Estimation of components of genetic variance and heritability for flowering time and yield in gerbera using Derivative-Free Restricted Maximum Likelihood (DFRML)

Summary Additive genetic components of variance and narrow-sense heritabilities were estimated for flowering time (FT) and cut-flower yield (Y) for six generations of the Davis Population of gerbera using Derivative-Free Restricted Maximum Likelihood (DFRML). Additive genetic variance accounted for 54% of the total variability for FT and 30% of the total variability for Y. The heritability of FT (0.54) agreed with previous ANOVA-based estimates. However, the heritability of Y (0.30) was substantially lower than estimates using ANOVA. The advantages of DFRML and its applications in the estimation of components of genetic variance and heritabilities of plant populations are discussed.     

Prediction of breeding values and selection responses with genetic heterogeneity of environmental variance

There is empirical evidence that genotypes differ not only in mean, but also in environmental variance of the traits they affect. Genetic heterogeneity of environmental variance may indicate genetic differences in environmental sensitivity. The aim of this study was to develop a general framework for prediction of breeding values and selection responses in mean and environmental variance with genetic heterogeneity of environmental variance. Both means and environmental variances were treated as heritable traits. Breeding values and selection responses were predicted with little bias using linear, quadratic, and cubic regression on individual phenotype or using linear regression on the mean and within-family variance of a group of relatives. A measure of heritability was proposed for environmental variance to standardize results in the literature and to facilitate comparisons to "conventional" traits. Genetic heterogeneity of environmental variance can be considered as a trait with a low heritability. Although a large amount of information is necessary to accurately estimate breeding values for environmental variance, response in environmental variance can be substantial, even with mass selection. The methods developed allow use of the well-known selection index framework to evaluate breeding strategies and effects of natural selection that simultaneously change the mean and the variance.     

Long-term response to genomic selection: effects of estimation method and reference population structure for different genetic architectures

Background

Genomic selection has become an important tool in the genetic improvement of animals and plants. The objective of this study was to investigate the impacts of breeding value estimation method, reference population structure, and trait genetic architecture, on long-term response to genomic selection without updating marker effects.

Methods

Three methods were used to estimate genomic breeding values: a BLUP method with relationships estimated from genome-wide markers (GBLUP), a Bayesian method, and a partial least squares regression method (PLSR). A shallow (individuals from one generation) or deep reference population (individuals from five generations) was used with each method. The effects of the different selection approaches were compared under four different genetic architectures for the trait under selection. Selection was based on one of the three genomic breeding values, on pedigree BLUP breeding values, or performed at random. Selection continued for ten generations.

Results

Differences in long-term selection response were small. For a genetic architecture with a very small number of three to four quantitative trait loci (QTL), the Bayesian method achieved a response that was 0.05 to 0.1 genetic standard deviation higher than other methods in generation 10. For genetic architectures with approximately 30 to 300 QTL, PLSR (shallow reference) or GBLUP (deep reference) had an average advantage of 0.2 genetic standard deviation over the Bayesian method in generation 10. GBLUP resulted in 0.6% and 0.9% less inbreeding than PLSR and BM and on average a one third smaller reduction of genetic variance. Responses in early generations were greater with the shallow reference population while long-term response was not affected by reference population structure.

Conclusions

The ranking of estimation methods was different with than without selection. Under selection, applying GBLUP led to lower inbreeding and a smaller reduction of genetic variance while a similar response to selection was achieved. The reference population structure had a limited effect on long-term accuracy and response. Use of a shallow reference population, most closely related to the selection candidates, gave early benefits while in later generations, when marker effects were not updated, the estimation of marker effects based on a deeper reference population did not pay off.     

