Utilising genetic contributions to maximise long term response to selection

1996 ◽  
Vol 1996 ◽  
pp. 115-115
Author(s):  
B Grundy ◽  
B Villanueva ◽  
J A Woolliams
Keyword(s):  
Genetic Relationships ◽  
Response To Selection ◽  
Genetic Progress ◽  
Breeding Objective ◽  
Selection Decisions ◽  
The Matrix ◽  
Estimated Breeding Values ◽  
Genetic Contributions ◽  
Term Response

The concept of long term contributions was devised by Wray and Thompson (1990) to describe the accumulation of inbreeding in a population under selection, and further developed by Woolliams and Thompson (1994) to describe genetic progress. This study describes a method to utilise these relationships for optimising schemes where the breeding objective is cumulative net response with restrictions on inbreeding. The selection decisions at a given generation can be obtained from maximising the function f(x) of accumulated gain corrected for squared contributions: f(x) = xTg-λTAx, where x is the vector of long term contributions, g is the vector of estimated breeding values, A is the matrix of genetic relationships which has not been corrected for reduced Mendelian variance with inbreeding (unlike the method of Wray and Goddard, 1994), and λ is a constant taking positive values.

Utilising genetic contributions to maximise long term response to selection

1996 ◽  
Vol 1996 ◽  
pp. 115-115
Author(s):  
B Grundy ◽  
B Villanueva ◽  
J A Woolliams
Keyword(s):  
Genetic Relationships ◽  
Response To Selection ◽  
Genetic Progress ◽  
Breeding Objective ◽  
Selection Decisions ◽  
The Matrix ◽  
Estimated Breeding Values ◽  
Genetic Contributions ◽  
Term Response

The concept of long term contributions was devised by Wray and Thompson (1990) to describe the accumulation of inbreeding in a population under selection, and further developed by Woolliams and Thompson (1994) to describe genetic progress. This study describes a method to utilise these relationships for optimising schemes where the breeding objective is cumulative net response with restrictions on inbreeding. The selection decisions at a given generation can be obtained from maximising the function f(x) of accumulated gain corrected for squared contributions: f(x) = xTg-λTAx, where x is the vector of long term contributions, g is the vector of estimated breeding values, A is the matrix of genetic relationships which has not been corrected for reduced Mendelian variance with inbreeding (unlike the method of Wray and Goddard, 1994), and λ is a constant taking positive values.

Managing genetic resources in selected and conserved populations

2004 ◽  
Vol 30 ◽  
pp. 113-132 ◽  
Author(s):  
B. Villanueva ◽  
R. Pong-Wong ◽  
J.A. Woolliams ◽  
S. Avendaño
Keyword(s):  
Genetic Resources ◽  
Genetic Relationships ◽  
Molecular Genetic ◽  
Selection Response ◽  
Pedigree Information ◽  
Genetic Progress ◽  
Breeding Populations ◽  
Expected Gain ◽  
Best Linear Unbiased ◽  
Estimated Breeding Values

AbstractManaging the rate of inbreeding (ΔF) provides a general framework for managing genetic resources in farmed breeding populations. Methods for managing ΔF have been developed over the last five years and they allow the attainment of the greatest expected genetic progress while restricting at the same time the increase in inbreeding. This is achieved by optimising the contribution that each candidate for selection must have to produce the next generation. The methods take into account all available performance and pedigree information and use Best Linear Unbiased Prediction (BLUP) estimates as a predictor of merit. Importantly, these tools give at least equal, but more often more gain than traditional selection based on truncation of BLUP estimated breeding values when compared at the same ΔF. Deterministic predictions for the expected gain obtained with optimised selection with ΔF restricted are now available. The optimisation tool can be also applied in a conservation context to minimise ΔF with restrictions to avoid loss in performance in valuable traits. Information on known quantitative trait loci or on markers linked to them can be incorporated into the optimisation process to further increase selection response. Molecular genetic information can also be incorporated into these tools to increase the precision of genetic relationships between individuals and to manage ΔF at specific positions or genome regions.

