scholarly journals Optimizing design to estimate genetic correlations between environments with common environmental effects

2020 ◽  
Vol 98 (2) ◽  
Author(s):  
Maria Lozano-Jaramillo ◽  
Hans Komen ◽  
Yvonne C J Wientjes ◽  
Han A Mulder ◽  
John W M Bastiaansen
Keyword(s):  
Genetic Correlation ◽  
Environmental Effects ◽  
Genetic Correlations ◽  
Improve Performance ◽  
Breeding Programs ◽  
Genotype By Environment ◽  
Optimizing Design ◽  
Minimum Number ◽  
Optimal Population ◽  
Different Levels

Abstract Breeding programs for different species aim to improve performance by testing members of full-sib (FS) and half-sib (HS) families in different environments. When genotypes respond differently to changes in the environment, this is defined as genotype by environment (G × E) interaction. The presence of common environmental effects within families generates covariance between siblings, and these effects should be taken into account when estimating a genetic correlation. Therefore, an optimal design should be established to accurately estimate the genetic correlation between environments in the presence of common environmental effects. We used stochastic simulation to find the optimal population structure using a combination of FS and HS groups with different levels of common environmental effects. Results show that in a population with a constant population size of 2,000 individuals per environment, ignoring common environmental effects when they are present in the population will lead to an upward bias in the estimated genetic correlation of on average 0.3 when the true genetic correlation is 0.5. When no common environmental effects are present in the population, the lowest standard error (SE) of the estimated genetic correlation was observed with a mating ratio of one dam per sire, and 10 offspring per sire per environment. When common environmental effects are present in the population and are included in the model, the lowest SE is obtained with mating ratios of at least 5 dams per sire and with a minimum number of 10 offspring per sire per environment. We recommend that studies that aim to estimate the magnitude of G × E in pigs, chicken, and fish should acknowledge the potential presence of common environmental effects and adjust the mating ratio accordingly.

scholarly journals Genetic Variation and Correlation among Resin Yield, Growth, and Morphologic Traits of Pinus massoniana

2013 ◽  
Vol 62 (1-6) ◽  
pp. 38-43 ◽  
Author(s):  
Qinghua Liu ◽  
Zhichun Zhou ◽  
Huihua Fan ◽  
Yurong Liu
Keyword(s):  
Genetic Correlation ◽  
Genetic Correlations ◽  
Tree Height ◽  
Pinus Massoniana ◽  
The Other ◽  
Breeding Programs ◽  
Family Effects ◽  
Breast Height ◽  
Sib Families ◽  
The Individual

AbstractIn breeding programs, the variations and relationships among main traits need to be understood to develop selection and breeding strategies. Resin is considered as one of most important non-timber production of P. massoniana which can privides terpenes used in the chemical industry. The present study assessed the genetic variations in growth, morphologic traits, and resin yield, as well as the phenotypic and genetic correlations between these traits of 45 half-sib families of eight-year-old Pinus massoniana trees. All traits show highly significant family effects. The individual heritability for diameter at breast height (DBH) was the highest (hi2=0.55). Heritabilities for resin yield, tree height, crown depth, and the height to the live crown were slightly lower than DBH, ranging from 0.32 to 0.45. The other traits were under weak genetic control and heritabilities ranged from 0.17 to 0.20. All growth and morphologic traits were significantly correlated genetically with resin yield. Number of living branches had the highest genetic correlation with resin yield (rg=0.99), followed by DBH and number of living whorls (rg=0.73 and 0.70). Only a moderate positive genetic correlation with resin yield was found with the other traits (rg=0.47-0.57), except for height under the living branches (rg=-0.45). The results of this study indicate that both resin yield and growth can be improved simultaneously in the next generation. Of the traits assessed DBH was the optimum trait for indirectly selecting high-yielding resin trees.

scholarly journals Genotype by Environment Interaction in Pinus sylvestris L. in Southern Sweden

