Mating animals by minimising the covariance between ancestral contributions generates less inbreeding without compromising genetic gain in breeding schemes with truncation selection

Quadratic indices are a general approach for the joint management of genetic gain and inbreeding in artificial selection programmes. They provide the optimal contributions that selection candidates should have to obtain the maximum gain when the rate of inbreeding is constrained to a predefined value. This study shows that, when using quadratic indices, the selective advantage is a function of the Mendelian sampling terms. That is, at all times, contributions of selected candidates are allocated according to the best available information about their Mendelian sampling terms (i.e. about their superiority over their parental average) and not on their breeding values. By contrast, under standard truncation selection, both estimated breeding values and Mendelian sampling terms play a major role in determining contributions. A measure of the effectiveness of using genetic variation to achieve genetic gain is presented and benchmark values of 0·92 for quadratic optimisation and 0·5 for truncation selection are found for a rate of inbreeding of 0·01 and a heritability of 0·25.

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Pre-selection against a lethal recessive allele in breeding schemes with optimum-contribution selection or truncation selection

Genetics Selection Evolution ◽

10.1186/s12711-021-00669-4 ◽

2021 ◽

Vol 53 (1) ◽

Author(s):

Line Hjortø ◽

Mark Henryon ◽

Huiming Liu ◽

Peer Berg ◽

Jørn Rind Thomasen ◽

...

Keyword(s):

Genetic Gain ◽

Recessive Allele ◽

Selection Strategy ◽

Carrier Status ◽

Truncation Selection ◽

Selection Strategies ◽

Significant Difference ◽

Selection Step ◽

Breeding Schemes ◽

Male Carriers

Abstract Background We tested the hypothesis that breeding schemes with a pre-selection step, in which carriers of a lethal recessive allele (LRA) were culled, and with optimum-contribution selection (OCS) reduce the frequency of a LRA, control rate of inbreeding, and realise as much genetic gain as breeding schemes without a pre-selection step. Methods We used stochastic simulation to estimate true genetic gain realised at a 0.01 rate of true inbreeding (ΔFtrue) by breeding schemes that combined one of four pre-selection strategies with one of three selection strategies. The four pre-selection strategies were: (1) no carriers culled, (2) male carriers culled, (3) female carriers culled, and (4) all carriers culled. Carrier-status was known prior to selection. The three selection strategies were: (1) OCS in which $$\Delta {\text{F}}_{{{\text{true}}}}$$ Δ F true was predicted and controlled using pedigree relationships (POCS), (2) OCS in which $$\Delta {\text{F}}_{{{\text{true}}}}$$ Δ F true was predicted and controlled using genomic relationships (GOCS), and (3) truncation selection of parents. All combinations of pre-selection strategies and selection strategies were tested for three starting frequencies of the LRA (0.05, 0.10, and 0.15) and two linkage statuses with the locus that has the LRA being on a chromosome with or without loci affecting the breeding goal trait. The breeding schemes were simulated for 10 discrete generations (t = 1, …, 10). In all breeding schemes, ΔFtrue was calibrated to be 0.01 per generation in generations t = 4, …, 10. Each breeding scheme was replicated 100 times. Results We found no significant difference in true genetic gain from generations t = 4, …, 10 between breeding schemes with or without pre-selection within selection strategy. POCS and GOCS schemes realised similar true genetic gains from generations t = 4, …, 10. POCS and GOCS schemes realised 12% more true genetic gain from generations t = 4, …, 10 than truncation selection schemes. Conclusions We advocate for OCS schemes with pre-selection against the LRA that cause animal suffering and high costs. At LRA frequencies of 0.10 or lower, OCS schemes in which male carriers are culled reduce the frequency of LRA, control rate of inbreeding, and realise no significant reduction in true genetic gain compared to OCS schemes without pre-selection against LRA.

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Breeding schemes in reindeer husbandry

Rangifer ◽

10.7557/2.23.2.360 ◽

2003 ◽

Vol 23 (2) ◽

pp. 45 ◽

Cited By ~ 3

Author(s):

Lars Rönnegård ◽

J. A. Woolliams ◽

Öje Danell

Keyword(s):

