Lecture 11: Industry services for Sheep Genetics

Transcription

1 Lecture 11: Industry services for Sheep Genetics Luke Stephen & Sam Gill Learning objectives At the end of this topic you should: Understand and describe the way in which Sheep Genetics has improved sheepmeat production Understand the relevance of genetic correlation to ASBVs Be able to separate environmental from genetic effects Understand the measures of accuracy for ASBVs and FBVs 11.1 Introduction Sheep Genetics (SG) is the national genetic information and evaluation service for both the meat and wool sectors of the sheep industry. SG has been developed jointly by Meat & Livestock Australia (MLA) and Australian Wool Innovation Limited (AWI), together with industry. Sheep Genetics has been developed to utilise the world s most comprehensive sheep genetic database and evaluation service for the Australian sheep industry underpinned by a best practice quality assurance system. SG acts as a resource for sheep genetic information and improvement through which commercial producers, ram breeders and service providers can interact. It will supplement the skills of ram breeders and sheep classers by evaluating current measurements and providing further information, often on traits not assessable by the eye e.g. reproduction, carcase and internal parasite characteristics. SG works with federal and state agencies, breed societies, livestock agents, sheep classers, agricultural advisors and veterinary consultants, fleece testing businesses and genetic service providers. It functions as Australia s sheep genetic information database for all stakeholders to use. SG is also an evolving data system that is able to be upgraded to accommodate the new traits such as eating quality and genomic technologies that are due for implementation. MERINOSELECT for Merino breeders and commercial wool producers. MERINOSELECT has been operating since 2005 bringing together the numerous Merino evaluation services that were running under one banner. LAMBPLAN continues as the brand name under which genetic information is delivered to Terminal, Maternal and Dual Purpose sire breeders and commercial lamb and sheep producers Overview of Sheep Genetics Sheep Genetics supplies ram breeders and commercial lamb and sheep producers with an estimate of the value of an animal s genes to contribute to the productivity and profitability of their lamb and sheep enterprises. It provides flexibility enabling ram breeders to concentrate on the traits considered important to their breeding objective and the requirements of their clients. LAMBPLAN information assists ram buyers to choose rams that will produce slaughter lambs or replacement breeding ewes that meet their breeding objectives, while MERINOSELECT provides information for ram buyers to buy Merino rams to either produce wool or be used as a dual purpose animal. For example, using LAMBPLAN, a lamb producer wanting to increase the weight and decrease fatness in his or her trade or export lambs can select rams that have genes that meet these criteria. Similarly a 1st cross breeder can select a ram that will produce daughters that have higher fertility and produce heavier lambs at weaning. If you consider that a ram contributes half of the total genetics of lambs and 1st cross ewes, you start to realise the potential of having such a high level of control over which rams are used. LAMBPLAN currently performs two different forms of analysis for the meat industry: WOOL412/512 Sheep Production 11-1