Genetic analysis of a red tilapia (<Emphasis Type="Italic">Oreochromis</Emphasis> spp.) population undergoing three generations of selection for increased body weight at harvest

Quantitative genetic analysis was performed on 10,919 data records collected over three generations from the selection programme for increased body weight at harvest in red tilapia (Oreochromis spp.). They were offspring of 224 sires and 226 dams (50 sires and 60 dams per generation, on average). Linear mixed models were used to analyse body traits (weight, length, width and depth), whereas threshold generalised models assuming probit distribution were employed to examine genetic inheritance of survival rate, sexual maturity and body colour. The estimates of heritability for traits studied (body weight, standard length, body width, body depth, body colour, early sexual maturation and survival) across statistical models were moderate to high (0.13–0.45). Genetic correlations among body traits and survival were high and positive (0.68–0.96). Body length and width exhibited negative genetic correlations with body colour (? 0.47 to ? 0.25). Sexual maturity was genetically correlated positively with measurements of body traits (weight and length). Direct and correlated genetic responses to selection were measured as estimated breeding values in each generation and expressed in genetic standard deviation units (σ_G). The cumulative improvement achieved for harvest body weight was 1.72 σ_G after three generations or 12.5% per generation when the gain was expressed as a percentage of the base population. Selection for improved body weight also resulted in correlated increase in other body traits (length, width and depth) and survival rate (ranging from 0.25 to 0.81 genetic standard deviation units). Avoidance of black spot parent matings also improved the overall red colour of the selected population. It is concluded that the selective breeding programme for red tilapia has succeeded in achieving significant genetic improvement for a range of commercially important traits in this species, and the large genetic variation in body colour and survival also shows that there are prospects for future improvement of these traits in this population of red tilapia.     

Predicting breeding values and genetic components using generalized linear mixed models for categorical and continuous traits in walnut (<Emphasis Type="Italic">Juglans regia</Emphasis>)

Genetic components for economically important traits in walnut (Juglans regia) were estimated for the first time using historical pedigree and heirloom phenotypic data from the walnut breeding program at the University of California, Davis. The constructed pedigree is composed of ~ 15,000 individuals and is derived from current and historic phenotypic records dating back > 50 years and located across California. To predict the additive genetic values of individuals under selection, generalized linear mixed models (GLMM), implemented with MCMCglmm, were developed. Several repeatability models were established to obtain the best model and predict the genetic parameters for each trait. Repeatability for yield, harvest date, extra-light kernel color (ELKC), and lateral bearing were predicted at 0.82, 0.98, 0.63, and 0.96, respectively, and average narrow-sense heritabilities were 0.54, 0.77, 0.49, and 0.75, respectively. Each individual in the pedigree was ranked by its estimated breeding value (EBV). The genetic trend showed specific patterns for each trait, and real genetic improvement was found over time. The completed pedigree built here, the estimated breeding values, and the ranking of individuals according to their breeding values, can be used to guide future crossing designs in the walnut breeding program and future implementation of genomic selection methods in walnut.     

Selection for uniformity in livestock by exploiting genetic heterogeneity of residual variance

In some situations, it is worthwhile to change not only the mean, but also the variability of traits by selection. Genetic variation in residual variance may be utilised to improve uniformity in livestock populations by selection. The objective was to investigate the effects of genetic parameters, breeding goal, number of progeny per sire and breeding scheme on selection responses in mean and variance when applying index selection. Genetic parameters were obtained from the literature. Economic values for the mean and variance were derived for some standard non-linear profit equations, e.g. for traits with an intermediate optimum. The economic value of variance was in most situations negative, indicating that selection for reduced variance increases profit. Predicted responses in residual variance after one generation of selection were large, in some cases when the number of progeny per sire was at least 50, by more than 10% of the current residual variance. Progeny testing schemes were more efficient than sib-testing schemes in decreasing residual variance. With optimum traits, selection pressure shifts gradually from the mean to the variance when approaching the optimum. Genetic improvement of uniformity is particularly interesting for traits where the current population mean is near an intermediate optimum.     

