Beyond HI-Power now leads the Canadian LPI index with +4002 gLPI. He is followed by Kenyon-Hill Ltchwrth Oli, who has +3958 gLPI. The stage concluded with T-Spruce Ethan, the #1 gLPI sire of the December ’23 run, with +3956 gLPI. In the top LPI Domestic daughter proven list, Genosource Captain has the highest gLPI at +3761. The Genomic sire Progenesis Aneesh is now the #1 TYPE bull, with a nog with less than +18 Conformation. Hyden Limited P is the #1 daughter confirmed TYPE bull with a +17 conformation.

• CANADA – GLPI – Genomics – Rel. in Canada – 04/24
• CANADA – Top LPI – Domestic – Dtr proven – 04/24
• CANADA – Top LPI – Mace – Dtr proven – 04/24
• CANADA – Conformation Genomic Bulls – 04/24
• CANADA – Conf. – Domestic – Dtr. Proven 04/24 

There have been no changes to the top three B&W RZG Interbull Genomic rankings. The B&W RZG Interbull Genomic rating is topped by a Rover son, Real Syn, who has +166 RZG (-5 for RZG)! He is followed by Vivify at +161 RZG, who completes the stage with Rome at +160 RZG! Skill Red leads the R&W Interbull Genomic ranking with +161 RZG. CR7 P, Redford, and Handout P finished second with +158 RZG, while Koepon Redbull, Pringle-Red, and Kretos-Red finished third with +157 RZG. Genosource Captain remains the top B&W Interbull Dtr proven sire, with +153 RZG, followed by Ginetta at +150 RZG and Madboy, AltaZarek, Pursuit, and Commitment in a tie for third place at +148 RZG. Zoom Red and Freestyle-Red are the #1 R&W Interbull Dtr proven sires, with +148 RZG.

• GERMANY – B&W – Interbull Genomics – 04/24
• GERMANY – B&W – Interbull Dtr Proven – 04/24
• GERMANY – B&W – Domestic Genomics – 04/24
• GERMANY – B&W – Dtr Proven – 04/24
• GERMANY – B&W – Domestic 99% R Bulls – 04/24
• GERMANY – R&W – Interbull Genomics – 04/24
• GERMANY – R&W – Interbull Dtr Proven – 04/24
• GERMANY – R&W – Domestic Genomics – 04/24
• GERMANY – R&W – Dtr Proven – 04/24
• GERMANY – R&W – Domestic 99% R Bulls – 04/24 

Due to a base adjustment, the breeding values for all bulls having a gNVI breeding value have decreased by roughly 20 NVI points this run. The publishing criteria for the conformation breeding values of imported bulls have also been updated. Delta Boyan (s. Warren P *RC) is the #1 NVI B&W Genomic sire this run, with +391 gNVI, followed by Tigerwoods De La Vigne at +386 gNVI and Sitron at +379 gNVI rounding out the top three. Furthermore, we discover in this top 20 DG Dr. No @ AI-Total at +328 gNVI and +1950kgM. Delta Cream P Red is this run’s #1 NVI R&W Genomic sire, with +375 gNVI. At the fourth slot, we discover NH Skyliner-Red (s. Sputnik *RC) at +358 gNVI, +3739 kgM, and +532 INET.

• Netherlands – B&W – Genomic Bulls – 04/24
• Netherlands – B&W – Dtr proven bulls – 04/24
• Netherlands – B&W – Dtr proven INTERBULL – 04/24
• Netherlands – R&W – Genomic Bulls – 04/24
• Netherlands – R&W – Dtr proven bulls – 04/24
• Netherlands – R&W – Dtr proven INTERBULL – 04/24 

Ecbert (s. Gladius) is the new leader in the Italian gPFT genomic (domestic) list, with +5123 gPFT. Alanzo’s son Al.Co.Bia Essence comes in second at +5048 gPFT, while Al.Co.Bia Soproni, a Zingler x Mojo, rounds out the top three with +5002 gPFT. Yoox leads the Italian daughter proven ranking with +4545 gPFT, followed by Aristocrat son Wilder Holocron at +4524 gPFT and Isolabella Inseme Distefano at +4501 gPFT.

