scholarly journals Definition and Estimation of Higher-Order Gene Fixation Indices

Genetics ◽  
1987 ◽  
Vol 117 (4) ◽  
pp. 783-793
Author(s):  
Kermit Ritland
Keyword(s):  
Polymorphic Locus ◽  
Fixation Index ◽  
Genotypic Frequency ◽  
Frequency Data ◽  
Selective Neutrality ◽  
Gene Associations ◽  
Fixation Indices ◽  
The Relationship ◽  
Unequal Frequency ◽  
Gene Index

ABSTRACT Fixation indices summarize the associations between genes that arise from the joint effects of inbreeding and selection. In this paper, fixation indices are derived for pairs, triplets and quadruplets of genes at a single multiallelic locus. The fixation indices are obtained by dividing cumulants by constants; the cumulants describe the statistical distribution of alleles and the constants are functions of gene frequency. The use of cumulants instead of moments is necessary only for four-gene indices, when the fourth cumulant is used. A second type of four-gene index is also required, and this index is based upon the covariation of second-order cumulants. At multiallelic loci, a large number of indices is possible. If alleles are selectively neutral, the number of indices is reduced and the relationship between gene identity and gene cumulants is shown.—Two-gene indices can always be estimated from genotypic frequency data at a single polymorphic locus. Three-gene indices are also estimable except when allele frequency equals one-half. Four-gene indices are not estimable unless selection is assumed to have an equal effect upon each allele (such as under selective neutrality) and the locus contains at least three alleles of unequal frequency. For diallelic or selected loci, an alternative four- gene fixation index is proposed. This index incorporates both types of four-gene associations but cannot be related to gene identity.

Implied volatility smirk and future stock returns: evidence from the German market

2015 ◽  
Vol 41 (12) ◽  
pp. 1357-1379
Author(s):  
Di Mo ◽  
Neda Todorova ◽  
Rakesh Gupta
Keyword(s):  
High Frequency ◽  
Implied Volatility ◽  
Stock Index ◽  
High Frequency Data ◽  
Frequency Data ◽  
European Options ◽  
German Market ◽  
Content Type ◽  
The Relationship ◽  
Option Market

Purpose – The purpose of this paper is to investigate the relationship between option’s implied volatility smirk (IVS) and excess returns in the Germany’s leading stock index Deutscher-Aktien Index (DAX) 30. Design/methodology/approach – The study defines the IVS as the difference in implied volatility derived from out-of-the-money put options and at-the-money call options. This study employs the ordinary least square regression with Newey-West correction to analyse the relationship between IVS and excess DAX 30 index returns in Germany. Findings – The authors find that the German market adjusts information in an efficient way. Consequently, there is no information linkage between option volatility smirk and market index returns over the nine years sample period after considering the control variables, global financial crisis dummies, and the subsample test. Research limitations/implications – This study finds that the option market and the DAX 30 index are informationally efficient. Implications of the findings are that the investors cannot profit from the information contained in the IVS since the information is simultaneously incorporated into option prices and the stock index prices. The findings of this study are applicable to other markets with European options and for market participants who seek to exploit short-term market divergence from efficiency. Originality/value – The relationship between IVS and stock price changes has not been investigated sufficiently in academic literature. This study looks at this relationship in the context of European options using high-frequency transactions data. Prior studies look at this relationship for only American options using daily data. Pricing efficiency of the European option market using high-frequency data have not been studied in the prior literature. The authors find different results for the German market based on this high-frequency data set.

SSR cross-amplification and variation within coffee trees (Coffea spp.)

