Data from: RAD genotyping reveals fine-scale genetic structuring and provides powerful population assignment in a widely distributed marine species, the American lobster (Homarus americanus).

Deciphering genetic structure and inferring connectivity in marine species
have been challenging due to weak genetic differentiation and limited
resolution offered by traditional genotypic methods. The main goal of this
study was to assess how a population genomics framework could help
delineate the genetic structure of the American lobster (Homarus
americanus) throughout much of the species’ range and increase the
assignment success of individuals to their location of origin. We
genotyped 10 156 filtered SNPs using RAD sequencing to delineate genetic
structure and perform population assignment for 586 American lobsters
collected in 17 locations distributed across a large portion of the
species’ natural distribution range. Our results revealed the existence of
a hierarchical genetic structure, first separating lobsters from the
northern and southern part of the range (FCT = 0.0011; P-value = 0.0002)
and then revealing a total of 11 genetically distinguishable populations
(mean FST = 0.00185; CI: 0.0007–0.0021, P-value < 0.0002),
providing strong evidence for weak, albeit fine-scale population
structuring within each region. A resampling procedure showed that
assignment success was highest with a subset of 3000 SNPs having the
highest FST. Applying Anderson's (Molecular Ecology Resources, 2010,
10, 701) method to avoid ‘high-grading bias’, 94.2% and 80.8% of
individuals were correctly assigned to their region and location of
origin, respectively. Lastly, we showed that assignment success was
positively associated with sample size. These results demonstrate that
using a large number of SNPs improves fine-scale population structure
delineation and population assignment success in a context of weak genetic
structure. We discuss the implications of these findings for the
conservation and management of highly connected marine species,
particularly regarding the geographic scale of demographic independence.