Genetic evaluation and selection response for growth in meat-type quail through random regression models using B-spline functions and Legendre polynomials

The objective was to estimate (co)variance functions using random regression models (RRM) with Legendre polynomials, B-spline function and multi-trait models aimed at evaluating genetic parameters of growth traits in meat-type quail. A database containing the complete pedigree information of 7000 meat-type quail was utilized. The models included the fixed effects of contemporary group and generation. Direct additive genetic and permanent environmental effects, considered as random, were modeled using B-spline functions considering quadratic and cubic polynomials for each individual segment, and Legendre polynomials for age. Residual variances were grouped in four age classes. Direct additive genetic and permanent environmental effects were modeled using 2 to 4 segments and were modeled by Legendre polynomial with orders of fit ranging from 2 to 4. The model with quadratic B-spline adjustment, using four segments for direct additive genetic and permanent environmental effects, was the most appropriate and parsimonious to describe the covariance structure of the data. The RRM using Legendre polynomials presented an underestimation of the residual variance. Lesser heritability estimates were observed for multi-trait models in comparison with RRM for the evaluated ages. In general, the genetic correlations between measures of BW from hatching to 35 days of age decreased as the range between the evaluated ages increased. Genetic trend for BW was positive and significant along the selection generations. The genetic response to selection for BW in the evaluated ages presented greater values for RRM compared with multi-trait models. In summary, RRM using B-spline functions with four residual variance classes and segments were the best fit for genetic evaluation of growth traits in meat-type quail. In conclusion, RRM should be considered in genetic evaluation of breeding programs.     

Multiple-population versus hierarchical conifer breeding programs: a comparison of genetic diversity levels

Advanced-generation domestication programs for forest-tree species has raised some concerns about the maintenance of genetic diversity in forest-tree breeding programs. Genetic diversity in natural stands was compared with two genetic conservation options for a third-generation elite Pinus taeda breeding population. The breeding population was subdivided either on the basis of geographic origin and selection goals (multiple-population or MPBS option) or stratified according to genetic value (hierarchical or HOPE option). Most allelic diversity in the natural stands of loblolly pine is present in the domesticated breeding populations. This was true at the aggregate level for both multiple-population (MPBS) and the hierarchical (HOPE) populations. Individual subpopulations within each option had less genetic diversity but it did not decline as generations of improvement increased. Genetic differentiation within the subdivided breeding populations ranged from 1 to 5%, genetic variability is within each subpopulation rather than among subpopulations for both MPBS (>95%) and the HOPE approaches (>98%). Nei's G_st estimates for amongpopulation differentiation were biased upwards relative to estimates of from Weir and Cockerham (1984).     

Optimised parent selection and minimum inbreeding mating in small aquaculture breeding schemes: a simulation study

The effectiveness of low cost breeding scheme designs for small aquaculture breeding programmes were assessed for their ability to achieve genetic gain while managing inbreeding using stochastic simulation. Individuals with trait data were simulated over 15 generations with selection on a single trait. Combinations of selection methods, mating strategies and genetic evaluation options were evaluated with and without the presence of common environmental effects. An Optimal Parent Selection (OPS) method using semi-definite programming was compared with a truncation selection (TS) method. OPS constrains the rate of inbreeding while maximising genetic gain. For either selection method, mating pairs were assigned from the selected parents by either random mating (RM) or Minimum Inbreeding Mating (MIM), which used integer programming to determine mating pairs. Offspring were simulated for each mating pair with equal numbers of offspring per pair and these offspring were the candidates for selection of parents of the next generation. Inbreeding and genetic gain for each generation were averaged over 25 replicates. Combined OPS and MIM led to a similar level of genetic gain to TS and RM, but inbreeding levels were around 75% lower than TS and RM after 15 generations. Results demonstrate that it would be possible to manage inbreeding over 15 generations within small breeding programmes comprised of 30 to 40 males and 30 to 40 females with the use of OPS and MIM. Selection on breeding values computed using Best Linear Unbiased Prediction (BLUP) with all individuals genotyped to obtain pedigree information resulted in an 11% increase in genetic merit and a 90% increase in the average inbreeding coefficient of progeny after 15 generations compared with selection on raw phenotype. Genetic evaluation strategies using BLUP wherein elite individuals by raw phenotype are genotyped to obtain parentage along with a range of different samples of remaining individuals did not increase genetic progress in comparison to selection on raw phenotype. When common environmental effects on full-sib families were simulated, performance of small breeding scheme designs was little affected. This was because the majority of selection must anyway be applied within family due to inbreeding constraints.     