2 Terminal - provides genetic information for use in prime lamb enterprises. It directly compares animals using an across-flock and across-breed analysis. It compares breeds such as the Poll Dorset, White Suffolk, Texel, Suffolk, Dorset and Dorper. Maternal - provides genetic information to aid selection of rams for breeding 1st Cross ewes for use in a dual purpose production system. It compares animals within breed and across-flock. Animals compared within breed include Border Leicesters, Coopworths, Corriedales and SAMMs MERINOSELECT compares across flocks and is limited to comparing within breed only. MERINOSELECT does compare all the different wool types of Merinos in the industry in the one analysis, comparing superfine animals with fine-fine/medium with medium strong. Sheep Genetics provides breeders and producers with information on the value of animals genes in the form of Australian Sheep Breeding Values (ASBVs). ASBVs can be used to identify the best rams or ewes that meet a breeding objective. ASBVs allow producers to evaluate a ram s genetic potential for a range of traits that directly impact on the profitability of the lamb and sheep production business. ASBVs describe genetic differences in production traits in livestock in simple, practical terms. ASBVs are available for growth traits, fat and muscle depth; fleece weight and quality traits; reproductive ability, breech strike and parasite resistance. ASBVs for structural traits (such as jaws, pasterns, and body length) & eating quality traits (Shear force, Intra Muscular Fat & Lean Meat Yield) are currently under development How does Sheep Genetics work? The basic principles underlying animal selection decisions are: Identifying differences between animals for commercially desired traits; and then; Choosing those animals that have the best overall combination of characteristics to achieve the breeding objective. In practice, the process is more difficult than stated because the differences you identify between animals must be genetic if those desirable characteristics are to be passed on to their progeny. You can only utilise the genetic component of the desirable attributes you identify in any animal. The question is "How much of the desirable characteristics you see in an animal is an expression of genetic merit and how much is a result of the environment? ( Environment being all non-genetic influences, primarily related to nutrition). This can be summarised as: Performance = Genes + Environment or more correctly as: Phenotype = Genotype + Environment An example of an environmental effect is the fluctuation in seasonal conditions properties continually encounter. In the stud business feeding plays an important (marketing) role and the confusing effect of environment is no more evident than in the multi-vendor sale ring. A ram s genetic merit is constant irrespective of his condition but unfortunately the market (usually) penalises breeders who may not put as much effort into preparation and finishing. Buying without knowledge of the genetics and the environment is risky. When purchasing better genetics ensure that the management and environment is good enough to allow those better genes to express their potential, but also ensure the performance exhibited is an expression of better genes and not just good management or a better environment! What are Australian Sheep Breeding Values? An Estimated Breeding Value (EBV) is an estimate of the animal s true breeding value. These are used in most animal breeding industries such as the sheep, cattle, dairy, and pig industries, with a high degree of success. The sheep industry uses Australian Sheep Breeding Values (ASBVs) that must meet minimum accuracy and linkage standards before they can be reported. This provides an increased level of quality and confidence in the product that is delivered back to the sheep industry. ASBVs are an estimate of the genetic component of an animal s performance. They do not necessarily reflect the animal's observed performance, which is a combination of both genetic and environmental influences. An ASBV is the difference (+ or -) between an individual animal and the benchmark to which the animal is being compared. For example: an ASBV of +6 for post weaning weight means that the animal is genetically better by 6kg at post-weaning age than the base. Only half of the value of an 11-2 WOOL412/512 Sheep Production

