Master of Science, Universite Libre De Bruxelles (2010)
Bachelier, Universite Libre De Bruxelles (2008)
Doctor of Philosophy, Ecole Polytechnique Federale Lausanne (2015)
A comparison of eDNA to camera trapping for assessment of terrestrial mammal diversity.
Proceedings. Biological sciences
2020; 287 (1918): 20192353
Before environmental DNA (eDNA) can establish itself as a robust tool for biodiversity monitoring, comparison with existing approaches is necessary, yet is lacking for terrestrial mammals. Moreover, much is unknown regarding the nature, spread and persistence of DNA shed by animals into terrestrial environments, or the optimal experimental design for understanding these potential biases. To address some of these challenges, we compared the detection of terrestrial mammals using eDNA analysis of soil samples against confirmed species observations from a long-term (approx. 9-year) camera-trapping study. At the same time, we considered multiple experimental parameters, including two sampling designs, two DNA extraction kits and two metabarcodes of different sizes. All mammals regularly recorded with cameras were detected in eDNA. In addition, eDNA reported many unrecorded small mammals whose presence in the study area is otherwise documented. A long metabarcode (220 bp) offering a high taxonomic resolution, achieved a similar efficiency as a shorter one (70 bp) and a phosphate buffer-based extraction gave similar results as a total DNA extraction method, for a fraction of the price. Our results support that eDNA-based monitoring should become a valuable part of ecosystem surveys, yet mitochondrial reference databases need to be enriched first.
View details for DOI 10.1098/rspb.2019.2353
View details for PubMedID 31937227
Rapid identification and interpretation of gene-environment associations using the new R.SamBada landscape genomics pipeline.
Molecular ecology resources
Sambetaada is a genome-environment association (GEA) software, designed to search for signatures of local adaptation. However, pre- and post-processing of data can be labour-intensive, preventing wider uptake of the method. We have now developed R.SamBada, an R-package providing a pipeline for landscape genomic analysis based on Sambetaada, spanning from the retrieval of environmental conditions at sampling locations to gene annotation using the Ensembl genome browser. As a result, R.SamBada standardizes the landscape genomics pipeline, eases the search for candidate genes of local adaptation, enhancing reproducibility of landscape genomic studies. The efficiency and power of the pipeline is illustrated using two examples: sheep populations from Morocco with no evident population structure, and Lidia cattle from Spain displaying population sub-structuring. In both cases, R.SamBada enabled rapid identification and interpretation of candidate genes, which are further discussed in the light of local adaptation. The package is available in the R CRAN package repository and on GitHub (github. com/SolangeD/R.SamBada). This article is protected by copyright. All rights reserved.
View details for DOI 10.1111/1755-0998.13044
View details for PubMedID 31136078