Inferring the demographic history underlying parallel genomic divergence among pairs of parasitic and nonparasitic lamprey ecotypes

Abstract

Understanding the evolutionary mechanisms generating parallel genomic divergence patterns among replicate ecotype pairs remains an important challenge in speciation research. We investigated the genomic divergence between the anadromous parasitic river lamprey (Lampetra fluviatilis) and the freshwater-resident nonparasitic brook lamprey (Lampetra planeri) in nine population pairs displaying variable levels of geographic connectivity. We genotyped 338 individuals with RAD sequencing and inferred the demographic divergence history of each population pair using a diffusion approximation method. Divergence patterns in geographically connected population pairs were better explained by introgression after secondary contact, whereas disconnected population pairs have retained a signal of ancient migration. In all ecotype pairs, models accounting for differential introgression among loci outperformed homogeneous migration models. Generating neutral predictions from the inferred divergence scenarios to detect highly differentiated markers identified greater proportions of outliers in disconnected population pairs than in connected pairs. However, increased similarity in the most divergent genomic regions was found among connected ecotype pairs, indicating that gene flow was instrumental in generating parallelism at the molecular level. These results suggest that heterogeneous genomic differentiation and parallelism among replicate ecotype pairs have partly emerged through restricted introgression in genomic islands.

Genetic basis for variation in salinity tolerance between stickleback ecotypes

“…; Lee ; Rougemont et al . ). Fishes have adapted to most aquatic habitats across a wide range of salinities from freshwater to seawater and are therefore a good model system for studying the genetic basis for adaptation to divergent salinity environments.…”

Comparing Pool‐seq, Rapture, and GBS genotyping for inferring weak population structure: The American lobster (Homarus americanus) as a case study

“…Using large genomic SNP datasets, both methods have shown significant improvement in our capacity to resolve fine-scale population structure compared to microsatellites markers (Ferchaud, Laporte, Perrier, & Bernatchez, 2018;Malenfant, Coltman, & Davis, 2015;Vendrami et al, 2017). Moreover, these methods have enhanced the accuracy of demographic inference (Le Moan, Gagnaire, & Bonhomme, 2016;Rougemont et al, 2017;Shafer, Gattepaille, Stewart, & Wolf, 2015).…”

Genetic Analysis of Larval Dispersal, Gene Flow, and Connectivity

“…Comparing results from different analyses may generate insights or reveal problems inherent in any single approach, particularly for predicting marine connectivity and its implications for fisheries management or the design of networks of MPAs in a rapidly changing environment. However, even though individual-and population-based estimates of connectivity can be inferred from the same data, direct comparisons of migration rates over evolutionary timescales to migration on more recent ecological timescales have been rare (e.g., Pusack et al 2014;D'Aloia et al 2015;Pinsky et al 2016), possibly because gene flow is often too high to expect informative population-based results on the spatial scale at which individual-based methods are most often applied (but see Pinsky et al 2016), and because the types of genetic markers that are best for individual-based methods (microsatellites and SNPs, but see Rougemont et al 2016) are also not ideal for some of the most powerful population-based methods (DNA sequences). In addition to inferences about larval dispersal from genetic data, direct measurements of the impacts of dispersal on demographic processes are likely crucial for 20 demonstrating meaningful demographic connectivity for the purposes of resource management (Waples 1998;Lowe and Allendorf 2010).…”

“…Because ABC methods do not make full use of sequence data (i.e., the coalescent), they typically do not provide estimates of demographic parameters as precise as those from MCMC methods (Beaumont et al 2002). However, the practical advantages of ABC lie in the capability to consider very large genome-wide data sets and to make direct comparisons among complex demographic models defined by the investigator (e.g., Rougemont et al 2016). Alternatively, when estimating migration rates between two or more populations, the joint site frequency spectrum (SFS) can also be used instead of summary statistics.…”