scholarly journals Distinct Patterns of Selective Sweep and Polygenic Adaptation in Evolve and Resequence Studies

2020 ◽  
Vol 12 (6) ◽  
pp. 890-904 ◽  
Author(s):  
Neda Barghi ◽  
Christian Schlötterer
Keyword(s):  
Experimental Evolution ◽  
Selective Sweep ◽  
Time Series Data ◽  
Empirical Studies ◽  
Series Data ◽  
Stabilizing Selection ◽  
Selection Signatures ◽  
Polygenic Adaptation ◽  
Frequency Changes ◽  
Optimum Model

Abstract In molecular population genetics, adaptation is typically thought to occur via selective sweeps, where targets of selection have independent effects on the phenotype and rise to fixation, whereas in quantitative genetics, many loci contribute to the phenotype and subtle frequency changes occur at many loci during polygenic adaptation. The sweep model makes specific predictions about frequency changes of beneficial alleles and many test statistics have been developed to detect such selection signatures. Despite polygenic adaptation is probably the prevalent mode of adaptation, because of the traditional focus on the phenotype, we are lacking a solid understanding of the similarities and differences of selection signatures under the two models. Recent theoretical and empirical studies have shown that both selective sweep and polygenic adaptation models could result in a sweep-like genomic signature; therefore, additional criteria are needed to distinguish the two models. With replicated populations and time series data, experimental evolution studies have the potential to identify the underlying model of adaptation. Using the framework of experimental evolution, we performed computer simulations to study the pattern of selected alleles for two models: 1) adaptation of a trait via independent beneficial mutations that are conditioned for fixation, that is, selective sweep model and 2) trait optimum model (polygenic adaptation), that is adaptation of a quantitative trait under stabilizing selection after a sudden shift in trait optimum. We identify several distinct patterns of selective sweep and trait optimum models in populations of different sizes. These features could provide the foundation for development of quantitative approaches to differentiate the two models.

scholarly journals Distance to trait optimum is a crucial factor determining the genomic signature of polygenic adaptation

2019 ◽  
Author(s):  
Eirini Christodoulaki ◽  
Neda Barghi ◽  
Christian Schlötterer
Keyword(s):  
Allele Frequency ◽  
Ad Hoc ◽  
Time Series Data ◽  
Series Data ◽  
Data Sets ◽  
Multiple Time ◽  
Adaptive Architecture ◽  
Polygenic Adaptation ◽  
Frequency Changes ◽  
Multiple Time Points

AbstractPolygenic adaptation is frequently associated with small allele frequency changes of many loci. Recent works suggest, that large allele frequency changes can be also expected. Laboratory natural selection (LNS) experiments provide an excellent experimental framework to study the adaptive architecture under controlled laboratory conditions: time series data in replicate populations evolving independently to the same trait optimum can be used to identify selected loci. Nevertheless, the choice of the new trait optimum in the laboratory is typically an ad hoc decision without consideration of the distance of the starting population to the new optimum. Here, we used forward-simulations to study the selection signatures of polygenic adaptation in populations evolving to different trait optima. Mimicking LNS experiments we analyzed allele frequencies of the selected alleles and population fitness at multiple time points. We demonstrate that the inferred adaptive architecture strongly depends on the choice of the new trait optimum in the laboratory and the significance cut-off used for identification of selected loci. Our results not only have a major impact on the design of future Evolve and Resequence (E&R) studies, but also on the interpretation of current E&R data sets.

scholarly journals Impact of Foreign Direct Investment on Human Development Index in South Africa

2020 ◽  
Vol 7 (1) ◽  
pp. 58
Author(s):  
Marius KOUNOU
Keyword(s):  
South Africa ◽  
Foreign Direct Investment ◽  
Direct Investment ◽  
Poverty Reduction ◽  
Time Series Data ◽  
Empirical Studies ◽  
Sub Saharan Africa ◽  
Series Data ◽  
Long Run ◽  
The Impact

Many studies have been done on the impact of Foreign Direct Investment on economic growth and poverty reduction in developing countries, however there is a lack of empirical studies of FDI impact on poverty reduction in South Africa which is the second largest FDI recipients of one of the poorest regions in the world (sub Saharan Africa). We used time series data from 1990 to 2017 with the ARDL method to evaluate the impact of FDI Inflow on HDI in the country. The results show that FDI inflow has no significant impact on HDI both in the short run and long run on the country. This result is consistent with findings reported in the literature.