2008 ◽  
Vol 57 (1-6) ◽  
pp. 306-311 ◽  
Author(s):  
B. Hannrup ◽  
G. Jansson ◽  
Ö. Danell
Keyword(s):  
Pinus Sylvestris ◽  
Genetic Correlation ◽  
Growth Traits ◽  
Genetic Correlations ◽  
Site Index ◽  
Genotype By Environment Interaction ◽  
Environment Interaction ◽  
Height Increment ◽  
Southern Sweden ◽  
Genotype By Environment

Abstract To estimate the amount of genotype by environment interaction (G x E) data was obtained within the Swedish breeding program of Pinus sylvestris L. The calculations were based on estimates of G x E expressed by the genetic correlations across trials. In total, 66 progeny trials were included coming from 17 different test series. The number of parents tested per progeny trial was in average 52. Some parents were tested in several series and in total 812 parents were represented in the study. The results of our study showed that the amount of G x E for growth traits in Pinus sylvestris in southern Sweden was low. The median genetic correlation across trials for height, height increment and diameter were in the range 0.75-0.80 and the pattern of interaction was largely unpredictable from site differences in site index, latitude, longitude and altitude.

scholarly journals SIMULTANEOUS SELECTION OF MOST STABLE AND HIGH YIELDING GENOTYPES IN BREEDING PROGRAMS BY NONPARAMETRIC METHODS

AGROFOR ◽  
2018 ◽  
Vol 2 (2) ◽  
Author(s):  
Naser SABAGHNIA ◽  
Hamid HATAMI-MALEKI ◽  
Mohsen JANMOHAMMADI
Keyword(s):  
Statistical Methods ◽  
Environmental Effects ◽  
High Stability ◽  
Nonparametric Methods ◽  
High Yield ◽  
Ge Interaction ◽  
Breeding Programs ◽  
Genotype By Environment ◽  
Simultaneous Selection ◽  
Selection Of

Explaining genotype by environment (GE) interaction is important in breedingprograms because environmental effects are very often greater than genotypiceffects in multi-environment trials. Statistical methods that select for high yield andstability have been proposed, but have not been compared for their usefulnessespecially for nonparametric methods. We compared fourteen nonparametricmethods used for analyzing GE interaction at a set of experimental lentil data (11genotypes at 20 environments). Nonparametric methods consist of six Huehn’sstatistics (S1, S2, S3, S4, S5 and S6), four Thennarasu’s statistics (NP1, NP2, NP3and NP4), tow Sabaghnia’s statistics (NS1 and NS2), Kang’s RS andnonparametric method of Fox et al. (1990). Considering mean yield versusnonparametric stability values via their plotting in a plot, indicated four differentsections as A, B, C and D. The genotype fall in the section D were the mostfavorable genotypes due to high mean yield as well as high stability performance.Plot of the most nonparametric methods showed that genotypes G1 (1.21 t ha-1), G2(1.34 t ha-1) and G5 (1.38 t ha-1) were the most favorable genotypes and so thesegenotypes considered both yield and stability simultaneously. Although, most ofthe nonparametric methods have static (biological) concept of stability and measurethe real concept of stability but plotting them versus mean yield and selecting thegenotypes of section D, could identify relatively the high mean yield genotypes asthe most stable ones.

scholarly journals Quantitative Genetics of Growth Rate and Filet Quality Traits in Atlantic Salmon Inferred From a Longitudinal Bayesian Model for the Left-Censored Gaussian Trait Growth Rate

2020 ◽  
Vol 11 ◽  
Author(s):  
Ólafur H. Kristjánsson ◽  
Bjarne Gjerde ◽  
Jørgen Ødegård ◽  
Marie Lillehammer
Keyword(s):  
Growth Rate ◽  
Body Weight ◽  
Atlantic Salmon ◽  
Genetic Correlation ◽  
Genetic Correlations ◽  
Growth Potential ◽  
Quality Traits ◽  
Breeding Programs ◽  
Test Fish ◽  
Average Body