Genetic Gain ◽

Mass Selection ◽

Effective Population ◽

Selection Programme ◽

Breeding Schemes ◽

The Difference ◽

Genetic Contributions ◽

Parameter Values ◽

Open Nucleus

The objective of the paper was to investigate annual genetic gain from selection (G), and the influence of selection on the inbreeding effective population size (Ne), for different possible breeding schemes within a reindeer herding district. The breeding schemes were analysed for different proportions of the population within a herding district included in the selection programme. Two different breeding schemes were analysed: an open nucleus scheme where males mix and mate between owner flocks, and a closed nucleus scheme where the males in non-selected owner flocks are culled to maximise G in the whole population. The theory of expected long-term genetic contributions was used and maternal effects were included in the analyses. Realistic parameter values were used for the population, modelled with 5000 reindeer in the population and a sex ratio of 14 adult females per male. The standard deviation of calf weights was 4.1 kg. Four different situations were explored and the results showed: 1. When the population was randomly culled, Ne equalled 2400. 2. When the whole population was selected on calf weights, Ne equalled 1700 and the total annual genetic gain (direct + maternal) in calf weight was 0.42 kg. 3. For the open nucleus scheme, G increased monotonically from 0 to 0.42 kg as the proportion of the population included in the selection programme increased from 0 to 1.0, and Ne decreased correspondingly from 2400 to 1700. 4. In the closed nucleus scheme the lowest value of Ne was 1300. For a given proportion of the population included in the selection programme, the difference in G between a closed nucleus scheme and an open one was up to 0.13 kg. We conclude that for mass selection based on calf weights in herding districts with 2000 animals or more, there are no risks of inbreeding effects caused by selection.

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The effect of improved reproductive performance on genetic gain and inbreeding in MOET breeding schemes for beef cattle

Genetics Selection Evolution ◽

10.1186/1297-9686-27-4-347 ◽

1995 ◽

Vol 27 (4) ◽

pp. 347 ◽

Cited By ~ 8

Author(s):

B Villanueva ◽

JA Woolliams ◽

G Simm

Keyword(s):

Beef Cattle ◽

Reproductive Performance ◽

Genetic Gain ◽

Breeding Schemes

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Predicting genetic gain when rates of inbreeding are constrained to pre-defined values

Proceedings of the British Society of Animal Science ◽

10.1017/s1752756200012059 ◽

2003 ◽

Vol 2003 ◽

pp. 46-46

Author(s):

S. Avendaño ◽

J.A. Woolliams ◽

B. Villanueva

Keyword(s):

Beef Cattle ◽

Genetic Gain ◽

Index Score ◽

Optimal Selection ◽

Dynamic Selection ◽

Novel Approach ◽

Breeding Schemes ◽

The Uk ◽

Selection Algorithms

Dynamic selection algorithms using quadratic indices to optimise the contributions of selection candidates for maximising rates of genetic gain (ΔG) while constraining the rate of inbreeding (ΔF) in the long-term to pre-defined values, are available (Grundy et al, 1998). Avendaño et al (2001 a,b) applied these optimal selection algorithms on the UK Meatlinc (sheep) and Aberdeen Angus (beef cattle) pedigree breeds and found substantial expected increases (of at least 17%) in the average index score at the observed ΔF. Although these algorithms constitute powerful operational tools for breeding schemes, the framework for deterministically predicting ΔG under optimal selection with restricted ΔF is not yet available. This study presents a novel approach to this problem.

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Efficiency of nucleus breeding schemes in dual-purpose cattle of Tanzania

Animal Science ◽

10.1017/s0003356100004694 ◽

1990 ◽

Vol 50 (2) ◽

pp. 245-251 ◽

Cited By ~ 5

Author(s):

J. S. Kasonta ◽

G. Nitter

Keyword(s):

Artificial Insemination ◽

Genetic Gain ◽

Cattle Breed ◽

Progeny Testing ◽

Environment Interaction ◽

Dual Purpose ◽

Model Calculations ◽

Dual Purpose Cattle ◽

Total Profit ◽

Breeding Schemes

ABSTRACTFor the Mpwapwa cattle breed in Tanzania, the efficiency of various breeding schemes including an open nucleus was investigated by model calculations. Artificial insemination and intensive recording of production are assumed to be applied in a nucleus which is the main breeding unit. As a pre-nucleus, associated herds with less intense data recording serve as the basis to screen superior cows for nucleus replacements, provide the capacity for progeny testing, and operate as bull multipliers for commercial herds.The criteria of efficiency were genetic gain and profit from selection for a dual purpose breeding objective (milk and beef) in a total population of 10 000 cows. Introducing a two breeding tier scheme through separating all recorded cows into a nucleus and pre-nucleus leads to an increase of the genetic gain rather than the profit. Further improvement is obtained by introduction of artificial insemination in pre-nucleus herds. The nucleus size should not exceed about 5% of the cow population and an optimum size of the pre-nucleus is about 15%. Opening the nucleus to replacement cows coming from the pre-nucleus affects the aggregate genetic gain very little although it can be recommended if milk yield is to be mainly improved or if the total profit is taken into account. Furthermore, the nucleus should be opened if there is little difference between the heritabilities in the nucleus and pre-nucleus and also in order to avoid detrimental effects of inbreeding and genotype × environment interaction.

