Reference-free Analysis of scRNA-seq Data Reveals Elevated rRNA and mtRNA Transcription during Neurogenesis in Axolotl

Analysis of single-cell RNA-seq data is typically performed on a gene expression matrix estimated by aligning reads to a reference transcriptome. However, this approach is difficult to apply to organisms with no or incomplete reference transcriptomes. In addition, events deviating from the reference remain undetected. Here we present a reference-free method to analyze single-cell RNA-seq data based on k-mers. We assess the performance of our method on a metastatic renal cell carcinoma dataset and find that it is largely able to capture differentially expressed genes. We then analyze a recently generated dataset to study neurogenesis in Axolotl and observe increased levels of transcription of rRNA and mtRNA during neurogenesis as well as a miRNA with previously predicted links to neuronal development. We also detect lncRNAs and intron retention in heart disease-related genes in diseased cardiomyocytes in an analysis of a congenital heart disease dataset.