmissions on chromosome 20 in liver cancer cell lines

Quanhui Wang1, Bo Wen, Tong Wang

  • 1Beijing Institute of Genomics, Chinese Academy of Sciences , No. 1 Beichen West Road, Beijing 100101, China.

Insights

This study used a transomics approach to analyze chromosome 20 (Chr.20) gene expression in liver cancer. Findings reveal efficient mRNA to protein translation, identifying potential metastasis-related single nucleotide variants (SNVs).

Area of Science:

  • Genomics
  • Proteomics
  • Cancer Biology

Background:

  • Cancer genomics identifies numerous mutations, including in chromosome 20 (Chr.20) genes, with mRNA evidence but limited protein-level validation.
  • Understanding the translation of mutated Chr.20 gene messages into proteins is crucial for cancer research.

Purpose of the Study:

  • To profile the expression status of human Chr.20 genes using a transomics strategy.
  • To investigate the efficiency of mRNA to protein translation for Chr.20 genes in liver cancer cell lines.
  • To identify potential metastasis-related single nucleotide variants (SNVs) on Chr.20.

Main Methods:

  • Employed a transomics strategy integrating transcriptome and translatome data.
  • Analyzed ribosome nascent-chain complex-bound mRNAs (RNC-mRNA) to assess translating mRNAs.
  • Utilized proteomics and targeted mass spectrometry (MRM) for protein-level validation of SNVs.

Main Results:

  • Approximately 80% of Chr.20 coding genes showed mRNA signals, while only 45% were detected at the proteome level.
  • Efficient transmission of gene information from transcriptional to translational stages was observed.
  • Over 40% of identified SNVs on Chr.20 genes were exclusive to metastatic cell lines, suggesting a role in metastasis.
  • 20 SNV sites in 16 Chr.20 genes were validated through proteomics and MRM.

Conclusions:

  • The transomics approach provides a comprehensive view of Chr.20 gene expression across transcriptional, translational, and proteomic levels.
  • Findings highlight the efficient translation of Chr.20 mRNA and identify potential metastasis-related SNVs.
  • This integrated omics data is valuable for understanding gene expression trends and discovering novel cancer markers.

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