An accessible metagenomic strategy allows for better characterisation of invertebrate bulk samples
Callens, M.; Le Berre, G.; Van den Bulcke, L.; Lolivier, M.; Derycke, S. (2025). An accessible metagenomic strategy allows for better characterisation of invertebrate bulk samples. Mol. Ecol. Resour. 25(8): e14126. https://dx.doi.org/10.1111/1755-0998.14126
In: Molecular Ecology Resources. Blackwell Publishing: Oxford. ISSN 1755-098X; e-ISSN 1755-0998, more
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| Author keywords |
biodiversity monitoring; bulk samples; invertebrates; metagenomics |
| Authors | | Top |
- Callens, M., more
- Le Berre, G.
- Van den Bulcke, L., more
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- Lolivier, M.
- Derycke, S., more
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| Abstract |
DNA-based techniques are a popular approach for assessing biodiversity in ecological research, especially for organisms which are difficult to detect or identify morphologically. Metabarcoding, the most established method for determining species composition and relative abundance in bulk samples, can be more sensitive and time- and cost-effective than traditional morphological approaches. However, one drawback of this method is PCR bias caused by between-species variation in the amplification efficiency of a marker gene. Metagenomics, bypassing PCR amplification, has been proposed as an alternative to overcome this bias. Several studies have already shown the promising potential of metagenomics, but they all indicate the unavailability of reference genomes for most species in any ecosystem as one of the primary bottlenecks preventing its wider implementation. In this study, we present a strategy that combines unassembled reads of low-coverage whole genome sequencing and publicly available reference genomes to construct a genomic reference database, thus circumventing high sequencing costs and intensive bioinformatic processing. We show that this approach is superior to metabarcoding for approximating relative biomass of macrobenthos species from bulk samples. Furthermore, these results can be obtained with a sequencing effort comparable to metabarcoding. The strategy presented here can thus accelerate the implementation of metagenomics in biodiversity assessments, as it should be relatively easy to adopt by laboratories familiar with metabarcoding and can be used as an accessible alternative. |
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