The use of Hardy-Weinberg Equilibrium in clonal plant systems.
Ontology highlight
ABSTRACT:
SUBMITTER: Douhovnikoff V
PROVIDER: S-EPMC4725330 | biostudies-other | 2016 Feb
REPOSITORIES: biostudies-other
Similar Datasets
Project description:The century-old Hardy-Weinberg law remains fundamental to population genetics. Typically Hardy-Weinberg equilibrium is tested in unrelated individuals using a chi(2) goodness-of-fit test that compares expected and observed numbers of heterozygotes and homozygotes. In this report, we propose a likelihood ratio test for Hardy-Weinberg equilibrium that accommodates a mixture of pedigree and random sample data. The underlying statistical model depends on a parameter gamma determining the ratio of heterozygous genotypes to homozygous genotypes among pedigree founders. As our heterozygous-homozygous test accommodates markers with dominant and recessive alleles, it can handle the phase ambiguities encountered in combining several linked single nucleotide polymorphisms into a single supermarker. No prior haplotyping is necessary. Our experience on real and simulated data suggests that the heterozygous-homozygous test has good type-one error and power.
| S-EPMC2986695 | biostudies-literature
Project description:Hexaploids, a group of organisms containing three complete sets of chromosomes in a single nucleus, are of utmost importance to evolutionary studies and breeding programs. Many studies have focused on hexaploid linkage analysis and QTL mapping in controlled crosses, but little methodology has been developed to reveal how hexaploids diversify and evolve in natural populations. We formulate a general framework for studying the pattern of genetic variation in autohexaploid populations through testing deviation from Hardy-Weinberg equilibrium (HWE) at individual molecular markers. We confirm that hexaploids cannot reach exact HWE but can approach asymptotic HWE at 8-9 generations of random mating. We derive a statistical algorithm for testing HWE and the occurrence of double reduction for autopolyploids, a phenomenon that affects population variation during long evolutionary processes. We perform computer simulation to validate the statistical behavior of our test procedure and demonstrate its usefulness by analyzing a real data set for autohexaploid chrysanthemum. When extended to allohexaploids, our test procedure will provide a generic tool for illustrating the genome structure of hexaploids in the quest to infer their evolutionary status and design association studies of complex traits.
| S-EPMC9250657 | biostudies-literature
Project description:Panmixia is a key issue in maintaining genetic diversity, which facilitates evolutionary potential during environmental changes. Additionally, conservation biologists suggest the importance of avoiding small or subdivided populations, which are prone to losing genetic diversity. In this paper, computer simulations were performed to the genetic drift of neutral alleles in random mating populations with or without spatial constraints by randomly choosing a mate among the closest neighbours. The results demonstrated that the number of generations required for the neutral allele to become homozygous (Th) varied proportionally to the population size and also strongly correlated with spatial constraints. The average Th for populations of the same size with spatial constraints was approximately one-and-a-half times longer than without constraints. With spatial constraints, homozygous population clusters formed, which reduced local diversity but preserved global diversity. Therefore, panmixia might be harmful in preserving the genetic diversity of an entire population. The results also suggested that the gene flow or gene exchange among the subdivided populations must be carefully processed to restrict diseases transmission or death during transportation and to monitor the genetic diversity. The application of this concept to similar systems, such as information transfer among peers, is also discussed.
