Genetic Markers Associated with Milk Production and Thermotolerance in Holstein Dairy Cows Managed in a Heat-Stressed Environment

Influence of different environmental challenges on the expression of productive traits in Holstein cattle in the southern region of Brazil

The genotype-environment interaction (GEI) can lead to variations in gene expression related to traits, affecting the breeding value of animals. Assess the effects of GEI on milk yield (MY), fat yield (FY), and protein yield (PY) at 305 days in milk in first-, second and third-parity cows, employing the reaction norms model for Holstein cattle in Paraná state. The study utilized data from the milk testing service provided by the Paraná Association of Holstein Cattle Breeders (APCBRH) in Curitiba, PR, Brazil. This encompassed records from 378,000 records across one to three lactations from 2012 to 2022, originating from 513 herds in 72 cities within the state of Paraná. The environmental gradient was established by standardizing the contemporary group solutions derived from the animal model, disregarding GEI. Reaction norms were calculated using a Random Regression Model, and genotype classification correlations were determined by Spearman's correlation, comparing the breeding values estimated for the analyzed traits in each environmental gradient. Heritability for MY during the first lactation was moderate (0.28) in the least challenging environmental gradient, but of low magnitude (0.18) in the most challenging one. FY heritability estimates varied from low (0.09) to moderate (0.28) across environmental gradients, whereas PY heritability remained low regardless of lactation number and environmental challenge. The study did not identify the occurrence of GEI effects on fat yield, irrespective of parity. No GEI effect was observed on MY or PY in the first and second lactations. However, in the third lactation, GEI affected significantly the MY and PY in Holstein cattle in the state of Paraná, particularly under extreme environmental gradients. The selection for MY, PY, and FY during the first lactation may be the best strategy to promote genetic progress in these traits, because of the smaller effect of GEI at this stage.

Validation of Polymorphisms Associated with the Immune Response After Vaccination Against Porcine Reproductive and Respiratory Syndrome Virus in Yorkshire Gilts

Porcine respiratory and reproductive syndrome is a viral disease that impacts the health and profitability of swine farms, largely due to significant variation in the vaccination response. The objective was to identify and validate molecular markers associated with the antibody response in gilts following vaccination against the PRRSV. The study included one hundred (n = 100) 6-month-old Yorkshire gilts that were negative for the PRRSV. Gilts were randomly assigned to one of two treatments, PRRS-vaccinated (n = 75) and control (n = 25) groups. Blood samples collected on day 21 were analyzed to evaluate the antibody response, as indicated by the sample-to-positive (S/P) ratio, to the PRRSV following vaccination. DNA was extracted and genotyped using a low-density chip containing 10,000 single nucleotide polymorphisms (SNPs). A genome-wide association study (GWAS) was conducted to identify candidate SNPs associated with the S/P ratio, which were validated in two independent gilt populations (n = 226). The SNPs rs707264998, rs708860811, and rs81358818 in the genes RNF144B, XKR9, and BMAL1, respectively, were significantly associated (p < 0.01) with the S/P ratio and demonstrated an additive effect. In conclusion, three SNPs are proposed as candidate markers for an enhanced immune response to vaccination against the PRRSV and may be beneficial in genetic selection programs.

Analysis of Population Structure and Selective Signatures for Milk Production Traits in Xinjiang Brown Cattle and Chinese Simmental Cattle

This study aims to elucidate the population structure and genetic diversity of Xinjiang brown cattle (XJBC) and Chinese Simmental cattle (CSC) while conducting genome-wide selective signatures analyses to identify selected genes associated with milk production traits in both breeds. Based on whole-genome resequencing technology, whole-genome single nucleotide polymorphisms (SNPs) of 83 Xinjiang brown cattle and 80 Chinese Simmental cattle were detected to resolve the genetic diversity and genetic structure of the two populations, whole-genome selective elimination analysis was performed for the two breeds of cattle using the fixation index (Fst) and nucleotide diversity (θπ ratio), and enrichment analysis was performed to explore their biological functions further. Both breeds exhibited relatively rich genetic diversity, with the Chinese Simmental cattle demonstrating higher genetic diversity than Xinjiang brown cattle. The IBS and G matrix results indicated that most individuals in the two populations were farther apart from each other. The PCA and neighbor-joining tree revealed no hybridization between the two breeds, but there was a certain degree of genetic differences among the individuals in the two breeds. Population structure analysis revealed that the optimal number of ancestors was three when K = 3. This resulted in clear genetic differentiation between the two populations, with only a few individuals having one ancestor and the majority having two or three common ancestors. A combined analysis of Fst and θπ was used to screen 112 candidate genes related to milk production traits in Xinjiang brown cattle and Chinese Simmental cattle. This study used genome-wide SNP markers to reveal the genetic diversity, population structure, and selection characteristics of two breeds. This study also screened candidate genes related to milk production traits, providing a theoretical basis for conserving genetic resources and improving genetic selection for milk production traits in Xinjiang brown cattle and Chinese Simmental cattle.

