HiFine: integrating Hi-C-based and shotgun-based methods to refine binning of metagenomic contigs
HiFine: integrating Hi-C-based and shotgun-based methods to refine binning of metagenomic contigs
复制标题
DOI：
10.1093/bioinformatics/btac295
复制
发表时间：
2022-05-12
期刊：
影响因子：
5.8
通讯作者：
Sun, Fengzhu
中科院分区：
文献类型：
--
作者：
Du, Yuxuan;Sun, Fengzhu
动机：宏基因组分箱旨在通过将短读段组装的宏基因组重叠群聚类到草稿基因组箱中，直接从生态系统中检索微生物基因组。传统的基于鸟枪法的分箱方法取决于重叠群的组成和丰度分布，并且由于缺乏足够的样本来构建可靠的共丰度分布而受到损害。当应用于单个样本时，基于鸟枪的分箱方法很难仅使用成分信息来区分密切相关的物种。作为一种替代的分箱方法，基于 Hi-C 的分箱采用宏基因组 Hi-C 技术来测量宏基因组片段之间的邻近接触。然而，物种间 DNA 片段的错误连接不可避免地会产生虚假的物种间 Hi-C 接触，从而将来自不同基因组的重叠群连接起来，从而削弱了最终基因组草图的纯度。因此，必须开发一种分箱流程来克服单一样本上两种分箱方法的缺点。结果：我们开发了 HiFine，一种新颖的分箱流程，通过集成基于 Hi-C 和基于鸟枪的分箱工具来细化宏基因组重叠群的分箱结果。 HiFine 为源自基于 Hi-C 和鸟枪法的分箱方法的原始 bin 集设计了碎片化策略，这大大提高了初始 bin 的纯度，然后合并碎片 bin 并招募未分箱的重叠群。我们证明 HiFine 显着改善了两种类型分箱方法的现有分箱结果，并在公开数据集上构建物种基因组方面取得了更好的性能。据我们所知，HiFine 是第一个集成不同类型工具用于宏基因组重叠群分箱的管道。
Motivation: Metagenomic binning aims to retrieve microbial genomes directly from ecosystems by clustering meta-genomic contigs assembled from short reads into draft genomic bins. Traditional shotgun-based binning methods depend on the contigs' composition and abundance profiles and are impaired by the paucity of enough samples to construct reliable co-abundance profiles. When applied to a single sample, shotgun-based binning methods struggle to distinguish closely related species only using composition information. As an alternative binning approach, Hi-C-based binning employs metagenomic Hi-C technique to measure the proximity contacts between metagenomic fragments. However, spurious inter-species Hi-C contacts inevitably generated by incorrect ligations of DNA fragments between species link the contigs from varying genomes, weakening the purity of final draft genomic bins. Therefore, it is imperative to develop a binning pipeline to overcome the shortcomings of both types of binning methods on a single sample.Results: We develop HiFine, a novel binning pipeline to refine the binning results of metagenomic contigs by integrating both Hi-C-based and shotgun-based binning tools. HiFine designs a strategy of fragmentation for the original bin sets derived from the Hi-C-based and shotgun-based binning methods, which considerably increases the purity of initial bins, followed by merging fragmented bins and recruiting unbinned contigs. We demonstrate that HiFine significantly improves the existing binning results of both types of binning methods and achieves better performance in constructing species genomes on publicly available datasets. To the best of our knowledge, HiFine is the first pipeline to integrate different types of tools for the binning of metagenomic contigs.