Metabarcoding data allow for reliable biomass estimates in the most abundant animals on earth
Microscopic organisms are the dominant and most diverse organisms on Earth. Nematodes, as part of this microscopic diversity, are by far the most abundant animals and their diversity is equally high. Molecular metabarcoding is often applied to study the diversity of microorganisms,...
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| Autores principales: | , , , |
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| Formato: | article |
| Lenguaje: | EN |
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Pensoft Publishers
2019
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/cfd25af10c7e4687a63bc961c7de8746 |
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| Sumario: | Microscopic organisms are the dominant and most diverse organisms on Earth. Nematodes, as part of this microscopic diversity, are by far the most abundant animals and their diversity is equally high. Molecular metabarcoding is often applied to study the diversity of microorganisms, but has yet to become the standard to determine nematode communities. As such, the information metabarcoding provides, such as in terms of species coverage, taxonomic resolution and especially if sequence reads can be linked to the abundance or biomass of nematodes in a sample, has yet to be determined. Here, we applied metabarcoding using three primer sets located within ribosomal rRNA gene regions to target assembled mock-communities consisting of 18 different nematode species that we established in 9 different compositions. We determined abundances and biomass of all species added to examine if relative sequence abundance or biomass can be linked to relative sequence reads. We found that nematode communities are not equally represented by the three different primer sets and we found that relative read abundances almost perfectly correlated positively with relative species biomass for two of the primer sets. This strong biomass-read number correlation suggests that metabarcoding reads can reveal biomass information even amongst more complex nematode communities as present in the environment and possibly can be transferred to better study other groups of organisms. This biomass-read link is of particular importance for more reliably assessing nutrient flow through food-webs, as well as adjusting biogeochemical models through user-friendly and easily obtainable metabarcoding data.
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