Estimates Of Relatedness Research Articles

Estimating pairwise relatedness in a small sample of individuals

The genetic relatedness between individuals because of their recent common ancestry is now routinely estimated from marker genotype data in molecular ecology, evolutionary biology and conservation studies. The estimators developed for this purpose assume that marker allele freque218 in a population are known without errors. Unfortunately, however, these frequencies, upon which both the definition and the estimation of relatedness are based, are rarely known in reality. Frequently, the only data available in a relatedness analysis are a sample of multilocus genotypes from which both allele frequencies and relatedness must be deduced. Furthermore, because of various constraints, sample sizes of individuals can be quite small (say <50 individuals) in practice. This study shows, for the first time, that the widely used relatedness estimators become severely biased when they use allele frequencies calculated from an extremely small sample (say <10 individuals). The extent of bias depends on the sample size, the (unknown) population allele frequencies, the actual relatedness and the estimators. It also shows that relatedness estimators become even more biased when they use allele frequencies calculated from a sample by omitting a focal pair of individuals whose relatedness is being estimated. This study modifies two estimators to suit small samples and shows, both analytically and by analysing simulated and empirical data, that the two modified estimators are much less biased, more precise and more accurate than the original estimators. These performance advantages of the modified estimators are shown to increase with a decreasing sample size of individuals and with an increasing value of actual relatedness.

A Unified Characterization of Population Structure and Relatedness.

Many population genetic activities, ranging from evolutionary studies to association mapping, to forensic identification, rely on appropriate estimates of population structure or relatedness. All applications require recognition that quantities with an underlying meaning of allelic dependence are not defined in an absolute sense, but instead are made “relative to” some set of alleles other than the target set. The 1984 Weir and Cockerham estimate made explicit that the reference set of alleles was across populations, whereas standard kinship estimates do not make the reference explicit. Weir and Cockerham stated that their estimates were for independent populations, and standard kinship estimates have an implicit assumption that pairs of individuals in a study sample, other than the target pair, are unrelated or are not inbred. However, populations lose independence when there is migration between them, and dependencies between pairs of individuals in a population exist for more than one target pair. We have therefore recast our treatments of population structure, relatedness, and inbreeding to make explicit that the parameters of interest involve the differences in degrees of allelic dependence between the target and the reference sets of alleles, and so can be negative. We take the reference set to be the population from which study individuals have been sampled. We provide simple moment estimates of these parameters, phrased in terms of allelic matching within and between individuals for relatedness and inbreeding, or within and between populations for population structure. A multi-level hierarchy of alleles within individuals, alleles between individuals within populations, and alleles between populations, allows a unified treatment of relatedness and population structure. We expect our new measures to have a wide range of applications, but we note that their estimates are sensitive to rare or private variants: some population-characterization applications suggest exploiting those sensitivities, whereas estimation of relatedness may best use all genetic markers without filtering on minor allele frequency.

Novel efficient genome-wide SNP panels for the conservation of the highly endangered Iberian lynx

BackgroundThe Iberian lynx (Lynx pardinus) has been acknowledged as the most endangered felid species in the world. An intense contraction and fragmentation during the twentieth century left less than 100 individuals split in two isolated and genetically eroded populations by 2002. Genetic monitoring and management so far have been based on 36 STRs, but their limited variability and the more complex situation of current populations demand more efficient molecular markers. The recent characterization of the Iberian lynx genome identified more than 1.6 million SNPs, of which 1536 were selected and genotyped in an extended Iberian lynx sample.MethodsWe validated 1492 SNPs and analysed their heterozygosity, Hardy-Weinberg equilibrium, and linkage disequilibrium. We then selected a panel of 343 minimally linked autosomal SNPs from which we extracted subsets optimized for four different typical tasks in conservation applications: individual identification, parentage assignment, relatedness estimation, and admixture classification, and compared their power to currently used STR panels.ResultsWe ascribed 21 SNPs to chromosome X based on their segregation patterns, and identified one additional marker that showed significant differentiation between sexes. For all applications considered, panels of autosomal SNPs showed higher power than the currently used STR set with only a very modest increase in the number of markers.ConclusionsThese novel panels of highly informative genome-wide SNPs provide more powerful, efficient, and flexible tools for the genetic management and non-invasive monitoring of Iberian lynx populations. This example highlights an important outcome of whole-genome studies in genetically threatened species.

