- This may seem a bit out of context, but it is actually something I have been meaning to write for awhile. It may get its own page eventually, but for now, here it is in 'blog form: my feelings on the oft-debated issue of alpaca breed standards. Since the first commercial North American importation of alpacas in 1984, breeders in the United States have debated whether to draft a breed standard for the Huacaya alpaca. Breeders of the Suri alpaca – the cousin to the Huacaya, whose long, lustrous fiber somewhat resembles dredlocks from a distance – have had a breed standard in place since 2006. At the time of this writing, there is no such standard for the Huacaya.
- This is a little bit of a follow-up to a post I wrote (coincidentally, almost exactly a year ago now) on Huacaya alpaca Breed Standards. The original post was posted on a popular Facebook alpaca forum, and it generated quite a bit of controversy (as intended). A bit more recently, I posted this tentative outline of a commercial production-based Huacaya alpaca breed standard on the same forum. It, too, generated quite a bit of interest, though the response was surprisingly positive. Interestingly, the thing that the most people disagreed with was the line, "The only permissible color is white." I stand by that statement. Introducing color only muddies the water when to majority of production-based alpaca breeders wish to focus on white, and it's hard enough to breed for pure white as it is.
- An alpaca evaluation sheet.
- This paper discusses the range of genetic breeding programs which are available to Australian livestock industries. It presents a short history of genetic evaluation schemes and discusses the Australian Dairy Herd Improvement Scheme, BREEDPLAN for Beef Cattle, PIGBLUP, KIDPLAN, and the newly created Sheep Genetics Australia which combines wool and meat into one database. The paper concludes with an update on the Alpaca Across-Herd Genetic Evaluation (AGE) program and presents data on the traits measured to date.
- This information note aims to assist ram buyers interpret raw measurements on animals to better select rams for individual needs.
- Consider any species that typically gives birth to one offspring per mating, and that within that species is any simply-inherited trait with a dominant ‘A’ allele and a recessive ‘a’ allele. Now consider four individuals of that species, all with known genotypes: a heterozygous dominant male (’Aa’), a homozygous dominant female (’AA’), a heterozygous dominant female (’Aa’), and a homozygous recessive female (’aa’). Assume a genetic test doesn’t exist. The mating outcomes of the male over each of these females can be summarised as:
- The Optical Fibre Diameter Analyser 2000 (OFDA2000) model allows coefficient of variation of fibre diameter (CVFD) to be separated into a between fibre diameter variation component and an along fibre diameter variation component. Both traits are heritable (0.4 and 0.20, respectively) but not as heritable as CVFD on a minicored sample (0.67). Only CVFD between fibres is genetically strongly (-0.7) correlated with SS to nearly the same extend as CVFD (-0.65). It is more effective to use CVFD of wool samples as an indirect selection criterion to improve SS. In addition this will also result in a reduction in the propensity of FD to blowout along the staple. Keywords: Genetic parameters, fibre diameter variation, staple strength, micron blowout.
- Without ignoring breed standards and common sense, breeders can apply their own interpretations and tastes, creating the healthy diversity necessary for the ultimate survival of the species. I realize that I’ve made this point before – but it’s an important one and bears repeating. No matter what your own personal vision or dream is, before you decide to embrace a trend, ask yourself: “Is it fad or function?”
- The breed standard for the Cheshire Alpaca was developed by Howling Hill Farm to better define our breeding goals for our Huacaya alpacas. Like all breed standards, the below describes an ideal animal, the archetypical Cheshire Alpaca. Unlike the standards for most domesticated breeds, however, this standard describes an animal that is still developing. Many animals on our farm and others come very close to meeting this standard in many ways – some in nearly every defined trait. However, the majority fall short in some fashion, and this is to be expected, as development of the breed has only recently been undertaken. For this reason, many more faults are allowable than would be expected in a traditional breed standard, though the ideals are always described and noted in the preceding text. Over time, as the breed develops and more individuals are produced that meet the standard in its entirety, many faults will likely be moved from the category of “Major” to “Disqualifying."
