Evidence map›Paper›PMID 36824325›Full record

ArticleGigaByte (Hong Kong, China)2021

Efficient and stable metabarcoding sequencing data using a DNBSEQ-G400 sequencer validated by comprehensive community analyses.

Xiaohuan Sun, Yue-Hua Hu, Jingjing Wang, Chao Fang, Jiguang Li, Mo Han, Xiaofang Wei, Haotian Zheng, Xiaoqing Luo, Yangyang Jia and 3 more

Abstract read
In one paragraph

Article in GigaByte (Hong Kong, China), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

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  7. Consolidation ofStudies in mycology · 2022
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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

13 authors.

Xiaohuan SunBGI-Shenzhen, Shenzhen 518083, China.ORCID https://orcid.org/0000-0002-3411-5995
Yue-Hua HuCAS Key Laboratory of Tropical Forest Ecology, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Mengla 666303, China.
Jingjing WangMGI, BGI-Shenzhen, Shenzhen 518083, China.
Chao FangBGI-Shenzhen, Shenzhen 518083, China.ORCID https://orcid.org/0000-0002-6830-3337
Jiguang LiMGI, BGI-Shenzhen, Shenzhen 518083, China.
Mo HanBGI-Shenzhen, Shenzhen 518083, China.ORCID https://orcid.org/0000-0002-4404-297X
Xiaofang WeiMGI, BGI-Shenzhen, Shenzhen 518083, China.
Haotian ZhengBGI-Shenzhen, Shenzhen 518083, China.
Xiaoqing LuoBGI-Shenzhen, Shenzhen 518083, China.
Yangyang JiaBGI-Shenzhen, Shenzhen 518083, China.
Meihua GongMGI, BGI-Shenzhen, Shenzhen 518083, China.
Liang XiaoBGI-Shenzhen, Shenzhen 518083, China.
Zewei SongBGI-Shenzhen, Shenzhen 518083, China.ORCID https://orcid.org/0000-0002-0606-6946

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Metabarcoding is a widely used method for fast characterization of microbial communities in complex environmental samples. However, the selction of sequencing platform can have a noticeable effect on the estimated community composition. Here, we evaluated the metabarcoding performance of a DNBSEQ-G400 sequencer developed by MGI Tech using 16S and internal transcribed spacer (ITS) markers to investigate bacterial and fungal mock communities, as well as the ITS2 marker to investigate the fungal community of 1144 soil samples, with additional technical replicates. We show that highly accurate sequencing of bacterial and fungal communities is achievable using DNBSEQ-G400. Measures of diversity and correlation from soil metabarcoding showed that the results correlated highly with those of different machines of the same model, as well as between different sequencing modes (single-end 400 bp and paired-end 200 bp). Moderate, but significant differences were observed between results produced with different sequencing platforms (DNBSEQ-G400 and MiSeq); however, the highest differences can be caused by selecting different primer pairs for PCR amplification of taxonomic markers. These differences suggested that care is needed while jointly analyzing metabarcoding data from differenet experiments. This study demonstrated the high performance and accuracy of DNBSEQ-G400 for short-read metabarcoding of microbial communities. Our study also produced datasets to allow further investigation of microbial diversity.

Identifiers

PMID36824325
PMCPMC9632034

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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.