Volume 96, April 2024, 101255Author links open overlay panel, , Abstract

Single-cell technologies have transformed biomedical research over the last decade, opening up new possibilities for understanding cellular heterogeneity, both at the genomic and transcriptomic level. In addition, more recent developments of spatial transcriptomics technologies have made it possible to profile cells in their tissue context. In parallel, there have been substantial advances in sequencing technologies, and the third generation of methods are able to produce reads that are tens of kilobases long, with error rates matching the second generation short reads. Long reads technologies make it possible to better map large genome rearrangements and quantify isoform specific abundances. This further improves our ability to characterize functionally relevant heterogeneity. Here, we show how researchers have begun to combine single-cell, spatial transcriptomics, and long-read technologies, and how this is resulting in powerful new approaches to profiling both the genome and the transcriptome. We discuss the achievements so far, and we highlight remaining challenges and opportunities.

Section snippetsBackground

Sequencing technologies have had a transformative impact on molecular biology, and they have allowed for quantitative characterization of many different aspects of cells. Since the invention of Sanger sequencing in 1977 (Sanger et al., 1977), there have been several significant milestones which have greatly expanded the use of these methods beyond reading DNA. Three advances that have had lasting impact are single-cell RNA-seq (scRNA-seq), spatial transcriptomics, and long-read sequencing. In

Combinations of single-cell, spatial, and long-read technologies

There is a wide variety of biological questions that could be studied when single-cell and long-read technologies are combined (Wen and Tang 2022). When applied to RNA, long-read sequencing can enable refined classification of the transcriptional state, in particular by facilitating isoform quantification. Applied to DNA, it can facilitate the identification of complex structural variants and lineage tracing. Now the combination of these technologies has also made it possible to profile such

Perspective

Today, there are several complementary technologies available for both single-cell and long-read studies. We have drafted a decision tree (Fig. 2) to facilitate the selection of a suitable combination of technologies; Table 1, Table 2, Table 3, Table 4, Table 5, Table 6, Table 7 summarize the key technical characteristics of methods mentioned in each category and Table 8 provides details of the current bioinformatic tools. The options available have complementary strengths, and one should

Web references

Pacific Biosciences, 2023, Revivo system for long-read sequencing. https://www.pacb.com/revio/Accessed November 15, 2023.

10X Genomics, 2023, Visium spatial gene expression. https://www.10xgenomics.com/products/spatial-gene-expression Accessed November 15, 2023.

10X, Genomics, 2023. Which 10X Assays are compatible with long-read sequencing applications https://kb.10xgenomics.com/hc/en-us/articles/10618695456781-Which-10x-Assays-are-compatible-with-long-read-sequencing-applications- Accessed

CRediT authorship contribution statement

Chengwei Ulrika Yuan: Conceptualization, Investigation, Writing – original draft, Writing – review & editing. Fu Xiang Quah: Conceptualization, Investigation, Writing – original draft, Writing – review & editing. Martin Hemberg: Conceptualization, Investigation, Supervision, Writing – review & editing.

Acknowledgements

CUY was funded by Cambridge Commonwealth European and International Trust, FXQ was funded by the Wellcome Trust and Cambridge Commonwealth European and International Trust, and MH was supported by funds from the Evergrande Center.

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