Incomplete Pedigree Research Articles

Genetic analysis and family screening for dilated cardiomyopathy: a retrospective analysis of the stepwise pedigree approach

Aims This study aimed to assess the practicality of using a stepwise pedigree-based approach to differentiate between familial and sporadic Dilated Cardiomyopathy (DCM), while also considering timing of the genetic analysis. The analysis includes an examination of the extent to which complete family investigations were conducted in real-world scenarios as well as the length of the investigation. Methods The stepwise pedigree approach involved conducting a comprehensive family history spanning 3 to 4 generations, reviewing medical records of relatives, and conducting clinical screening using echocardiography and electrocardiogram on first-degree relatives. Familial DCM was diagnosed when at least 2 family members were found to have DCM, and genetic analysis was considered as an option. This study involved a manual review of all DCM investigations conducted at the Centre of Cardiovascular Genetics at Umeå University Hospital, where the stepwise pedigree approach has been employed since 2007. Results The investigation process had a mean duration of 643 days (95% CI 560.5–724.9). Of the investigations preformed, 94 (68%) were complete, 12 (9%) were ongoing, and 33 (24%) were prematurely terminated and thus incomplete. At the conclusion of the investigations, 55 cases (43%) were classified as familial DCM, 50 (39%) as sporadic DCM, and 22 (18%) remained unassessed due to incomplete pedigrees. Among the familial cases, genetic verification was achieved in 40%. Conclusion The stepwise pedigree approach is time consuming, and the investigations are often incomplete which may suggest that a more direct approach to genetic analysis, may be warranted.

Genetic characterization of a captive marmoset (Callithrix jacchus) colony using genotype-by-sequencing.

The marmoset is a fundamental nonhuman primate model for the study of aging, neurobiology, and many other topics. Genetic management of captive marmoset colonies is complicated by frequent chimerism in the blood and other tissues, a lack of tools to enable cost-effective, genome-wide interrogation of variation, and historic mergers and migrations of animals between colonies. We implemented genotype-by-sequencing (GBS) of hair follicle derived DNA (a minimally chimeric DNA source) of 82 marmosets housed at the Southwest National Primate Research Center (SNPRC). Our primary goals were the genetic characterization of our marmoset population for pedigree verification and colony management and to inform the scientific community of the functional genetic makeup of this valuable resource. We used the GBS data to reconstruct the genetic legacy of recent mergers between colonies, to identify genetically related animals whose relationships were previously unknown due to incomplete pedigree information, and to show that animals in the SNPRC colony appear to exhibit low levels of inbreeding. Of the >99,000 single-nucleotide variants (SNVs) that we characterized, >9800 are located within gene regions known to harbor pathogenic variants of clinical significance in humans. Overall, we show the combination of low-resolution (sparse) genotyping using hair follicle DNA is a powerful strategy for the genetic management of captive marmoset colonies and for identifying potential SNVs for the development of biomedical research models.

Unraveling inbreeding patterns and selection signals in Alpine Grey cattle

Inbreeding plays a crucial role in livestock breeding, influencing genetic diversity and phenotypic traits. Genomic data have helped address limitations posed by incomplete pedigrees, providing deeper insights into breed genetic diversity. This study assesses inbreeding levels via pedigree and genomic approaches and analyzes old and recent inbreeding using runs of homozygosity (ROH), and selection signals in Alpine Grey cattle. Pedigree data from 165 575 individuals, analyzed with INBUPGF90 software, computed inbreeding coefficients. Genomic-based coefficients derived from PLINK v1.9. or DetectRUNS R package analyses of 1 180 individuals’ genotypes. Common single nucleotide polymorphisms within ROH pinpointed genomic regions, aggregating into “ROH islands” indicative of selection pressure. Overlaps with USCS Genome Browser unveiled gene presence. Moderate correlations (0.20–0.54) existed between pedigree and genomic coefficients, with most genomic estimators having higher (>0.8) correlation values. Inbreeding averaged 0.04 in < 8 Mb ROH segments, and 0.03 in > 16 Mb segments; > 90% of ROHs were < 8 Mb, indicating ancient inbreeding prevalence. Recent inbreeding proved less detrimental than in cosmopolitan breeds. Two major ROH islands on chromosomes 6 and 7 harbored genes linked to immune response, disease resistance (PYURF, HERC3), and fertility (EIF4EBP3, SRA1). This study underscores the need for detailed inbreeding analyses to understand genetic characteristics and historical changes in local breeds like Alpine Grey cattle. Genomic insights, especially from ROH, facilitated overcoming pedigree limitations, illuminating breed genetic diversity. Our findings reveal ancient inbreeding's enduring genetic impact and ROH islands potential for selective sweeps, elucidating traits in Alpine Grey cattle.