scholarly journals The Influencing Factors on Unemployment Level - The Case of Albania

2017 ◽  
Vol 3 (3) ◽  
pp. 103
Author(s):  
Eleni Vangjeli ◽  
Jorida Agolli
Keyword(s):  
Time Series ◽  
Fast Food ◽  
Time Series Data ◽  
Empirical Studies ◽  
Mutual Effect ◽  
Series Data ◽  
Total Employment ◽  
Employment Level ◽  
Domestic Investments ◽  
The Impact

Research background: The empirical studies in labor market indicated that there are many factors that affect unemployment. These studies have analyzed these factors and concluded that exist a mutual relationship between them and unemployment. The relation between employment and FDI were studied by Craigwell (2006) and Karlsson et al. (2009). The effects of minimal wage on employment were studied by Katz and Kruger (1992) and Card (1992a) as well as Stephen Machin and Alan Manning (1994). Card, D. and Krueger, B. (1994) analyzed the effects of minimum wage raise, on fast-food restaurants in New Jersey and Pennsylvania. On the other hand, Neumark and Wascher (2000) in their findings explained that raising the minimal wage by 10% reduced the teenager employment rate with 1-2% and brought the reduction of total employment by 1.5-2%. Meanwhile, Grossberg and Sicilian (2004), found mixed results in their estimations of the minimal wage effects on employment duration period. Krugman, P(2015) one of the economy nobelist defends the theory of raising the minimal wage as a condition for improving the wellbeing. W. Phillips, (1958) studied a negative inverse relation between unemployment and inflation. Barro (1995), De Gregorio (1994), Bruno (1994) concluded that low inflation is accompanied by economic growth and higher employment level. Purpose of the article: The main aim of this article is to study and analyse factors affecting unemployment levels, because the unemployment is a critical problem in our country. We have analyzed the mutual effect of selected factors on unemployment level. The selected factors are FDI, domestic investments, inflation and minimal wage. Methodology/methods: To calculate the impact of this factors on the unemploymentlevel was used time series data for the period 1995 – 2013. Relying on time series data was made regression analysis using SPPS-21 program. Findings: Based on the testing results, we conclude that FDI, domestic investments and inflation affect negatively the unemployment level and this effect is statistically important, whereas the minimal wage has a low positive effect but such effect is not important.

scholarly journals The Effects of External Debts on Economic Growth of Kyrgyzstan

2017 ◽  
Author(s):  
Tolkun Zhumakunova ◽  
Zhainagul Kydyralieva
Keyword(s):  
Economic Growth ◽  
Soviet Union ◽  
Foreign Currency ◽  
Time Series Data ◽  
Negative Impact ◽  
Empirical Studies ◽  
Foreign Debt ◽  
Series Data ◽  
Least Squares Regression ◽  
Adf Test

In developing countries, insufficient internal sources cause the increase of need on external sources. These countries in order to maintain their economic growth apply for external debt to cover the gap of foreign currency and savings. After the collapse of Soviet Union, Kyrgyzstan began to use external funds. It is very important to use these sources in accurate areas and efficiently. Most empirical studies indicate a negative correlation between foreign debt and economic growth, especially in those countries whose foreign debts are relatively high. This work examines the correlation between foreign debt and economic growth in Kyrgyz economy. Toward this objective, it uses the economic indicators of Kyrgyzstan between 1993 and 2015. The stationarity of time series data used in this study was tested by the ADF test. Than a least-squares regression analysis is performed. According to the findings of study, foreign debt in Kyrgyzstan have a negative impact on economic growth. According to results foreign debt should be reduced in order to increase the level of economic growth in Kyrgyzstan.

scholarly journals Estimating time-varying selection coefficients from time series data of allele frequencies

2020 ◽  
Author(s):  
Iain Mathieson
Keyword(s):  
Time Series ◽  
East Asia ◽  
Ancient Dna ◽  
Experimental Evolution ◽  
Time Series Data ◽  
Natural Populations ◽  
Allele Frequencies ◽  
Series Data ◽  
Alcohol Metabolism ◽  
The Past

