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A two-locus model of selection in autotetraploids: Chromosomal gametic disequilibrium and selection for an adaptive epistatic gene combination.

ABSTRACT: In this paper, we present a two-locus model of selection for an autotetraploid population. We also investigate a measure of disequilibrium that occurs between homologous chromosomes in the diploid gametes of autotetraploids, namely chromosomal gametic disequilibrium. We apply the model and measure of disequilibrium to compare how an adaptive epistatic gene combination is inherited and selected for in an autotetraploid versus diploid population. Autotetraploids are expected to have higher genomic mutation and recombination rates relative to diploids, due to a greater ploidy level. These two processes can work in opposition in terms of selection for adaptive epistatic gene combinations. While a higher genomic mutation rate can generate the alleles that confer an epistatic combination more quickly, a higher recombination rate is expected to break the combination down more quickly. We show that chromosomal gametic disequilibrium in autotetraploids can potentially compensate for less linkage disequilibrium in autotetraploids. We also explore how double reduction affects the inheritance of and selection for an epistatic gene combination. Over all, our analysis provides theoretical evidence that adaptive epistatic combinations can be selected for more efficiently in autotetraploids versus diploids. This may provide insight into empirical work that finds epistasis has a role in causing population differentiation between autotetraploid plant populations.

SUBMITTER: Griswold CK

PROVIDER: S-EPMC5637366 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature

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A two-locus model of selection in autotetraploids: Chromosomal gametic disequilibrium and selection for an adaptive epistatic gene combination.

Griswold C K CK Williamson M W MW

Heredity 20170823 5

In this paper, we present a two-locus model of selection for an autotetraploid population. We also investigate a measure of disequilibrium that occurs between homologous chromosomes in the diploid gametes of autotetraploids, namely chromosomal gametic disequilibrium. We apply the model and measure of disequilibrium to compare how an adaptive epistatic gene combination is inherited and selected for in an autotetraploid versus diploid population. Autotetraploids are expected to have higher genomic ...[more]

PMID: 28832578

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Project description:BACKGROUND: Purely epistatic multi-locus interactions cannot generally be detected via single-locus analysis in case-control studies of complex diseases. Recently, many two-locus and multi-locus analysis techniques have been shown to be promising for the epistasis detection. However, exhaustive multi-locus analysis requires prohibitively large computational efforts when problems involve large-scale or genome-wide data. Furthermore, there is no explicit proof that a combination of multiple two-locus analyses can lead to the correct identification of multi-locus interactions. RESULTS: The proposed 2LOmb algorithm performs an omnibus permutation test on ensembles of two-locus analyses. The algorithm consists of four main steps: two-locus analysis, a permutation test, global p-value determination and a progressive search for the best ensemble. 2LOmb is benchmarked against an exhaustive two-locus analysis technique, a set association approach, a correlation-based feature selection (CFS) technique and a tuned ReliefF (TuRF) technique. The simulation results indicate that 2LOmb produces a low false-positive error. Moreover, 2LOmb has the best performance in terms of an ability to identify all causative single nucleotide polymorphisms (SNPs) and a low number of output SNPs in purely epistatic two-, three- and four-locus interaction problems. The interaction models constructed from the 2LOmb outputs via a multifactor dimensionality reduction (MDR) method are also included for the confirmation of epistasis detection. 2LOmb is subsequently applied to a type 2 diabetes mellitus (T2D) data set, which is obtained as a part of the UK genome-wide genetic epidemiology study by the Wellcome Trust Case Control Consortium (WTCCC). After primarily screening for SNPs that locate within or near 372 candidate genes and exhibit no marginal single-locus effects, the T2D data set is reduced to 7,065 SNPs from 370 genes. The 2LOmb search in the reduced T2D data reveals that four intronic SNPs in PGM1 (phosphoglucomutase 1), two intronic SNPs in LMX1A (LIM homeobox transcription factor 1, alpha), two intronic SNPs in PARK2 (Parkinson disease (autosomal recessive, juvenile) 2, parkin) and three intronic SNPs in GYS2 (glycogen synthase 2 (liver)) are associated with the disease. The 2LOmb result suggests that there is no interaction between each pair of the identified genes that can be described by purely epistatic two-locus interaction models. Moreover, there are no interactions between these four genes that can be described by purely epistatic multi-locus interaction models with marginal two-locus effects. The findings provide an alternative explanation for the aetiology of T2D in a UK population. CONCLUSION: An omnibus permutation test on ensembles of two-locus analyses can detect purely epistatic multi-locus interactions with marginal two-locus effects. The study also reveals that SNPs from large-scale or genome-wide case-control data which are discarded after single-locus analysis detects no association can still be useful for genetic epidemiology studies.

Project description:BackgroundThe statistical genetics phenomenon of epistasis is widely acknowledged to confound disease etiology. In order to evaluate strategies for detecting these complex multi-locus disease associations, simulation studies are required. The development of the GAMETES software for the generation of complex genetic models, has provided the means to randomly generate an architecturally diverse population of epistatic models that are both pure and strict, i.e. all n loci, but no fewer, are predictive of phenotype. Previous theoretical work characterizing complex genetic models has yet to examine pure, strict, epistasis which should be the most challenging to detect. This study addresses three goals: (1) Classify and characterize pure, strict, two-locus epistatic models, (2) Investigate the effect of model 'architecture' on detection difficulty, and (3) Explore how adjusting GAMETES constraints influences diversity in the generated models.ResultsIn this study we utilized a geometric approach to classify pure, strict, two-locus epistatic models by "shape". In total, 33 unique shape symmetry classes were identified. Using a detection difficulty metric, we found that model shape was consistently a significant predictor of model detection difficulty. Additionally, after categorizing shape classes by the number of edges in their shape projections, we found that this edge number was also significantly predictive of detection difficulty. Analysis of constraints within GAMETES indicated that increasing model population size can expand model class coverage but does little to change the range of observed difficulty metric scores. A variable population prevalence significantly increased the range of observed difficulty metric scores and, for certain constraints, also improved model class coverage.ConclusionsThese analyses further our theoretical understanding of epistatic relationships and uncover guidelines for the effective generation of complex models using GAMETES. Specifically, (1) we have characterized 33 shape classes by edge number, detection difficulty, and observed frequency (2) our results support the claim that model architecture directly influences detection difficulty, and (3) we found that GAMETES will generate a maximally diverse set of models with a variable population prevalence and a larger model population size. However, a model population size as small as 1,000 is likely to be sufficient.

Dataset Information

A two-locus model of selection in autotetraploids: Chromosomal gametic disequilibrium and selection for an adaptive epistatic gene combination.

Publications

A two-locus model of selection in autotetraploids: Chromosomal gametic disequilibrium and selection for an adaptive epistatic gene combination.

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