Harnessing genomic information for livestock improvement
Summary (2 min read)
Introduction
- Since 1960, global livestock productivity (including carcass weight of meat- producing species, milk yield of dairy cows and egg production) has increased by 20–30% as a result of advances in nutrition, disease control and genetics1.
- Genome- wide SNP arrays are available for the main livestock species.
- These efforts have uncovered millions of genetic variants for all the main livestock species and profoundly changed their understanding of the domestication process (box 1).
- The description of the number, location and effects of the genetic variants that affect a phenotype of interest.
- Unlike in humans, who typically produce only one affected offspring, samples were available from a number of affected animals, which greatly facilitated the identification of the causative mutation.
GS for complex agricultural traits
- With the exception of the breed- defining characteristics, inherited defects and EL mutations discussed above, nearly all economically important traits in livestock are complex polygenic traits.
- Examples of such major gene effects segregating within breeds include, among others, variants in MSTN in cattle112–115 and sheep67 and RYR1, PRKAG3 and IGF2 in pig116–118, which all affect muscularity; DGAT1, GHR and ABCG2, which affect milk yield and composition in cattle119–121; and PLAG1, HMGA2 and LCORL, which affect stature in cattle122,123.
- The accuracy of GEBV will be highest when the prior distribution best matches the true distribution of SNP effects111.
- Balancing selection for variants with large effects is common in livestock.
GBLUP selection
- A more complete understanding of balancing selection operating at specific loci could be exploited to prioritize or avoid specific matings in breeding programmes (see From selecting animals to selective matings using genomic information).
- Strategies to further improve the accuracy of whole- genome-sequence- based GS currently involve either selecting or assigning more weight to a subset of imputed variants that are more likely to be causative.
- Much remains to be learned about how variants perturb regulatory elements, including whether they need to be within the element or can influence regulatory function from a distance.
- First, the linkage phase between causative variants and distant genotyped SNPs may differ between breeds.
Editing livestock genomes
- Programmable nucleases have revived interest in editing livestock genomes.
- The anticipated revolution has yet to occur.
- Indeed, the rate of double- stranded break- induced NHEJ is now high enough that, despite mosaicism commonly reducing germline transmission, it has become more effective (in terms of the number of embryos required to obtain an edited offspring) to circumvent SCNT and inject the programmable nucleases directly into the zygote when aiming to generate LoF mutations172.
- Thus far, efforts in editing the genome of livestock have mostly concentrated on largely uncontroversial human health applications, such as generating animal models of human genetic diseases, producing biopharmaceuticals and xenotransplantation.
- As the number of animals with both phenotypic records and SNP genotypes increases into the millions and as fine- mapping methods continue to improve, a growing number of causative variants (particularly those with the largest effects) is bound to be identified, as has been shown to occur for common complex diseases in humans36.
New applications of genomic technology
- Detecting cows with subclinical mastitis by bulk genotyping of tank milk.
- One of the major health issues on dairy farms is mastitis186.
- This ensemble of allelic ratios reflects the combination of the cows’ known SNP genotypes, and the unknown proportion of DNA contributed by each cow to the tank milk.
Conclusions and future perspectives
- The field of animal breeding just completed a prototypical, once- in-a- lifetime Gartner hype cycle.
- Whole- genome sequencing of 234 bulls facilitates mapping of monogenic and complex traits in cattle.
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Frequently Asked Questions (14)
Q2. What is the way to edit the genome of a sire?
Before dissemination, the sire’s genome would be edited for a number of causative variants to render them homozygous for the favourable allele.
Q3. How do DNMs with large effects on the selected traits be detected?
DNMs with large effects on the selected traits sequentially undergo hard sweeps, causing large effects detectable by GWAS until the corresponding variants reach fixation126.
Q4. How many SNPs are needed to genotype the milk of a cow?
The number of SNPs needed to achieve adequate accuracy depends on the number of cows on the farm: tens of thousands of SNPs are sufficient for farms with tens of cows, but hundreds of thousands of SNPs are needed for farms with several hundred cows.
Q5. What is the way to compensate for the fact that causative SNPs are?
One way to compensate for the fact that most causative SNPs are not directly interrogated on the arrays is to impute full sequence information on genotyped animals.
Q6. What was the first step in the development of somatic cell nuclear transfer?
The inability to derive embryonic stem cells prevented homologous recombination- based techniques until the development of somatic cell nuclear transfer (SCNT)171, which enabled refined gene replacement by homologous recombination in cultured fetal fibroblasts followed by nuclear transfer to enucleated oocytes.
Q7. How can the authors predict the effects of a magnitude that is virtually impossible under this model?
effects of a magnitude that is virtually impossible under this model have been identified and with GBLUP, their effects will be over- conservatively regressed downwards in genomic predictions.
Q8. What are the main applications of genome editing in livestock?
Thus far, efforts in editing the genome of livestock have mostly concentrated on largely uncontroversial human health applications, such as generating animal models of human genetic diseases, producing biopharmaceuticals and xenotransplantation.
Q9. What is the convincing evidence that the remainder of the heritability is highly polygenic?
The most convincing evidence indicates that the remainder of the heritability is highly polygenic, corresponding to hundreds if not thousands of genetic variants that each has a very small effect on the trait of interest89.
Q10. What are some examples of major gene effects segregating within breeds?
Examples of such major gene effects segregating within breeds include, among others, variants in MSTN in cattle112–115 and sheep67 and RYR1, PRKAG3 and IGF2 in pig116–118, which all affect muscularity; DGAT1, GHR and ABCG2, which affect milk yield and composition in cattle119–121; and PLAG1, HMGA2 and LCORL, which affect stature in cattle122,123.
Q11. What are some examples of a ryr1 variant in pigs that causes ?
Classic examples include a RYR1 variant in pigs that increases carcass yield in heterozygotes but causes porcine stress syndrome and related syndromes in homozygotes112 and bovine MSTN LoF variants that increase muscle mass in heterozygotes but cause birthing difficulties for mothers of homozygous calves.
Q12. How long did PT take to expose differences in the BVs?
Before GS, candidate elite dairy sires that had identical EBVs based on pedigree information (for instance, because they were full- sibs) required expensive and time- consuming PT to expose differences in the BVs: their individual EBVs were estimated from the performances of tens to hundreds (depending on the country) of daughters, and PT took at least 5 years at a cost of ~US$50,000 per bull10.
Q13. How many elements overlap potential promoters, enhancers and insulators?
Nearly 1 million evolutionarily constrained elements that overlap potential promoters, enhancers and insulators have been identified24.
Q14. What can be done to help identify the target genes whose expression is perturbed by these?
eQTL information can certainly help to identify the target genes whose expression is perturbed by these regulatory variants41,42,155.