Hierarchical structures which lie hidden between human complex conditions and reproductivity cannot be simple, and trends of each population component does not necessarily pertain to evolutionary theories. As an illustration, the fitness of individuals with heritable extreme conditions can be low across continuing generations in observational data. Autism and schizophrenia are characterized by such evolutionary paradox of survival and hypo-reproductivity in the complex human diversity. Theoretical mechanisms for the observational fact were evaluated using a simple formula which was established to simulate stochastic epistasis-mediated phenotypic diversity. The survival of the hypo-reproductive extreme tail could be imitated just by the predominant presence of stochastic epistasis mechanism, suggesting that stochastic epistasis might be a genetic prerequisite for the evolutionary paradox. As supplemental cofactors of stochastic epistasis, a random link of the extreme tail to both un- and hyper-reproductivity and group assortative mating were shown to be effective for the paradox. Especially, the mixed localization of un- and hyper-reproductivity in the tail of a generational population evidently induced the continuous survival of outliers and extremes. These hypothetical considerations and mathematical simulations may suggest the significance of stochastic epistasis as the essential genetic background of complex human diversity.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1016/j.biosystems.2021.104393 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Simulation of functional additive and non-additive genetic effects using statistical estimates from quantitative genetic models.
Heredity (Edinb)
July 2024
Center for Quantitative Genetics and Genomics, Aarhus University, Aarhus, Denmark.
Stochastic simulation software is commonly used to aid breeders designing cost-effective breeding programs and to validate statistical models used in genetic evaluation. An essential feature of the software is the ability to simulate populations with desired genetic and non-genetic parameters. However, this feature often fails when non-additive effects due to dominance or epistasis are modeled, as the desired properties of simulated populations are estimated from classical quantitative genetic statistical models formulated at the population level.
View Article and Find Full Text PDFscCompressSA: dual-channel self-attention based deep autoencoder model for single-cell clustering by compressing gene-gene interactions.
BMC Genomics
April 2024
Zhejiang Sci-Tech University, Second Street 928, Hangzhou, Zhejiang, 310018, China.
Background: Single-cell clustering has played an important role in exploring the molecular mechanisms about cell differentiation and human diseases. Due to highly-stochastic transcriptomics data, accurate detection of cell types is still challenged, especially for RNA-sequencing data from human beings. In this case, deep neural networks have been increasingly employed to mine cell type specific patterns and have outperformed statistic approaches in cell clustering.
View Article and Find Full Text PDFPervasive G × E interactions shape adaptive trajectories and the exploration of the phenotypic space in artificial selection experiments.
Genetics
December 2023
Université Paris-Saclay, INRAE, CNRS, AgroParisTech, GQE-Le Moulon, Gif-sur-Yvette 91190, France.
Quantitative genetics models have shown that long-term selection responses depend on initial variance and mutational influx. Understanding limits of selection requires quantifying the role of mutational variance. However, correlative responses to selection on nonfocal traits can perturb the selection response on the focal trait; and generations are often confounded with selection environments so that genotype by environment (G×E) interactions are ignored.
View Article and Find Full Text PDFDynamic epistasis analysis reveals how chromatin remodeling regulates transcriptional bursting.
Nat Struct Mol Biol
May 2023
Division of Gene Regulation, the Netherlands Cancer Institute, Oncode Institute, Amsterdam, the Netherlands.
Transcriptional bursting has been linked to the stochastic positioning of nucleosomes. However, how bursting is regulated by the remodeling of promoter nucleosomes is unknown. Here, we use single-molecule live-cell imaging of GAL10 transcription in Saccharomyces cerevisiae to measure how bursting changes upon combined perturbations of chromatin remodelers, the transcription factor Gal4 and preinitiation complex components.
View Article and Find Full Text PDFImpact of population size on early adaptation in rugged fitness landscapes.
Philos Trans R Soc Lond B Biol Sci
May 2023
Institute of Bioengineering, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland.
Owing to stochastic fluctuations arising from finite population size, known as genetic drift, the ability of a population to explore a rugged fitness landscape depends on its size. In the weak mutation regime, while the mean steady-state fitness increases with population size, we find that the height of the first fitness peak encountered when starting from a random genotype displays various behaviours versus population size, even among small and simple rugged landscapes. We show that the accessibility of the different fitness peaks is key to determining whether this height overall increases or decreases with population size.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!