Characterization of Loss-of-Imprinting in Breast Cancer at the Cellular Level by Integrating Single-Cell Full-Length Transcriptome with Bulk RNA-Seq Data

Biomolecules. 2024 Dec 14;14(12):1598. doi: 10.3390/biom14121598.

Abstract

Genomic imprinting, the parent-of-origin-specific gene expression, plays a pivotal role in growth regulation and is often dysregulated in cancer. However, screening for imprinting is complicated by its cell-type specificity, which bulk RNA-seq cannot capture. On the other hand, large-scale single-cell RNA-seq (scRNA-seq) often lacks transcript-level detail and is cost-prohibitive. Here, we address this gap by integrating bulk RNA-seq with full-length transcript scRNA-seq to investigate imprinting dynamics in breast cancer. By analyzing scRNA-seq data from 486 cancer cells across subtypes, we identified multiple SNPs in imprinted genes, including HM13, MEST (PEG1), SNHG14 and PEG10, showing consistent biallelic expression. Bulk RNA-seq, however, revealed that this biallelic expression arises from transcript-specific imprinting, rather than loss-of-imprinting (LOI). The imprinted SNPs identified in bulk RNA-seq predominantly demonstrate proper monoallelic expression in scRNA-seq. As a clear exception, an HER2+ breast cancer sample exhibited distinct LOI of MEST. Previous bulk RNA-seq-based observations about MEST LOI in breast cancer could not exclude a non-cancer cell impact, but our results validate that MEST LOI is cancer-specific. This study demonstrates the complementary utility of bulk and scRNA-seq in imprinting studies, confirming MEST LOI as a genuine event in breast cancer.

Keywords: Genomic imprinting; breast cancer; bulk RNA-seq; loss-of-imprinting (LOI); single-cell RNA-seq.

MeSH terms

  • Breast Neoplasms* / genetics
  • Breast Neoplasms* / pathology
  • Cell Line, Tumor
  • Female
  • Gene Expression Regulation, Neoplastic
  • Genomic Imprinting* / genetics
  • Humans
  • Polymorphism, Single Nucleotide* / genetics
  • RNA-Seq / methods
  • Sequence Analysis, RNA / methods
  • Single-Cell Analysis* / methods
  • Transcriptome* / genetics