Genetic and morphological divergences between wild and captive-bred populations ofSalmo trutta abanticus

Salmo trutta abanticus is a non-anadromous trout species native to Lake Abant and Seven Lakes in Turkey. A restocking programme by captive breeding was initiated in 1999 to support S. trutta abanticus population. Reared 2-year-old juveniles from randomly caught wild parental individuals in Maçka breeding farm were introduced into Lake Abant. We aimed to compare genetic and morphological divergences between wild- and captive-bred populations using seven microsatellite loci and geometric morphometric measurements. A significant genetic and morphological divergences were detected between all population in Fst and canonical variate analysis based on geometric morphometric with 10 homolog landmark. Eighty-six microsatellites alleles were recorded across loci. Number of private alleles, observed alleles and observed heterozygosity are statistically significant higher in Maçka captive-bred population than Lake Abant and Seven Lakes populations. Of 42 tests, three departures from Hardy–Weinberg equilibrium were detected in all populations after Bonferroni correction. Two pairs of loci (Ssa85 – Str73 and Str73-Str543) in Maçka, one pairs of loci (Ssa85-Str73) in Abant and two pairs of loci (Ssa85-Str60 and Str73-Str543) in Seven Lakes populations show linkage disequilibrium. Population structure analysed with Structure software showed three genetic groups (∆K = 3) in our studied populations. Relatedness estimates show higher mean relatedness values (r = 0.220 ± 0.230) for Maçka captive-breed population than wild populations of Abant Lake and Seven Lakes (r = 0.140 ± 0.210 and r = 0.170 ± 0.200 respectively).

Phylogenetic comparative methods

Phylogenetic comparative methods (PCMs) enable us to study the history of organismal evolution and diversification. PCMs comprise a collection of statistical methods for inferring history from piecemeal information, primarily combining two types of data: first, an estimate of species relatedness, usually based on their genes, and second, contemporary trait values of extant organisms. Some PCMs also incorporate information from geological records, especially fossils, but also other gradual and episodic events in the Earth's history (for example, trait data from fossils or the global oxygen concentration as an independent variable). It is important to note at the outset that PCMs are not concerned with reconstructing the evolutionary relationships among species; this has to do with estimating the phylogeny from genetic, fossil and other data, and a separate set of methods for this process makes up the field of phylogenetics. PCMs as a set of methods are distinct from, but are not completely independent of, phylogenetics. PCMs are used to address the questions: how did the characteristics of organisms evolve through time and what factors influenced speciation and extinction?

Demerelate: calculating interindividual relatedness for kinship analysis based on codominant diploid genetic markers using R.

The Demerelate package offers algorithms to calculate different interindividual relatedness measurements. Three different allele sharing indices, five pairwise weighted estimates of relatedness and four pairwise weighted estimates with sample size correction are implemented to analyse kinship structures within populations. Statistics are based on randomization tests; modelling relatedness coefficients by logistic regression, modelling relatedness with geographic distance by mantel correlation and comparing mean relatedness between populations using pairwise t-tests. Demerelate provides an advance on previous software packages by including some estimators not available in R to date, along with FIS , as well as combining analysis of relatedness and spatial structuring. An UPGMA tree visualizes genetic relatedness among individuals. Additionally, Demerelate summarizes information on data sets (allele vs. genotype frequencies; heterozygosity; FIS values). Demerelate is - to our knowledge - the first R package implementing basic allele sharing indices such as Blouin's Mxy relatedness, the estimator of Wang corrected for sample size (wangxy ), estimators based on Morans I adapted to genetic relatedness as well as combining all estimators with geographic information. The R environment enables users to better understand relatedness within populations due to the flexibility of Demerelate of accepting different data sets as empirical data, reference data, geographical data and by providing intermediate results. Each statistic and tool can be used separately, which helps to understand the suitability of the data for relatedness analysis, and can be easily implemented in custom pipelines.

