isolated while the other one shows high genetic similarity to downstream populations. There are indications of different spawning sites as reflected in genetic structuring among parr from different creeks. We used >3000 SNPs on a subsample and find that the SNPs largely confirm the allozyme pattern but give considerably lower F ST values, and potentially indicate further structuring within populations. This type of complex genetic substructuring over microgeographical scales might be more common than anticipated and needs to be considered in conservation management.
Developing genomic insights is challenging in nonmodel species for which resources are often scarce and prohibitively costly. Here, we explore the potential of a recently established approach using Pool‐seq data to generate a de novo genome assembly for mining exons, upon which Pool‐seq data are used to estimate population divergence and diversity. We do this for two pairs of sympatric populations of brown trout (Salmo trutta): one naturally sympatric set of populations and another pair of populations introduced to a common environment. We validate our approach by comparing the results to those from markers previously used to describe the populations (allozymes and individual‐based single nucleotide polymorphisms [SNPs]) and from mapping the Pool‐seq data to a reference genome of the closely related Atlantic salmon (Salmo salar). We find that genomic differentiation (FST) between the two introduced populations exceeds that of the naturally sympatric populations (FST = 0.13 and 0.03 between the introduced and the naturally sympatric populations, respectively), in concordance with estimates from the previously used SNPs. The same level of population divergence is found for the two genome assemblies, but estimates of average nucleotide diversity differ (trueπ¯ ≈ 0.002 and trueπ¯ ≈ 0.001 when mapping to S. trutta and S. salar, respectively), although the relationships between population values are largely consistent. This discrepancy might be attributed to biases when mapping to a haploid condensed assembly made of highly fragmented read data compared to using a high‐quality reference assembly from a divergent species. We conclude that the Pool‐seq‐only approach can be suitable for detecting and quantifying genome‐wide population differentiation, and for comparing genomic diversity in populations of nonmodel species where reference genomes are lacking.
Sympatric populations are conspecific populations that coexist spatially. They are of interest in evolutionary biology by representing the potential first steps of sympatric speciation and are important to identify and monitor in conservation management. Reviewing the literature pertaining to sympatric populations, we find that most cases of sympatry appear coupled to phenotypic divergence, implying ease of detection. In comparison, phenotypically cryptic, sympatric populations seem rarely documented. We explore the statistical power for detecting population mixtures from genetic marker data, using commonly applied tests for heterozygote deficiency (i.e., Wahlund effect) and the structure software, through computer simulations. We find that both tests are efficient at detecting population mixture only when genetic differentiation is high, sample size and number of genetic markers are reasonable and the sympatric populations happen to occur in similar proportions in the sample. We present an approximate expression based on these experimental factors for the lower limit of F , beyond which power for structure collapses and only the heterozygote-deficiency tests retain some, although low, power. The findings suggest that cases of cryptic sympatry may have passed unnoticed in population genetic screenings using number of loci typical of the pre-genomics era. Hence, cryptic sympatric populations may be more common than hitherto thought, and we urge more attention being diverted to their detection and characterization.
This is an open access article under the terms of the Creat ive Commo ns Attri butio n-NonCo mmerc ial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
Sympatric populations occur in many freshwater fish species; such populations are typically detected through morphological distinctions that are often coupled to food niche and genetic separations. In salmonids, trophic and genetically separate sympatric populations have been reported in landlocked Arctic char, whitefish and brown trout. In Arctic char and brown trout rare cases of sympatric, genetically distinct populations have been detected based on genetic data alone, with no apparent morphological differences, that is "cryptic" structuring. It remains unknown whether such cryptic, sympatric structuring can be coupled to food niche separation. Here, we perform an extensive screening for trophic divergence of two genetically divergent, seemingly cryptic, sympatric brown trout populations documented to remain in stable sympatry over several decades in two interconnected, tiny mountain lakes in a nature reserve in central Sweden. We investigate body shape, body length, gill raker metrics, breeding status and diet (stomach content analysis and stable isotopes) in these populations. We find small significant differences for body shape, body size and breeding status, and no evidence of food niche separation between these two populations. In contrast, fish in the two lakes differed in body shape, diet, and nitrogen and carbon isotope signatures despite no genetic difference between lakes.These genetically divergent populations apparently coexist using the same food resources and showing the same adaptive plasticity to the local food niches of the two separate lakes. Such observations have not been reported previously but may be more common than recognised as genetic screenings are necessary to detect the structures. K E Y W O R D Sbody shape, geometric morphometrics, gill rakers, population genetic structure, stable isotopes, stomach content 1
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