Genome ◽  
2004 ◽  
Vol 47 (6) ◽  
pp. 1071-1081 ◽  
Author(s):  
V Poncet ◽  
P Hamon ◽  
J Minier ◽  
C Carasco ◽  
S Hamon ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Null Allele ◽  
Polymorphic Locus ◽  
Coffea Canephora ◽  
Fixation Index ◽  
High Genetic Diversity ◽  
Allele Number ◽  
Primer Sets ◽  
Polymorphism Level ◽  
Potential Use

Primer sets were developed from 85 Coffea arabica sequences in addition to 25 already published primer sets. They were subsequently used for amplification in six African Coffea species: Coffea canephora (CAN), Coffea eugenioides (EUG), Coffea heterocalyx (HET), Coffea liberica (LIB), Coffea sp. Moloundou (MOL) and Coffea pseudozanguebariae (PSE). The amplification percentages for these 110 primer pairs ranged from 72.7% for LIB to 86.4% for PSE. Good transferability was thus obtained within the Coffea genus. When focusing on the two species CAN and PSE, high genetic diversity, high polymorphic locus rates (above 80%) and a mean allele number per polymorphic locus of more than 3 were noted. The estimated null allele percentage was –11% for PSE and –9% for CAN. Sixty three percent (CAN) and 79.5% (PSE) of the fixation index (Fis) values were positive. The within-species polymorphism information content (PIC) distribution showed two modes for both species. Although the two species shared 30 polymorphic loci, no correlation between CAN and PSE PIC values was obtained. All of these data are discussed in relation to the polymorphism level and the potential use of these SSRs for subsequent analysis of genetic diversity or genetic mapping.Key words: microsatellite, Coffea, transferability, genetic diversity.

scholarly journals GCSENet: A GCN, CNN and SENet ensemble model for microRNA-disease association prediction

2021 ◽  
Vol 17 (6) ◽  
pp. e1009048
Author(s):  
Zhong Li ◽  
Kaiyancheng Jiang ◽  
Shengwei Qin ◽  
Yijun Zhong ◽  
Arne Elofsson
Keyword(s):  
Disease Gene ◽  
Critical Role ◽  
Mirna Gene ◽  
Disease Association ◽  
New Drugs ◽  
Evaluation Indexes ◽  
Gene Associations ◽  
Feature Weight ◽  
The Relationship ◽  
Positive Effect

Recently, an increasing number of studies have demonstrated that miRNAs are involved in human diseases, indicating that miRNAs might be a potential pathogenic factor for various diseases. Therefore, figuring out the relationship between miRNAs and diseases plays a critical role in not only the development of new drugs, but also the formulation of individualized diagnosis and treatment. As the prediction of miRNA-disease association via biological experiments is expensive and time-consuming, computational methods have a positive effect on revealing the association. In this study, a novel prediction model integrating GCN, CNN and Squeeze-and-Excitation Networks (GCSENet) was constructed for the identification of miRNA-disease association. The model first captured features by GCN based on a heterogeneous graph including diseases, genes and miRNAs. Then, considering the different effects of genes on each type of miRNA and disease, as well as the different effects of the miRNA-gene and disease-gene relationships on miRNA-disease association, a feature weight was set and a combination of miRNA-gene and disease-gene associations was added as feature input for the convolution operation in CNN. Furthermore, the squeeze and excitation blocks of SENet were applied to determine the importance of each feature channel and enhance useful features by means of the attention mechanism, thus achieving a satisfactory prediction of miRNA-disease association. The proposed method was compared against other state-of-the-art methods. It achieved an AUROC score of 95.02% and an AUPR score of 95.55% in a 10-fold cross-validation, which led to the finding that the proposed method is superior to these popular methods on most of the performance evaluation indexes.

scholarly journals Bayesian analyses question the role of climate in Chulmun demography

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Habeom Kim ◽  
Gyoung-Ah Lee ◽  
Enrico R. Crema
Keyword(s):  
Regional Differences ◽  
Negative Impact ◽  
Population Decline ◽  
Frequency Data ◽  
Coastal Regions ◽  
Bayesian Analyses ◽  
Time Frequency ◽  
Potential Factor ◽  
The Relationship