Embedding of semantic predications

This paper concerns the generation of distributed vector representations of biomedical concepts from structured knowledge, in the form of subject-relation-object triplets known as semantic predications. Specifically, we evaluate the extent to which a representational approach we have developed for this purpose previously, known as Predication-based Semantic Indexing (PSI), might benefit from insights gleaned from neural-probabilistic language models, which have enjoyed a surge in popularity in recent years as a means to generate distributed vector representations of terms from free text. To do so, we develop a novel neural-probabilistic approach to encoding predications, called Embedding of Semantic Predications (ESP), by adapting aspects of the Skipgram with Negative Sampling (SGNS) algorithm to this purpose. We compare ESP and PSI across a number of tasks including recovery of encoded information, estimation of semantic similarity and relatedness, and identification of potentially therapeutic and harmful relationships using both analogical retrieval and supervised learning. We find advantages for ESP in some, but not all of these tasks, revealing the contexts in which the additional computational work of neural-probabilistic modeling is justified.

Single-Step BLUP with Varying Genotyping Effort in Open-Pollinated Picea glauca.

Maximization of genetic gain in forest tree breeding programs is contingent on the accuracy of the predicted breeding values and precision of the estimated genetic parameters. We investigated the effect of the combined use of contemporary pedigree information and genomic relatedness estimates on the accuracy of predicted breeding values and precision of estimated genetic parameters, as well as rankings of selection candidates, using single-step genomic evaluation (HBLUP). In this study, two traits with diverse heritabilities [tree height (HT) and wood density (WD)] were assessed at various levels of family genotyping efforts (0, 25, 50, 75, and 100%) from a population of white spruce (Picea glauca) consisting of 1694 trees from 214 open-pollinated families, representing 43 provenances in Québec, Canada. The results revealed that HBLUP bivariate analysis is effective in reducing the known bias in heritability estimates of open-pollinated populations, as it exposes hidden relatedness, potential pedigree errors, and inbreeding. The addition of genomic information in the analysis considerably improved the accuracy in breeding value estimates by accounting for both Mendelian sampling and historical coancestry that were not captured by the contemporary pedigree alone. Increasing family genotyping efforts were associated with continuous improvement in model fit, precision of genetic parameters, and breeding value accuracy. Yet, improvements were observed even at minimal genotyping effort, indicating that even modest genotyping effort is effective in improving genetic evaluation. The combined utilization of both pedigree and genomic information may be a cost-effective approach to increase the accuracy of breeding values in forest tree breeding programs where shallow pedigrees and large testing populations are the norm.

Turnover and post‐bottleneck genetic structure in a recovering population of Peregrine Falcons Falco peregrinus

Dispersal is a process that increases genetic diversity and genetic connectivity of populations. We studied the turnover rate of breeding adults and genetic population structure to estimate dispersal in Peregrine Falcons in Finland. We used relatedness estimates among Finnish Peregrine Falcons over a 5‐year period, genotyping over 500 nestlings with 10 microsatellite loci to reveal the rate of turnover. Our results reveal a high turnover rate (21.7%) that does not seem to be correlated with the breeding success of the previous year. The extent of population genetic structure and diversity, and possible signs of the population crash during the 1970s, was assessed with a reduced dataset, excluding relatives. We found genetic diversity to be similar to previously studied falcon populations (expected heterozygosity of 0.581) and no population genetic structuring among our sampled populations. We did not find a genetic imprint of the past population bottleneck that the Finnish Peregrine population experienced. We conclude that high dispersal rates are likely to have contributed to maintaining genetic diversity across the landscape, by mixing individuals within the species’ distribution in Finland and thus preventing genetic structuring and negative effects associated with the population decline in the 1970s.

