Find research datasets worth reusing

Data from: Prevalence characteristics of cervical human papillomavirus (HPV) genotypes in the Taizhou area, China: a cross-sectional study of 37 967 women from the general population

Objectives: High-risk human papillomaviruses (hrHPVs) are highly prevalent worldwide, and HPV genotypes differ between geographical regions; however, sexually transmitted HPV may lead to cervical carcinogenesis. The objective of this cross-sectional study was to estimate the prevalence characteristics of cervical HPV genotypes in Taizhou, Southeast China. Setting and participants: A population-based sample of 37 967 eligible women (median age: 41.6; range: 15–90 years) visiting the Taizhou ENZE Medical Center in Taizhou (2012–2016) was analysed. HPV genotyping was performed on the collected specimens using a GP5+/bioGP6+-PCR/MPG assay by Luminex 200, which simultaneously identifies 27 different HPV genotypes and the β-globin gene (internal control). Results: The overall HPV infection rate was 22.8% in the Taizhou-based population, and the prevalence of high-risk HPV, low-risk HPV and mixed high-risk and low-risk HPV infection was 14.2%, 5.7% and 3.0%, respectively. The most prevalent genotypes were HPV52 (19.7%), 16 (11.9%), 58 (11.5%), 39 (7.2%), 18 (6.6%) and 56 (5.6%). The rate of multiple-type HPV infection was 5.7% in the whole population, and the HPV52+58, HPV16+52 and HPV16+18 mixed genotypes were most common in women with multiple infections. The age-specific HPV prevalence showed a bimodal curve, with a first peak below the age of 21 years (41.6%), followed by a second peak in the age group of 56–60 years (28.5%). Moreover, the HPV infection rate differed significantly between the outpatient and physical examination groups (24.0% vs 19.5%, p<0.0001). Further data comparisons showed that the distribution of HPV genotypes varied markedly between the two groups. Conclusions: Data from this study could be valuable for HPV-based cervical cancer screening efforts in certain areas, support the local vaccination programme in the Taizhou region and facilitate future diagnosis and treatment of HPV diseases.

opencc-zeroDec 2012View details →

Data from: Using semidefinite programming to optimize unequal deployment of genotypes to a clonal seed orchard

Tree breeders must often consider the conservation of genetic diversity, while at the same time, maximizing response to selection. In the case of seed orchards, the buyer of seed wants maximum performance, while satisfying a restriction, sometimes legislated, on the diversity deployed to the forest. Optimal selection will not completely avoid kinship but rather maximize gain while imposing a constraint on average relatedness. Here, we present the application of semidefinite programming (SDP) as a flexible approach to optimize the deployment of genotypes to a clonal seed orchard. We formulate the selection problem as an SDP, where average breeding value is to be maximized, while imposing constraints on relatedness, as well as maximum and minimum contributions from each candidate. An open-source solver, SDPA, was embedded into a tool designed to make the optimization of seed orchards by SDP simple and flexible. Case studies optimizing seed orchards for Scots pine and loblolly pine illustrate how this flexibility can be used to impose additional constraints on the scion material available from some candidate genotypes and optimize selection even when related candidates have varying degrees of coancestry among them. Additional situations where SDP can be employed are discussed.

Data from: Reliable effective number of breeders/adult census size ratios in seasonal-breeding species: opportunity for integrative demographic inferences based on capture-mark-recapture data and multilocus genotypes