Heritability of post-mixing aggressiveness in grower-stage pigs and its relationship with production traits

2006 ◽  
Vol 82 (5) ◽  
pp. 615-620 ◽  
Author(s):  
S.P. Turner ◽  
I. M. S. White ◽  
S. Brotherstone ◽  
M. J. Farnworth ◽  
P. W. Knap ◽  
...  
Keyword(s):  
Growth Rate ◽  
Genetic Relationships ◽  
Skin Lesions ◽  
Standard Errors ◽  
Average Weight ◽  
Production Traits ◽  
Genetic Progress ◽  
Primary Producer ◽  
Additional Costs

AbstractMixing of commercial pigs frequently leads to intense aggression. Considerable phenotypic variation exists between individuals and selection against aggressiveness may offer a long-term reduction in aggression without incurring additional costs to the primary producer. The genetic contribution to aggressiveness was quantified in this study using the number of skin lesions as an indicator of involvement in aggression. A sample of 1132 pigs were mixed at an average weight of 27·9 (s.d. 4·6) kg into 96 pens on a commercial sire line nucleus unit. Post-mixing aggressiveness of pigs was assessed using the lesion score (LS) approach. Growth rate, between 27·9 and 91·9 kg, and backfat depth at 91·9 kg were recorded for a subsample of 658 pigs. With a pedigree file of 1947 animals, a heritability of 0·22 was estimated for the LS trait. No significant genetic or phenotypic correlations were found between LS and growth rate or backfat depth, but standard errors of estimates were large. The response to selection, when all selection pressure was placed on the LS trait, was a 25% reduction in LS per generation. It is therefore technically possible to select for a reduced LS without substantially inhibiting genetic progress in growth rate or backfat depth through antagonistic genetic relationships.

scholarly journals Long-Term Evaluation of Breeding Scheme Alternatives for Endangered Honeybee Subspecies

Insects ◽  
2020 ◽  
Vol 11 (7) ◽  
pp. 404 ◽  
Author(s):  
Manuel Plate ◽  
Richard Bernstein ◽  
Andreas Hoppe ◽  
Kaspar Bienefeld
Keyword(s):  
Small Populations ◽  
Genetic Progress ◽  
Selection Decisions ◽  
Population Sizes ◽  
Term Evaluation ◽  
Honeybee Subspecies ◽  
Genetic Evaluations ◽  
Genetic Structures ◽  
Modern Breeding

Modern breeding structures are emerging for European honeybee populations. However, while genetic evaluations of honeybees are becoming increasingly well understood, little is known about how selection decisions shape the populations’ genetic structures. We performed simulations evaluating 100 different selection schemes, defined by selection rates for dams and sires, in populations of 200, 500, or 1000 colonies per year and considering four different quantitative traits, reflecting different genetic parameters and numbers of influential loci. Focusing on sustainability, we evaluated genetic progress over 100 years and related it to inbreeding developments. While all populations allowed for sustainable breeding with generational inbreeding rates below 1% per generation, optimal selection rates differed and sustainable selection was harder to achieve in smaller populations and for stronger negative correlations of maternal and direct effects in the selection trait. In small populations, a third or a fourth of all candidate queens should be selected as dams, whereas this number declined to a sixth for larger population sizes. Furthermore, our simulations indicated that, particularly in small populations, as many sires as possible should be provided. We conclude that carefully applied breeding provides good prospects for currently endangered honeybee subspecies, since sustainable genetic progress improves their attractiveness to beekeepers.

Strategies to maximise the allelic diversity maintained in small conserved populations

2004 ◽  
Vol 30 ◽  
pp. 324-326
Author(s):  
J. Fernández ◽  
M.A. Toro ◽  
A. Caballero
Keyword(s):  
Environmental Changes ◽  
Gene Diversity ◽  
Allelic Diversity ◽  
Optimal Strategies ◽  
Small Population ◽  
Response To Selection ◽  
Expected Heterozygosity ◽  
Or Gene ◽  
Term Response

One of the main objectives in conservation programmes is to maintain the highest levels of genetic variability, for the population to be able to face future environmental changes and to assure long-term response to selection, either natural or artificial (Oldenbroek, 1999, Barker, 2001). The classical measure of genetic diversity is the expected heterozygosity, or gene diversity (GD), but allelic diversity (AD), or the number of different alleles per locus, also has evolutionary importance. Most optimal strategies for conservation have aimed to maximise GD (e.g. Caballero and Toro 2000), but AD has received much less attention. The objective of the present study is to test the efficiency of the maintenance of allelic diversity of strategies based either on the allelic diversity itself or on the expected heterozygosity in a small population, using information from molecular markers.

SELECTION LIMITS: HAVE THEY BEEN REACHED WITH THE DAIRY COW?

