Evidence map›Paper›PMID 30333049›Full record

ArticleGenome biology2018

Holo-Seq: single-cell sequencing of holo-transcriptome.

Zhengyun Xiao, Guo Cheng, Yang Jiao, Chen Pan, Ran Li, Danmei Jia, Jing Zhu, Chao Wu, Min Zheng, Junling Jia

Abstract read
In one paragraph

Article in Genome biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
–field-weighted citation impact
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

28 citing papers in PubMed.

  1. Review
  2. Article
  3. MicroRNAs and Their Profiling via Single-Cell Sequencing Technologies.Methods in molecular biology (Clifton, N.J.) · 2026
    Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Transcriptome and Temporal Transcriptome Analyses in Single Cells.International journal of molecular sciences · 2024
    Review
  11. Article
  12. Review
  13. Beyond the Code: Noncoding RNAs in Skin Wound Healing.Cold Spring Harbor perspectives in biology · 2022
    Article
  14. Article
  15. Article
  16. Review
  17. Single-cell quantification of a broad RNA spectrum reveals unique noncoding patterns associated with cell types and states.Proceedings of the National Academy of Sciences of the United States of America · 2021
    Article
  18. Article
  19. Review
  20. Article
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

10 authors.

Zhengyun XiaoLife Sciences Institute and Innovation Center for Cell Signaling Network, Zhejiang University, Hangzhou, 310058, Zhejiang, People's Republic of China.
Guo ChengLife Sciences Institute and Innovation Center for Cell Signaling Network, Zhejiang University, Hangzhou, 310058, Zhejiang, People's Republic of China.
Yang JiaoLife Sciences Institute and Innovation Center for Cell Signaling Network, Zhejiang University, Hangzhou, 310058, Zhejiang, People's Republic of China.
Chen PanLife Sciences Institute and Innovation Center for Cell Signaling Network, Zhejiang University, Hangzhou, 310058, Zhejiang, People's Republic of China.
Ran LiLife Sciences Institute and Innovation Center for Cell Signaling Network, Zhejiang University, Hangzhou, 310058, Zhejiang, People's Republic of China.
Danmei JiaLife Sciences Institute and Innovation Center for Cell Signaling Network, Zhejiang University, Hangzhou, 310058, Zhejiang, People's Republic of China.
Jing ZhuBeijing Ming-tian Genetics Ltd., Beijing, 100070, People's Republic of China.
Chao WuLife Sciences Institute and Innovation Center for Cell Signaling Network, Zhejiang University, Hangzhou, 310058, Zhejiang, People's Republic of China. wuchao1984@zju.edu.cn.
Min ZhengCollaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang University, Hangzhou, 310003, Zhejiang, People's Republic of China. minzheng@zju.edu.cn.
Junling JiaLife Sciences Institute and Innovation Center for Cell Signaling Network, Zhejiang University, Hangzhou, 310058, Zhejiang, People's Republic of China. junlingjia@zju.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Current single-cell RNA-seq approaches are hindered by preamplification bias, loss of strand of origin information, and the inability to observe small-RNA and mRNA dual transcriptomes. Here, we introduce a single-cell holo-transcriptome sequencing (Holo-Seq) that overcomes all three hurdles. Holo-Seq has the same quantitative accuracy and uniform coverage with a complete strand of origin information as bulk RNA-seq. Most importantly, Holo-Seq can simultaneously observe small RNAs and mRNAs in a single cell. Furthermore, we acquire small RNA and mRNA dual transcriptomes of 32 human hepatocellular carcinoma single cells, which display the genome-wide super-enhancer activity and hepatic neoplasm kinetics of these cells.

Indexed as

Single-Cell AnalysisAnimalsHEK293 CellsHumansIntronsMaleMCF-7 CellsMice, Inbred C57BLMiddle AgedRNA, AntisenseRNA, MessengerSequence Analysis, RNATranscriptomeRNA, AntisenseRNA, MessengerAnti-sense transcriptLiver cancermRNA-SeqSingle cellSmall-RNA-SeqSuper-enhancerTotal RNA-Seq

Identifiers

PMID30333049
PMCPMC6193298

What OpenQuestion holds

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LicenceCC BY
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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.