Applications of Next-Generation Sequencing Technologies and Statistical Tools in Identifying Pathways and Biomarkers for Heat Tolerance in Livestock

The climate change-associated abnormal weather patterns negatively influences the productivity and performance of farm animals. Heat stress is the major detrimental factor hampering production, causing substantial economic loss to the livestock industry. Therefore, it is important to identify heat-tolerant breeds that can survive and produce optimally in any given environment. To achieve this goal, a clearer understanding of the genetic differences and the underlying molecular mechanisms associated with climate change impacts and heat tolerance are a prerequisite. Adopting next-generation biotechnological and statistical tools like whole transcriptome analysis, whole metagenome sequencing, bisulphite sequencing, genome-wide association studies (GWAS), and selection signatures provides an opportunity to achieve this goal. Through these techniques, it is possible to identify permanent genetic markers for heat tolerance, and by incorporating those markers in marker-assisted breeding selection, it is possible to achieve the target of breeding for heat tolerance in livestock. This review gives an overview of the recent advancements in assessing heat tolerance in livestock using such 'omics' approaches and statistical models. The salient findings from this research highlighted several candidate biomarkers that have the potential to be incorporated into future heat-tolerance studies. Such approaches could revolutionise livestock production in the changing climate scenario and support the food demands of the growing human population.

Developmental programming of production and reproduction in dairy cows: V. Association of the main and interactive effects of maternal level of milk production and milk fat to protein ratio with offspring's birth weight, survival, and productive and reproductive performance from birth to the first lactation period

Level of dam milk production (DMP) and dam milk fat to protein ratio (DFPR), as an indicator of metabolic status in dairy cows, have been identified to be associated with productive and reproductive performance of the offspring. Yet whether the interaction of DMP by DFPR can be associated with performance of the offspring have not been studied to our knowledge. Therefore, the present study was conducted to investigate the association of the main and interactive effects of DMP and DFPR with offspring's birth weight, survival, milk yield and fertility. To this end, data of birth weight, culling rate, milk yield and reproductive variables of offspring born to lactating dams (n = 14,582) and data associated with DMP and DFPR during 305-day lactation were retrieved. Afterwards, offspring were classified in three categories of DMP, including DMP1 (dams with <10.00 × 103 kg of 305-day milk production), DMP2 (dams with ≥10.00 × 103 kg and <14.00 × 103 kg of 305-day milk production), DMP3 (dams with ≥14.00 × 103 kg of 305-day milk production), and three categories of DFPR, including DFPR1 (offspring born to dams with <1.00 FPR), DFPR2 (offspring born to dams with ≥1.00 and < 1.40 FPR) and DFPR3 (offspring born to dams with ≥1.40 FPR). Statistical analysis revealed no association of the interaction effect of DMP by DFPR with investigated variables in the offspring (P > 0.05). However, the main effect of DMP was positively associated with milk yield, but negatively associated with survival, age at first insemination and conception during nulliparity, and transgenerational improvement in milk yield in the offspring (P < 0.05). Moreover, the main effect of DFPR was positively associated with birth weight, survival and first service conception rate during nulliparity, but negatively associated with metabolic status and reproductive performance during primiparity in the offspring (P < 0.05). In conclusion, the present study did not find any interaction effect of DMP by DFPR on productive and reproductive variables in the offspring. This finding implicates the association of DMP with milk production in the offspring was regardless of DFPR. Moreover, this finding implies the association of DFPR with postpartum metabolic status and reproductive performance in the offspring was regardless of DMP.

Genetic factors influencing milk and fat yields in tropically adapted dairy cattle: insights from quantitative trait loci analysis and gene associations

OBJECTIVE

The objective of this study was to identify genes associated with 305-day milk yield (MY) and fat yield (FY) that also influence the adaptability of the Thai multibreed dairy cattle population to tropical conditions.

METHODS

A total of 75,776 imputed and actual single nucleotide polymorphisms (SNPs) from 2,661 animals were used to identify genomic regions associated with MY and FY using the single-step genomic best linear unbiased predictions. Fixed effects included herd-yearseason, breed regression, heterosis regression and calving age regression effects. Random effects were animal additive genetic and residual. Individual SNPs with a p-value smaller than 0.05 were selected for gene mapping, function analysis, and quantitative trait loci (QTL) annotation analysis.

RESULTS

A substantial number of QTLs associated with MY (9,334) and FY (8,977) were identified by integrating SNP genotypes and QTL annotations. Notably, we discovered 17 annotated QTLs within the health and exterior QTL classes, corresponding to nine unique genes. Among these genes, Rho GTPase activating protein 15 (ARHGAP15) and catenin alpha 2 (CTNNA2) have previously been linked to physiological traits associated with tropical adaptation in various cattle breeds. Interestingly, these two genes also showed signs of positive selection, indicating their potential role in conferring tolerance to trypanosomiasis, a prevalent tropical disease.

CONCLUSION

Our findings provide valuable insights into the genetic basis of MY and FY in the Thai multibreed dairy cattle population, shedding light on the underlying mechanisms of tropical adaptation. The identified genes represent promising targets for future breeding strategies aimed at improving milk and fat production while ensuring resilience to tropical challenges. This study significantly contributes to our understanding of the genetic factors influencing milk production and adaptability in dairy cattle, facilitating the development of sustainable genetic selection strategies and breeding programs in tropical environments.

