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New mitochondrial primers for metabarcoding of insects designed and evaluated using in silico methods

机译:使用计算机方法设计和评估用于昆虫代谢条形码的新型线粒体引物

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摘要

Insect metabarcoding has been mainly based on PCR amplification of short fragments within the “barcoding region” of the gene cytochrome oxidase I (COI). However, because of the variability of this gene, it has been difficult to design good universal PCR primers. Most primers used today are associated with gaps in the taxonomic coverage or amplification biases that make the results less reliable and impede the detection of species that are present in the sample. We identify new primers for insect metabarcoding using computational approaches ( and ) applied to the most comprehensive reference databases of mitochondrial genomes of Hexapoda assembled to date. New primers are evaluated in silico against previously published primers in terms of taxonomic coverage and resolution of the corresponding amplicons. For the latter criterion, we propose a new index, exclusive taxonomic resolution, which is a more biologically meaningful measure than the standard index used today. Our results show that the best markers are found in the ribosomal RNA genes (12S and 16S); they resolve about 90% of the genetically distinct species in the reference database. Some markers in protein‐coding genes provide similar performance but only at much higher levels of primer degeneracy. Combining two of the best individual markers improves the effective taxonomic resolution with up to 10%. The resolution is strongly dependent on insect taxon: COI primers detect 40% of Hymenoptera, while 12S primers detect 12% of Collembola. Our results indicate that amplicon‐based metabarcoding of insect samples can be improved by choosing other primers than those commonly used today.
机译:昆虫超条形码主要基于PCR扩增细胞色素氧化酶I(COI)基因“条形码区域”内的短片段。然而,由于该基因的可变性,难以设计好的通用PCR引物。当今使用的大多数引物都与分类覆盖率或扩增偏差有关,从而使结果可靠性降低并阻碍了样品中存在物种的检测。我们使用迄今已组装的六足纲线粒体基因组最全面的参考数据库,使用计算方法(和)确定用于昆虫metabarcoding的新引物。根据分类覆盖率和相应扩增子的分辨率,对计算机上与以前发表的引物进行计算机评估新引物。对于后一个标准,我们提出了一个新的索引,即专有分类学分辨率,这是一种比当今使用的标准索引更具生物学意义的度量。我们的结果表明,在核糖体RNA基因(12S和16S)中发现了最佳标记。他们解析了参考数据库中大约90%的遗传上不同的物种。蛋白质编码基因中的某些标记提供相似的性能,但仅在引物简并性更高的水平上。结合使用两种最佳的单个标记,可将有效的分类学分辨率提高多达10%。分辨率很大程度上取决于昆虫分类群:COI引物可检测到40%的膜翅目,而12S引物可检测到12%的Collembola。我们的结果表明,通过选择除当今常用引物以外的其他引物,可以改善昆虫样品的基于扩增子的元条形码。

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