scholarly journals Ohana: detecting selection in multiple populations by modelling ancestral admixture components

2019 ◽  
Author(s):  
Jade Yu Cheng ◽  
Fernando Racimo ◽  
Rasmus Nielsen
Keyword(s):  
Native American ◽  
Allele Frequency ◽  
Mexican Americans ◽  
Gaussian Approximation ◽  
Simulated Data ◽  
Fat Distribution ◽  
Likelihood Method ◽  
Multiple Populations ◽  
Frequency Changes ◽  
Candidate Regions

AbstractOne of the most powerful and commonly used methods for detecting local adaptation in the genome is the identification of extreme allele frequency differences between populations. In this paper, we present a new maximum likelihood method for finding regions under positive selection. The method is based on a Gaussian approximation to allele frequency changes and it incorporates admixture between populations. The method can analyze multiple populations simultaneously and retains power to detect selection signatures specific to ancestry components that are not representative of any extant populations. We evaluate the method using simulated data and compare it to related methods based on summary statistics. We also apply it to human genomic data and identify loci with extreme genetic differentiation between major geographic groups. Many of the genes identified are previously known selected loci relating to hair pigmentation and morphology, skin and eye pigmentation. We also identify new candidate regions, including various selected loci in the Native American component of admixed Mexican-Americans. These involve diverse biological functions, like immunity, fat distribution, food intake, vision and hair development.

Genetic and statistical analyses of strong selection on polygenic traits: what, me normal?

Genetics ◽  
1994 ◽  
Vol 138 (3) ◽  
pp. 913-941 ◽  
Author(s):  
M Turelli ◽  
N H Barton
Keyword(s):  
Allele Frequency ◽  
Genetic Variance ◽  
Gaussian Approximation ◽  
Selection Response ◽  
Disruptive Selection ◽  
Breeding Values ◽  
Central Moments ◽  
Linkage Disequilibria ◽  
The Mean ◽  
Frequency Changes

Abstract We develop a general population genetic framework for analyzing selection on many loci, and apply it to strong truncation and disruptive selection on an additive polygenic trait. We first present statistical methods for analyzing the infinitesimal model, in which offspring breeding values are normally distributed around the mean of the parents, with fixed variance. These show that the usual assumption of a Gaussian distribution of breeding values in the population gives remarkably accurate predictions for the mean and the variance, even when disruptive selection generates substantial deviations from normality. We then set out a general genetic analysis of selection and recombination. The population is represented by multilocus cumulants describing the distribution of haploid genotypes, and selection is described by the relation between mean fitness and these cumulants. We provide exact recursions in terms of generating functions for the effects of selection on non-central moments. The effects of recombination are simply calculated as a weighted sum over all the permutations produced by meiosis. Finally, the new cumulants that describe the next generation are computed from the non-central moments. Although this scheme is applied here in detail only to selection on an additive trait, it is quite general. For arbitrary epistasis and linkage, we describe a consistent infinitesimal limit in which the short-term selection response is dominated by infinitesimal allele frequency changes and linkage disequilibria. Numerical multilocus results show that the standard Gaussian approximation gives accurate predictions for the dynamics of the mean and genetic variance in this limit. Even with intense truncation selection, linkage disequilibria of order three and higher never cause much deviation from normality. Thus, the empirical deviations frequently found between predicted and observed responses to artificial selection are not caused by linkage-disequilibrium-induced departures from normality. Disruptive selection can generate substantial four-way disequilibria, and hence kurtosis; but even then, the Gaussian assumption predicts the variance accurately. In contrast to the apparent simplicity of the infinitesimal limit, data suggest that changes in genetic variance after 10 or more generations of selection are likely to be dominated by allele frequency dynamics that depend on genetic details.

scholarly journals Testing for ancient selection using cross-population allele frequency differentiation

2015 ◽  
Author(s):  
Fernando Racimo
Keyword(s):  
Allele Frequency ◽  
Modern Human ◽  
Composite Likelihood ◽  
Likelihood Method ◽  
Population Allele Frequency ◽  
Long Time ◽  
Ancient Times ◽  
Frequency Changes ◽  
Beneficial Allele ◽  
Two Populations

A powerful way to detect selection in a population is by modeling local allele frequency changes in a particular region of the genome under scenarios of selection and neutrality, and finding which model is most compatible with the data. Chen et al. (2010) developed a composite likelihood method called XP-CLR that uses an outgroup population to detect departures from neutrality which could be compatible with hard or soft sweeps, at linked sites near a beneficial allele. However, this method is most sensitive to recent selection and may miss selective events that happened a long time ago. To overcome this, we developed an extension of XP-CLR that jointly models the behavior of a selected allele in a three-population tree. Our method - called 3P-CLR - outperforms XP-CLR when testing for selection that occurred before two populations split from each other, and can distinguish between those events and events that occurred specifically in each of the populations after the split. We applied our new test to population genomic data from the 1000 Genomes Project, to search for selective sweeps that occurred before the split of Yoruba and Eurasians, but after their split from Neanderthals, and that could have led to the spread of modern-human-specific phenotypes. We also searched for sweep events that occurred in East Asians, Europeans and the ancestors of both populations, after their split from Yoruba. In both cases, we are able to confirm a number of regions identified by previous methods, and find several new candidates for selection in recent and ancient times. For some of these, we also find suggestive functional mutations that may have driven the selective events.

