Dataset Information

PADRE: Pedigree-Aware Distant-Relationship Estimation.

ABSTRACT: Accurate estimation of shared ancestry is an important component of many genetic studies; current prediction tools accurately estimate pairwise genetic relationships up to the ninth degree. Pedigree-aware distant-relationship estimation (PADRE) combines relationship likelihoods generated by estimation of recent shared ancestry (ERSA) with likelihoods from family networks reconstructed by pedigree reconstruction and identification of a maximum unrelated set (PRIMUS), improving the power to detect distant relationships between pedigrees. Using PADRE, we estimated relationships from simulated pedigrees and three extended pedigrees, correctly predicting 20% more fourth- through ninth-degree simulated relationships than when using ERSA alone. By leveraging pedigree information, PADRE can even identify genealogical relationships between individuals who are genetically unrelated. For example, although 95% of 13(th)-degree relatives are genetically unrelated, in simulations, PADRE correctly predicted 50% of 13(th)-degree relationships to within one degree of relatedness. The improvement in prediction accuracy was consistent between simulated and actual pedigrees. We also applied PADRE to the HapMap3 CEU samples and report new cryptic relationships and validation of previously described relationships between families. PADRE greatly expands the range of relationships that can be estimated by using genetic data in pedigrees.

SUBMITTER: Staples J

PROVIDER: S-EPMC5005450 | biostudies-literature | 2016 Jul

REPOSITORIES: biostudies-literature

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PADRE: Pedigree-Aware Distant-Relationship Estimation.

Staples Jeffrey J Witherspoon David J DJ Jorde Lynn B LB Nickerson Deborah A DA Below Jennifer E JE Huff Chad D CD

American journal of human genetics 20160630 1

Accurate estimation of shared ancestry is an important component of many genetic studies; current prediction tools accurately estimate pairwise genetic relationships up to the ninth degree. Pedigree-aware distant-relationship estimation (PADRE) combines relationship likelihoods generated by estimation of recent shared ancestry (ERSA) with likelihoods from family networks reconstructed by pedigree reconstruction and identification of a maximum unrelated set (PRIMUS), improving the power to detect ...[more]

PMID: 27374771

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Project description:BackgroundEstimation of genetic relatedness, or kinship, is used occasionally for recreational purposes and in forensic applications. While numerous methods were developed to estimate kinship, they suffer from high computational requirements and often make an untenable assumption of homogeneous population ancestry of the samples. Moreover, genetic privacy is generally overlooked in the usage of kinship estimation methods. There can be ethical concerns about finding unknown familial relationships in third-party databases. Similar ethical concerns may arise while estimating and reporting sensitive population-level statistics such as inbreeding coefficients for the concerns around marginalization and stigmatization.ResultsHere, we present SIGFRIED, which makes use of existing reference panels with a projection-based approach that simplifies kinship estimation in the admixed populations. We use simulated and real datasets to demonstrate the accuracy and efficiency of kinship estimation. We present a secure federated kinship estimation framework and implement a secure kinship estimator using homomorphic encryption-based primitives for computing relatedness between samples in two different sites while genotype data are kept confidential. Source code and documentation for our methods can be found at https://doi.org/10.5281/zenodo.7053352.ConclusionsAnalysis of relatedness is fundamentally important for identifying relatives, in association studies, and for estimation of population-level estimates of inbreeding. As the awareness of individual and group genomic privacy is growing, privacy-preserving methods for the estimation of relatedness are needed. Presented methods alleviate the ethical and privacy concerns in the analysis of relatedness in admixed, historically isolated and underrepresented populations.Short abstractGenetic relatedness is a central quantity used for finding relatives in databases, correcting biases in genome wide association studies and for estimating population-level statistics. Methods for estimating genetic relatedness have high computational requirements, and occasionally do not consider individuals from admixed ancestries. Furthermore, the ethical concerns around using genetic data and calculating relatedness are not considered. We present a projection-based approach that can efficiently and accurately estimate kinship. We implement our method using encryption-based techniques that provide provable security guarantees to protect genetic data while kinship statistics are computed among multiple sites.

Project description:Variance and covariance components of growth and production traits were analyzed employing REML animal model to assess the Dahlem Red (PD-3) chicken population for direct additive genetic, maternal effects and to estimate the estimated breeding value (EBV), genetic parameters, genetic trends and rate of inbreeding (ΔF) utilizing seven generation's data. The generation and hatch had significant (P≤0.01) effect on the body weight at 0 day (BW0), 2 (BW2), 4 (BW4) and 6 weeks (BW6) and shank length at six weeks of age (SL6). The average least squares means (LSM) for BW6 and SL6 were 273.93±0.62 g and 53.97±0.05 mm, respectively. All the production traits were significantly (P≤0.01) influenced by generation and hatch. The average LSM for age at sexual maturity (ASM), egg production up to 40 weeks (EP40) and egg mass up to 40 weeks (EM40) were 168.82±0.25 d, 72.60±0.41 eggs and 4.21±0.07 kg, respectively. Model 5 with additive direct, maternal genetic, maternal permanent environmental and residual variance components was the best for BW0, BW2 and BW4 based on the AIC values obtained in WOMBAT. Model 4 was the best model for BW6, SL6, ASM, EP40 and EM40 with additive direct, maternal permanent environmental and residual variance components. Maternal effects were higher during early age, decreased with age, and remained present until 20 weeks of age. The heritability (h2) estimates were low to moderate in magnitude for all the growth traits and ranged from 0.02±0.03 to 0.19±0.03. The maternal heritability was high at hatch (0.35±0.06), decreased gradually until 4th week (0.02±0.01) and ceased afterwards. The heritabilities of EP40 (0.11±0.03) and EM40 (0.12±0.04) were low. The direct additive genetic correlations (ra) between BW2, BW4, BW6 and SL6 were high and positive (P≤ 0.05). The additive genetic and maternal permanent environmental correlation between EP40 and EM40 were high and positive (P≤ 0.05). The EBV of EM40 was significant (P≤ 0.05) with 0.48 kg/generation in PD-3 chicken at the end of the seventh generation. The EBV of EP40 showed an increasing trend with a genetic gain of 1.87 eggs per generation. The average inbreeding coefficient of the population was 0.019 and average ΔF was 0.007 over the last seven generations of selection. The EBV trends for primary and associated traits showed linear trends in the desired direction and negligible inbreeding.

Dataset Information

PADRE: Pedigree-Aware Distant-Relationship Estimation.

Publications

PADRE: Pedigree-Aware Distant-Relationship Estimation.

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