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11 results for “parentage assignments”
Data from: Validating dispersal distances inferred from autoregressive occupancy models with genetic parentage assignments
1.Dispersal distances are commonly inferred from occupancy data but have rarely been validated. Estimating dispersal from occupancy data is further complicated by imperfect detection and the presence of unsurveyed patches. 2.We compared dispersal distances inferred from seven years of occupancy data for 212 wetlands in a metapopulation of the secretive and threatened California black rail (Laterallus jamaicensis coturniculus) to distances between parent-offspring dyads identified with 16 microsatellites. 3.We used a novel autoregressive multi-season occupancy model that accounted for both unsurveyed patches and imperfect detection to quantify patch isolation using buffer radius (BRM) and incidence function (IFM) connectivity measures at 15 scales (1–10, 15, 20, 25, and 30 km). Connectivity measures were then fit as colonization covariates in occupancy models to estimate a model-averaged dispersal distance. 4.As predicted, colonization was more strongly related to connectivity at small spatial scales (< 10 km). AIC weights were greatest at 7 km for BRM and at 4 km for IFM. 5.Model-averaged dispersal distances (BRM = 7.46 km; IFM = 5.48 km) showed good agreement with the mean (± SE) dispersal distance from 23 parent-offspring dyads (5.58 ± 1.92 km), indicating reasonably accurate mean dispersal distances can be inferred from occupancy data when isolation strongly affects colonization.
Data from: Validating dispersal distances inferred from autoregressive occupancy models with genetic parentage assignments
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SNP array for parentage assignment of the Manila clam, Ruditapes philippinarum
<p>The Manila clam <i>Ruditapes philippinarum</i>, a major cultured shellfish species, is threatened by infection with the microparasite <i>Perkinsus olseni</i>, whose prevalence increases with high water temperatures. Under the current trend of climate change, the already severe effects of this parasitic infection might rapidly increase the frequency of mass mortality events. Treating infectious diseases in bivalves is notoriously problematic, therefore selective breeding for resistance represents a key strategy for mitigating the negative impact of pathogens. A crucial step in initiating selective breeding is the estimation of genetic parameters for traits of interest, which relies on the ability to record parentage and accurate phenotypes in a large number of individuals. Here, to estimate the heritability of resistance against <i>P. olseni</i>, a field experiment mirroring conditions in industrial clam production was set up, a genomic tool was developed for parentage assignment, and parasite load was determined through quantitative PCR.</p> <p>A mixed-family cohort of potentially 1479 clam families was produced in a hatchery by mass spawning of 53 dams and 57 sires. The progenies were seeded in a commercial clam production area in the Venice lagoon, Italy, where high prevalence of <i>P. olseni</i> had previously been reported. Growth and parasite load were monitored every month and, after one year, more than 1000 individuals were collected and DNA and phenotype records.</p> <p>A 245-SNP panel was developed using candidate markers obtained from a pooled sequencing approach on two DNA samples from all the potential parents and from a Venice lagoon clam population. For 246 individuals of the mixed-family F1, sire and dam representation were high (75 and 85%, respectively), indicating a very limited risk of inbreeding. Moderate heritability (0.20 – 0.30) was estimated for growth traits, while parasite load showed high heritability, estimated at 0.52. No significant genetic correlations were found between growth-associated traits and parasite load.</p> <p>Overall, the study shows high potential for selecting clams resistant to parasite<i> </i>load<i>.</i> Breeding for resistance may help limit the negative effects of climate change on clam production, as the prevalence of the parasite is predicted to increase under a future scenario of higher temperatures. Finally, the limited genetic correlation between resistance and growth suggests that breeding programs could incorporate dual selection without negative interactions.</p>
Data from: An empirical comparison of SNPs and microsatellites for parentage and kinship assignment in a wild sockeye salmon (Oncorhynchus nerka) population
Because of their high variability, microsatellites are still considered the marker of choice for studies on parentage and kinship in wild populations. Nevertheless, single nucleotide polymorphisms (SNPs) are becoming increasing popular in many areas of molecular ecology, owing to their high-throughput, easy transferability between laboratories and low genotyping error. An ongoing discussion concerns the relative power of SNPs compared to microsatellites – that is, how many SNP loci are needed to replace a panel of microsatellites? Here, we evaluate the assignment power of 80 SNPs (HE=0.30, 80 independent alleles) and 11 microsatellites (HE =0.85, 194 independent alleles) in a wild population of about 400 sockeye salmon with two commonly used software packages (Cervus3, Colony2) and, for SNPs only, a newly developed software (SNPPIT). Assignment success was higher for SNPs than for microsatellites, especially for parent pairs, irrespective of the method used. Colony2 assigned a larger proportion of offspring to at least one parent than the other methods, though Cervus and SNPPIT detected more parent pairs. Identification of full sib groups without parental information from relatedness measures was possible using both marker systems, though explicit reconstruction of such groups in Colony2 was impossible for SNPs because of computation time. Our results confirm the applicability of SNPs for parentage analyses and refute the predictability of assignment success from the number of independent alleles.