3 ASBV is passed onto the next generation. So in this case an animal with an ASBV for +6, progeny will on average be 3 kg heavier. ASBVs are reported in different terms for different traits. Some traits are reported in actual units of measurement, for example, kg of bodyweight, mm of fat depth or eye muscle depth, microns of fibre diameter, % of lambs weaned. Some traits are reported as a percentage of the average, for example, % greasy or clean fleece weight. ASBVs are always reported in the same units for a given trait, providing a common language to describe genetic potential across the entire sheep industry. This means the same language is used to express growth rate in a Poll Dorset and growth rate in a Merino. Why are ASBVs so useful to breeders? Animal breeders have always sought the best genes from wherever they can find them. Many current breeds are in fact recent mixtures designed to meet changing market requirements by drawing on genetic resources available. This process continues with infusion of genes underway in different breeds of sheep. Effective livestock breeding, for both meat and fibre, relies on the ability of the breeder to select parent animals that have the most desirable set of genes to contribute to their offspring. Any livestock selection decision carries a degree of risk i.e. will a sire s progeny perform as well as their sire has? ASBVs use performance records from the animal in question and from all known and recorded relatives to get the best prediction of genetic merit. Drawing on a wider sample of genes provides a much more reliable prediction. ASBVs have been developed to rank animals on their ability to produce superior progeny for key performance traits including wool quantity and quality, growth, carcase characteristics, reproduction and lamb survival and worm resistance. This value provides producers with an objective measurement to compare potential breeding stock, enabling selection of the most suitable animals. It is important that both seed stock and commercial breeders are encouraged to use ASBVs rather than raw estimates of performance because ASBVs provide a clearer value of the potential for animals to pass on superior genes to their progeny. Remember that animals can only pass their genes on to their progeny. Breeders use ASBVs to identify animals with the best package of genes for each "job" (market specifications) the animal is being selected for: - Terminal sires are selected with emphasis on fast growth and high carcase merit; - Maternal breeds are selected with emphasis on fertility, mothering ability and lambs with high growth and carcase value Merinos are selected for wool quality & quantity, growth, disease resistance, reproduction and carcase value. What traits does Sheep Genetics evaluate? Sheep Genetics is structured to allow ram breeders to measure and evaluate a wide range of commercially important production traits. ASBVs are available in the following core traits: Wool quantity & quality Growth Carcase Reproduction Worm resistance Breech strike resistance ASBVs are available from birth to adult ages (Table 11.1). Ram breeders have the option of selecting the traits that best fit their breeding objectives. Table 11.1: ASBVs by age available through Sheep Genetics (Sheep Genetics 2011). Trait Birth Weaning Post Weaning Yearling Hoggett Adult Weight ü ü ü ü ü ü Muscle & Fat Depth ü terminals only ü ü ü Fleece Traits ü ü ü Scrotal cirumfrence ü ü ü Worm Egg Count ü ü ü ü ü WOOL412/512 Sheep Production 11-3

4 11.4 Calculating ASBVs The skill in breeding sheep for any purpose relies on the ability of the breeder to select parent animals that have a desirable set of genes to contribute to the next generation. ASBVs enable this to be done by estimating the genetic merit of animals for key production traits. This information is presented in simple units of production that specifically identifies those animals that you need for your breeding operation. Accurate pictures of the value of animal genes require three sorts of information (Figure 11.1): Performance data (including performance of all relatives) Knowledge of environmental factors affecting performance, Knowledge of how strongly different traits are inherited (heritability). No-one can actually look at a gene and figure out what it will do - LAMBPLAN simply uses a range of information to help identify those animals with the best genes for the production system and market. Figure 11.1: ASBVs use information from a number of sources to improve accuracy (Sheep Genetics 2011). The performance of an individual animal for a specific trait is partly due to the expression of its own genes. This can be measured using scales (body weight, fleece weight), equipment such as a Sirolan Fleecescan, an OFDA2000 (fibre diameter, coefficient of variation of fibre diameter), an ultrasound scanner (eye-muscle depth, fat depth) or observation by the breeder (number of lambs born, structural soundness). It is important that as many animals as possible are measured within an unselected group to get the most accurate breeding values. Measuring only the 'tops' of a group means less variation and lower breeding values (Figure 11.2). These records are an expression of how good or bad the animal s genes are for that trait given the environment in which that animal has been managed. It is important that an animal s performance is adjusted for the environment, as only the genetic value of an animal is passed on to its progeny. One of the keys to successful results from Sheep Genetics is the accuracy of the information that is collected. Flexibility enables a breeder to collect information at regular intervals throughout the animal s development to maturity (including sire and dam, conception method, sex, date of birth, birth type, rear type and management group) within management constraints. Accurate and consistent animal identification, which is essential for genetic evaluation, is achieved through use of an industry standard 11-4 WOOL412/512 Sheep Production

