MetaCC allows scalable and integrative analyses of both long-read and short-read metagenomic Hi-C data
Abstract Metagenomic Hi-C (metaHi-C) can identify contig-to-contig relationships with respect to their proximity within the same physical cell. Shotgun libraries in metaHi-C experiments can be constructed by next-generation sequencing (short-read metaHi-C) or more recent third-generation sequencing...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2023-10-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-023-41209-6 |
| _version_ | 1797558631225360384 |
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| author | Yuxuan Du Fengzhu Sun |
| author_facet | Yuxuan Du Fengzhu Sun |
| author_sort | Yuxuan Du |
| collection | DOAJ |
| description | Abstract Metagenomic Hi-C (metaHi-C) can identify contig-to-contig relationships with respect to their proximity within the same physical cell. Shotgun libraries in metaHi-C experiments can be constructed by next-generation sequencing (short-read metaHi-C) or more recent third-generation sequencing (long-read metaHi-C). However, all existing metaHi-C analysis methods are developed and benchmarked on short-read metaHi-C datasets and there exists much room for improvement in terms of more scalable and stable analyses, especially for long-read metaHi-C data. Here we report MetaCC, an efficient and integrative framework for analyzing both short-read and long-read metaHi-C datasets. MetaCC outperforms existing methods on normalization and binning. In particular, the MetaCC normalization module, named NormCC, is more than 3000 times faster than the current state-of-the-art method HiCzin on a complex wastewater dataset. When applied to one sheep gut long-read metaHi-C dataset, MetaCC binning module can retrieve 709 high-quality genomes with the largest species diversity using one single sample, including an expansion of five uncultured members from the order Erysipelotrichales, and is the only binner that can recover the genome of one important species Bacteroides vulgatus. Further plasmid analyses reveal that MetaCC binning is able to capture multi-copy plasmids. |
| first_indexed | 2024-03-10T17:34:10Z |
| format | Article |
| id | doaj.art-0a7e83bd6a9a4c5f88810fb86541b204 |
| institution | Directory Open Access Journal |
| issn | 2041-1723 |
| language | English |
| last_indexed | 2024-03-10T17:34:10Z |
| publishDate | 2023-10-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj.art-0a7e83bd6a9a4c5f88810fb86541b2042023-11-20T09:54:05ZengNature PortfolioNature Communications2041-17232023-10-0114111210.1038/s41467-023-41209-6MetaCC allows scalable and integrative analyses of both long-read and short-read metagenomic Hi-C dataYuxuan Du0Fengzhu Sun1Department of Quantitative and Computational Biology, University of Southern CaliforniaDepartment of Quantitative and Computational Biology, University of Southern CaliforniaAbstract Metagenomic Hi-C (metaHi-C) can identify contig-to-contig relationships with respect to their proximity within the same physical cell. Shotgun libraries in metaHi-C experiments can be constructed by next-generation sequencing (short-read metaHi-C) or more recent third-generation sequencing (long-read metaHi-C). However, all existing metaHi-C analysis methods are developed and benchmarked on short-read metaHi-C datasets and there exists much room for improvement in terms of more scalable and stable analyses, especially for long-read metaHi-C data. Here we report MetaCC, an efficient and integrative framework for analyzing both short-read and long-read metaHi-C datasets. MetaCC outperforms existing methods on normalization and binning. In particular, the MetaCC normalization module, named NormCC, is more than 3000 times faster than the current state-of-the-art method HiCzin on a complex wastewater dataset. When applied to one sheep gut long-read metaHi-C dataset, MetaCC binning module can retrieve 709 high-quality genomes with the largest species diversity using one single sample, including an expansion of five uncultured members from the order Erysipelotrichales, and is the only binner that can recover the genome of one important species Bacteroides vulgatus. Further plasmid analyses reveal that MetaCC binning is able to capture multi-copy plasmids.https://doi.org/10.1038/s41467-023-41209-6 |
| spellingShingle | Yuxuan Du Fengzhu Sun MetaCC allows scalable and integrative analyses of both long-read and short-read metagenomic Hi-C data Nature Communications |
| title | MetaCC allows scalable and integrative analyses of both long-read and short-read metagenomic Hi-C data |
| title_full | MetaCC allows scalable and integrative analyses of both long-read and short-read metagenomic Hi-C data |
| title_fullStr | MetaCC allows scalable and integrative analyses of both long-read and short-read metagenomic Hi-C data |
| title_full_unstemmed | MetaCC allows scalable and integrative analyses of both long-read and short-read metagenomic Hi-C data |
| title_short | MetaCC allows scalable and integrative analyses of both long-read and short-read metagenomic Hi-C data |
| title_sort | metacc allows scalable and integrative analyses of both long read and short read metagenomic hi c data |
| url | https://doi.org/10.1038/s41467-023-41209-6 |
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