Application of the Investigator Argus X-12 QS Kit and the Famlinkx Software for Solving Complex Kinship Forensic Genetics Cases in Colombia: Case Report

X-chromosome short tandem repeats (X-STRs) genotyping is a powerful ¬tool in forensic genetics for resolving intricate kinship cases due to its distinctive inheritance pattern. It proves particularly valuable in scenarios where the application of autosomal (A-STR) and Y-chromosomal STR (Y-STR) markers falls short in addressing such cases, especially those involving complex situations and kinship analyses encompassing extensive and incomplete pedigrees. The recent advancement and implementation of the Argus X-12 QS kit along with the FamilinkX software for X-STR analysis have facilitated the resolution of forensic cases that were formerly inconclusive or not received by the laboratory due to their high complexity. This article delineates seven intricate cases of kinship and identification conducted at the Forensic Genetics Laboratory of the National Institute of Legal Medicine and Forensic Sciences in Bogotá, Colombia, in instances where autosomal STRs yielded non-conclusive or weak likelihood ratio (LR) values, the combination of the Argus X-12 QS kit and the FamilinkX software proved instrumental in elucidating and enhancing LR values, thereby leading to conclusive outcomes. The article details a case involving the confirmation of the identity of a body retrieved from water, which was subsequently returned to the institute by its relatives for identification. It also encompasses cases involving maternal half-siblings, complex pedigrees with paternal half-aunts, and others. In each scenario, the total LR was estimated by combining the LR of autosomal STRs (LR AS-STR) with the LR of X-STRs (LR X-STR), utilizing the population frequency database specific to Colombia. Additionally, the LRs of X-STRs obtained using population frequency data from Colombia were compared with those from Mexico. The data derived from both the Mexican and Colombian populations exhibited a high degree of similarity. The collective LR values substantiate the efficacy of X-STR markers, particularly in resolving cases of maternal half-siblings. The analysis underscores the robust informativeness of the 12 X-STR loci examined in the context of forensic testing

Improving the efficiency of multi-location field trials with complete and incomplete relationship information

The increasingly cost-efficient availability of ‘omics’ data has led to the development of a rich framework for predicting the performance of non-phenotyped selection candidates in recent years. The improvement of phenotypic analyses by using pedigree and/or genomic relationship data has however received much less attention, albeit it has shown large potential for increasing the efficiency of early generation yield trials in some breeding programs. The aim of this study was accordingly to assess the possibility to enhance phenotypic analyses of multi-location field trials with complete relationship information as well as when merely incomplete pedigree and/or genomic relationship information is available for a set of selection candidates. For his purpose, four winter bread wheat trial series conducted in Eastern and Western Europe were used to determine the experimental efficiency and accuracy of different resource allocations with a varying degree of relationship information. The results showed that modelling relationship between the selection candidates in the analyses of multi-location trial series was up to 20% more efficient than employing routine analyses, where genotypes are assumed to be unrelated. The observed decrease in efficiency and accuracy when reducing the testing capacities was furthermore less pronounced when modelling relationship information, even in cases when merely partial pedigree and/or genomic information was available for the phenotypic analyses. Exploiting complete and incomplete relationship information in both preliminary yield trials and multi-location trial series has thus large potential to optimize resource allocations and increase the selection gain in programs that make use of various predictive breeding methods.