• ITALY – Dtr proven PFT (Domestic) – 04/24
• ITALY – Genomic PFT (Domestic) – 04/24
• ITALY – Foreign Genomic PFT – 04/24 

Diamond Genetics bred the top three with PLI Genomics bulls for the April 24 run. DG Peace leads this list with +908 PLI (+22). He is the Captain son of Paessens Jezebel VG-86-NL, a 2-year-old cow from the Meier-Madows EL Jezebel EX-92-USA herd. He is followed by another Captain son, DG Space of the Ladys-Manor Ruby D cow family, who has +873 PLI (+13). DG Dillon, bred by Diamond Genetics and sold to Cogent, rounds out the top three with +868 PLI. Genosource Captain remains at the top of the PLI Daughter Proven list, with +874 PLI, followed by Westcoast River at +778 PLI and FB Kenobi Targaryen at +710 PLI.

op index bulls in the United Kingdom:

• UK – PLI Young Genomic Bulls – 04/24
• UK – PLI Daughter Proven Bulls – 04/24
• UK – TYPE Merit Young Genomic Bulls – 04/24
• UK – TYPE Merit Daughter Proven – 04/24 

The Scandinavian nations’ indices (Denmark, Sweden, and Finland) are now accessible online. There have been no changes to the top three with NTM genomics bulls this run. Mecanico remains the top NTM genomic sire, with +46 NTM, followed by VH Karat *RC at +43 NTM and Dixon at +42 NTM. VH Deco *RC, VH Fillman, Yoda, and Youngster tied for the top place in the NTM daughter-proven ranking with +28 NTM each.

• SCANDINAVIA – NTM Genomic bulls 04/24
• SCANDINAVIA – NTM Proven bulls 04/24 

We begin today with the first indices arriving from Switzerland. Blakely’s son Swissgen Enrico is the new leader on the Swiss chart, with +1667 ISET. He is followed by the #1 ISET sire of the December ’23 run, TGD-Holstein Beautyman (+1647 ISET), and Swissgen Empire (s. Blakely) (+1633 ISET). S-S-I Hodedoe Montley remains at the top of the Interbull daughter-proven index, with +1572 ISET. He is followed by Wilra SSI Rivet Genuine at +1552 ISET, while Larcrest Commitment comes in third with +1532 ISET.

All top ranks may be seen by clicking on this link.

• SWITZERLAND – ISET – Genomic 04/24
• SWITZERLAND – ISET – Interbull Dtr proof – 04/24
• SWITZERLAND – ISET – Domestic dtr proven 04/24
• SWITZERLAND – Top 100 ISET heifers 04/24
• SWITZERLAND – Top 100 ISET cows 04/24
• SWITZERLAND – Top 100 RC RED ISET heifers 04/24 

Lactanet is collaborating with Angus Genetics Incorporated (AGI) to share genotyping of Angus bulls from Canada, the U.S., and Australia to assist in beef-on-dairy breeding decisions. This move comes as dairy sector stakeholders call for better information on crossbred calves, which are a significant potential income stream on Canadian dairy farms. The “perfect trifecta” of conditions led to calls for better beef-on-dairy information, with genomic testing of dairy animals allowing for accurate rankings within a herd, regardless of age, of the best dams from which to build bloodlines.

The movement to breed the rest of the animals to beef sires has increased the chance of getting a heifer calf from those top ranking animals to 95%. Nearly 40% of Holstein breeders and 30% of Jersey and Ayrshire breeders across Canada use some form of this strategy, with producers now looking at other traits such as calving ease when selecting beef bulls for lower-ranking dams. To aid beef-on-dairy decisions, Lactanet can collect on-farm data it already performs on participating Dairy Herd Improvement and DairyComp herds.

Lactanet also has access to data on calf move-ins and move-outs through its leadership of the DairyTrace national traceability program, but generally knows little on the beef sire side. Genotyping the crossbred calves could grow and strengthen the database, but it is unlikely any dairy producer will pay to genotype animals that will leave the farm within a few weeks.

A key difference between the beef-on-dairy strategy and a genetic program to build dairy strengths over the long term is that the beef strategy typically doesn’t aim to build long-lasting bloodlines. Lactanet will not invest in a beef-on-dairy genotyping initiative, as it would require a huge investment of money, people, and time with little chance of a return on investment. Instead, a collaboration has begun with Missouri-based Angus Genetics Incorporated (AGI) for access to genomic data from Angus bulls in the U.S., Australia, and Canada. The organization will soon include a “Beef on Dairy Query” on its website, alongside other “Query” options for searching bull or cow information.

Breed breed associations could eventually share their information about carcass weights or carcass quality if they’re collecting such data. For the most reliable information, more research is necessary in North America into beef-on-dairy breeding.