In selective breeding programs for Atlantic salmon, test fish are slaughtered at an average body weight where growth rate and carcass traits as filet fat (FF), filet pigment (FP) and visceral fat index (FF) are recorded. The objective of this study was to obtain estimates of genetic correlations between growth rate (GR), and the three carcass quality traits when fish from the same 206 families (offspring of 120 sires and 206 dams from 2 year-classes) were recorded both at the same age (SA) and about the same body weight (SW). In the SW group, the largest fish were slaughtered at five different slaughter events and the remaining fish at the sixth slaughter event over 6 months. Estimates of genetic parameters for the traits were obtained from a Bayesian multivariate model for (potentially) truncated Gaussian traits through a Gibbs sampler procedure in which phantom GR values were obtained for the unslaughtered, and thus censored SW group fish at each slaughter event. The heritability estimates for the same trait in each group was similar; about 0.2 for FF, 0.15 for FP and 0.35 for VF and GR. The genetic correlation between the same traits in the two groups was high for growth rate (0.91 ± 0.05) visceral index (0.86 ± 0.05), medium for filet fat (0.45 ± 0.17) and low for filet pigment (0.13 ± 0.27). Within the two groups, the genetic correlation between growth rate and filet fat changed from positive (0.59 ± 0.14) for the SA group to negative (−0.45 ± 0.17) for the SW group, while the genetic correlation between growth rate and filet pigment changed from negative (−0.33 ± 0.22) for the SA group to positive (0.62 ± 0.16) for the SW group. The genetic correlation of growth rate with FF and FP is sensitive to whether the latter traits are measured at the same age or the same body weight. The results indicate that selection for increased growth rate is not expected to have a detrimental effect on the quality traits if increased growth potential is realized through a reduced production time.

Genetic and Environmental Influences on Executive Functions and Intelligence in the ABCD Study

2020 ◽  
Author(s):  
Samantha M Freis ◽  
Claire Morrison ◽  
Jeffrey M. Lessem ◽  
John K. Hewitt ◽  
Naomi P. Friedman
Keyword(s):  
Cognitive Development ◽  
Executive Functions ◽  
Genetic Correlation ◽  
Middle Childhood ◽  
Middle Age ◽  
Environmental Influences ◽  
Genetic Correlations ◽  
Twin Studies

Executive functions (EFs) and intelligence (IQ) are phenotypically correlated and heritable; however, they show variable genetic correlations in twin studies spanning childhood to middle age. We analyzed data from over 11,000 children (9-10-year-olds, including 749 twin pairs) in the Adolescent Brain Cognitive Development (ABCD) Study to examine the phenotypic and genetic relations between EFs and IQ in childhood. We identified two EF factors – Common EF and Updating-Specific, which were both related to IQ (rs = .64-.81). Common EF and IQ were heritable (53-67%), and their genetic correlation (rG = .86) was not significantly different than 1. These results suggest that EFs and IQ are phenotypically but not genetically separable in middle childhood.

scholarly journals Realized Sampling Variances of Estimates of Genetic Parameters and the Difference Between Genetic and Phenotypic Correlations

Genetics ◽  
1996 ◽  
Vol 143 (3) ◽  
pp. 1409-1416 ◽  
Author(s):  
Kenneth R Koots ◽  
John P Gibson
Keyword(s):  
Genetic Correlation ◽  
Genetic Parameters ◽  
Genetic Parameter ◽  
Genetic Correlations ◽  
Phenotypic Correlation ◽  
Parameter Estimates ◽  
Sampling Variance ◽  
Phenotypic Correlations ◽  
Genetic And Phenotypic Correlations ◽  
Heritability Estimates

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.

scholarly journals Convolutional Neural Networks to Estimate Dry Matter Yield in a Guineagrass Breeding Program Using UAV Remote Sensing

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 3971
Author(s):  
Gabriel Silva de Oliveira ◽  
José Marcato Junior ◽  
Caio Polidoro ◽  
Lucas Prado Osco ◽  
Henrique Siqueira ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Dry Matter ◽  
Pearson Correlation ◽  
Genetic Correlations ◽  
Remote Sensing Data ◽  
Breeding Program ◽  
Yield Traits ◽  
Dry Matter Yield ◽  
Breeding Programs ◽  
Ground Truth Data