The ratio of the effective number of breeders (Nb) to the adult census size (Na), Nb/ Na, approximates the departure from the standard capacity of a population to maintain genetic diversity in one reproductive season. This information is relevant for assessing population status, understanding evolutionary processes operating at local scales and unraveling how life-history traits affect these processes. However, our knowledge on Nb/Na ratios in nature is limited because estimation of both parameters is challenging. The sibship frequency (SF) method is adequate for reliable Nb estimation because it is based on sibship and parentage reconstruction from genetic marker data, thereby providing demographic inferences that can be compared with field-based information. In addition, capture-mark-recapture (CMR) robust design methods are well suited for Na estimation in seasonal-breeding species. We used tadpole genotypes of three pond-breeding amphibian species (Epidalea calamita, Hyla molleri and Pelophylax perezi, n = 73-96 single-cohort tadpoles / species genotyped at 15-17 microsatellite loci) and candidate parental genotypes (n = 94-300 adults / species) to estimate Nb by the SF method. To assess the reliability of Nb estimates, we compared sibship and parentage inferences with field-based information and checked for the convergence of results in replicated subsampled analyses. Finally, we used CMR data from a 6-year monitoring program to estimate annual Na in the three species and calculate the Nb/Na ratio. Reliable ratios were obtained for E. calamita (Nb/Na = 0.18-0.28) and P. perezi (0.5), but in H. molleri Na could not be estimated and genetic information proved insufficient for reliable Nb estimation. Integrative demographic studies taking full advantage of SF and CMR methods can provide accurate estimates of the Nb/Na ratio in seasonal-breeding species. Importantly, the SF method provides results that can be readily evaluated for reliability. This represents a good opportunity for obtaining robust demographic inferences with wide applications for evolutionary and conservation research.

Data from: Genomewide genotyping of a novel Mexican Chile Pepper collection illuminates the history of landrace differentiation after Capsicum annuum L. domestication

Studies of genetic diversity among phenotypically distinct crop landraces improve our understanding of fruit evolution and genome structure under domestication. Chile peppers (Capsicum spp. L.) are economically valuable and culturally important species, and extensive phenotypic variation among landraces exists in southern Mexico, a center of C. annuum diversity. We collected 103 chile pepper seed accessions from 22 named landraces across 27 locations in southern Mexico. We genotyped these accessions with genotyping-by-sequencing (GBS), yielding 32,623 filtered single-nucleotide polymorphisms. Subsequently, we genotyped 32 additional C. annuum accessions from a global collection for comparison to the Mexican collection. Within the Mexican collection, genetic assignment analyses showed clear genetic differentiation between landraces and clarified the unique nature of the Tusta landrace. Further clustering analyses indicated that the largest fresh-use Chile de Agua, and dry-use Costeño landraces were part of separate clades, indicating that these two landraces likely represent distinct populations. The global accessions showed considerable admixture and limited clustering, which may be due to the collapse of use-type divisions outside of Central America. The separation of the Mexican landraces in part by fruit morphology related to use, highlights the relevance of this use-type morphological diversity for plant breeders and the utility of fruit development variation for evolutionary biologists.

Data from: An SSR based approach incorporating a novel algorithm for identification of rare maize genotypes facilitates criteria for landrace conservation in Mexico

Since maize was domesticated in Mexico around 9000 years ago, local farmers have selected and maintained seed stocks with particular traits and adapted to local conditions. In the present day many of these landraces are still cultivated, however increased urbanization and migration from rural areas implies a risk that this invaluable maize germplasm may be lost. In order to implement an efficient mechanism of conservation in situ, the diversity of these landrace populations must be estimated. Development of a method to select the minimum number of samples that would include the maximum number of alleles and identify germplasm harboring rare combinations of particular alleles will also safeguard the efficient ex-situ conservation of this germplasm. To reach this goal a strategy based on SSR analysis and a novel algorithm to define a minimum collection and rare genotypes using landrace populations from Puebla State, Mexico was developed as a "proof of concept" for methodology that could be extended to all maize landrace populations in Mexico and eventually to other native crops. The SSR based strategy using bulked DNA samples allows rapid processing of large numbers of samples and can be set up in most laboratories equipped for basic molecular biology. Therefore, continuous monitoring of landrace populations locally could easily be carried out. This methodology can now be applied to support incentives for small farmers for the in situ conservation of these traditional cultivars.

opencc-zeroSep 2019View details →

An interaction between host and microbe genotypes determines colonization success of a key bumble bee gut microbiota member

