Animal Science White Papers, Technical Reports, & Animal Science Fact Sheets
2015 Breeding strategies and programmes Peter Amer
Daniel Allain
Santiago Avendano
Manuel Baselga
Paul Boettcher
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Recommended Citation Amer, Peter; Allain, Daniel; Avendano, Santiago; Baselga, Manuel; Boettcher, Paul; Dürr, João; Garreau, Hervé; Gootwine, Elisha; Gutierrez, Gustavo; Knap, Pieter; Manfredi, Eduardo; Olori, Victor; Preisinger, Rudolf; Serradilla, Juan Manuel; Piles, Miriam; Santos, Bruno; and Stalder, Kenneth, "Breeding strategies and programmes" (2015). Animal Science White Papers, Technical Reports, & Fact Sheets. 6. https://lib.dr.iastate.edu/ans_whitepapers/6
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Abstract This section serves as an update of the overview of the state of the art in genetic improvement methods presented in the first report on The tS ate of the World’s Animal Genetic Resources for Food and Agriculture (first SoW-AnGR) (FAO, 2007a).1 The importance of appropriate breeding strategies and programmes is highlighted throughout the Global Plan of Action for Animal Genetic Resources (FAO, 2007b), particularly in Strategic Priority Area 2, Sustainable Use and Development. The am terial presented in the first SoW-AnGR included an overview of the “context for genetic improvement”, which described both the factors influencing the objectives of breeding programmes (market demands, wider societal concerns about the nature and impacts of livestock production, the need to provide animals suitable for a diverse range of production environments, growing recognition of the importance of maintaining genetic diversity in livestock populations, etc.) and the latest scientific nda technological developments in the field. This was followed by a description of the various activities or “elements” that make up a breeding programme and then by a review of the current state of breeding programmes by production system (high input vs. low input) and by species. Much of this material remains relevant. While the livestock sector is continuously evolving (see Part 2), the challenges that breeding programmes have to contend with remain broadly similar to those that existed at the time the first SoW-AnGR was prepared (2005/2006). Similarly, the basic constituent elements of a typical breeding programme have not changed.
Disciplines Agriculture | Animal Sciences | Genetics and Genomics | Molecular Genetics
Comments This report is published as FAO. 2015. Part 4: THE STATE OF THE ART, Section C: Breeding strategies and programmes In: The eS cond Report on the State of the World’s Animal Genetic Resources for Food and Agriculture, edited by B.D. Scherf & D. Pilling. FAO Commission on Genetic Resources for Food and Agriculture Assessments. Rome. Posted with permission.
Authors Peter Amer, Daniel Allain, Santiago Avendano, Manuel Baselga, Paul Boettcher, João Dürr, Hervé Garreau, Elisha Gootwine, Gustavo Gutierrez, Pieter Knap, Eduardo Manfredi, Victor Olori, Rudolf Preisinger, Juan Manuel Serradilla, Miriam Piles, Bruno Santos, and Kenneth Stalder
This report is available at Iowa State University Digital Repository: https://lib.dr.iastate.edu/ans_whitepapers/6 Breeding strategies and programmes c
Section C Breeding strategies and programmes
1 Introduction the basic constituent elements of a typical breed- ing programme have not changed. This section serves as an update of the overview This update largely follows the same structure of the state of the art in genetic improvement as that described above for the first SoW-AnGR. methods presented in the first report on The State Emphasis is given to recent developments, but of the World’s Animal Genetic Resources for Food each subsection aims to provide sufficient back- and Agriculture (first SoW-AnGR) (FAO, 2007a).1 ground information (where relevant, a short The importance of appropriate breeding strategies recapitulation of the material presented in and programmes is highlighted throughout the the first report) to make it comprehensible, in Global Plan of Action for Animal Genetic Resources standalone form, to the non-specialist reader. (FAO, 2007b), particularly in Strategic Priority High-input systems are again treated separately Area 2, Sustainable Use and Development. The from low-input systems. These terms can be material presented in the first SoW-AnGR included defined in various ways, but for the purposes an overview of the “context for genetic improve- of this section, “high-input systems” is used to ment”, which described both the factors influ- refer to systems in which external inputs such encing the objectives of breeding programmes as supplementary feeds, veterinary medicines (market demands, wider societal concerns about and advanced breeding and reproductive tech- the nature and impacts of livestock production, nologies are relatively easily obtainable and the need to provide animals suitable for a diverse widely used (precise levels of use will depend range of production environments, growing rec- on the particular circumstances) and “low- ognition of the importance of maintaining genetic input systems” to systems where the use of such diversity in livestock populations, etc.) and the technologies is more limited, often because of latest scientific and technological developments factors such as inaccessibility, unaffordability, in the field. This was followed by a description lack of relevant knowledge or lack of organiz- of the various activities or “elements” that make ational capacity. Departures from the structure up a breeding programme and then by a review of the first SoW-AnGR include separate sub- of the current state of breeding programmes by sections on sheep and goat breeding in high- production system (high input vs. low input) and input systems and the addition of a subsection by species. Much of this material remains relevant. on rabbit breeding in high-input systems. The While the livestock sector is continuously evolving issue of breeding in the context of conservation (see Part 2), the challenges that breeding pro- programmes is addressed in Part 4 Section D. As grammes have to contend with remain broadly indicated above, the broad context for breeding similar to those that existed at the time the first programmes (trends in the livestock sector) is SoW-AnGR was prepared (2005/2006). Similarly, addressed in Part 2.
1 FAO, 2007a, Part 4 Section D (pages 381–427).
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2 Scientific and technological Many breeding organizations, particularly in advances the dairy cattle, pig and chicken industries, have long been using mate selection software to mini- mize the effects of inbreeding in their breeding 2.1 Quantitative genetics populations (Weigel and Lin, 2000). Over recent Since the time the first SoW-AnGR was prepared years, the various algorithms have been made (2005/2006), there have been few technological more efficient (e.g. Kinghorn, 2011) and their advances in the field of quantitative genetics. value in the control of genetic defects has been The standard method for estimating breeding recognized (Van Eenennaam and Kinghorn, values and ranking animals according to their 2014). Not surprisingly given the increasing use genetic merit continues to be traditional BLUP of genomic information in breeding programmes (best linear unbiased prediction). This method (see Subsection 2.3 and Subsection 4), soft- uses phenotypic information on animals and their ware for managing inbreeding in the context of relatives to predict the genetic potential of each increasingly available genomic data has also been animal. Existing tools for controlling inbreeding developed (e.g. Schierenbeck et al., 2011). in herds and populations (e.g. Meuwissen, 1997) have become more widely utilized. From a given 2.2 Molecular genetics set of selection candidates, these tools allow Knowledge of the biology of traits is being the selection of a group of parents in which the enhanced by the availability of an ever increasing genetic merit is maximized while a measure of amount of genetic information, much of it genetic variation (e.g. the average coefficient of unavailable only a few years ago. Genotypes can coancestry) is constrained. now be obtained much faster and at a lower
Box 4C1 Reduction of genetic variability and its consequences in cattle breeds
Intensive selection may reduce the genetic diversity of Low Ne does not yet seem to have affected the livestock populations even if the number of animals selection potential of widely used transboundary remains high. A study of Holstein, Jersey and Angus breeds. However, other effects – related to the spread cattle (very widely used international transboundary of inherited disorders or to a reduction in fitness cattle breeds) undertaken by de Roos et al. (2008) associated with inbreeding depression – have been used single nucleotide polymorphism (SNP) markers observed. A recent study estimated that in Holstein to investigate linkage disequilibrium (non-random and Jersey cattle a 1 percent increase in inbreeding, association between alleles). Information on linkage as indicated by pedigree or genomic information, was disequilibrium can be used to trace the evolution of associated with a decrease of 0.4‑0.6 percent of the
effective population size (Ne) over past generations. phenotypic mean for milk, fat and protein yields and
Several historical episodes of reduction in Ne were an increase of 0.02‑0.05 percent for calving intervals. identified, including one 10 000 generations ago – Inbreeding depression can be managed either by corresponding to the time of cattle domestication minimizing overall inbreeding within the breeding
– during which Ne fell to a few thousands. Another scheme or by targeting specific regions of the genome reduction occurred over recent generations, during associated with inbreeding depression. which time effective population sizes fell to close to 100 as a result of the introduction of new breeding Based on de Roos et al. (2008) and Pryce et al. (2014). techniques. See also Part 1 Section F Table 1F1.
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cost than they could just five years ago. A simple was judged to be profitable in dairy cattle even biological sample (usually blood, hair, tissue or with only moderate linkage between the marker semen) from an individual animal can be used to and the causative gene. However, for species determine its entire DNA sequence. Of particular lacking the complex system of artificial insemin- interest are the areas where the sequence differs, ation (AI) and progeny testing that is in place for at a single point, from that of the common ref- dairy cattle, MAS was considered to be a profita- erence sequence for the respective species. Such ble strategy only in the case of highly informat- differences are referred to as single nucleotide ive markers located very close to the causative loci polymorphisms (SNPs). Combined with enhanced (Boichard et al., 2006). computational capacity, these developments mean In recent years, the availability of genomic that researchers can analyse the genome for more information has greatly increased and continues complex traits than ever previously thought poss- to accumulate at a rapid pace. Cost-efficient DNA ible. It is likely that genotyping costs will continue sequencing methods have facilitated the devel- to decline and that computational capacity will opment of assays that can provide genotypes for continue to improve – and that therefore the use tens to hundreds of thousands of SNPs for only a of these tools will become ever more widespread few tens or hundreds of dollars per animal. Thus, in the coming years (see Part 4 Section B). nearly all genes with effects on phenotypic traits can be marked by a SNP. It has become possible 2.3 Gene-based selection to apply genome-wide approaches that are more As knowledge of molecular genetics and trait comprehensive than simple MAS based on a few biology has improved, it has been possible to markers. improve breeding programmes through the Researchers have established ways of incorp- use of various types of gene-based selection. orating information on the genetic make-up of Most traits of economic importance in livestock individual animals into breeding programmes are so-called quantitative traits, the pheno- for complex traits influenced by many genes, types of which are the result of the combined a process known as genome-enabled select- small effects of many genes. In some instances, ion. There are two general approaches to this: however, individual genes can have substantial genome-enhanced BLUP (Garrick, 2007; Van- effects. Molecular genetics can be used to detect Raden, 2007; Zhang et al., 2007) and SNP-effect the presence of these genes and this inform- models. ation can be used in concert with phenotypic Whereas genetic evaluations based on tradi- information from animals and their relatives tional BLUP utilize average relationships based in a process generally referred to as marker- on animals’ pedigrees, genome-enhanced assisted selection (MAS), where “marker” refers BLUP utilizes the actual genomic relationship to a polymorphic locus either directly responsible between the animals. For example, with tradi- for the genetic differences observed or “linked” tional BLUP, two animals with the same sire are to the causative locus by being situated nearby assumed to have exactly one-quarter of their on the same chromosome. Most commonly, MAS genes in common. In reality, this proportion is is applied using linked loci rather than the caus- not a fixed quantity, but rather ranges from zero ative gene, although some accuracy is lost by to one-half. Genome-enhanced BLUP allows doing this. this proportion to be estimated more precisely. At the time the first SoW-AnGR was prepared The approach can be extended – via a method (2005/2006), several countries had incorporated known as single-step genome-enhanced BLUP – MAS into their national breeding programmes for to incorporate phenotypes from individuals that dairy cattle (e.g. Liu et al., 2004; Boichard et al., are not genotyped (Aguilar et al., 2010; Chris- 2006) and other species. The application of MAS tensen and Lund, 2010).