Evaluation of Genetic Diversity in Dog Breeds Using Pedigree and Molecular Analysis: A Review

Domestic dogs are important for many economic and social reasons, and they have become a well-known model species for human disease. According to research, dog breeds exhibit significant levels of inbreeding and genetic diversity loss, decreasing the population’s ability to adapt in certain conditions, and indicating the need of conservation strategies. Before the development of molecular markers, pedigree information was used for genetic diversity management. In recent years, genomic tools are frequently applied for accurate estimation of genetic diversity and improved genetic conservation due to incomplete pedigrees and pedigree errors. The most frequently used molecular markers include PCR-based microsatellite markers (STRs) and DNA sequencing-based single-nucleotide polymorphism markers (SNP). The aim of this review was to highlight genetic diversity studies on dog breeds conducted using pedigree and molecular markers, as well as the importance of genetic diversity conservation in increasing the adaptability and survival of dog breed populations.

Single-step genomic BLUP with many metafounders.

Single-step genomic BLUP (ssGBLUP) model for routine genomic prediction of breeding values is developed intensively for many dairy cattle populations. Compatibility between the genomic (G) and the pedigree (A) relationship matrices remains an important challenge required in ssGBLUP. The compatibility relates to the amount of missing pedigree information. There are two prevailing approaches to account for the incomplete pedigree information: unknown parent groups (UPG) and metafounders (MF). unknown parent groups have been used routinely in pedigree-based evaluations to account for the differences in genetic level between groups of animals with missing parents. The MF approach is an extension of the UPG approach. The MF approach defines MF which are related pseudo-individuals. The MF approach needs a Γ matrix of the size number of MF to describe relationships between MF. The UPG and MF can be the same. However, the challenge in the MF approach is the estimation of Γ having many MF, typically needed in dairy cattle. In our study, we present an approach to fit the same amount of MF as UPG in ssGBLUP with Woodbury matrix identity (ssGTBLUP). We used 305-day milk, protein, and fat yield data from the DFS (Denmark, Finland, Sweden) Red Dairy cattle population. The pedigree had more than 6 million animals of which 207,475 were genotyped. We constructed the preliminary gamma matrix (Γ pre ) with 29MF which was expanded to 148MF by a covariance function (Γ 148). The quality of the extrapolation of the Γ pre matrix was studied by comparing average off-diagonal elements between breed groups. On average relationships among MF in were 1.8% higher than in Γ pre . The use of Γ 148 increased the correlation between the G and A matrices by 0.13 and 0.11 for the diagonal and off-diagonal elements, respectively. [G]EBV were predicted using the ssGTBLUP and Pedigree-BLUP models with the MF and UPG. The prediction reliabilities were slightly higher for the ssGTBLUP model using MF than UPG. The ssGBLUP MF model showed less overprediction compared to other models.

The necessity of considering founder kinships in conservation breeding programs

AbstractConservation breeding programs pursue the double objective of preserving genetic diversity and producing individuals to support in situ conservation measures. Genetic management and monitoring are commonly based on pedigree analyses and are therefore dependent on the pedigree quality and the underlying assumption that founders of the captive population are neither inbred nor related to each other or to the captive population. Should founders be related, this assumption may lead to an overestimation of genetic diversity and an underestimation of inbreeding in captivity. In this study, we examined the effects of the founder assumption on estimates of genetic diversity by combining three approaches: (1) computer simulations of pedigrees of theoretical captive populations and their associated in situ source populations, (2) analysis of pedigrees of real conservation breeding programs and (3) microsatellite‐based computation of kinship among founders from a captive population of houbara bustard. The theoretical approach revealed that the captive population's average mean kinship Mk increases linearly with founder average Mk. The bias in Mk due to the founder assumption was strongly related to the effective size of the source population and to pedigree quality while remaining critical after 25 generations of captivity. Results based on real populations were consistent with theoretical ones and confirmed the overestimation of genetic diversity in captive populations. Overall, our results indicate that under situations classically encountered in conservation breeding programs (e.g. small and isolated source population, incomplete pedigrees), estimates of genetic diversity are potentially highly overestimated, challenging the genetic management of captive populations of species of conservation concern.

