Background: Early single-cell RNA-seq (scRNA-seq) studies suggested that it was unusual to see more than one isoform being produced from a gene in a single cell, even when multiple isoforms were detected in matched bulk RNA-seq samples. However, these studies generally did not consider the impact of dropouts or isoform quantification errors, potentially confounding the results of these analyses. Results: In this study, we take a simulation based approach in which we explicitly account for dropouts and isoform quantification errors. We use our simulations to ask to what extent it is possible to study alternative splicing using scRNA-seq. Additionally, we ask what limitations must be overcome to make splicing analysis feasible. We find that the high rate of dropouts associated with scRNA-seq is a major obstacle to studying alternative splicing. In mice and other well-established model organisms, the relatively low rate of isoform quantification errors poses a lesser obstacle to splicing analysis. We find that different models of isoform choice meaningfully change our simulation results. Conclusions: To accurately study alternative splicing with single-cell RNA-seq, a better understanding of isoform choice and the errors associated with scRNA-seq is required. An increase in the capture efficiency of scRNA-seq would also be beneficial. Until some or all of the above are achieved, we do not recommend attempting to resolve isoforms in individual cells using scRNA-seq.
BackgroundEarly single-cell RNA-seq (scRNA-seq) studies suggested that it was unusual to see more than one isoform being produced from a gene in a single cell, even when multiple isoforms were detected in matched bulk RNA-seq samples. However, these studies generally did not consider the impact of dropouts or isoform quantification errors, potentially confounding the results of these analyses.
Innate lymphoid cells (ILCs) are rare tissue-resident “helper” lymphocytes that do not express diversified antigen receptors. Type 3 ILCs (ILC3s) are an important class of these cells enriched in the respiratory and intestinal mucosa, where they regulate inflammation and mucosal homeostasis. To gain insight into the cis-regulatory circuitries underlying ILC3 function, we used high-resolution Capture Hi-C to profile promoter-anchored chromosomal contacts in human primary ILC3s. Combining significant interaction detection with the Activity-By-Contact approach adapted to Capture Hi-C, we reveal a multitude of contacts between promoters and distal regulatory elements and obtain evidence for distinct regulatory wiring of alternative promoters. We find that promoter-interacting regions in ILC3s are enriched for genetic variants associated with multiple immune diseases. Focusing on Crohn’s disease (CD), in which ILC3s are established mediators, we used a Bayesian approach that incorporates multivariate fine-mapping to link CD-associated genetic variants with putative target genes. We identify known and previously unimplicated genes in conferring genetic risk of CD through activity in ILC3s. This includes the CLN3gene that is mutated in the neurodegenerative disorder Batten disease. UsingCln3mutant mice, we show thatCLN3is a putative negative regulator of IL-17 production in an inflammatory subset of ILC3s. This finding suggests a functional role forCLN3in ILC3 biology, with mechanistic implications for both Crohn’s and Batten diseases.
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