2b-RAD Genotyping of the Seagrass Cymodocea nodosa Along a Latitudinal Cline Identifies Candidate Genes for Environmental Adaptation

Abstract

Plant populations distributed along broad latitudinal gradients often show patterns of clinal variation in genotype and phenotype. Differences in photoperiod and temperature cues across latitudes influence major phenological events, such as timing of flowering or seed dormancy. Here, we used an array of 4,941 SNPs derived from 2b-RAD genotyping to characterize population differentiation and levels of genetic and genotypic diversity of three populations of the seagrass Cymodocea nodosa along a latitudinal gradient extending across the Atlantic-Mediterranean boundary (i.e., Gran Canaria—Canary Islands, Faro—Portugal, and Ebro Delta—Spain). Our main goal was to search for potential outlier loci that could underlie adaptive differentiation of populations across the latitudinal distribution of the species. We hypothesized that such polymorphisms could be related to variation in photoperiod-temperature regime occurring across latitudes. The three populations were clearly differentiated and exhibited diverse levels of clonality and genetic diversity. Cymodocea nodosa from the Mediterranean displayed the highest genotypic richness, while the Portuguese population had the highest clonality values. Gran Canaria exhibited the lowest genetic diversity (as observed heterozygosity). Nine SNPs were reliably identified as outliers across the three sites by two different methods (i.e., BayeScan and pcadapt), and three SNPs could be associated to specific protein-coding genes by screening available C. nodosa transcriptomes. Two SNPs-carrying contigs encoded for transcription factors, while the other one encoded for an enzyme specifically involved in the regulation of flowering time, namely Lysine-specific histone demethylase 1 homolog 2. When analyzing biological processes enriched within the whole dataset of outlier SNPs identified by at least one method, “regulation of transcription” and “signalling” were among the most represented. Our results highlight the fundamental importance signal integration and gene-regulatory networks, as well as epigenetic regulation via DNA (de)methylation, could have for enabling adaptation of seagrass populations along environmental gradients.

Signs of local adaptation by genetic selection and isolation promoted by extreme temperature and salinity in the Mediterranean seagrass Posidonia oceanica

“…Clonality assessment, including genetic distance among all samples and number of distinct multilocus lineages (MLLs) for each site, was done using the R package poppr (Kamvar et al, 2015). The genetic distance limit for setting delimitation of clones was determined based on the maximum genetic distance detected between technical replicates as done in a recent study (Ruocco et al, 2022). Based on the results from the clonality assessment, clones as well as technical replicates (i.e.…”

“…This kind of approach (i.e. RAD sequencing) has been widely applied to study evolutionary mechanisms of different marine organisms (Gaither et al, 2015; Hohenlohe et al, 2010; Jahnke et al, 2022; van Oppen et al, 2018) including some recent studies on seagrasses (Phair et al, 2019; 2020; Ruocco et al, 2022). We hypothesize that (i) the high levels of salinity and temperature in the interior of the lagoon have selected the most resistant genotypes favouring the local adaptation of the P. oceanica population to these extreme conditions, (ii) these genotypes manage to survive under conditions that exceed the thresholds of the species through genetic mutations in certain functional loci and/or their high phenotypic plasticity.…”

“…This kind of approach (i.e. RAD sequencing) has been widely applied to study evolutionary mechanisms of different marine organisms (Gaither et al, 2015;Hohenlohe et al, 2010;Jahnke et al, 2022;van Oppen et al, 2018) including some recent studies on seagrasses (Phair et al, 2019;Ruocco et al, 2022).…”

“…light (Dattolo et al, 2017), water quality (Maxwell et al, 2014), nutrients (Pazzaglia et al, 2020), salinity (Tomasello et al, 2009), warming (Marín‐Guirao et al, 2018), among others] and over a wide range of spatial scales [e.g. between sites of the same region (Maxwell et al, 2014), between regions (Tuya et al, 2019), along with depth gradients (Dattolo et al, 2017), latitudinal gradients (Jahnke et al, 2019; Ruocco et al, 2022) and between seas (Nguyen et al, 2020; Pansini et al, 2021; Stipcich et al, 2022)]. It is important to note that conclusions on local adaptation on seagrasses have been derived not only from population genetic data, but also from the comparison of phenotypic responses to environmental stressors among populations.…”

“…To date, knowledge of the genetic basis underlying local adaptation to environmental conditions in seagrasses remains scarce (but see Hughes & Stachowicz, 2004; Ruggiero & Reusch, 2005; Ruocco et al, 2022; Tuya et al, 2021). Moreover, intraspecific variation among populations is often ignored or under‐estimated when assessing specific responses of populations to their surrounding environment, as well as, when predicting potential changes in their future distribution (Hu et al, 2021; Pazzaglia et al, 2021).…”