5 format. To achieve the data quality required to maintain the integrity of LAMBPLAN ASBVs, an independent person must collect or conduct some of the trait measurements. This is an accredited ultrasound scanner for fat and muscle measurements or an accredited wool laboratory or in-shed equipment for wool characteristics. Figure 11.2: Breeding values are deviations within the group (Sheep Genetics 2007). Related animals share some common genes. Measuring relatives of an individual is effectively looking at more samples of the genes that they have in common. Information obtained from related animals increases our knowledge about the value of the genes of any given animal. Half siblings (animals that have a common sire or dam) on average have 25% of their genes in common, therefore if you have a record on an animals half sibs you have further information on the genes of the animal of interest. Table 11.2 shows two individual animals with the same Eye Muscle Depth (EMD) from families with differences in average EMD values. Animal comes from a family with an average EMD greater than the average of the population. It is likely that its genes are superior for eye-muscle depth. While animal has the same EMD, because it comes from a family that has below average EMD its genes are likely to be poorer for that trait. This is a good example of why it is important to look at the genetic information supplied for carcase traits rather than focusing on the actual scan measurement. Table 11.2: Likely vs measured genetic values for EMD (Sheep Genetics 2011). Animal EMD Family mean EMD Likely genetic value for EMD mm 35 mm above average Better genes for EMD mm 25 mm below average Poorer genes for EMD Group average for EMD 30 mm 11.5 Genetic correlation In any animal selection program genetic correlations, or relationships, may exist between traits of interest. The effect is that when selecting for one trait another trait, or traits, may be influenced in the progeny of the selected animals. This occurs because some of the genes that influence the expression of a trait of interest also affect other traits. In many cases, one or more genes affect more than one trait and the traits are said to be genetically correlated. Measuring or observing a second trait can provide more information about the desired trait, than just a measure of the trait alone. Correlations are described as either positive or negative (or zero where no correlation exists). A positive correlation is when selection for one trait leads to an increase in another trait (e.g. growth rate and birth weight). A negative correlation is when selection for one trait leads to a decrease in another trait (e.g. growth rate and eye muscle depth at constant weight). While the correlated effect is what happens on average in the population, there will be animals that do not conform to the expected correlation (e.g. high growth with below average birth weight). Often these animals are referred to as curve benders, as they break trait relationships. For seed stock and commercial breeders, these are often highly desirable animals. To identify these animals within the population requires all traits of interest to be measured and analysed. Tables 11.3, 11.4 and 11.5 illustrate genetic correlations and heritability for a range of traits. The heritability is shown in bold on the WOOL412/512 Sheep Production 11-5

6 diagonal with genetic correlations given as positive (+) or negative (-). "0" represents no correlation between traits Only a proportion of the observed superiority or inferiority of an animal (after adjustment for known nongenetic effects) is actually passed onto progeny. The degree to which differences are passed on - or inherited - is known as the heritability of a trait. The heritability of the desired traits is used to produce sound genetic estimations of breeding values. Table 11.3: Indicative heritabilities and genetic correlations for maternal breeds (Sheep Genetics 2011). BWT 0.10 WWT PWWT YWT PFAT PEMD YGFW PWEC PSC NLW MWWT BWT WWT PWWT YWT PFAT PEMD YGFW PWEC PSC NLW MWWT Table 11.4: Indicative heritabilities and genetic correlations for terminal breeds (Sheep Genetics 2011). BWT 0.10 WWT PWWT PFAT PEMD PWEC NLW MWWT BWT WWT PWWT PFAT PEMD PWEC NLW MWWT 11-6 WOOL412/512 Sheep Production

