The basics
Genomics is the study of DNA. DNA is the building blocks of genes and it is the genes that determine whether an animal has the potential, for example, to grow or be fertile –whether an animal achieves its genetic potential is dependent on the management the animal is exposed to. DNA is present in all cells and remains the same throughout an animal’s life; in other words the DNA of a calf taken at one day of age is the same as that animal’s DNA several years later. Apart from identical twins, each animal has a different DNA profile. This is com-monly referred to as the animal’s genotype.
The potential immediate uses of genomic information in cattle production is in Figure 1. Other more futuristic uses include personalised management, development of diagnostics and vaccines amongst others.
The use of genomic information in cattle breeding is not new. Genomics has being used routinely in parentage testing. Because each animal inherits half its DNA from its sire and its dam, parentage assignment can be accurately undertaken based on the DNA information of the individual and its parent(s). Genomics is also routinely used in cattle breeding in the screening of (AI) bulls for known lethal major genes or congenital defects. DNA can be obtained from blood, hair or tissue samples.
Interest in the more wide-spread application of genomic technology in cattle breeding has, however, rapidly intensified in recent years. This growing excitement has been fuelled by the rapidly declining cost of acquiring a genotype but also advancements in the statistical methodology to effectively and efficiently analyse the vast quantities of genomic data being generated. While heretofore applications of genomics in cattle breeding exploited knowledge on only a few pieces of DNA (e.g. Merial/Igenity marker panels), today’s application of genomic selection utilises information on tens or hundreds of thousands of pieces of DNA of an individual. The increased information available per animal results in a now-proven more accurate genetic evaluation.
The technology commonly used internationally heretofore in genomic selection programs exploits DNA information at 54,001 locations across the animal’s DNA. These tiny changes in the DNA sequence of an animal are commonly called SNPs
(pronounced “snips”) and the platform used to determine the genotype of an animal is referred to as a SNPchip
(pronounced “snip-chip”). Ireland developed its own SNPchip for use in dairy and beef cattle. A total of 53988 SNPs are now included on the SNPchip; the characterisation of SNPs on the chip is in Table 1.
Imputation is a process where our knowledge of inheritance of DNA facilitates the prediction (called imputation) of SNPs that are not actually genotyped. Therefore a lower density, lower cost genotype platform can be used to generate higher density genotype information. To avoid the necessity of imputation in dairying, all 40,446 SNPs used in the Irish dairy genomic evaluations are included on the Irish SNP-chip. Parentage testing to date is undertaken using microsatellites which are a different form of DNA variation to SNPs. Microsatellites are more expensive to undertake, can contain errors, and can only be used for parentage testing (i.e. cannot be used for genomic selection). SNPs, in contrast, are considerably less expensive per unit genotype, are, on a whole, more accurate for parentage (in)validation but also assignment (even without the dam being genotyped), and can be used for genomic evaluations. Ireland is in the process of transitioning all parentage testing in cattle (and sheep) to SNPs. Embarking on such an initiative, however, would require all back-pedigree to be re-genotyped with SNPs. An innovative approach was developed to predict (termed impute) microsatellites from the available SNPs.
This therefore eliminates the necessity to re-genotype back-pedigree with SNPs with obvious cost-savings. SNPs are also included on the custom SNP-chip to aid in the accurate prediction of the proportion of Angus and Hereford in a (meat) sample. Mutations in genes of known lethal effects (e.g. CVM, BLAD, DUMPS, Brachaspyina) as well as mutations leading to congenital defects (e.g.Congenital contractural arachnodactyly also known as fawn calf, Arthrogryposis Multiplex or Curly Calf Syndrome) or in genes of known major effect (e.g.myostatin, DGAT1) are also included on the SNP-chip. All tests can be undertaken with just a single biological sample which could be blood, hair, ear biopsy, meat, or semen and is available to all farmers for !22; this price is 8% of the cost several years ago and is expected to become cheaper in the coming years.
