Abstract
We combine kinship estimates with traditional F-statistics to explain contemporary drivers of population genetic differentiation despite high gene flow. We investigate range-wide population genetic structure of the California spiny (or red rock) lobster (Panulirus interruptus) and find slight, but significant global population differentiation in mtDNA (ΦST = 0.006, P = 0.001; Dest_Chao = 0.025) and seven nuclear microsatellites (FST = 0.004, P < 0.001; Dest_Chao = 0.03), despite the species’ 240- to 330-day pelagic larval duration. Significant population structure does not correlate with distance between sampling locations, and pairwise FST between adjacent sites often exceeds that among geographically distant locations. This result would typically be interpreted as unexplainable, chaotic genetic patchiness. However, kinship levels differ significantly among sites (pseudo-F16,988 = 1.39, P = 0.001), and ten of 17 sample sites have significantly greater numbers of kin than expected by chance (P < 0.05). Moreover, a higher proportion of kin within sites strongly correlates with greater genetic differentiation among sites (Dest_Chao, R2 = 0.66, P < 0.005). Sites with elevated mean kinship were geographically proximate to regions of high upwelling intensity (R2 = 0.41, P = 0.0009). These results indicate that P. interruptus does not maintain a single homogenous population, despite extreme dispersal potential. Instead, these lobsters appear to either have substantial localized recruitment or maintain planktonic larval cohesiveness whereby siblings more likely settle together than disperse across sites. More broadly, our results contribute to a growing number of studies showing that low FST and high family structure across populations can coexist, illuminating the foundations of cryptic genetic patterns and the nature of marine dispersal.
Highlights
Determining the temporal and spatial scales of dispersal and gene flow across species’ ranges is essential forOne underutilized approach is the coupling of indirect metrics of gene flow (e.g. F-statistics, Dest_Chao) with more direct measures such as kinship or parentage analyses (e.g. Loiselle et al 1995; Selkoe et al 2006; Buston et al 2009; Christie et al 2010; Palsbøll et al 2010)
There was no pattern of isolation by distance (IBD) in the data set, whether we examined all sampling locations together, or for any of the specific subregions, as described for the Mitochondrial DNA (mtDNA) results (Table S1, Supporting information)
While the agreement between nuclear and mitochondrial markers confirms that the results are not due to statistical artifact, the nature of F-statistics leaves us without a clear indication of what is driving the pattern of genetic differentiation
Summary
Determining the temporal and spatial scales of dispersal and gene flow across species’ ranges is essential forOne underutilized approach is the coupling of indirect metrics of gene flow (e.g. F-statistics, Dest_Chao) with more direct measures such as kinship or parentage analyses (e.g. Loiselle et al 1995; Selkoe et al 2006; Buston et al 2009; Christie et al 2010; Palsbøll et al 2010). One underutilized approach is the coupling of indirect metrics of gene flow (e.g. F-statistics, Dest_Chao) with more direct measures such as kinship or parentage analyses By assessing how alleles are shared among individuals, kinship analyses can elucidate which locations have comparatively little ongoing genetic exchange in situations where low FST values suggest high contemporary population connectivity. This clarification is important because such inferences can be due to historically high migration rates, effective population sizes or measurement error (Hart & Marko 2010; Marko & Hart 2011, 2012; Faurby & Barber 2012)
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