scholarly journals Hyperbolastic Models from a Stochastic Differential Equation Point of View

Mathematics ◽  
2021 ◽  
Vol 9 (16) ◽  
pp. 1835
Author(s):  
Antonio Barrera ◽  
Patricia Román-Román ◽  
Francisco Torres-Ruiz
Keyword(s):  
Differential Equation ◽  
Simulated Data ◽  
Real Data ◽  
Point Of View ◽  
Likelihood Method ◽  
Numerical Resolution ◽  
The Family ◽  
The Common ◽  
Linear Differential ◽  
Mean Function

A joint and unified vision of stochastic diffusion models associated with the family of hyperbolastic curves is presented. The motivation behind this approach stems from the fact that all hyperbolastic curves verify a linear differential equation of the Malthusian type. By virtue of this, and by adding a multiplicative noise to said ordinary differential equation, a diffusion process may be associated with each curve whose mean function is said curve. The inference in the resulting processes is presented jointly, as well as the strategies developed to obtain the initial solutions necessary for the numerical resolution of the system of equations resulting from the application of the maximum likelihood method. The common perspective presented is especially useful for the implementation of the necessary procedures for fitting the models to real data. Some examples based on simulated data support the suitability of the development described in the present paper.

scholarly journals The Relationship between Native American Ancestry, Body Mass Index and Diabetes Risk among Mexican-Americans

PLoS ONE ◽  
2015 ◽  
Vol 10 (10) ◽  
pp. e0141260 ◽  
Author(s):  
Hao Hu ◽  
Chad D. Huff ◽  
Yuko Yamamura ◽  
Xifeng Wu ◽  
Sara S. Strom
Keyword(s):  
Body Mass Index ◽  
Native American ◽  
Body Mass ◽  
Mexican Americans ◽  
Diabetes Risk ◽  
Native American Ancestry ◽  
The Relationship

scholarly journals Using seasonal genomic changes to understand historical adaptation: parallel selection on stickleback in highly-variable estuaries

2020 ◽  
Author(s):  
Alan Garcia-Elfring ◽  
Antoine Paccard ◽  
Timothy J. Thurman ◽  
Ben A. Wasserman ◽  
Eric P. Palkovacs ◽  
...  
Keyword(s):  
Natural Selection ◽  
Allele Frequency ◽  
Calcium Binding ◽  
Gasterosteus Aculeatus ◽  
Environmental Changes ◽  
Threespine Stickleback ◽  
Functional Enrichment ◽  
Genomic Changes ◽  
Parallel Selection ◽  
Frequency Changes

AbstractParallel evolution is considered strong evidence for natural selection. However, few studies have investigated the process of parallel selection as it plays out in real time. The common approach is to study historical signatures of selection in populations already well adapted to different environments. Here, to document selection in action under natural conditions, we study six populations of threespine stickleback (Gasterosteus aculeatus) inhabiting bar-built estuaries that undergo seasonal cycles of environmental changes. Estuaries are periodically isolated from the ocean due to sandbar formation during dry summer months, with concurrent environmental shifts that resemble the long-term changes associated with postglacial colonization of freshwater habitats by marine populations. We used pooled whole-genome sequencing (Pool-WGS) to track seasonal allele frequency changes in these populations and search for signatures of natural selection. We found consistent changes in allele frequency across estuaries, suggesting a potential role for parallel selection. Functional enrichment among candidate genes included transmembrane ion transport and calcium binding, which are important for osmoregulation and ion balance. The genomic changes that occur in threespine stickleback from bar-built estuaries could provide a glimpse into the early stages of adaptation that have occurred in many historical marine to freshwater transitions.

scholarly journals Mutation Rate Model Used in the DNA VIEW Program

2020 ◽  
Vol 10 (10) ◽  
pp. 3585 ◽  
Author(s):  
Tomasz Krajka
Keyword(s):  
Computer Simulation ◽  
Allele Frequency ◽  
Mutation Rate ◽  
Allele Frequencies ◽  
Rate Model ◽  
Dna Database ◽  
Mutation Model ◽  
Population Allele Frequency ◽  
Frequency Changes

The first problem considered in this paper is the problem of correctness of a mutation model used in the DNA VIEW program. To this end, we theoretically predict population allele frequency changes in time according to this and similar models (we determine the limit frequencies of alleles—they are uniformly distributed). Furthermore, we evaluate the speed of the above changes using computer simulation applied to our DNA database. Comparing uniformly distributed allele frequencies with these existing in the population (for example, using entropy), we conclude that this mutation model is not correct. The evolution does not follow this direction (direction of uniformly distributed frequencies). The second problem relates to the determination of the extent to which an incorrect mutation model can disturb DNA VIEW program results. We show that in typical computations (simple paternity testing without maternal mutation) this influence is negligible, but in the case of maternal mutation, this should be taken into account. Furthermore, we show that this model is inconsistent from a theoretical viewpoint. Equivalent methods result in different error levels.