Frequency of major-gene variants in Irish cattle
Knowledge of the carrier status of candidate parents for different genetic mutations (e.g.myostatin) and the impact of mating animals of different genotype status is crucial to a successful herd-breeding program. Knowledge on how the frequency of these mutations is changing across time can provide useful information for breed societies of the impact of prevailing breeding strategies on likely future consequences. Table 2 summarises the frequency of different mutations in a population of 14,128 Irish Holstein-Friesian animals; Table 3 summarises the prevalence of several mutations in Irish purebred beef cattle. The proportion of Holstein-Friesian animals with the A1A1, A1A2 and A2A2 genotype was 14, 45, 41% respectively. Of the animals that were carriers of the lethal mutations, 66% (Bracyspina) to 79% (BLAD) were females. Of the animals that were CVM carriers, 2.5% to 3% of them were also carriers of brachyspina and BLAD, respectively.
It is well known, for example, that calvings from the mating of animals carrying the nt821 variant in the myostatin gene (i.e. the double muscling gene) have a greater likelihood of requiring assistance at calving. Knowledge of the nt821 status of the cow and potential mates for such mutations can therefore be extremely useful in making mating decisions but also in the manage-ment of the cow prior to and around calving. For example, the progeny from a mating between two carrier parents has a 25% chance of being a double copy carrier, 50% of being a single copy carrier, and a 25% of not carrying the deleterious allele.
Although extremely useful for an individual mating decision, farmers are generally limited to using the sires that are available to them. Therefore, close monitoring in the trend of genotypes for each mutation at the population level can provide an early warning of likely future issues, at the population level, both for herdbook breeders but also commer-cial farmers. The advantage of the Irish SNP-chip is that with just a single sample, the status of each animal for each mutation is obtained as well as also parentage testing and more accurate prediction of genetic merit.
Genomic evaluations
The first step in a successful genomic selection program is to accurately quantify the impact each of the pieces of DNA have on the plethora of animal characteristics recorded such as growth rate, carcass traits, fertility, and other traits of economic importance. To achieve this, genotype and performance records on several thousands of animals are required. These animals can be either cows themselves or their sires. The greater the number of animals with both genotype and performance records available, the greater will be the accuracy of genomic predictions of young calves.
Based on earlier research in beef cattle in Ireland, it was obvious that a very large population of genotyped and phenotyped animals would be required to develop an accurate genomic evaluation that worked well across breeds. This led to a national initiative to genotype a large population of Irish beef cows
(http://www.icbf.com/wp/wp-
content/uploads/2013/07/Selection-of-animals-for-use-in-beef-genomic-selection-program.pdf).
Genomic evaluations were under-taken using 104,169 beef genotypes including a combination of AI sires, natural mating sires and cows. To test whether genomic information could aid in the prediction of future perform-ance, a genetic evaluation was undertaken using data up to the year 2008; the genetic merit of animals born after the year 2008 was predicted based on DNA information only and compared to their genetic merit in the year 2015 (which included their performance information). The prediction accuracy varied per trait but was approximately 0.60 to 0.70. The improvement in reliability for the individual traits is in Table 4. The relative improvement in reliability (in terms of progeny equivalents) was greatest for the lower heritability traits of fertility and survival; this is particularly relevant since it actually takes longer in the life of a bull to receive information on the fertility performance of his daughters. Having genomic information on an animal is equivalent to the animal have fertility performance on almost 100 daughters – not bad for an animal who is potentially only 3 weeks of age!
Other uses of genomic information in cattle production
Knowledge of the breed proportion of an animal or meat sample is useful for meat provenance but also in the design of mating programs to maximise heterosis. The breed composition of an animal resulting from the mating of at least one crossbred parent cannot be known with certainty without exploiting DNA information. Only a small number of SNPs are required to achieve extremely accurate traceability systems from fork to farm. Incorrect or missing pedigree information seriously biases inbreeding estimates of animals but also the estimated extent of relationship between animals. For example, the estimated relationship between two full sibs with no parentage recorded (or incorrect parentage) is zero while in fact we know this is not true – genomic information can help resolve such discrepancies and therefore aid in decision support to avoid the mating of close relatives but also facilitate the mating of animals related in pedigree but not related at the genomic level. Genomic information through the development of more accurate predictions of genetic merit also facilitates personalised management or more tailored management strategies where, for example, animals of greater potential for growth rate or milk yield can be fed accordingly. This is currently undertaken at a breed level but we know within breed differences in performance clearly exist.