AbstractTime series data of allele frequencies are a powerful resource for detecting and classifying natural and artificial selection. Ancient DNA now allows us to observe these trajectories in natural populations of long-lived species such as humans. Here, we develop a hidden Markov model to infer selection coefficients that vary over time. We show through simulations that our approach can accurately estimate both selection coefficients and the timing of changes in selection. Finally, we analyze some of the strongest signals of selection in the human genome using ancient DNA. We show that the European lactase persistence mutation was selected over the past 5,000 years with a selection coefficient of 2-2.5% in Britain, Central Europe and Iberia, but not Italy. In northern East Asia, selection at the ADH1B locus associated with alcohol metabolism intensified around 4,000 years ago, approximately coinciding with the introduction of rice-based agriculture. Finally, a derived allele at the FADS locus was selected in parallel in both Europe and East Asia, as previously hypothesized. Our approach is broadly applicable to both natural and experimental evolution data and shows how time series data can be used to resolve fine-scale details of selection.

scholarly journals The impact of inflation on the unemployment rate in Egypt: a VAR approach

2021 ◽  
Vol 107 ◽  
pp. 06009
Author(s):  
Emad Attia Mohamed Omran ◽  
Yuriy Bilan
Keyword(s):  
Unemployment Rate ◽  
Time Series Data ◽  
Empirical Studies ◽  
Impulse Response Function ◽  
High Rate ◽  
Series Data ◽  
Vector Autoregressive ◽  
Political Effects ◽  
The Impact ◽  
The Relationship

Unemployment and inflation are among the most critical phenomena facing both developed and developing countries due to their harmful social, economic, and political effects. The Egyptian monetary policy’s main objective is to maintain a low inflation rate in the medium run to keep the confidence and a high rate of investment and economic growth. At the same time, economists argue that targeting a low-rate of inflation may increase unemployment. Although the classical Philips curve indicates a trade-off between inflation and unemployment, several empirical studies have argued that the relationship between inflation and unemployment depends on the shocks’ source and lagged responses. The main objective of this paper is to examine the relationship between inflation and Egypt’s unemployment rate. We used time-series data from 1980 to 2019, where a vector autoregressive (VAR) model and the Impulse response function tool (IRF) were employed. The results show that inflation has a positive relationship with GDP while negatively affecting the unemployment rate.

scholarly journals The Impact of Foreign Direct Investment on Economic Growth in Nigeria

2015 ◽  
Vol 7 (4) ◽  
pp. 90-97
Author(s):  
Sani Ali Ibrahim
Keyword(s):  
Economic Growth ◽  
Foreign Direct Investment ◽  
Direct Investment ◽  
Time Series Data ◽  
Empirical Studies ◽  
Trade Openness ◽  
National Income ◽  
Series Data ◽  
Long Run ◽  
The Impact

The economic development performance can be used to measure the economic growth of a given country. In economic analysis, a country can attain economic growth through the growth in national income measurement. However, there were rigorous discussions on the role of foreign direct investment (FDI) on economic growth and continued to be a topic of discussion on the contemporary economy. This paper serves as an extension to the previous empirical studies on the issue by providing some evidence from time series data for the period 1971 to 2013 of Nigeria. The primary aim of this study is to analyze the impact of FDI on economic growth of Nigeria taking trade openness, Gross Fixed Capital Formation and human capital as control variables. To investigate the long run equilibrium relationship, Johansen and Juselius co-integration approach is analyzed, while the speed of adjustment in the short run is analyzed through the use of VECM method. In Nigeria, FDI, GFCF and HK have long run relationship with economic growth. However, the coefficient of ECM in Nigeria is statistically significant at 1% level of significance. Thus, 10.8% of the adjustment is achieved due to the correction of the adjustment speed in a year.

scholarly journals Pengaruh Mekanisme Good Corporate Governance, Debt to Equity Ratio, Asset Growth terhadap Kinerja Perusahaan

2018 ◽  
Vol 1 (2) ◽  
Author(s):  
Kartika Mirawati Tika Mirawati ◽  
Meina Wulansari
Keyword(s):  
Corporate Governance ◽  
Time Series Data ◽  
Stock Exchange ◽  
Empirical Studies ◽  
Secondary Data ◽  
Series Data ◽  
Independent Variables ◽  
Mining Companies ◽  
Good Corporate Governance ◽  
Asset Growth

