Understanding the expression patterns of specific mRNA isoforms is crucial for unravelling the complexities of development, homeostasis, and disease pathogenesis. Long-read single-cell RNA-sequencing (LR scRNA-seq) allows us to profile both known and novel RNA isoforms at the single-cell level, meaning we can explore how isoform expression varies, both within and between cell types.
We utilized an updated, faster, and more accurate version of our LR scRNA-seq analysis package, FLAMES, to explore isoform expression dynamics in the developing brain. To model the developing neocortex we used cortical organoids and stem cell derived cortical neurons and demonstrate that FLAMES can accurately quantify full-length RNA isoform at single cell resolution. With this information we can identify cell types, including outer radial glial progenitors and somatostatin interneuron subtypes, and map developmental trajectories of maturing and migrating early born neurons.
Our analysis identified over 178,000 unique isoforms, including more than 10,000 previously unknown. We discovered thousands of differentially expressed genes and isoforms associated with synaptic transmission, neuronal projection, axonogenesis, and neuron development, validating the expression quantification obtained from FLAMES. This included cell-type-specific isoform expression, such as in the PKM gene, which expressed different RNA isoforms in stem cell, radial glia and neuronal populations. Finally, we demonstrated that the majority of genes exhibit cell-type-specific isoform expression profiles, underscoring the critical role of isoform dynamics in shaping cellular populations.
Our findings highlight the effectiveness of LR scRNA-seq for isoform-level quantification, especially in elucidating the complexities of brain development. This methodology paves the way for transformative insights into understanding complex developmental systems and diseases.