Genetic variation within and between subpopulations of the Australian Merino breed

2016 ◽  
Vol 56 (1) ◽  
pp. 87 ◽  
Author(s):  
Andrew A. Swan ◽  
Daniel J. Brown ◽  
Julius H. J. van der Werf
Keyword(s):  
Genetic Variation ◽  
Variance Components ◽  
Additive Genetic Variance ◽  
Genetic Correlations ◽  
Fibre Diameter ◽  
Genetic Group ◽  
Additive Variance ◽  
Breeding Values ◽  
Genetic Groups ◽  
Australian Merino

Genetic variation within and between Australian Merino subpopulations was estimated from a large breeding nucleus in which up to 8500 progeny from over 300 sires were recorded at eight sites across Australia. Subpopulations were defined as genetic groups using the Westell–Quaas model in which base animals with unknown pedigree were allocated to groups based on their flock of origin if there were sufficient ‘expressions’ for the flock, or to one of four broad sheep-type groups otherwise (Ultra/Superfine, Fine/Fine-medium, Medium/Strong, or unknown). Linear models including genetic groups and additive genetic breeding values as random effects were used to estimate variance components for 12 traits: yearling greasy and clean fleece weight (ygfw and ycfw), yearling mean and coefficient of variation of fibre diameter (yfd and ydcv), yearling staple length and staple strength (ysl and yss), yearling fibre curvature (ycuv), yearling body wrinkle (ybdwr), post-weaning weight (pwt), muscle (pemd) and fat depth (pfat), and post-weaning worm egg count (pwec). For the majority of traits, the genetic group variance ranged from approximately equal to two times larger than the additive genetic (within group) variance. The exceptions were pfat and ydcv where the genetic group to additive variance ratios were 0.58 and 0.22, respectively, and pwec and yss where there was no variation between genetic groups. Genetic group correlations between traits were generally the same sign as corresponding additive genetic correlations, but were stronger in magnitude (either more positive or more negative). These large differences between genetic groups have long been exploited by Merino ram breeders, to the extent that the animals in the present study represent a significantly admixed population of the founding groups. The relativities observed between genetic group and additive genetic variance components in this study can be used to refine the models used to estimate breeding values for the Australian Merino industry.

Genetic variation for resistance to clinical and subclinical diseases exists in growing pigs

2001 ◽  
Vol 73 (3) ◽  
pp. 375-387 ◽  
Author(s):  
M. Henryon ◽  
P. Berg ◽  
J. Jensen ◽  
S. Andersen
Keyword(s):  
Genetic Variation ◽  
Respiratory Diseases ◽  
Additive Genetic Variance ◽  
Genetic Correlations ◽  
Frailty Model ◽  
Growing Pigs ◽  
Disease Category ◽  
Breeding Values ◽  
Additive Genetic Variation ◽  
Subclinical Disease

AbstractThe objective of this study was to test that genetic variation for resistance to clinical and subclinical diseases exists in growing pigs. A total of 13 551 male growing pigs were assessed for resistance to five categories of clinical and subclinical disease: (i) any clinical or subclinical disease, (ii) lameness, (iii) respiratory diseases, (iv) diarrhoea, and (v) other diseases (i.e. any clinical or subclinical disease with the exception of (ii), (iii), and (iv)). Additive genetic variation for resistance to each disease category was estimated by fitting a Weibull, sire-dam frailty model to time until the pigs were first diagnosed with a disease from that category. Genetic correlations among the resistances to each disease category were approximated as product-moment correlations among predicted breeding values of the sires. Additive genetic variation was detected for resistance to (i) any clinical or subclinical disease (additive genetic variance for log-frailty (± s.e.) = 0·18 ± 0·05, heritability on the logarithmic-time scale = 0·10), (ii) lameness (0·29 ± 0·11, 0·16), (iii) respiratory diseases (0·24 ± 0·16, 0·12), (iv) diarrhoea (0·30 ± 0·27, 0·16), and (v) the other diseases (0·34 ± 0·15, 0·19) and there were generally positive and low-to-moderate correlations among the predicted breeding values (-0·03 to + 0·65). These results demonstrate that additive genetic variation for resistance to clinical and subclinical diseases does exist in growing pigs, and suggests that selective breeding for resistance could be successful.