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Simple genome-enhanced BLUP is based on low-density and high-density genotyping has the assumption that all regions of the genome been shown to be approximately 0.95 (Hickey et have an equal influence on the phenotype being al., 2012). evaluated. Although this assumption facilitates If genomic information is used alone (i.e. is the statistical analysis and generally yields satis- based exclusively on historical phenotypic data), factory results, our knowledge of biology tells the genetic improvement resulting from selection us that this assumption is not strictly true; only may not exceed that achieved using traditional certain genes have actual physiological effects BLUP with phenotypes for selection candidates on a given trait. Computational methods such as (Dekkers, 2007; Muir, 2007). Moreover, because Bayesian regression allow differential weighting of the effects of selection and recombination, the of specific genomic regions that have a particu- accuracy of genomic estimated breeding values larly large statistical association with the trait of (GEBVs) decreases as the number of generations interest, in other words where findings are con- from the training population increases. All avail- sistent with the presence of a quantitative trait able phenotypic and genomic information should locus (QTL) affecting the trait. be incorporated into GEBVs to ensure that they In SNP effect models, effects on phenotype are are as accurate as possible. simultaneously estimated for all genotyped SNPs Studies have attempted to predict GEBVs for in a so-called “training population” for which full one breed based on the phenotypes of a train- phenotypic information is available (Erbe et al., ing population belonging to another breed. The 2010). The output is referred to as a “SNP-key” value of this approach has been found to be small and can be used to predict the breeding value or non-existent (Hayes et al., 2009a; Erbe et al., of animals that are genotyped, but for which no 2012). In numerically small breeds that have ade- phenotypic data have been recorded. Such pre- quate phenotyping, multibreed genomic selection dicted breeding values are obtained by summing may, in future, prove to be an interesting option the estimated effects at each genotyped SNP. To (Hozé et al., 2014), especially for breeds with a incorporate information from individuals that shared genetic history. However, in developing have not been genotyped, the resulting genomic countries, a lack of routinely recorded reference prediction is “blended” with an estimate of populations is likely to be a significant barrier breeding value derived using traditional BLUP. for the foreseeable future (see Subsection 5.3). This blended estimate is used as the final genetic Development of genome-enabled selection strat- index value for each animal. egies that can alleviate the constraints imposed Another distinction to note is that between by low population sizes and limited pheno- high- and low-density genotyping. High-density typic data is therefore a priority. genotyping involves analysing 50 000 to 1 million Genome-enabled selection can be expected SNPs. Low-density genotyping only analyses a to improve the accuracy of EBVs, particularly for few hundred to a few thousand SNPs. The cost young animals for which phenotypic data are not of high-density genotyping is more than twice available (Meuwissen et al., 2001). Increasing EBV that of low-density genotyping. Costs can be accuracy proportionally increases the expected reduced via a process known as “imputation”, in rate of genetic gain. Having more accurate EBVs which high-density genotyping is conducted only at a younger age allows selection decisions to be in a base population of animals that have many made earlier, which reduces the generation inter- descendants (usually AI sires) and the inform- val and increases genetic gain per unit of time. ation obtained is then used to develop a system In general, genome-enabled selection is bene- for inferring or deducing the missing inform- ficial because it can be used to increase the accu- ation for animals that have been subject only to racy of the EBVs of animals without direct pheno- low-density genotyping. The correlation between typic measurements. This general rule applies not
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only with respect to young animals, but also to sex- been identified in the Holstein breed. The defect, limited traits, traits that are difficult or impossible to known as brachyspina syndrome, is caused by a measure in the live animal, traits measured at the 3.3 kb (kilo base pair) deletion in the so-called end of an animal’s productive life and as yet un- FANCI gene (Charlier et al., 2012). Despite the determined traits that are not currently measured low incidence of brachyspina syndrome (thought but may become important in the future. In the to be less than 1 in 100 000), the frequency of latter instance, data collected in the future could the carrier state may be greater than 7 percent. be used to obtain EBVs for animals that are no The large discrepancy between the low incid- longer living but from which cryopreserved semen ence and relatively large percentage of carr- or other germplasm is available. Genetic material iers is accounted for by the fact that almost all from these animals could thus potentially be used homozygous mutant calves die during pregnancy. to enhance the trait in the in vivo population. Identifying this mutation would not have been Genome-enabled selection has been imple- possible without state of the art genomic tools. mented in some animal breeding programmes, Producers can now select against animals carrying including programmes for pigs and dairy cattle. a single copy of the gene and thereby improve In pigs, generation intervals are already low, and fertility in the Holstein breed. hence the greatest effect of genome-enabled Arachnomelia is a monogenic recessive defect selection is on the accuracy of selection for traits affecting skeletal development in cattle. The caus- that are difficult to measure or measured late in ative mutation, mapped to chromosome 5, was life, such as disease resistance (difficult to define identified using array-based sequence capture and and measure systematically), feed efficiency parallel sequencing technologies (Drögemüller et (expensive to measure directly) and longevity al., 2010), state of the art genomic tools at the (sow longevity is a sex-limited trait that is not time. A healthy, partially inbred cow known to recorded until the animal is culled from the herd). be carrying one copy of the mutation was re-se- In addition to quantitative traits (and arguably quenced and a single heterozygous position was to an even greater degree) the use of genomic identified. As in the case of brachyspina syndrome, information has increased our ability to manage homozygous recessive offspring die before birth, Mendelian traits, i.e. those traits controlled by which negatively affects fertility. Again, animals a single or small number of genes. In particular, carrying the gene can be selected against in order genomic approaches have been used to identify to improve the fertility of the population. causative mutations or genomic regions associ- Genomic information can also be utilized to ated with deleterious recessive traits, and genetic correct pedigree errors (Seroussi et al., 2013) markers have been developed to help eliminate and reconstruct pedigrees when parentage data these genetic defects or attempt to fix beneficial have not been recorded (Kirkpatrick et al., 2011). traits within a population. Using genomic information in this way not only Deleterious recessive traits are often character- increases the accuracy of genome-enhanced BLUP ized by a completely homozygous chromosomal (Munoz et al., 2014), but can also improve trad- region that includes the mutation responsible itional BLUP EBVs. Correcting pedigree errors for the defect and flanking regions on either allows more accurate understanding of the true side of it. Such completely homozygous regions relationships among individuals in the herd. This can be relatively simply detected by sequencing is important when establishing contemporary or genotyping a small group of affected animals groups to estimate breeding values. (even as few as ten) and comparing their geno- types to those of unaffected animals (Charlier 2.4 Reproductive technology et al., 2008). For example, in dairy cattle, a rare The state of the art in the use of reproductive recessive genetic defect affecting cow fertility has technologies has not changed greatly in recent
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Box 4C2 Genetically modified animals in agriculture
Technologies related to genetic modification (GM) gene influences multiple unrelated phenotypes) are a have advanced significantly in recent years. Classical possibility. It also has to be borne in mind that genetic gene transfer techniques have been complemented progress often involves a multiplicity of genes and that by new tools such as genome editing, a technique in such cases transgenesis is of little interest. that allows the identification and modification (small In a large majority of cases, the development of GM insertions or deletions) of a specific DNA sequence animals for potential use in food production is only instead of the insertion of a foreign DNA sequence at the research stage. A few cases are close to final into the cell (Carlson et al., 2013). approval. As yet, no GM animals have been approved Many transgenic animals have been developed, for commercial use in food production. both for biomedical purposes (production of There are still many unresolved ethical issues biomolecules, xenotransplantation, medical models, related to the use and development of GM animals, etc.) and for potential use in agriculture, including including concerns related to the invasiveness of in the improvement of economically important traits procedures and their effects on welfare and health such as growth rate, wool growth, feed conversion, and those related to intellectual property issues. milk composition, meat quality, disease resistance Attitudes towards GM animals vary from country to and survival. One example is the development of a country. In Europe, for example, the development of transgenic chicken expressing a short-hairpin RNA (an GM animals is subject to many restrictions. However, RNA sequence whose structure can be used to silence some developing countries have adopted a more the expression of specific genes) that interferes with permissive approach. For instance, Argentina and H5N1 propagation and thereby confers resistance to China have invested massively in the development of avian influenza (Lyall et al., 2011). GM animals for food production. Such animals may In comparison to conventional breeding, transgenic play a growing role in the coming years. The extent strategies may allow faster introduction of new alleles to which this occurs is likely to depend on consumer and genes of interest. However, the production of attitudes to the use of GM technology. GM animals is labour intensive and costly. Moreover, unforeseen negative pleiotropic side effects (when a For more information see Forabosco et al., 2013; Jonas et al., 2014.
years, at least in terms of application in the field. in some production systems young animals of One area of advancement has been increased the undesired sex often suffer from neglect, the commercial use of semen sexing, predomi- use of sexed semen can also indirectly enhance nantly in cattle and particularly in dairy cattle animal welfare. (see Boxes 3E6 and 3E7 in Part 3 Section E). This Challenges associated with the use of sexed process involves the use of a molecular biology semen include a slight decline in conception rate technology known as flow cytometry to sort X (a fall to 80 or 85 percent of the rate obtained and Y sperm cells (Johnson and Welch, 1999). The using conventional semen) and the fact that obvious advantage is that sexed semen can be sexed semen is not available from all potential used to obtain offspring of the desired sex (more sires (Van Doormaal, 2010). These challenges than 90 percent accuracy can be achieved). This are likely to be overcome as more experience is allows the rate of genetic improvement to be gained in the use of sexed semen and as compa- increased, as selection intensity can be increased nies make sexed semen routinely available for all and the generation interval shortened. Given that sires. Another challenge is that semen sexing does
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not work well in all species. In cattle, for example, transfer of genes across species, it may also raise overall semen and sperm volumes are low and fewer ethical questions. Research on this technol- the technology works well. Pigs, however, have ogy is increasing and has the potential to have a relatively large semen and sperm volumes, which significant effect on animal production and the means that a lot of time (up to a day per sample) management of AnGR (see Box 4C2). is needed to sort a single semen collection into X and Y sperm cells. To enable widespread use of semen sexing in this species, flow cytometry tech- 3 The elements of a breeding nology will need to be improved so as to allow programme sorting to be done much more quickly, as many commercial boar studs collect semen from as Genetic improvement strategies fall into three many as 100 boars in a day. main categories: selection between breeds; select- Reproductive technologies targeting the female ion within breeds or lines; and cross-breeding. animal (multiple ovulation, embryo transfer, in vitro The choice of which strategy to pursue will fertilization and cloning) have been available for depend on the characteristics of the production most major livestock species for some time (all had system and of the types of animal available (i.e. already been developed at the time the first SoW- already present in the local area or potentially AnGR was prepared – 2005/2006). Active research introduced). To reduce the risk of costly failures, into these technologies continues to improve their any options under consideration need to be thor- success rates and their efficiencies, hence decreas- oughly assessed. Detailed advice on planning a ing their costs. Nevertheless, cost remains a major breeding strategy is provided in the FAO guide- constraint to their more widespread use. Genomic lines Breeding strategies for sustainable manage- developments could, however, help change this. ment of animal genetic resources (FAO, 2010). As discussed above, genome-enabled BLUP and All within-breed selection programmes (straight- related approaches have increased the accuracies breeding programmes) have a number of common of EBVs. In particular, the EBVs of female animals, elements. Setting up a breeding programme especially young females, have become more accu- involves defining a breeding goal and the design rate. This improved accuracy has increased the of a scheme that is able to deliver genetic progress monetary value of the best females (Pryce et al., in line with this goal. This requires, inter alia, the 2012). In theory, this increases the expected return identification of selection criteria, recording of on investments in reproductive technologies that animals’ performances and pedigrees, genetic eval- increase the number of offspring per female. uation, selection and mating, progress monitoring Cloning and genetic modification (GM) have and dissemination of genetic improvement. been available for many years, but have not A breeding goal is a list of traits to be targeted gained widespread commercial use. This is largely by the breeding programme, including their for economic reasons, but there are also poten- relative importance, and a description of how tial ethical concerns. Among livestock species, they should be changed genetically (increased, cloning is most frequently undertaken in horses, decreased or maintained the same). Breeding where individual animals can have extremely goals inevitably shift over time in response to the high values because of their earning potential changing requirements of livestock producers and in racing and other riding competitions. Since ultimately the demands of consumers and society the first SoW-AnGR was prepared, technologies at large. For many years, production traits were involving “genome editing” have been devel- the primary target. Later, traits affecting function oped. These techniques tend to be much more such as longevity, health and reproductive ability efficient than more traditional GM approaches. were added, as it was observed that selection Moreover, as genome editing does not involve for production had led to deterioration in these
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traits. Today, as a result of societal pressures, recording systems (FAO, 2015). Abundant and increasing attention is being given to behaviour, accurate measurements lead to efficient select- well-being and other novel traits. For example, in ion. As described above (Subsection 2), develop- response to the elimination of gestation stalls in ments in the field of genome-enabled selection pig husbandry, the breeding industry has started are creating significant new opportunities to to select for more docile sows, which it is hoped improve animal breeding. A key prerequisite is to will be more tractable in situations where animals have sufficient phenotypic information recorded are housed in groups during gestation. for the traits that potentially benefit the most As breeding objectives become broader, breed- from the use of this technology (e.g. health traits, ers increasingly have to deal with antagonisms sex-limited traits and traits that are difficult or between different sets of traits. When the genetic impossible to measure in live animals). correlation between two traits is favourable, Genetic evaluation is the process of deter- selecting for one trait can bring a correlated bene- mining which animals have a superior genotype ficial response in the other trait. However, when for the traits of interest so that decisions can traits are antagonistically correlated, selecting for be taken as to which animals should be used to one trait will lead to an undesirable response in breed the next generation. As performance is the other. In such cases, it is common practice to influenced both by the animal’s genetics and by include both traits in the selection objective and its environment, genetic evaluation involves sep- select animals with desirable attributes for both arating environmental components from genetic traits. This strategy allows all traits to be improved components. As described above in Subsection 2, over time (Neeteson-van Nieuwenhoven et al., genetic evaluation methods based on information 2013). Typically, the most efficient way to select on the performance of animals and their relatives for multiple traits is to combine them into a are now being supplemented by methods that “selection index” (Phocas et al., 2013). Traits are involve the use of molecular genetic information. weighted according to index coefficients that The extent to which these new methods have consider the economic importance of traits and moved beyond the research level and into com- their genetic relationships and maximize the mercial production varies from species to species correlation between the selection index and the (see Subsection 4 and also Part 3 Section E). breeding goal. Capacity to store performance and pedigree The outcomes of breeding programmes, part- data for use in genetic evaluations is continuously icularly in species with long generation intervals, increasing as more sophisticated computer hard- are realized many years after selection decisions ware becomes more widely available. It is likely are made. Even in poultry, a genetic change that technology will continue to improve and implemented in a breeding nucleus will take at that capacity to run yet more complex genomic least three years to have a noticeable effect at evaluations will not be limited by hardware avail- commercial level. This underlines the need to ability. The greatest limitation may prove to be a anticipate future demands when defining breed- lack of progress in the development of software ing goals. Breeders and breeding organizations for these types of analysis because of a lack of need to be tuned into societal pressures and how trained personnel in the field of animal breed- they are likely to affect future demand. ing and genetics and a lack of labs working on Animal identification and the recording of the development of the specialized software animals’ performance and pedigrees are the required. driving forces of genetic improvement. Detailed Family information in genetic evaluation advice on the development of animal recording increases the probability of co-selecting close rela- systems is provided in the FAO guidelines on the tives, which in turn leads to increased inbreeding. Development of integrated multipurpose animal Various methods are used to reduce inbreeding
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while maintaining high rates of genetic gain. All that all the elements of a breeding programme are based on the principle of reducing the average can be implemented even under very basic con- relationship between the individuals selected. ditions. Success is possible without the use of Computer programmes have been developed to elaborate data recording and genetic evaluation optimize selection decisions for a given list of can- systems, without genomic tools and without the didates for which pedigree information and EBVs use of reproductive technologies (see Subsection 5 are available (Weigel and Lin, 2000). Other mating for further discussion of breeding programmes in rules or methods for reducing the accumulation low-input systems). of inbreeding in a population were outlined in the first SoW-AnGR2 (see also Part 4 Section D and FAO, 2013). These rules have been utilized in 4 Breeding programmes in commercial poultry and pig breeding to maintain high-input systems inbreeding at relatively low levels. Many breeding companies have moved towards using programs such as “Mate Select” to control inbreeding more 4.1 Dairy and beef cattle systematically. The characteristics of the cattle breeding industry The progress achieved in a breeding pro- highlighted in the first SoW-AnGR3 included: gramme is usually assessed by regressing average • a relatively decentralized structure (com- phenotypic and breeding values on year of birth. pared to the pig and poultry sectors), with In addition, breeders run regular internal and different organizations performing comple- external performance testing. An external testing mentary tasks in the breeding scheme (iden- scheme needs to cover a wide range of production tification, performance recording, genetic environments to ensure that selected animals can evaluation, selection and commercialization perform well under a wide range of conditions. of genetics), the most distinctive feature Other sources of information, and probably the being the role played by commercial produc- most important, are field results and feedback ers in the provision of data used in genetic from customers. Frequently, companies test their evaluation; products against those of their competitors. • (in the dairy sector) a historical emphasis The impact of a breeding programme depends on production traits (milk yield and com- on the dissemination of genetic progress to cus- ponents) that had led to a great increase in tomers or into the wider livestock population. milk output, but also to a deterioration in Reproductive technologies, particularly AI, play so-called functional traits, i.e. those related an important role in many species. They allow to the animal’s health and fertility; this had genetic material to be transported around the led breeding organizations to increase the world and greatly increase the number of off- weight of functional traits in selection indices; spring that can be obtained from a superior • (in the beef sector) a focus on increasing breeding animal. As discussed above (Subsec- growth rates that had caused an increase in tion 2.3), recent years have not seen major tech- calving problems associated with calf size, as nological advances in this field. However, the well as creating potential fertility problems use of reproductive technologies is becoming associated with heifers being unable to meet more widespread in many countries (see Part 3 higher nutritional demands associated with Section E). a larger size; Despite the ever-increasing sophistication of • a need to improve the recording of func- breeding technologies, it is important to recall tional traits, particularly in beef cattle;