The Identification of a 1916 Irish Rebel: New Approach for Estimating Relatedness From Low Coverage Homozygous Genomes

Thomas Kent was an Irish rebel who was executed by British forces in the aftermath of the Easter Rising armed insurrection of 1916 and buried in a shallow grave on Cork prison’s grounds. In 2015, ninety-nine years after his death, a state funeral was offered to his living family to honor his role in the struggle for Irish independence. However, inaccuracies in record keeping did not allow the bodily remains that supposedly belonged to Kent to be identified with absolute certainty. Using a novel approach based on homozygous single nucleotide polymorphisms, we identified these remains to be those of Kent by comparing his genetic data to that of two known living relatives. As the DNA degradation found on Kent’s DNA, characteristic of ancient DNA, rendered traditional methods of relatedness estimation unusable, we forced all loci homozygous, in a process we refer to as “forced homozygote approach”. The results were confirmed using simulated data for different relatedness classes. We argue that this method provides a necessary alternative for relatedness estimations, not only in forensic analysis, but also in ancient DNA studies, where reduced amounts of genetic information can limit the application of traditional methods.

Genetic variation and fine-scale population structure in American pikas across a human-modified landscape

Natural resource extraction can represent a major human modification to the landscape. Habitat reclamation is becoming an increasingly important strategy for abating the loss of biodiversity associated with these developments; however, the demographic and genetic consequences of colonizing artificial habitat remain unknown in many species. Here, we investigated the genetic consequences of landscape modifications for the American pika (Ochotona princeps) relative to two major developments in British Columbia, Canada: a large open-pit copper mine (Highland Valley Copper) under partial reclamation and a bisecting major highway (97C). We assessed microsatellite genotypic data for 109 individuals across 15 sites located either within the mine on artificial habitat or on adjacent natural habitat both north and south of the highway. There were no significant differences in levels of heterozygosity, allelic richness or inbreeding between natural (n = 7) and artificial sites (n = 8). However, pikas residing on artificial habitat exhibited significantly higher relatedness estimates. Bayesian clustering analyses revealed two distinct genetic units corresponding to north and south of the highway, with further substructure detected in the south. Likewise, high genetic friction was detected in the central region of the area, largely corresponding to the highway and modified landscape associated with the mine. At a finer scale, pairwise estimates of differentiation and migration rates suggest little gene flow may be occurring among sites across the sampling area, with some evidence for directional migration from artificial to natural sites. Overall, artificial habitat has been successful in promoting occupancy for American pikas, however, barriers to gene flow likely associated with resource extraction and road construction limit connectivity across the landscape.

Fine-Scale Genetic Structure in Female Mule Deer (Odocoileus hemionus)

Abstract. Fine-scale genetic structure in animal populations can have important consequences for evolutionary processes and can influence conservation and management decisions. Cervids often live in matrilineal social groups, and this spatial grouping can create fine-scale genetic structure among females. We used DNA and radio-location data at Fort Carson Military Reservation in south central Colorado, USA, to determine whether female mule deer (Odocoileus hemionus) living in close proximity were more likely to be related. Spatial data were obtained over an 18-month period using data transmitted from GPS collars. Average positions for each animal were correlated with relatedness estimates calculated using 7 microsatellite loci. We found significant spatial autocorrelation for females at distances ≤1000 m, which suggests that females were frequently philopatric. In addition, females appeared to occasionally disperse over relatively longer distances, as we found evidence of related females separated by dist...

Swinger: a user‐friendly computer program to establish captive breeding groups that minimize relatedness without pedigree information

Captive breeding programmes are often a necessity for the continued persistence of a population or species. They typically have the goal of maintaining genetic diversity and minimizing inbreeding. However, most captive breeding programmes have been based on the assumption that the founding breeders are unrelated and outbred, even though insitu anthropogenic impacts often mean these founders may have high relatedness and substantial inbreeding. In addition, polygamous group-breeding species in captivity often have uncertain pedigrees, making it difficult to select the group composition for subsequent breeding. Molecular-based estimates of relatedness and inbreeding may instead be used to select breeding groups (≥two individuals) that minimize relatedness and filter out inbred individuals. swinger constructs breeding groups based on molecular estimates of relatedness and inbreeding. The number of possible combinations of breeding groups quickly becomes intractable by hand. swinger was designed to overcome this major issue in ex situ conservation biology. The user can specify parameters within swinger to reach breeding solutions that suit the mating system of the target species and available resources. We provide evidence of the efficiency of the software with an empirical example and using simulations. The only data required are a typical molecular marker data set, such as a microsatellite or SNP data set, from which estimates of inbreeding and pairwise relatedness may be obtained. Such molecular data sets are becoming easier to gather from non-model organismswithnext-generation sequencing technology. swinger is an open-source software with a user-friendly interface and isavailable at http://www.molecularecology.flinders.edu.au/molecular-ecology-lab/software/swinger/swinger/ and https://github.com/Yuma248/Swinger.