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Designing dairy cattle breeding schemes under genomic selection: a review of international research

Animal Production Science ◽

10.1071/an11098 ◽

2012 ◽

Vol 52 (3) ◽

pp. 107 ◽

Cited By ~ 67

Author(s):

J. E. Pryce ◽

H. D. Daetwyler

Keyword(s):

Dairy Cattle ◽

Genomic Selection ◽

Genetic Gain ◽

Reproductive Technologies ◽

Progeny Testing ◽

Genomic Breeding ◽

Breeding Values ◽

Scheme Design ◽

Dairy Cattle Breeding ◽

Breeding Schemes

High rates of genetic gain can be achieved through (1) accurate predictions of breeding values (2) high intensities of selection and (3) shorter generation intervals. Reliabilities of ~60% are currently achievable using genomic selection in dairy cattle. This breakthrough means that selection of animals can happen at a very early age (i.e. as soon as a DNA sample is available) and has opened opportunities to radically redesign breeding schemes. Most research over the past decade has focussed on the feasibility of genomic selection, especially how to increase the accuracy of genomic breeding values. More recently, how to apply genomic technology to breeding schemes has generated a lot of interest. Some of this research remains the intellectual property of breeding companies, but there are examples in the public domain. Here we review published research into breeding scheme design using genomic selection and evaluate which designs appear to be promising (in terms of rates of genetic gain) and those that may have unfavourable side-effects (i.e. increasing the rate of inbreeding). The schemes range from fairly conservative designs where bulls are screened genomically to reduce numbers entering progeny testing, to schemes where very large numbers of bull calves are screened and used as sires as soon as they reach sexual maturity. More radical schemes that incorporate the use of reproductive technologies (in juveniles) and genomic selection in nucleus herds are also described. The models used are either deterministic and more recently tend to be stochastic, simulating populations of cattle. A key driver of the rate of genetic gain is the generation interval, which could range from being similar to that in conventional testing (~5 years), down to as little as 1.5 years. Generally, the rate of genetic gain is between 12% and 100% more than in conventional progeny testing, while the rate of inbreeding tends to be lower per generation than in progeny testing because Mendelian sampling terms can be estimated more accurately. However, short generation intervals can lead to higher rates of inbreeding per year in genomic breeding programs.

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New cycle, same old mistakes? Overlapping vs. discrete generations in long-term recurrent selection

10.1101/2021.10.12.464059 ◽

2021 ◽

Author(s):

Marlee R. Labroo ◽

Jessica E. Rutkoski

Keyword(s):

Genetic Gain ◽

Overlapping Generations ◽

Recurrent Selection ◽

Phenotypic Selection ◽

Breeding Value ◽

Breeding Values ◽

Truncation Selection ◽

Breeding Cycles ◽

Error Bias

Background: Recurrent selection is a foundational breeding method for quantitative trait improvement. It typically features rapid breeding cycles that can lead to high rates of genetic gain. In recurrent phenotypic selection, generations do not overlap, which means that breeding candidates are evaluated and considered for selection for only one cycle. With recurrent genomic selection, candidates can be evaluated based on genomic estimated breeding values indefinitely, therefore facilitating overlapping generations. Candidates with true high breeding values that were discarded in one cycle due to underestimation of breeding value could be identified and selected in subsequent cycles. The consequences of allowing generations to overlap in recurrent selection are unknown. We assessed whether maintaining overlapping and discrete generations led to differences in genetic gain for phenotypic, genomic truncation, and genomic optimum contribution recurrent selection by simulation of traits with various heritabilities and genetic architectures across fifty breeding cycles. We also assessed differences of overlapping and discrete generations in a conventional breeding scheme with multiple stages and cohorts. Results: With phenotypic selection, overlapping generations led to decreased genetic gain compared to discrete generations due to increased selection error bias. Selected individuals, which were in the upper tail of the distribution of phenotypic values, tended to also have high absolute error relative to their true breeding value compared to the overall population. Without repeated phenotyping, these erroneously outlying individuals were repeatedly selected across cycles, leading to decreased genetic gain. With genomic truncation selection, overlapping and discrete generations performed similarly as updating breeding values precluded repeatedly selecting individuals with inaccurately high estimates of breeding values in subsequent cycles. Overlapping generations did not outperform discrete generations in the presence of a positive genetic trend with genomic truncation selection, as past generations had lower mean genetic values than the current generation of selection candidates. With genomic optimum contribution selection, overlapping and discrete generations performed similarly, but overlapping generations slightly outperformed discrete generations in the long term if the targeted inbreeding rate was extremely low. Conclusions: Maintaining discrete generations in recurrent phenotypic mass selection leads to increased genetic gain, especially at low heritabilities, by preventing selection error bias. With genomic truncation selection and genomic optimum contribution selection, genetic gain does not differ between discrete and overlapping generations assuming non-genetic effects are not present. Overlapping generations may increase genetic gain in the long term with very low targeted rates of inbreeding in genomic optimum contribution selection.