Changes in Genetic Variation Induced by Drift

2018 ◽  
Author(s):  
Bruce Walsh ◽  
Michael Lynch
Keyword(s):  
Genetic Variation ◽  
Variance Components ◽  
Genetic Variance ◽  
Additive Genetic Variance ◽  
Additive Variance

In the absence of the input of new variation, drift eventually removes all of the additive-genetic variance in a population. When nonadditive genetic variance is present, some of this variation can be transiently converted into additive variance, resulting in the latter occasionally increasingly (for a time) under inbreeding. This chapter examines the conditions under which such a conversion can occur, which leads to a discussion of the more complex covariances between inbred relatives, requiring the introduction of several new genetic-variance components to be introduced. It also examines the expected equilibrium levels of additive variance under drift-mutation equilibrium.

Comparison of three Australian Merino strains for wool and body traits. II. Estimates of between-stud genetic parameters

1970 ◽  
Vol 21 (5) ◽  
pp. 837 ◽  
Author(s):  
N Jackson ◽  
JW James
Keyword(s):  
Genetic Correlations ◽  
Fibre Diameter ◽  
Short Term ◽  
Breeding Values ◽  
Genetic And Phenotypic Correlations ◽  
Selection For ◽  
Fleece Weight ◽  
Subsequent Selection ◽  
Australian Merino

Data from two-tooth rams and ewes representing seven Australian Merino studs were analysed to provide estimates of between-stud genetic variances and between-stud genetic correlations for 20 wool and body traits. The estimates were used to compare two methods of choosing foundation animals for a new stud: selection within one stud or selection within each of several studs. Where only one trait was considered in selection, and provided that accurate estimates of stud mean breeding values were available, selection from a single stud was superior, although there were some differences between traits in the degree of superiority. Where more than one trait was considered the conclusion depended on the relative magnitudes and signs of the between and within-stud genetic and phenotypic correlations. In the particular case of selection for high clean fleece weight and fine fibre diameter, a strong unfavourable between-stud genetic correlation shifted the emphasis more toward selection from several studs, but selection from a single stud was still superior when accurate estimates of stud mean breeding values for clean fleece weight were available. When response to subsequent selection, as well as immediate gain in choice of founders, was considered, the conclusions were reversed. For a single trait, selection from several studs was always superior in the long term (three or more generations), and also in the short term when accurate estimates of stud mean breeding values were not available.

scholarly journals Additive genetic variance and covariance between relatives in synthetic wheat crosses with variable parental ploidy levels

Genetics ◽  
2021 ◽  
Vol 217 (2) ◽  
Author(s):  
L E Puhl ◽  
J Crossa ◽  
S Munilla ◽  
P Pérez-Rodríguez ◽  
R J C Cantet
Keyword(s):  
Hexaploid Wheat ◽  
Variance Components ◽  
Bayesian Model ◽  
Synthetic Hexaploid Wheat ◽  
Data Sets ◽  
Hierarchical Bayesian Model ◽  
Additive Variance ◽  
Ploidy Levels ◽  
Breeding Values ◽  
Synthetic Hexaploid

Abstract Cultivated bread wheat (Triticum aestivum L.) is an allohexaploid species resulting from the natural hybridization and chromosome doubling of allotetraploid durum wheat (T. turgidum) and a diploid goatgrass Aegilops tauschii Coss (Ae. tauschii). Synthetic hexaploid wheat (SHW) was developed through the interspecific hybridization of Ae. tauschii and T. turgidum, and then crossed to T. aestivum to produce synthetic hexaploid wheat derivatives (SHWDs). Owing to this founding variability, one may infer that the genetic variances of native wild populations vs improved wheat may vary due to their differential origin and evolutionary history. In this study, we partitioned the additive variance of SHW and SHWD with respect to their breed origin by fitting a hierarchical Bayesian model with heterogeneous covariance structure for breeding values to estimate variance components for each breed category, and segregation variance. Two data sets were used to test the proposed hierarchical Bayesian model, one from a multi-year multi-location field trial of SHWD and the other comprising the two species of SHW. For the SHWD, the Bayesian estimates of additive variances of grain yield from each breed category were similar for T. turgidum and Ae. tauschii, but smaller for T. aestivum. Segregation variances between Ae. tauschii—T. aestivum and T. turgidum—T. aestivum populations explained a sizable proportion of the phenotypic variance. Bayesian additive variance components and the Best Linear Unbiased Predictors (BLUPs) estimated by two well-known software programs were similar for multi-breed origin and for the sum of the breeding values by origin for both data sets. Our results support the suitability of models with heterogeneous additive genetic variances to predict breeding values in wheat crosses with variable ploidy levels.