The purpose of this research was to determine whether or not utilizing a cow’s parents’ genotypes for imputing single nucleotide polymorphisms (SNPs) affected the calculation of genomic inbreeding coefficients. The imputation genotypes of 68,127 Italian Holstein dairy cows were examined using a variety of genotyping methods. Genomic inbreeding coefficients were calculated using four PLINK v1.9 estimators, two genomic relationship matrix (grm)-based estimators, and one run of homozygosity (ROH; FROH) estimator. When at least one of the parents was genotyped, the findings revealed consistently high genomic inbreeding coefficients. However, skewed genomic inbreeding coefficients were seen in cows genotyped with MD SNP panels whose SNPs were poorly represented in the chosen imputation SNP data set and did not have their parents genotyped, in contrast to what was predicted based on actual genotype data. For cows genotyped with MD, the estimators Fhat1, Fhat2, and Fgrm gave greater genomic inbreeding coefficients, even when both parents and the maternal grandsire were genotyped. Overall, FROH was the strongest estimator, followed by F and Fhat3.

Word genome single nucleotide polymorphisms (SNPs) are frequently employed in cattle breeding programs throughout the globe to estimate genomic breeding values, as well as genome-wide association studies, population genetics, and determining realized homozygosity and inbreeding. Breeding businesses may cut genotyping costs by genotyping a small number of core animals with HD SNP panels and a large number of LD/HD animals, then projecting them to HD genotypes or a set of predetermined SNPs.

Imputation success in dairy cattle breeding is determined by three major factors: the relationship between core animals genotyped in HD and those to be imputed from LD/MD to HD, the distribution along the genome and the number of SNPs in the LD/MD panels, and the linkage disequilibrium between SNPs in the LD/MD and HD. Although there are strategies for achieving high imputation accuracy, variability in genomic estimations based on imputed SNP data is to be anticipated.

This work expands on recent findings on whole genome imputation SNP-based genomic inbreeding coefficients (FSNP) in dairy cattle. Extreme genomic inbreeding coefficients might be the outcome of imputation, particularly in cows genotyped with MD SNP panels with just a handful of their SNPs included in the final imputation SNP data. The goal of this research was to see whether significant genomic inbreeding coefficients in cows genotyped with MD SNP panels that had few of their SNPs included in the final imputation SNP data might be attributed to not having their parents genotyped during the imputation process.

Whole genome SNP data is frequently imputed in dairy cow breeding, which may significantly decrease genotyping costs. However, there may be cows with incorrect imputation owing to the lack of genotyped parents. The findings revealed that whole genome SNP inbreeding coefficients might be skewed for cows who did not have parents or maternal grandparents genotyped and were also genotyped with an SNP panel with low representation of its SNPs on the chosen imputation SNP data.

Artificial insemination businesses provide top genetics for dairy cow genetic improvement projects, with the most marketable bulls having the most genetic value. This extensive within-family selection results in higher degrees of connection, which leads to increased inbreeding. Reducing or even restricting inbreeding often results in the selection of lower-index bulls. As improved reproductive methods become more widely used and long-term technologies like as in vitro breeding evolve, selection intensities on bull and cow dams may skyrocket, worsening the situation even further.

The dairy genetics community must now decide who is prepared to decrease the pace of genetic gain in order to effectively regulate inbreeding. The literature has several instances of the negative impacts of inbreeding, however it is not true that all inbreeding is equal, and a distinct boundary exists between safe and risky. There is likely to be a tipping point beyond which we do not want to go, but its position is uncertain. Lush (1945) proposed that generations of high-intensity selection may necessarily result in large percentages of homozygosity.

To analyze the present situation, we may compare changes in phenotypic performance during inbreeding to rates of genetic gain. In all but one situation, annual genetic benefits outweigh inbreeding depression: the daughter pregnancy rate, which decreases by 0.02 PTA units each year. This is not to say that there is nothing to be worried about; it just means that we are not yet losing ground. As the phrase goes, “When you’re in a hole, stop digging,” but we need to act first.

The desire for elite genetics contributes to the continual loss of genetic variety in dairy cow herds, making it harder to preserve heterozygosity. Elite bulls are no longer enough; they must also have good breeding values for milk, components, fertility, and other attributes. Most marketed bulls cannot hit all of these criteria, but it is often assumed that they will.

Some measures may be used to reduce inbreeding rates in dairy cow herds. Refine PTA Adjustments: Genetic assessments in the United States are altered to account for the potential implications of future inbreeding. Predicted transmitting abilities (PTA) for bulls closely related to the population are reduced to account for inbreeding depression, while PTA for bulls less related to the population than average are increased to account for advantageous heterosis. However, the problem with this strategy is that the top AI bulls causing genetic change in the population are often severe outliers, and post-hoc modifications lack theoretical support.