Evaluating semantic similarity between Chinese biomedical terms through multiple ontologies with score normalization: An initial study

BackgroundSemantic similarity estimation significantly promotes the understanding of natural language resources and supports medical decision making. Previous studies have investigated semantic similarity and relatedness estimation between biomedical terms through resources in English, such as SNOMED-CT or UMLS. However, very limited studies focused on the Chinese language, and technology on natural language processing and text mining of medical documents in China is urgently needed. Due to the lack of a complete and publicly available biomedical ontology in China, we only have access to several modest-sized ontologies with no overlaps. Although all these ontologies do not constitute a complete coverage of biomedicine, their coverage of their respective domains is acceptable. In this paper, semantic similarity estimations between Chinese biomedical terms using these multiple non-overlapping ontologies were explored as an initial study. MethodsTypical path-based and information content (IC)-based similarity measures were applied on these ontologies. From the analysis of the computed similarity scores, heterogeneity in the statistical distributions of scores derived from multiple ontologies was discovered. This heterogeneity hampers the comparability of scores and the overall accuracy of similarity estimation. This problem was addressed through a novel language-independent method by combining semantic similarity estimation and score normalization. A reference standard was also created in this study. ResultsCompared with the existing task-independent normalization methods, the newly developed method exhibited superior performance on most IC-based similarity measures. The accuracy of semantic similarity estimation was enhanced through score normalization. This enhancement resulted from the mitigation of heterogeneity in the similarity scores derived from multiple ontologies. ConclusionWe demonstrated the potential necessity of score normalization when estimating semantic similarity using ontology-based measures. The results of this study can also be extended to other language systems to implement semantic similarity estimation in biomedicine.

Phylogenomic re-assessment of the thermophilic genus Geobacillus

Geobacillus is a genus of Gram-positive, aerobic, spore-forming obligate thermophiles. The descriptions and subsequent affiliations of the species in the genus have mostly been based on polyphasic taxonomy rules that include traditional sequence-based methods such as DNA–DNA hybridization and comparison of 16S rRNA gene sequences. Currently, there are fifteen validly described species within the genus. The availability of whole genome sequences has provided an opportunity to validate and/or re-assess these conventional estimates of genome relatedness. We have applied whole genome approaches to estimate the phylogenetic relatedness among the sixty-three Geobacillus strains for which genome sequences are currently publicly available, including the type strains of eleven validly described species. The phylogenomic metrics AAI (Average Amino acid Identity), ANI (Average Nucleotide Identity) and dDDH (digital DNA–DNA hybridization) indicated that the current genus Geobacillus is comprised of sixteen distinct genomospecies, including several potentially novel species. Furthermore, a phylogeny constructed on the basis of the core genes identified from the whole genome analyses indicated that the genus clusters into two monophyletic clades that clearly differ in terms of nucleotide base composition. The G+C content ranges for clade I and II were 48.8–53.1% and 42.1–44.4%, respectively. We therefore suggest that the Geobacillus species currently residing within clade II be considered as a new genus.

Within-group relatedness is correlated with colony-level social structure and reproductive sharing in a social fish.