2 FAO, 2007a, page 395. 3 FAO, 2007a, pages 396–400.
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• a lack of capacity to implement direct selec- of reliable phenotypic records, either because of tion for feed efficiency, resulting from a lack logistical problems or because of high costs. The of capacity to obtain feed-intake data for automation of milking procedures has become sufficient numbers of animals; significantly more widespread during the past • a lack of market mechanisms that reward decade and is generating a large volume of new producers for improved meat quality; records that could potentially be used to expand • (in the beef sector) a lack of well-organized the portfolio of traits evaluated. The practice of cross-breeding programmes; breeding companies establishing contracts with • a major role played by breeders’ associations, the owners of large herds to collect data on novel along with significant input from public traits is foreseen to become more common in the institutions in terms of data management future and to play an increasingly important role and genetic evaluation; and in genetic evaluation of these traits. These prac- • a trend towards the internationalization of tices may increase the accuracy of genetic eval- AI companies. uation, but perhaps only for the specific stand- These characteristics have changed little in ardized environment in which they are recorded. the years since the first SoW-AnGR was prepared In beef cattle, growth and carcass traits continue (2005/2006). Decentralization remains a common to be the main selection objectives, although theme. Ownership of individual animals remains calving and fertility traits are receiving increas- with private livestock keepers, particularly in ing attention. Difficulties with reliable recording the case of female animals, although there is are even more acute in beef than in dairy oper- a general trend towards concentration. Breed ations. Assessing the sophisticated carcass classifi- associations continue to play a major role. The cation data collected by slaughterhouses (e.g. the trend towards globalization continues, both in EUROP carcass classification system)5 for genetic terms of the organization of AI companies and evaluation purposes would improve the selection the use of breeds in a transboundary manner. process. However, it would require a consistent Cross-breeding is a routine practice in dairy animal identification infrastructure, from birth cattle as a means of increasing profitability by to slaughter (or, perhaps, much more widespread improving functionality and fitness. As discussed reliance on DNA-based measures of animal ident- in more detail below, the adoption of genomic ification and genetic relationships) that would selection has been nothing short of revolution- allow the development of consolidated data- ary. The evaluation, acquisition and marketing bases. Current breeding objectives in dairy and of AI bulls have been transformed, with a much beef cattle are summarized in Tables 4C1 and 4C2. greater emphasis now given to younger bulls The development of technologies that allow with no progeny. fast, accurate and affordable determination of The breeding objectives listed in the first SoW- SNPs has enabled the AI industry to make effi- AnGR4 are still relevant to most selection pro- cient use of genetic markers for selection pur- grammes worldwide, but some changes have poses and represents the most significant advance occurred. In many countries, selection indices for in cattle breeding since the adoption of AI (see dairy cattle have been adjusted so as to reduce Subsection 2 for a general description of the role the emphasis given to production traits and to of genetic markers in animal breeding). The com- accentuate functional traits such as fertility, lon- pletion of the bovine genome sequence and ref- gevity and udder health. The major obstacle to erence assembly (Elsik et al., 2009) enabled the including more health traits and novel traits such 5 See Commission Regulation (EEC) No 2930/81 of 12 October as feed efficiency in selection programmes is a lack 1981 adopting additional provisions for the application of the Community scale for the classification of carcasses of adult 4 FAO, 2007a, Table 99 (page 397). bovine animals (available at http://tinyurl.com/qejooac).
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Table 4C1 Selection criteria in dairy cattle
Traits Comments Milk quantity More frequently the quantity of protein and/or fat Production traits Milk quality Concentration of protein and/or fat Feed efficiency Rarely measured directly Conception rate For males, it may be calculated based on mates or daughters Reproduction traits Ease of calving Often used for mating, rather than selection Survival Measured as longevity Either directly based on incidence or indirectly based on somatic cell concentration in milk and Mastitis resistance Robustness traits udder conformation of daughters Leg soundness Usually based on conformation traits and observed mobility Body conformation Decreased body size has a positive association with feed efficiency and longevity
Note: This table updates and expands upon information provided in Table 99 of the first SoW-AnGR (FAO, 2007a).
Table 4C2 Selection criteria in beef cattle
Traits Comments Body size Ideal size depends on environment Growth rate Weight at various ages (e.g. birth, weaning, one year of age) Measured indirectly based on growth, has an intermediate optimum because high milk production Milking ability Production traits results in waste Carcass quality Carcass yield, loin muscle area Feed efficiency Meat quality Marbling (intramuscular fat), tenderness Male fertility Measured by using scrotal circumference Mothering ability Reproduction traits Ease of calving Based on scores provided by breeders Calving interval Seasonal production requires regular yearly calving Survival Longevity Robustness traits Conformation Leg soundness is important for function in rangeland conditions Temperament To improve safety and increase ease of management
Note: This table updates and expands upon information provided in Table 99 of the first SoW-AnGR (FAO, 2007a).
identification of the several thousands of SNPs are now regularly identified among genotyped used to develop low-cost SNP chips. Genomic cattle (Table 4C3). screening of a large proportion of the population Adoption of genomic selection has been facilitates the discovery of haplotypes associated extremely rapid in the dairy sector and has already with economically important traits such as reces- replaced the progeny testing schemes that were sive disorders, reproductive performance, coat the state of the art for several decades. Males, colour and polledness. Carriers of such haplotypes and a rapidly increasing number of females, are
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Table 4C3 Recessive haplotypes tracked in the genomic evaluation system in the United States of America
Breed Haplo- OMIA Gene Condition/trait Frequency Chromosome Reference type 9913 ID1 name (%)
Cooper et al., 2014, Ayrshire AH1 001934 UBE3B Conception rate 13.0 17 Venhoranta et al., 2014 BH1 001825 — Abortion 6.67 7 VanRaden et al., 2011 BH2 001939 — Abortion 7.78 19 Schwarzenbacher et al., 2012 Hafner et al., 1993, BHD 001247 SPAST Spinal dysmyelination 2.19 11 Thomsen et al., 2010 Brown Swiss El-Hamidi et al., 1989, BHM 000939 KDSR (FVT1) Spinal muscular atrophy 3.61 24 Krebs et al., 2007 Progressive degenerative BHW 000827 myeloencephalopathy 1.56 4 McClure et al., 2013 (Weaver syndrome) HBR — MC1R (MSHR) Black/red coat colour 0.8 18 Lawlor et al., 2014 Dominant red coat HDR — 0.04 3 Lawlor et al., 2014 colour Agerholm et al., 2006, HH0 000151 FANCI Brachyspina 2.76 21 Charlier et al., 2012 HH1 000001 APAF1 Abortion 1.92 5 Adams et al., 2012 VanRaden et al., 2011, HH2 001823 — Abortion 1.66 1 McClure et al., 2014 Daetwyler et al., 2014, HH3 001824 SMC2 Abortion 2.95 8 McClure et al., 2014 HH4 001826 GART Abortion 0.37 1 Fritz et al., 2013
Holstein HH5 001941 — Abortion 2.22 9 Cooper et al., 2013 Leukocyte adhesion HHB 000595 ITGB2 0.25 1 Shuster et al., 1992 deficiency, type I (BLAD) Complex vertebral HHC 001340 SLC35A3 1.37 3 Agerholm et al., 2001 malformation Deficiency of uridine HHD 000262 UMPS monophosphate 0.01 1 Shanks et al., 1984 synthase (DUMPS) Eldridge et al., 1951, HHM 000963 LRP4 Syndactyly (mule foot) 0.07 15 Duchesne et al., 2006 Medugorac et al., 2012, HHP 000483 POLLED Polled/horns 0.71 1 Rothammer et al., 2014 HHR 001199 MC1R (MSHR) Red coat colour 5.42 18 Joerg et al., 1996 JH1 001697 CWC15 Abortion 12.10 15 Sonstegard et al., 2013 Jersey JH2 001942 — Abortion 1.3 26 VanRaden et al., 2014
Note: 1 Online Mendelian Inheritance in Animals (http://omia.angis.org.au/) identification number for Bos taurus (National Center for Biotechnology Information species code 9913). Source: Cole et al., 2015.
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genotyped at very young ages and not used as take the lead and supply innovative and custom- breeding animals if their GEBVs do not meet the ized services to dairy breeders in a manner similar selection criteria. In combination with advances in to that already pertaining in the poultry and pig multiple ovulation and embryo transfer (MOET), industries. Data ownership has become a key genomic selection has shortened the generation issue and control over the genetic-improvement interval to such an extent that the sires of the cur- process may shift from breeders to corporations rently active AI bulls do not yet have any recorded (Dürr, 2013). progeny. The replacement of progeny testing has Genomic selection has advanced more slowly been a revolution in dairy cattle breeding, but yet in the beef sector. This is mainly because of dif- another paradigm shift is now taking hold. The ferences in population structure (in dairy breeds, relatively low reproductive capacity of cattle and the large number of offspring produced per bull the rates of involuntary culling have traditionally through AI improves the precision of genomic meant that the female offspring from all cows selection), the fact that major production traits were needed as replacements within a given herd. such as growth rate can be measured in all Therefore, genetic improvement via the dam-of- animals relatively early in life and the lack of daughters pathway has been negligible. Now, the large phenotypic and animal-pedigree databases combination of sexed-semen technologies and for beef cattle. low-density, low-cost SNP chips has increased both the selection intensity and the selection accuracy 4.2 Sheep within this pathway, thus creating a new opportu- The first SoW-AnGR presented an overview of the nity for additional genetic improvement. state of sheep breeding in high-input systems, Because the accuracy of GEBVs is highly noting the selection criteria utilized and describ- dependent on the size of reference populations ing the organization of the breeding sector in (Hayes et al., 2009b), even the largest cattle different parts of the world.6 Table 4C4 sum- populations greatly benefit from international marizes the traits most commonly considered exchanges of genomic data. Exporting coun- in current sheep breeding programmes. While tries took the lead in adopting genomic techno- the broad characteristics of the sheep breeding logies and formed consortia to share genotypes. industry remain similar to those described in Interbull, a subcommittee of the International the first SoW-AnGR, breeding programmes for Committee for Animal Recording (ICAR), has con- high-input systems have undergone consider- tinually adapted its activities to account for the able change in the past decade. Although devel- use of genomic information in genetic evalua- opments in genomic prediction are exciting and tion. The market has become polarized into two have attracted considerable research investment major blocks, the importers and the exporters of in a number of countries, structural and economic genetics. The technological gap between these effects are also very important. two blocks has widened rapidly, both because of While in general, sheep breeding programmes the investments required and because of a rela- have typically aimed to improve production and tive lack of expertise in the importing countries. reproduction traits, identification of molecular Poor results from multibreed genomic predictions markers for major genes that directly affect sheep have hindered genomic applications in smaller, health has led to the incorporation of selection non-mainstream, populations and the hegemony for health traits. Selection for the ARR haplotype of the Holstein has been increasing at a greater at the PRNP locus and against the VRQ haplo- speed. The potential uses of genomics are seem- type has been used in several countries to reduce ingly limitless. New actors coming from sectors susceptibility to scrapie (Hunter, 2007). Selection not directly related to dairy or beef breeding (e.g. pharmaceutical companies) have started to 6 FAO, 2007a, pages 400–402.
