Investigating the impact of database choice on the accuracy of metagenomic read classification for the rumen microbiome.
Investigating the impact of database choice on the accuracy of metagenomic read classification for the rumen microbiome.
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DOI：
10.1186/s42523-022-00207-7
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发表时间：
2022-11-18
影响因子：
4.7
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中科院分区：
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微生物组分析正迅速转向高通量方法，如宏基因组测序。宏基因组数据的准确分类学分类依赖于参考序列数据库及其相关的分类学。然而，对于研究不足的环境，如瘤胃微生物组，许多序列将来自参考数据库中不存在的新的或未培养的微生物。因此，来自研究不足的环境的宏基因组数据的分类学分类可能是不准确的。为了评估分类学读段分类的准确性，本研究对从Hungate收集的培养的瘤胃微生物基因组模拟的宏基因组数据进行了分类。为了评估参考数据库对分类学分类准确性的影响，使用几个参考数据库使用Kraken 2对数据进行分类。研究发现，参考数据库的选择和组成对分类结果和准确性有显著影响。特别是，NCBI RefSeq被证明是一个糟糕的数据库选择。我们的研究结果表明，不准确的读段分类可能是一个重要的问题，影响所有使用不足的参考数据库的研究。我们观察到，将来自瘤胃的培养参考基因组添加到参考数据库中大大提高了分类率和准确性。我们还证明了宏基因组组装的基因组（MAG）有可能通过代表未培养的微生物来进一步提高分类准确性，否则这些微生物的序列将被未分类或错误分类。然而，分类准确性强烈依赖于分配给这些MAG的分类标签。因此，我们强调了准确的参考分类信息的重要性，并建议，与正式的分类谱系，MAG有可能提高分类率和准确性，特别是在环境中，如瘤胃研究不足或包含许多新的基因组。在线版本包含补充材料，可通过10.1186/s42523-022-00207-7获得。
Microbiome analysis is quickly moving towards high-throughput methods such as metagenomic sequencing. Accurate taxonomic classification of metagenomic data relies on reference sequence databases, and their associated taxonomy. However, for understudied environments such as the rumen microbiome many sequences will be derived from novel or uncultured microbes that are not present in reference databases. As a result, taxonomic classification of metagenomic data from understudied environments may be inaccurate. To assess the accuracy of taxonomic read classification, this study classified metagenomic data that had been simulated from cultured rumen microbial genomes from the Hungate collection. To assess the impact of reference databases on the accuracy of taxonomic classification, the data was classified with Kraken 2 using several reference databases. We found that the choice and composition of reference database significantly impacted on taxonomic classification results, and accuracy. In particular, NCBI RefSeq proved to be a poor choice of database. Our results indicate that inaccurate read classification is likely to be a significant problem, affecting all studies that use insufficient reference databases. We observed that adding cultured reference genomes from the rumen to the reference database greatly improved classification rate and accuracy. We also demonstrated that metagenome-assembled genomes (MAGs) have the potential to further enhance classification accuracy by representing uncultivated microbes, sequences of which would otherwise be unclassified or incorrectly classified. However, classification accuracy was strongly dependent on the taxonomic labels assigned to these MAGs. We therefore highlight the importance of accurate reference taxonomic information and suggest that, with formal taxonomic lineages, MAGs have the potential to improve classification rate and accuracy, particularly in environments such as the rumen that are understudied or contain many novel genomes. The online version contains supplementary material available at 10.1186/s42523-022-00207-7.