Single-cell and long-read sequencing to enhance modelling of splicing and cell-fate determination

Abstract

Single-cell sequencing technologies have revolutionised the life sciences and biomedical research. Single-cell sequencing provides high-resolution data on cell heterogeneity, allowing high-fidelity cell type identification, and lineage tracking. Computational algorithms and mathematical models have been developed to make sense of the data, compensate for errors and simulate the biological processes, which has led to breakthroughs in our understanding of cell differentiation, cell-fate determination and tissue cell composition. The development of long-read (a.k.a. third-generation) sequencing technologies has produced powerful tools for investigating alternative splicing, isoform expression (at the RNA level), genome assembly and the detection of complex structural variants (at the DNA level). In this review, we provide an overview of the recent advancements in single-cell and long-read sequencing technologies, with a particular focus on the computational algorithms that help in correcting, analysing, and interpreting the resulting data. Additionally, we review some mathematical models that use single-cell and long-read sequencing data to study cell-fate determination and alternative splicing, respectively. Moreover, we highlight the emerging opportunities in modelling cell-fate determination that result from the combination of single-cell and long-read sequencing technologies.

Keywords: Alternative splicing; Isoform expression; Mathematical modelling; Pesudotemopral trajectory inference; RNA velocity; Transcriptome diversity.

Fig. 1

Schema of alternative splicing. DNA encoding a gene is transcribed into pre-mRNA typically consisting of multiple exons. Alternative splicing leads to different mature mRNA transcripts (isoforms) including possible retained introns and different combinations of exons, which, after translation, produce multiple protein isoforms with potentially different functions. Created with BioRender.com.

Fig. 2

Schema of mRNA synthesis and degradation. DNA is transcribed into pre-mRNA with a rate, α(t), at time t. The nascent RNA molecule (pre-mRNA) is further processed, via splicing, into mature mRNA with a rate, β(t), at time t. Ultimately, the mRNA molecule undergoes degradation with a rate, γ(t), at time t. Created with BioRender.com.