scholarly journals A note on genetic parameters and accuracy of estimated breeding values in honey bees

2019 ◽  
Vol 51 (1) ◽  
Author(s):  
Evert W. Brascamp ◽  
Piter Bijma
Keyword(s):  
Honey Bees ◽  
Variance Components ◽  
Genetic Parameters ◽  
Additive Genetic Variance ◽  
Breeding Value ◽  
Phenotypic Variance ◽  
Breeding Values ◽  
Estimated Breeding Values ◽  
Additive Genetic Relationship ◽  
The Relationship

Abstract Background In honey bees, observations are usually made on colonies. The phenotype of a colony is affected by the average breeding value for the worker effect of the thousands of workers in the colony (the worker group) and by the breeding value for the queen effect of the queen of the colony. Because the worker group consists of multiple individuals, interpretation of the variance components and heritabilities of phenotypes observed on the colony and of the accuracy of selection is not straightforward. The additive genetic variance among worker groups depends on the additive genetic relationship between the drone-producing queens (DPQ) that produce the drones that mate with the queen. Results Here, we clarify how the relatedness between DPQ affects phenotypic variance, heritability and accuracy of the estimated breeding values of replacement queens. Second, we use simulation to investigate the effect of assumptions about the relatedness between DPQ in the base population on estimates of genetic parameters. Relatedness between DPQ in the base generation may differ considerably between populations because of their history. Conclusions Our results show that estimates of (co)variance components and derived genetic parameters were seriously biased (25% too high or too low) when assumptions on the relationship between DPQ in the statistical analysis did not agree with reality.

Genetic evaluation of crossbred lamb production. 4. Genetic parameters for first-cross animal performance

2007 ◽  
Vol 58 (8) ◽  
pp. 839 ◽  
Author(s):  
V. M. Ingham ◽  
N. M. Fogarty ◽  
A. R. Gilmour ◽  
R. A. Afolayan ◽  
L. J. Cummins ◽  
...  
Keyword(s):  
Genetic Variation ◽  
Meat Quality ◽  
Mixed Models ◽  
Fixed Effects ◽  
Growth Traits ◽  
Genetic Correlations ◽  
Fibre Diameter ◽  
Quality Traits ◽  
Meat Quality Traits ◽  
Lamb Growth

The study estimated heritability for lamb growth and carcass performance, hogget ewe wool production, and worm egg count among crossbred progeny of maternal breed sires, as well as the genetic and phenotypic correlations among the traits. The data were from crossbred progeny of 91 sires from maternal breeds including Border Leicester, East Friesian, Finnsheep, Coopworth, White Suffolk, Corriedale, and Booroola Leicester. The sires were mated to Merino ewes at 3 sites over 3 years (and also Corriedale ewes at one site), with 3 common sires used at each site and year to provide genetic links. These sheep comprised part of the national maternal sire central progeny test program (MCPT) to evaluate the genetic variation for economically important production traits in progeny of maternal and dual-purpose (meat and wool) sires and the scope for genetic improvement. The matings resulted in 7846 first-cross lambs born, with 2964 wether lambs slaughtered at an average age of 214 days, and wool data from 2795 hogget ewes. Data were analysed using univariate mixed models containing fixed effects for site, year, sex and type of birth and rearing, dam source and sire breed, and random terms for sire and dam effects. Heritabilities and genetic correlations were estimated based on variances from progeny of 70 sires by fitting the same mixed models using a REML procedure in univariate and multivariate analyses. Estimates of heritability were low for lamb growth traits (0.07–0.29), meat colour and meat pH (0.10–0.23), and faecal worm egg count (0.10), moderate for carcass fat and muscle traits (0.32–0.47), and moderate to high for wool traits (0.36–0.55). Estimates of direct genetic correlations among liveweights at various ages were high and positive (0.41–0.77) and those between liveweights and most carcass and meat quality traits were small and varied in sign. Liveweights were moderately to highly positively correlated with most wool traits, except fibre diameter (–0.28–0.08). The study indicates that there is genetic variation for wool, growth, carcass, and meat quality traits, as well as for faecal worm egg count, with scope for selection within Australian maternal sire breeds of sheep.

