A recursive method for computing expected kinship and inbreeding in complex and dynamic breeding programmes

Sitzenstock, F.; Ytournel, F.; Simianer, Henner

doi:10.1111/j.1439-0388.2012.01010.x

Cited by 5 publications

(8 citation statements)

References 31 publications

(42 reference statements)

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“…As a third example, we consider a commercial layer breeding programme with a four‐line cross as described in Sitzenstock et al. (2013). The scheme for one breeding cycle in line A, one of the four lines, is given in Figure 3.…”

Section: Resultsmentioning

confidence: 99%

A unifying concept of animal breeding programmes

Simianer

Büttgen

Ganesan

et al. 2021

J Animal Breeding Genetics

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Modern animal breeding programmes are constantly evolving with advances in breeding theory, biotechnology and genetics. Surprisingly, there seems to be no generally accepted succinct definition of what exactly a breeding programme is, neither is there a unified language to describe breeding programmes in a comprehensive, unambiguous and reproducible way. In this work, we try to fill this gap by suggesting a general definition of breeding programmes that also pertains to cases where genetic progress is not achieved through selection, but, for example, through transgenic technologies, or the aim is not to generate genetic progress, but, for example, to maintain genetic diversity. The key idea of the underlying concept is to represent a breeding programme in modular form as a directed graph that is composed of nodes and edges, where nodes represent cohorts of breeding units, usually individuals, and edges represent breeding activities, like “selection” or “reproduction.” We claim, that by defining a comprehensive set of nodes and edges, it is possible to represent any breeding programme of arbitrary complexity by such a graph, which thus comprises a full description of the breeding programme. This concept is implemented in a web‐based tool (MoBPSweb, available at http://www.mobps.de) and has a link to the R‐package MoBPS (Modular Breeding Program Simulator) to simulate the described breeding programmes. The approach is illustrated by showcasing three different breeding programmes of increasing complexity. The concept allows a formal description of breeding programmes, which is requested, for example, in legal regulations of the European Union, but so far cannot be provided in a standardized format. In the discussion, we point out potential limitations of the concept and argue that the general approach can be easily extended to account for novel breeding technologies, to breeding of crops or experimental species, but also to modelling diversity dynamics in natural populations.

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Section: Resultsmentioning

confidence: 99%

A unifying concept of animal breeding programmes

Simianer

Büttgen

Ganesan

et al. 2021

J Animal Breeding Genetics

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“…We apply a deterministic method (Sitzenstock et al . ) to calculate the average kinship and following from that the effective population size on the basis of the gene flow theory (Hill ). Each selection group is subdivided in age classes, so‐called cohorts, with the information: (i) number of animals, (ii) if the age class arises from reproduction or ageing and (iii) the paternal (resp.…”

Section: Methodsmentioning

confidence: 99%

“…The average kinship is the probability that, in a selection group or between two selection groups, two randomly chosen alleles are identical by descent at the same locus (Malé cot 1948). We apply a deterministic method (Sitzenstock et al 2012) to calculate the average kinship and following from that the effective population size on the basis of the gene flow theory (Hill 1974). Each selection group is subdivided in age classes, so-called cohorts, with the information: (i) number of animals, (ii) if the age class arises from reproduction or ageing and (iii) the paternal (resp.…”

Section: Average Kinship and Effective Population Sizementioning

confidence: 99%

The potential of embryo transfer in a German horse‐breeding programme

Sitzenstock

Rathke

Ytournel

et al. 2012

J Animal Breeding Genetics

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A reference horse-breeding programme with 13500 foals each year was modelled with ZPLAN+. This new software for the optimization of the structures in breeding programmes is based on ZPLAN. In two scenarios, the implementation of a rigorous selection of mares was implemented. In scenario I, the mare performance test was the point of selection, while in scenario II, further information on 20 competitions in two more years is available. These selected mares were used for embryo transfer (ET), partly in combination with multiple ovulation (MOET). The selection intensity and the number of foals out of (MO)ET were varied in both scenarios. It was expected that 250, 500 and 1000 mares are available for selecting 20, 50, 100 or 200 donor mares each year. The number of foals out of (MO)ET was varied between one and six foals per donor mare and year. Donor mares were used for ET for 4 years. It became clear that with high selection intensities of donor mares and high reproduction rates of them, the yearly genetic gain in a horse-breeding programme could increase over a large range. In scenario II, the additional information on 20 competitions increased the accuracy of the selection index to 0.85. With 200 selected donor mares of 1000 available mares and six foals per year, the genetic gain could almost be doubled compared to the reference scenario. The implementation of ET and a related higher usage of few selected mares entails rising costs and a reduction in the genetic variance. In the most extreme MOET scenario, the effective population size was reduced by 19% relative to the reference scenario. Only if the increase in genetic gain can be converted into higher return for the breeders, the implementation of (MO)ET schemes is a realistic and sensible option for horse-breeding programmes.

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“…As a second example, we consider a commercial layer breeding program with a four-line cross as described in Sitzenstock et al (2013). The scheme for one breeding cycle in line A, one of the four lines, is given in Figure 3.…”

Section: Commercial Layer Breeding Programmentioning

confidence: 99%

“…Finally, a formal breeding program description can be used as input for a software to simulate breeding programs. In fact, the JSON file to be exported from MoBPSweb (Pook et al 2020a) can be used as an input parameter file in the R-package MoBPS Breeding scheme for line A of a four-line cross in a commercial layer breeding program as described in Sitzenstock et al (2013). Details on the attributes of all nodes and edges can be found in Supplementary File S3.…”

Section: Commercial Layer Breeding Programmentioning

confidence: 99%

A unifying concept of animal breeding programs

Simianer¹,

Ganesan²,

Buettgen³

et al. 2020

Preprint

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Modern animal breeding programs are constantly evolving with advances in breeding theory, biotechnology and genetics. Surprisingly, there seems to be no generally accepted succinct definition of what exactly a breeding program is, neither is there a unified language to describe breeding programs in a comprehensive, unambiguous and reproducible way. In this work, we try to fill this gap by suggesting a general definition of breeding programs that also pertains to cases where genetic progress is not achieved through selection, but e.g. through transgenic technologies, or the aim is not to generate genetic progress, but e.g. to maintain genetic diversity. The key idea of the underlying concept is to represent a breeding program in modular form as a directed graph that is composed of nodes and edges, where nodes represent cohorts of breeding units, usually individuals, and edges represent breeding activities, like 'selection' or 'reproduction'. We claim, that by defining a comprehensive set of nodes and edges it is possible to represent any breeding program of arbitrary complexity by such a graph, which thus comprises a full description of the breeding program. This concept is implemented in a web-based tool (MoBPSweb, available at www.mobps.de) which is described in a companion paper, and has a link to the R-package MoBPS (Modular Breeding Program Simulator) to simulate the described breeding programs. The approach is illustrated by showcasing three different breeding programs of increasing complexity. Finally, potential limitations of the concept are indicated and extensions to other fields, like plant breeding, are discussed.

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A recursive method for computing expected kinship and inbreeding in complex and dynamic breeding programmes

Cited by 5 publications

References 31 publications

A unifying concept of animal breeding programmes

A unifying concept of animal breeding programmes

The potential of embryo transfer in a German horse‐breeding programme

A unifying concept of animal breeding programs

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