- The aim of selection is to increase the frequency of desired alleles and decrease the frequency of undesired genes in a population, ideally producing animals that breed true for the genotypes and phenotypes selected for. One influence on the effectiveness of selection on gene frequency changes is the initial gene frequency in a population. Consider two alleles at locus A: A1 is wanted and A2 is not. This graph plots the frequency of A2 in each successive generation, showing the effect of selection against that unwanted allele A2 over many generations:
- Ram buying is an important part of a sheep business. Often it is only done on one day per year, so it may seem difficult to justify investing too much time in picking your rams. However, the impact of your ram buying decision can have a large and lasting impact on the profitability and sustainability of your sheep enterprise. This guide is aimed at helping you to understand the complexities of breeding profitable yet functional sheep that are right for your business. It focuses on how to make genetic gain in your sheep flock by selecting rams with the right estimated breeding values (EBVs).
- Successful breeding programmes involve the use of many different tools to help you determine whether your breeding aims are being achieved. Fleece testing is an objective tool to monitor the changes in individual and herd fleece characteristics.
- The genomc-based Flock Profile test was developed by team of researched from Sheep CRC, AGBU, NSW DPI and Sheep Genetics. The Flock Profile test is suitable for any commercial Merino breeder.
- Describing the genotype of some simply-inherited traits in an individual animal can be straightforward — horned cattle are always ‘pp’, and looking at an Andalusian chicken will tell you if it is ‘BB’ (black), ‘Bb’ (slate-blue) or ‘bb’ (white). We know the exact alleles carried, and in which proportions. When it comes to describing the genotype of a population however, we refer to gene and genotypic frequencies instead.
- A glossary of breed standard terms.
- Inbreeding is the mating of closely related animals to increase homozygosity within a population. Common alleles become more concentrated — the gene frequency increases in other words — and animals become more and more closely related with each generation. The reliability of high performing animals producing more high performing animals becomes very predictable. It sounds like the only breeding approach you’ll ever need, but there can be consequences. Outbreeding on the other hand increases heterozygosity by mating unrelated animals. New alleles are introduced and the gene pool widens. From this and the Hardy-Weinberg Equilibrium, it would appear that a breeding programme would go nowhere fast were it to rely solely on outbreeding. Yet there can be benefits.
- Recently we calculated the probabilities of several mating scenarios producing a homozygous recessive, assuming the test animal (invariably a male) is a carrier. As most recessive alleles are not wanted, the sooner a carrier can be identified, the sooner it can be culled from a breeding programme. But knowing the odds aren’t quite enough — odds are an indicator and not a guarantee of outcome. By sheer luck a carrier may produce a homozygous recessive after just one mating. Or it could take three, or ten, or more, matings — it’s all down to the random assortment of alleles and which sperm fertilises which egg. As well as knowing the odds, breeders also need to know how many matings are required to be confident that a tested animal isn’t a carrier. We need to know the level of confidence.
- Strategies for breeders and breed associations.
- A collection of articles on new opportunities in genetics and genomics.
Preference-Based Approaches to Deriving Breeding Objectives: Application to Sheep and Plant BreedingA preference-based approach, using the internet-based software 1000Minds, was used to derive part-worth utilities of farmers’ assessments with respect to traits in the definition of a breeding objective for sheep in Ireland and pasture plants in Australia. The most critical issue in developing such approaches is the clear definition of traits and the use of realistic ranges of variation in trait performance in order to define alternatives. Conversion of part-worth utilities (percentages) into economic values requires that the economic value is generated within the survey by providing respondents with options that relate to traits which can be defined in economic terms. In presenting alternatives, application of discounted gene-flow principles to breeding objectives in survey-based methods depends on the way questions are asked. It was apparent that respondents’ understanding of traits (attributes, levels), experience with the traits, and how alternatives are presented are very important in using preference-based approaches to define breeding objectives. Issues related to separation of true differences in preferences,confounding and double counting (in animal breeding objectives) are challenges in development of breeding objectives from such preference approaches.
