scholarly journals Untangling the Mathematical Relation Between Natural Selection and Adaptive Radiation Using Macromolecules and Microevolutionary Forces

2020 ◽  
pp. 313-339
Author(s):  
Bharat Kwatra ◽  
Maanvi Mudgil
Keyword(s):  
Natural Selection ◽  
Dna Fingerprinting ◽  
Adaptive Radiation ◽  
Environment Interaction ◽  
Male And Female ◽  
Evolutionary Forces ◽  
Gene Environment Interaction ◽  
Gene Environment ◽  
Mathematical Relation

Simulating natural selection over subsequent generations of Oniscus asellus, the fittest selected male and female bugs in different diet was used to analyze the concentration of proteins in their body along their frequency in continuous mapped generations over hundred seed values, further DNA Fingerprinting of these selected bugs revealed a relationship with their parents originated from different geographic areas/borders. It was observed that variation in microevolutionary forces caused variation in macromolecules by setting up a gene-environment interaction which deduced natural selection in order to define adaptive radiation and speciation by micro-evolutionary forces.

Gene-Environment Interaction in the Determination of Levels of Haemostatic Variables Involved in Thrombosis and Fibrinolysis

1997 ◽  
Vol 78 (01) ◽  
pp. 457-461 ◽  
Author(s):  
S E Humphries ◽  
A Panahloo ◽  
H E Montgomery ◽  
F Green ◽  
J Yudkin
Keyword(s):  
Environment Interaction ◽  
Gene Environment Interaction ◽  
Gene Environment

Gene-environment Interaction on the Risk of Type 2 Diabetes Among Ethnic Minority Populations Living in Europe and North America: A Systematic Review

2020 ◽  
Vol 16 (5) ◽  
pp. 457-470 ◽  
Author(s):  
Mohammad H. Zafarmand ◽  
Parvin Tajik ◽  
René Spijker ◽  
Charles Agyemang
Keyword(s):  
Type 2 Diabetes ◽  
North America ◽  
Ethnic Minority ◽  
Ethnic Minorities ◽  
Minority Groups ◽  
Environment Interaction ◽  
Ethnic Minority Groups ◽  
Gene Environment Interaction ◽  
Gene Environment

Background: The body of evidence on gene-environment interaction (GEI) related to type 2 diabetes (T2D) has grown in the recent years. However, most studies on GEI have sought to explain variation within individuals of European ancestry and results among ethnic minority groups are inconclusive. Objective: To investigate any interaction between a gene and an environmental factor in relation to T2D among ethnic minority groups living in Europe and North America. Methods: We systematically searched Medline and EMBASE databases for the published literature in English up to 25th March 2019. The screening, data extraction and quality assessment were performed by reviewers independently. Results: 1068 studies identified through our search, of which nine cohorts of six studies evaluating several different GEIs were included. The mean follow-up time in the included studies ranged from 5 to 25.7 years. Most studies were relatively small scale and few provided replication data. All studies included in the review included ethnic minorities from North America (Native-Americans, African- Americans, and Aboriginal Canadian), none of the studies in Europe assessed GEI in relation to T2D incident in ethnic minorities. The only significant GEI among ethnic minorities was HNF1A rs137853240 and smoking on T2D incident among Native-Canadians (Pinteraction = 0.006). Conclusion: There is a need for more studies on GEI among ethnicities, broadening the spectrum of ethnic minority groups being investigated, performing more discovery using genome-wide approaches, larger sample sizes for these studies by collaborating efforts such as the InterConnect approach, and developing a more standardized method of reporting GEI studies are discussed.

scholarly journals Estimating the effective sample size in association studies of quantitative traits

2021 ◽  
Author(s):  
Andrey Ziyatdinov ◽  
Jihye Kim ◽  
Dmitry Prokopenko ◽  
Florian Privé ◽  
Fabien Laporte ◽  
...  
Keyword(s):  
Statistical Power ◽  
Quantitative Traits ◽  
Mixed Model ◽  
Association Studies ◽  
Effective Sample Size ◽  
Environment Interaction ◽  
Uk Biobank ◽  
Gene Environment Interaction ◽  
Gene Environment ◽  
The Uk

Abstract The effective sample size (ESS) is a metric used to summarize in a single term the amount of correlation in a sample. It is of particular interest when predicting the statistical power of genome-wide association studies (GWAS) based on linear mixed models. Here, we introduce an analytical form of the ESS for mixed-model GWAS of quantitative traits and relate it to empirical estimators recently proposed. Using our framework, we derived approximations of the ESS for analyses of related and unrelated samples and for both marginal genetic and gene-environment interaction tests. We conducted simulations to validate our approximations and to provide a quantitative perspective on the statistical power of various scenarios, including power loss due to family relatedness and power gains due to conditioning on the polygenic signal. Our analyses also demonstrate that the power of gene-environment interaction GWAS in related individuals strongly depends on the family structure and exposure distribution. Finally, we performed a series of mixed-model GWAS on data from the UK Biobank and confirmed the simulation results. We notably found that the expected power drop due to family relatedness in the UK Biobank is negligible.

scholarly journals Maternal iron deficiency perturbs embryonic cardiovascular development in mice

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Jacinta I. Kalisch-Smith ◽  
Nikita Ved ◽  
Dorota Szumska ◽  
Jacob Munro ◽  
Michael Troup ◽  
...  
Keyword(s):  
Iron Deficiency ◽  
Environment Interaction ◽  
Cardiovascular Development ◽  
Retinoic Acid Signalling ◽  
Gene Environment Interaction ◽  
Iron Administration ◽  
Gene Environment ◽  
Cardiovascular Defects ◽  
Craniofacial Defects ◽  
Maternal Iron

AbstractCongenital heart disease (CHD) is the most common class of human birth defects, with a prevalence of 0.9% of births. However, two-thirds of cases have an unknown cause, and many of these are thought to be caused by in utero exposure to environmental teratogens. Here we identify a potential teratogen causing CHD in mice: maternal iron deficiency (ID). We show that maternal ID in mice causes severe cardiovascular defects in the offspring. These defects likely arise from increased retinoic acid signalling in ID embryos. The defects can be prevented by iron administration in early pregnancy. It has also been proposed that teratogen exposure may potentiate the effects of genetic predisposition to CHD through gene–environment interaction. Here we show that maternal ID increases the severity of heart and craniofacial defects in a mouse model of Down syndrome. It will be important to understand if the effects of maternal ID seen here in mice may have clinical implications for women.

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