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- Title
Exploring high-quality microbial genomes by assembling short-reads with long-range connectivity.
- Authors
Zhang, Zhenmiao; Xiao, Jin; Wang, Hongbo; Yang, Chao; Huang, Yufen; Yue, Zhen; Chen, Yang; Han, Lijuan; Yin, Kejing; Lyu, Aiping; Fang, Xiaodong; Zhang, Lu
- Abstract
Although long-read sequencing enables the generation of complete genomes for unculturable microbes, its high cost limits the widespread adoption of long-read sequencing in large-scale metagenomic studies. An alternative method is to assemble short-reads with long-range connectivity, which can be a cost-effective way to generate high-quality microbial genomes. Here, we develop Pangaea, a bioinformatic approach designed to enhance metagenome assembly using short-reads with long-range connectivity. Pangaea leverages connectivity derived from physical barcodes of linked-reads or virtual barcodes by aligning short-reads to long-reads. Pangaea utilizes a deep learning-based read binning algorithm to assemble co-barcoded reads exhibiting similar sequence contexts and abundances, thereby improving the assembly of high- and medium-abundance microbial genomes. Pangaea also leverages a multi-thresholding algorithm strategy to refine assembly for low-abundance microbes. We benchmark Pangaea on linked-reads and a combination of short- and long-reads from simulation data, mock communities and human gut metagenomes. Pangaea achieves significantly higher contig continuity as well as more near-complete metagenome-assembled genomes (NCMAGs) than the existing assemblers. Pangaea also generates three complete and circular NCMAGs on the human gut microbiomes. Here, the authors develop Pangaea, an assembler that uses short-reads with long-range connectivity to create high-quality microbial genomes affordably, showing it outperforms existing methods in generating more complete genomes from both mock and real metagenomic samples.
- Subjects
PANGAEA (Supercontinent); MICROBIAL genomes; NUCLEOTIDE sequencing; SHOTGUN sequencing; HUMAN microbiota; METAGENOMICS; GENOMES; BAR codes
- Publication
Nature Communications, 2024, Vol 15, Issue 1, p1
- ISSN
2041-1723
- Publication type
Article
- DOI
10.1038/s41467-024-49060-z