There has been a proliferation of studies demonstrating an organism's health is influenced by its microbiota. However, factors influencing beneficial microbe colonization and the evolution of these relationships remain understudied relative to host-pathogen interactions. Vertically transmitted beneficial microbes are predicted to show high levels of specificity in colonization, including genotype matching, which may transpire through coevolution. We investigate how host and bacterial genotypes influence colonization of a core coevolved microbiota member in bumble bees. The hindgut colonizing Snodgrassella alvi confers direct benefits, but, as an early colonizer, also facilitates the further development of a healthy microbiota. Due to predominantly vertical transmission promoting tight evolution between colonization factors of bacteria and host lineages, we predict that genotype-by-genotype interactions will determine successful colonization. Germ-free adult bees from seven bumble bee colonies (host genotypic units) were inoculated with one of six genetically distinct strains of S. alvi. Subsequent colonization within host-genotype and microbe-genotype combinations ranged from zero to one hundred percent, and an interaction between host and microbe genotypes determined colonization success. This novel finding of a genotype-by-genotype interaction determining colonization in an animal host-beneficial microbe system has implications for the ecological and evolutionary dynamics of host and microbe, including associated host-fitness benefits.

Data from: Population structure, relatedness and ploidy levels in an apple gene bank revealed through genotyping-by-sequencing

In recent years, new genome-wide marker systems have provided highly informative alternatives to low density marker systems for evaluating plant populations. To date, most apple germplasm collections have been genotyped using low-density markers such as simple sequence repeats (SSRs), whereas only a few have been explored using high-density genome-wide marker information. We explored the genetic diversity of the Pometum gene bank collection (University of Copenhagen, Denmark) of 349 apple accessions using over 15,000 genome-wide single nucleotide polymorphisms (SNPs) and 15 SSR markers, in order to compare the strength of the two approaches for describing population structure. We found that 119 accessions shared a clonal relationship with at least one other accession in the collection, resulting in the identification of 272 (78%) unique accessions. Of these unique accessions, over half (52%) share a first-degree relationship with at least one other accession. There is therefore a high degree of clonal and family relatedness in the Danish apple gene bank. We find significant genetic differentiation between Malus domestica and its supposed primary wild ancestor, M. sieversii, as well as between accessions of Danish origin and all others. Overall, we found strong concordance between analyses based on the genome-wide SNPs and the 15 SSR loci. However, we argue that GBS is superior to traditional SSR approaches because it allowed the estimation of ploidy levels that were in accordance with flow cytometry results, and can be further exploited in genome-wide association studies (GWAS). Finally, we compare GBS with SSR for the purposes of characterizing a diverse apple gene bank and discuss the advantages and constraints of the two approaches.

Data from: Evidence for selection-by-environment but not genotype-by-environment interactions for fitness-related traits in a wild mammal population

How do environmental conditions influence selection and genetic variation in wild populations? There is widespread evidence for selection-by-environment interactions (S*E), but we reviewed studies of natural populations estimating the extent of genotype-by-environment interactions (G*E) in response to natural variation in environmental conditions, and found that evidence for G*E appears to be rare within single populations in the wild. Studies estimating the simultaneous impact of environmental variation on both selection and genetic variation are especially scarce. Here, we used 24 years of data collected from a wild Soay sheep population to quantify how an important environmental variable, population density, impacts upon (1) selection through annual contribution to fitness and (2) expression of genetic variation, in six morphological and life-history traits: body weight; hind leg length; parasite burden; horn length; horn growth; and testicular circumference. Our results supported the existence of S*E: selection was stronger in years of higher population density in all traits apart from horn growth, with directional selection being stronger under more adverse conditions. Quantitative genetic models revealed significant additive genetic variance for body weight, leg length, parasite burden, horn length and testes size, but not for horn growth or our measure of annual fitness. However, random regression models found variation between individuals in their responses to the environment in only three traits, and did not support the presence of G*E for any trait. Our analyses of St Kilda Soay sheep data thus concurs with our cross-study review that, while natural environmental variation within a population can profoundly alter the strength of selection on phenotypic traits, there is less evidence for its effect on the expression of genetic variance in the wild.

opencc-zeroDec 2015View details →

Data from: Genotypic diversity mitigates negative effects of density on plant performance: a field experiment and life-cycle analysis of common evening primrose Oenothera biennis

