Genetic parameters asociated with characters affecting egg production in the domestic fowl. II. Heritability of egg production for two part-annual periods of measurement and the genetic correlation between them

Estimates of important genetic parameters have been obtained from an experimental flock using data collected over a period of 3 years. A total of 1784 progeny, obtained from 42 sires and 383 dams, supplied records for analysis. The information was mainly extracted using the analysis of variance and covariance from which estimates of genetic variance and covariance were obtained. Pooling the results within years and, where applicable, within breeding groups, estimates of heritability were obtained as follows: Production Index: part period, 32 per cent.; 72 weeks, 31 per cent. Survivor Index: part period, 33 per cent.; 72 weeks, 33 per cent. The low mortality rate should be borne in mind when comparing the estimates for the Production Index with those obtained by other workers. The estimated genetic correlation between the Production Index for these two periods was 0.72. The magnitude of the heritability estimates indicates the presence of a considerable amount of additive genetic variation. The proportion of this type of genetic variation has probably been increased by the minimizing of environmental variation effected by the randomization of birds over the housing space and, in the case of the part period of recording, by the corrections applied for hatching date influence. Early selection, based on partial records, has been shown to be approximately 1½ times as effective in producing genetic improvement as selection based on the full production.

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Genetic parameters associated with characters effecting egg production in the domestic fowl. I. Heritability of total egg production during the pullet year

Australian Journal of Agricultural Research ◽

10.1071/ar9560625 ◽

1956 ◽

Vol 7 (6) ◽

pp. 625 ◽

Cited By ~ 1

Author(s):

BL Sheldon

Keyword(s):

Standard Error ◽

Domestic Fowl ◽

Egg Production ◽

Genetic Parameters ◽

Research Centre ◽

Narrow Sense ◽

White Leghorn ◽

Components Of Variance ◽

Production Index ◽

The Mean

Egg production records of White Leghorn pullets hatched a t the Poultry Research Centre, Werribee, Vic., during 1947 to 1950 inclusive have been analysed both on a hen-housed (Production Index) and a survivor basis. Estimates of heritability were obtained by two methods: (1) by the analysis of components of variance between families of full sibs and half-sibs; (2) by estimating the intra-sire regression of the mean performance of offspring on dam's performance. Heritability, in the narrow sense, of Production Index during the pullet year is shown to be 23-30 per cent. with a reasonably low standard error, while heritability of survivors' production is slightly lower but not significantly so. Possible reasons are advanced for the low estimates of heritability of survivors' production.

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RIB AND VERTEBRAL NUMBERS IN SWINE: II. GENETIC ASPECTS

Canadian Journal of Animal Science ◽

10.4141/cjas62-037 ◽

1962 ◽

Vol 42 (2) ◽

pp. 240-251 ◽

Cited By ~ 10

Author(s):

H. T. Fredeen ◽

J. A. Newman

Keyword(s):

Genetic Variation ◽

Genetic Correlation ◽

Analysis Of Variance ◽

Genetic Parameters ◽

Bilateral Asymmetry ◽

Vertebral Number

Genetic parameters for rib and vertebral number in swine were estimated from data for 4,219 pigs produced by 78 sires and 359 dams of the Lacombe breed. Regressions of offspring on mid-parent were.599 ±.017 for vertebral number and.734 ±.020 for rib number and the corresponding full sib correlations estimated from the analysis of variance were.591 ±.071 and.591 ±.060. The genetic correlation between these two skeletal traits was estimated as.813 ±.022 by the regression of offspring on mid-parent and.792 ±.016 by the analysis of components of covariance.Continuous genetic variation for both traits was demonstrated. The modal phenotype (i.e., 16 pairs of ribs and 22 vertebrae) produced progeny more uniform for both traits than did parents of non-modal phenotypes. Bilateral asymmetry (within-pig variance) was also least among progeny of "modal" parents.

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Genetic parameters for egg weight v. age curve, and other egg production and egg weight traits, in synthetic lines of chickens

Australian Journal of Agricultural Research ◽

10.1071/ar9830085 ◽

1983 ◽

Vol 34 (1) ◽

pp. 85 ◽

Cited By ~ 5

Author(s):

BH Yoo ◽

BL Sheldon ◽

RN Podger

Keyword(s):

