Evidence map›Paper›PMID 34193237›Full record

ArticleGenome biology2021

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

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

Open access · goldAbstract read
In one paragraph

Article in Genome biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 69 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
69citing papers in PubMed, 1 pooled it
8.0field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

69 citing papers in PubMed, 1 synthesis or guideline pooled it, 102 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Review
  5. Review
  6. Article
  7. Review
  8. Review
  9. Review
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Long and Accurate: How HiFi Sequencing is Transforming Genomics.Genomics, proteomics & bioinformatics · 2025
    Review
  16. Article
  17. Article
  18. Review
  19. Review
  20. scEccDNAdb: an integrated single-cell eccDNA resource for human and mouse.Database : the journal of biological databases and curation · 2024
    Article

9 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 4 institutions in 1 country.

Xiaoying Fan *Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou, 510005, China.
Cheng Yang *Beijing Advanced Innovation Center for Genomics (ICG), School of Life Sciences, Department of General Surgery, Third Hospital, Peking University, Beijing, 100871, China.
Wen Li *Beijing Advanced Innovation Center for Genomics (ICG), School of Life Sciences, Department of General Surgery, Third Hospital, Peking University, Beijing, 100871, China.
Xiuzhen BaiBeijing Advanced Innovation Center for Genomics (ICG), School of Life Sciences, Department of General Surgery, Third Hospital, Peking University, Beijing, 100871, China.
Xin ZhouBeijing Advanced Innovation Center for Genomics (ICG), School of Life Sciences, Department of General Surgery, Third Hospital, Peking University, Beijing, 100871, China.
Haoling XieBeijing Advanced Innovation Center for Genomics (ICG), School of Life Sciences, Department of General Surgery, Third Hospital, Peking University, Beijing, 100871, China.
Lu WenBeijing Advanced Innovation Center for Genomics (ICG), School of Life Sciences, Department of General Surgery, Third Hospital, Peking University, Beijing, 100871, China.
Fuchou TangBeijing Advanced Innovation Center for Genomics (ICG), School of Life Sciences, Department of General Surgery, Third Hospital, Peking University, Beijing, 100871, China. tangfuchou@pku.edu.cn.
Peking University · CNCenter for Life Sciences · CNGuangzhou Regenerative Medicine and Health Guangdong Laboratory · CNMinistry of Education of the People's Republic of China · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

There is no effective way to detect structure variations (SVs) and extra-chromosomal circular DNAs (ecDNAs) at single-cell whole-genome level. Here, we develop a novel third-generation sequencing platform-based single-cell whole-genome sequencing (scWGS) method named SMOOTH-seq (single-molecule real-time sequencing of long fragments amplified through transposon insertion). We evaluate the method for detecting CNVs, SVs, and SNVs in human cancer cell lines and a colorectal cancer sample and show that SMOOTH-seq reliably and effectively detects SVs and ecDNAs in individual cells, but shows relatively limited accuracy in detection of CNVs and SNVs. SMOOTH-seq opens a new chapter in scWGS as it generates high fidelity reads of kilobases long.

Indexed as

Genome, HumanBase SequenceChromosome MappingColorectal NeoplasmsDNA, CircularDNA Copy Number VariationsDNA Transposable ElementsHEK293 CellsHigh-Throughput Nucleotide SequencingHumansK562 CellsPolymorphism, Single NucleotideSingle-Cell AnalysisWhole Genome SequencingDNA, CircularDNA Transposable ElementsExtra-chromosomal circular DNAsSingle-cell genome sequencingSingle-molecule sequencingStructure variantsThird-generation sequencing platform

Identifiers

PMID34193237
PMCPMC8247186
OpenAlexW3177325667

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.