1.Genotypic diversity in plant populations is known to enhance plant performance and ecosystem function. Nonetheless, the effect of genotypic diversity has rarely been examined across a population's lifecycle despite the expectation that changing conditions, such as population density, will alter the benefits of diversity. 2.We simultaneously manipulated a component of genotypic diversity (richness, the number of genotypes) and density of common evening primrose Oenothera biennis to address the consequences for herbivory and lifetime fitness in a two-year field experiment that spanned seed germination to life-time fruit production. We genotyped >1100 seedlings with microsatellite DNA markers to determine realized diversity and density in plots sown with O.biennis seeds. Our design achieved quantitative variation in plant density and diversity, with one to 44 individuals established in field plots and two to eight genotypes per polyculture plot (based on microsatellite analysis of reproductive plants). 3.We found a strong interaction between seed density and genetic diversity, with germination and establishment being 24% higher in genetic polycultures than monocultures, but only at low seed density. At high seed density, the opposite pattern emerged, with polycultures having 12% fewer individuals established than monocultures. Initial effects of emergence on plot density persisted through to the fruiting stage. 4.Higher plant densities result in increased mortality, decreased probability of reproduction, decreased plant height, and lower levels of life-time fruit production per plant. Increasing genotypic diversity increased the probability of reproduction overall, and showed a significant interaction with plant density mitigating the negative effects of high density on individual height and lifetime fruit production. 5.Synthesis. Plant density and genotypic diversity interacted from the very earliest stages of seed germination and establishment of O. biennis. This effect persisted over the two-year life-cycle of plants, and genotypic diversity buffered against the negative fitness consequences of high plant density. These results imply a dynamic interplay between the long-held paradigm of density effects in plant ecology and the genetic structure of populations.

Data from: Genotyping-by-sequencing for estimating relatedness in non-model organisms: avoiding the trap of precise bias

There has been remarkably little attention to using the high resolution provided by genotyping-by-sequencing (i.e. RADseq and similar methods) datasets for assessing relatedness in wildlife populations. A major hurdle is the genotyping error, especially allelic dropout, often found in this type of dataset that could lead to downward-biased, yet precise, estimates of relatedness. Here we assess the applicability of genotyping-by-sequencing datasets for relatedness inferences given their relatively high genotyping error rates. Individuals of known relatedness were simulated under genotyping error, allelic dropout, and missing data scenarios based on an empirical ddRAD dataset, and their true relatedness was compared to that estimated by seven relatedness estimators. We found that an estimator chosen through such analyses can circumvent the influence of genotyping error, with the estimator of Ritland (1996) shown to be unaffected by allelic dropout and to be the most accurate when there is genotyping error. We also found that the choice of estimator should not rely solely on the strength of correlation between estimated and true relatedness as a strong correlation does not necessarily mean estimates are close to true relatedness. We also demonstrated how even a large SNP dataset with genotyping error (allelic dropout or otherwise) or missing data still performs better than a perfectly genotyped microsatellite dataset of tens of markers. The simulation-based approach used here can be easily implemented by others on their own genotyping-by-sequencing datasets to confirm the most appropriate and powerful estimator for their dataset.

opencc-zeroDec 2014View details →

Data from: Divergence in DNA photorepair efficiency among genotypes from contrasting UV radiation environments in nature

Populations of organisms routinely face abiotic selection pressures, and a central goal of evolutionary biology is to understand the mechanistic underpinnings of adaptive phenotypes. Ultraviolet radiation (UVR) is one of earth's most pervasive environmental stressors, potentially damaging DNA in any organism exposed to solar radiation. We explored mechanisms underlying differential survival following UVR exposure in genotypes of the water flea Daphnia melanica derived from natural ponds of differing in UVR intensity. The UVR tolerance of a D. melanica genotype from a high-UVR habitat depended on the presence of visible and UV-A light wavelengths necessary for photoenzymatic repair of DNA damage, a repair pathway widely shared across the tree of life. We then measured the acquisition and repair of cyclobutane pyrimidine dimers, the primary form of UVR-caused DNA damage, in D. melanica DNA following experimental UVR exposure. We demonstrate that genotypes from high-UVR habitats repair DNA damage faster than genotypes from low-UVR habitats in the presence of visible and UV-A radiation necessary for photoenzymatic repair, but not in dark treatments. Because differences in repair rate only occurred in the presence of visible and UV-A radiation, we conclude that differing rates of DNA repair, and therefore differential UVR tolerance, are a consequence of variation in photoenzymatic repair efficiency. We then rule out a simple gene expression hypothesis for the molecular basis of differing repair efficiency, as expression of the CPD photolyase gene photorepair did not differ among D. melanica lineages, both in the presence and absence of UVR.