7 Table 11.5: Indicative heritabilities and genetic correlations for Merinos (Sheep Genetics 2011). YWT 0.35 YFAT YEMD YCFW YFD YFDCV YCURV YSL YSS YWEC NLW YWT YFAT YEMD YCFW YFD YFDCV YCURV YSL YSS YWEC NLW 11.6 Environmental effects For all traits, there are factors other than the animal s genes that influence the level of performance that is expressed. The effect of non-genetic or environmental factors on animal performance means that using a simple measure of performance alone will not give an accurate guide to the animals genetic merit. To make an ASBV as accurate as possible environmental factors need to be taken into account. Easily identified environmental effects include birth date, age of dam, birth type, rearing type, weaning group and post weaning management groups. Other, often forgotten, effects may be disease problems, structural faults or feeding differences between show and flock rams, for example. An example is that twins tend to be smaller (on average) than single-born lambs (Figure 11.3). They also cut less, but coarser wool. This is not because they have poorer genes for growth, body weight, fleece weight or fibre diameter, but because they have had to share nutrition both pre and post birth. Their environment has not (on average) been as good as that experienced by single lambs. Another example is that progeny born to maiden females on average have a poorer environment than progeny born to females that have had more than one parity (births). Figure 11.3: Two rams from the same AI program with the same sire and maternal genetics - The larger ram is a single born ram, the smaller is a triplet born ram, though both have relatively same genetic potential for growth (T. Bull Sonning, Holbrook). WOOL412/512 Sheep Production 11-7

8 Comparing animals from different environments and breeds A common issue raised about genetic evaluation is how animals bred in widely differing environments and management systems can be validly compared. Separating the genetic and environmental components of an animal s measured performance is achieved through genetic linkage. Genetic linkage occurs when two or more studs share common genes. Genetic linkage is created by sires (predominantly) and is developed between studs when common sires have been used, by AI or natural mating, and the subsequent progeny are performance recorded in a valid contemporary group Genetic linkage LAMBPLAN & MERINOSELECT ASBVs use information from all relatives of each animal regardless of the flock or group (Figure 11.4). This Across-Flock feature of ASBVs means that all animals can be directly compared for their genetic value, allowing the benchmarking of the whole breed. One of the strengths of genetic evaluation is that it enables direct comparison of animals across studs, which are often run under vastly different management, climatic and nutritional regimes. To do this the LAMBPLAN or MERINOSELECT evaluation must be able to calculate an Australian Sheep Breeding Value (ASBV) that is free of non-genetic (environmental) effects on the animal s performance. Genetic linkage is one of the tools that allow this to occur. Figure 11.4: Criteria to be met before an ASBV will be reported (Sheep Genetics 2011). If there is no genetic linkage, ASBVs cannot be calculated, and breeders will receive Flock Breeding Values (FBVs). FBVs allow comparison of animals within flock only. In addition to comparing across flocks, genetic linkage is required for comparison across management groups and years within a flock. To effectively achieve this linkage it is important not to change all sires from one year to the next. Small studs, in particular, need to be wary of this situation. How is genetic linkage developed? The most effective way to create genetic linkage is to have progeny from a sire pedigree and performance recorded in two or more studs (Figure 11.5). AI sires commonly perform this function due to their accessibility by all breeders. However, a sire used by natural mating that was born and raised in another flock and not used as a sire performs the same function. It should be noted that sires need not be used in the same year in each stud. Purchasing new stud sires from other performance-recorded studs also plays a key role in developing genetic linkage WOOL412/512 Sheep Production