Reduced relative fitness in hatchery-origin Pink Salmon in two streams in Prince William Sound, Alaska.

Previous studies generally report that hatchery‐origin Pacific Salmon (Oncorhynchus spp.) have lower relative reproductive success (RRS) than their natural‐origin counterparts. We estimated the RRS of Pink Salmon (O. gorbuscha) in Prince William Sound (PWS), Alaska using incomplete pedigrees. In contrast to other RRS studies, Pink Salmon have a short freshwater life history, freshwater habitats in PWS are largely unaltered by development, and sampling was conducted without the aid of dams or weirs resulting in incomplete sampling of spawning individuals. Pink Salmon released from large‐scale hatchery programs in PWS have interacted with wild populations for more than 15 generations. Hatchery populations were established from PWS populations but have subsequently been managed as separate broodstocks. Gene flow is primarily directional, from hatchery strays to wild populations. We used genetic‐based parentage analysis to estimate the RRS of a single generation of stray hatchery‐origin Pink Salmon in two streams, and across the odd‐ and even‐year lineages. Despite incomplete sampling, we assigned 1745 offspring to at least one parent. Reproductive success (RS), measured as sampled adult offspring that returned to their natal stream, was significantly lower for hatchery‐ vs. natural‐origin parents in both lineages, with RRS ranging from 0.03 to 0.47 for females and 0.05 to 0.86 for males. Generalized linear modeling for the even‐year lineage indicated that RRS was lower for hatchery‐origin fish, ranging from 0.42 to 0.60, after accounting for sample date (run timing), sample location within the stream, and fish length. Our results strongly suggest that hatchery‐origin strays have lower fitness in the wild. The consequences of reduced RRS on wild productivity depend on whether the mechanisms underlying reduced RRS are environmentally driven, and likely ephemeral, or genetically driven, and likely persistent across generations.

Extended Pedigrees of Apple Cultivars from the University of Minnesota Breeding Program Elucidated Using SNP Array Markers

Apple (Malus ×domestica Borkh.) breeding at the University of Minnesota (UMN) has been ongoing continuously since 1908 when staff originally planted thousands of seedlings from open-pollinated (OP) seeds collected from regional orchards. The first cultivar from the program, ‘Minnehaha’, was introduced in 1920 and several others from these OP seeds followed over the next 3 decades. Controlled crosses were initiated in 1916, and until the time of this publication, 28 cultivars have been introduced. Historical records of parentage, as recorded by staff in notebooks and in 20th-century publications, have been used to inform breeding decisions but might be incorrect as indicated by earlier explorations of parentage using simple sequence repeat (SSR) markers. Our objective was to elucidate parentage and extended pedigrees of all available cultivars introduced from the UMN apple breeding program using evaluations of Mendelian errors and shared haplotype length information based on data from single nucleotide polymorphism (SNP) arrays. Sixteen of the 21 cultivars introduced before ‘Honeycrisp’ (1991) had incorrect or incomplete pedigrees that are now at least partially elucidated. These include the two most important regional cultivars in the 20th century: ‘Haralson’ (parents: ‘Malinda’ and ‘Wealthy’) and ‘Fireside’ (parents: ‘Wealthy’ and ‘Northwest Greening’). ‘Wealthy’, a widely grown cultivar in the United States in the late 19th and early 20th centuries, was a frequent parent of older UMN cultivars. ‘Malinda’ was a less frequent parent than indicated by breeding records. ‘Duchess of Oldenburg’ (synonym ‘Borowitsky’) was revealed as an ancestor of overwhelming importance in the UMN breeding program. It was an ancestor of 27 of the 28 UMN cultivars, including as a parent of two cultivars, and a grandparent of 15 cultivars, including ‘Honeycrisp’.