opencc-zeroAug 2019View details →

Data from: Attack of the PCR clones: rates of clonality have little effect on RAD-seq genotype calls

Interpretation of high-throughput sequence data requires an understanding of how decisions made during bioinformatic data processing can influence results. One source of bias that is often cited is PCR clones (or PCR duplicates). PCR clones are common in restriction site associated sequencing (RAD-seq) datasets, which are increasingly being used for molecular ecology. To determine the influence PCR clones and the bioinformatic handling of clones have on genotyping, we evaluate four RAD-seq datasets. Datasets were compared before and after clones were removed to estimate the number of clones present in RAD-seq data, quantify how often the presence of clones in a dataset cause genotype calls to change compared to when clones were removed, investigate the mechanisms that lead to genotype call changes, and test if clones bias heterozygosity estimates. Our RAD-seq datasets contained 30 – 60% PCR clones, but 95% of RAD-tags had five or fewer clones. Relatively few genotypes changed once clones were removed (5-10%), and the vast majority of these changes (98%) were associated with genotypes switching from a called to no-call state or vice versa. PCR clones had a larger influence on genotype calls in individuals with low read depth but appeared to influence genotype calls at all loci similarly. Removal of PCR clones reduced the number of called genotypes by 2% but had almost no influence on estimates of heterozygosity. As such, while steps should be taken to limit PCR clones during library preparation, PCR clones are likely not a substantial source of bias for most RAD-seq studies.

opencc-zeroDec 2011View details →

Data from: Detecting small-scale genotype-environment interactions in apomictic dandelion (Taraxacum officinale) populations

Studies of genotype × environment interactions (G×E) and local adaptation provide critical tests of natural selection's ability to counter opposing forces such as gene flow. Such studies may be greatly facilitated in asexual species, given the possibility for experimental replication at the level of true genotypes (rather than populations) and the possibility of using molecular markers to assess genotype-environment associations in the field (neither of which is possible for most sexual species). Here we tested for G×E in asexual dandelions (Taraxacum officinale) by subjecting six genotypes to experimental drought, mown, and benign (control) conditions, and subsequently using microsatellites to assess genotype-environment associations in the field. We found strong G×E, with genotypes that performed poorly under benign conditions showing the highest performance under stressful conditions (drought or mown). Our six focal genotypes comprise >80% of plants in local populations. The most common genotype in the field showed its highest relative performance under mown conditions (the most common habitat in our study area), and almost all plants of this genotype in the field were found growing in mowed lawns. Genotypes performing best under benign experimental conditions were found most frequently in unmown conditions in the field. These results are strongly indicative of local adaptation at a very small scale, with unmown microsites of only a few square meters typically embedded within larger mown lawns. By studying an asexual species we were able to map genotypes with known ecological characteristics to environments with high spatial precision.

Data from: A high density SNP chip for genotyping great tit (Parus major) populations and its application to studying the genetic architecture of exploration behaviour

High density SNP microarrays ('SNP chips') are a rapid, accurate and efficient method for genotyping several hundred thousand polymorphisms in large numbers of individuals. While SNP chips are routinely used in human genetics and in animal and plant breeding, they are less widely used in evolutionary and ecological research. In this paper we describe the development and application of a high density Affymetrix Axiom chip with around 500 000 SNPs, designed to perform genomics studies of great tit (Parus major) populations. We demonstrate that the per-SNP genotype error rate is well below 1% and that the chip can also be used to identify structural or copy number variation (CNVs). The chip is used to explore the genetic architecture of exploration behaviour (EB), a personality trait that has been widely studied in great tits and other species. No SNPs reached genome-wide significance, including at DRD4, a candidate gene. However, EB is heritable and appears to have a polygenic architecture. Researchers developing similar SNP chips may note: (i) SNPs previously typed on alternative platforms are more likely to be converted to working assays, (ii) detecting SNPs by more than one pipeline, and in independent datasets, ensures a high proportion of working assays, (iii) allele frequency ascertainment bias is minimised by performing SNP discovery in individuals from multiple populations and (iv) samples with the lowest call rates tend to also have the greatest genotyping error rates.

