The future of phenomics in dairy cattle breeding

Cole, John B.; Eaglen, Sophie; Maltecca, Christian; Mulder, Henk; Pryce, J.E.

doi:10.1093/af/vfaa007

Cited by 46 publications

(37 citation statements)

References 29 publications

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“…It is a wellknown principle in genetic improvement programs that the phenotype is the driver of population improvement (Coffey, 2020). New technologies are enabling the largescale collection of novel phenotypes, such as milk composition and animal behavior, often in real-time (Cole et al, 2020). Although such high-throughput phenotyping has been a feature of plant improvement programs for several years (e.g., Fahlgren et al, 2015), it is still in its early stages in livestock production systems (Koltes et al, 2019).…”

Section: New Technologies New Participants and New Pipelinesmentioning

confidence: 99%

Invited review: The future of selection decisions and breeding programs: What are we breeding for, and who decides?

Cole

Dürr

Nicolazzi

2021

Journal of Dairy Science

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Genetic selection has been a very successful tool for the long-term improvement of livestock populations, and the rapid adoption of genomic selection over the last decade has doubled the rate of gain in some populations. Breeding programs seek to identify genetically superior parents of the next generation, typically as a function of an index that combines information about many economically important traits into a single number. In the United States, the data that drive this system are collected through the national dairy herd improvement program that began more than a century ago. The resulting information about animal performance, pedigree, and genotype is used to compute genomic evaluations for comparing and ranking animals for selection. However, the full expression of genetic potential requires that animals are placed in environments that can support such performance. The Agricultural Research Service of the US Department of Agriculture and the Council on Dairy Cattle Breeding collaborate to deliver state-of-the-art genomic evaluations to the dairy industry. Today, most breeding stock are selected and marketed using the net merit dollars (NM$) selection index, which evolved from 2 traits in 1926 (milk and fat yield) to a combination of 36 individual traits following the last NM$ update in 2018. Updates to NM$ require the estimation of many different values, and it can be difficult to achieve consensus from stakeholders on what should be added to, or removed from, the index at each review, and how those traits should be weighted. Over time, the majority of the emphasis in the index has shifted from yield traits to fertility, health, and fitness traits. Phenotypes for some of these new traits are difficult or expensive to measure, or require changes to on-farm habits that have not been widely adopted. This is driving interest in sensor-based systems that provide continuous measurements of the farm environment, individual animal performance, and detailed milk composition. There is also a need to capture more detailed data about the environment in which animals perform, including information about feeding, housing, milking systems, and infectious and parasitic load. However, many challenges accompany these new technologies, including a lack of standardization or validation, need for high-speed internet connections, increased computational requirements, and interpretations that are often not backed by direct observations of biological phenomena. This work will describe how US selection objectives are developed, as well as discuss opportunities and challenges associated with new technologies for measuring and recording animal performance.

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Section: New Technologies New Participants and New Pipelinesmentioning

confidence: 99%

Invited review: The future of selection decisions and breeding programs: What are we breeding for, and who decides?

Cole

Dürr

Nicolazzi

2021

Journal of Dairy Science

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“…Phenomics is a hot, promising area but is not exempt from risks and cannot be considered a panacea. As Cole et al [12] warn us, 'these new approaches have their own challenges, ranging from bias to interpretability and there is a temptation to oversell outcomes' . One serious issue is that, in contrast to genotypes, phenome data may not be easily transferable or comparable across farms.…”

Section: The Way Aheadmentioning

confidence: 99%

“…This is surprising since new technologies allow the assessment of new phenotypes that are in high demand by the society, such as those related to animal welfare, resilience, disease incidence or resource use efficiency [5][6][7][8]. Fortunately, recent work indicates that animal phenomics is becoming popular in the animal sciences too, e.g., [9][10][11][12], and as reflected in public initiatives such as the USDA Agricultural Genomes to Phenomes Initiative AG2PI (https ://www.ag2pi .org/).…”