| S-EPMC4725899 | biostudies-literature
Project description:Objective: Departure from Hardy Weinberg Equilibrium (HWE) may occur due to a variety of causes, including purifying selection, inbreeding, population substructure, copy number variation or genotyping error. We searched for specific characteristics of HWE-departure due to genotyping error. Methods: Genotypes of a random set of genetic variants were obtained from the Exome Aggregation Consortium (ExAC) database. Variants with <80% successful genotypes or with minor allele frequency (MAF) <1% were excluded. HWE-departure (d-HWE) was considered significant at p < 10E-05 and classified as d-HWE with loss of heterozygosity (LoH d-HWE) or d-HWE with excess heterozygosity (gain of heterozygosity: GoH d-HWE). Missing genotypes, variant type (single nucleotide polymorphism (SNP) vs. insertion/deletion); MAF, standard deviation (SD) of MAF across populations (MAF-SD) and copy number variation were evaluated for association with HWE-departure. Results: The study sample comprised 3,204 genotype distributions. HWE-departure was observed in 134 variants: LoH d-HWE in 41 (1.3%), GoH d-HWE in 93 (2.9%) variants. LoH d-HWE was more likely in variants located within deletion polymorphisms (p < 0.001) and in variants with higher MAF-SD (p = 0.0077). GoH d-HWE was associated with low genotyping rate, with variants of insertion/deletion type and with high MAF (all at p < 0.001). In a sub-sample of 2,196 variants with genotyping rate >98%, LoH d-HWE was found in 29 (1.3%) variants, but no GoH d-HWE was detected. The findings of the non-random distribution of HWE-violating SNPs along the chromosome, the association with common deletion polymorphisms and indel-variant type, and the finding of excess heterozygotes in genomic regions that are prone to cross-hybridization were confirmed in a large sample of short variants from the 1,000 Genomes Project. Conclusions: We differentiated between two types of HWE-departure. GoH d-HWE was suggestive for genotyping error. LoH d-HWE, on the contrary, pointed to natural variabilities such as population substructure or common deletion polymorphisms.
| S-EPMC5671567 | biostudies-literature
Project description:Testing for Hardy-Weinberg equilibrium (HWE) is an important component in almost all analyses of population genetic data. Genetic markers that violate HWE are often treated as special cases; for example, they may be flagged as possible genotyping errors, or they may be investigated more closely for evolutionary signatures of interest. The presence of population structure is one reason why genetic markers may fail a test of HWE. This is problematic because almost all natural populations studied in the modern setting show some degree of structure. Therefore, it is important to be able to detect deviations from HWE for reasons other than structure. To this end, we extend statistical tests of HWE to allow for population structure, which we call a test of "structural HWE." Additionally, our new test allows one to automatically choose tuning parameters and identify accurate models of structure. We demonstrate our approach on several important studies, provide theoretical justification for the test, and present empirical evidence for its utility. We anticipate the proposed test will be useful in a broad range of analyses of genome-wide population genetic data.
| S-EPMC6827367 | biostudies-literature
Project description:BackgroundMeasures of linkage disequilibrium (LD) play a key role in a wide range of applications from disease association to demographic history estimation. The true population LD cannot be measured directly and instead can only be inferred from genetic samples, which are unavoidably subject to measurement error. Previous studies of r2 (a measure of LD), such as the bias due to finite sample size and its variance, were based on the special case that the true population-wise LD is zero. These results generally do not hold for non-zero [Formula: see text] values, which are more common in real genetic data.ResultsThis work generalises the estimation of r2 to all levels of LD, and for both phased and unphased data. First, we provide new formulae for the effect of finite sample size on the observed r2 values. Second, we find a new empirical formula for the variance of the observed r2, equals to 2E[r2](1?-?E[r2])/n, where n is the diploid sample size. Third, we propose a new routine, Constrained ML, a likelihood-based method to directly estimate haplotype frequencies and r2 from diploid genotypes under Hardy-Weinberg Equilibrium. While serving the same purpose as the pre-existing Expectation-Maximisation algorithm, the new routine can have better convergence and is simpler to use. A new likelihood-ratio test is also introduced to test for the absence of a particular haplotype. Extensive simulations are run to support these findings.ConclusionMost inferences on LD will benefit from our new findings, from point and interval estimation to hypothesis testing. Genetic analyses utilising r2 information will become more accurate as a result.
| S-EPMC7045472 | biostudies-literature
Project description:Hardy-Weinberg Equilibrium (HWE) is used to estimate the number of homozygous and heterozygous variant carriers based on its allele frequency in populations that are not evolving. Deviations from HWE in large population databases have been used to detect genotyping errors, which can result in extreme heterozygote excess (HetExc). However, HetExc might also be a sign of natural selection since recessive disease causing variants should occur less frequently in a homozygous state in the population, but may reach high allele frequency in a heterozygous state, especially if they are advantageous. We developed a filtering strategy to detect these variants and applied it on genome data from 137,842 individuals. The main limitations of this approach were quality of genotype calls and insufficient population sizes, whereas population structure and inbreeding can reduce sensitivity, but not precision, in certain populations. Nevertheless, we identified 161 HetExc variants in 149 genes, most of which were specific to African/African American populations (∼79.5%). Although the majority of them were not associated with known diseases, or were classified as clinically "benign," they were enriched in genes associated with autosomal recessive diseases. The resulting dataset also contained two known recessive disease causing variants with evidence of heterozygote advantage in the sickle-cell anemia (HBB) and cystic fibrosis (CFTR). Finally, we provide supporting in silico evidence of a novel heterozygote advantageous variant in the chromodomain helicase DNA binding protein 6 gene (CHD6; involved in influenza virus replication). We anticipate that our approach will aid the detection of rare recessive disease causing variants in the future.