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Table 4C4 Selection criteria in sheep
Traits Comments
Body size Ideal size depends on environment
Growth rate Weight at various ages (e.g. birth, weaning, one year of age)
Meat yield Proportion of fat in the carcass and lean distribution across carcass regions Production traits Meat quality Marbling (intramuscular fat), tenderness
Fleece weight, fibre diameter, advanced processing characteristics (e.g. coefficient of variation of Wool quantity and quality fibre diameter, staple strength)
Milk yield and quality
Litter size Twinning rate, larger numbers of offspring may be detrimental
Reproduction traits Mothering ability Number of lambs weaned, milk yield, early growth
Weaning rate Number of lambs weaned, combining effects of litter size and lamb survival
Survival Longevity
Parasite resistance Helminths, blowfly strike
Robustness traits Scrapie resistance Based on molecular tests
Mastitis resistance Trait indirectly selected for based on somatic cell concentration in milk
Udder conformation
Note: This table updates and expands upon information provided in Table 99 of the first SoW-AnGR (FAO, 2007a).
against day blindness in Awassi sheep is being The potential to exploit genomic selection undertaken via the CNGA3 locus (Reicher et al., is less in small milking ruminants than in dairy 2010) and resistance to maedi visna infection has cattle breeds such as the Holstein, which have been shown to have favourable alleles at the larger values per animal, longer generation inter- TMEM154 locus (Heaton et al., 2012). vals in progeny testing schemes, smaller effective In the very intensive sheep-farming systems of population sizes and larger numbers of historical Europe and the Middle East, where high prolificacy individuals with accurately recorded phenotypes is economically important, use of genetic techno- and genotypes. However, because genomic selec- logies such as introgression of the FecB mutation tion simplifies the AI cooperative structure, a shift with the aid of molecular genotyping (Gootwine towards genomic breeding strategies is occurring, et al., 2008) and the advent of genomic selection at least in some French milking sheep breeding (Larroque et al., 2014) have created substantial programmes (Duchemin et al., 2012; Larroque et opportunities to increase the rate of genetic pro- al., 2014) (see Box 4C3). gress. Breeding programmes for improving milk In the meat and wool sectors, programmes such production traits are in place in several European as the National Sheep Improvement Program in counties. Most milk recording is carried out in the United States of America7 and LAMBPLAN8 in France, Italy and Spain, where large-scale use of Australia evaluate records of on-farm performance AI facilitates breeding work. According to an ICAR survey reported in 2013 (Astruc, 2014), there are 7 www.nsip.org about 2 million sheep under recording, almost 8 http://www.sheepgenetics.org.au/Breeding-services/ exclusively in European countries. LAMBPLAN-Home
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Box 4C3 increasingly being forced into harsher production Adoption of genomic selection in French dairy environments due to rapid expansion of the dairy sheep breeds industry (Morris and Kenyon, 2014). The three test sites of the country’s central progeny testing Given the importance of ewe-milk production in structure, widely recognized as a key facilitator France, there is growing interest in implementing of accelerating rates of genetic progress, have genomic selection in dairy sheep breeds. The recently been supplemented by two additional reliabilities of genomic breeding values for the sites, both of which are commercial farms operat- Lacaune and Blond-Faced Manech sheep breeds are ing in very harsh production environments. similar to those of the Montbéliard and Normande Despite considerable investment in genomic dairy cattle breeds, as they all have reference approaches, there are still challenges to the inte- populations of a similar size (Duchemin, 2012; Baloche gration of these technologies into breeding pro- et al., 2014). A simulation study of the Lacaune has grammes. Both the Australian approach, based indicated that genomic selection could increase on a very large reference population with inten- annual genetic gain by 15 percent as a result of an sive phenotypic recording, and the New Zealand increase in the intensity of selection of young rams approach, based on industry sires as the train- (Buisson et al., 2014). The simulation predicted that ing resource, have produced relatively modest the increased income obtained would compensate improvements in selection accuracy compared, for the extra costs of genotyping. Based on this for example, to those achieved in Holstein cattle information, Lacaune breeders decided, in 2015, to (Dodds et al., 2014; Swann et al., 2014). To date, shift to a genomic breeding programme. It is assumed adoption of genomic selection approaches in that genotyping costs will continue to decrease in both countries has been limited to highly pro- the future, thus increasing the potential economic gressive breeders who wish to be at the forefront benefits of genomic selection. Breeders of the Blond- of technology and are content with marginal Faced Manech breed are planning to adopt routine gains in the rate of genetic progress. Work on genomic selection in the near future. how to integrate genomic predictions into novel breeding programme structures and attempts to reduce testing costs per animal and per breeding scheme via two-stage selection strategies (Sise records and provide the industry with EBVs for et al., 2011) and combination with reproductive many traits for elite and young rams belonging to technologies (Granleese et al., 2013) have been a range of breeds. Some EBVs are combined to cal- identified as keys to increased adoption. Research culate indexes for specific breeding goals. is also being undertaken into higher-density Breed shifts and the introduction of compos- chips and gene sequences, although there is ite breed types have been transformational in little evidence of practical benefits. Exploiting New Zealand and Australia over recent decades. the ever-decreasing costs of genome sequencing This has been driven, at least partly, by shifts in remains an exciting challenge for the future. focus from wool production to meat production. Formal industry structures and coordinated Interestingly, in New Zealand, although higher provision of genetic improvement services such as performance composites rapidly took substantial databases and genetic evaluation systems are crit- market share following the introduction of novel ical to the success of genetic evaluation systems. breeds from Europe, much of this market share However, even where such systems exist, rates of has since been recovered by breed types (includ- adoption of new technologies may be poor and ing lower-performance composites) identified by rates of penetration into the commercial sector by farmers as having higher levels of robustness in rams from flocks in which the latest technologies breeding ewes. Sheep flocks in New Zealand are are used may be very low (Amer et al., 2007). An
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example of steps that can be taken to overcome Box 4C4 challenges of this kind is provided in Box 4C4. Improving the system of sheep breeding in Ireland 4.3 Goats The first SoW-AnGR provided a short review In Ireland, a new and modern support structure has of the state of goat-breeding programmes in been put in place to support sheep breeding. The high-input systems, noting that such programmes initial challenge has been to engage with a breeding were mainly concentrated in Europe and North sector that historically relied on basic phenotypes and America and focused mainly on dairy breeds. physical type traits as primary selection criteria, and Breeding programmes for meat goats were to overcome the barrier of having many small breeder described as being present in a few countries flocks with low levels of genetic connectedness with well-developed goat-meat sectors, such as among them. A central progeny testing scheme has Australia, South Africa and the United States of been established, which originally had the goal of America.9 This overall picture has not changed increasing levels of genetic connectedness. More greatly in the recent years. Well-structured goat recently, the focus has switched to identifying sires breeding programmes are generally found only of sires that excel for a balance of maternal and in developed countries where the production, carcass traits (Pabiou et al., 2014). If these sires get processing and commercialization of goat prod- used through AI in a large number of flocks that ucts are well organized. Table 4C5 lists the most market rams for natural service, it will be possible to important traits considered in contemporary multiply the elite genetic material across a substantial breeding programmes for dairy and meat breeds. proportion of the industry. This strategy is less reliant All effective goat breeding programmes are on widespread uptake of recording by all breeders, based on straight-breeding. They rely on the exist- for many of whom ram production and marketing is ence of well-characterized breeds and breeders’ a secondary source of income. In addition, interest associations that can manage herd books and is growing in Ireland in the potential of genomic performance-recording systems. As with other selection, and also imported genetics, to accelerate genetic progress. 9 FAO, 2007a, page 402.
Table 4C5 Selection criteria in goats
Traits Comments Body size Growth rate Weight at various ages (e.g. birth, weaning, one year of age) Production traits Meat quality Marbling (intramuscular fat), tenderness Milk yield and quality Fibre quantity and quality Fleece weight and fibre diameter (for mohair and cashmere producers) Litter size Twinning rate, larger numbers of offspring may be detrimental Reproduction traits Mothering ability Number of kids weaned, combining effects of litter size and kid survival Survival Longevity Robustness traits Mastitis resistance
Note: This table updates and expands upon information provided in Table 99 of the first SoW-AnGR (FAO, 2007a).
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species, goat breeds are monitored for inbreed- adoption of genomic selection and has estab- ing, and the selection and diffusion of AI bucks is lished reference populations for the popular modulated to minimize inbreeding (Colleau et al., Alpine and Saanen breeds (Larroque et al., 2014). 2011; Palhiere et al., 2014). Obtaining EBVs that are Study of these populations suggests that the reli- sufficiently reliable for efficient selection requires ability of genomic evaluation would be less than the recording of pedigree information and at in dairy cattle breeds with large populations, but least a minimum of genetic connection between similar to that in cattle breeds with equivalent herds. Schemes based on progeny testing and population sizes (ibid.). In addition, in contrast to the collective use of sires have become somewhat the findings of most studies in dairy cattle (e.g. more common in recent years. In addition to the Kemper et al., 2015), joint genomic evaluation French and Norwegian programmes noted in the of goat breeds tends to improve the accuracy of first SoW-AnGR (the former involving the use of GEBVs (Carillier et al., 2014). AI and the latter the sharing of sires among coop- erating breeders), examples now include selec- 4.4 Pigs tion schemes for Spanish dairy breeds (Murciano- The basic structure of the pig breeding sector granadina, Malagueña, Florida and Payoya), based remains similar to that described in the first SoW- on progeny-tested males and the use of their AnGR.11 In the typical breeding programme, pedi- semen for planned matings throughout the whole gree selection occurs only within pure-bred lines selection nucleus (Seradilla, 2014). Although (designated as sire or dam lines) in the nucleus some of these schemes have achieved a degree of (i.e. the top layer of the production pyramid). Sire success (Menendez-Buxadera et al., 2014), several lines are selected for growth and carcass traits, constraints to their further development remain to meat quality and robustness. Dam lines are also be resolved, particularly with regard to their eco- selected for reproduction traits. New lines are nomic sustainability (Serradilla, 2008). regularly developed by crossing existing lines There have also been some notable devel- and/or by specialized selection in a particular opments in Latin America. In Brazil, selection direction. A breeding organization’s final prod- schemes for improving meat and milk production ucts are parent sows (two- or three-way crosses) have been implemented in small selection nuclei and parent boars (pure lines or two-way crosses). of imported and locally adapted breeds (Lôbo et These parent animals are used by producers to al., 2010). In Mexico, a small selection nucleus has breed pigs for slaughter. been organized by a group of breeders from the The pig-breeding sector is less concentrated state of Guanajuato, which also progeny tests sires than the poultry sector (see Subsection 4.5). There through AI and undertakes genetic evaluation of are still many breed associations and many coun- sires and dams (Torres Vázquez et al., 2009). tries have some kind of national, often semi-gov- The main technological innovation in recent ernmental, genetic evaluation scheme (e.g. the years has been the development of tools for the National Swine Registry in the United States of exploitation of molecular genomics in advanced America, the Canadian Centre for Swine Improve- selection schemes. Gene-assisted selection is cur- ment Inc. and LGPC-IFIP-INRA12 in France). These rently applied in France and Norway to improve schemes compete with pig-breeding companies milk protein content (Manfredi and Ådnøi, 2012). that may be owned by cooperatives (e.g. Topigs, The International Goat Genome Consortium10 has Danavl, Nucléus and ANAS) or by families (e.g. worked with a private company to develop a ACMC, Grimaud, Hendrix and JSR) or may be commercially available SNP chip for goats (Toss- er-Klopp, 2012). France has investigated the 11 FAO, 2007a, pages 402–405. 12 Livres Généalogiques Porcins Collectifs - Institut de la Filière 10 http://www.goatgenome.org/ Porcine - Institut National de la Recherche Agronomique.