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Selection with control of inbreeding in populations with overlapping generations: a comparison of methods

Animal Science ◽

10.1017/s1357729800051547 ◽

2000 ◽

Vol 70 (1) ◽

pp. 1-8 ◽

Cited By ~ 15

Author(s):

A. K. Sonesson ◽

B. Grundy ◽

J. A. Woolliams ◽

T. H. E. Meuwissen

Keyword(s):

Computer Simulations ◽

Optimization Algorithm ◽

Genetic Gain ◽

Overlapping Generations ◽

Current Level ◽

Comparison Of Methods ◽

Genetic Response ◽

Age Classes ◽

Feasible Method ◽

Breeding Schemes

AbstractMethods that maximize genetic response in populations with overlapping generations while controlling rate of inbreeding by constraining the average relationship among selection candidates were compared. Firstly, computer simulations of closed nucleus selection schemes showed that a two-stage optimization algorithm approach, where the distribution of parents within and thereafter over age classes was optimized resulted in different breeding schemes than an approach that performed an iteration on this distribution. It yielded significantly lower annual genetic gain (0·194 v. 0·223 σp units), fewer animals selected (21·9 v. 26·4) and longer generation intervals (2·38 v. 1·68 years) but maintained the rate of inbreeding closer to its constraint. In large schemes, iteration may be computationally the only feasible method for the optimization of parents across age classes. Secondly, the use of conventional relationships for constraining inbreeding was compared with that of augmented relationships, which do not depend on the level of inbreeding. Both relationships resulted in very similar breeding schemes, but the use of augmented relationships avoids correction of the current level of inbreeding. Thirdly, a constraint of the rate of inbreeding on a per year basis was compared with a constraint on a per generation basis. When optimizing per generation, the generation interval was shorter compared with a scheme where an analogous annual restriction was in place (2·01 v. 2·38 years) and the annual rate of genetic gain was higher (0·214 v. 0·194 σp units).

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Intensified Use of Reproductive Technologies and Reduced Dimensions of Breeding Schemes Put Genetic Diversity at Risk in Dairy Cattle Breeds

Animals ◽

10.3390/ani10101903 ◽

2020 ◽

Vol 10 (10) ◽

pp. 1903

Author(s):

Anna-Charlotte Doublet ◽

Gwendal Restoux ◽

Sébastien Fritz ◽

Laura Balberini ◽

Guillaume Fayolle ◽

...

Keyword(s):

Genetic Diversity ◽

Dairy Cattle ◽

Genetic Gain ◽

Reproductive Technologies ◽

Vitro Fertilization ◽

Cattle Breeds ◽

Reduced Dimensions ◽

Recent Trends ◽

Breeding Schemes

In the management of dairy cattle breeds, two recent trends have arisen that pose potential threats to genetic diversity: the use of reproductive technologies (RT) and a reduction in the number of bulls in breeding schemes. The expected outcome of these changes, in terms of both genetic gain and genetic diversity, is not trivial to predict. Here, we simulated 15 breeding schemes similar to those carried out in large French dairy cattle breeds; breeding schemes differed with respect to their dimensions, the intensity of RT use, and the type of RT involved. We found that intensive use of RT resulted in improved genetic gain, but deteriorated genetic diversity. Specifically, a reduction in the interval between generations through the use of ovum pick-up and in vitro fertilization (OPU-IVF) resulted in a large increase in the inbreeding rate both per year and per generation, suggesting that OPU-IVF could have severe adverse effects on genetic diversity. To achieve a given level of genetic gain, the scenarios that best maintained genetic diversity were those with a higher number of sires/bulls and a medium intensity of RT use or those with a higher number of female donors to compensate for the increased intensity of RT.

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