Standard Deviation ◽

Genetic Correlation ◽

Egg Production ◽

Genetic Parameters ◽

Genetic Correlations ◽

Egg Mass ◽

Control Line ◽

Egg Weight ◽

Egg Number ◽

Selection For

An exponential curve, W = P-Qexp(- Rt), where W is egg weight at age t, was fitted to egg weights of individual pullets, and genetic parameters were estimated for P, Q and R, the residual standard deviation and other egg weight and egg production characters. The data consisted of records collected over six generations on more than 4000 pullets in two selection lines and a control line which originated from a synthetic gene pool of White Leghorn x Australorp crosses. The half-sib and offspring-on-parent regression estimates of heritability pooled over the lines were 0.23 and 0.33 for P, 0.14 and 0.20 for Q, and 0.14 and 0.25 for R. Genetic correlations were estimated to be -0.10 between P and Q, -0.46 between P and R, and 0.90 between Q and R. These estimates suggest that the egg weight v. age curve may be modified to increase the proportion of eggs in desirable weight grades and reduce the incidence of oversized eggs later in the production year. The genetic correlation between mean weight of first 10 eggs and egg weight at 62 weeks of age was estimated to be 0.68, further suggesting that early egg weight may be improved partly independently of late egg weight. The heritability estimates of egg mass output were not higher than those of egg number in spite of the highly heritable average egg weight being an important component of egg mass, probably because of the negative genetic correlation (r = -0.49) between egg number and average egg weight. The standard deviation of individual pullet's egg weights was moderately heritable and genetically correlated positively with egg weight characters and negatively with egg production; these estimates were consistent with the responses to selection for reduced egg weight variability observed elsewhere

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Genetic analysis of clinical mastitis during different risk periods in Finnish Ayrshire

Agricultural and Food Science ◽

10.2137/145960607782219373 ◽

2008 ◽

Vol 16 (2) ◽

pp. 115 ◽

Cited By ~ 3

Author(s):

E. NEGUSSIE ◽

I. STRANDÉN ◽

E. MÄNTYSAARI

Keyword(s):

Genetic Variation ◽

Genetic Information ◽

Genetic Parameters ◽

Genetic Correlations ◽

Clinical Mastitis ◽

Data Sets ◽

Threshold Models ◽

Early Lactation ◽

Sire Evaluation ◽

Using Data

Clinical mastitis (CM) records from first-lactation Finnish Ayrshire were analysed by linear and threshold models to assess the effects trait definition on estimates of genetic parameters and sire evaluation. The studied CM traits were defined by dividing lactation into six lactation stages (risk periods) by days (d) after calving: CM1 (-7 to 150 d), CM2 (-30 to 30 d), CM3 (-30 to 150 d), CM4 (31 to 150 d), CM5 (150 to 300 d), CM6 (-30 to 300 d). In addition, two data sets were prepared to assess the effect of excluding (Data I) or including (Data II) records of culled cows on estimates of genetic parameters. Sire variances and heritabilities were larger using Data II. When data from longer intervals was used heritabilities of CM were slightly higher than shorter intervals indicating that longer intervals tend to obscure genetic variation between animals. Of all CM traits, heritability of liability to CM with threshold-liability model was highest for CM2 (h2=0.083) implying that most of the genetic information on CM is in early lactation. In sire evaluation, a multitrait index calculated by combining CM2, CM4 and CM5 had the highest correlation with all other univariate CM trait evaluations. This and the magnitude (less than 1.0) of genetic correlations between CM traits suggest that a multitrait model considering CM from the different risk periods would be appropriate for CM sire evaluation.;

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303 ASAS-EAAP Talk: On the estimation of genetic parameters from molecular data

Journal of Animal Science ◽

10.1093/jas/skaa278.059 ◽

2020 ◽

Vol 98 (Supplement_4) ◽

pp. 33-33

Author(s):

Miguel Toro Ibáñez

Keyword(s):

Linkage Disequilibrium ◽

Genetic Correlation ◽

Genomic Selection ◽

Genetic Parameters ◽

Genetic Variance ◽

Genetic Correlations ◽

Molecular Data ◽

Snp Markers ◽

Directional Selection ◽

Recombination Rates

Abstract We deal with several problems that arise when inferring genetic parameters at the level of quantitative trait loci (QTL) from molecular data such as SNP markers. Linkage Disequilibrium (LD) is recognized as a factor creating ambiguity in the partition of genetic variance. Here, using a simple model with three loci (one QTL and two markers), it is shown that the markers generate apparent AxA and DxD epistasis, even if only third order disequilibrium exists and the QTL is dominant. The problem of “phantom epistasis” is not alleviated by larger sample sizes (de los Campos et al., 2019). We also show that markers can give a distorted picture of the genetic correlation between traits: The genomic correlation could be greater, lower or even of opposite sign than the true genetic correlation. Therefore, speculating about genetic correlations and even about their causes (e.g., pleiotropy) using genomic data is often conjectural. Thirdly, we examine the problem of directional selection generating negative linkage disequilibrium (“Bulmer effect”) in the short term from a genomic selection perspective. It seems that the reduction in response due to the Bulmer effect is the same for genomic selection as for selection based on traditional BLUP. However, the reduction in response with genomic selection is greater than when selection is based directly on phenotypes only (Van Grevenhof et al. 2012). It is also expected that directional selection for a polygenic trait should increase recombination rate, provided there is genetic variance for recombination. It is then of relevance to ask whether recombination rates could be manipulated in order to increase selection response (Battagin et al., 2016). Finally, we consider that recombination and epistasis are closely intertwined: Epistasis generate LD and recombination break them up. Then, we should expect genomes to be modular: regions with low recombination containing functionally related genes loosely linked to other regions.

