Methodology for the identification of relevant loci for milk traits in dairy cattle, using machine learning algorithms.

Machine learning methods were considered efficient in identifying single nucleotide polymorphisms (SNP) underlying a trait of interest. This study aimed to construct predictive models using machine learning algorithms, to identify loci that best explain the variance in milk traits of dairy cattle. Further objectives involved validating the results by comparison with reported relevant regions and retrieving the pathways overrepresented by the genes flanking relevant SNPs. Regression models using XGBoost (XGB), LightGBM (LGB), and Random Forest (RF) algorithms were trained using estimated breeding values for milk production (EBVM), milk fat content (EBVF) and milk protein content (EBVP) as phenotypes and genotypes on 40417 SNPs as predictor variables. To evaluate their efficiency, metrics for actual vs. predicted values were determined in validation folds (XGB and LGB) and out-of-bag data (RF). Less than 4500 relevant SNPs were retrieved for each trait. Among the genes flanking them, signaling and transmembrane transporter activities were overrepresented. The models trained:•Predicted breeding values for animals not included in the dataset.•Were efficient in identifying a subset of SNPs explaining phenotypic variation. The results obtained using XGB and LGB algorithms agreed with previous results. Therefore, the method proposed could be applied for future association studies on milk traits.

MVAΔ008 viral vector encoding the model protein OVA induces improved immune response against the heterologous antigen and equal levels of protection in a mice tumor model than the conventional MVA.

Modified vaccinia Ankara virus (MVA) is extensively used as a vaccine vector. We have previously observed that MVAΔ008, an MVA lacking the gene that codes for interleukin-18 binding protein, significantly increases CD8+ and CD4+ T-cell responses to vaccinia virus (VACV) epitopes and recombinant HIV antigens. However, the efficacy of this vector against pathogens or tumor cells remains unclear. Thus, the aim of this study was to evaluate the cellular immune response and the protection induced by recombinant MVAs encoding the model antigen ovalbumin (OVA). We used the MO5 melanoma tumor model (OVA-expressing tumor) as an approach for evaluating the vector-induced efficacy. Our results show that MVAΔ008-OVA (optimized vector) induced higher in vivo specific cytotoxicity and ex vivo T-cell IFN-γ responses against OVA than the conventional MVA vector. Importantly, the recombinant vectors were capable of controlling MO5 tumor growth. Indeed, the administration of MVAΔ008-OVA or MVA-OVA in prophylactic and therapeutic schemes provided total protection and longer survival of mice, respectively. Overall, our results demonstrate the improved immunogenicity and the protective capacity of MVAΔ008 against a heterologous model antigen. These findings suggest that MVAΔ008 constitutes an excellent candidate for vaccine development against pathogens or cancer therapy.

Single nucleotide polymorphisms in candidate genes associated with milk yield in Argentinean Holstein and Holstein x Jersey cows.

BACKGROUND: Research on loci influencing milk production traits of dairy cattle is one of the main topics of investigation in livestock. Many genomic regions and polymorphisms associated with dairy production have been reported worldwide. In this context, the purpose of this study was to identify candidate loci associated with milk yield in Argentinean dairy cattle. A database of candidate genes and single nucleotide polymorphisms (SNPs) for milk production and composition was developed. Thirty-nine SNPs belonging to 22 candidate genes were genotyped on 1643 animals (Holstein and Holstein x Jersey). The genotypes obtained were subjected to association studies considering the whole population and discriminating the population by Holstein breed percentage. Phenotypic data consisted of milk production values recorded during the first lactation of 1156 Holstein and 462 Holstein x Jersey cows from 18 dairy farms located in the central dairy area of Argentina. From these records, 305-day cumulative milk production values were predicted. RESULTS: Eight SNPs (rs43375517, rs29004488, rs132812135, rs137651874, rs109191047, rs135164815, rs43706485, and rs41255693), located on six Bos taurus autosomes (BTA4, BTA6, BTA19, BTA20, BTA22, and BTA26), showed suggestive associations with 305-day cumulative milk production (under Benjamini-Hochberg procedure with a false discovery rate of 0.1). Two of those SNPs (rs43375517 and rs135164815) were significantly associated with milk production (Bonferroni adjusted p-values < 0.05) when considering the Holstein population. CONCLUSIONS: The results obtained are consistent with previously reported associations in other Holstein populations. Furthermore, the SNPs found to influence bovine milk production in this study may be used as possible candidate SNPs for marker-assisted selection programs in Argentinean dairy cattle.

microRNAs and the mammary gland: A new understanding of gene expression.

MicroRNAs (miRNAs) have been identified in cells as well as in exosomes in biological fluids such as milk. In mammary gland, most of the miRNAs studied have functions related to immunity and show alterations in their pattern of expression during lactation. In mastitis, the inflammatory response caused by Streptococcus uberis alters the expression of miRNAs that may regulate the innate immune system. These small RNAs are stable at room temperature and are resistant to repeated freeze/thaw cycles, acidic conditions and degradation by RNAse, making them resistant to industrial procedures. These properties mean that miRNAs could have multiple applications in veterinary medicine and biotechnology. Indeed, lactoglobulin-free milk has been produced in transgenic cows expressing specific miRNAs. Although plant and animal miRNAs have undergone independent evolutionary adaptation recent studies have demonstrated a cross-kingdom passage in which rice miRNA was isolated from human serum. This finding raises questions about the possible effect that miRNAs present in foods consumed by humans could have on human gene regulation. Further studies are needed before applying miRNA biotechnology to the milk industry. New discoveries and a greater knowledge of gene expression will lead to a better understanding of the role of miRNAs in physiology, nutrition and evolution.