Producing Better Alpaca Fleece – The Benefits of Using the Alpaca Across-Herd Genetic Evaluation (AGE) SystemThe Alpaca Across-herd Genetic Evaluation (AGE) project has successfully established a most important genetic improvement tool for a commercial livestock industry. This report describes this achievement and its importance to rapid genetic improvement in the alpaca industry. This research is of benefit primarily to Australian and New Zealand alpaca breeders to show them the progress achieved with the establishment of an Alpaca Across-herd Genetic Evaluation system and to encourage them to enter their alpacas into the AGE system. An AGE commercial service has been established for the Australian alpaca industry. This service is a world first for the alpaca industry. In the analysis of March 2008 there were 100 herds, 1879 progeny and 3872 alpacas.
- The relationship between traits exhibited by any sire or dam and the traits of their progeny is indeed a fickle affair, causing untold frustration for those determined to breed their ‘ideal’ alpaca. Firstly, there is the issue of whether the desired traits of the breeding sire or dam are being influenced by genetics or by environmental factors. In the latter case, the predictability of whether the parent’s traits shall pass on to their progeny becomes (almost) purely a matter of luck.
- Last week’s post on The Hardy-Weinberg Equlibrium and its Implications covered the five external forces that shift that equilibrium to cause a change in gene and genotypic frequencies: selection; gene mutations; migration in and out of a population; random genetic drift; and non-random matings. Three of these are controllable by breeders and routinely applied in breeding programmes: selection; migration in and out; and non-random matings. The other two — gene mutations and random genetic drift — are completely random forces beyond anyone’s control, and patterns of inheritance are ultimately down to the sheer chance of gene segregation during meiosis and ‘luck of the draw’. Gene mutations are extremely rare events and, should they even occur at all, are as likely to have good, bad or indifferent effects . Any mutation that does appear is most likely to be of a single allele, as the chance of two or more mutations occurring simultaneously, much less being inherited together, is even more remote. Such an allele, or any other rare allele for that matter, may then be subject to that other random force: random genetic drift.
- When selecting rams for a commercial enterprise the first step is to set your breeding objective. Spend a few minutes to write down precisely what you are aiming for, including the levels of performance and by when you want to achieve it. Find more information on setting a breeding objective. Because the most effective way to select for a trait or characteristic is to directly measure or assess that characteristic, you should buy rams from a stud that objectively measures or collects scores (using a standardized system) for the traits you wish to improve. For instance, staple strength can be selected with much higher accuracy if the stud directly measures staple strength on its rams, rather than just having the ASBV calculated from related measurements such as fibre diameter coefficient of variation. However, the ram’s own performance is only part of the picture. What you see in the ram isn’t necessarily what you will get in the progeny because much of the ram’s performance is a result of the ‘environment’. Nutritional differences between animals are a key environmental element and not only come from what they eat, but whether they were born or reared as a twin or their mother was a maiden ewe—giving them less nutrition during pregnancy and lactation than for a single lamb and/or from a mature ewe. Also, climate, disease and management differences will affect how they perform. If you know these environmental factors for each individual, and if you have been able to inspect all of the animal’s relatives and see their performance data, you’d be able to predict very accurately, how the progeny will look and perform. However, this is not practical for you to do, so studs that provide you with Australian Sheep Breeding Values (ASBVs) already have this information taken into account. Pedigree information, management groups, data from relatives and relationships to rams used in the stud and elsewhere are all accounted for and very important when calculating Australian Sheep Breeding Values. Importantly, you can accurately compare rams from different studs (whether at opposite sides of the country or having had quite different management) if they both provide ASBVs for the same trait.
- To select for a simply-inherited trait requires knowing just three things: the number of loci involved (often just one), the number of alleles at each locus (usually a small number), and the genotypes or possible genotypes of the parents-to-be (again typically a small number). In the case of a simply-inherited trait that is partially dominant, such as Andalusian chicken colour, all three pieces of information are known. There is just one locus (B), two alleles (’B’ and ‘b’), and three genotypes easily identifiable by eye (’BB’, black; ‘Bb’, slate blue; and ‘bb’, white).
- While — for the most part — there are differences between simply-inherited and polygenic traits, they also share much in common. Both types of trait are still determined by genes and inheritance.
