SMOOTH-seq: single-cell genome sequencing of human cells on a third-generation sequencing platform

Fan, Xiaoying; Yang, Cheng; Li, Wen; Bai, Xiuzhen; Zhou, Xin; Xie, Haoling; Wen, Lu; Tang, Fuchou

doi:10.1186/s13059-021-02406-y

Cited by 65 publications

(55 citation statements)

References 45 publications

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“…The low allelic frequencies of subclonal SVs can present a substantial challenge for both accurate detection and probabilistic assignment of breakpoints to subclones using bulk sequencing methods, where our ability to detect SVs is impaired by sequencing a pooled sample from a heterogeneous population [96]. Singlecell WGS has greatly helped to accurately determine the clonality of SVs [97][98][99][100]. Regardless, challenges in establishing clonality will inevitably result in a substantial underestimation of the proportion of SVs that are subclonal.…”

Section: Structural Variation As a Critical Dimension In Tumour Evolu...mentioning

confidence: 99%

Unravelling the tumour genome: The evolutionary and clinical impacts of structural variants in tumourigenesis

Hamdan

Ewing

2022

The Journal of Pathology

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Structural variants (SVs) represent a major source of aberration in tumour genomes. Given the diversity in the size and type of SVs present in tumours, the accurate detection and interpretation of SVs in tumours is challenging. New classes of complex structural events in tumours are discovered frequently, and the definitions of the genomic consequences of complex events are constantly being refined. Detailed analyses of short-read whole-genome sequencing (WGS) data from large tumour cohorts facilitate the interrogation of SVs at orders of magnitude greater scale and depth. However, the inherent technical limitations of short-read WGS prevent us from accurately detecting and investigating the impact of all the SVs present in tumours. The expanded use of long-read WGS will be critical for improving the accuracy of SV detection, and in fully resolving complex SV events, both of which are crucial for determining the impact of SVs on tumour progression and clinical outcome. Despite the present limitations, we demonstrate that SVs play an important role in tumourigenesis. In particular, SVs contribute significantly to late-stage tumour development and to intratumoural heterogeneity. The evolutionary trajectories of SVs represent a window into the clonal dynamics in tumours, a comprehensive understanding of which will be vital for influencing patient outcomes in the future. Recent findings have highlighted many clinical applications of SVs in cancer, from early detection to biomarkers for treatment response and prognosis. As the methods to detect and interpret SVs improve, elucidating the full breadth of the complex SV landscape and determining how these events modulate tumour evolution will improve our understanding of cancer biology and our ability to capitalise on the utility of SVs in the clinical management of cancer patients.

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Section: Structural Variation As a Critical Dimension In Tumour Evolu...mentioning

confidence: 99%

Unravelling the tumour genome: The evolutionary and clinical impacts of structural variants in tumourigenesis

Hamdan

Ewing

2022

The Journal of Pathology

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“…Cancer cells can rapidly adapt to changes in the tumor micro-environment by amplifying the oncogenes on their eccDNA ( 61 ). Numerous experimental methods have been developed to detect eccDNA including Circle-Seq based on next-generation sequencing ( 62 ) and SMOOTH-seq based on third-generation sequencing platforms ( 63 ). Several computational methods have been developed to analyze eccDNAs including AmpliconArchitect ( 64 ), ECdetect ( 6 ) to identify eccDNAs from whole-genome sequencing data, and Circle-Map ( 65 ) and Circle_finder ( 66 ) to detect eccDNAs in Circle-seq and ATAC-seq data, respectively.…”

Section: Discussion and Perspectivesmentioning

confidence: 99%

CircleBase: an integrated resource and analysis platform for human eccDNAs

Zhao

Shi

Ruan

et al. 2021

Nucleic Acids Research

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Rapid advances in high-throughput sequencing technologies have led to the discovery of thousands of extrachromosomal circular DNAs (eccDNAs) in the human genome. Loss-of-function experiments are difficult to conduct on circular and linear chromosomes, as they usually overlap. Hence, it is challenging to interpret the molecular functions of eccDNAs. Here, we present CircleBase (http://circlebase.maolab.org), an integrated resource and analysis platform used to curate and interpret eccDNAs in multiple cell types. CircleBase identifies putative functional eccDNAs by incorporating sequencing datasets, computational predictions, and manual annotations. It classifies them into six sections including targeting genes, epigenetic regulations, regulatory elements, chromatin accessibility, chromatin interactions, and genetic variants. The eccDNA targeting and regulatory networks are displayed by informative visualization tools and then prioritized. Functional enrichment analyses revealed that the top-ranked cancer cell eccDNAs were enriched in oncogenic pathways such as the Ras and PI3K-Akt signaling pathways. In contrast, eccDNAs from healthy individuals were not significantly enriched. CircleBase provides a user-friendly interface for searching, browsing, and analyzing eccDNAs in various cell/tissue types. Thus, it is useful to screen for potential functional eccDNAs and interpret their molecular mechanisms in human cancers and other diseases.

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“…Except transcriptome information, single-cell genome sequencing also provides new perspectives to our understanding of tumors, such as SNS, 40 SCI-seq, 10 SMOOTH-seq. 41 In general, four steps have been implemented to acquire single-cell genomic sequencing data, including cell isolation, whole-genome amplification (WGA), interrogation of WGA products, and error correction. 42 Due to only two copies of genomic DNA in human cells, WGA is one of the challenges for single-cell genome sequencing.…”

Section: Overviewmentioning

confidence: 99%

High-throughput single-сell sequencing in cancer research

Jia

Chu

Zheng³

et al. 2022

Sig Transduct Target Ther

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With advances in sequencing and instrument technology, bioinformatics analysis is being applied to batches of massive cells at single-cell resolution. High-throughput single-cell sequencing can be utilized for multi-omics characterization of tumor cells, stromal cells or infiltrated immune cells to evaluate tumor progression, responses to environmental perturbations, heterogeneous composition of the tumor microenvironment, and complex intercellular interactions between these factors. Particularly, single-cell sequencing of T cell receptors, alone or in combination with single-cell RNA sequencing, is useful in the fields of tumor immunology and immunotherapy. Clinical insights obtained from single-cell analysis are critically important for exploring the biomarkers of disease progression or antitumor treatment, as well as for guiding precise clinical decision-making for patients with malignant tumors. In this review, we summarize the clinical applications of single-cell sequencing in the fields of tumor cell evolution, tumor immunology, and tumor immunotherapy. Additionally, we analyze the tumor cell response to antitumor treatment, heterogeneity of the tumor microenvironment, and response or resistance to immune checkpoint immunotherapy. The limitations of single-cell analysis in cancer research are also discussed.

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SMOOTH-seq: single-cell genome sequencing of human cells on a third-generation sequencing platform

Cited by 65 publications

References 45 publications

Unravelling the tumour genome: The evolutionary and clinical impacts of structural variants in tumourigenesis

Unravelling the tumour genome: The evolutionary and clinical impacts of structural variants in tumourigenesis

CircleBase: an integrated resource and analysis platform for human eccDNAs

High-throughput single-сell sequencing in cancer research

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