| S-EPMC7083100 | biostudies-literature
Project description:Testing for Hardy-Weinberg equilibrium (HWE) is commonly used as a quality control filter in genome-wide scans for markers with experimentally determined genotypes. In contrast, for markers with imputed genotypes, there are post-imputation metrics of quality that can be used as screens but there are no formal tests of deviation from HWE. Similarly, there are no formal tests of deviation from HWE for probabilistic genotypes that are generated by sequencing projects. Here, I describe generalizations of the approximate ?(2) and exact tests of HWE for use with uncertain genotypes. The tests fully account for the probabilities of all possible genotypes at a marker for each individual. By computer simulation, the approximate and exact tests are shown to maintain valid control of the type I error rate. Calculations of the loss of power as the uncertainty in genotypes increases are illustrated. The tests are compatible with chip-based genotypes for single-nucleotide polymorphisms and copy number polymorphisms, imputed genotypes, and probabilistic assignments of genotype from variable-coverage sequence data.
| S-EPMC4141651 | biostudies-literature
Project description:Mendelian randomization (MR) permits causal inference between exposures and a disease. It can be compared with randomized controlled trials. Whereas in a randomized controlled trial the randomization occurs at entry into the trial, in MR the randomization occurs during gamete formation and conception. Several factors, including time since conception and sampling variation, are relevant to the interpretation of an MR test. Particularly important is consideration of the "missingness" of genotypes that can be originated by chance, genotyping errors, or clinical ascertainment. Testing for Hardy-Weinberg equilibrium (HWE) is a genetic approach that permits evaluation of missingness. In this paper, the authors demonstrate evidence of nonconformity with HWE in real data. They also perform simulations to characterize the sensitivity of HWE tests to missingness. Unresolved missingness could lead to a false rejection of causality in an MR investigation of trait-disease association. These results indicate that large-scale studies, very high quality genotyping data, and detailed knowledge of the life-course genetics of the alleles/genotypes studied will largely mitigate this risk. The authors also present a Web program (http://www.oege.org/software/hwe-mr-calc.shtml) for estimating possible missingness and an approach to evaluating missingness under different genetic models.
| S-EPMC2640163 | biostudies-literature
Project description:Recently, there have been many case-control studies proposed to test for association between haplotypes and disease, which require the Hardy-Weinberg equilibrium (HWE) assumption of haplotype frequencies. As such, haplotype inference of unphased genotypes and development of haplotype-based HWE tests are crucial prior to fine mapping. The goodness-of-fit test is a frequently-used method to test for HWE for multiple tightly-linked loci. However, its degrees of freedom dramatically increase with the increase of the number of loci, which may lack the test power. Therefore, in this paper, to improve the test power for haplotype-based HWE, we first write out two likelihood functions of the observed data based on the Niu's model (NM) and inbreeding model (IM), respectively, which can cause the departure from HWE. Then, we use two expectation-maximization algorithms and one expectation-conditional-maximization algorithm to estimate the model parameters under the HWE, IM and NM models, respectively. Finally, we propose the likelihood ratio tests LRT[Formula: see text] and LRT[Formula: see text] for haplotype-based HWE under the NM and IM models, respectively. We simulate the HWE, Niu's, inbreeding and population stratification models to assess the validity and compare the performance of these two LRT tests. The simulation results show that both of the tests control the type I error rates well in testing for haplotype-based HWE. If the NM model is true, then LRT[Formula: see text] is more powerful. While, if the true model is the IM model, then LRT[Formula: see text] has better performance in power. Under the population stratification model, LRT[Formula: see text] is still more powerful. To this end, LRT[Formula: see text] is generally recommended. Application of the proposed methods to a rheumatoid arthritis data set further illustrates their utility for real data analysis.
| S-EPMC3805574 | biostudies-literature