Evidence map›Paper›PMID 40603748›Full record

ArticleNature biomedical engineering2025

A fuzzy sequencer for rapid DNA fragment counting and genotyping.

Wenxiong Zhou, Li Kang, Shuo Qiao, Haifeng Duan, Chenghong Yin, Chao Liu, Zhizhao Liao, Mingchuan Tang, Ruiying Zhang, Lei Li and 13 more

Abstract read
In one paragraph

Article in Nature biomedical engineering, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

23 authors.

Wenxiong Zhou *Biomedical Pioneering Innovation Center (BIOPIC), Peking-Tsinghua Center for Life Sciences, School of Life Sciences, Peking University, Beijing, China.ORCID http://orcid.org/0000-0002-6633-3583
Li Kang *Biomedical Pioneering Innovation Center (BIOPIC), Peking-Tsinghua Center for Life Sciences, School of Life Sciences, Peking University, Beijing, China.
Shuo Qiao *Biomedical Pioneering Innovation Center (BIOPIC), Peking-Tsinghua Center for Life Sciences, School of Life Sciences, Peking University, Beijing, China.
Haifeng Duan *Cygnus Biosciences, BDA, Beijing, China.
Chenghong Yin *Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing, China.
Chao Liu *Department of Infectious Diseases, Peking University Third Hospital, Beijing, China.ORCID http://orcid.org/0000-0001-5886-4264
Zhizhao LiaoBiomedical Pioneering Innovation Center (BIOPIC), Peking-Tsinghua Center for Life Sciences, School of Life Sciences, Peking University, Beijing, China.
Mingchuan TangBiomedical Pioneering Innovation Center (BIOPIC), Peking-Tsinghua Center for Life Sciences, School of Life Sciences, Peking University, Beijing, China.
Ruiying ZhangCygnus Biosciences, BDA, Beijing, China.
Lei LiCygnus Biosciences, BDA, Beijing, China.
Lei ShiCygnus Biosciences, BDA, Beijing, China.
Meijie DuSchool of Life Sciences, State Key Laboratory of Green Biomanufacturing, Center for Synthetic and Systems Biology, Tsinghua University, Beijing, China.
Yipeng WangBeijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing, China.
Wentao YueBeijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing, China.
Yan XiaoInstitute of Pathogen Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Lin DiBiomedical Pioneering Innovation Center (BIOPIC), Peking-Tsinghua Center for Life Sciences, School of Life Sciences, Peking University, Beijing, China.
Xiannian ZhangBiomedical Pioneering Innovation Center (BIOPIC), Peking-Tsinghua Center for Life Sciences, School of Life Sciences, Peking University, Beijing, China.
Yuhong PangBiomedical Pioneering Innovation Center (BIOPIC), Peking-Tsinghua Center for Life Sciences, School of Life Sciences, Peking University, Beijing, China.ORCID http://orcid.org/0009-0006-5464-3521
Mingkun LiBeijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, China.ORCID http://orcid.org/0000-0003-1041-1172
Lili RenInstitute of Pathogen Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Jianbin WangSchool of Life Sciences, State Key Laboratory of Green Biomanufacturing, Center for Synthetic and Systems Biology, Tsinghua University, Beijing, China. jianbinwang@tsinghua.edu.cn.ORCID http://orcid.org/0000-0001-6725-7925
Zitian ChenCygnus Biosciences, BDA, Beijing, China. czitian@gmail.com.ORCID http://orcid.org/0009-0008-7139-2335
Yanyi HuangBiomedical Pioneering Innovation Center (BIOPIC), Peking-Tsinghua Center for Life Sciences, School of Life Sciences, Peking University, Beijing, China. yanyi@pku.edu.cn.ORCID http://orcid.org/0000-0002-7297-1266

Funding

Beijing Municipal Science and Technology Commission Z201100005320016Beijing Municipal Science and Technology Commission Z211100003321006Beijing Municipal Science and Technology Commission Z221100007022003National Natural Science Foundation of China (National Science Foundation of China) T2225005
6 · The paper itself

Abstract

High-throughput sequencing technologies generate a vast number of DNA sequence reads simultaneously, which are subsequently analysed using the information contained within these fragmented reads. The assessment of sequencing technology relies on information efficiency, which measures the amount of information entropy produced per sequencing reaction cycle. Here we propose a fuzzy sequencing strategy that exhibits information efficiency more than twice that of currently prevailing cyclic reversible terminator sequencing methods. To validate our approach, we develop a fully functional and high-throughput fuzzy sequencer. This sequencer implements an efficient fluorogenic sequencing-by-synthesis chemistry and we test it across various application scenarios, including copy-number variation detection, non-invasive prenatal testing, transcriptome profiling, mutation genotyping and metagenomic profiling. Our findings demonstrate that the fuzzy sequencing strategy outperforms existing methods in terms of information efficiency and delivers accurate resequencing results with faster turnaround times.

Indexed as

DNAFuzzy LogicGenotyping TechniquesHigh-Throughput Nucleotide SequencingSequence Analysis, DNADNA Copy Number VariationsGene Expression ProfilingGenotypeHumansMutationDNA

Identifiers

PMID40603748
PMCPMC12705452

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.