Forage dry matter is the main source of nutrients in the diet of ruminant animals. Thus, this trait is evaluated in most forage breeding programs with the objective of increasing the yield. Novel solutions combining unmanned aerial vehicles (UAVs) and computer vision are crucial to increase the efficiency of forage breeding programs, to support high-throughput phenotyping (HTP), aiming to estimate parameters correlated to important traits. The main goal of this study was to propose a convolutional neural network (CNN) approach using UAV-RGB imagery to estimate dry matter yield traits in a guineagrass breeding program. For this, an experiment composed of 330 plots of full-sib families and checks conducted at Embrapa Beef Cattle, Brazil, was used. The image dataset was composed of images obtained with an RGB sensor embedded in a Phantom 4 PRO. The traits leaf dry matter yield (LDMY) and total dry matter yield (TDMY) were obtained by conventional agronomic methodology and considered as the ground-truth data. Different CNN architectures were analyzed, such as AlexNet, ResNeXt50, DarkNet53, and two networks proposed recently for related tasks named MaCNN and LF-CNN. Pretrained AlexNet and ResNeXt50 architectures were also studied. Ten-fold cross-validation was used for training and testing the model. Estimates of DMY traits by each CNN architecture were considered as new HTP traits to compare with real traits. Pearson correlation coefficient r between real and HTP traits ranged from 0.62 to 0.79 for LDMY and from 0.60 to 0.76 for TDMY; root square mean error (RSME) ranged from 286.24 to 366.93 kg·ha−1 for LDMY and from 413.07 to 506.56 kg·ha−1 for TDMY. All the CNNs generated heritable HTP traits, except LF-CNN for LDMY and AlexNet for TDMY. Genetic correlations between real and HTP traits were high but varied according to the CNN architecture. HTP trait from ResNeXt50 pretrained achieved the best results for indirect selection regardless of the dry matter trait. This demonstrates that CNNs with remote sensing data are highly promising for HTP for dry matter yield traits in forage breeding programs.

Genotype by environment interaction for yearling weight in Nellore cattle applying reaction norms models

2018 ◽  
Vol 58 (11) ◽  
pp. 1996
Author(s):  
S. Ribeiro ◽  
J. P. Eler ◽  
V. B. Pedrosa ◽  
G. J. M. Rosa ◽  
J. B. S. Ferraz ◽  
...  
Keyword(s):  
Genetic Correlation ◽  
Environmental Gradient ◽  
Genotype By Environment Interaction ◽  
Reaction Norms ◽  
Breeding Value ◽  
Environment Interaction ◽  
Genotype By Environment ◽  
Genotype Environment Interaction ◽  
Nellore Cattle ◽  
Gradient Variation

In the present study, a possible existence of genotype × environment interaction was verified for yearling weight in Nellore cattle, utilising a reaction norms model. Therefore, possible changes in the breeding value were evaluated for 46 032 animals, from three distinct herds, according to the environmental gradient variation of the different contemporary groups. Under a Bayesian approach, analyses were carried out utilising INTERGEN software resulting in solutions of contemporary groups dispersed in the environmental gradient from –90 to +100 kg. The estimates of heritability coefficients ranged from 0.19 to 0.63 through the environmental gradient and the genetic correlation between intercept and slope of the reaction norms was 0.76. The genetic correlation considering all animals of the herds in the environmental gradient ranged from 0.83 to 1.0, and the correlation between breeding values of bulls in different environments ranged from 0.79 to 1.0. The results showed no effect of genotype × environment interaction on yearling weight in the herds of this study. However, it is important to verify a possible influence of the genotype × environment in the genetic evaluation of beef cattle, as different environments might cause interference in gene expression and consequently difference in phenotypic response.