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corporations (e.g. PIC). Over the years, pig-breed- pure-bred relatives that are selection candidates ing companies have tended to amalgamate into in the nucleus (Wei and Van der Steen, 1991). larger and more cost-efficient entities. This approach implies increasing the emphasis Pig-breeding programmes have been very given to robustness traits such as survival rates, successful in improving economically important leg soundness, disease resistance, stress suscept- traits (e.g. Chen et al., 2002; Tribout et al., 2010), ibility and longevity. Table 4C6 presents a with growth and carcass performance (growth summary of current selection objectives in pig rate, leanness and feed efficiency) having been breeding. Recent changes have been quantitative targeted since the 1970s and greater attention rather than qualitative: a gradual shift towards given to reproductive performance (litter size, robustness traits and efficiency. An important piglet survival and farrowing interval) and meat development for the late 2010s will be the intro- quality (water binding capacity, colour and intra- duction of boar taint as a breeding goal trait in muscular fat content) from the 1990s onwards. the European Union, where piglet castration is Since the 2000s, the focus has been shifting likely to end in 2018. towards breeding for more robust and efficient With ongoing intensification of the product- animals to meet the needs of a more diverse ion sector, pig health is becoming ever more range of production environments (Merks et al., important. This requires, in the first place, 2012). This has required strategies for dealing improving sanitary status and biosecurity at with genotype by environment interactions. One the breeding-farm level, so that diseases are popular approach is the combined cross-bred not introduced from the breeding farms into and pure-bred selection (CCPS) scheme, which the production pyramid. It has also triggered involves recording the cross-bred progeny of AI attempts to breed for disease resistance and nucleus boars under commercial conditions and against metabolic disorders. However, this using the data to estimate the breeding values of work is only in its initial stages. Globally, pig
Table 4C6 Selection criteria in pigs
Traits Comments Growth rate At various ages Carcass quality Carcass yield, carcass leanness, uniformity Production traits Feed efficiency Meat quality Water-holding capacity, colour, intramuscular fat content Litter size Reproduction traits Piglet survival Mothering ability of the sow, viability of the piglets, litter uniformity Farrowing interval Stress susceptibility: halothane sensitivity Allele eradication at a single gene; still relevant in a few extreme sire lines only Congenital defects Atresia ani, cryptorchidism, splayleg, hernias, hermaphrodites, etc. Leg soundness Osteochondrosis and many other aspects Robustness traits Disease resistance Specific Escherichia coli strains Survival Piglet viability (effect of the sire); postweaning survival rates Sow longevity
Note: This is an updated version of Table 100 of the first SoW-AnGR (FAO, 2007a).
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production is gradually shifting from temperate 4.5 Poultry to warmer climatic zones and this has created The first SoW-AnGR provided an overview of the requirements for animals that are resilient to poultry-breeding industry, noting its hierarch- hot conditions. This has led to the introduction ical structure, often referred to as the “breeding of novel breeding–goal traits such as lactation pyramid”, and its concentration in the hands of a feed intake (Renaudeau et al., 2014). In Western small number of companies.13 It also discussed the societies, increasing attention to animal welfare main selection criteria in poultry breeding pro- is leading to the introduction of novel housing grammes, noting a trend towards the inclusion of systems, which in turn is leading to the adopt- ever more traits in breeding objectives. ion of a new set of breeding-goal traits, mainly A typical poultry breeding programme includes related to various aspects of animal behav- a biosecure breeding nucleus from which genetic iour. Growing concern about environmental improvement is disseminated to the wider indus- efficiency (e.g. greenhouse gas emission, phos- try through multiplication tiers at great-grand phorus retention and nitrogen excretion) is parent, grandparent and parent levels. Improved likely to increase the emphasis given to feed birds are multiplied and crossed, in three or four efficiency in genetic improvement programmes. steps, in the lower tiers of the breeding structure Because of the competitive nature of the indus- to produce broiler or layer birds (see Table 4C7). It try and its high levels of investment, commercial is important to note, however, that the traditional breeding companies usually spearhead the use portrayal of the structure of the poultry industry of technologies. Many use MAS in one form or as a pyramid, with the breeding programme at another and a handful have implemented full- the apex, is something of an over simplification scale genomic selection (Van Eenennaam et al., (Laughlin, 2007). The structure can more accu- 2014). These are expensive technologies, and rately be represented by two pyramids: a small studies have been undertaken to evaluate their supporting pyramid at the base, representing the financial feasibility in various breeding systems specialized breeding programmes, and a larger (e.g. Abell et al., 2014). Another important inverted pyramid above, representing the other innovation has been the development of opti- tiers of production, with the consumer at the top mization routines that balance between genetic (see Figure 4C1). The supporting pyramid contains improvement and inbreeding in the planning all the elements needed to maintain a breeding of selection and mating schedules at nucleus programme: experimental lines, test lines and level (see Subsections 2.1 and 3). At present, a pure lines, along with the various support systems major focus of development is accommodating of modern genetics, including a strong research genomic information in mate-selection proce- dures. 13 FAO, 2007a, pages 404–405.
Table 4C7 Cross-breeding scheme and relative numbers in a typical broiler breeding programme
Level in breeding pyramid Paternal lines Maternal lines
Pedigree stock A♂ × A♀ B♂ × B♀ C♂ × C♀ D♂ × D♀ Great grand parents 1 A♂ × 10 A♀ 10 B♂ × 100 B♀ 3 C♂ × 30 C♀ 25 D♂ × 250 D♀ Grand parents 250 A♂ × 2 500 B♀ 1 500 C ♂ × 12 500 D♀ Parents 62 500 AB♂ × 625 000 CD♀ Broilers 87 million ABCD
Source: Adapted from Hiemstra and Napel, 2013.
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Figure 4C1 Poultry breeding is a global business and Structure of the poultry breeding industry poultry are raised in production environments that vary substantially in terms of ambient tem- perature, humidity, altitude, disease exposure, Consumers feed quality and management capacity. Many Processing/retailers/food service regions where poultry are produced are highly vulnerable to climate change, and the develop- Broilers ment of resilient strains able to cope with climate
Parent stock change-affected production environments has • Science and become a focus of many breeding programmes. technology Grandparent stock The high cost of recording and the need to • Regulations Great-grand parent maintain strict biosecurity mean that breed- • Consumer requirements • Ethics ing companies typically undertake selection at • Code of practice Improved stock a limited number of sites, rather than at many •Animal welfare sites spread around the world. There is therefore •Sustainability
Feedback a high potential for genotype × environment interactions (Neeteson-van Nieuwenhoven et al., 2013). To reduce the problem, poultry breeders Control lines Development lines have developed crosses that are robust to minor changes in the production environment. This is achieved by testing the siblings of selection and development base geared towards respond- candidates, different lines or different cross-bred ing to feedback from every tier of the industry progeny in multiple production facilities and field and from society. environments. The field data are then combined The poultry-breeding industry remains concen- with data obtained in the breeding nucleus. trated in few hands. Fewer than five groups of Increasing attention is also being paid to the primary breeders dominate the market for breed- need to reduce the carbon footprint of poultry pro- ing stock (Fuglie and Heisey, 2011) and some of duction systems. This has led to an increased focus these are involved in the production of more than on the efficiency of production and a consequent one poultry species. Most breeding companies shift in breeding objectives. Life-cycle analyses have are based in Europe or North America, with sub- indicated that the feed supply chain contributes a sidiaries in major production regions. large proportion of the poultry sector’s share of The main breeding objectives and selection global greenhouse gas emissions (Pelletier et al., criteria in commercial poultry breeding are sum- 2014). Improving feed efficiency is thus a key factor marized in Table 4C8. Since the 1960s, breeding in reducing the environmental impact of poultry goals have evolved from a narrow starting point production (Olori, 2010; Pelletier et al., 2014). It emphasizing production traits to now encompass has been estimated that an improvement in feed a very broad range of considerations, including efficiency resulting in a saving of 15 g feed per kg reproduction, animal health, product quality and body weight gained would reduce global poultry environmental impact. This expansion has been feed requirements by around 1.85 million tonnes particularly notable during the last two decades per year, freeing up about 4 000 km2 of arable (Neeteson-van Nieuwenhoven et al., 2013). The land14 (Neeteson-van Nieuwenhoven et al., 2013). trend has been driven by the need for efficiency, Feed intake, feed conversion ratio and residual including in environmental terms, as well as by feed intake are included in breeding objectives in the need for robustness and adaptability to varying production environments. 14 Based on 2010 harvest yield of 466 tonnes of wheat per km2.
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Table 4C8 Selection criteria in poultry
Traits Comments Egg number Egg production Hen house production Chickens, ducks and geese: number of saleable eggs per bird Hen-day percentage Egg weight Egg weight/size, shape index Shell breaking strength Broiler and layer chickens: shell breaking strength, puncture score, Shell thickness Egg quality – external dynamic stiffness, resonance frequency; egg weight loss between Shell porosity/egg weight loss setting and transfer as a measure of shell porosity Shell colour, egg shape Egg quality – internal Haugh unit, albumen height, yolk percentage Growth rate Body weight at various ages Chickens, turkeys and ducks: high emphasis on selection against Breast meat percentage Meat production fat in meat-type ducks; fat percentage assessed on live birds using Leg meat percentage multidimensional ultrasound measures as well as condition scoring Fat percentage Eviscerated yield percentage Feed intake Feed conversion ratio is feed intake per kg weight gain in meat-type Feed efficiency Residual feed intake birds and per kg egg mass in layers Feed conversion ratio Liveability, leg health and walking Selection for improved robustness, disease resistance and liveability Gait, bone strength traits and for decrease of (for example) tibial dyschondroplasia Gut health Health, welfare and assessed with a lixiscope, valgus/varus, osteoporosis, toe defects, Heart and lung function metabolic fitness footpad dermatitis, femoral head necrosis and hockburn; heart and Feather-pecking behaviour lung function assessed by measuring blood oxygen saturation using Feather cover an oximeter End of lay condition score Fertility and hatchability Early and late embryo mortality Broiler and layer chickens and turkeys: hatchability in terms of hatch Reproductive efficiency Chick viability (survivability beyond day of of fertile eggs or hatch of set eggs hatch) Plumage colour Plumage Feather quality
Note: This is an updated version of Table 101 of the first SoW-AnGR (FAO, 2007a). the turkey, layer and broiler sectors. To account for reproductive performance while avoiding obesity group dynamics in feeding, some breeding pro- and associated welfare problems in breeding grammes have invested in feed recording systems birds. However, welfare concerns about hunger based on transponder technology that allow con- have also been raised (D’Eath, 2009). Recent tinuous recording of the feed intake of individ- research has focused on behavioural and neuro- ual birds in housed groups (Bley and Bessei, 2008; physiological measures of hunger (Dixon et al, Howie et al., 2010; Tu et al., 2011). This technology 2014; Dunn et al., 2013) and the development also allows the genetic basis of feeding behaviour of feeding strategies that optimise reproductive under competition to be studied (Howie et al., performance while avoiding both obesity and 2009; Howie et al., 2010). hunger (Van Emous, 2015). One problem that has been highlighted by some Reproductive ability is not only vital to the prof- authors (e.g. Dawkins and Layton, 2012) is the itability of the breeding companies’ customers, risk that rapid growth potential may pose to the it also affects the intensity of selection within the welfare and the fertility of breeding birds. Feed breeding nucleus. Increased longevity, egg fertility management has been effective in optimizing and hatchability, chick viability and persistency of
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performance are therefore key breeding objectives. candidates, and disease-resistance traits that could These traits are significantly affected by hen age. otherwise only be meaningfully selected for on the New methodologies based on random regression basis of challenge tests (i.e. tests involving expo- models are now used to evaluate these traits (Wolc sure to disease). It is now clear that despite these et al., 2009; 2010) and this facilitates examination developments traditional data recording remains of the persistency of performance over time. important, as the accuracy of genomics-predicted Livability (survival to the end of the production breeding values relies on accurate phenotypic data. cycle) and persistent performance require healthy Further statistical and technological developments birds that are free of physical and physiological that reduce the cost of genotyping individual defects. Breeding objectives therefore include birds will be key to the widespread application of traits that contribute to the health and welfare genomic selection and its contribution to poultry of the birds. For example, in the egg-layer sector, breeding in the coming decades. efforts are made to minimize cannibalism and feather pecking in group-housing systems. Traits 4.6 Rabbits monitored include feather coverage at various Intensive rabbit-meat production is based on ages. Some companies select breeding stock while three-way or four-way cross-breeding (Baselga the birds are housed in groups, particularly in the and Blasco 1989; Lebas et al. 1997). In maternal case of broilers. A strategy based on group selec- lines, litter size remains the most common select- tion using so-called social interaction models has ion criterion because of its high economic value also been shown to be feasible (Bijma, 2010) and (Prayaga and Eady, 2000; Cartuche et al., 2014). is being evaluated (Ellen et al., 2011). However, it However, functional traits, such as doe longevity, is generally difficult to estimate genetic param- kit survival, maternal traits and genetic resistance eters for such effects, especially when group to bacterial disease, are emerging as criteria in sizes are large, and this may limit the use of such breeding programmes targeting more sustain- methods. Livability also requires reduction in the able production (Piles et al., 2006; Eady et al., incidence of cardio-vascular problems (sudden 2007; Garreau et al., 2008a; Sanchez et al., death syndrome and ascites) and leg problems 2008). Paternal lines are commonly selected for in broilers and turkeys. However, the causes of post-weaning daily gain or for weight at a point these problems are multifactorial and have been close to market age (Rochambeau et al., 1989; the focus of research efforts for decades. Many Lukefahr et al., 1996; Piles and Blasco, 2003; Larzul breeding programmes regularly select against et al., 2005). These criteria are easy to record and contact dermatitis (foot pad and hock burn) have a favourable genetic correlation with feed (Kapell et al., 2012a) and for improved clinical conversion index (Piles et al., 2004), which is very and subclinical leg health (Kapell et al., 2012b), as important for efficient production, as feeding well as for measures of heart rate and oxygen sat- accounts for the highest proportion of total costs. uration as indicators of ascites and sudden death. In Europe, demands from slaughterhouses mean Poultry breeders have adopted genomic select- that carcass yield is becoming increasingly impor- ion (see Subsection 2.3) as a means of increasing tant. Disease resistance has also become a major selection accuracy and reducing generation inter- issue. Thus, in addition to weight at slaughter vals (Avendano et al., 2010; Avendano et al., 2012; age or average daily gain, some paternal lines Sitzenstock et al., 2013; Wolc et al., 2014). The are now selected for carcass traits and against greatest benefit from genomic selection is expected susceptibility to digestive disorders (Eady et al., to be seen in the improvement of traits expressed 2007; Garreau et al., 2008b). Breeding objectives in only one sex and/or at a late age (e.g. egg pro- in rabbits are summarized in Table 4C9. duction, fertility and hatchability), carcass traits that Meat-rabbit selection schemes are found mainly hitherto required the sacrifice of potential selection in France, Spain, Italy, Hungary, Egypt and Saudi
