Bayesian Inference of Natural Selection from Allele Frequency Time Series

Schraiber, Joshua G.; Evans, Steven N.; Slatkin, Montgomery

doi:10.1534/genetics.116.187278

Cited by 108 publications

(79 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…ref. 43), as well as the use of approximate Bayesian computation (ABC), which failed to provide informative posteriors even after we implemented a Sequential Monte Carlo (SMC) procedure that theoretically improved the efficiency of by a factor of 10 9 .…”

Section: Methodsmentioning

confidence: 99%

Spotted phenotypes in horses lost attractiveness in the Middle Ages

Wutke

Benecke

Sandoval‐Castellanos

et al. 2016

Sci Rep

View full text Add to dashboard Cite

Horses have been valued for their diversity of coat colour since prehistoric times; this is especially the case since their domestication in the Caspian steppe in ~3,500 BC. Although we can assume that human preferences were not constant, we have only anecdotal information about how domestic horses were influenced by humans. Our results from genotype analyses show a significant increase in spotted coats in early domestic horses (Copper Age to Iron Age). In contrast, medieval horses carried significantly fewer alleles for these phenotypes, whereas solid phenotypes (i.e., chestnut) became dominant. This shift may have been supported because of (i) pleiotropic disadvantages, (ii) a reduced need to separate domestic horses from their wild counterparts, (iii) a lower religious prestige, or (iv) novel developments in weaponry. These scenarios may have acted alone or in combination. However, the dominance of chestnut is a remarkable feature of the medieval horse population.

show abstract

Section: Methodsmentioning

confidence: 99%

Spotted phenotypes in horses lost attractiveness in the Middle Ages

Wutke

Benecke

Sandoval‐Castellanos

et al. 2016

Sci Rep

View full text Add to dashboard Cite

show abstract

“…15. This analysis based on Bayesian probabilities was performed for each allele that presented diversity among ancient individuals (Fig.…”

Section: Methodsmentioning

confidence: 99%

Malaria was a weak selective force in ancient Europeans

Gelabert

Olalde

de-Dios

et al. 2017

Sci Rep

View full text Add to dashboard Cite

Malaria, caused by Plasmodium parasites, is thought to be one of the strongest selective forces that has shaped the genome of modern humans and was endemic in Europe until recent times. Due to its eradication around mid-twentieth century, the potential selective history of malaria in European populations is largely unknown. Here, we screen 224 ancient European genomes from the Upper Palaeolithic to the post-Roman period for 22 malaria-resistant alleles in twelve genes described in the literature. None of the most specific mutations for malaria resistance, like those at G6PD, HBB or Duffy blood group, have been detected among the available samples, while many other malaria-resistant alleles existed well before the advent of agriculture. We detected statistically significant differences between ancient and modern populations for the ATP2B4, FCGR2B and ABO genes and we found evidence of selection at IL-10 and ATP2B4 genes. However it is unclear whether malaria is the causative agent, because these genes are also involved in other immunological challenges. These results suggest that the selective force represented by malaria was relatively weak in Europe, a fact that could be associated to a recent historical introduction of the severe malaria pathogen.The malaria parasite Plasmodium falciparum is one of the main causes of child mortality worldwide, although other species from the same genus, P. vivax, P. malariae and P. ovale are also causative agents of the disease. Therefore, it is not surprising that malaria is one of the strongest known selective pressures that have recently shaped the human genome. Malaria is the evolutionary driving force behind sickle-cell disease (HbS), thalassemia, glucose-6-phosphatase deficiency (G6PD) and other erythrocyte defects that together comprise the most common Mendelian diseases of humankind. Remarkably, populations from different geographical areas have developed different genetic mechanisms adapted to malaria resistance; for instance, the HbS allele at the HBB gene is common in Africa but rare in Southeast Asia, whereas the HbE alelle shows a reversed pattern. Resistance to malaria includes primarily genes involved in immunological response, but also some involved in inflammation and cell adhesion and even genes related to metabolic pathways. The fact that different malaria-resistance alleles have arisen in different places suggests that this adaptation occurred relatively recent in human history, at least well after the Out of Africa migration 1 . P. falciparum may have rapidly spread from its African tropical origins to other tropical and subtropical regions of the world only within the last 6,000 years 2 . The recent origin of the worldwide P. falciparum populations, which are the most malignant of human malarial parasites, may account for its virulence 3 . Thus, haplotype analysis at the G6PD locus suggests that the African resistance allele to P. falciparum originated within the last 10,000 years 4 while a similar analysis at the HbE alleles (variants of the HBB gene) in...

show abstract

“…These probabilities were then used in a maximum likelihood (ML) framework for inferring the model parameters, including effective population size. More recently, improved analytic approximations to the likelihood function were developed using concepts such as spectral representations of the transition density (Steinrücken et al 2014) and path augmentation (Schraiber et al 2016). Other approaches have employed Bayesian inference methods (Foll et al 2015;Ferrer-Admetlla et al 2016) and likelihood ratio tests (Feder et al 2014).…”

mentioning

confidence: 99%

Maximum Likelihood Estimation of Fitness Components in Experimental Evolution

et al. 2019

View full text Add to dashboard Cite

Estimating fitness differences between allelic variants is a central goal of experimental evolution. Current methods for inferring such differences from allele frequency time series typically assume that the effects of selection can be described by a fixed selection coefficient. However, fitness is an aggregate of several components including mating success, fecundity, and viability. Distinguishing between these components could be critical in many scenarios. Here, we develop a flexible maximum likelihood framework that can disentangle different components of fitness from genotype frequency data, and estimate them individually in males and females. As a proof-of-principle, we apply our method to experimentally evolved cage populations of Drosophila melanogaster, in which we tracked the relative frequencies of a loss-of-function and wild-type allele of yellow. This X-linked gene produces a recessive yellow phenotype when disrupted and is involved in male courtship ability. We find that the fitness costs of the yellow phenotype take the form of substantially reduced mating preference of wild-type females for yellow males, together with a modest reduction in the viability of yellow males and females. Our framework should be generally applicable to situations where it is important to quantify fitness components of specific genetic variants, including quantitative characterization of the population dynamics of CRISPR gene drives.

show abstract

Bayesian Inference of Natural Selection from Allele Frequency Time Series

Cited by 108 publications

References 35 publications

Spotted phenotypes in horses lost attractiveness in the Middle Ages

Spotted phenotypes in horses lost attractiveness in the Middle Ages

Malaria was a weak selective force in ancient Europeans

Maximum Likelihood Estimation of Fitness Components in Experimental Evolution

Contact Info

Product

Resources

About