Developing a monitoring program of genetic diversity: what do stakeholders say?

A validated protocol for eDNA-based monitoring of within-species genetic diversity in a pond-breeding amphibian

In light of the dramatic decline in amphibian biodiversity, new cost-efficient tools to rapidly monitor species abundance and population genetic diversity in space and time are urgently needed. It has been amply demonstrated that the use of environmental DNA (eDNA) for single-species detection and characterization of community composition can increase the precision of amphibian monitoring compared to traditional (observational) approaches. However, it has been suggested that the efficiency and accuracy of the eDNA approach could be further improved by more timely sampling; in addition, the quality of genetic diversity data derived from the same DNA has been confirmed in other vertebrate taxa, but not amphibians. Given the availability of previous tissue-based genetic data, here we use the common frog Rana temporaria Linnaeus, 1758 as our target species and an improved eDNA protocol to: (i) investigate differences in species detection between three developmental stages in various freshwater environments; and (ii) study the diversity of mitochondrial DNA (mtDNA) haplotypes detected in eDNA (water) samples, by amplifying a specific fragment of the COI gene (331 base pairs, bp) commonly used as a barcode. Our protocol proved to be a reliable tool for monitoring population genetic diversity of this species, and could be a valuable addition to amphibian conservation and wetland management.

Re-thinking the environment in landscape genomics

Detecting the extrinsic selective pressures shaping genomic variation is critical for a better understanding of adaptation and for forecasting evolutionary responses of natural populations to changing environmental conditions. With increasing availability of geo-referenced environmental data, landscape genomics provides unprecedented insights into how genomic variation and underlying gene functions affect traits potentially under selection. Yet, the robustness of genotype-environment associations used in landscape genomics remains tempered due to various limitations, including the characteristics of environmental data used, sampling designs employed, and statistical frameworks applied. Here, we argue that using complementary or new environmental data sources and well-informed sampling designs may help improve the detection of selective pressures underlying patterns of local adaptation in various organisms and environments.

A multispecies amplicon sequencing approach for genetic diversity assessments in grassland plant species

Grasslands are widespread and economically relevant ecosystems at the basis of sustainable roughage production. Plant genetic diversity (PGD; i.e., within‐species diversity) is related to many beneficial effects on the ecosystem functioning of grasslands. The monitoring of PGD in temperate grasslands is complicated by the multiplicity of species present and by a shortage of methods for large‐scale assessments. However, the continuous advancement of high‐throughput DNA sequencing approaches has improved the prospects of broad, multispecies PGD monitoring. Among them, amplicon sequencing stands out as a robust and cost‐effective method. Here, we report a set of 12 multispecies primer pairs that can be used for high‐throughput PGD assessments in multiple grassland plant species. The target loci were selected and tested in two phases: a “discovery phase” based on a sequence capture assay (611 nuclear loci assessed in 16 grassland plant species), which resulted in the selection of 11 loci; and a “validation phase”, in which the selected loci were targeted and sequenced using multispecies primers in test populations of Dactylis glomerata L., Lolium perenne L., Festuca pratensis Huds., Trifolium pratense L. and T. repens L. The multispecies amplicons had nucleotide diversities per species from 5.19 × 10⁻³ to 1.29 × 10⁻², which is in the range of flowering‐related genes but slightly lower than pathogen resistance genes. We conclude that the methodology, the DNA sequence resources, and the primer pairs reported in this study provide the basis for large‐scale, multispecies PGD monitoring in grassland plants.