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Table 4C9 Selection criteria in rabbits
Traits Comments
Growth rate or weight at slaughter
Meat production Carcass yield
Thigh muscle volume Using computerized tomography
Litter size
Litter weight Reproductive efficiency Individual weaning weight Direct and maternal effects
Number of teats
Longevity Length of productive life
Homogeneity of birth weight Indirect criterion for kit survival Health and welfare Genetic resistance to diseases Mainly digestive disorders
Fibre production Total fleece weight at each harvest (every 80-120 days)
Fur size Live body weight
Fur density Density of fibres per skin unit area
Fur structure and composition Bristliness or guard-hair content Fur priming Scoring extent of the moult and hair follicle activity
Arabia. Pedigree selection occurs strictly in spe- • improving the quality of the fibre or fur so that cialized paternal and maternal lines, mainly using it can be processed into superior end-products the BLUP methodology. Genetic improvement is and thus attract a higher unit value. diffused from the breeding nucleus into the wider Functional and adaptation traits (reproduc- population via pyramidally structured multiplica- tion, health, growth and maternal traits) are also tion units. Some public research organizations are taken into consideration, but to a lesser extent deeply involved in meat-rabbit breeding, either than in meat production. BLUP methodology is providing scientific and logistic support to private used for genetic evaluation. Programmes are breeding companies (e.g. the Institut National de mainly located in France and China and are oper- la Recherche Agronomique in France) or directly ated by public organizations and some private managing breeding nuclei (e.g. the Polytechnic companies. University of Valencia and Instituto de Investi- The main objectives of selection in com- gación y Tecnología Agroalimentarias in Spain and mercial rabbit lines (i.e. prolificacy and feed the University of Kaposvar in Hungary). efficiency) have not changed in recent years. In contrast to meat-rabbit breeding, fibre (Rafat However, research has provided information on et al., 2008) and fur production in rabbits is based the feasibility of improving traits such as the on pure-bred selection in specialized breeds: length of does’ productive lives (Sanchez et al., Angora for fibre and Rex for fur. Genetic improve- 2008; Larzul et al., 2014), homogeneity of litter ment of fibre and fur production in rabbits targets: weight at birth (Garreau et al., 2008a), carcass • increasing production of fibre or fur to give dressing percentage, heat tolerance (Sanchez greater economic return per animal and pro- and Piles, 2013), resistance to pasteurellosis and duction unit; and diseases causing digestive disorders (Garreau
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et al., 2008b; Eady et al., 2007), and efficient the biological processes underlying important production of semen doses for AI (Tusell et al., traits. 2012). As a consequence, new breeding pro- The design and implementation of recording grammes targeting kit and doe survival, carcass systems for specific difficult-to-measure traits, dressing percentage and digestive health have such as individual feed intake, would allow been implemented in commercial lines, with consideration to be given to new breeding successful results. In addition, new selection cri- strategies for improving the efficiency of pro- teria for improving prolificacy (ovulation rate duction. The development of advanced statist- and litter size – Ziadi et al., 2013) and feed effi- ical models and procedures involving, inter alia, ciency (residual feed intake and daily weight direct and indirect effects (e.g. social effects gain under feed restriction – Drouilhet et al., for traits recorded in animals raised in groups), 2013) have also been introduced. Results from genetic × environment interactions and the use experiments on Angora rabbits have shown of information from cross-bred animals in com- that selection for total fleece weight, a simple mercial farms is also a major issue for future trait that is easy to measure on-farm, positively research. affects both quantitative and qualitative traits in wool production (Rafat et al., 2007; Rafat et al., 2008). 5 Breeding programmes in Future priorities in rabbit breeding relate to low-input systems the intensification of production to cope with the expected growth in global demand for animal The first SoW-AnGR provided an overview of protein in a way that is economically, environ- the various challenges involved in establishing mentally and socially sustainable and to the need breeding programmes (including those involv- to adapt to changing environmental conditions. ing cross-breeding) in low-input systems.15 It Breeding for improved disease resistance (robust- highlighted the importance of involving live- ness) has become a major challenge because of stock keepers from the outset in the planning the effect that some infectious diseases (e.g. and implementation of such programmes and of epizootic rabbit enteropathy and pasteurellosis) paying attention to traits related to the efficiency have been having on efficiency and productivity, of production (i.e. taking input use into account the safety of rabbit products, animal welfare and rather than simply targeting increased output). public perceptions of rabbit production. Research This subsection provides an updated account, objectives are increasingly focusing on quanti- beginning with a short description of the main fying the genetic control of the host–pathogen options currently available for establishing breed- interactions, as well as on identifying SNPs associ- ing programmes in low-input systems and then ated with resistance. addressing the specific considerations that need The recent development of high-throughput to be taken into account in the implementation genomic tools and statistical methods for dealing of such programmes. with massive amounts of data could allow select- ion based on SNPs associated with resistance 5.1 Breeding strategy options traits. The rabbit genome has been sequenced As noted above (Subsection 3), a genetic improve- (Carneiro et al., 2014) and the implement- ment strategy can involve selection among ation of gene-based and genomic selection is an breeds, cross-breeding and/or within-breed emerging area of research in rabbit breeding. Its selection. In a low-input system it is particularly suitability in this species is still under discussion. important to ensure that any breeds introduced As with other species, the use of genomic inform- ation could also lead to better understanding of 15 FAO, 2007a, pages 405–419.
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and any crosses produced are able to thrive itions and in terms of eroding the existing locally in the local production environment. As in all adapted animal genetic resources. Uncontrolled circumstances, breeding strategies for low-input cross-breeding is regarded as major threat to systems should be based on careful assessments animal genetic resources in many countries (see of the current state of the targeted production Part 1 Section F). systems, the trends affecting them and the needs Meta-analyses of studies on dairy and beef and objectives of the local livestock keepers and cattle in tropical environments (Burrow, 2006; of society more broadly (FAO, 2010). Galukende et al., 2013) have shown that in most A properly implemented cross-breeding scheme cases F1 crosses perform better than other gen- offers the opportunity to combine the positive otypes. For instance, Galukande et al. (2013) attributes of two different breeds. In a low- showed that 50 percent B. taurus × B. indicus input system, this will often involve an attempt to cross-breeds had on average 2.6, 2.4 and combine the adaptive qualities of a locally adapted 2.2 times higher milk yield than local B. indicus breed with the higher production potential of an in highland, tropical wet and dry and semi-arid exotic breed. There are several different types of climatic zones, respectively. However, harsher breeding schemes that can be considered: production environments can lead to increasing • pure-bred or terminal crossing systems – problems with a lack of adaptedness (including mating of animals from separate pure-bred reproductive problems) in cross-bred animals populations over one or two generations to and particularly in exotic parental lines. When produce a generation of cross-bred animals evaluating a programme involving cross-breed- that “terminates” the system, i.e. has desir- ing with exotics, it is therefore important to able qualities in production terms, but is not consider a multiyear time horizon, accounting used for breeding; both for the lifetime profitability of individual • rotational crossing – producing an initial animals (i.e. considering input costs, lifespan, two-way cross and then, in each subsequent reproductive success, etc., in addition to product generation, alternating the sire breed used output) and the costs of maintaining the various (can include the incorporation of additional populations needed to keep the programme breeds); and operating in the long term. • creation of a new synthetic breed – cross- Improving a breed through straight breeding ing two or more breeds in order to achieve is a long-term commitment. In low-input systems a desired proportion of each, followed by it generally involves either a programme based inter se mating of these animals. on a central nucleus or a community-based The two first options have the advantage breeding programme. Central nucleus schemes of continuously producing a heterosis effect. involve genetic improvement in a nucleus However, they may present logistical difficulties, flock or herd and subsequent dissemination of and maintaining an exotic parental line in low- improved genetic material directly or indirectly input conditions may be problematic (see Serradilla, (via a multiplier layer) into the base population. 2001 for discussion of this issue in goats). As with The scope of the operation is, in principle, the any other kind of breeding scheme, determining whole population of the respective breed. The what is possible in the specific local circumstances nucleus may be “closed” (gene flow occurs in is a key element of planning a cross-breeding strat- one direction only – from the nucleus to the base egy. It has to be emphasized that if cross-breeding population) or “open” (gene flow can also occur efforts are not carefully planned, or if plans are in the opposite direction, i.e. superior animals not properly followed, activities of this kind may from the base population may be used to sup- create serious problems, both in terms of produc- plement the nucleus). ing animals that are not well suited to local cond-
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The advantage of a programme based on has increased in recent years (e.g. Kosgey et al., a central nucleus is that it allows the use of 2006; Mueller, 2006; Pastor et al., 2008; Wurzinger advanced genetic evaluation methods (BLUP) et al., 2008; Tadele et al., 2010; Valle Zárate and and hence rapid genetic progress. Performance Markemann, 2010; Wurzinger et al., 2011; Abegaz et and pedigree recording is usually limited to al., 2013). A review prepared by Mueller et al. (2015) the nucleus. A weakness is that such schemes describes eight case studies of community-based depend heavily on organizational, technical programmes. An overview of the main character- and financial support (Mueller et al., 2015). istics of these programmes is provided in Table 4C11, They also tend to be hierarchical rather than along with some additional examples. participatory in their planning and operation Experience indicates that establishing a suc- and hence often fail adequately to address the cessful community-based programme requires needs of livestock keepers in low-input systems the involvement of a range of stakeholders (live- (e.g. Gizaw et al., 2013). Over the years, schemes stock keepers, local government, NGOs, univers- of this type, entirely managed and controlled ities, etc.) (Wurzinger et al., 2013a). Adopting a by governments or state operators – and with participatory approach from the start of the plan- minimal, if any, participation on the part of live- ning process will help to ensure commitment and stock keepers – have been established in many ownership and to clarify the roles and responsibil- developing countries (Wurzinger et al., 2013a). ities of the various stakeholders involved. A large proportion of them have failed. Such schemes have proven to be effective only when 5.2 Specific challenges involved governments and other funding agencies in establishing and operating have a long-term perspective and continue to breeding programmes in low- provide technical and financial support until the input systems programmes have achieved self-sustainability The recording scheme of a community-based (Wurzinger et al., 2011). breeding programme needs to be cost-effective Community-based schemes (Mueller; 2006; and should not be too elaborate for local condi- Mueller et al., 2015) operate at the scale of a tions (Wurzinger et al., 2011). Performance testing single community rather than at the scale of the at central stations and visual appraisal in herds are whole breed population. As well as operating commonly used in recording schemes for meat and at community scale, they are also community- fibre production. A milk-recording scheme is more based in the sense that livestock keepers are challenging, as it requires repeated measurements. the main players in their design and operation, Timely feedback is needed in order to maintain although support of various kinds may be provided livestock keepers’ interest in the recording scheme by external stakeholders. A number of different (Wurzinger et al., 2011; Iñiguez et al., 2013). types of structure are possible (Haile et al., 2011; As most livestock keepers are interested in Gizaw et al., 2013). Schemes may operate with improving many different traits, the use of an or without a nucleus and, if present, the nucleus economic selection index (see Subsection 3) to may be open or closed. The nucleus may also have determine which animals should be used for a “dispersed” character, i.e. rather than being breeding is generally recommended (e.g. Gizaw maintained as a single unit the nucleus animals et al., 2010). In the case of breeding schemes are maintained in several different flocks or based on dispersed nuclei, livestock keepers will herds. Table 4C10 contrasts the typical character- need to be more involved in the implementation istics of conventional and community-based of the animal identification and recording activi- breeding programmes. ties, and they will also need to agree on arrange- The number of community-based breeding ments for sharing males to establish genetic link- programmes implemented in low-input systems ages between herds/flocks.
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Table 4C10 Characteristics of conventional and community-based livestock breeding programmes
Characteristic Conventional breeding programme Community-based breeding programme
Geographical limit Regional – inter-regional Communities
Market orientation Commercial Subsistence – commercial
Agent of programme Breeding company – breeder organization Livestock keeper – breeder
Breeding objective Defined by company – breeder organization Defined by breeder – livestock keeper
Breeding structure Large scale, pyramidal Small scale, one or two tiers
Genetic resources International Local
Infrastructure Available Limited
Management Intensive – high input Extensive – low input
Risk taker Company – livestock keeper organization Livestock keeper
Decision on share of benefits Variable Livestock keeper
Source: Mueller et al., 2015.
