Livestock milk has been a nutritious food source for humankind for thousands of years. Consequently, artificial selection has shaped the genome of modern farm mammals to increase milk yield and improve nutritional composition. Genomics and phenomics constitute two key pillars supporting modern genetic improvement in livestock species. Lactation genomics is concerned with the genome structure, function, evolution, and regulation underlying lactation biology. Genomics applications have revolutionized dairy cattle breeding globally in the past two decades. For example, genomic selection has increased genetic gain considerably by reducing generation intervals and increasing selection intensity and accuracy. Nowadays, dairy farmers can use genomic testing to support the more accurate selection or culling replacement decisions without waiting for progeny test results on males or lactation records on females. Additional benefits of genomics include verifying parentage, controlling inbreeding, and avoiding the spread of genetic disorders by using genomic-enhanced mating plans.
Lactation phenomics refers to high-dimensional and close-to-biology phenotypic data on an animal-wide scale, breaking down composite traits into more direct indicators of ultimate breeding goals that can be easily measured in large-scale farming applications. In practice, the success of selective breeding is highly dependent on the quality of phenotypes. While livestock breeders have used complex selection indices for decades to combine many traits into single performance measurement, there is a renewed interest in collecting high-throughput data on individual animals driven by various genome-mapping initiatives, precision livestock farming tools, environmental and societal challenges, and promising technologies for low-cost and accurate phenotypes. The latest ten-year blueprint for animal genomics research by the U.S. Department of Agriculture emphasizes the importance of closing the genome-to-phenome gaps.
Despite significant progress achieved in the past decades, lactation biology is still a novel science. The genomic and biological mechanisms underlying milk production and their relationship with other physiological processes are still largely unknown. In the context of genomic applications, there are opportunities and challenges with lactation genomics. For instance, we can now observe two types of bulls: young genomic-tested bulls and proven bulls from progeny tests. Genomic tests can be done right after birth or even with embryos. Hence, genomic-tested bulls are usually young and not yet producing milk-recording offspring, and they tend to have lower reliabilities than proven bulls. This situation imposes a dilemma for using genomic-tested bulls versus proven bulls in practice, and relevant strategies are not fully explored. Concerning genomic prediction, single-step genomic best linear unbiased prediction (ssGBLUP) enables the simultaneous integration of phenotypes, pedigree, and genomic information of all animals, regardless of being genotyped or not, but implementing ssGBLUP in dairy cattle is still challenging due to the vast number of genotyped animals available for genomic evaluation. In dairy cattle, crossbreeding schemes (e.g., Beef-on-Dairy) are gaining popularity in recent years, but current methods to predict crossbred performance are arguably limited to additive genetic effects. Non-additive genetic effects such as dominance and epistasis are essential components contributing to crossbred performance but are not well modeled by current prediction models. Modeling genotype-by-environment (GxE) interactions based on genomic data and comprehensive environmental gradients is paramount for identifying breeding candidates for specific geographical regions and production systems. The use of whole-genome sequence data to better understand the genomic background of lactation in farm animals and make predictions of genomic breeding values is also advancing at a fast rate over the past decade. Many more topics and domains in lactation genomics are still yet to be addressed.
This Research Topic is intended to provide a forum on all aspects of lactation genomics and phenomics in livestock or model animals (e.g., cattle, sheep, goats, buffaloes, camels, yaks) and information for bridging the genome-to-phenome gap. We welcome review and research papers on relevant topics, which include but are not limited to the following:
• Genomics underlying the structure and functionality of lactation biology.
• Prediction of dairy crossbred performance.
• Recognition of Mendelian traits using genomics, including deleterious recessive traits.
• Phenotypic and genomic modeling of test-day records for dairy genetic evaluations.
• Yield correction factors for estimating daily and lactation yields.
• Genetics and genomics of lactation persistency, including modeling and economic analyses.
• Genomic selection models for dairy cattle breeding, including single-step BLUP and alternative approaches.
• Selection indices for refining dairy cattle breeding goals.
• Impact of low pass sequencing and genotype imputation on genomic prediction.
• The dilemma of young genomic tested versus proven dairy bulls and relevant strategies.
• Tropical dairy breeding focusing on adaptation and environmental resilience (e.g., heat tolerance, survival, and resistance to endo- and ectoparasites).
• Genomics solutions to metabolic and nutritional problems related to milk production.
• Genomic mating and sustainable dairy breeding, farming, and management.
• Genomics and phenomics solutions for small populations of dairy cattle.
• On-farm analytics and precision management for providing the optimal environment for high-performing dairy cows and timely management decisions.
• Genomic solutions with a balanced emphasis on efficiency and resilience.
• Analyses of the trade-offs of dairy productivity and overall animal resilience.
• Bridging the genome-to-phenome gap by enhanced understanding in detail of how genomic information encoded is translated into a phenotype.
• Opportunities and challenges associated with new phenotypes or data from high-throughput phenotyping with a focus on milk production.
• Country or regional reports as retrospective and prospective reviews of studies and applications in dairy genomics or/and phenomics; and,
• Economic and societal/cultural analyses or surveys related to dairy production and novel farming systems.