Genetic and phenotypic trends and parameters in reproduction, greasy fleece weight and liveweight in Merino lines divergently selected for multiple rearing ability

2004 ◽  
Vol 44 (8) ◽  
pp. 745 ◽  
Author(s):  
S. W. P. Cloete ◽  
A. R. Gilmour ◽  
J. J. Olivier ◽  
J. B. van Wyk
Keyword(s):  
Genetic Correlations ◽  
Annual Production ◽  
Production Traits ◽  
Genetic Progress ◽  
Additive Variance ◽  
Genetic Changes ◽  
Environmental Correlations ◽  
Breeding Values ◽  
Reproduction Traits ◽  
Fleece Weight

Genetic and phenotypic trends and parameters were estimated for reproduction, fleece weight and liveweight in a South African Merino population, divergently selected from 1986, either for (H line) or against (L line) maternal multiple rearing ability. Annual reproduction, ewe greasy fleece weight and pre-joining liveweight data were recorded on 809 Merino ewes, from 1986 to 2002. Phenotypic trends indicated divergence in reproduction traits between the H and L lines. The direct additive variance ratio (h2 ± s.e.) for day of lambing was 0.08 ± 0.02. Estimates of h2 for reproduction traits were: 0.10 ± 0.02 for number of lambs born per ewe; 0.04 ± 0.02 for number of lambs weaned per ewe; and 0.04 ± 0.02 for weight of lamb weaned per ewe, corrected for the gender of the lamb. Corresponding h2 estimates for annual production were 0.57 ± 0.06 for greasy fleece weight and 0.48 ± 0.06 for ewe liveweight at joining. Service sire only exerted a significant (P<0.05) effect on day of lambing, but it accounted for merely 2% of the overall phenotypic variation. Ewe permanent environment variance ratios (c2ewe) for the reproduction traits were: 0.07 ± 0.03 for number of lambs born per ewe; 0.11 ± 0.03 for number of lambs weaned per ewe; and 0.11 ± 0.03 for total weight of lamb weaned per ewe. Corresponding c2ewe estimates for annual production traits were 0.14 ± 0.05 for greasy fleece weight and 0.27 ± 0.06 for ewe joining weight. Genetic and ewe permanent environmental correlations between measures of reproduction exceeded 0.7. Genetic correlations of reproduction traits with greasy fleece weight were low and variable in sign. Genetic correlations of reproduction traits with ewe joining weight were positive and particularly high for weight of lamb weaned. Permanent environmental correlations of reproduction traits with greasy fleece weight and joining weight were generally low to moderate. Genetic trends for the H and L lines (derived from averaged direct breeding values within birth years) were divergent (P<0.01) for all reproduction traits. Expressed as percentage of the overall least squares means of the respective traits, breeding values in the H line increased annually, with 1.3% for lambs born per ewe, 1.5% for lambs weaned per ewe and by 1.8% for weight of lamb weaned per ewe. Corresponding trends in the L line were, respectively, –0.6%, –1.0% and –1.2% per year. Substantial genetic progress in annual lamb output was attainable, despite relatively small h2 estimates. This response was achieved without unfavourable genetic changes in wool and liveweight.

Response to selection in Australian Merino sheep. VIII.* Further results on selection for high clean wool weight with attention to quality

1978 ◽  
Vol 29 (3) ◽  
pp. 615 ◽  
Author(s):  
HN Turner ◽  
N Jackson
Keyword(s):  
Genetic Correlations ◽  
Fibre Diameter ◽  
Control Group ◽  
Environment Interaction ◽  
Genetic Progress ◽  
Weight One ◽  
The Mean ◽  
Selection For ◽  
Made In ◽  
Australian Merino

