Evidence map›Paper›PMID 37978521›Full record

ArticleBMC medical genomics2023

Accuracy and depth evaluation of clinical low pass genome sequencing in the detection of mosaic aneuploidies and CNVs.

Yanqiu Liu, Shengju Hao, Xueqin Guo, Linlin Fan, Zhihong Qiao, Yaoshen Wang, Xiaoli Wang, Jianfen Man, Lina Wang, Xiaoming Wei and 4 more

Open access · goldAbstract read
In one paragraph

Article in BMC medical genomics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
4.1field-weighted citation impact, top 6% 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.

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 7 citations in OpenAlex.

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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

14 authors at 4 institutions in 2 countries.

Yanqiu Liu *Jiangxi Maternal and Child Health Hospital Affiliated to Nanchang Medical College, Nanchang, 33000, Jiangxi, China.
Shengju Hao *Medical Genetics Center, Gansu Provincial Clinical Research Center for Birth Defects and Rare Diseases, Gansu Provincial Maternity and Child-care Hospital, Lanzhou, 730050, China.
Xueqin Guo *Clin Lab, BGI Genomics, Wuhan, 430074, China.
Linlin FanClin Lab, BGI Genomics, Tianjin, 300308, China.
Zhihong QiaoClin Lab, BGI Genomics, Tianjin, 300308, China.
Yaoshen WangClin Lab, BGI Genomics, Tianjin, 300308, China.
Xiaoli WangClin Lab, BGI Genomics, Shenzhen, 518083, China.
Jianfen ManClin Lab, BGI Genomics, Wuhan, 430074, China.
Lina WangClin Lab, BGI Genomics, Wuhan, 430074, China.
Xiaoming WeiClin Lab, BGI Genomics, Wuhan, 430074, China.
Huanhuan PengMGI Tech, Shenzhen, 518083, China.
Zhiyu PengBGI Genomics, Shenzhen, 518083, China.
Yan SunBGI Genomics, Shenzhen, 518083, China. sunyan2@bgi.com.
Lijie SongClin Lab, BGI Genomics, Tianjin, 300308, China. songlijie@bgi.com.
BGI Group (China) · CNBGI GenomicsGansu Provincial Maternal and Child Health Hospital · CNJiangxi Maternal and Child Health Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLow-pass genome sequencing (LP GS) has shown distinct advantages over traditional methods for the detection of mosaicism. However, no study has systematically evaluated the accuracy of LP GS in the detection of mosaic aneuploidies and copy number variants (CNVs) in prenatal diagnosis. Moreover, the influence of sequencing depth on mosaicism detection of LP GS has not been fully evaluated.

methodsTo evaluate the accuracy of LP GS in the detection of mosaic aneuploidies and mosaic CNVs, 27 samples with known aneuploidies and CNVs and 1 negative female sample were used to generate 6 simulated samples and 21 virtual samples, each sample contained 9 different mosaic levels. Mosaic levels were simulated by pooling reads or DNA from each positive sample and the negative sample according to a series of percentages (ranging from 3 to 40%). Then, the influence of sequencing depth on LP GS in the detection of mosaic aneuploidies and CNVs was evaluated by downsampling.

resultsTo evaluate the accuracy of LP GS in the detection of mosaic aneuploidies and CNVs, a comparative analysis of mosaic levels was performed using 6 simulated samples and 21 virtual samples with 35 M million (M) uniquely aligned high-quality reads (UAHRs). For mosaic levels > 30%, the average difference (detected mosaic levels vs. theoretical mosaic levels) of 6 mosaic CNVs in simulated samples was 4.0%, and the average difference (detected mosaic levels vs. mosaic levels of Y chromosome) of 6 mosaic aneuploidies and 15 mosaic CNVs in virtual samples was 2.7%. Furthermore, LP GS had a higher detection rate and accuracy for the detection of mosaic aneuploidies and CNVs of larger sizes, especially mosaic aneuploidies. For depth evaluation, the results of LP GS in downsampling samples were compared with those of LP GS using 35 M UAHRs. The detection sensitivity of LP GS for 6 mosaic aneuploidies and 15 mosaic CNVs in virtual samples increased with UAHR. For mosaic levels > 30%, the total detection sensitivity reached a plateau at 30 M UAHRs. With 30 M UAHRs, the total detection sensitivity was 99.2% for virtual samples.

conclusionsWe demonstrated the accuracy of LP GS in mosaicism detection using simulated data and virtual samples, respectively. Thirty M UAHRs (single-end 35 bp) were optimal for LP GS in the detection of mosaic aneuploidies and most mosaic CNVs larger than 1.48 Mb (Megabases) with mosaic levels > 30%. These results could provide a reference for laboratories that perform clinical LP GS in the detection of mosaic aneuploidies and CNVs.

Indexed as

AneuploidyDNA Copy Number VariationsChromosome MappingFemaleHumansMosaicismPregnancyPrenatal DiagnosisLow pass genome sequencingMosaic aneuploidiesMosaic CNVs

Identifiers

PMID37978521
PMCPMC10656965
OpenAlexW4388762601

What OpenQuestion holds

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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.