Livestock milk has been a nutritious food source for humankind for thousands of years. Consequently, artificial selection has shaped the genome of modern farm mammals to increase milk yield and improve nutritional composition. Genomics and phenomics constitute two key pillars supporting modern genetic improvement in livestock species. Lactation genomics is concerned with the genome structure, function, evolution, and regulation underlying lactation biology. Genomics applications have revolutionized dairy cattle breeding globally in the past two decades. For example, genomic selection has increased genetic gain considerably by reducing generation intervals and increasing selection intensity and accuracy. Nowadays, dairy farmers can use genomic testing to support the more accurate selection or culling replacement decisions without waiting for progeny test results on males or lactation records on females. Additional benefits of genomics include verifying parentage, controlling inbreeding, and avoiding the spread of genetic disorders by using genomic-enhanced mating plans.
Lactation phenomics refers to high-dimensional and close-to-biology phenotypic data on an animal-wide scale, breaking down composite traits into more direct indicators of ultimate breeding goals that can be easily measured in large-scale farming applications. In practice, the success of selective breeding is highly dependent on the quality of phenotypes. While livestock breeders have used complex selection indices for decades to combine many traits into single performance measurement, there is a renewed interest in collecting high-throughput data on individual animals driven by various genome-mapping initiatives, precision livestock farming tools, environmental and societal challenges, and promising technologies for low-cost and accurate phenotypes. The latest ten-year blueprint for animal genomics research by the U.S. Department of Agriculture emphasizes the importance of closing the genome-to-phenome gaps.
Despite significant progress achieved in the past decades, lactation biology is still a novel science. The genomic and biological mechanisms underlying milk production and their relationship with other physiological processes are still largely unknown. In the context of genomic applications, there are opportunities and challenges with lactation genomics. For instance, we can now observe two types of bulls: young genomic-tested bulls and proven bulls from progeny tests. Genomic tests can be done right after birth or even with embryos. Hence, genomic-tested bulls are usually young and not yet producing milk-recording offspring, and they tend to have lower reliabilities than proven bulls. This situation imposes a dilemma for using genomic-tested bulls versus proven bulls in practice, and relevant strategies are not fully explored. Concerning genomic prediction, single-step genomic best linear unbiased prediction (ssGBLUP) enables the simultaneous integration of phenotypes, pedigree, and genomic information of all animals, regardless of being genotyped or not, but implementing ssGBLUP in dairy cattle is still challenging due to the vast number of genotyped animals available for genomic evaluation. In dairy cattle, crossbreeding schemes (e.g., Beef-on-Dairy) are gaining popularity in recent years, but current methods to predict crossbred performance are arguably limited to additive genetic effects. Non-additive genetic effects such as dominance and epistasis are essential components contributing to crossbred performance but are not well modeled by current prediction models. Modeling genotype-by-environment (GxE) interactions based on genomic data and comprehensive environmental gradients is paramount for identifying breeding candidates for specific geographical regions and production systems. The use of whole-genome sequence data to better understand the genomic background of lactation in farm animals and make predictions of genomic breeding values is also advancing at a fast rate over the past decade. Many more topics and domains in lactation genomics are still yet to be addressed.
This Research Topic is intended to provide a forum on all aspects of lactation genomics and phenomics in livestock or model animals (e.g., cattle, sheep, goats, buffaloes, camels, yaks) and information for bridging the genome-to-phenome gap. We welcome review and research papers on relevant topics, which include but are not limited to the following:
• Genomics underlying the structure and functionality of lactation biology.
• Prediction of dairy crossbred performance.
• Recognition of Mendelian traits using genomics, including deleterious recessive traits.
• Phenotypic and genomic modeling of test-day records for dairy genetic evaluations.
• Yield correction factors for estimating daily and lactation yields.
• Genetics and genomics of lactation persistency, including modeling and economic analyses.
• Genomic selection models for dairy cattle breeding, including single-step BLUP and alternative approaches.
• Selection indices for refining dairy cattle breeding goals.
• Impact of low pass sequencing and genotype imputation on genomic prediction.
• The dilemma of young genomic tested versus proven dairy bulls and relevant strategies.
• Tropical dairy breeding focusing on adaptation and environmental resilience (e.g., heat tolerance, survival, and resistance to endo- and ectoparasites).
• Genomics solutions to metabolic and nutritional problems related to milk production.
• Genomic mating and sustainable dairy breeding, farming, and management.
• Genomics and phenomics solutions for small populations of dairy cattle.
• On-farm analytics and precision management for providing the optimal environment for high-performing dairy cows and timely management decisions.
• Genomic solutions with a balanced emphasis on efficiency and resilience.
• Analyses of the trade-offs of dairy productivity and overall animal resilience.
• Bridging the genome-to-phenome gap by enhanced understanding in detail of how genomic information encoded is translated into a phenotype.
• Opportunities and challenges associated with new phenotypes or data from high-throughput phenotyping with a focus on milk production.
• Country or regional reports as retrospective and prospective reviews of studies and applications in dairy genomics or/and phenomics; and,
• Economic and societal/cultural analyses or surveys related to dairy production and novel farming systems.
