Relative species abundance estimation in artificial mixtures of insects using mito-metagenomics and a correction...

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.