- The word trait, you may recall, is often used interchangeably with phenotype, but they are not the same thing at all. A trait is something that can be measured or observed, for example temperament, colour or wool staple length/year. A phenotype is the value of the trait: ‘aggressive’, ‘brindle’ or ‘120mm’. Traits fall into two categories: simply-inherited and polygenic.
- Below are some tables that summarise the levels of confidence and numbers of matings required to detect a completely recessive allele. These assume that all the mates are of one group, such as all are known carriers, or all are daughters, or all are randomly picked from a population.
- S.H.I.P. incorporates a variety of tools for Suri owners to utilize the pedigree, phenotype and fiber records for preserving and advancing the Suri industry while adding value to individual Suris within herds. This page is a summary of some of the questions and answers most frequently asked for education and understanding of S.H.I.P.
- Once animals have been selected for breeding, the next step is to decide which are mated to which via a mating system. Some examples of mating systems, each with different intentions, were briefly covered here. Last week we saw how selecting for a particular allelic expression (ie selecting for ‘best’ phenotype) can change the gene frequency significantly in a population. Genotypic frequencies change indirectly as a result — they ‘tag along’. Mating systems do however change genotypic frequencies directly, with gene frequencies less affected. These systems fall into two general categories: inbreeding systems and outbreeding systems. Inbreeding is a mating system which increases homozygosity. Outbreeding is a mating system which increases heterozygosity.
- Outbreeding (also called crossbreeding) is the opposite of inbreeding, in that unrelated animals are mated with the effect of increasing heterozygosity. Let’s step through an example by starting with two unrelated populations, 1 and 2. Population 1 has gene frequencies at the A locus of p1 = 0.8 and q1 = 0.2. Population 2 has gene frequencies at the A locus of p2 = 0.1 and q2 = 0.9. Right away we can tell the two are unrelated as the gene frequencies differ so much. Now cross them to create an F1 generation. (Back in Explaining Mendel’s Results Visually we defined an F1 generation as one resulting from the crossing of two purebred populations. Here we are using it more broadly to include two unrelated, but not necessarily purebred, populations.)
- Selecting animals for breeding is a process by which those deemed ‘best’ are allowed to be parents, and those deemed not, aren’t. The next generation is similarly assessed, and the next, and the next, with the population expected to improve incrementally each time. This gradual improvement over time is due to the frequency of desirable genes increasing in the population and the frequency of undesirable genes decreasing in the population. This results in a group of animals with increased breeding value, as they have a higher concentration of ‘best’ genes more likely to be passed onto the next generation. That next generation, with its higher concentration of ‘best’ genes will perform* at a higher level than earlier generations did. (* ‘Performance’ here is a breeding term that doesn’t necessarily refer to athletic performance such as speed. Rather, it refers to the resulting phenotype, as determined by the genotype. ‘Performance’ could be how fine a sheep’s wool is, for example.) Gene frequencies, breeding values and performance are all intertwined. Increasing breeding values and performance in a population increases the frequencies of desirable genes. Increasing the frequencies of desirable genes increases breeding values and performance.
- Last week we saw how crossbreeding — or more accurately, random matings and/or matings between unrelated populations — do not change gene and genotypic frequencies from generation to generation. This phenomenon is known as the Hardy-Weinberg Equlibrium, named after its co-discovers the English mathematician Godfrey Hardy and the German obstetrician-gynecologist Wilhelm Weinberg. The Hardy-Weinberg Equilbrium states that gene and genotypic frequencies will not change from generation to generation, assuming random matings in the absence of external forces. It further states that, given two alleles at a locus with gene frequencies p and q within a population, that the genotypic frequencies of those alleles will be P = p2, H = 2pq, and Q = q2.
- In The Maths of Matings, Part 1 I promised to write a supplementary post explaining mathematical logs, and here it is!
- Having gone over confidence levels, it’s time to apply that and step through some maths! Let’s now calculate confidence levels and the required number of test matings to be statistically confident that a tested animal is not a carrier of a recessive allele. Everything below assumes that the tested animal is a sire, that there is one offspring from one mating, and that all mates (dams) are of the same type for the allele of interest. That is, they are either all known carriers, or are all daughters of the tested sire, or are all randomly selected from the same population.