Data from: A comparative assessment of SNP and microsatellite markers for assigning parentage in a socially monogamous bird
Single-nucleotide polymorphisms (SNPs) are preferred over microsatellite markers in many evolutionary studies, but have only recently been applied to studies of parentage. Evaluations of SNPs and microsatellites for assigning parentage have mostly focused on special cases that require a relatively large number of heterozygous loci, such as species with low genetic diversity or with complex social structures. We developed 120 SNP markers from a transcriptome assembled using RNA-sequencing of a songbird with the most common avian mating system—social monogamy. We compared the effectiveness of 97 novel SNPs and six previously described microsatellites for assigning paternity in the black-throated blue warbler, Setophaga caerulescens. We show that the full panel of 97 SNPs (mean Ho = 0.19) was as powerful for assigning paternity as the panel of multiallelic microsatellites (mean Ho = 0.86). Paternity assignments using the two marker types were in agreement for 92% of the offspring. Filtering individual samples by a 50% call rate and SNPs by a 75% call rate maximized the number of offspring assigned with 95% confidence using SNPs. We also found that the 40 most heterozygous SNPs (mean Ho = 0.37) had similar power to assign paternity as the full panel of 97 SNPs. These findings demonstrate that a relatively small number of variable SNPs can be effective for parentage analyses in a socially monogamous species. We suggest that the development of SNP markers is advantageous for studies that require high-throughput genotyping or that plan to address a range of ecological and evolutionary questions.
Data from: A comparative assessment of SNP and microsatellite markers for assigning parentage in a socially monogamous bird
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Data from: An empirical comparison of SNPs and microsatellites for parentage and kinship assignment in a wild sockeye salmon (Oncorhynchus nerka) population
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SNP array for parentage assignment of the Manila clam, Ruditapes philippinarum
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Data from: Using probability modelling and genetic parentage assignment to test the role of local mate availability in mating system variation.
The formal testing of mating system theories with empirical data is important for evaluating the relative importance of different processes in shaping mating systems in wild populations. Here we present a generally applicable probability modelling framework to test the role of local mate availability in determining a population's level of genetic monogamy. We provide a significance test for detecting departures in observed mating patterns from model expectations based on mate availability alone, allowing the presence and direction of behavioural effects to be inferred. The assessment of mate availability can be flexible and in this study it was based on population density, sex ratio and spatial arrangement. This approach provides a useful tool for (1) isolating the effect of mate availability in variable mating systems and (2) in combination with genetic parentage analyses, gaining insights into the nature of mating behaviours in elusive species. To illustrate this modelling approach, we have applied it to investigate the variable mating system of the mountain brushtail possum (Trichosurus cunninghami) and compared the model expectations with the outcomes of genetic parentage analysis over an 18 year study. The observed level of monogamy was higher than predicted under the model. Thus, behavioural traits, such as mate guarding or selective mate choice, may increase the population level of monogamy. We show that combining genetic parentage data with probability modelling can facilitate an improved understanding of the complex interactions between behavioural adaptations and demographic dynamics in driving mating system variation.
Data from: Using probability modelling and genetic parentage assignment to test the role of local mate availability in mating system variation.
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Parentage Assignment in Brown trout strains (Salmo trutta) and their hybrids using microsatellite markers
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