1984 ◽  
Vol 64 (2) ◽  
pp. 207-215 ◽  
Author(s):  
B. W. KENNEDY
Keyword(s):  
Genetic Variability ◽  
Dairy Cattle ◽  
Milk Production ◽  
Milk Yield ◽  
Genetic Relationships ◽  
Genetic Progress ◽  
Genetic Theory ◽  
Term Selection ◽  
High Production

Genetic theory suggests that at some point genetic progress for milk production might plateau either through exhaustion of genetic variability or through development of antagonistic genetic relationships between milk yield and components of fitness. Although there have been no long-term selection experiments with dairy cattle, empirical evidence from field data indicates that selection limits for increased milk production have not been reached nor will they be in the foreseeable future. The rate of genetic improvement in milk yield is accelerating. Rather than witnessing a decline in genetic variability, as genetic theory would indicate, we seem to be experiencing an increase in genetic variability as production levels increase with time which is likely due to improved management allowing for greater expression of genetic variability. There is some evidence of genetic antagonisms between milk yield and fitness traits, fertility and health measures in particular, and this could impose a limit to selection for increased milk production. The solution to this problem is probably through improved management of high producing cows, to reduce stress associated with high production. Key words: Dairy cattle, selection, genetic variation

scholarly journals The effect of gene interactions on the long-term response to selection

2016 ◽  
Vol 113 (16) ◽  
pp. 4422-4427 ◽  
Author(s):  
Tiago Paixão ◽  
Nicholas H. Barton
Keyword(s):  
Additive Genetic Variance ◽  
Evolutionary Process ◽  
Complex Trait ◽  
Gene Interactions ◽  
Response To Selection ◽  
Long Term Effects ◽  
Genotypic Variance ◽  
Total Response ◽  
Term Response

The role of gene interactions in the evolutionary process has long been controversial. Although some argue that they are not of importance, because most variation is additive, others claim that their effect in the long term can be substantial. Here, we focus on the long-term effects of genetic interactions under directional selection assuming no mutation or dominance, and that epistasis is symmetrical overall. We ask by how much the mean of a complex trait can be increased by selection and analyze two extreme regimes, in which either drift or selection dominate the dynamics of allele frequencies. In both scenarios, epistatic interactions affect the long-term response to selection by modulating the additive genetic variance. When drift dominates, we extend Robertson’s [Robertson A (1960) Proc R Soc Lond B Biol Sci 153(951):234−249] argument to show that, for any form of epistasis, the total response of a haploid population is proportional to the initial total genotypic variance. In contrast, the total response of a diploid population is increased by epistasis, for a given initial genotypic variance. When selection dominates, we show that the total selection response can only be increased by epistasis when some initially deleterious alleles become favored as the genetic background changes. We find a simple approximation for this effect and show that, in this regime, it is the structure of the genotype−phenotype map that matters and not the variance components of the population.

scholarly journals Genomic selection in livestock populations

2010 ◽  
Vol 92 (5-6) ◽  
pp. 413-421 ◽  
Author(s):  
MICHAEL E. GODDARD ◽  
BEN J. HAYES ◽  
THEO H. E. MEUWISSEN
Keyword(s):  
Genomic Selection ◽  
Nucleotide Polymorphism ◽  
Single Nucleotide ◽  
Factors Affecting ◽  
Snp Data ◽  
Genomic Tools ◽  
Breeding Programmes ◽  
Estimated Breeding Values ◽  
Term Response

SummaryMost traits of economic importance in livestock are either quantitative or complex. Despite considerable efforts, there has been only limited success in identifying the polymorphisms that cause variation in these traits. Nevertheless, selection based on estimated breeding values (BVs), calculated from data on phenotypic performance and pedigree has been very successful. Genomic tools, such as single nucleotide polymorphism (SNP) chips, have led to a new method of selection called ‘genomic selection’ in which dense SNP genotypes covering the genome are used to predict the BV. In this review we consider the statistical methodology for estimating BVs from SNP data, factors affecting the accuracy, the long-term response to genomic selection and the design of breeding programmes including the management of inbreeding.

scholarly journals Increasing long-term response to selection

1994 ◽  
Vol 26 (5) ◽  
pp. 431 ◽  
Author(s):  
NR Wray ◽  
ME Goddard
Keyword(s):  
Response To Selection ◽  
Term Response
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