Genetic importance of fat and eye muscle depth in Merino breeding programs

2016 ◽  
Vol 56 (4) ◽  
pp. 690 ◽  
Author(s):  
D. J. Brown ◽  
A. A. Swan
Keyword(s):  
Carcass Traits ◽  
Genetic Correlations ◽  
Fibre Diameter ◽  
Economic Index ◽  
Parasite Resistance ◽  
Eye Muscle ◽  
Breeding Programs ◽  
Dual Purpose ◽  
Internal Parasite ◽  
Reproduction Traits

Australian Merino breeders have traditionally selected animals for breeding predominately on the basis of wool characteristics. Over recent decades, an increasing proportion of Merino breeders are interested in producing a ewe that can be used for prime-lamb production, but that also performs well for wool characteristics. Correlations between ultrasound carcass traits and other traits such as wool, internal parasite resistance and reproduction traits, are not very well known. The aims of this study were three-fold: (1) to estimate the genetic relationships between ultrasound carcass traits and wool, internal parasite resistance and reproduction traits, (2) to determine the value of recording ultrasound carcass traits in Merino breeding programs, and (3) to evaluate the impact of improving ewe genetic merit for fatness on their reproduction performance. Ultrasound fat and eye muscle depth had small to moderate genetic correlations with most traits, with positive correlations observed for bodyweight, fibre diameter, fibre curvature and reproduction, and negative correlations observed for fleece weight, fibre diameter coefficient of variation, worm egg count and breech wrinkle. As expected on the basis of these genetic correlations, estimated breeding values for fat depth of ewes had a positive association with their observed reproduction performance, but the effect explained only minimal variation in reproductive performance, and was extremely variable among flocks and years. A range of measurement scenarios was investigated for three standard MERINOSELECT indexes. Measuring fat and eye muscle depth resulted in 3%, 4% and 21% additional economic index gain for the fine, medium and dual purpose indexes, respectively, whereas measuring reproduction traits directly resulted in 17%, 27% and 45% additional gain in the economic index. Dual purpose index gains benefited more from measuring ultrasound carcass traits as it is the only index with a direct economic value placed on carcass traits. Measuring fat and eye muscle depth also resulted in a greater reduction in worm egg count. The results indicated that desirable genetic progress can be made in wool, ultrasound carcass, internal parasite resistance and number of lambs born and weaned simultaneously using multiple trait selection to account for the mix of favourable and unfavourable correlations between these traits. These results also demonstrated that the best method to maximise economic gain is to measure as many traits (or closely correlated traits) in the breeding objective as possible.

Genetic Parameters and Genotype-by-Environment Interactions in Regional Progeny Tests of Pinus taeda L. in the Southern USA

2020 ◽  
Author(s):  
Edwin Lauer ◽  
Andrew Sims ◽  
Steven McKeand ◽  
Fikret Isik
Keyword(s):  
Genetic Variation ◽  
Pinus Taeda ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Breeding Program ◽  
Model Fit ◽  
Genotype By Environment Interactions ◽  
Genotype By Environment ◽  
Progeny Tests ◽  
Pinus Taeda L

Abstract Genetic parameters were estimated using a five-series multienvironment trial of Pinus taeda L. in the southern USA. There were 324 half-sib families planted in five test series across 37 locations. A set of six variance/covariance matrices for the genotype-by-environment (G × E) effect for tree height and diameter were compared on the basis of model fit. In single-series analysis, extended factor analytical models provided generally superior model fit to simpler models for both traits; however, in the combined-series analysis, diameter was optimally modeled using simpler variance/covariance structures. A three-way compound term for modeling G × E interactions among and within series yielded substantial improvements in terms of model fit and standard errors of predictions. Heritability of family means ranged between 0.63 and 0.90 for both height and diameter. Average additive genetic correlations among sites were 0.70 and 0.61 for height and diameter, respectively, suggesting the presence of some G × E interaction. Pairs of sites with the lowest additive genetic correlations were located at opposite ends of the latitude range. Latent factor regression revealed a small number of parents with large factor scores that changed ranks significantly between southern and northern environments. Study Implications Multienvironmental progeny tests of loblolly pine (Pinus taeda L.) were established over 10 years in the southern United States to understand the genetic variation for the traits of economic importance. There was substantial genetic variation between open-pollinated families, suggesting that family selection would be efficient in the breeding program. Genotype-by-environment interactions were negligible among sites in the deployment region but became larger between sites at the extremes of the distribution. The data from these trials are invaluable in informing the breeding program about the genetic merit of selection candidates and their potential interaction with the environment. These results can be used to guide deployment decisions in the southern USA, helping landowners match germplasm with geography to achieve optimal financial returns and conservation outcomes.

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