Three easy fixes for sire use can enhance genetic progress in community-based breeding programmes.

We analysed options to optimize the use of sires in sheep and goat community-based breeding programmes (CBBP) for three scenarios occurring under field conditions: premature sale of selection candidates, fixed service periods of selected sires and incomplete sire pedigrees. The first scenario was studied by looking at the outcome of combinations of selection pressures in successive selection stages. A compromise of early sale of sire candidates and genetic progress can be obtained by selecting in two stages, such that selection pressure in the first stage is chosen in terms of achieving an acceptable selection potential after the second stage. Simulations showed the dependency of this compromise on selection accuracies and correlation between selection criteria. For a typical sheep CBBP, only 20% of the top three months weighting male lambs need to be retained to achieve 80% of the potential selection differential on six months weight. For the second scenario, two alternatives to fixed service periods were analysed. When across-age BLUP EBVs are not available, individual sires can be programmed to stay in service according to their initial ranking. In typical sheep, CBBPs genetic progress can be increased by about 9% over response to selection with optimum fixed sire service periods. When BLUP EBVs are available, a simulated retrospective analyses of across-age selection of sires in two current sheep CBBPs increased more than twofold the average breeding values actually observed. Thirdly, we studied the benefit of considering possible sires and their mating probabilities when estimating BLUP breeding values instead of setting such sires as unknown. In a current goat CBBP with up to three possible sires included in the pedigree, the accuracy of breeding values nears the accuracy when sires are known and are higher than accuracies when sires are unknown or when possible sires are ignored.

ESTIMATE OF GENETIC COMPONENTS OF BIRTH WEIGHT USING MULTI-BREED MODELS WITH DIFFERENT PEDIGREE STRUCTURES IN MESTIZO SHEEP

The objectives of this paper were to verify the influence of the multi-breed model and pedigree structure in the estimates of the genetic components to birth weight in a mestizo herd. Using 1234 birth weight records in two ways, one dataset with complete pedigree information (n = 1028) and another with incomplete pedigree information (n = 1234). The pedigree was composed for 10 sires, 366 and 448 dams for complete and incomplete pedigree, respectively. Used for analysis the maximum restricted likelihood method about the animal model, considering the birth weight trait, for a dataset with or not complete pedigree, used the WOMBAT program. The direct heritability coefficients in both datasets did not present large difference, 0.06 and 0.09 to best models in the complete and incomplete pedigree, respectively. However, in the incomplete pedigree, the maternal heritability was 0.29. The residual variance, which on the best model of the dataset with complete pedigree presented 0.51 and 0.35 for the best model of the dataset with incomplete pedigree. Concluding, we find the influence of de multi-breed model only in the dataset with complete pedigree, that considered the direct and breed effects. In the dataset with incomplete pedigree, the better model was that considered the direct and maternal additive effects.

Personalized genealogical history of UK individuals inferred from biobank-scale IBD segments

BackgroundThe genealogical histories of individuals within populations are of interest to studies aiming both to uncover detailed pedigree information and overall quantitative population demographic histories. However, the analysis of quantitative details of individual genealogical histories has faced challenges from incomplete available pedigree records and an absence of objective and quantitative details in pedigree information. Although complete pedigree information for most individuals is difficult to track beyond a few generations, it is possible to describe a person’s genealogical history using their genetic relatives revealed by identity by descent (IBD) segments—long genomic segments shared by two individuals within a population, which are identical due to inheritance from common ancestors. When modern biobanks collect genotype information for a significant fraction of a population, dense genetic connections of a person can be traced using such IBD segments, offering opportunities to characterize individuals in the context of the underlying populations. Here, we conducted an individual-centric analysis of IBD segments among the UK Biobank participants that represent 0.7% of the UK population.ResultsWe made a high-quality call set of IBD segments over 5 cM among all 500,000 UK Biobank participants. On average, one UK individual shares IBD segments with 14,000 UK Biobank participants, which we refer to as “relatives.” Using these segments, approximately 80% of a person’s genome can be imputed. We subsequently propose genealogical descriptors based on the genetic connections of relative cohorts of individuals sharing at least one IBD segment and show that such descriptors offer important information about one’s genetic makeup, personal genealogical history, and social behavior. Through analysis of relative counts sharing segments at different lengths, we identified a group, potentially British Jews, who has a distinct pattern of familial expansion history. Finally, using the enrichment of relatives in one’s neighborhood, we identified regional variations of personal preference favoring living closer to one’s extended families.ConclusionsOur analysis revealed genetic makeup, personal genealogical history, and social behaviors at the population scale, opening possibilities for further studies of individual’s genetic connections in biobank data.