This study aims to determine the effect of the mechanism of Good Corporate Governance, DER, Asset Growth on company performance (empirical studies on mining companies listed on the Indonesia, Thailand, Malaysia Stock Exchange period 2010-2017). This research is a quantitative research which aims to systematically explained about the facts and properties in an object in the study then merged between variables related to it by presenting secondary data from financial reports from mining companies in the countries of Indonesia, Malaysia and Thailand. The population used in this study were mining companies listed on the Indonesia, Malaysia and Thailand Stock Exchanges in the period 2013 to 2017. The samples used in this study were 15 mining companies in the countries of Indonesia, Malaysia and Thailand by using the Purpose Method. Sampling the objectives for obtaining a representative sample that matches the criteria that have been confirmed. In this study, the data analysis method used is the data panel (pooled data) which is a combination of time series data and data between individuals or cross sections in mining companies in Indonesia, Malaysia and Thailand. Research Results for mining companies in Indonesia The R square value of this model is 0.732 percent, meaning that the variation of the profit company's performance can be explained by the independent variables analyzed, namely the mechanism of Good Corporate Governance, DER, the remaining Asset Growth percent of 73.20 the remaining 26.80 percent is explained by other factors not included in this study. Furthermore, the R square value of this model of 0.731 percent means that the variation of the company's profit performance can be explained by the independent variables analyzed, namely the mechanism of Good Corporate Governance, DER, the remaining percent Asset Growth of 73.10 the remaining 26.90 percent is explained by other factors not included in this research .. and thailand country The R square value of this model is 0.849 percent which means that the variation of profit that can be explained by the independent variables analyzed are NIM, BOPO, CAR and NPL of 84.90 percent of the remaining 15.10 percent is explained by other factors that do not included in this study.

scholarly journals The education investment dimension of international personal remittances in Colombia

2015 ◽  
Vol 4 (4) ◽  
pp. 428-436
Author(s):  
Kunofiwa Tsaurai
Keyword(s):  
Time Series Data ◽  
Empirical Studies ◽  
Series Data ◽  
International Remittances ◽  
Long Run ◽  
Integration Test ◽  
Enrolment Ratio ◽  
Capital Development ◽  
Integrated Or ◽  
The Relationship

The study investigated the relationship between personal international remittances received and gross enrolment ratio in Colombia. There are three hypotheses explaining the relationship between personal international remittances and education (human capital development). These are (1) remittances-led education hypothesis, (2) education-led remittances hypothesis and (3) neutrality hypothesis that says there is no relationship at all between these two variables. Although majority of the empirical studies support the remittances-led education hypothesis, the subject is still attracting contradicting findings and not yet conclusive. It is on the backdrop of such lack of consensus in the literature that the author investigated the relationship between personal remittances received and gross enrolment ratio primary and secondary (%) in Colombia. The study used the auto-regressive distributive lag (ARDL) bounds co-integration testing technique with annual time series data ranging between 1978 and 2010 to determine the existence of a long run relationship between personal remittances and education in Colombia. The ARDL F-bounds co-integration test revealed that personal remittances received and gross enrolment ratio for both primary and secondary schools in Colombia are not co-integrated or they do not have any long run relationship, thus supporting the neutrality hypothesis. This conclusion was arrived at using either personal remittances or gross enrolment ratio as a dependent variable. These results imply that personal remittances received in Colombia were directed more towards consumption and not invested in education. The study therefore urges the Colombian authorities to concientise the recipients of the personal remittances to invest in the children’s education rather than spending the remittances on consumption purposes

scholarly journals Benchmarking software tools for detecting and quantifying selection in Evolve and Resequencing studies

2019 ◽  
Author(s):  
Christos Vlachos ◽  
Claire Burny ◽  
Marta Pelizzola ◽  
Rui Borges ◽  
Andreas Futschik ◽  
...  
Keyword(s):  
Experimental Evolution ◽  
Time Series Data ◽  
Software Tools ◽  
Series Data ◽  
Test Statistics ◽  
Selection Processes ◽  
Study Selection ◽  
Powerful Approach ◽  
Future Data ◽  
Data Collections

AbstractThe combination of experimental evolution with whole genome re-sequencing of pooled individuals, also called Evolve and Resequence (E&R) is a powerful approach to study selection processes and to infer the architecture of adaptive variation. Given the large potential of this method, a range of software tools were developed to identify selected SNPs and to measure their selection coefficients. In this benchmarking study, we are comparing 15 test statistics implemented in 10 software tools using three different scenarios. We demonstrate that the power of the methods differs among the scenarios, but some consistently outperform others. LRT-1, which takes advantage of time series data consistently performed best for all three scenarios. Nevertheless, the CMH test, which requires only two time points had almost the same performance. This benchmark study will not only facilitate the analysis of already existing data, but also affect the design of future data collections.

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