In group-living species, the degree of relatedness among group members often governs the extent of reproductive sharing, cooperation and conflict within a group. Kinship among group members can be shaped by the presence and location of neighbouring groups, as these provide dispersal or mating opportunities that can dilute kinship among current group members. Here, we assessed how within-group relatedness varies with the density and position of neighbouring social groups in Neolamprologus pulcher, a colonial and group-living cichlid fish. We used restriction site-associated DNA sequencing (RADseq) methods to generate thousands of polymorphic SNPs. Relative to microsatellite data, RADseq data provided much tighter confidence intervals around our relatedness estimates. These data allowed us to document novel patterns of relatedness in relation to colony-level social structure. First, the density of neighbouring groups was negatively correlated with relatedness between subordinates and dominant females within a group, but no such patterns were observed between subordinates and dominant males. Second, subordinates at the colony edge were less related to dominant males in their group than subordinates in the colony centre, suggesting a shorter breeding tenure for dominant males at the colony edge. Finally, subordinates who were closely related to their same-sex dominant were more likely to reproduce, supporting some restraint models of reproductive skew. Collectively, these results demonstrate that within-group relatedness is influenced by the broader social context, and variation between groups in the degree of relatedness between dominants and subordinates can be explained by both patterns of reproductive sharing and the nature of the social landscape.

SSRs, SNPs and DArTs comparison on estimation of relatedness and genetic parameters’ precision from a small half-sib sample population of Eucalyptus grandis

Simple sequence repeats (SSR) are the most widely used molecular markers for relatedness inference due to their multi-allelic nature and high informativeness. However, there is a growing trend toward using high-throughput and inter-specific transferable single-nucleotide polymorphisms (SNP) and Diversity Arrays Technology (DArT) in forest genetics owing to their wide genome coverage. We compared the efficiency of 15 SSRs, 181 SNPs and 2816 DArTs to estimate the relatedness coefficients, and their effects on genetic parameters’ precision, in a relatively small data set of an open-pollinated progeny trial of Eucalyptus grandis (Hill ex Maiden) with limited relationship from the pedigree. Both simulations and real data of Eucalyptus grandis were used to study the statistical performance of three relatedness estimators based on co-dominant markers. Relatedness estimates in pairs of individuals belonging to the same family (related) were higher for DArTs than for SNPs and SSRs. DArTs performed better compared to SSRs and SNPs in estimated relatedness coefficients in pairs of individuals belonging to different families (unrelated) and showed higher ability to discriminate unrelated from related individuals. The likelihood-based estimator exhibited the lowest root mean squared error (RMSE); however, the differences in RMSE among the three estimators studied were small. For the growth traits, heritability estimates based on SNPs yielded, on average, smaller standard errors compared to those based on SSRs and DArTs. Estimated relatedness in the realized relationship matrix and heritabilities can be accurately inferred from co-dominant or sufficiently dense dominant markers in a relatively small E. grandis data set with shallow pedigree.

Evolutionary potential in the Alpine: trait heritabilities and performance variation of the dwarf willow Salix herbacea from different elevations and microhabitats.

Alpine ecosystems are seriously threatened by climate change. One of the key mechanisms by which plants can adapt to changing environmental conditions is through evolutionary change. However, we still know little about the evolutionary potential in wild populations of long‐lived alpine plants. Here, we investigated heritabilities of phenological traits, leaf size, and performance traits in natural populations of the long‐lived alpine dwarf shrub Salix herbacea using relatedness estimates inferred from SSR (Simple Sequence Repeat) markers. Salix herbacea occurs in early‐ and late‐snowmelt microhabitats (ridges and snowbeds), and we assessed how performance consequences of phenological traits and leaf size differ between these microhabitats in order to infer potential for evolutionary responses. Salix herbacea showed low, but significant, heritabilities of leaf size, clonal and sexual reproduction, and moderate heritabilities of phenological traits. In both microhabitats, we found that larger leaves, longer intervals between snowmelt and leaf expansion, and longer GDD (growing‐degree days) until leaf expansion resulted in a stronger increase in the number of stems (clonal reproduction). In snowbeds, clonal reproduction increased with a shorter GDD until flowering, while the opposite was found on ridges. Furthermore, the proportion of flowering stems increased with GDD until flowering in both microhabitats. Our results suggest that the presence of significant heritable variation in morphology and phenology might help S. herbacea to adapt to changing environmental conditions. However, it remains to be seen if the rate of such an evolutionary response can keep pace with the rapid rate of climate change.