Results of selection for high clean wool weight per head with control of quality are reported for two selection groups over the period 1966–74. Results for the same experiment for the periods 1950–1959 and 1961–64 were reported earlier. Both groups were selected for high clean wool weight, one (S) with a ceiling on fibre diameter and degree of skin wrinkle, and the other (MS) with a lower limit on staple crimp frequency and a ceiling on skin wrinkle. Genetic progress in clean wool weight was greater in S than in MS over the 1966–74 period (0.12–0.15 lb/annum, compared with 0.06–0.09). This was to be expected from genetic correlations of clean wool weight with fibre diameter (low positive) and staple crimp frequency (high negative). The result supports the previous recommendation that staple crimp frequency is an inefficient way of controlling wool quality while attempting to improve quantity by selection, because its use severely restricts the likely progress in quantity. The actual rate of progress in the S group was similar to that in the period 1950–59, which was followed by a fall in superiority of the selected over the control group animals born during 1961–64. The recovery of response in the 1966–74 period negates the suggestion that the loss of response during the 1961-64 period was due to a 'plateau'. The most likely explanation is that a genotype x environment interaction occurred, such that the genetic gain made in the 1950-59 period could not be expressed in the poorer environments of 1960–65, but reappeared gradually under the improving environment of the 1966–74 period. Attempts to remove this interaction by regression of response on the mean clean wool weight of the unselected control group (as an index of the level of the environment) for each year, were not successful. The interaction is, therefore, not simply a case of all selection groups being equal when the environment is poor. ________________ *Part VII, Aust. J. Agric. Res., 26: 937 (1975).

Genetic studies on growth, reproduction and wool productiontraits in Harnali sheep

2016 ◽  
Author(s):  
SPACE Lalit ◽  
Z. S. Malik ◽  
D. S. Dalal ◽  
C. S. Patil ◽  
S. P. Dahiya
Keyword(s):  
Body Weight ◽  
Growth Traits ◽  
Additive Genetic Variance ◽  
Genetic Correlations ◽  
Fibre Diameter ◽  
Reproductive Traits ◽  
Phenotypic Correlation ◽  
Reproduction Traits ◽  
Heritability Estimates ◽  
Fleece Weight

Data on growth, reproduction and wool traits of 1603 Harnali sheep maintained at Lala Lajpat Rai University of Veterinary and Animal Sciences, Hisar over a period of 22 years (1992-2013) were utilized for genetic analysis. The overall least squares mean for birth weight (BW), weaning weight (WW), six month body weight (SMW), age at first lambing (AFL), weight at lambing (WL), average lambing interval (ALI), greasy fleece weight (GFW), staple length (SL) and Fibre diameter (FD) were estimated as 3.35±0.02 kg, 12.41±0.08 kg, 16.30±0.12 kg, 707.05±2.07 days, 26.91±0.10 kg and 402.85±2.40 days, 1.62±0.02 kg, 5.65±0.03 cm and 25.85±0.07 μ, respectively. The effect of year of birth, sex of lamb and dam's weight at lambing were significant for all growth traits. The effect of year of birth and dam's weight at lambing were significant for all reproduction traits and GFW. No definite trend was observed over the years for body weights and reproductive traits. The effect of sex was significant for early growth traits. The heritability estimates were moderate for all the growth traits with high genetic correlations of BW and WW with SMW. Reproduction traits had lower estimates of heritability which indicated presence of lower additive genetic variance for these traits. Heritability estimates for studied wool traits were moderate to high. Positive genetic and phenotypic correlation of BW and WW with six month body weight and grease fleece weight indicated that selection for six month body weight would increase body weight and grease fleece weight.

scholarly journals Bedeutung der Varianzkomponentenschätzung für die Zucht von landwirtschaftlichen Nutztieren – eine Übersicht

2000 ◽  
Vol 43 (5) ◽  
pp. 523-534
Author(s):  
R. Röhel ◽  
J. Krieter ◽  
R. Preisinger
Keyword(s):  
Variance Components ◽  
Genetic Relationships ◽  
Additive Genetic Variance ◽  
Period Change ◽  
Farm Animals ◽  
Selection Strategy ◽  
Sampling Variance ◽  
Breeding Values ◽  
Variance Components Estimation ◽  
Estimation Of Variance

Abstract. Title of the paper: The importance of variance components estimation in breeding of farm animals – a review The present paper showed the importance of variance components estimation in animal breeding. Beside the use of variance components for estimation of breeding values, the components have a high importance on further breeding aspects, such as indication of selection limits, optimisation of test period, change of Performance during growth, and determination of the best selection traits. Maternal and non-additive genetic variance components can be estimated and their high influence on choice of the optimal selection strategy are explained. Standard errors of crossbreeding parameters are influenced by genetic relationships and are only unbiased when using all genetic variances and covariances among animals. Genotype-environmental-interaction and heterogeneous variances, which result in high reduction in selection response, can be obtained in a variance components estimation. The high value of Bayesian methods in order to describe the sampling variance of variance components and to account for the Standard error of estimation of variance components in the estimation of breeding values is explained.

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