Estimation of additive and non-additive genetic effects for fertility and reproduction traits in North American Holstein cattle using genomic information.

Non-additive genetic effects are usually ignored in animal breeding programs due to data structure (e.g., incomplete pedigree), computational limitations and over-parameterization of the models. However, non-additive genetic effects may play an important role in the expression of complex traits in livestock species, such as fertility and reproduction traits. In this study, components of genetic variance for additive and non-additive genetic effects were estimated for a variety of fertility and reproduction traits in Holstein cattle using pedigree and genomic relationship matrices. Four linear models were used: (a) an additive genetic model; (b) a model including both additive and epistatic (additive by additive) genetic effects; (c) a model including both additive and dominance effects; and (d) a full model including additive, epistatic and dominance genetic effects. Nine fertility and reproduction traits were analysed, and models were run separately for heifers (N=5,825) and cows (N=6,090). For some traits, a larger proportion of phenotypic variance was explained by non-additive genetic effects compared with additive effects, indicating that epistasis, dominance or a combination thereof is of great importance. Epistatic genetic effects contributed more to the total phenotypic variance than dominance genetic effects. Although these models varied considerably in the partitioning of the components of genetic variance, the models including a non-additive genetic effect did not show a clear advantage over the additive model based on the Akaike information criterion. The partitioning of variance components resulted in a re-ranking of cows based solely on the cows' additive genetic effects between models, indicating that adjusting for non-additive genetic effects could affect selection decisions made in dairy cattle breeding programs. These results suggest that non-additive genetic effects play an important role in some fertility and reproduction traits in Holstein cattle.

Controlling bias in genomic breeding values for young genotyped bulls

The objectives of this study were to investigate bias in genomic predictions for dairy cattle and to find a practical approach to reduce the bias. The simulated data included phenotypes, pedigrees, and genotypes, mimicking a dairy cattle population (i.e., cows with phenotypes and bulls with no phenotypes) and assuming selection by breeding values or no selection. With the simulated data, genomic estimated breeding values (GEBV) were calculated with a single-step genomic BLUP and compared with true breeding values. Phenotypes and genotypes were simulated in 10 generations and in the last 4 generations, respectively. Phenotypes in the last generation were removed to predict breeding values for those individuals using only genomic and pedigree information. Complete pedigrees and incomplete pedigrees with 50% missing dams were created to construct the pedigree-based relationship matrix with and without inbreeding. With missing dams, unknown parent groups (UPG) were assigned in relationship matrices. Regression coefficients (b1) and coefficients of determination (R2) of true breeding values on (G)EBV were calculated to investigate inflation and accuracy in GEBV for genotyped animals, respectively. In addition to the simulation study, 18 linear type traits of US Holsteins were examined. For the 18 type traits, b1 and R2 of GEBV with full data sets on GEBV with partial data sets for young genotyped bulls were calculated. The results from the simulation study indicated inflation in GEBV for genotyped males that were evaluated with only pedigree and genomic information under BLUP selection. However, when UPG for only pedigree-based relationships were included, the inflation was reduced, accuracy was highest, and genetic trends had no bias. For the linear type traits, when UPG for only pedigree-based relationships were included, the results were generally in agreement with those from the simulation study, implying less bias in genetic trends. However, when including no UPG, UPG in pedigree-based relationships, or UPG in genomic relationships, inflation and accuracy in GEBV were similar. The results from the simulation and type traits suggest that UPG must be defined accurately to be estimable and inbreeding should be included in pedigree-based relationships. In dairy cattle, known pedigree information with inbreeding and estimable UPG plays an important role in improving compatibility between pedigree-based and genomic relationship matrices, resulting in more reliable genomic predictions.

