scholarly journals Analysis of the inheritance, selection and evolution of growth trajectories.

Genetics ◽  
1990 ◽  
Vol 124 (4) ◽  
pp. 979-993 ◽  
Author(s):  
M Kirkpatrick ◽  
D Lofsvold ◽  
M Bulmer
Keyword(s):  
Covariance Function ◽  
Genetic Model ◽  
Growth Trajectory ◽  
Growth Trajectories ◽  
Sampling Errors ◽  
Genetic Covariance ◽  
Selection Gradient ◽  
Infinite Dimensional ◽  
Evolutionary Changes ◽  
Gradient Function

Abstract We present methods for estimating the parameters of inheritance and selection that appear in a quantitative genetic model for the evolution growth trajectories and other "infinite-dimensional" traits that we recently introduced. Two methods for estimating the additive genetic covariance function are developed, a "full" model that fully fits the data and a "reduced" model that generates a smoothed estimate consistent with the sampling errors in the data. By decomposing the covariance function into its eigenvalues and eigenfunctions, it is possible to identify potential evolutionary changes in the population's mean growth trajectory for which there is (and those for which there is not) genetic variation. Algorithms for estimating these quantities, their confidence intervals, and for testing hypotheses about them are developed. These techniques are illustrated by an analysis of early growth in mice. Compatible methods for estimating the selection gradient function acting on growth trajectories in natural or domesticated populations are presented. We show how the estimates for the additive genetic covariance function and the selection gradient function can be used to predict the evolutionary change in a population's mean growth trajectory.

Adolescent Tri-ponderal Mass Index Growth Trajectories and Incident Diabetes Mellitus in Early Adulthood

2021 ◽  
Author(s):  
Yi-Fan Wu ◽  
Hsien-Yu Fan ◽  
Yang-Ching Chen ◽  
Kuan-Liang Kuo ◽  
Kuo-Liong Chien
Keyword(s):  
Early Adulthood ◽  
Growth Mixture Modeling ◽  
The Body ◽  
Growth Trajectory ◽  
Incident Diabetes ◽  
Growth Trajectories ◽  
City Hospital ◽  
Z Score ◽  
Increased Risk ◽  
Adult Diabetes

Abstract Purpose Studies have reported the influence of adolescent obesity on development of adult diabetes, but the effect of the growth pattern during this period has rarely been explored. Also, the tri-ponderal mass index (TMI) was thought to be a better estimation of adolescent body fat levels than the body mass index (BMI), so we sought to investigate whether growth trajectories derived by these two indices could predict incident diabetes. Methods We conducted a study by using the Taipei City Hospital Radiation Building Database, a longitudinal cohort established from 1996 until now. Physical exam results including blood test results were collected annually and the BMI z-score/TMI growth trajectory groups during 13–18 years of age were identified using growth mixture modeling. A Cox proportional hazard model for incident diabetes was used to examine the risk of baseline obese status and different BMI/TMI growth trajectories. Results Five growth trajectory groups were identified for the BMI z-score and the TMI. During approximately 20,400 person-years follow-up, 33 of 1,387 participants developed diabetes. Baseline obesity defined by the BMI z-score and the TMI were both related to adult diabetes. The persistent increase TMI growth trajectory exhibited a significantly increased risk of diabetes after adjusting for baseline obese status and other correlated covariates (hazard ratio: 2.85, 95% confidence interval (CI): 1.01–8.09). There was no association between BMI growth trajectory groups and incident diabetes. Conclusions A specific TMI growth trajectory pattern during adolescence might be critical for diabetes prevention efforts.

scholarly journals Behavioral syndromes shape evolutionary trajectories via conserved genetic architecture

2019 ◽  
Author(s):  
Raphael Royauté ◽  
Ann Hedrick ◽  
Ned A. Dochtermann
Keyword(s):  
Genetic Architecture ◽  
Behavioral Syndromes ◽  
Behavioral Syndrome ◽  
Cellular Mechanisms ◽  
Genetic Covariance ◽  
Behavioral Traits ◽  
Field Crickets ◽  
Evolutionary Changes ◽  
Evolutionary Trajectories ◽  
Gryllus Integer