Data from: The effect of rhizosphere microbes outweighs host plant genotype in reducing insect herbivory

Rhizosphere microbes affect plant performance, including plant resistance against insect herbivores; yet, a direct comparison of the relative influence of rhizosphere microbes vs. plant genotype on herbivory levels and on metabolites related to defense is lacking. In the crucifer Boechera stricta, we tested the effects of rhizosphere microbes and plant genotype on herbivore resistance, the primary metabolome, and select secondary metabolites. Plant populations differed significantly in the concentrations of 6 glucosinolates (GLS), secondary metabolites known to provide herbivore resistance in the Brassicaceae. The population with lower GLS levels experienced ~60% higher levels of aphid (Aphis spp.) attack; no association was observed between GLS and damage by a second herbivore, flea beetles (Altica spp.). Rhizosphere microbiome (disrupted vs. intact native microbiome) had no effect on plant GLS concentrations. However, aphid number and flea beetle damage were respectively ~3-fold and 7-fold higher among plants grown in the disrupted vs. intact native microbiome treatment. These differences may be attributable to shifts in primary metabolic pathways previously implicated in host defense against herbivores, including increases in pentose and glucoronate interconversion among plants grown with an intact microbiome. Further, native microbiomes with distinct community composition (as estimated from 16s rRNA amplicon sequencing) differed 2-fold in their effect on host plant susceptibility to aphids. The findings suggest that rhizosphere microbes, including distinct native microbiomes, can play a greater role than plant genotype in defense against insect herbivores, and act through metabolic mechanisms independent of plant genotype.

opencc-zeroDec 2011View details →

Data from: Estimation of genotyping error rate from repeat genotyping, unintentional recaptures and known parent-offspring comparisons in 16 microsatellite loci for brown rockfish (Sebastes auriculatus)

Genotyping errors are present in almost all genetic data and can affect biological conclusions of a study, particularly for studies based on individual identification and parentage. Many statistical approaches can incorporate genotyping errors, but usually need accurate estimates of error rates. Here, we used a new microsatellite data set developed for brown rockfish (Sebastes auriculatus) to estimate genotyping error using three approaches: (i) repeat genotyping 5% of samples, (ii) comparing unintentionally recaptured individuals and (iii) Mendelian inheritance error checking for known parent–offspring pairs. In each data set, we quantified genotyping error rate per allele due to allele drop-out and false alleles. Genotyping error rate per locus revealed an average overall genotyping error rate by direct count of 0.3%, 1.5% and 1.7% (0.002, 0.007 and 0.008 per allele error rate) from replicate genotypes, known parent–offspring pairs and unintentionally recaptured individuals, respectively. By direct-count error estimates, the recapture and known parent–offspring data sets revealed an error rate four times greater than estimated using repeat genotypes. There was no evidence of correlation between error rates and locus variability for all three data sets, and errors appeared to occur randomly over loci in the repeat genotypes, but not in recaptures and parent–offspring comparisons. Furthermore, there was no correlation in locus-specific error rates between any two of the three data sets. Our data suggest that repeat genotyping may underestimate true error rates and may not estimate locus-specific error rates accurately. We therefore suggest using methods for error estimation that correspond to the overall aim of the study (e.g. known parent–offspring comparisons in parentage studies).

