Mito-metagenomics (MMG) is becoming an alternative to amplicon metabarcoding for the assessment of biodiversity in complex biological samples using high-throughput sequencing. Whereas MMG overcomes the biases introduced by the PCR step in the generation of amplicons, it is not yet a technique free of shortcomings. First, as the reads are obtained from shotgun sequencing, a very low proportion of reads map into the mitogenomes, so a high sequencing effort is needed. Second, as the number of mitogenomes per cell can vary among species, the relative species abundance (RSA) in a mixture could be wrongly estimated. Here, we challenge the MMG method to estimate the RSA using artificial libraries of 17 insect species whose complete genomes are available on public repositories. With fresh specimens of these species, we created single-species libraries to calibrate the bioinformatic pipeline and mixed-species libraries to estimate the RSA. Our results showed that the MMG approach confidently recovers the species list of the mixtures, even when they contain congeneric species. The method was also able to estimate the abundance of a species across different samples (within-species estimation) but failed to estimate the RSA within a single sample (across-species estimation) unless a correction factor accounting for the variable number of mitogenomes per cell was used. To estimate this correction factor, we used the proportion of reads mapping into mitogenomes in the single-species libraries and the lengths of the whole genomes and mitogenomes.

中文翻译：

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使用线粒体宏基因组学和线粒体 DNA 拷贝数的校正因子在昆虫人工混合物中的相对物种丰度估计

线粒体宏基因组学 (MMG) 正在成为扩增子宏条形码的替代方案，用于使用高通量测序评估复杂生物样本中的生物多样性。尽管 MMG 克服了 PCR 步骤在扩增子生成中引入的偏差，但它仍然不是一种没有缺点的技术。首先，由于读取是从鸟枪法测序中获得的，因此映射到有丝分裂基因组中的读取比例非常低，因此需要进行大量测序工作。其次，由于每个细胞的有丝分裂基因组数量可能因物种而异，因此可能会错误地估计混合物中的相对物种丰度 (RSA)。在这里，我们挑战 MMG 方法，使用 17 种昆虫物种的人工文库来估计 RSA，其完整基因组可在公共存储库中获得。有了这些物种的新鲜标本，我们创建了单一物种库来校准生物信息学管道和混合物种库来估计 RSA。我们的结果表明，MMG 方法可以自信地恢复混合物的物种列表，即使它们包含同类物种。该方法还能够估计不同样本中物种的丰度（种内估计），但未能估计单个样本内的 RSA（跨种估计），除非使用了解释每个细胞有丝分裂基因组可变数量的校正因子。为了估计这个校正因子，我们使用了映射到单物种文库中有丝分裂基因组的读数比例以及整个基因组和有丝分裂基因组的长度。