Correlational selection in the age of genomics

Svensson, Erik I.; Arnold, Stevan J.; Bürger, Reinhard; Csilléry, Katalin; Draghi, Jeremy A.; Henshaw, Jonathan M.; Jones, Adam G.; Lisle, Stephen De; Marques, David Alexander; McGuigan, Katrina; Simon, Monique Nouailhetas; Runemark, Anna

doi:10.1038/s41559-021-01413-3

Cited by 67 publications

(80 citation statements)

References 144 publications

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“…The genome aging science is distinct from previous research findings that elucidated the mechanism of longevity and the complex mechanism of whole organism aging [ 3 , 10 , 11 ]. However, recent studies on the molecular mechanism of organ and tissue aging, including the whole biological function, such as metabolism, its related diets, and lifestyle-related diseases, i.e., glucose intolerance/insulin resistance, microcirculatory disorder /coagulation system abnormality, and deterioration of cardiac function/cardiac hypertrophy, have indicated important factors that impact the actual age of an individual [ 12 ].…”

Section: Systematization Of Disease Concept According To Genome Aging Theorymentioning

confidence: 89%

“…It has been demonstrated that markers of aging are different in each organ [ 3 ]. Besides exposure to intrinsic factors, epithelial tissues are constantly exposed to extrinsic factors and stress, resulting in advanced tissue aging.…”

Section: Age-related Genetic Alterations In Normal Tissuesmentioning

confidence: 99%

“…Intrinsic aging-related factors and phenotypes are associated with the genetic material and genetic predisposition inherited from parents [ 2 ]. Although multiple factors are involved in regulation of physical aging [ 3 ], in this article, we have focused on molecular biology of senescence and current advances in the clinical science of aging.…”

Section: Introductionmentioning

confidence: 99%

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Epithelial Cell Transformation and Senescence as Indicators of Genome Aging: Current Advances and Unanswered Questions

Kitakaze

Chijimatsu

Vecchione³

et al. 2021

IJMS

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The recent advances in deciphering the human genome allow us to understand and evaluate the mechanisms of human genome age-associated transformations, which are largely unclear. Genome sequencing techniques assure comprehensive mapping of human genetics; however, understanding of gene functional interactions, specifically of time/age-dependent modifications, remain challenging. The age of the genome is defined by the sum of individual (inherited) and acquired genomic traits, based on internal and external factors that impact ontogenesis from the moment of egg fertilization and embryonic development. The biological part of genomic age opens a new perspective for intervention. The discovery of single cell-based mechanisms for genetic change indicates the possibility of influencing aging and associated disease burden, as well as metabolism. Cell populations with transformed genetic background were shown to serve as the origin of common diseases during extended life expectancy (superaging). Consequently, age-related cell transformation leads to cancer and cell degeneration (senescence). This article aims to describe current advances in the genomic mechanisms of senescence and its role in the spatiotemporal spread of epithelial clones and cell evolution.

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Section: Systematization Of Disease Concept According To Genome Aging Theorymentioning

confidence: 89%

Section: Age-related Genetic Alterations In Normal Tissuesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Epithelial Cell Transformation and Senescence as Indicators of Genome Aging: Current Advances and Unanswered Questions

Kitakaze

Chijimatsu

Vecchione³

et al. 2021

IJMS

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“…Quantitative genetic models allow one to use phenotypic trait values and pedigree information to estimate genetic variation in traits, that is, the heritable component in the observed phenotypic variation that could contribute to evolutionary changes (Falconer & Mackay, 2009). These models also allow one to estimate genetic correlation and covariance, parameters that indicate the strength and the signs of the statistical associations between traits that remain stable from the current generation to the next due to pleiotropy or linkage disequilibrium (Svensson et al., 2021). These associations between traits can play a key role in shaping multi‐trait responses to selection (Etterson & Shaw, 2001).…”

Section: Introductionmentioning

confidence: 99%

Genetic variation in leaf traits and gas exchange responses to vapour pressure deficit in contrasting conifer species

et al. 2022

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Recent years have seen an increasing recognition of the importance of intraspecific trait variation in shaping community dynamics and ecosystem processes (Siefert et al., 2015;Violle et al., 2012). In particular, there has been an increasing interest in incorporating evolutionary processes into trait-based, mechanistic models to predict species and ecosystem responses to climate change (Berzaghi et al., 2020;Moran et al., 2016). Such incorporation requires a better understanding of the genetic variation in key functional traits.

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“…For this reason, linkage disequilibrium is negligible except for trait covariation among closely related individuals. Third, trait covariation could be a result of natural selection for particular trait relationships that are advantageous (Bolstad et al, 2015;Lande, 1979;Roff, Mostowy, & Fairbairn, 2002;Shoval et al, 2012;Sinervo & Svensson, 2002;Svensson et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Detecting natural selection in trait-trait coevolution

Jiang

Zhang

2021

Preprint

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No phenotypic trait evolves independently of all other traits, but the cause of trait-trait coevolution is poorly understood. While the coevolution could arise simply from pleiotropic mutations that simultaneously affect the traits concerned, it could also result from multivariate natural selection favoring certain trait relationships. To gain a general mechanistic understanding of trait-trait coevolution, we examine the evolution of 220 cell morphology traits across 16 natural strains of the yeast Saccharomyces cerevisiae and the evolution of 24 wing morphology traits across 110 fly species of the family Drosophilidae, along with the variations of these traits among gene deletion or mutation accumulation lines (a.k.a. mutants). For numerous trait pairs, the phenotypic correlation among evolutionary lineages differs significantly from that among mutants. Specifically, we find hundreds of cases where the evolutionary correlation between traits is strengthened or reversed relative to the mutational correlation, which, according to our population genetic simulation, is likely caused by multivariate selection. Furthermore, we detect selection for enhanced modularity of the yeast traits analyzed. Together, these results demonstrate that trait-trait coevolution is shaped by natural selection and suggest that the pleiotropic structure of mutation is not optimal. Because the morphological traits analyzed here are chosen largely because of their measurability, our conclusion is likely general.

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Correlational selection in the age of genomics

Cited by 67 publications

References 144 publications

Epithelial Cell Transformation and Senescence as Indicators of Genome Aging: Current Advances and Unanswered Questions

Epithelial Cell Transformation and Senescence as Indicators of Genome Aging: Current Advances and Unanswered Questions

Genetic variation in leaf traits and gas exchange responses to vapour pressure deficit in contrasting conifer species

Detecting natural selection in trait-trait coevolution

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