A comparison of the rate of genetic gain and inbreeding in open nucleus and closed flock breeding systems for sheep.

Breeding Systems ◽

Optimum Structure ◽

Sheep Breeding ◽

Group Breeding ◽

Breeding Schemes ◽

Best Linear Unbiased ◽

Open Nucleus

Open nucleus systems (ONS) have been used in sheep breeding for a number of years, usually in group breeding schemes. In the simplest form the population is divided into two tiers, the nucleus flock composed of elite individuals, while the base, which forms the majority of the population, is usually sub-divided into a number of individual flocks. Animals born in the nucleus may be selected as replacements in the base, while superior animals born in the base may become part of the breeding population of the nucleus. The optimum structure and genetic benefits of using an ONS under Australasian conditions have been extensively studied using deterministic predictions (James, 1977; Mueller and James, 1983). However, subsequent advances in genetic evaluation (e.g. the application of Best Linear Unbiased Prediction (BLUP)) and the smaller flock sizes typical in Europe, are likely to impact on the outcome and optimum structure of such systems.

A comparison of alternative nucleus breeding systems and a sire referencing scheme for sheep improvement

Animal Science ◽

10.1017/s1357729800014569 ◽

1996 ◽

Vol 62 (2) ◽

pp. 265-270 ◽

Cited By ~ 6

Author(s):

J. A. Roden

Keyword(s):

Selection Response ◽

Breeding Systems ◽

Sequential Selection ◽

Best Linear Unbiased ◽

The Mean ◽

Nucleus Breeding ◽

Open Nucleus ◽

Selection Of

AbstractStochastic simulation was used to compare selection response and rate of inbreeding in four nucleus breeding systems and a sire referencing scheme for sheep: an open nucleus system (ONS), an open nucleus system with sequential selection of the nucleus (ONS-S), a sire referencing scheme (SRS) and a dispersed open nucleus system (DONS). Selection was based on best linear unbiased prediction of breeding values for a single trait measurable on all individuals prior to selection. Selection in a population of 1200 ewes equally divided into 10 flocks was simulated over a 15-year period. The mean rate of genetic gain was proportionately about 0-15 higher in ONS-S and DONS compared with ONS and SRS. The rate of inbreeding in SRS was considerably lower and in ONS-S, considerably higher, than in the other systems. The level of prolificacy in the population did not influence the relative ranking of the breeding systems but may have implications for their optimal structure.

Practical breeding developments and future prospects

BSAP Occasional Publication ◽

10.1017/s0263967x00002019 ◽

1990 ◽

Vol 14 ◽

pp. 13-22

Author(s):

M. K. Curran

Keyword(s):

Future Prospects ◽

Population Changes ◽

Multiple Ovulation ◽

Group Breeding ◽

Breeding Schemes ◽

Best Linear Unbiased ◽

The Uk ◽

Terminal Sire

AbstractThis paper is a review of practical sheep breeding improvement schemes and techniques in the UK. Recent breed population changes in each of the broad categories of hill, longwool/crossing, longwool ewe, terminal sire and shortwool ewe breeds are outlined. Current or planned improvement programmes are reported for Welsh Mountain, Beulah, Scottish Blackface, Border Leicester, Cambridge, Friesland, Romney, Texel, Suffolk, Lleyn and Merino breeds. The techniques of genetic improvement currently available are discussed including some costs and likely genetic gains; techniques include group breeding schemes, artificial insemination, multiple ovulation and embryo transplant, best linear unbiased prediction and transgenic methods. The application of these techniques and contribution they could make to future sheep improvement are assessed.

A simulation study of open nucleus and closed nucleus breeding systems in a sheep population

Animal Science ◽

10.1017/s1357729800008213 ◽

1995 ◽

Vol 60 (1) ◽

pp. 117-124 ◽

Cited By ~ 7

Author(s):

J. A. Roden

Keyword(s):

Genetic Gain ◽

Live Weight ◽

Breeding Systems ◽

Breeding Value ◽

Sheep Population ◽

Best Linear Unbiased ◽

Nucleus Breeding ◽

Open Nucleus ◽

Selection Of

AbstractStochastic simulation was used to compare the results of alternative breeding systems in a sheep population divided into 10 flocks of 120 ewes. The breeding systems compared were selection within closed flocks (CF), a closed nucleus system (CNS), an open nucleus system (ONS) and open nucleus systems with the selection of nucleus replacements being restricted to either nucleus born males (ONSRm) or nucleus born females (ONSRf). Selection was for a best linear unbiased prediction of breeding value for lamb live weight which had a heritability of 0·17. The open nucleus breeding systems (ONS, ONSRm, ONSRf) resulted in higher rates of genetic gain, more predictable selection responses and lower rates of inbreeding than either the closed nucleus system (CNS) or selection within closed flocks (CF). Initial genetic differences between flocks resulted in higher rates of genetic gain in the nucleus breeding systems due to the use of between flock genetic variance. In the ONS system up to 25% of nucleus sires and approximately 50% of nucleus dams were born in base flocks. Nevertheless if selection of either nucleus sires or dams was restricted to nucleus born animals there was very little change in genetic gain or rate of inbreeding.