AbstractWe investigate the relationship between climatic and demographic events in Korea during the Chulmun period (10,000–3,500 cal. BP) by analyzing paleoenvironmental proxies and 14C dates. We focus on testing whether a cooling climate, and its potential negative impact on millet productivity around the mid 5th-millennium cal. BP, triggered the population decline suggested by the archaeological record. We employ a Bayesian approach that estimates the temporal relationship between climatic events and change-points in the rate of growth in human population as inferred from radiocarbon time frequency data. Our results do not support the climate-induced population decline hypothesis for three reasons. First, our Bayesian analyses suggest that the cooling event occurred after the start of the population decline inferred from the radiocarbon time–frequency record. Second, we did not find evidence showing a significant reduction of millet-associated dates occurring during the cooling climate. Third, we detected different magnitudes of decline in the radiocarbon time–frequency data in the inland and coastal regions, indicating that the even if cooling episodes were ultimately responsible of these population ‘busts’, their impact was most likely distinct between these regions. We discuss our results highlighting the long tradition of mobility-based subsistence strategy in coastal regions as a potential factor contributing to the regional differences we were able to detect.

scholarly journals Evolution of enzyme levels in metabolic pathways: A theoretical approach. Part 2

2021 ◽  
Author(s):  
Charlotte Coton ◽  
Christine Dillmann ◽  
Dominique de Vienne
Keyword(s):  
Metabolic Pathways ◽  
Metabolic Networks ◽  
Cell Function ◽  
Enzyme Concentration ◽  
Adaptive Landscape ◽  
Selective Neutrality ◽  
Simplifying Assumptions ◽  
Selection For ◽  
The Relationship ◽  
Competition For Resources

Metabolism is essential for cell function and adaptation. Because of their central role in metabolism, kinetic parameters and enzyme concentrations are under constant selective pressure to adapt the fluxes of the metabolic networks to the needs of the organism. In the line of various studies dealing with enzyme evolution, we recently developed a model of evolution of enzyme concentrations under selection for increased flux, considered as a proxy of fitness (Coton 2021). Taking into account two realistic cellular constraints, competition for resources and co-regulations, we determined the evolutionary equilibria and the ranges of neutral variations of enzyme concentrations. In this article, we give more generality to this model, by considering that the enzymes of a pathway can belong to different groups of co-regulation. We determined the equilibria and showed that the constraints modify the adaptive landscape by limiting the number of independent dimensions. We also showed that any trade-off between enzyme concentration is sufficient to limit the flux and to relax selection for increasing other enzyme concentrations. Even though the model is based on simplifying assumptions, the complexity of the relationship between enzyme concentrations prevents the analysis of selective neutrality.

Genomic Approaches Identify Novel Gene Associations with Out of Season Lambing in Sheep

2019 ◽  
Vol 110 (5) ◽  
pp. 577-586 ◽  
Author(s):  
Christian J Posbergh ◽  
Michael L Thonney ◽  
Heather J Huson
Keyword(s):  
Candidate Genes ◽  
Multiple Testing ◽  
Association Studies ◽  
Reproductive Hormones ◽  
Day Length ◽  
Fixation Index ◽  
Multiple Testing Correction ◽  
Genetic Progress ◽  
Genome Wide ◽  
Gene Associations

Abstract Sheep are seasonally polyestrous, traditionally breeding when the day length shortens in the autumn. The changing photoperiod stimulates reproductive hormones through a series of chemical pathways, ultimately leading to cyclicity. Some breeds of sheep, such as the Polypay and Dorset, have been selected for reduced seasonality and can lamb year-round. Despite this selection, there is still variation within these breeds in the ability to lamb out of season. The identification of out of season lambing quantitative trait loci has the potential to improve genetic progress using genomic selection schemes. Association studies, fixation index (FST), and runs of homozygosity (ROH) were evaluated to identify regions of the genome that influence the ability of ewes to lamb out of season. All analyses used genotypic data from the Illumina Ovine HD beadchip. Genome-wide associations were tested both across breeds in 257 ewes and within the Dorset and Polypay breeds. FST was measured across breeds and between UK and US Dorsets to assess population differences. ROH were estimated in ewes to identify homozygous regions contributing to out of season lambing. Significant associations after multiple testing correction were found through these approaches, leading to the identification of several candidate genes for further study. Genes involved with eye development, reproductive hormones, and neuronal changes were identified as the most promising for influencing the ewe’s ability to lamb year-round. These candidate genes could be advantageous for selection for improved year-round lamb production and provide better insight into the complex regulation of seasonal reproduction.