Section: Introductionmentioning

confidence: 99%

Phenomes: the current frontier in animal breeding

Pérez‐Enciso

Steibel

2021

Genet Sel Evol

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Improvements in genomic technologies have outpaced the most optimistic predictions, allowing industry-scale application of genomic selection. However, only marginal gains in genetic prediction accuracy can now be expected by increasing marker density up to sequence, unless causative mutations are identified. We argue that some of the most scientifically disrupting and industry-relevant challenges relate to ‘phenomics’ instead of ‘genomics’. Thanks to developments in sensor technology and artificial intelligence, there is a wide range of analytical tools that are already available and many more will be developed. We can now address some of the pressing societal demands on the industry, such as animal welfare concerns or efficiency in the use of resources. From the statistical and computational point of view, phenomics raises two important issues that require further work: penalization and dimension reduction. This will be complicated by the inherent heterogeneity and ‘missingness’ of the data. Overall, we can expect that precision livestock technologies will make it possible to collect hundreds of traits on a continuous basis from large numbers of animals. Perhaps the main revolution will come from redesigning animal breeding schemes to explicitly allow for high-dimensional phenomics. In the meantime, phenomics data will definitely enlighten our knowledge on the biological basis of phenotypes.

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“…They also found that while level of supplementary feeding influenced the magnitude of difference between cows, it did not affect direction of trends. Recently, Cole et al (2020) illustrated the proportion of improvement in milk protein yield of US Holstein cattle attributable to improved genetic and environment (management). Using a similar approach on Australian data, one-third of the gain in protein yield since 1990 can be attributed to genetic improvement ( Fig.…”

Section: Macro-valuation Example 1: Genetic Gain Versus Phenotypic Imentioning

confidence: 99%

Demonstrating the value of herd improvement in the Australian dairy industry

Newton

Axford²,

et al. 2021

Anim. Prod. Sci.

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Herd improvement has been occurring since the domestication of livestock, although the tools and technologies that support it have changed dramatically. The Australian dairy industry tracks herd improvement through a range of approaches, including routine monitoring of genetic trends and farmer usage of the various tools and technologies. However, a less structured approach has been taken to valuing the realised and potential impacts of herd improvement. The present paper aims to demonstrate the value of herd improvement, while exploring considerations for undertaking such a valuation. Attractive value propositions differ among and within dairy stakeholder groups. While broad-scale valuations of genetic trends and industry progress are valued by government and industry, such valuations do not resonate with farmers. The cumulative nature of genetic gain and compounding factor of genetic lag means that long timeframes are needed to fully illustrate the value of genetic improvement. However, such propositions do not align with decision-making timeframes of most farming businesses. Value propositions that resonate with farmers and can lead to increased uptake and confidence in herd improvement tools include smaller scale cost–benefit analyses and on-farm case studies developed in consultation with industry, including farmers. Non-monetary assessments of value, such as risk and environmental footprint, are important to some audiences. When additionality, that is, the use of data on multiple occasions, makes quantifying the value of the data hard, qualitative assessments of value can be helpful. This is particularly true for herd recording data. Demonstrating the value of herd improvement to the dairy industry, or any livestock sector, requires a multi-faceted approach that extends beyond monetary worth. No single number can effectively capture the full value of herd improvement in a way that resonates with all farmers, let alone dairy stakeholders. Extending current monitoring of herd improvement to include regular illustrations of the value of the tools that underpin herd improvement is important for fostering uptake of new or improved tools as they are released to industry.

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The future of phenomics in dairy cattle breeding

Cited by 46 publications

References 29 publications

Invited review: The future of selection decisions and breeding programs: What are we breeding for, and who decides?

Invited review: The future of selection decisions and breeding programs: What are we breeding for, and who decides?

Phenomes: the current frontier in animal breeding

Demonstrating the value of herd improvement in the Australian dairy industry

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