9 Figure 11.5: Linkage occurs when progeny from a common (link) can be compared against progeny from sires in different groups, flocks or breeds (Sheep Genetics 2011). Genetic evaluation uses the link sire as a reference point from which it looks at the relative performance of other sires. Essentially genetic evaluation systems are interested in the +2 kg, -3 kg, etc, deviations to calculate ASBVs, which are derived from the actual weights and measures submitted by breeders. A point to note is that evaluation of sires is only effective when at least two sires are represented in a management group (same sex, similar age and same nutrition and management). When only one sire is represented in a management group, the performance of the lambs in that group contributes no information to their sire s ASBVs. How to improve genetic linkage Genetic linkage is commonly developed from: The pedigree links that exist between flocks simply because breeders sell rams and ewes to each other. If there is good pedigree information from the flocks involved, this provides a basis for acrossflock evaluation. The use of Artificial Insemination (AI). Young sire programs. These are an excellent mechanism for ensuring continual flock linkage as well as testing new genetics. Entering sires in sire evaluations, such as Merino Superior Sires. In these centralised progeny tests, progeny of sires from different flocks are evaluated in a single, common environment. Across breed ASBVs Across breed ASBVs are currently available only for the terminal meat sheep breeds. For example, ASBVs for Poll Dorsets, Texels and White Suffolks can all be compared with each other. ASBVs for maternal breeds are across flock but within breed breeding values. For example, ASBVs from Coopworth flock X can be compared with ASBVs from Coopworth flock Y, but not with ASBVs from Border Leicester flock W. Merino ASBVs are across flock within breed breeding values. As the terminal meat sheep industry becomes more focused on commercial performance (e.g. faster growth, superior carcases, high weaning rates, good milking ability, and worm resistance,) more breeders will use the best genetics they can find, regardless of source. Across-breed ASBVs have simplified this selection in the same way that ASBVs do within breeds. As this process continues, breeders will put together packages of the best genes available for the range of industry requirements. New combinations of genes will be continually evolved drawing on the entire gene pool. Where appropriate data is available, SG is able to evaluate animals across a range of breeds. The calculation of across-breed ASBVs is, in principle, no different to calculating across-flock ASBVs. It requires across-breed genetic linkage in addition to across flock genetic linkage. There are two key forms of across breed genetic linkage available for the sheep industry: WOOL412/512 Sheep Production 11-9

10 1. Trials such as the Sheep CRC s Information Nucleus Flock where sires of different breeds are compared on the basis of their crossbred progeny in a common location. 2. Pedigree connections where sires of one breed are used over ewes of another and the resulting progeny are compared to purebred progeny. Commercial producers are now able to compare the performance of terminal sire rams from different breeds. This ensures that the best ram can be selected for a specific target market, regardless of which flock it is from ASBV and FBV accuracy By definition, ASBVs are an estimate. Accuracy, published as a percentage, is a reflection of the amount of effective information that is available to calculate the ASBVs for an animal. Accuracy is influenced by; heritability of the trait; size of the group in which the animal is compared; correlation between the trait reported and other records available; accuracy of parents ASBVs; and amount of performance information available on the animal itself and its relatives. Accuracies are calculated for both ASBVs and FBVs. This is reported as individual trait accuracy. A minimum level of accuracy must be achieved before ASBVs and FBVs can be reported (Figure 11.6). FBVs have to meet the same minimum standards of accuracy as ASBVs, but FBVs do not have accuracies published with them. Whole flock recording for the appropriate range of traits will improve accuracy of ASBVs. Figure 11.6: Accuracy reporting thresholds for ASBVs and FBVs (Sheep Genetics 2011). Accuracy cannot account for some breeder influenced data quality issues, for example, how well management groups are defined. How accurate are ASBVs and index values? Typically, animals first get an ASBV (or Index Value) when they get a weight record, for example a birth or weaning weight. At this time, we usually already know quite a bit about their ancestors, and will now have similar records on some half-siblings (animals with the same sire or dam). As more information is collected on other traits accuracy will rise (Figure 11.7). The animal may then be selected for breeding, which means it will get progeny and in time those progeny may have performance records added to the evaluation. This means that the accuracy of ASBVs goes through two major steps. Initially, when the animal has its own records and records on relatives (ancestors, full sibs, half sibs, etc) and secondly, when it gets progeny WOOL412/512 Sheep Production

