Elucidating the cellular dynamics of the brain with single-cell RNA sequencing

Abstract

Single-cell RNA-sequencing (scRNA-seq) has emerged in recent years as a breakthrough technology to understand RNA metabolism at cellular resolution. In addition to allowing new cell types and states to be identified, scRNA-seq can permit cell-type specific differential gene expression changes, pre-mRNA processing events, gene regulatory networks and single-cell developmental trajectories to be uncovered. More recently, a new wave of multi-omic adaptations and complementary spatial transcriptomics workflows have been developed that facilitate the collection of even more holistic information from individual cells. These developments have unprecedented potential to provide penetrating new insights into the basic neural cell dynamics and molecular mechanisms relevant to the nervous system in both health and disease. In this review we discuss this maturation of single-cell RNA-sequencing over the past decade, and review the different adaptations of the technology that can now be applied both at different scales and for different purposes. We conclude by highlighting how these methods have already led to many exciting discoveries across neuroscience that have furthered our cellular understanding of the neurological disease.

Retrotransposons as Drivers of Mammalian Brain Evolution

“…To what extent, and according to which species-specific paths, brain functionality in mammals relies on retrotransposon exaptation will become increasingly clear as the particularly challenging aspects of retrotransposon molecular biology become easier to address. Major challenges include: (i) the unambiguous identification of expressed retrotransposon loci, together with the related issue of insertional and internal sequence polymorphisms [ 192 ], which becomes highly relevant when studies of retrotransposon impact are to be conducted at the population level; (ii) the implementation of a single-cell perspective while addressing the expression and genomic impact of retrotransposons, which appears particularly relevant in the case of brain biology given the extremely diverse specialization of neurons [ 193 , 244 ]; (iii) the experimental assessment of cis -regulatory roles of retrotransposons by means of their systematic perturbation, e.g., through CRISPR-based approaches [ 120 ].…”

Advancements in Genomic and Behavioral Neuroscience Analysis for the Study of Normal and Pathological Brain Function

“…However, similar to scRNA-Seq, spatially-resolved transcriptomics generates large datasets, is prone to technical bias and noise, and assumes a one-to-one relationship between spots and cells. While an individual spot may be roughly the size of a single cell, it may overlap multiple cells, especially with the highly-branched nature of neurons and glia ( Cardona-Alberich et al, 2021 ; Close et al, 2021 ). As technology develops, scalability and resolution will increase ( Rao et al, 2021 ).…”

Understanding Mammalian Hair Follicle Ecosystems by Single-Cell RNA Sequencing

“…The location information of cells is very important for the study of the cell fate regulation mechanism and the cell lineage generation process. Therefore, although the scRNA-seq dataset tells cells what happened and the molecular relationship between them, we do not know whether the cells obtained by sequencing are closely linked or far apart in the original sample, or whether organ development is related to specific tissue structure or two specific cell distances [ 89 ]. Although the known marker genes were used to identify cell types, the spatial background of tissue genes was obtained by restoring scRNA-seq from the spatial localization of known primitive cells.…”

“…Space transcriptomics will become an important supplement to scRNA-seq in the future [ 89 ]. Therefore, the application of ST technology in the study of spatial heterogeneity of hair follicles still has great room for improvement and application.…”