A 100-Year Review: Methods and impact of genetic selection in dairy cattle-From daughter-dam comparisons to deep learning algorithms.

In the early 1900s, breed society herdbooks had been established and milk-recording programs were in their infancy. Farmers wanted to improve the productivity of their cattle, but the foundations of population genetics, quantitative genetics, and animal breeding had not been laid. Early animal breeders struggled to identify genetically superior families using performance records that were influenced by local environmental conditions and herd-specific management practices. Daughter-dam comparisons were used for more than 30 yr and, although genetic progress was minimal, the attention given to performance recording, genetic theory, and statistical methods paid off in future years. Contemporary (herdmate) comparison methods allowed more accurate accounting for environmental factors and genetic progress began to accelerate when these methods were coupled with artificial insemination and progeny testing. Advances in computing facilitated the implementation of mixed linear models that used pedigree and performance data optimally and enabled accurate selection decisions. Sequencing of the bovine genome led to a revolution in dairy cattle breeding, and the pace of scientific discovery and genetic progress accelerated rapidly. Pedigree-based models have given way to whole-genome prediction, and Bayesian regression models and machine learning algorithms have joined mixed linear models in the toolbox of modern animal breeders. Future developments will likely include elucidation of the mechanisms of genetic inheritance and epigenetic modification in key biological pathways, and genomic data will be used with data from on-farm sensors to facilitate precision management on modern dairy farms.

Relationship between gene polymorphism and milk production traits in Teleorman Black Head sheep breed / Relación entre el polimorfismo de genes y rasgos de producción de leche en la ovejas Teleorman cabeza negra

Objective. This study is a preliminary step of a larger national program aimed to develop a strategy for "in situ" preservation of Teleorman Black Head sheep population. In this paper we estimated the effect of β-lactoglobulin, casein and prolactin on some quantitative and qualitative milk traits in this local sheep population. Material and methods. Genotyping methodology included PCR for CSN3 (A and B alleles) and PCR-RFLP for LGB (A and B alleles) and PRL (T and C alleles), respectively. Repeated milking and milk composition analysis were used for the polymorphism effect estimation. Results. No association between CSN3 polymorphism and milk traits was found. Effect of LGB on production traits was quite constant. Genotype AA performed better than AA. PRL marker effect showed small differences than LGB. Concerning milk, fat and protein yield, AA genotype for PRL had a smaller positive impact than AA genotype for LGB. Regarding fat and protein content, PRL showed a negative effect for AA and positive for AA genotype, respectively. Conclusions. Positive association between LGB and milk yield and composition recommend this candidate gene like marker for a future MAS program. Although PRL gene is also associated with an increased milk quantity, inverse response over milk composition must be considered in MAS strategy. Our study demonstrated that both LGB and PRL markers could became an advent of MAS utilization in Romanian dairy sheep breeding industry.

Objetivo. Este estudio es un paso preliminar de un programa nacional más amplio destinado a desarrollar una estrategia para la conservación "in situ"de la población de ovejas Cabeza Negra de Teleorman. En este trabajo se estimó el efecto de la β-lactoglobulina, caseína y prolactina en algunos rasgos cuantitativos y cualitativos de la leche en esta población de ovejas locales. Material y métodos. Metodología de PCR para genotipificación incluido CSN3 (A y B alelos) y PCR-RFLP para LGB (A y B alelos) y PRL (T y C alelos). Análisis y composición de la leche de ordeños repetidos se utilizaron para estimación el efecto del polimorfismo. Resultados. No se encontró asociación entre el polimorfismo y la leche rasgos CSN3. Efecto de LGB en los rasgos de producción era bastante constante. Genotipo AA obtenido mejores resultados que AA. Efecto marcador PRL mostró pequeñas diferencias que LGB. En cuanto a la leche grasa y proteína el genotipo AA para PRL tuvo un impacto positivo más pequeño que el genotipo AA para LGB. En cuanto a contenido de grasa y proteína, PRL mostró un efecto negativo para AA y positivo para AA genotipo. Conclusiones. La asociación positiva entre LGB y la producción de leche y la composición recomienda este gen candidato como marcador para un futuro programa de MAS. Aunque gen PRL también se asocia con un incremento en la cantidad de leche, la respuesta inversa sobre composición de la leche debe ser considerado en la estrategia de MAS. Nuestro estudio demostró que los marcadores tanto LGB y PRL podrían venir a ser utilizados en MAS en la industria rumana de cría de ovejas lecheras.