11 Figure 11.7: Accuracy is built up with the inclusion of more information. a) Animal s and parent s measurements b) Animal s and parent s measurements, 15 measurements from brothers/sisters c) Animal s and parent s measurements, 15 measurements from brothers/sisters, 15 measurements from progeny d) Animal s and parent s measurements, 15 measurements from brothers/sisters, 30 measurements from progeny (Sheep Genetics 2011). Factors that affect accuracy In addition to the amount of data available, the quality of the data also affects accuracy. Table 11.6 shows the major factors that ensure maximum accuracy of ASBVs and Index Values. These factors determine whether the breeder gets maximum value from the effort put into recording. Table 11.6: Major factors to ensure accuracy (Sheep Genetics 2011). Increased Accuracy Reduced Accuracy accurate management groups poor identification of management groups two or more sires progeny in each management group all progeny in a management group by one sire even mating group sizes some sires get many progeny, others few progeny animals get similar amounts of performance information some animals get many records, others very few accurate pedigree records poor pedigree data Good records, even-sized mating groups, and similar amounts of performance data for similar groups of animals, all contribute to ensuring that ASBVs are as accurate as possible. The impact of accuracy on genetic progress It is important to keep accuracy in perspective. Accuracy and genetic merit are not the same. It is quite possible to have animals that have very low ASBVs, but for those ASBVs to be very accurate. Conversely, animals may have high ASBVs with low accuracy. The ability to make genetic gain is strongly influenced by: having accurate information about animals genetic merit, plus finding plenty of animals with high genetic merit. The most accurate information will come from whole flock pedigree and performance recording with good data structure and accurate management grouping. From this foundation, the main challenge is then to identify better and better animals each year. The way to do this is to select the animals with the best ASBVs and Index Values for the particular production system that; Have performed well themselves; and Have a reasonable number of well-performed relatives. Typically, for studs that are making genetic progress, this will mean using 7 8 young sires for every 2 3 older sires. This might seem risky - after all, the older sires have higher accuracy. However, remember that the ASBVs and Index Values have used all available information, and taken account of how much information is available on each animal, young or old. This means that animals with the best ASBVs and Index Values will be the best bets for breeding. While the ASBVs and Index Values may change for individual young animals as they get progeny, a team of young animals (sires for example), will breed very close to their average ASBV or Index value. This occurs through an averaging effect because ASBVs and Index values have equal chance of moving up or down. Several elite breeding schemes use such an approach. WOOL412/512 Sheep Production 11-11

12 Exactly the same principle can be applied for any trait (including the Selection Index) and for any mating group, (e.g. a larger team of rams or a mating set of rams and ewes). In all cases, the larger the number of animals being considered, the closer they will breed to their average ASBV or Index Selection indexes A selection index combines several traits to give one value that reflects the performance of the sheep relative to the breeder s objective. The 3 steps in producing a selection index are: Calculating the ASBV for each trait in the breeding objective. Determining the relative importance of each trait. Multiplying the ASBV by its relative importance and adding together for all traits. To make it simpler for breeders and buyers of rams, SG calculates several standard indexes for LAMBPLAN & MERINOSELECT. The standard indexes have different relative emphasis on the various traits to correspond to different breeding objectives. Each breeder should ensure that the index they use when selecting rams matches their flock breeding objective. Each breed has decided on the relative emphasis to place on each ASBV to calculate a breed index. However there is an opportunity for ram breeders to calculate a number of different indexes to allow ram buyers to select for their own breeding objective. A selection index can be used to select effectively for two or more traits that may have antagonistic genetic relationships. For example selecting to increase fleece weight alone will result in an increase in fibre diameter because there is a positive genetic correlation between the traits. However a selection index takes this genetic correlation into account and puts appropriate weightings on the traits which can result in improvement of both traits together Readings Reading 1 is provided on web learning management systems and suggested readings are listed Below: 1. Sheep Genetics Australia (SG) Breeders Guide, 'Understanding MERINOSELECT ASBVs'; 'Understanding LAMBPLAN ASBVs' and 'Understanding LAMBPLAN Maternal ASBVs', SG, available at Sheep Genetics (SG). 'An introduction to MERINOSELECT', SG, available at References Sheep Genetics (SG) Data supplied courtesy of SG. Meat and Livestock Australia (MLA) and Australian Wool Innovation Ltd (AWI). Sheep Genetics (SG) Ram Breeders Manual Sheep Genetics (SG) Breeders Bulletin - quarterly WOOL412/512 Sheep Production