AbstractBehaviors are often correlated within broader syndromes, creating the potential for evolution in one behavior to drive evolutionary changes in other behaviors. Despite demonstrations that behavioral syndromes are common across taxa, whether this potential for evolutionary effects is realized has not yet been demonstrated. Here we show that populations of field crickets (Gryllus integer) exhibit a genetically conserved behavioral syndrome structure despite differences in average behaviors. We found that the distribution of genetic variation and genetic covariance among behavioral traits was consistent with genes and cellular mechanisms underpinning behavioral syndromes rather than correlated selection. Moreover, divergence among populations’ average behaviors was constrained by the genetically conserved behavioral syndrome. Our results demonstrate that a conserved genetic architecture linking behaviors has shaped the evolutionary trajectories of populations in disparate environments—illustrating an important way by which behavioral syndromes result in shared evolutionary fates.

scholarly journals The Heritability of Type D Personality by an Extended Twin-Pedigree Analysis in the Netherlands Twin Register

2020 ◽  
Author(s):  
Ruifang Li-Gao ◽  
Dorret I. Boomsma ◽  
Eco J. C. de Geus ◽  
Johan Denollet ◽  
Nina Kupper
Keyword(s):  
The Netherlands ◽  
Variance Components ◽  
Genetic Model ◽  
Additive Genetic Variance ◽  
Type D Personality ◽  
Continuous Measure ◽  
Genetic Covariance ◽  
Type D ◽  
Genetic Components ◽  
Increased Risk

Abstract Type D (Distressed) personality combines negative affectivity (NA) and social inhibition (SI) and is associated with an increased risk of cardiovascular disease. We aimed to (1) validate a new proxy based on the Achenbach System of Empirically Based Assessment (ASEBA) for Type D personality and its NA and SI subcomponents and (2) estimate the heritability of the Type D proxy in an extended twin-pedigree design in the Netherlands Twin Register (NTR). Proxies for the dichotomous Type D classification, and continuous NA, SI, and NAxSI (the continuous measure of Type D) scales were created based on 12 ASEBA items for 30,433 NTR participants (16,449 twins and 13,984 relatives from 11,106 pedigrees) and sources of variation were analyzed in the ‘Mendel’ software package. We estimated additive and non-additive genetic variance components, shared household and unique environmental variance components and ran bivariate models to estimate the genetic and non-genetic covariance between NA and SI. The Type D proxy showed good reliability and construct validity. The best fitting genetic model included additive and non-additive genetic effects with broad-sense heritabilities for NA, SI and NAxSI estimated at 49%, 50% and 49%, respectively. Household effects showed small contributions (4–9%) to the total phenotypic variation. The genetic correlation between NA and SI was .66 (reflecting both additive and non-additive genetic components). Thus, Type D personality and its NA and SI subcomponents are heritable, with a shared genetic basis for the two subcomponents.

scholarly journals The ‘algebra of evolution’: the Robertson–Price identity and viability selection for body mass in a wild bird population

2020 ◽  
Vol 375 (1797) ◽  
pp. 20190359 ◽  
Author(s):  
G. K. Hajduk ◽  
C. A. Walling ◽  
A. Cockburn ◽  
L. E. B. Kruuk
Keyword(s):  
Phenotypic Diversity ◽  
Additive Genetic Variance ◽  
Natural Populations ◽  
Phenotypic Selection ◽  
Relative Fitness ◽  
Price Equation ◽  
Genetic Covariance ◽  
Selection Gradient ◽  
Viability Selection ◽  
Temporal Correlations

By the Robertson–Price identity, the change in a quantitative trait owing to selection, is equal to the trait's covariance with relative fitness. In this study, we applied the identity to long-term data on superb fairy-wrens Malurus cyaneus , to estimate phenotypic and genetic change owing to juvenile viability selection. Mortality in the four-week period between fledging and independence was 40%, and heavier nestlings were more likely to survive, but why? There was additive genetic variance for both nestling mass and survival, and a positive phenotypic covariance between the traits, but no evidence of additive genetic covariance. Comparing standardized gradients, the phenotypic selection gradient was positive, β P = 0.108 (0.036, 0.187 95% CI), whereas the genetic gradient was not different from zero, β A = −0.025 (−0.19, 0.107 95% CI). This suggests that factors other than nestling mass were the cause of variation in survival. In particular, there were temporal correlations between mass and survival both within and between years. We suggest that use of the Price equation to describe cross-generational change in the wild may be challenging, but a more modest aim of estimating its first term, the Robertson–Price identity, to assess within-generation change can provide valuable insights into the processes shaping phenotypic diversity in natural populations. This article is part of the theme issue ‘Fifty years of the Price equation’.