Table 4C11 Selected community-based breeding programmes
Country Species Main Period Location Total animal Breeding Key references product population system Mueller, 1995; Argentina Goats Mohair 1987 – ongoing Dispersed 62 000 Open nucleus Lanari et al., 2009; Mueller, 2013b Bolivia Llamas Fibre 2008 – 2012 Villages 2 500 Open nucleus Wurzinger et al., 2008 (Plurinational State of) Haile et al., 2011; Ethiopia Sheep Meat 2009 – ongoing Communal 10 000 All flock Duguma et al., 2011; Mirkena et al., 2012 Iran Goats Cashmere 2009 – ongoing Nomad 2 800 Open nucleus Mueller, 2013 (Islamic Republic of) Dispersed Kenya Goats Dairy 1997 – ongoing 20 000 Open nucleus Ojango et al., 2010 groups
Mexico Goats Dairy 2007 – ongoing Village 200 All flock Wurzinger et al., 2013b
Valencia-Posadas Mexico Goats Dairy 2000 – ongoing Villages 1 500 Open nucleus et al., 2012 Mueller et al., 2002; Peru Sheep Wool 1996 – ongoing Communal 160 000 Open nucleus Mueller, 2013 Dispersed Multilevel Uganda Chickens Eggs 2003 – ongoing >120 000 Roothaert et al., 2011 groups cross-breeding Valle Zárate and Viet Nam Pigs Meat 2000 – ongoing Villages 700 Open nucleus Markemann, 2010; Roessler et al., 2012
Sources: Mueller et al., 2015; Valencia-Posadas et al., 2012.
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Box 4C5 GENECOC – the breeding programme for meat goats and sheep in Brazil
In 2003, the Brazilian Agricultural Research in the implementation of a community-based Corporation (EMBRAPA) launched the Breeding programme, including in the definition of breeding Program for Meat Goats and Sheep – GENECOC*. Up objectives, performance testing in young rams and the to that time, there had been no structured breeding organization of monthly planning meetings. programmes for goats and sheep in Brazil and there Today, in addition to its activities in Brazil, GENECOC was a lack of recorded information on the performance also participates in projects in other countries, of these species. including Ethiopia and the United States of America. GENECOC is a genetic advisory service that aims to The principal impacts of the programme have encourage and assist programme participants with been in adding value to locally adapted sheep and record keeping in their flocks and the generation goat breeds and optimizing their use while respecting of reliable information that can be used in selection environmental concerns. Experience has shown that it decisions. GENECOC targets all kinds of animals and is important to identify and involve key stakeholders, breeders, focusing particularly on locally adapted to use a well-organized and well-trusted data- breeds and low-input systems. Breeding strategies are collection system backed-up by government funding matched to local production systems. However, the and, when designing breeding objectives and selection main feature of the scheme is the use of web-based criteria, to consider not only traits related to market software to record, organize, store and manage the trends, but also traits that livestock keepers judge information generated. The system includes tools for to be important. Future plans include expanding selecting animals for total genetic merit through the activities to include additional sheep and goat breeds use of (breed specific) selection indexes and identifying and expanding the system for multiplying improved the set of matings that maximizes the genetic gain of animals to cover additional local production systems. the flock, while controlling inbreeding. One important action undertaken under the programme targets the Morada Nova sheep, a Provided by Raimundo Nonato Braga Lôbo. For further information see Lôbo et al. (2010); Lôbo et al. (2011) and locally adapted breed that was once at risk of Shiotsuki et al. (2014). extinction. Participatory methodologies are used *http://srvgen.cnpc.embrapa.br/pagina/english/principal.php
Morada Nova sheep in Northeast region of Brazil Weighing Morada Nova lambs
Photo credit: Olivardo Facó. Photo credit: Olivardo Facó.
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Box 4C6 Establishing a cross-breeding scheme for dairy goats in the United Republic of Tanzania
Toggenburg goats were introduced into Babati, United TOBRA started with 249 000 shillings*** in the Republic of Tanzania, as the result of a Farm Africa form of registration fees and other contributions. As project in 1990. The project originally brought in four of 2007, it had more than 12 000 000 shillings. It has pure-bred Toggenburg does and one Toggenburg employed a treasurer and manages the costs of its buck and established a women’s group that operated meetings and agricultural shows at district, region, a goat-in-trust* scheme. Because of the poor zonal and national levels. performance of the women’s group, a sister project The main objectives in forming the association were: was initiated, under which commercial groups (groups • to increase milk productivity from goats through of goat keepers raising animals for commercial as well cross-breeding Toggenburg and indigenous as subsistence purposes) were established through a goats, taking advantage of the high milk pro- goat-in-trust scheme. duction of the former and the disease resistance In 1997, the commercial goat raisers formed of the latter; the Toggenburg Breed Association (TOBRA) as a • to produce pure Toggenburgs so that genetics commercial dairy goat production association. In 1998, could be exchanged with farmers from Kenya TOBRA was registered by the Ministry of Home Affairs. and Uganda; and At the time it had only 12 members. In 2001, TOBRA • to improve the income of the members though established eight dairy goat production groups. By the selling milk and live animals (pure-breeds and end of 2007,** the number of groups had expanded crosses). to 52, involving 188 farmers, with an average of eight goats each. People were initially very reluctant to join *A scheme in which the loan of a goat is paid back in the form of the groups, but following sensitization efforts they another goat that can be passed on to another participant. began to join voluntarily. Association members raise **This is the most recent date for which published figures are available. Since then the farmers have continued their goat breeding and pure Toggenburgs, 75 percent Toggenburg crosses and production activities under the supervision of the local extension services. 50 percent Toggenburg crosses. The cross-bred animals *** Equivalent to approximately US$400 at the time. Provided by Yacobo Msanga, National Coordinator for the Management are carefully evaluated by analysing their pedigrees of Animal Genetic Resources, the United Republic of Tanzania. and productive and reproductive performances. For further information see Msanga and Bee (2006) and Bee et al. (2006).
Participatory approaches to setting breed- prerequisites for the long-term sustainability of ing goals and identifying traits to be recorded a breeding programme. have been recommended as a means of pro- Controlling inbreeding can be a major issue in moting the involvement of livestock keepers in breeding schemes in low-input systems, especially the operation of community-based programmes in closed central nucleus schemes and in commu- (Gizaw et al., 2010; Wurzinger et al., 2011). nity-based schemes operating on a limited scale. Potential methods include individual interviews Gizaw et al. (2009) recommend that for an accept- with livestock keepers, workshops with groups able rate of inbreeding, sheep breeding schemes of livestock keepers and exercises involving should include at least 600 ewes and 15 rams. the use of choice cards or the ranking of live Rotation of males between livestock keepers’ animals (e.g. Duguma et al., 2010; Haile et al., herds/flocks or between the nucleus and livestock 2011). More generally, a participatory approach keepers’ herds/flocks can help to limit inbreeding. that engages the various actors involved will The use of sire-reference schemes (i.e. schemes in help ensure their commitment and ownership, which each cooperating livestock keeper agrees
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Box 4C7 Community-driven breeding programmes for locally adapted pig breeds in Viet Nam
Demand for pork in Viet Nam has increased enabling the smallholders to be independent in terms substantially since the 1990s, driven by economic of supplying replacement animals and improving development and urbanization. Although large-scale genetic stocks. Prolific Mong Cai gilts were distributed private enterprises have benefited from subsidies mainly to semi-intensive producers and robust Ban introduced with the aim of expanding exports, sows to less market-oriented smallholders. smallholder farmers still represent the backbone Although some of the collective actions planned of the Vietnamese pig sector, especially in the under the project were successfully implemented – for northern part of the country. To cope with increasing instance, improving the access of rural small-scale competition and quality requirements, market- pig producers to veterinary services and establishing oriented smallholders increasingly raise modern multipronged market outlets – the attempt to pig lines and hybrids, often in unsystematic cross- establish a community-based stratified cross-breeding breeding schemes. This has reduced the population scheme proved to be difficult. The organizational sizes of autochthonous breeds and pushed them into structures of a cross-breeding scheme must be remote areas. accompanied by a well-balanced business plan that Under a pilot project implemented by German accounts for the greater burden placed upon nucleus and Vietnamese research institutions in collaboration breeders. In this example, although farmers preferred with the provincial veterinary department and to use pure-bred dam lines, and Mong Cai breeders private partners (funded by the German Research could therefore obtain a good price for sows, this was Foundation, DFG), a community-driven pig-breeding and marketing programme was established in the Mog Cai sow and fatteners mountainous Son La province in northwestern Viet Nam. The farmers’ pig-breeding cooperative involves ten villages, representing communities with different resource endowments, production objectives and consequently different requirements from their pig genetic resources. Initially, pure-bred indigenous Mong Cai and Ban gilts were distributed among 179 cooperative members and a revolving fund was established with the aim of
Ban sow and litter
Photo credit: Kerstin Schöll. Photo credit: Kerstin Schöll. (Cont.)
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Box 4C7 (Cont.) Community-driven breeding programmes for locally adapted pig breeds in Viet Nam
not sufficient to compensate them for the low prices in these niche markets, farmers will probably continue obtained for pure-bred Mong Cai finishers. The market pure-breeding the Ban breed and this will create a for the latter completely collapsed because of rapid pool of sow replacements for farmers that exclusively shifts in customer preferences towards leaner pork. practice cross-breeding. In the future, farmers will probably turn to breeding In conclusion, this case illustrates how a self- centres or commercial farms to obtain pure-bred Mong sustained community-driven pig breeding and Cai sow replacements. In contrast, marketing of pure- marketing programme can only sustainably contribute bred Ban products via a short supply chain, avoiding to rural development and breed conservation if it can a large number of intermediaries, proved to be be flexibly adapted to market conditions. successful in linking remote resource-poor Ban keepers to highly remunerative specialty markets in the Red Note: This box updates Box 89 of the first SoW-AnGR (FAO, 2007a). River Delta. Because of the prices that can be realized Provided by Philipp Muth and Anne Valle Zárate.
