Evidence map›Paper›PMID 38934545›Full record

ArticlemSystems2024

Comparison of the full-length sequence and sub-regions of 16S rRNA gene for skin microbiome profiling.

Han Zhang, Xiang Wang, Anqi Chen, Shilin Li, Ruiyang Tao, Kaiqin Chen, Ping Huang, Liliang Li, Jiang Huang, Chengtao Li and 1 more

Abstract readComparative Study
In one paragraph

Article in mSystems, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

  1. Review
  2. Article
  3. Microbial genomics · 2026
    Article
  4. Article
  5. Article
  6. UMI-guided single locus sequence typing method for phylotypingFrontiers in cellular and infection microbiology · 2026
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Review
  16. Review
  17. Article
  18. Comparative Analyses of Gut Microbiomes inEcology and evolution · 2025
    Article
  19. 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

11 authors.

Han Zhang *Institute of Forensic Science, Fudan University, Shanghai, China.
Xiang Wang *Institute of Cancer Stem Cell, Cancer Center, Dalian Medical University, Dalian, Liaoning, China.
Anqi ChenInstitute of Forensic Science, Fudan University, Shanghai, China.
Shilin LiInstitute of Forensic Science, Fudan University, Shanghai, China.
Ruiyang TaoShanghai Key Laboratory of Forensic Medicine, Shanghai Forensic Service Platform, Ministry of Justice, Academy of Forensic Science, Shanghai, China.
Kaiqin ChenKey Laboratory of Cell Engineering of Guizhou Province, Clinical Stem Cell Research Institute, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou, China.
Ping HuangInstitute of Forensic Science, Fudan University, Shanghai, China.
Liliang LiDepartment of Forensic Medicine, School of Basic Medical Sciences, Fudan University, Shanghai, China.
Jiang HuangThe Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, Guizhou, China.
Chengtao LiInstitute of Forensic Science, Fudan University, Shanghai, China.ORCID 0000-0001-6852-9144
Suhua ZhangInstitute of Forensic Science, Fudan University, Shanghai, China.ORCID 0000-0002-3984-9728

Funding

MOST | National Natural Science Foundation of China (NSFC) 82072123MOST | National Natural Science Foundation of China (NSFC) 82371896
6 · The paper itself

Abstract

The skin microbiome plays a pivotal role in human health by providing protective and functional benefits. Furthermore, its inherent stability and individual specificity present novel forensic applications. These aspects have sparked considerable research enthusiasm among scholars across various fields. However, the selection of specific 16S rRNA hypervariable regions for skin microbiome studies is not standardized and should be validated through extensive research tailored to different research objectives and targeted bacterial taxa. Notably, third-generation sequencing (TGS) technology leverages the full discriminatory power of the 16S gene and enables more detailed and accurate microbial community analyses. Here, we conducted full-length 16S sequencing of 141 skin microbiota samples from multiple human anatomical sites using the PacBio platform. Based on this data, we generated derived 16S sub-region data through an

Indexed as

BacteriaMicrobiotaRNA, Ribosomal, 16SSkinDNA, BacterialHigh-Throughput Nucleotide SequencingHumansPhylogenySequence Analysis, DNADNA, BacterialRNA, Ribosomal, 16S16S variable regionfull-length sequencingin silico experimentskin microbiota

Identifiers

PMID38934545
PMCPMC11264597

What OpenQuestion holds

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Registered trials

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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.