The effect of stage of growth on the genetic and phenotypic parameter estimates of food intake in pigs using a covariance function model

2000 ◽  
Vol 2000 ◽  
pp. 40-40
Author(s):  
A.D. Hall ◽  
P.R. Bampton ◽  
A.J. Webb
Keyword(s):  
Food Intake ◽  
Covariance Function ◽  
Parameter Estimates ◽  
Dimensional Approach ◽  
Function Model ◽  
Daily Food Intake ◽  
Infinite Dimensional ◽  
Phenotypic Parameter ◽  
Daily Food ◽  
Discrete Traits

Many traits that are of interest to breeders, such as food intake, are expressed continuously during the life of an animal and the individual's phenotype will change with age. Traditional genetic analysis of these traits has treated as them as discrete traits, ignoring the correlations among records at different ages. Recently methods have been developed to overcome this deficiency and allow an infinite dimensional approach, which can provide more accurate estimates of genetic and phenotypic parameters (Kirkpatrick et al. 1994, Meyer and Hill 1997). The aim of this study was to investigate the effect of stage of growth on the genetic and phenotypic parameter estimates of daily food intake.

scholarly journals Artificial selection on phenotypically plastic traits

1999 ◽  
Vol 74 (3) ◽  
pp. 265-270 ◽  
Author(s):  
MARK KIRKPATRICK ◽  
THOMAS BATAILLON
Keyword(s):  
Artificial Selection ◽  
Mass Selection ◽  
Genetic Covariance ◽  
Linear Unbiased Prediction ◽  
Infinite Dimensional ◽  
Covariance Functions ◽  
Breeding Schemes ◽  
Best Linear Unbiased ◽  
Efficient Breeding ◽  
Selection Of

Many phenotypes respond physiologically or developmentally to continuously distributed environmental variables such as temperature and nutritional quality. Information about phenotypic plasticity can be used to improve the efficiency of artificial selection. Here we show that the quantitative genetic theory for ‘infinite-dimensional’ traits such as reaction norms provides a natural framework to accomplish this goal. It is expected to improve selection responses by making more efficient use of information about environmental effects than do conventional methods. The approach is illustrated by deriving an index for mass selection of a phenotypically plastic trait. We suggest that the same approach could be extended directly to more general and efficient breeding schemes, such as those based on general best linear unbiased prediction. Methods for estimating genetic covariance functions are reviewed.

The evolution of growth trajectories and other complex quantitative characters

Genome ◽  
1989 ◽  
Vol 31 (2) ◽  
pp. 778-783 ◽  
Author(s):  
Mark Kirkpatrick ◽  
David Lofsvold
Keyword(s):  
Growth Rate ◽  
Genetic Variation ◽  
Degrees Of Freedom ◽  
Natural Populations ◽  
Genetic Data ◽  
Growth Trajectories ◽  
Infinite Dimensional ◽  
Quantitative Characters ◽  
Method Analysis ◽  
Complex Characters

Growth trajectories differ from many other quantitative, characters in that they are characterized by a continuous function rather than by a finite number of discrete measurements. We review here recently developed methods for predicting the evolution of growth trajectories under the influence of natural or artificial selection. Using our method, analysis of genetic data from mice shows that the patterns of genetic variation arising from developmental processes impose constraints on evolution of growth trajectories. These constraints can be quantified to reveal the families of growth trajectories that can be produced by selection and those families that cannot. The data suggest there may be relatively few evolutionary degrees of freedom for growth trajectories despite the presence of abundant additive genetic variation to alter size and (or) growth rate at every age. The description of these constraints may be useful to both biologists who would like to determine the evolutionary options available to natural populations and to breeders who would like to alter growth trajectories to economically improve domesticated species. Our methods and conclusions can be generalized to other kinds of "infinite-dimensional" or complex characters, including morphological shapes and norms of reaction.Key words: growth trajectories, quantitative genetics, constraints, infinite-dimensional characters, body size.

