Targeted single-cell RNA sequencing of transcription factors facilitates biological insights from human cell experimental models

Single-cell RNA sequencing (scRNA-seq) is a widely used method for identifying cell types and trajectories in biologically heterogeneous samples, but it is limited in its detection and quantification of lowly expressed genes. This results in missing important biological signals, such as the expression of key transcription factors (TFs) driving cellular differentiation. We show that targeted sequencing of ∼1000 TFs (scCapture-seq) in iPSC-derived neuronal cultures greatly improves the biological information garnered from scRNA-seq. Increased TF resolution enhanced cell type identification, developmental trajectories, and gene regulatory networks. This allowed us to resolve differences among neuronal populations, which were generated in two different laboratories using the same differentiation protocol. ScCapture-seq improved TF-gene regulatory network inference and thus identified divergent patterns of neurogenesis into either excitatory cortical neurons or inhibitory interneurons. Furthermore, scCapture-seq revealed a role for of retinoic acid signaling in the developmental divergence between these different neuronal populations. Our results show that TF targeting improves the characterization of human cellular models and allows identification of the essential differences between cellular populations, which would otherwise be missed in traditional scRNA-seq. scCapture-seq TF targeting represents a cost-effective enhancement of scRNA-seq, which could be broadly applied to improve scRNA-seq resolution

Targeted single-cell RNA sequencing of transcription factors facilitates biological insights from human cell experimental models

Single-cell RNA sequencing (scRNA-seq) is a widely used method for identifying cell types and trajectories in biologically heterogeneous samples, but it is limited in its detection and quantification of lowly expressed genes. This results in missing important biological signals, such as the expression of key transcription factors (TFs) driving cellular differentiation. We show that targeted sequencing of ∼1000 TFs (scCapture-seq) in iPSC-derived neuronal cultures greatly improves the biological information garnered from scRNA-seq. Increased TF resolution enhanced cell type identification, developmental trajectories, and gene regulatory networks. This allowed us to resolve differences among neuronal populations, which were generated in two different laboratories using the same differentiation protocol. ScCapture-seq improved TF-gene regulatory network inference and thus identified divergent patterns of neurogenesis into either excitatory cortical neurons or inhibitory interneurons. Furthermore, scCapture-seq revealed a role for of retinoic acid signaling in the developmental divergence between these different neuronal populations. Our results show that TF targeting improves the characterization of human cellular models and allows identification of the essential differences between cellular populations, which would otherwise be missed in traditional scRNA-seq. scCapture-seq TF targeting represents a cost-effective enhancement of scRNA-seq, which could be broadly applied to improve scRNA-seq resolution

Brain matters: unveiling the distinct contributions of region, age, and sex to glia diversity and CNS function

The myelinated white matter tracts of the central nervous system (CNS) are essential for fast transmission of electrical impulses and are often differentially affected in human neurodegenerative diseases across CNS region, age and sex. We hypothesize that this selective vulnerability is underpinned by physiological variation in white matter glia. Using single nucleus RNA sequencing of human post-mortem white matter samples from the brain, cerebellum and spinal cord and subsequent tissue-based validation we found substantial glial heterogeneity with tissue region: we identified region-specific oligodendrocyte precursor cells (OPCs) that retain developmental origin markers into adulthood, distinguishing them from mouse OPCs. Region-specific OPCs give rise to similar oligodendrocyte populations, however spinal cord oligodendrocytes exhibit markers such as SKAP2 which are associated with increased myelin production and we found a spinal cord selective population particularly equipped for producing long and thick myelin sheaths based on the expression of genes/proteins such as HCN2. Spinal cord microglia exhibit a more activated phenotype compared to brain microglia, suggesting that the spinal cord is a more pro-inflammatory environment, a difference that intensifies with age. Astrocyte gene expression correlates strongly with CNS region, however, astrocytes do not show a more activated state with region or age. Across all glia, sex differences are subtle but the consistent increased expression of protein-folding genes in male donors hints at pathways that may contribute to sex differences in disease susceptibility. These findings are essential to consider for understanding selective CNS pathologies and developing tailored therapeutic strategies

Oligodendroglial Heterogeneity in Neuropsychiatric Disease

Oligodendroglia interact with neurons to support their health and maintain the normal functioning of the central nervous system (CNS). Human oligodendroglia are a highly heterogeneous population characterised by distinct developmental origins and regional differences, as well as variation in cellular states, as evidenced by recent analysis at single-nuclei resolution. Increasingly, there is evidence to suggest that the highly heterogeneous nature of oligodendroglia might underpin their role in a range of CNS disorders, including those with neuropsychiatric symptoms. Understanding the role of oligodendroglial heterogeneity in this group of disorders might pave the way for novel approaches to identify biomarkers and develop treatments

Associations between alcohol use and accelerated biological ageing

Data supporting the manuscript "Associations between alcohol use and accelerated biological ageing". Specifically: Genome Wide Association Study of brain age.Bøstrand, Sunniva MK; Vaher, Kadi; De Nooij, Laura; Harris, Matthew A; Cole, James H; Cox, Simon R; Marioni, Riccardo E; McCartney, Daniel L; Walker, Rosie M; McIntosh, Andrew M; Evans, Kathryn L; Whalley, Heather C; Wootton, Robyn E; Clarke, Toni-Kim. (2020). Associations between alcohol use and accelerated biological ageing, [dataset]. University of Edinburgh. Centre for Clinical Brain Sciences. https://doi.org/10.7488/ds/2956