A comparison of DMET Plus microarray and genome-wide technologies by assessing population substructure.

The capacity of the Affymetrix drug metabolism enzymes and transporters (DMET) Plus pharmacogenomics genotyping chip to estimate population substructure and cryptic relatedness was evaluated. The results were compared with estimates using genome-wide HapMap data for the same individuals. For 301 unrelated individuals, spanning three continental populations and one admixed population, genotypic data were collected using the Affymetrix DMET Plus microarray. Genome-wide data on these individuals were obtained from HapMap release 3. Population substructure was assessed using Eigenstrat and ADMIXTURE software for both platforms. Cryptic relatedness was explored by inbreeding coefficient estimation. Nonparametric tests were used to determine correlations of the analytical results of the two genotyping platforms. Principal components analysis identified population substructure for both datasets, with 15.8 and 16.6% of the total variance explained in the first two principal components for DMET Plus and HapMap data, respectively. ADMIXTURE results correctly identified four subpopulations within each dataset. Nonparametric rank correlations indicated significant associations between analyses with an average ρ=0.7272 (P<10) across the three continental populations and ρ=0.4888 for the admixed population. Concordance correlation coefficients (average ρc=0.9693 across all four subpopulations) strongly indicate concordance between ADMIXTURE results. Inbreeding coefficients were slightly inflated (16 individuals>0.15) using DMET Plus data and no cryptic relatedness was indicated using HapMap data. The inflated inbreeding estimation could be because of the limited number of markers provided by DMET as a random sample of 1832 markers from HapMap also yielded inflated estimates of cryptic relatedness (39 individuals>0.15). Furthermore, use of single nucleotide polymorphisms located in genes involved in metabolism and transport may have different allele frequencies in subpopulations than single nucleotide polymorphisms sampled from the whole genome. The DMET Plus pharmacogenomics genotyping chip is effective in quantifying population substructure across the three continental populations and inferring the presence of an admixed population. On the basis of our results, these microarrays offer sufficient depth for covariate adjustment of population substructure in genomic association studies.

Evidence of the phenotypic expression of a lethal recessive allele under inbreeding in a wild population of conservation concern.

Deleterious recessive alleles that are masked in outbred populations are predicted to be expressed in small, inbred populations, reducing both individual fitness and population viability. However, there are few definitive examples of phenotypic expression of lethal recessive alleles under inbreeding conditions in wild populations. Studies that demonstrate the action of such alleles, and infer their distribution and dynamics, are required to understand their potential impact on population viability and inform management responses. The Scottish population of red-billed choughs (Pyrrhocorax pyrrhocorax), which currently totals <60 breeding pairs and is of major conservation concern, has recently been affected by lethal blindness in nestlings. We used family data to show that the pattern of occurrence of blindness within and across affected families that produced blind nestlings was exactly 0·25, matching that expected given a single-locus autosomal lethal recessive allele. Furthermore, the observed distribution of blind nestlings within affected families did not differ from that expected given Mendelian inheritance of such an allele. Relatedness estimates showed that individuals from affected families were not more closely related to each other than they were to individuals from unaffected families that did not produce blind nestlings. Blind individuals tended to be less heterozygous than non-blind individuals, as expected if blindness was caused by the expression of a recessive allele under inbreeding. However, there was no difference in the variance in heterozygosity estimates, suggesting that some blind individuals were relatively outbred. These results suggest carriers of the blindness allele may be widely distributed across contemporary families rather than restricted to a single family lineage, implying that the allele has persisted across multiple generations. Blindness occurred at low frequency (affecting 1·6% of observed nestlings since 1981). However, affected families had larger initial brood sizes than unaffected families. Such high fecundity of carriers of a lethal recessive allele might reflect overdominance, potentially reducing purging and increasing allele persistence probability. We thereby demonstrate the phenotypic expression of a lethal recessive allele in a wild population of conservation concern, and provide a general framework for inferring allele distribution and persistence and informing management responses.