Coancestry rate\u2019s estimate of effective population size for genetic variability monitoring

Different methods and formulae have been suggested to estimate effective population size based on pedigree data. These methods vary in their sensitivity to various sources of bias related to heterogenous pedigree knowledge or pedigree structure. We propose here to adapt a pre-existing method estimating coancestry rate for the specific purpose of monitoring genetic variability within livestock and captive populations. Coancestry rate is computed by averaging coancestries between pairs of individuals corrected by their equivalent numbers of generations, while restricting pedigree information to a maximum number of generations. Simulation demonstrated that restricting the number of generations allows a much clearer observation of the impact of recent events on genetic variability. Restricting the number of generations for the calculation of coancestry also has less bias related to incomplete pedigree, although it may overestimate effective population size due to non-independence in family sizes across generations. This strategy was tested on the Norwegian Nordland Lyngen horse, the Colblood Trotter horse, the French Avranchin sheep, and Bresse chicken, illustrating the applications of the approach for the monitoring of genetic variability.

Development of a genetic tool for determining breed purity of cattle

Breed registries have been established for livestock species to maintain the purity of breeds and to document the ancestry of animals. However, a significant number of animals are unregistered with no or incomplete pedigree data and uncertain ancestral breed origin. Although many local livestock breeds are “at risk” on the basis of the number of purebred breeding females in a breed registry, there is often also a reservoir of unregistered animals that may belong to the same breed. However, due to the missing pedigree it is not possible for breed societies or herd books to include those animals in their breeding program for purebred animals. A genetic test was developed to unequivocally determine the breed origin of cattle without pedigree data. Such a test will open up the possibility to incorporate animals without pedigree data in the breed registry that turn out to be purebred based on the test results. In this study we developed and validated such a test. Genotype data (50k SNP array) were used to compose reference populations for six local Dutch cattle breeds. The combination Principal Component Analysis and Random Forest was used to perform SNP selection. A total of 133 informative SNPs were selected to determine breed composition of individual animals. Overall, 82.0% of the animals in the test population are correctly assigned to the breed in question. For Dutch Red and White Friesian and Deep Red Cattle we suggest that if an animal has a percentage for its own breed <0.775 to use the combined percentage of two breeds (Deep Red Cattle with Meuse‐Rhine‐Yssel and Dutch Red and White Friesian with Dutch Friesian). Using this criteria 88.9% (104 out of 117) of the animals in the test population is correctly assigned.The developed test was successful and will be implemented in practice to identify (partly) unregistered individuals as being purebred (or not) for one of the Dutch local cattle breeds.

Pedigree structure of American bison (Bison bison) population

An effective realization of breeding programs in zoos is strongly determined by completeness of animal pedigree information. The knowledge of pedigree structure allows to maintain optimal genetic variability of a given population. The aim of this study was to estimate the parameters describing the pedigree structure of American bison housed in zoos in the context of further management of the population. Finally, 4269 American bison were analysed (1883 males, 2217 females, and 169 with unknown sex). The registered animals were born between years 1874 and 2013. The following pedigree parameters were estimated: number of fully traced generations, number of complete generations equivalent, index of pedigree completeness, individual inbreeding coefficients, increase of inbreeding for each individual, effective population size, and genetic diversity. The maximum number of fully traced generations was 3 (the mean value is 0.693). The mean inbreeding coefficient for the population studied was 3.26%, whereas individual increase in inbreeding ranged from 0 to 25.12%. Although the pedigree parameters (including the inbreeding level) in the American bison obtained in the present study seem to be acceptable (from the perspective of other wild animal populations), they can be over/underestimated due to incomplete pedigree.

