Department of Integrative Biology, University of Guelph, Guelph, ON N1G 2W1, Canada.
Centre for Biodiversity Genomics, University of Guelph, Guelph, ON N1G 2W1, Canada.
Nucleic Acids Res. 2022 Sep 9;50(16):9279-9293. doi: 10.1093/nar/gkac689.
Metagenomics and total RNA sequencing (total RNA-Seq) have the potential to improve the taxonomic identification of diverse microbial communities, which could allow for the incorporation of microbes into routine ecological assessments. However, these target-PCR-free techniques require more testing and optimization. In this study, we processed metagenomics and total RNA-Seq data from a commercially available microbial mock community using 672 data-processing workflows, identified the most accurate data-processing tools, and compared their microbial identification accuracy at equal and increasing sequencing depths. The accuracy of data-processing tools substantially varied among replicates. Total RNA-Seq was more accurate than metagenomics at equal sequencing depths and even at sequencing depths almost one order of magnitude lower than those of metagenomics. We show that while data-processing tools require further exploration, total RNA-Seq might be a favorable alternative to metagenomics for target-PCR-free taxonomic identifications of microbial communities and might enable a substantial reduction in sequencing costs while maintaining accuracy. This could be particularly an advantage for routine ecological assessments, which require cost-effective yet accurate methods, and might allow for the incorporation of microbes into ecological assessments.
宏基因组学和总 RNA 测序(total RNA-Seq)有可能提高对各种微生物群落的分类鉴定能力,从而将微生物纳入常规生态评估中。然而,这些无靶向-PCR 的技术需要更多的测试和优化。在这项研究中,我们使用 672 种数据处理工作流程处理了市售微生物模拟群落的宏基因组学和总 RNA-Seq 数据,确定了最准确的数据处理工具,并比较了它们在相等和递增测序深度下的微生物鉴定准确性。数据处理工具的准确性在重复实验中差异很大。在相等的测序深度下,总 RNA-Seq 比宏基因组学更准确,甚至在测序深度比宏基因组学低几乎一个数量级的情况下也更准确。我们表明,虽然数据处理工具需要进一步探索,但对于无靶向-PCR 的微生物群落分类鉴定,总 RNA-Seq 可能是宏基因组学的一个有利替代方法,并且可以在保持准确性的同时,大幅降低测序成本。这对于需要经济高效但准确的方法的常规生态评估可能是一个特别的优势,并且可能允许将微生物纳入生态评估中。