scholarly journals Heterosis and heritability estimates of purine alkaloids and polyphenols in cocoa

2016 ◽  
Vol 24 (3) ◽  
pp. 235
Author(s):  
P.O. Effa ◽  
M.L. Ondobo ◽  
P.F. Djocgoue ◽  
N. Niemenak
2003 ◽  
Vol 62 (1) ◽  
pp. 5-10 ◽  
Author(s):  
Manfred Velden

It is proposed to simplify the debate about the heritability of mental traits in humans by concentrating on two crucial issues: Population specificity of heritability estimates and the relation of these estimates to the malleability of the trait to which they refer. It is demonstrated that due to vast differences between the environmental variations of populations there would have to be a heritability estimate for every imaginable population, and that a heritability estimate allows no predictions whatsoever about the malleability of the trait in question. It is therefore concluded that this field of research should be abandoned.


2004 ◽  
Vol 84 (1) ◽  
pp. 125-127
Author(s):  
Marcelo R. A. de Araujo ◽  
B. E. Coulman

To determine the nature and extent of inflation of estimates of heritabilities by parent-offspring regression methods, 40 clones of meadow bromegrass (Bromus riparius Rehm.) and their half-sib progenies were studied in completely randomized block design trials, with six replications in Saskatoon and Melfort, Canada. Clones and progenies were evaluated for dry matter yield, seed yield, plant height, fertility index and harvest index. The results of the analysis showed a consistent inflation of heritability estimates derived from the simple parent-offspring regression, when compared to the regression estimate by variance-covariance analysis. The two methods successfully removed the environmental covariances from the estimates. However, in the simple regression analysis, error covariance was not removed from the numerat or; therefore, heritabilities estimated by this methodology were higher than those estimated by the variance-covariance method. It was concluded that estimates derived from variance-covariance analysis provide less biased estimates of heritability. Key words: Regression analysis, heritability, meadow bromegrass


Genetics ◽  
1996 ◽  
Vol 143 (3) ◽  
pp. 1409-1416 ◽  
Author(s):  
Kenneth R Koots ◽  
John P Gibson

Abstract A data set of 1572 heritability estimates and 1015 pairs of genetic and phenotypic correlation estimates, constructed from a survey of published beef cattle genetic parameter estimates, provided a rare opportunity to study realized sampling variances of genetic parameter estimates. The distribution of both heritability estimates and genetic correlation estimates, when plotted against estimated accuracy, was consistent with random error variance being some three times the sampling variance predicted from standard formulae. This result was consistent with the observation that the variance of estimates of heritabilities and genetic correlations between populations were about four times the predicted sampling variance, suggesting few real differences in genetic parameters between populations. Except where there was a strong biological or statistical expectation of a difference, there was little evidence for differences between genetic and phenotypic correlations for most trait combinations or for differences in genetic correlations between populations. These results suggest that, even for controlled populations, estimating genetic parameters specific to a given population is less useful than commonly believed. A serendipitous discovery was that, in the standard formula for theoretical standard error of a genetic correlation estimate, the heritabilities refer to the estimated values and not, as seems generally assumed, the true population values.


2020 ◽  
Vol 23 (6) ◽  
pp. 330-337
Author(s):  
Olatz Mompeo ◽  
Rachel Gibson ◽  
Paraskevi Christofidou ◽  
Tim D. Spector ◽  
Cristina Menni ◽  
...  

AbstractA healthy diet is associated with the improvement or maintenance of health parameters, and several indices have been proposed to assess diet quality comprehensively. Twin studies have found that some specific foods, nutrients and food patterns have a heritable component; however, the heritability of overall dietary intake has not yet been estimated. Here, we compute heritability estimates of the nine most common dietary indices utilized in nutritional epidemiology. We analyzed 2590 female twins from TwinsUK (653 monozygotic [MZ] and 642 dizygotic [DZ] pairs) who completed a 131-item food frequency questionnaire (FFQ). Heritability estimates were computed using structural equation models (SEM) adjusting for body mass index (BMI), smoking status, Index of Multiple Deprivation (IMD), physical activity, menopausal status, energy and alcohol intake. The AE model was the best-fitting model for most of the analyzed dietary scores (seven out of nine), with heritability estimates ranging from 10.1% (95% CI [.02, .18]) for the Dietary Reference Values (DRV) to 42.7% (95% CI [.36, .49]) for the Alternative Healthy Eating Index (A-HEI). The ACE model was the best-fitting model for the Healthy Diet Indicator (HDI) and Healthy Eating Index 2010 (HEI-2010) with heritability estimates of 5.4% (95% CI [−.17, .28]) and 25.4% (95% CI [.05, .46]), respectively. Here, we find that all analyzed dietary indices have a heritable component, suggesting that there is a genetic predisposition regulating what you eat. Future studies should explore genes underlying dietary indices to further understand the genetic disposition toward diet-related health parameters.


2012 ◽  
Vol 35 (5) ◽  
pp. 361-362 ◽  
Author(s):  
Wim E. Crusio

AbstractCharney describes several mechanisms that will bias estimates of heritability in unpredictable directions. In addition, the mechanisms described by Charney explain the puzzling fact that research in human-behavior genetics routinely reports higher heritabilities than animal studies do. However, I argue that the concept of heritability has no real place in human research anyway.


2008 ◽  
Vol 91 (4) ◽  
pp. 1640-1647 ◽  
Author(s):  
C.D. Dechow ◽  
H.D. Norman ◽  
N.R. Zwald ◽  
C.M. Cowan ◽  
O.M. Meland

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