Efficient and accurate computation of base generation allele frequencies

Allele frequencies are used for several aspects of genomic prediction, with the assumption that these are equal to the allele frequency in the base generation of the pedigree. The current standard method, however, calculates allele frequencies from the current genotyped population. We compared the current standard method with BLUP and general least squares (GLS) methods explicitly targeting the base population to determine whether there is a more accurate and still efficient method of calculating allele frequencies that better represents the base generation. A data set based on a typical dairy population was simulated for 325,266 animals; the last 100,078 animals in generations 9 to 12 of the population were genotyped, with 1,670 SNP markers. For the BLUP method, several SNP genotypes were analyzed with a multitrait model by assuming a heritability of 0.99 and no genetic correlation among them. This method was limited by the time required for each BLUP to converge (approximately 6 min per BLUP run of 15 SNP). The GLS method had 2 implementations. The first implementation, using imputation on the fly and multiplication of sparse matrices, was very efficient and required just 49 s and 1.3 GB of random access memory. The second implementation, using a dense full A22-1 matrix, was very inefficient and required more than 1 d of wall clock time and more than 118.2 GB of random access memory. When no selection was considered in the simulations, all methods predicted equally well. When selection was introduced, higher correlations between the estimated allele frequency and known base generation allele frequency were observed for BLUP (0.96 ± 0.01) and GLS (0.97 ± 0.01) compared with the current standard method (0.87 ± 0.01). The GLS method decreased in accuracy when introducing incomplete pedigree, with 25% of sires in the first 5 generations randomly replaced as unknown to erroneously identify founder animals (0.93 ± 0.01) and a further decrease for 8 generations (0.91 ± 0.01). There was no change in accuracy when introducing 5% genotyping errors (0.97 ± 0.01), 5% missing genotypes (0.97 ± 0.01), or both 5% genotyping errors and missing genotypes (0.97 ± 0.01). The GLS method provided the most accurate estimates of base generation allele frequency and was only slightly slower compared with the current method. The efficient implementation of the GLS method, therefore, is very well suited for practical application and is recommended for implementation.

Generalized disequilibrium test for association in qualitative traits incorporating imprinting effects based on extended pedigrees

BackgroundFor dichotomous traits, the generalized disequilibrium test with the moment estimate of the variance (GDT-ME) is a powerful family-based association method. Genomic imprinting is an important epigenetic phenomenon and currently, there has been increasing interest of incorporating imprinting to improve the test power of association analysis. However, GDT-ME does not take imprinting effects into account, and it has not been investigated whether it can be used for association analysis when the effects indeed exist.ResultsIn this article, based on a novel decomposition of the genotype score according to the paternal or maternal source of the allele, we propose the generalized disequilibrium test with imprinting (GDTI) for complete pedigrees without any missing genotypes. Then, we extend GDTI and GDT-ME to accommodate incomplete pedigrees with some pedigrees having missing genotypes, by using a Monte Carlo (MC) sampling and estimation scheme to infer missing genotypes given available genotypes in each pedigree, denoted by MCGDTI and MCGDT-ME, respectively. The proposed GDTI and MCGDTI methods evaluate the differences of the paternal as well as maternal allele scores for all discordant relative pairs in a pedigree, including beyond first-degree relative pairs. Advantages of the proposed GDTI and MCGDTI test statistics over existing methods are demonstrated by simulation studies under various simulation settings and by application to the rheumatoid arthritis dataset. Simulation results show that the proposed tests control the size well under the null hypothesis of no association, and outperform the existing methods under various imprinting effect models. The existing GDT-ME and the proposed MCGDT-ME can be used to test for association even when imprinting effects exist. For the application to the rheumatoid arthritis data, compared to the existing methods, MCGDTI identifies more loci statistically significantly associated with the disease.ConclusionsUnder complete and incomplete imprinting effect models, our proposed GDTI and MCGDTI methods, by considering the information on imprinting effects and all discordant relative pairs within each pedigree, outperform all the existing test statistics and MCGDTI can recapture much of the missing information. Therefore, MCGDTI is recommended in practice.