- To recap from last week: 1. The formulae for one offspring per mating and with mates from the same group (eg all are known carriers, or all are daughters of the tested sire, or all are randomly selected from a population) are:
- We can easily identify homozygous recessive genotypes and partially-dominant traits simply by looking at the phenotypes of the progeny. Identifying carriers of recessive alleles isn’t as simple, as recessive alleles are hidden — the phenotype of an ‘AA’ animal is indistinguishable from that of an ‘Aa’ animal. The purpose of test matings is to identify carriers of recessive alleles by forcing any such alleles that may be present to appear in progeny. It takes just one such progeny to be born to show without doubt that the tested parent is indeed a carrier. But as there is no guarantee of such a birth, it is more a matter of knowing how many offspring must be born to be sure that the tested animal is definitively not a carrier.
The Relative Importance of Information on Unrelated Individuals on the Prediction of Genomic Breeding ValuesThe theory of genomic selection is based on the prediction of the effects of genetic markers in linkage disequilibrium (LD) with quantitative trait loci (QTL). However, there is increasing evidence that genomic selection also relies on relationships between individuals or the patterns of LD associated with these relationships to accurately predict genetic value. This study aimed to examine the relative importance of information on essentially unrelated individuals on the estimation of breeding value when using gBLUP and BLUP. Analysis was undertaken using a simulated population of 2000 animals. Two reference populations were formed from 1750 animals and the accuracy of prediction was assessed for the remaining 250 animals that formed the test population. Two test populations were constructed such that one included 10 families that had no family members in the reference population and the other included 5 half siblings from 50 families. The gBLUP method more accurately predicted breeding value than BLUP in both test populations. The highest accuracy was achieved when gBLUP was used to predict the breeding value of closely related animals. However, gBLUP was still able to predict breeding value accurately even when animals were distantly related.
- The ideal Suri alpaca is the epitome of true alpaca type with a distinctive elegant profile, perfect head, and outstanding conformation. Suri Network members strongly believe that it is important to preserve the purity of the Suri genotype by breeding Suri males to Suri females. The Suri fleece exhibits highly aligned, draping locks of high luster, fine, slick and cool handling fiber. As Suri alpacas approach the ideal state, they express more positive fleece characteristics than less improved types. The concept of the ideal alpaca is not a static model. It is the process of the pursuit of excellence that will fuel genetic improvement for decades. Highly heritable traits are selected for genotypic gain in the individual offspring’s expression of positive breed characteristics, which exist along a continuum.
Use of Part Records in Merino Breeding Programs - The Inheritance of Wool Growth and Fibre Traits During Different Times of the Year to Determine Their Value in Merino Breeding ProgramsFibre diameter can vary dramatically along a wool staple, especially in the Mediterranean environment of southern Australia with its dry summers and abundance of green feed in spring. Other research results have shown a very low phenotypic correlation between fibre diameter grown between seasons. Many breeders use short staples to measure fibre diameter for breeding purposes and also to promote animals for sale. The effectiveness of this practice is determined by the relative response to selection by measuring fibre traits on a full 12 months wool staple as compared to measuring them only on part of a staple. If a high genetic correlation exists between the part record and the full record, then using part records may be acceptable to identify genetically superior animals. No information is available on the effectiveness of part records. This paper investigated whether wool growth and fibre diameter traits of Merino wool grown at different times of the year in a Mediterranean environment, are genetically the same trait, respectively. The work was carried out on about 7 dyebanded wool sections/animal.year, on ewes from weaning to hogget age, in the Katanning Merino resource flocks over 6 years. Relative clean wool growth of the different sections had very low heritability estimates of less than 0.10, and they were phenotypically and genetically poorly correlated with 6 or 12 months wool growth. This indicates that part record measurement of clean wool growth of these sections will be ineffective as indirect selection criteria to improve wool growth genetically. Staple length growth as measured by the length between dyebands, would be more effective with heritability estimates of between 0.20 and 0.30. However, these measurements were shown to have a low genetic correlation with wool grown for 12 months which