Genetic correlations derived from Full-sib relationships in soybean (Glycine max Merr.)

Summary Spaced plants of a segregating soybean hybrid population in the F₆ generation were scored for fourteen quantitative traits related to yield, foliage development and growth duration. Full-sib relationships were used to estimate the genetic additive components of variation and covariation. All genetic correlations between traits, as well as phenotypic and environmental correlations, were estimated separately. A principal component analysis was further performed in all three cases. Genetic correlations identified four different groups of traits comprised of: (I) seed number per pod; (II) mean seed weight; (III) dry weight and chlorophyll content per unit leaf area; (IV) all the other characters, including seed yield and total plant weight at maturity. Among these traits, stem diameter at ground level appeared to be a good indicator of yield. This distribution remained about the same for the environmental correlations, except that growth duration traits and foliage development traits became independent of yield. The implications of these results are discussed in relation to soybean breeding for climatic adaptation.     

Environmental effects on the structure of the G‐matrix

Genetic correlations between traits determine the multivariate response to selection in the short term, and thereby play a causal role in evolutionary change. Although individual studies have documented environmentally induced changes in genetic correlations, the nature and extent of environmental effects on multivariate genetic architecture across species and environments remain largely uncharacterized. We reviewed the literature for estimates of the genetic variance–covariance ( G ) matrix in multiple environments, and compared differences in G between environments to the divergence in G between conspecific populations (measured in a common garden). We found that the predicted evolutionary trajectory differed as strongly between environments as it did between populations. Between‐environment differences in the underlying structure of G (total genetic variance and the relative magnitude and orientation of genetic correlations) were equal to or greater than between‐population differences. Neither environmental novelty, nor the difference in mean phenotype predicted these differences in G . Our results suggest that environmental effects on multivariate genetic architecture may be comparable to the divergence that accumulates over dozens or hundreds of generations between populations. We outline avenues of future research to address the limitations of existing data and characterize the extent to which lability in genetic correlations shapes evolution in changing environments.     

水稻轮回选择群体XTBG-HP1表型遗传多样性分析

该研究基于4个陆稻群体及172个水稻品种或杂交组合,构建了水稻多亲本隐性核不育轮回选择群体XTBG-HP1,并经过4次轮回重组,采用16个表型性状对其进行了遗传多样性分析。结果表明:(1)该群体14个数量性状符合正态分布,各表型均存在极端性状个体。(2)数量性状变异系数范围为0.08～0.41,均值为0.20; Shannon-Wiener多样性指数范围为0.72～1.92,均值为1.50。(3)群体在株型与产量构成因子性状方面有显著的相关性,对株型的选择可以实现产量性状的改良。(4)剑叶长、每穗粒总数、千粒重、穗长、粒长、一次枝梗数、有效穗数、剑叶宽、二次枝梗数、抽穗期10个性状可作为群体综合评价指标。(5)剑叶长、二次枝梗数、每穗粒总数3个表型性状具有较高的遗传变异、丰富的遗传多样性及与综合得分F值相关系数较高。综合以上结果发现,后期群体进行基因挖掘、品种改良以及优良育种材料的选育可以基于剑叶长、二次枝梗数及每穗粒总数3个表型性状,同时要充分利用群体株型与产量构成因子性状间的显著相关性。此外,该研究群体中极端单性状或综合得分F值较高的个体,可进一步用于品种选育。     

