Single-cell SNP analyses and interpretations based on RNA-Seq data for colon cancer research

Single-cell sequencing is useful for illustrating the cellular heterogeneities inherent in many intricate biological systems, particularly in human cancer. However, owing to the difficulties in acquiring, amplifying and analyzing single-cell genetic material, obstacles remain for single-cell diversity assessments such as single nucleotide polymorphism (SNP) analyses, rendering biological interpretations of single-cell omics data elusive. We used RNA-Seq data from single-cell and bulk colon cancer samples to analyze the SNP profiles for both structural and functional comparisons. Colon cancer-related pathways with single-cell level SNP enrichment, including the TGF-β and p53 signaling pathways, were also investigated based on both their SNP enrichment patterns and gene expression. We also detected a certain number of fusion transcripts, which may promote tumorigenesis, at the single-cell level. Based on these results, single-cell analyses not only recapitulated the SNP analysis results from the bulk samples but also detected cell-to-cell and cell-to-bulk variations, thereby aiding in early diagnosis and in identifying the precise mechanisms underlying cancers at the single-cell level.