implies that these staple length measurements would only be half as efficient as the wool weight for 6 or 12 months to improve total clean wool weight. Heritability estimates of fibre diameter, coefficient of variation of fibre diameter and fibre curvature were relatively high and were genetically and phenotypically highly correlated across sections. High positive phenotypic and genetic correlations were also found between fibre diameter, coefficient of variation of fibre diameter and fibre curvature of the different sections and similar measurements for wool grown over 6 or 12 months. Coefficient of variation of fibre diameter of the sections also had a moderate negative phenotypic and genetic correlation with staple strength of wool staples grown over 6 months indicating that coefficient of variation of fibre diameter of any section would be as good an indirect selection criterion to improve stable strength as coefficient of variation of fibre diameter for wool grown over 6 or 12 months. The results indicate that fibre diameter, coefficient of variation of fibre diameter and fibre curvature of wool grown over short periods of time have virtually the same heritability as that of wool grown over 12 months, and that the genetic correlation between fibre diameter, coefficient of variation of fibre diameter and fibre curvature on part and on full records is very high (rg > 0.85). This indicates that fibre diameter, coefficient of variation of fibre diameter and fibre curvature on part records can be used as selection criteria to improve these traits. However, part records of greasy and clean wool growth would be much less efficient than fleece weight for wool grown over 6 or 12 months because of the low heritability of part records and the low genetic correlation between these traits on part records and on wool grown for 12 months.
- 1. Objectives of sheep classing Visual sheep classing is practised by all breeders and is essential to the quality of a woolgrower’s flock and enterprise profitability. Visual classing is quick, efficient, and cost effective for a large number of traits. It can be done at lamb marking, weaning, shearing, replacement selections and joining, although the major classing events usually take place with the annual selection of replacement ewes and rams. The objective of sheep classing is to identify and retain those sheep in a flock that will improve flock returns both now and in the future through more productive progeny. Improving productivity comes by increasing income and also reducing costs. Constant improvement is needed to overcome annual inflation increases to farm costs and competition from other enterprises. While productivity increases are the key, they should not make the animal more susceptible to disease, nor adversely affect doing ability, which leads to higher costs.
- In 2007, following extensive industry consultation, Australian Wool Innovation (AWI) & Meat and Livestock Australia (MLA) developed the Visual Sheep Scores to: • Provide the Australian sheep industry with a standardised set of visual assessment scores for the consistent description of important phenotypic traits of all breeds of sheep; • Develop a quick and simple scoring system to help sheep classers and breeders select sheep on visually-assessed traits to accelerate genetic gain; • Enable sheep breeders and classers to record and submit visual score data and genetic information to Sheep Genetics to progress development of across-flock Australian Sheep Breeding Values (ASBVs) for visually-assessed traits; and • Enable researchers to estimate the heritability of visually-assessed sheep traits, and to measure their relationships, if any, on important production traits such as fleece weight, fibre diameter, growth rate and body weight.
- But breeding is not about improving an individual animal per se — once it has been born you can’t refine it further by tinkering with its genome. Breeding is really about improving populations of animals, such that those individuals that are born are collective improvements on their ancestors. Those individuals, collectively, then provide the genetic base that will improve their descendants, and so on.
- Although a suri looks very different from the more common huacaya, the conformational traits to look out for are generally the same. The animal should be well proportioned, have straight legs and back, a rounded rump and correct bite. The ears may be slightly longer and the muzzle shorter than a huacaya.
- As mentioned, simply-inherited and polygenic traits are equally subject to the same Mendelian and non-Mendelian inheritance forces. And both can have gene and genotypic frequencies shifted by selection and mating systems. But while it is often straightforward to observe the effect of a simply-inherited trait owing to the small number of genes involved, this isn’t the case with polygenic traits. It is often not even known how many genes are involved in a particular polygenic trait, nor what the effect of each may be. It is because of this complexity that breeders must take very different approaches when working with simply-inherited and polygenic traits.