Genetic and plastic responses of a northern mammal to climate change

Climate change is predicted to be most severe in northern regions and there has been much interest in to what extent organisms can cope with these changes through phenotypic plasticity or microevolutionary processes. A red squirrel population in the southwest Yukon, Canada, faced with increasing spring temperatures and food supply has advanced the timing of breeding by 18 days over the last 10 years (6 days per generation). Longitudinal analysis of females breeding in multiple years suggests that much of this change in parturition date can be explained by a plastic response to increased food abundance (3.7 days per generation). Significant changes in breeding values (0.8 days per generation), were in concordance with predictions from the breeder's equation (0.6 days per generation), and indicated that an evolutionary response to strong selection favouring earlier breeders also contributed to the observed advancement of this heritable trait. The timing of breeding in this population of squirrels, therefore, has advanced as a result of both phenotypic changes within generations, and genetic changes among generations in response to a rapidly changing environment.     

Impact of depth of pedigree and inclusion of historical data on the estimation of additive variance and breeding values in a sugarcane breeding program

Sugarcane breeders in Australia combine data across four selection programs to obtain estimates of breeding value for parents. When these data are combined with full pedigree information back to founding parents, computing limitations mean it is not possible to obtain information on all parents. Family data from one sugarcane selection program were analysed using two different genetic models to investigate how different depths of pedigree and amount of data affect the reliability of estimating breeding value of sugarcane parents. These were the parental and animal models. Additive variance components and breeding values estimated from different amounts of information were compared for both models. The accuracy of estimating additive variance components and breeding values improved as more pedigree information and historical data were included in analyses. However, adding years of data had a much larger effect on the estimation of variance components of the population, and breeding values of the parents. To accurately estimate breeding values of all sugarcane parents, a minimum of three generations of pedigree and 5 years of historical data were required, while more information (four generations of pedigree and 7 years of historical data) was required when identifying top parents to be selected for future cross pollination.     

Are female reproductive status and male morphotypes of the giant freshwater prawn Macrobrachium rosenbergii altered by selection for high growth?

Understanding genetic changes in the hierarchical population structure of the giant freshwater prawn (GFP) Macrobrachium rosenbergii is important to improve productivity and profitability of prawn farming. We examined correlated responses in male morphotype and female reproduction status resulting from a selection programme for high growth in a GFP population undergoing four generations of selection. Two contemporary lines (selection and control) were maintained and produced simultaneously; the selection line was selected for high breeding values for harvest body weight and the control for average breeding values of the population. A total of 21,459 individual prawns were measured for body traits and morphotypes. Individual morphotype was recorded as a binary trait (0 and 1) and were analysed using a generalised threshold mixed model with a logit link function. Correlated genetic changes in three important male morphotypes (small, orange and blue claw males) were significant (p < 0.05–0.001) only in generation 2010 but not in the last generation (2012). Selection for high growth did not have an adverse effect on reproduction status of females, except that the selection line had a greater proportion of spawned females than the control (p = 0.01). Our results pointed out that selection for high growth may have had both positive and negative impacts on the social population structure of male morphotypes in GFP. Undesired changes in important morphotypes should be taken account of in genetic improvement programmes for GFP in order to minimise social competition effects and increase total biomass and consequently economic returns of the sector.     

Current genetic research in cotton in India

Genetic research on cotton in India in recent times is reviewed. Establishment of a gene bank with global accessions of the four cultivated species, as well as wild relatives, has facilitated genetic improvement of cotton in India. Genetic control of the economic traits has been studied by biometrical approaches, particularly the line x tester analysis, diallel cross and generation mean analysis. Both additive and non-additive gene actions have been reported for most of the traits. Heritability estimates are low to high. Studies on G×E interaction and stability parameters indicate availability of lines which are stable in their performance over locations and seasons. Genetic improvement of yield, fibre properties, lint percent, seed oil, earliness and resistance to key pests and diseases has been targeted and considerable success has been achieved. Single cross, three-way cross, multiple cross, back cross, biparental mating, mutation breeding and heterosis breeding are the main procedures employed for improvement of yield. Heterosis breeding has, however, made the most significant contributions in improvement of both yield and fibre quality in recent times. While resistant genotypes have been developed for most of the pests and diseases, resistance against cotton bollworms has not been achieved. Genetic engineering to incorporate the Bt gene in cotton to impart resistance to bollworms is in progress. Keeping in view the increased requirements of cotton in the future, thrust areas in genetic research have been indicated.     