scholarly journals Realized Measures to Explain Volatility Changes over Time

2020 ◽  
Vol 13 (6) ◽  
pp. 125
Author(s):  
Christos Floros ◽  
Konstantinos Gkillas ◽  
Christoforos Konstantatos ◽  
Athanasios Tsagkanos
Keyword(s):  
High Frequency ◽  
Realized Volatility ◽  
High Frequency Data ◽  
Leverage Effect ◽  
Frequency Data ◽  
Specific Group ◽  
Volatility Feedback ◽  
Changes Over Time ◽  
The Relationship ◽  
Over Time

We studied (i) the volatility feedback effect, defined as the relationship between contemporaneous returns and the market-based volatility, and (ii) the leverage effect, defined as the relationship between lagged returns and the current market-based volatility. For our analysis, we used daily measures of volatility estimated from high frequency data to explain volatility changes over time for both the S&P500 and FTSE100 indices. The period of analysis spanned from January 2000 to June 2017 incorporating various market phases, such as booms and crashes. Based on the estimated regressions, we found evidence that the returns of S&P500 and FTSE100 indices were well explained by a specific group of realized measure estimators, and the returns negatively affected realized volatility. These results are highly recommended to financial analysts dealing with high frequency data and volatility modelling.

The inheritance of diazinon resistance in an Australian strain of Musca domesticaL.

1963 ◽  
Vol 54 (3) ◽  
pp. 461-465 ◽  
Author(s):  
R. J. Hart
Keyword(s):  
Musca Domestica ◽  
Strong Evidence ◽  
Organic Phosphate ◽  
Dominant Factor ◽  
Frequency Data ◽  
House Flies ◽  
Response Information ◽  
Resistant Form ◽  
The Relationship

The genetics of diazinon resistance in an Australian strain of Musca domestica L. was investigated by means of two series of repeated back-crosses of the hybrid resistant form to the susceptible. Resistance was maintained through nine and eleven generations in the separate studies. The ratio of susceptible to resistant hybrid flies found in the progeny of each cross was approximately 1:1.In the second series, the frequency data were supported by dosage/response information on the relationship between dosage of insecticide and mortality. Together with the result of a previous study, the data furnish strong evidence that a fully dominant factor is responsible for the diazinon resistance in the Perth strain of house-flies resistant to organic phosphate insecticides.

scholarly journals Genetic loads at a polymorphic locus which is maintained by frequency-dependent selection

1970 ◽  
Vol 16 (2) ◽  
pp. 145-150 ◽  
Author(s):  
Motoo Kimura ◽  
Tomoko Ohta
Keyword(s):  
Population Size ◽  
Effective Population Size ◽  
Genetic Drift ◽  
Gene Frequency ◽  
Polymorphic Locus ◽  
Small Populations ◽  
Effective Population ◽  
Frequency Dependent ◽  
Frequency Dependent Selection ◽  
Selective Neutrality

SUMMARYIf a polymorphic locus is maintained in finite populations by frequency-dependent selection with selective neutrality at equilibrium, it is generally accompanied by two genetic loads, i.e. the dysmetric and the drift loads. The former arises because the fitness of the population may not be at a maximum at the equilibrium gene frequency and the latter because genetic drift in small populations displaces the gene frequency from its equilibrium value.In some simple models of frequency-dependent selection considered, the drift load is independent of selection coefficients and is approximately equal to (n−1)/(2Ne), where n is the number of alleles and Ne is the effective population size.

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