A method of using a genetic algorithm to examine the optimum structure of the Australian sheep breeding industry: open-nucleus breeding systems, MOET and AI

Australian Journal of Experimental Agriculture ◽

10.1071/ea9960249 ◽

1996 ◽

Vol 36 (3) ◽

pp. 249 ◽

Cited By ~ 7

Author(s):

B Horton

Keyword(s):

Genetic Algorithm ◽

Reproductive Rate ◽

Breeding Systems ◽

Optimum Structure ◽

Simple Method ◽

Sheep Breeding ◽

Multiple Ovulation ◽

Complex Models ◽

Australian Sheep ◽

Open Nucleus

A genetic algorithm was evaluated as a means of using a computer model to determine the optimum structure of the Australian sheep breeding industry. The model simulates an open-nucleus 3-tiered sheep breeding system to investigate the benefit of strategies such as multiple ovulation and embryo transfer (MOET) and artificial insemination (AI) in terms of both genetic improvement and dollar values. The model indicated that both MOET and non- MOET systems benefit from an open nucleus, and both could also benefit from the promotion of some ewes from the commercial flocks. However, MOET systems require a relatively large number of rams, whereas non- MOET systems should have a smaller number of rams despite the much larger number of ewes needed. Under the conditions studied here, there was only limited advantage of MOET over non-MOET schemes. The optimum structure of the MOET, non-MOET and closed systems differ substantially. A genetic algorithm is a simple method for considering a single change (such as reproductive rate, or open v. closed) that may require major changes in the industry structure to achieve the full benefits. The method could also be of value in many other situations requiring optimisation of complex models.

Optimum contribution selection using traditional best linear unbiased prediction and genomic breeding values in aquaculture breeding schemes

Journal of Animal Science ◽

10.2527/jas.2009-2731 ◽

2011 ◽

Vol 89 (3) ◽

pp. 630-638 ◽

Cited By ~ 27

Author(s):

H. M. Nielsen ◽

A. K. Sonesson ◽

T. H. E. Meuwissen

Keyword(s):

Genomic Breeding ◽

Breeding Values ◽

Breeding Schemes ◽

Best Linear Unbiased ◽

Unbiased Prediction

Correction: Weighted Genomic Best Linear Unbiased Prediction for Carcass Traits in Hanwoo Cattle. Genes 2019, 10, 1019

Genes ◽

10.3390/genes11091013 ◽

2020 ◽

Vol 11 (9) ◽

pp. 1013

Author(s):

Bryan Irvine Lopez ◽

Seung-Hwan Lee ◽

Jong-Eun Park ◽

Dong-Hyun Shin ◽

Jae-Don Oh ◽

...

Keyword(s):

Carcass Traits ◽

Best Linear Unbiased ◽

Hanwoo Cattle ◽

Unbiased Prediction

The authors wish to make the following corrections to this paper [...]

Genomic Prediction Using Alternative Strategies of Weighted Single-Step Genomic BLUP for Yearling Weight and Carcass Traits in Hanwoo Beef Cattle

Genes ◽

10.3390/genes12020266 ◽

2021 ◽

Vol 12 (2) ◽

pp. 266

Author(s):

Hossein Mehrban ◽

Masoumeh Naserkheil ◽

Deuk Hwan Lee ◽

Chungil Cho ◽

Taejeong Choi ◽

...

Keyword(s):

Quantitative Trait Loci ◽

Beef Cattle ◽

Genomic Prediction ◽

Quantitative Trait ◽

Carcass Traits ◽

Single Step ◽

Single Nucleotide ◽

Best Linear Unbiased

The weighted single-step genomic best linear unbiased prediction (GBLUP) method has been proposed to exploit information from genotyped and non-genotyped relatives, allowing the use of weights for single-nucleotide polymorphism in the construction of the genomic relationship matrix. The purpose of this study was to investigate the accuracy of genetic prediction using the following single-trait best linear unbiased prediction methods in Hanwoo beef cattle: pedigree-based (PBLUP), un-weighted (ssGBLUP), and weighted (WssGBLUP) single-step genomic methods. We also assessed the impact of alternative single and window weighting methods according to their effects on the traits of interest. The data was comprised of 15,796 phenotypic records for yearling weight (YW) and 5622 records for carcass traits (backfat thickness: BFT, carcass weight: CW, eye muscle area: EMA, and marbling score: MS). Also, the genotypic data included 6616 animals for YW and 5134 for carcass traits on the 43,950 single-nucleotide polymorphisms. The ssGBLUP showed significant improvement in genomic prediction accuracy for carcass traits (71%) and yearling weight (99%) compared to the pedigree-based method. The window weighting procedures performed better than single SNP weighting for CW (11%), EMA (11%), MS (3%), and YW (6%), whereas no gain in accuracy was observed for BFT. Besides, the improvement in accuracy between window WssGBLUP and the un-weighted method was low for BFT and MS, while for CW, EMA, and YW resulted in a gain of 22%, 15%, and 20%, respectively, which indicates the presence of relevant quantitative trait loci for these traits. These findings indicate that WssGBLUP is an appropriate method for traits with a large quantitative trait loci effect.

A method for reducing inbreeding with Best Linear Unbiased Prediction

Proceedings of the British Society of Animal Production (1972) ◽

10.1017/s030822960002362x ◽

1993 ◽

Vol 1993 ◽

pp. 33-33

Author(s):

B Grundy ◽

WG Hill

Keyword(s):

Breeding Value ◽

Best Linear Unbiased Predictor ◽

Genetic Merit ◽

Selection Decisions ◽

Best Linear Unbiased ◽

Estimated Breeding Value ◽

Commercial Environment ◽

Unbiased Prediction

An optimum way of selecting animals is through a prediction of their genetic merit (estimated breeding value, EBV), which can be achieved using a best linear unbiased predictor (BLUP) (Henderson, 1975). Selection decisions in a commercial environment, however, are rarely made solely on genetic merit but also on additional factors, an important example of which is to limit the accumulation of inbreeding. Comparison of rates of inbreeding under BLUP for a range of hentabilities highlights a trend of increasing inbreeding with decreasing heritability. It is therefore proposed that selection using a heritability which is artificially raised would yield lower rates of inbreeding than would otherwise be the case.