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What can genetic variation tell us about the evolution of senescence?

Proceedings of The Royal Society B Biological Sciences ◽

10.1098/rspb.2009.0183 ◽

2009 ◽

Vol 276 (1665) ◽

pp. 2271-2278 ◽

Cited By ~ 30

Author(s):

Jacob A. Moorad ◽

Daniel E.L. Promislow

Keyword(s):

Genetic Variation ◽

Variance Components ◽

Genetic Parameters ◽

Genetic Variance ◽

Mutation Accumulation ◽

Antagonistic Pleiotropy ◽

Age Classes ◽

Dominance Variance ◽

Quantitative Genetic ◽

Genetic Techniques

Quantitative genetic approaches have been developed that allow researchers to determine which of two mechanisms, mutation accumulation (MA) or antagonistic pleiotropy (AP), best explain observed variation in patterns of senescence using classical quantitative genetic techniques. These include the creation of mutation accumulation lines, artificial selection experiments and the partitioning of genetic variances across age classes. This last strategy has received the lion's share of empirical attention. Models predict that inbreeding depression (ID), dominance variance and the variance among inbred line means will all increase with age under MA but not under those forms of AP that generate marginal overdominance. Here, we show that these measures are not, in fact, diagnostic of MA versus AP. In particular, the assumptions about the value of genetic parameters in existing AP models may be rather narrow, and often violated in reality. We argue that whenever ageing-related AP loci contribute to segregating genetic variation, polymorphism at these loci will be enhanced by genetic effects that will also cause ID and dominance variance to increase with age, effects also expected under the MA model of senescence. We suggest that the tests that seek to identify the relative contributions of AP and MA to the evolution of ageing by partitioning genetic variance components are likely to be too conservative to be of general value.

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Inferring the trajectory of genetic variance in the course of artificial selection

Genetics Research ◽

10.1017/s0016672300004845 ◽

2001 ◽

Vol 77 (1) ◽

pp. 83-94 ◽

Cited By ~ 34

Author(s):

D. SORENSEN ◽

R. FERNANDO ◽

D. GIANOLA

Keyword(s):

Monte Carlo ◽

Markov Chain ◽

Genetic Parameters ◽

Genetic Variance ◽

Additive Genetic Variance ◽

Selection Response ◽

Selection Experiment ◽

Marginal Posterior Distribution ◽

Using Data ◽

True Values

A method is proposed to infer genetic parameters within a cohort, using data from all individuals in an experiment. An application is the study of changes in additive genetic variance over generations, employing data from all generations. Inferences about the genetic variance in a given generation are based on its marginal posterior distribution, estimated via Markov chain Monte Carlo methods. As defined, the additive genetic variance within the group is directly related to the amount of selection response to be expected if parents are chosen within the group. Results from a simulated selection experiment are used to illustrate properties of the method. Four sets of data are analysed: directional selection with and without environmental trend, and random selection, with and without environmental trend. In all cases, posterior credibility intervals of size 95% assign relatively high density to values of the additive genetic variance and heritability in the neighbourhood of the true values. Properties and generalizations of the method are discussed.

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Genetic parameters of growth between birth and sixteen weeks in Down Cross Sheep

Animal Science ◽

10.1017/s0003356100037788 ◽

1966 ◽

Vol 8 (1) ◽

pp. 129-135 ◽

Cited By ~ 14

Author(s):

J. C. Bowman ◽

J. S. Broadbent

Keyword(s):

Genetic Variation ◽

Combining Ability ◽

Genetic Parameters ◽

Genetic Variance ◽

Additive Genetic Variance ◽

Specific Combining Ability ◽

Limited Evidence

This paper reports a paternal half sib analysis of data collected over 3 years to estimate additive genetic variance of growth between birth and 16 weeks in crossbred progeny derived from Down rams. The data were divided into two groups and pooled estimates of parameters obtained by two methods. The paternal half sib intra-class correlations varied between 0·017 and 0·057 depending on pooling group and method. It is suggested that such low correlations arise because (a) most of the lambs in the study were still sucking at slaughter, close to 16 weeks of age, and the trait measured is thus largely influenced by maternal milking ability (b) the selection practised in the Down breeds may have been effective and reduced genetic variation and (c) there is considerable inbreeding in the Down breeds.In further analysis of data from four farms involving rams mated to more than one breed of ewe there was limited evidence of specific combining ability of growth between birth and 16 weeks of age for Welsh ewes compared to ewes of other breeds.

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