opencc-zeroDec 2013View details →

Data from: The magnitude of local adaptation under genotype-dependent dispersal

Dispersal moves individuals from patches where their immediate ancestors were successful to sites where their genotypes are untested. As a result, dispersal generally reduces fitness, a phenomenon known as "migration load." The strength of migration load depends on the pattern of dispersal and can be dramatically lessened or reversed when individuals move preferentially toward patches conferring higher fitness. Evolutionary ecologists have long modeled nonrandom dispersal, focusing primarily on its effects on population density over space, the maintenance of genetic variation, and reproductive isolation. Here, we build upon previous work by calculating how the extent of local adaptation and the migration load are affected when individuals differ in their dispersal rate in a genotype-dependent manner that alters their match to their environment. Examining a one-locus, two-patch model, we show that local adaptation occurs through a combination of natural selection and adaptive dispersal. For a substantial portion of parameter space, adaptive dispersal can be the predominant force generating local adaptation. Furthermore, genetic load may be largely averted with adaptive dispersal whenever individuals move before selective deaths occur. Thus, to understand the mechanisms driving local adaptation, biologists must account for the extent and nature of nonrandom, genotype-dependent dispersal, and the potential for adaptation via spatial sorting of genotypes.

opencc-zeroDec 2012View details →

Data from: Reconstructing paternal genotypes to infer patterns of sperm storage and sexual selection in the hawksbill turtle

Postcopulatory sperm storage can serve a range of functions, including ensuring fertility, allowing delayed fertilization and facilitating sexual selection. Sperm storage is likely to be particularly important in wide-ranging animals with low population densities, but its prevalence and importance in such taxa, and its role in promoting sexual selection, are poorly known. Here, we use a powerful microsatellite array and paternal genotype reconstruction to assess the prevalence of sperm storage and test sexual selection hypotheses of genetic biases to paternity in one such species, the critically endangered hawksbill turtle, Eretmochelys imbricata. In the majority of females (90.7%, N = 43), all offspring were sired by a single male. In the few cases of multiple paternity (9.3%), two males fertilized each female. Importantly, the identity and proportional fertilization success of males were consistent across all sequential nests laid by individual females over the breeding season (up to five nests over 75 days). No males were identified as having fertilized more than one female, suggesting that a large number of males are available to females. No evidence for biases to paternity based on heterozygosity or relatedness was found. These results indicate that female hawksbill turtles are predominantly monogamous within a season, store sperm for the duration of the nesting season and do not re-mate between nests. Furthermore, females do not appear to be using sperm storage to facilitate sexual selection. Consequently, the primary value of storing sperm in marine turtles may be to uncouple mating and fertilization in time and avoid costly re-mating.

opencc-zeroDec 2014View details →

Data from: Genetic parameters in subtropical pine F1 hybrids: heritabilities, between-trait correlations and genotype-by-environment interactions

Growth and stem straightness traits of 29 Pinus caribaea var. hondurensis × Pinus tecunumanii (PCH × PTEC) and 26 P. caribaea var. hondurensis × Pinus oocarpa (PCH × POOC) hybrid pair-crosses plus a total of 16 intraspecific families were assessed at ages 5, 8 and 15 years from planting at two sites. The PCH × PTEC hybrid was the most productive, yielding 37 % more than a Pinus elliottii local control and was 21 % superior to either parental species in DBH growth. PCH × POOC hybrid was, on average, 16 % superior to either parental species for DBH. Narrow-sense heritability estimates were low to moderate for growth traits (average of 0.27) and stem straightness (0.16). The estimated additive genetic correlations between growth traits and ages within traits were high (>0.8) and positive, providing confidence in early selection based on diameter at breast height. The high proportion of estimated additive genetic variance compared to dominance variance in the F1 pine hybrids suggests that breeding strategies that maximize the use of additive genetic variance may be effective. The ranking of the 11 PCH parents based on general hybridizing ability predictions (estimated breeding values as hybrids) was somewhat inconsistent between PTEC and POOC hybrid crosses for all traits (r 9 d.f. = 0.38–0.45; p ∼0.15–0.25). There was no evidence of practically important G × E interaction for the hybrids except for PCH × PTEC height growth. This study suggests that a single, multi-hybrid breeding population seems appropriate in Zimbabwe if the trial sites are representative of the planting target zone.