The Anti-Müllerian Hormone as Endocrine and Molecular Marker Associated with Reproductive Performance in Holstein Dairy Cows Exposed to Heat Stress

Anti-Müllerian hormone (AMH) is proposed as a biomarker for fertility in cattle, yet this associative relationship appears to be influenced by heat stress (HS). The objective was to test serum AMH and AMH-related single nucleotide polymorphisms (SNPs) as markers potentially predictive of reproductive traits in dairy cows experiencing HS. The study included 300 Holstein cows that were genotyped using BovineSNP50 (54,000 SNP). A genome-wide association study was then executed. Nine intragenic SNPs within the pathways that influence the AMH gene were found important with multiple comparisons adjustment tests (p < 1.09 × 10-6). A further validation study was performed in an independent Holstein cattle population, which was divided into moderate (MH; n = 152) and severe heat-stressed (SH; n = 128) groups and then subjected to a summer reproductive management program. Serum AMH was confirmed as a predictor of fertility measures (p < 0.05) in MH but not in the SH group. Cows were genotyped, which revealed four SNPs as predictive markers for serum AMH (p < 0.01), reproductive traits (p < 0.01), and additional physiological variables (p < 0.05). These SNPs were in the genes AMH, IGFBP1, LGR5, and TLR4. In conclusion, serum AMH concentrations and AMH polymorphisms are proposed as predictive markers that can be used in conjunction with genomic breeding value approaches to improve reproductive performance in Holstein cows exposed to summer HS conditions.

Candidate genes associated with heat stress and breeding strategies to relieve its effects in dairy cattle: a deeper insight into the genetic architecture and immune response to heat stress

The need for food products of animal origin is increasing worldwide. Satisfying these needs in a way that has minimal impact on the environment requires cutting-edge technologies and techniques to enhance the genetic quality of cattle. Heat stress (HS), in particular, is affecting dairy cattle with increasing frequency and severity. As future climatic challenges become more evident, identifying dairy cows that are more tolerant to HS will be important for breeding dairy herds that are better adapted to future environmental conditions and for supporting the sustainability of dairy farming. While research into the genetics of HS in the context of the effect of global warming on dairy cattle is gaining momentum, the specific genomic regions involved in heat tolerance are still not well documented. Advances in omics information, QTL mapping, transcriptome profiling and genome-wide association studies (GWAS) have identified genomic regions and variants associated with tolerance to HS. Such studies could provide deeper insights into the genetic basis for response to HS and make an important contribution to future breeding for heat tolerance, which will help to offset the adverse effects of HS in dairy cattle. Overall, there is a great interest in identifying candidate genes and the proportion of genetic variation associated with heat tolerance in dairy cattle, and this area of research is currently very active worldwide. This review provides comprehensive information pertaining to some of the notable recent studies on the genetic architecture of HS in dairy cattle, with particular emphasis on the identified candidate genes associated with heat tolerance in dairy cattle. Since effective breeding programs require optimal knowledge of the impaired immunity and associated health complications caused by HS, the underlying mechanisms by which HS modulates the immune response and renders animals susceptible to various health disorders are explained. In addition, future breeding strategies to relieve HS in dairy cattle and improve their welfare while maintaining milk production are discussed.

Exploring Genetic Markers: Mitochondrial DNA and Genomic Screening for Biodiversity and Production Traits in Donkeys

Donkeys (Equus asinus) play a pivotal role as essential livestock in arid and semi-arid regions, serving various purposes such as transportation, agriculture, and milk production. Despite their significance, donkey breeding has often been overlooked in comparison to other livestock species, resulting in limited genetic improvement programs. Preserving donkey genetic resources within each country necessitates the establishment of breed conservation programs, focusing on managing genetic diversity among populations. In recent years, significant strides have been made in sequencing and analyzing complete mitochondrial DNA (mtDNA) molecules in donkeys. Notably, numerous studies have honed in on the mitochondrial D-loop region, renowned for its remarkable variability and higher substitution rate within the mtDNA genome, rendering it an effective genetic marker for assessing genetic diversity in donkeys. Furthermore, genetic markers at the RNA/DNA level have emerged as indispensable tools for enhancing production and reproduction traits in donkeys. Traditional animal breeding approaches based solely on phenotypic traits, such as milk yields, weight, and height, are influenced by both genetic and environmental factors. To overcome these challenges, genetic markers, such as polymorphisms, InDel, or entire gene sequences associated with desirable traits in animals, have achieved widespread usage in animal breeding practices. These markers have proven increasingly valuable for facilitating the selection of productive and reproductive traits in donkeys. This comprehensive review examines the cutting-edge research on mitochondrial DNA as a tool for assessing donkey biodiversity. Additionally, it highlights the role of genetic markers at the DNA/RNA level, enabling the informed selection of optimal production and reproductive traits in donkeys, thereby driving advancements in donkey genetic conservation and breeding programs.