scholarly journals Unique Genomic and Phenotypic Responses to Extreme and Variable pH Conditions in Purple Urchin Larvae

2020 ◽  
Vol 60 (2) ◽  
pp. 318-331
Author(s):  
April D Garrett ◽  
Reid S Brennan ◽  
Anya L Steinhart ◽  
Aubrey M Pelletier ◽  
Melissa H Pespeni
Keyword(s):  
Genetic Variation ◽  
Allele Frequency ◽  
Sea Urchin ◽  
Genetic Basis ◽  
Adaptive Genetic Variation ◽  
Protein Coding ◽  
Purple Sea Urchin ◽  
Ph Conditions ◽  
Frequency Changes ◽  
Genetic Responses

Synopsis Environmental variation experienced by a species across space and time can promote the maintenance of genetic diversity that may be adaptive in future global change conditions. Selection experiments have shown that purple sea urchin, Strongylocentrotus purpuratus, populations have adaptive genetic variation for surviving pH conditions at the “edge” (pH 7.5) of conditions experienced in nature. However, little is known about whether populations have genetic variation for surviving low-pH events beyond those currently experienced in nature or how variation in pH conditions affects organismal and genetic responses. Here, we quantified survival, growth, and allele frequency shifts in experimentally selected developing purple sea urchin larvae in static and variable conditions at three pH levels: pH 8.1 (control), pH 7.5 (edge-of-range), and pH 7.0 (extreme). Variable treatments recovered body size relative to static treatments, but resulted in higher mortality, suggesting a potential tradeoff between survival and growth under pH stress. However, within each pH level, allele frequency changes were overlapping between static and variable conditions, suggesting a shared genetic basis underlying survival to mean pH regardless of variability. In contrast, genetic responses to pH 7.5 (edge) versus pH 7.0 (extreme) conditions were distinct, indicating a unique genetic basis of survival. In addition, loci under selection were more likely to be in exonic regions than regulatory, indicating that selection targeted protein-coding variation. Loci under selection in variable pH 7.5 conditions, more similar to conditions periodically experienced in nature, performed functions related to lipid biosynthesis and metabolism, while loci under selection in static pH 7.0 conditions performed functions related to transmembrane and mitochondrial processes. While these results are promising in that purple sea urchin populations possess genetic variation for surviving extreme pH conditions not currently experienced in nature, they caution that increased acidification does not result in a linear response but elicits unique physiological stresses and survival mechanisms.

scholarly journals Coat colour in mouse populations selected for weight gain: support for hitchhiking, not pleiotropy

2013 ◽  
Vol 95 (1) ◽  
pp. 4-13 ◽  
Author(s):  
PHILIP W. HEDRICK
Keyword(s):  
Weight Gain ◽  
Allele Frequency ◽  
High Weight ◽  
Coat Colour ◽  
Correlated Response ◽  
Term Selection ◽  
Low Weight ◽  
High Weight Gain ◽  
Frequency Changes ◽  
Positive Correlations

SummaryWith many molecular markers in many species, research efforts in quantitative genetics have focused on dissecting these traits and understanding the importance of factors such as correlated response due to hitchhiking or pleiotropy. Here, in an examination of long-term selection experiments in mice, the evidence strongly supports the primary importance of hitchhiking on the coat colour loci brown and dilute in mice selected for high weight gain. First, the amount of observed change in coat colour allele frequency could not be explained by genetic drift alone, implying that selection was of high importance. Second, the allele frequency changes included reversals in the direction change, but there were still positive correlations in the early generations with differences in weight gain between the phenotypes. Third, the correlation between the change in allele frequencies and phenotypic difference in weight gain declined over time, consistent with the decay expected from linkage associations. Fourth, the changes at both loci in a short-term selection experiment for low weight gain were in the opposite direction than the changes in the contemporaneous related population selected for high weight gain.

Changepoint Analysis of Binary and Ordinal Probit Models: An Application to Bank Rate Policy Under the Interwar Gold Standard

2011 ◽  
Vol 19 (2) ◽  
pp. 188-204 ◽  
Author(s):  
Jong Hee Park
Keyword(s):  
Time Series ◽  
Gold Standard ◽  
Time Series Data ◽  
Likelihood Function ◽  
Marginal Likelihood ◽  
Estimation Method ◽  
Simulated Data ◽  
Likelihood Method ◽  
Series Data ◽  
Ordinal Probit

In this paper, I introduce changepoint models for binary and ordered time series data based on Chib's hidden Markov model. The extension of the changepoint model to a binary probit model is straightforward in a Bayesian setting. However, detecting parameter breaks from ordered regression models is difficult because ordered time series data often have clustering along the break points. To address this issue, I propose an estimation method that uses the linear regression likelihood function for the sampling of hidden states of the ordinal probit changepoint model. The marginal likelihood method is used to detect the number of hidden regimes. I evaluate the performance of the introduced methods using simulated data and apply the ordinal probit changepoint model to the study of Eichengreen, Watson, and Grossman on violations of the “rules of the game” of the gold standard by the Bank of England during the interwar period.

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