Use the Right Metric: Genomic inbreeding assesses both identity-in-state and identity-by-descent, while pedigree inbreeding solely considers the latter. One technique to lower apparent inbreeding rates is to use pedigree inbreeding instead of genomic inbreeding. A more tempting strategy is to shift away from crude measurements of inbreeding and toward more accurate measures of diversity, such as runs of homozygosity (ROH) or direct measures of identity-by-descent (IBD). Timing is important, and older inbreeding is less concerning than current inbreeding since older haplotypes have been cleared of possible recessive genes.

Trim Pedigrees: Pedigree information is simple and inexpensive to record, but it has numerous limitations, including incompleteness, greater than expected genuine inbreeding, and underestimation of real ties among people. Trimming pedigrees to just a specific number of generations is a simple technique to minimize inbreeding. A similar alternative is to use a changing base year for inbreeding rather than a set reference year (the US uses 1960 as its base population).

Trimming pedigrees does not directly address rates of inbreeding in the population, either pedigree or genomic, but it is proposed because it may drive selection decisions away from families with the highest rates of recent inbreeding, which are the lineages most likely to contain genetic load that has not yet been purged.

The area of genetic selection has various obstacles, including the issue of bulls with the highest PTA being in high demand, independent culling levels, and implementing optimum contribution selection. To remedy this, it is proposed that instead of publicizing PTA for specific qualities, bulls be randomly assigned to the cow population. Bulls might also be given red, yellow, or green badges for each characteristic to signify their PTA, although this may not be desirable.

Homomorphic encryption may be used to hide the PTA provided to software from end users, although this is not a usual practice, and implementation is difficult. Hiding PTA would be a significant departure from existing methods, and most consumers or salesmen may not find this approach desirable.

Additional measures of genetic variety might be added to selection indices as a trait, exerting direct selection pressure on heterozygosity. This implies that choosing high-index bulls would entail some selection for increased heterozygosity, rather than trusting that inbreeding is taken into account during the mating process. However, this is a less efficient method of achieving optimum contribution selection, and it has been largely neglected in the United States since its inception.

Varona et al. (2019) recommended that an artificial purging system be built around a selection index that includes both breeding values and inbreeding burdens. This is a more attractive approach than include an ad hoc measure of variety in the index, and there is a strong theoretical underpinning to support its usage.

The implementation of optimum contribution selection in certain places, such as the United States, is not especially contentious owing to its complexity and the impression that the advantages do not outweigh the increased complexity. Many genetics end users are unwilling to accept the trade-off between genetic trend and heterozygosity preservation, and in a competitive market, they may just buy their sperm and embryos from another provider.

Finally, genetic protection procedures that limit germplasm interchange are allowing breeding projects run by several AI corporations to develop into distinct subpopulations within breeds. While it is unclear if these groupings are distinct enough to result in widespread outbreeding, current study indicates that bigger variances between families within a breed may exist than previously thought.

Genetics corporations may concentrate on selling embryos that represent perfect terminal dairy cows, necessitating a large increase in the scope of dairy embryo transfer. This would result in a system that is more like modern swine production than ancient dairy cow rearing. Some genetics businesses may begin selling embryos into smaller-scale specialist markets, such as those seeking high-genetic-merit polled animals.

Gene editing technologies have advanced, leading in increased efficiency and the capacity to stack numerous alterations. This might be a technique to sustain rates of genetic gain without experiencing negative repercussions or relying on natural purging. However, this strategy has several obstacles, including a lack of understanding about editing targets, an inability to edit dozens or hundreds of targets at the same time, and an ever-changing regulatory environment.

To effectively address the challenges posed by inbreeding, a collaboration between AI companies and the scientific community must persuade farmers that there is a real problem to be solved, that our proposed solutions will work, and that they are not being asked to jeopardize their livelihoods by participating in this process. The size of the issue is important, since many farmers are worried about the long-term impacts of inbreeding but do not necessarily agree that vigorous action must be done now. There is also common belief that the individuals who created the issue cannot be trusted to repair it, and that things function differently in the actual world than they do on paper.

Inbreeding is expected to attract greater attention in the future because of its impact on social license rather than production economics. Most laypeople are unaware of the fundamental distinction between inbreeding with stringent performance selection, as is used in animal breeding programs, and inbreeding with no performance selection. Increased genetic load also impairs an animal’s capacity to adapt to changes, which is concerning as the environment shifts.

Dairy cow breeding is a loosely connected method that allows for efficient management across the production chain. Effective population control will be challenging and will need adjustments on the side of AI businesses and farmers.