Designing artificial selection experiments for specific objectives

The observed genetic gain (ΔP) from selection in a finite population is the possible expected genetic gain E(Δ G) minus the difference in inbreeding depression effects in the selected and control lines. The inbreeding depression can be avoided by crossing the control and selected ♂ and ♀ parents to unrelated mates and summing the observed gains. The possible expected gain will be reduced by an amount D from the predicted gain because of the effects of the genetic limit and random genetic drift, the magnitude of which is a function of effective population size, N. The expected value of D is zero in unselected control populations and in the first generation for selected populations. Therefore, this source of bias can be reduced by increasing N in the selected populations and can be avoided by selecting for a single generation. To obtain observed responses which are unbiased estimates of the predicted response from which to estimate the realized heritability (or regression) in the zero generation, or to test genetic theory based on infinite population size, single-generation selection with many replications would be most efficient. To measure the "total" effect or genetic efficiency of a selection criterion or method, including the effect of different selection intensities, effective population sizes, and space requirements, more than one generation of selection is required to estimate the expected response in breeding values. The efficiency, in the sense of minimum variance, of estimating the expected breeding values at any generation t will decline as the number of generations t increases. The variance of either the estimated mean gain or the regression of gain on selection differential can be reduced more by increasing the number of replicates K than by increasing the number of generations t. Also the general pattern of the response over t can be estimated if the N's are known. Therefore, two- or not more than three-generation selection experiments with many replications would be most efficient.     

Synthesis and parameters of new populations of meat-type chickens

Summary Sire and dam populations of meat-type chickens were developed at the Animal Research Centre, Ottawa to provide unselected control populations suitable for modern broiler research, estimate genetic parameters of broiler traits, and initiate selection experiments. The populations were synthesized from 16 commercial broiler parent stocks (nine sire and seven dam stocks) during two generations of crossbreeding and one generation of random mating. The estimated genetic contribution per stock to the respective population ranged from 8.3 to 16.7% for autosomal genes, from 5.5 to 17.8% for genes on Z chromosomes, and from 0 to 25.0% for genes on W chromosomes. Genetic differences among the original stocks had not been fully diffused among individuals within the populations at the time parameters were estimated. Consequently, genetic parameter estimates are probably slightly biased. Estimated heritabilities of broiler traits in these populations were generally high, 0.39 to 0.63. Hence, rapid genetic change of these traits is possible. The genetic correlation between 28 to 49 day feed efficiency and corresponding weight gain was 0.69 and between feed efficiency and abdominal fat percentage was -0.68. Increasing body weight gain, improving feed efficiency and reducing abdominal fatness of broilers by selection appears feasible.Contribution No. 1203, Animal Research Centre     

Genetic parameters for lactation traits of milking ewes: protein content and composition,fat, somatic cells and individual laboratory cheese yield

The effects of some environmental variation factors and the genetic parameters for total milk traits (fat content, protein content, casein content, serum protein content, lactation mean of individual laboratory cheese yield (LILCY), lactation mean of somatic cell count (LSCC), and milk yield) were estimated from the records of 1 111 Churra ewes. Genetic parameters were estimated by multivariate REML. Heritability for fat content was low (0.10) as is usually found in the Churra breed. Heritabilities for protein content, casein content, serum protein content, LILCY, milk yield and somatic cell count were 0.31, 0.30, 0.22, 0.09, 0.26 and 0.11, respectively. The highest heritability estimates were for protein and casein contents. Casein content is not advisable as an alternative to protein content as a selection criterion for cheese yield improvement; it does not have any compelling advantages and its measurement is costly. Our results for LSCC indicated that efforts should focus on improving the level of management rather than selecting for somatic cells, in the actual conditions of the Churra breed.