The Selection Gradient of an Infinite-Dimensional Trait

1996 ◽  
Vol 56 (2) ◽  
pp. 509-523 ◽  
Author(s):  
Richard Gomulkiewicz ◽  
Jay H. Beder
Keyword(s):  
Selection Gradient ◽  
Infinite Dimensional

scholarly journals Dynamic Cost-Optimal Assessment of Complementary Diurnal Electricity Storage Capacity in High PV Penetration Grid

Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4496
Author(s):  
Samuel Matthew G. Dumlao ◽  
Keiichi N. Ishihara
Keyword(s):  
Monte Carlo ◽  
Solar Energy ◽  
Optimal Trajectory ◽  
Storage Capacity ◽  
Growth Trajectory ◽  
Growth Trajectories ◽  
Financial Assessment ◽  
The Cost ◽  
Pv Penetration ◽  
The Impact

Solar Photovoltaics (PV) is seen as one of the renewable energy technologies that could help reduce the world’s dependence on fossil fuels. However, since it is dependent on the sun, it can only generate electricity in the daytime, and this restriction is exacerbated in electricity grids with high PV penetration, where solar energy must be curtailed due to the mismatch between supply and demand. This study conducts a techno-economic analysis to present the cost-optimal storage growth trajectory that could support the dynamic integration of solar PV within a planning horizon. A methodology for cost-optimal assessment that incorporates hourly simulation, Monte Carlo random sampling, and a proposed financial assessment is presented. This approach was tested in Japan’s southernmost region since it is continuously increasing its solar capacity and is at the precipice of high PV curtailment scenario. The results show the existence of a cost-optimal storage capacity growth trajectory that balances the cost penalty from curtailment and the additional investment cost from storage. This optimal trajectory reduces the impact of curtailment on the energy generation cost to manageable levels and utilizes more solar energy potential that further reduces CO2 emissions. The results also show that the solar capacity growth rate and storage cost significantly impact the optimal trajectory. The incorporation of the Monte Carlo method significantly reduced the computational requirement of the analysis enabling the exploration of several growth trajectories, and the proposed financial assessment enabled the time-bound optimization of these trajectories. The approach could be used to calculate the optimal growth trajectories in other nations or regions, provided that historical hourly temperature, irradiance, and demand data are available.

scholarly journals A Model of Growth Trajectory Bifurcation in Animals Ontogeny

2019 ◽  
Vol 12 (1) ◽  
pp. 20
Author(s):  
V. L. Stass
Keyword(s):  
Conversion Coefficient ◽  
Growth Trajectory ◽  
Growth Trajectories ◽  
Growth Dynamic ◽  
Feed Conversion ◽  
Maximum Weight ◽  
Hybrid Dynamic System ◽  
Systemic Factors ◽  
Species Specific ◽  
New Variables

The aim of this study was to formulate and analyse a model of ontogenetic growth cessation in pigs. The cessation of growth when an animal reaches its species-specific size in ontogeny is still a problem. Systemic factors that contribute to this process are unknown. The focus of the research is an analysis of the growth dynamic that explains some aspects of the problem. The method applied to meet the purpose of the study was mathematical modelling. To enhance the understanding of the growth trajectories in ontogeny an analytical model of growth in pigs was built. The model was formulated as a hybrid dynamic system with discrete-time and continuum equations. The novelty of the study is a concept of ontogenetic growth in the pig. Both a new modelling technique, and new variables are introduced. A central theme of the study is an analysis of the growth trajectory bifurcation, and a description of the two emerged growth trajectories. A reading of a normal form of bifurcation applied to the growth trajectory bifurcation has been offered. The results suggest that ontogenetic growth in pigs is not continuous. The growth trajectory has bifurcation at the point the animals attain their individual maximum weight. At this point, two new growth trajectories emerge. On one trajectory, animals continue to grow till a species maximum weight is reached. On other trajectory, animals continue to live till obtainable life span is attained. The emerged trajectories are genetic channels that open the way to grow for the certain phenotypes. Ontogenetic growth stops when the feed conversion coefficient grows into infinity.

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