to use sires or semen from a group of high-quality challenge. This is true for both output and input so-called “reference” sires – Simm et al., 2001) in markets (Haile et al., 2011). Although a multi- the implementation of dispersed-nucleus schemes trait breeding objective is likely to be optimal, may reduce inbreeding in the short term but such breeding programmes are usually designed increase it in the long term at herd level. Systems so as to increase production to some degree. In for regularly providing males from other herds/ theory, the increased production may be used flocks are particularly important in situations simply to improve food security and nutrition where introducing animals (or semen or embryos) within a subsistence system, but more commonly from outside is not feasible. the programme is designed so as to generate When calculating the economic efficiency of a excess product that can be marketed. Genetic given breeding programme, it is important to take improvement requires investment of human and into account both the tangible and the intangible financial capital, and these inputs will be wasted benefits that accrue to various different groups if no market channel is available. Improvements of stakeholders (livestock keepers, retailers, to productivity achieved by breeding programmes government, etc.). Advice on how to evaluate in low-input systems are rarely due only, or even investment decisions in breeding programmes is primarily, to genetic improvement. Successful provided in FAO’s guideline publication Breeding genetic improvement programmes are usually strategies for sustainable management of animal complemented by enhanced veterinary care and genetic resources (FAO, 2010). Computer simul- nutrition, so reliable access to these resources is ation of the breeding programme can be used also important. Organization of livestock keepers to predict changes in targeted traits and their into associations or cooperatives to coordinate sensitivity to changes in various factors affecting activities and increase access to input and output genetic response (e.g. Gebre et al., 2014). markets is usually beneficial. In the longer term, Finally, in addition to genetic considerations, establishing a marketing system for superior factors related to market chains usually have a major breeding stock will also be beneficial, as it will influence on the success of breeding programmes provide breeders with another source of income in low-input environments. The absence of effec- and incentive for genetic improvement. tive marketing chains will present a significant
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5.3 Genomics and future strategies, and the need for a long-term perspec- developments tive in planning and implementation (Rothschild As discussed in Subsection 2, techniques that and Plastow, 2014). enable the use of genomic information in animal breeding have advanced greatly in recent years, particularly in the case of cattle, pigs and poultry. 6 Conclusions and research While these techniques offer major potential priorities benefits, particularly in terms of allowing the selection of animals at earlier ages and reduc- The main advances in breeding programmes and ing generation intervals, there are several con- related technologies over recent years have been cerns regarding their use in low-input produc- in the application of genomic information, par- tion systems. Effective use of these techniques ticularly in high-input production systems. Geno- requires more than just vague information on typing costs have dropped precipitously and for the phenotypes and genotypes of the breeds some species nearly all of the important selection concerned. A reliable data-recording scheme is candidates are genotyped, as have been the major absolutely necessary in order to provide the basis ancestors from which genetic material is avail- for associating genotypes to phenotypes. Such able. Genomic selection increases the accuracy of schemes are lacking in most low-input situations. EBVs, particularly for those animals for which no There are nevertheless steps that can begin to be phenotypic data are yet available. The impact on taken towards the use of these new technologies the commercial dairy breeding industry has been in developing countries. Efforts to identify genes revolutionary. Progeny testing now plays a minor or genomic regions associated with adaptation role. Breeding goals have seen various adjust- or variation in production traits in harsh envi- ments. In particular, greater emphasis is now ronments need to be stepped up in developing being placed on profit, rather than output, and countries and in low-input smallholder and past- therefore on health, survival and other traits that oralist production systems (Rothschild and Plastow, influence production costs. 2014). Once relevant genes have been charac- The genomic revolution has yet to affect devel- terized, livestock populations can potentially oping countries to a significant degree. Accurate be improved through genetic introgression or genomic selection depends on the availability of gene-assisted breeding programmes. With regard phenotypic data, which are usually lacking in the to genomic selection more specifically, implemen- low-input production systems typically found in tation requires the establishment of training and developing countries. Nevertheless, the situation validation populations, in which both pheno- in these countries has not remained static. Formal types and genotypes are recorded, so that the pre- breeding programmes, usually community-based, diction model can be established. Indigenous pop- have become more common and are improving ulations with low linkage disequilibrium gener- the productivity of animals and livelihoods of ally do not meet these requirements (Akanno et their keepers. However, significant work is still al., 2014). The use of widely used international required. Animal identification and pedigree and transboundary breeds as reference populations performance recording need to be expanded. for genomic selection in locally adapted breeds This is necessary even to take advantage of trad- seems to have little or no value, except perhaps itional approaches to breeding, let alone genomic in cross-bred populations, but this has not been selection. studied. Any attempt to implement genomic Little if any direct progress has occurred since improvement programmes needs to take into the first SoW-AnGR was prepared in terms of account the need for adequate infrastructure, determining the underlying genetics of pheno- technical skills, policies and communication typic adaptation to the environment. However, the
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tools with which to do this are in place. Genomic • developing economically viable means of analysis should allow breeders to determine actual including traits of increasing consumer genetic by environment interactions, although a concern in breeding goals, including traits tremendous amount of work remains to be done with uncertain economic value; in order to obtain the phenotypic information • developing strategies for improving needed to accurately predict such interactions. disease resistance without compromising Future research will need to address the need production; for new modes of production that can help • developing phenotype definitions for novel meet the expected growth in global demand for traits; animal protein in ways that are economically, • establishing standard phenotypic trait environmentally and socially sustainable and ontologies encompassing production traits, address the need to adapt livestock production disease traits and other welfare traits and to changing environmental conditions. In other environmental sensitivity; words, efficiency of production will be an increas- • developing tools to estimate and exploit ingly important consideration. This will include a non-additive genetic variation; wide range of efficiencies and involve not only • developing social-interaction models includ- increasing product yield per unit of input, but ing, male–female interactions, to facilitate also addressing negative effects such as environ- the improvement of reproductive, health and mental damage (see Box 4C8 for an example). welfare traits; Improvement in the use of feed resources, repro- ductive efficacy and prolificacy, and animal health Genomics and other “-omics” will be key topics for research, both in developed • characterizing the genome sequences (and and in developing countries. variation therein, including epigenetic trans- The following list of research priorities draws missible variants) of species, populations and on the Strategic Research Agenda of the Sus- individuals; tainable Farm Animal Breeding and Reproduc- • developing methods for optimal incorpo- tion Technology Platform, an extensive review of ration of genomic information in breed- research priorities in livestock breeding in Europe ing-value estimation; (FABRE TP, 2011). • developing proteomic and immunological metabolomic technologies for high-through- Selection to balance functionality and put analyses; production • developing schemes incorporating large- • improving knowledge of the genetics of: scale genotyping at embryo level; - disease resistance, resilience and immune • metagenomic sequencing of gastro-intestinal response; microbial communities; - host–pathogen interactions; - gut functionality and its relationship with Bioinformatics and biostatistics gut microbiota in different environments; • developing statistical programming tools rel- - emission of methane and production of evant to new traits and new phenotypes; other greenhouse gases; • supporting continued annotation and main- - variation in digestion of specific amino tenance of public genome databases; acids and phosphorus – along with • developing scalable bioinformatics tools to improving knowledge of nutrient (e.g. handle high-throughput data (e.g. genomic amino acid) requirements under different selection procedures or inference of genome- production conditions; and wide diversity parameters); - uniformity;
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Box 4C8 Genetic selection for reduced methane production – a future tool for climate change mitigation
The expanding world human population will require forces with the International Committee for Animal greater food production within the constraints of Recording (www.icar.org) to develop consensus on increasing societal pressure to minimize impact on protocols for the collection of methane production the environment. Animal breeding has in the past data, with the aim of facilitating the harmonization achieved substantial reductions in environmental and combination of existing and future data obtained load per unit of product, despite no explicit inclusion from different countries and with different collection of environmental load in breeding goals. Higher methods. The project will also facilitate discussions gains can be expected if breeding goals focus among experts aiming to identify possible predictor more specifically on environmental objectives. One traits for methane production (e.g. biomarkers in milk) important objective is to reduce the amount of that could be easily exploited. Methane production is enteric methane – a greenhouse gas with a warming currently not directly included in any national cattle potential 25 times that of carbon dioxide – produced breeding objective anywhere in the world. This is not by ruminants. However, a successful breeding strategy only because of a lack of sufficient data with which requires measurements on a large population of to make selection decisions, but also because of a lack animals. To facilitate genetic selection for reduced of consensus on how to optimally include methane methane production, it would therefore be highly production in a breeding objective. The project will desirable to combine individual national datasets to develop standards for expressing methane production, produce a multicountry database. However, data are taking into account the advantages and disadvantages collected using different protocols, and combining of expressing methane per unit (digestible) feed and them requires intensive consultation among per unit of consumable product (i.e. milk and/or meat) contributing scientists across a range of disciplines. and also the need to consider the time horizon of More importantly, however, scientists planning to emissions via a life-cycle assessment and to ensure undertake future studies on methane production have that selection for low emissions does not compromise not yet agreed protocols for how to proceed with the production efficiency. collection of data. The networks of METHAGENE (www.methagene. eu) and ASGGN (www.asggn.org) have joined Provided by Yvette de Haas.
• developing means of exploiting distributed Breeding strategies in low-input production computing technologies (GRID, Cloud) for systems more effective data storage, sharing, integra- • improving methods for planning and imple- tion and analysis; menting breeding strategies in production • improving the use of genomic sequences for systems where there is little or no organiz- predicting genetic values and detection of ational infrastructure, including means of de novo mutations; determining where breeding programmes • developing transcriptomic tools (arrays and are feasible and appropriate and how they RNA-seq); can be adapted to local circumstances; • exploiting the use of telecommunications and informatics technologies to improve data collection;
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• improving strategies for the establishment Conference, January 14–18 2012, Sandiego, CA, of stable cross-breeding systems; and USA. (Abstract P0555) (available at https://pag.con- • developing simulation tools to predict the fex.com/pag/xx/webprogram/Paper3932.html). consequences of introducing exotic breeds Agerholm, J.S., Bendixen, C., Andersen, O. & into local populations (as part of genetic Arnbjerg, J. 2001. Complex vertebral malformation impact assessment). in Holstein calves. Journal of Veterinary Diagnostic Investigation, 13: 283–289. Improving research cooperation Agerholm, J.S., McEvoy, F. & Arnbjerg, J. 2006. Research in the field of animal breeding could be Brachyspina syndrome in a Holstein calf. Journal of strengthened by promoting greater cooperation Veterinary Diagnostic Investigation, 18: 418–422. among the various stakeholders involved. Rele- Aguilar, I., Misztal, I., Johnson, D.L., Legarra, A., vant measures include: Tsuruta, S. & Lawlor, T.J. 2010. Hot topic: a unified • promoting even greater collaboration approach to utilize phenotypic, full pedigree, and ge- between the breeding industry, academia nomic information for genetic evaluation of Holstein and the public sector; final score. Journal of Dairy Science, 93: 743–752. • exploring the feasibility of capturing and Akanno, E.C., Schenkel, F.S., Sargolzaei, M., using production data from commercial pro- Friedship, R.M. & Robinson, J.A. 2014. Persistency ducers (e.g. encouraging the use of commer- of accuracy of genomic breeding values for different cial populations for high-resolution genetic simulated pig breeding programs in developing analyses); and countries. Journal of Animal Breeding and Genetics, • developing data-sharing policies that allow 131: 367–378. the value extracted from complex datasets to Amer, P.R., Nieuwhof, G.J., Pollott, G.E., Roughsedge, be maximized without compromising legiti- T., Conington, J. & Simm, G. 2007. Industry benefits mate commercial interests. from recent genetic progress in sheep and beef popu- lations. Animal, 1(10): 1414–1426. Astruc, J.M. 2014. Performance recording of dairy she- References ep. In Proceedings of the 38th ICAR Session, 28–31 May, 3012, Cork, Ireland (presentation available at Abegaz, S., Sölkner, J., Gizaw, S., Dessie, T., Haile, http://tinyurl.com/nzs9d7s). A. & Wurzinger, M. 2013. Description of goat Avendano, S., Watson, K. & Kranis, A. 2010. production systems and morphological characteristi- Genomics in poultry breeding – from utopias to de- cs of Abergelle and Western low-land goat breeds in liverables. In Proceedings of the 9th World Congress Ethiopia: implications for community-based breeding on Genetics Applied to Livestock Production, programmes. Animal Genetic Resources, 53: 69–78 Leipzig, Germany, 1–6 August 2010 (available at (available at http://www.fao.org/docs/eims/up- http://www.kongressband.de/wcgalp2010/assets/ load//314794/I3445Tri.pdf). pdf/0049.pdf). Abell, C.E., Dekkers, J.C., Rothschild, M.F., Mabry, Avendano, S. & Kranis, A. 2012. Genomics in poultry bre- J.W. & Stalder, K.J. 2014. Total cost estimation for eding – into consolidation phases. In Proceedings XXIV implementing genome-enabled selection in a mul- World’s Poultry Congress, 5–9 August 2012 Salvador, ti-level swine production system. Genetics Selection Bahia, Brazil (available at http://www.facta.org.br/ Evolution, 46: 32. wpc2012-cd/pdfs/plenary/Santiago_Avendano.pdf). Adams, H.A., Sonstegard, T., VanRaden, P.M., Null, Baloche, G., Legarra, A., Sallé, G., Larroque, H., D.J., Van Tassell, C. & Lewin, H. 2012. Identification Astruc, J.-M., Robert Granie, C. & Barillet, F. of a nonsense mutation in APAF1 that is causal 2014. Assessment of accuracy of genomic prediction for a decrease in reproductive efficiency in dairy for French Lacaune dairy sheep. Journal of Dairy cattle. In Proceedings Plant and Animal Genome XX Science, 97(2): 1107–1116.
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THE second report on t he state OF THE WORLD'S ANIMAL GENETIC RESOURCES FOr FOOD AND AGRICULTURE 495 Section B: Characterization, inventory and monitoring Author: Daniel Martin-Collado, Dafydd Pilling Reviewers: Workneh Ayalew, Kathiravan Periasamy, Michèle Tixier-Boichard Section C: Breeding programmes Author: Daniel Martin-Collado Reviewers: Vlatka Cubric Curik, Olaf Thieme Section D: Conservation programmes Author: Daniel Martin-Collado Reviewer: Kor Oldenbroek Section E: Reproductive and molecular biotechnologies Author: Daniel Martin-Collado Reviewer: Oswin Perera Section F: Legal and policy frameworks Authors: Dafydd Pilling, with contributions from Bendik Elstad, Dan Leskien, Irene Kitsara, Brittney Martin and Elżbieta Martyniuk Reviewers: Harvey Blackburn, Olivier Diana, Dan Leskien, Oliver Lewis, Sipke Joost Hiemstra, Gigi Manicad, Arthur da Silva Mariante, Sergio Pavon
Part 4 THE STATE OF THE ART Section A: Surveying, monitoring and characterization Authors: Paul Boettcher, Beate Scherf, Reviewers: Workneh Ayalew, Xavier Rognon Section B: Molecular tools for exploring genetic diversity Authors: Mike Bruford, Grégoire Leroy, Pablo Orozco-terWengel, Andrea Rau, Henner Simianer Reviewers: Bertrand Bed’Hom, Christine Flury, Catarina Ginja, Johannes Lenstra, Michael Stear Section C: Breeding strategies and programmes Authors: Peter Amer, Daniel Allain, Santiago Avendano, Manuel Baselga, Paul Boettcher, João Dürr, Hervé Garreau, Elisha Gootwine, Gustavo Gutierrez, Pieter Knap, Eduardo Manfredi, Victor Olori, Rudolf Preisinger, Juan Manuel Serradilla, Miriam Piles, Bruno Santos, Kenneth Stalder Reviewers: Hélène Larroque, Tadele Mirkena, Joaquin Pablo Mueller, Julie M.F. Ojango, Mauricio Valencia Posadas Section D: Conservation Authors: Harvey Blackburn, Paul Boettcher, Kor Oldenbroek Reviewers: Andréa Alves do Egito, Jesús Fernández Martín, Sipke Joost Hiemstra, Samuel Rezende Paiva, Geoff Simm Section E: Economics of animal genetic resources use and conservation Authors: Workneh Ayalew, Adam Drucker, Kerstin Zander Reviewer: Giovanni Signorello
Part 5 NEEDS AND CHALLENGES Author: Beate Scherf
The manuscript was further reviewed by Stuart Barker (Parts 1 and 2), David Notter (Parts 1, 2, 4 and 5), David Steane, Akke J. Van der Zijpp (Parts 1, 2 and 5). All the officers of FAO’s Animal Genetic Resources Branch also contributed to the reviewing process.
xxv Recommended citation: FAO. 2015. The Second Report on the State of the World’s Animal Genetic Resources for Food and Agriculture, edited by B.D. Scherf & D. Pilling. FAO Commission on Genetic Resources for Food and Agriculture Assessments. Rome (available at http://www.fao.org/3/a-i4787e/index.html).
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