Evidence map›Paper›PMID 32506266›Full record

ArticleGenes & genomics2020

A new metagenome binning method based on gene uniqueness.

Yulin Kang, Cheng Wan, Sifen Lu, Zhehan Fu, Antony K Chen, Zuhong Lu

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Article in Genes & genomics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

6 authors at 2 institutions in 1 country.

Yulin KangDepartment of Biomedical Engineering, College of Engineering, Peking University, Beijing, 100871, People's Republic of China.ORCID 0000-0002-7875-7930
Cheng WanDepartment of Biomedical Engineering, College of Engineering, Peking University, Beijing, 100871, People's Republic of China.
Sifen LuPrecision Medicine Center, Precision Medicine Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, People's Republic of China.
Zhehan FuDepartment of Biomedical Engineering, College of Engineering, Peking University, Beijing, 100871, People's Republic of China.
Antony K ChenDepartment of Biomedical Engineering, College of Engineering, Peking University, Beijing, 100871, People's Republic of China.
Zuhong LuDepartment of Biomedical Engineering, College of Engineering, Peking University, Beijing, 100871, People's Republic of China. zhlu@seu.edu.cn.
Peking University · CNSichuan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe human gut microbiome contains millions of genes and many undetected bacteria species. Recovering bacterial genomes from large complex metagenomes remains highly challenging, and current binning methods show insufficient recall rates.

objectiveThis study was performed to put forward a new metagenome binning method with promising recall rate and accuracy.

methodsWe found that more than 85% of the genes could be aligned to only one bacteria species by using strict BLAST parameters (identity > 90% and aligning length > 100 bp). This phenomenon was called "the gene uniqueness", which indicated that the most bacterial genes could be exclusive to the species' taxonomy. In our new metagenome binning method, we could cluster contigs based on gene similarity via a graph model. Any contig shared with same gene under Strict Blast parameters would be clustered into one bin.

resultswe obtained 1,131 bins and reconstructed the genomes of 12 unknown species for MetaHIT data Our method exhibited a more promising recall rate, faster running speed and lower time complexity than the current methods.

conclusionsThe present new metagenome binning method based on gene uniqueness had high recall rate and low error, which could be applied to assemble the bacterial genomes efficiently in complex metagenome.

Indexed as

AlgorithmsCluster AnalysisDNA Barcoding, TaxonomicGastrointestinal MicrobiomeGenome, BacterialHumansMetagenomeMetagenomicsSequence Analysis, DNABacteria assemblyBacterial genomeGene uniquenessMetagenomeMetagenome binning

Identifiers

PMID32506266
OpenAlexW3032925056

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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.