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• The U.S. dairy herd is 1% larger today but produces 19.2% more milk and 32.2% more butterfat.
• The industry’s Net Merit index, a proxy for cattle genetic progress on sustainability, shows that a cow produced by combining the best-known genes would be three times more sustainable based on improved genetics than the top Holstein bull on the market today.
• The introduction of genomics in 2008 has significantly improved milk, butterfat, and protein production, cow health, and cow longevity.
• The average genetic gain from 2000 to 2004 was $13.50 per year for marketed Holstein bulls.
• By 2010, genetic improvement leapt forward, more than doubling from $36.90 per year from 2004 to 2009 to the $83.33 annual genetic gain from 2010 to 2022.
• This six-fold improvement equates to a $329 million annual net gain when extrapolating this $70 annual gain per female across the annual U.S. dairy heifer calf crop.
• This development greatly enhances sustainability by generating more nutrition with less inputs.
• The aggregate gain since 2010 would be $4.28 billion when calculating the full genomic impact.
• This means the U.S. dairy industry needs fewer dairy cows each passing year to supply the same amount of milk to serve the domestic market or has transformed new growth in milk, butterfat, and protein into dairy products to deliver nutrition to international customers.
• ABS Global and Genus recently built a solar project at one of the world’s largest AI facilities, a bull barn in Wisconsin, housing 480 elite AI bulls.
• The complex includes a lab for processing bull semen, which accounts for nearly half of all sales in the U.S.
• This sexed semen product allows dairy farmers to use beef semen on dairy cows, reducing the number of replacements and generating more immediate revenue from dairy-beef cross calves.
• Research indicates that beef-dairy crossed calves are approaching the same efficiency as beef cattle and are 30% more efficient at converting feed to beef than Holstein steers.
• The combined amount of carbon saved by the solar panels’ production of electricity for the facility over 10 years is less than the carbon savings from just one month of genetic progress from future offspring of the facility’s 480 bulls.
• The genetic gain on offspring is measured by more production, better health, and longer cow life via the Net Merit Index.
• The impact for dairy processors is significant, with butterfat and protein production from Holstein cows improving annually by 0.46% and 1.23% annually in the genomic era.
• Genomic testing is making significant inroads as more females get tested each year, leading to less methane production, a reduced carbon footprint, and less feed for each additional unit of milk.
• By August 2023, CDCB received its 8 millionth genomic test, with 93% of genomic tests run on female dairy animals.
• The genetic super cow is not in sight, with the dairy community only 24% of the way to breeding the perfect Holstein cow.
• Genomic science can identify new traits that will help reduce methane production and carbon footprint, with the “feed saved” trait being the tip of the iceberg.

In the past 15 years, dairy farmers have been using genomic science to select cattle traits that improve productivity and support sustainability. The U.S. dairy herd today is 1% larger than in 2008 but produces 19.2% more pounds of milk and 32.2% more pounds of butterfat. The dairy industry still has room to grow more efficient through genomics. The industry’s Net Merit Index (NM$) shows that a cow produced by combining the best-known genes would be three times more sustainable based on improved genetics than the top Holstein bull on the market today.

Genomics has been the most important reason for improvements in milk, butterfat, and protein production, cow health, and cow longevity. The average genetic gain from 2000 to 2004 was $13.50 per year for marketed Holstein bulls. By 2010, genomic testing became commercially viable in the United States, genetic improvement leapt forward, more than doubling from $36.90 per year from 2004 to 2009 to $83.33 annual genetic gain from 2010 to 2022. This profound development greatly enhances sustainability, as new Holstein bulls entering active A.I. service father offspring that generate $83.33 in combined gains that enhance sustainability-related metrics.

Genetics has become a significant factor in the economic development of dairy farming, with research showing that beef-dairy crossed calves are approaching the same efficiency as beef cattle and are 30% more efficient at converting feed to beef than Holstein steers. This improvement in feed conversion and fewer days on feed prior to harvest yields a net carbon footprint reduction and reduced methane emissions. ABS Global found that the combined amount of carbon saved by the solar panels’ production of electricity for the facility over 10 years is less than the carbon savings from just one month of genetic progress from future offspring of the facility’s 480 bulls.

The impact of genomics on dairy processors has been significant, with butterfat and protein production improving annually by 0.46% and 1.75% annually in the genomic era. Commercial dairy farms have started to test more heifer calves at birth to determine those animals that would make the best replacements by making the best use of resources. Since 2020, it has taken less than 12 months to accumulate an additional 1 million genomic tests, with estimates indicating that 20% to 25% of the U.S. dairy heifer calf population is being tested annually.

However, genetic improvement is not yet reaching its ceiling, with only 24% of the dairy community being close to breeding the perfect Holstein cow. Genomic science can identify new traits that will help reduce methane production and carbon footprint, with the “feed saved” trait being the tip of the iceberg.

For the full story visit: Dairy Cattle Genomics is Quietly Improving Sustainability