Modification of a previously patented method to unequivocally score A2-like and A1-like bovine ß-casein variants.

A growing interest in the production and commercialization of A2 cow's milk has been observed in many countries in the last few years due to the beneficial properties for human health attributed to A2 ß-casein variant. Methods of varying complexity and different equipment requirements have been proposed for the determination of the ß-casein genotype of individual cows. We proposed herein a modification of a previously patented method based on an amplification-created restriction site PCR followed by restriction fragment length polymorphism analysis. This method allows to identify and differentiate A2-like from A1-like ß-casein variants, after differential endonuclease cleavage flanking the nucleotide that determines the amino acid at position 67 of ß-casein. The advantages of this method are that it: • enables to unequivocally score A2-like as well as A1-like ß-casein variants, • can be performed at low cost in simply equipped molecular biology laboratories, and • can be scaled up to analyze hundreds of samples per day. For these reasons, and based on the results obtained from the analysis carried out in this work, it showed to be a reliable method for the screening of herds to selective breeding of homozygous cows and bulls for A2 or A2-like alleles.

A comprehensive analysis of the genetic diversity and environmental adaptability in worldwide Merino and Merino-derived sheep breeds.

BACKGROUND: To enhance and extend the knowledge about the global historical and phylogenetic relationships between Merino and Merino-derived breeds, 19 populations were genotyped with the OvineSNP50 BeadChip specifically for this study, while an additional 23 populations from the publicly available genotypes were retrieved. Three complementary statistical tests, Rsb (extended haplotype homozygosity between-populations), XP-EHH (cross-population extended haplotype homozygosity), and runs of homozygosity (ROH) islands were applied to identify genomic variants with potential impact on the adaptability of Merino genetic type in two contrasting climate zones. RESULTS: The results indicate that a large part of the Merino's genetic relatedness and admixture patterns are explained by their genetic background and/or geographic origin, followed by local admixture. Multi-dimensional scaling, Neighbor-Net, Admixture, and TREEMIX analyses consistently provided evidence of the role of Australian, Rambouillet and German strains in the extensive gene introgression into the other Merino and Merino-derived breeds. The close relationship between Iberian Merinos and other South-western European breeds is consistent with the Iberian origin of the Merino genetic type, with traces from previous contributions of other Mediterranean stocks. Using Rsb and XP-EHH approaches, signatures of selection were detected spanning four genomic regions located on Ovis aries chromosomes (OAR) 1, 6 and 16, whereas two genomic regions on OAR6, that partially overlapped with the previous ones, were highlighted by ROH islands. Overall, the three approaches identified 106 candidate genes putatively under selection. Among them, genes related to immune response were identified via the gene interaction network. In addition, several candidate genes were found, such as LEKR1, LCORL, GHR, RBPJ, BMPR1B, PPARGC1A, and PRKAA1, related to morphological, growth and reproductive traits, adaptive thermogenesis, and hypoxia responses. CONCLUSIONS: To the best of our knowledge, this is the first comprehensive dataset that includes most of the Merino and Merino-derived sheep breeds raised in different regions of the world. The results provide an in-depth picture of the genetic makeup of the current Merino and Merino-derived breeds, highlighting the possible selection pressures associated with the combined effect of anthropic and environmental factors. The study underlines the importance of Merino genetic types as invaluable resources of possible adaptive diversity in the context of the occurring climate changes.

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.

Single nucleotide polymorphisms from candidate genes associated with nematode resistance and resilience in Corriedale and Pampinta sheep in Argentina.

Selective breeding of genetically resistant animals is considered a promising strategy to face the problem of nematode resistance to anthelmintics and mitigate concerns about the presence of chemical residues in animal food products and the environment. Gastrointestinal nematode resistance is a complex, multifactorial trait related to host immunity. However, the mechanisms underlying host resistance and response to infection remain to be fully elucidated. In this context, the objective of this study was to provide insight into the chromosomal regions determining nematode resistance and resilience in Corriedale and resistance in Pampinta sheep breeds. A total of 170 single nucleotide polymorphisms (SNP) from 76 candidate genes for immune response were studied in 624 Corriedale and 304 Pampinta animals. Lambs underwent artificial or natural challenges with infective larvae mainly from Haemonchus contortus. Fecal egg counts, estimated breeding values for fecal egg counts, and rate of packed cell volume change and FAMACHA© score change over the challenge were used, when available, as indicators of host parasite resistance or resilience. Phenotype-genotype association studies were conducted and significance values obtained were adjusted for multiple testing errors. Eight SNPs, located on OARs 3, 6, 12, and 20, reached significance in Corriedale sheep under artificial challenge. Those SNP represent allelic variants from the MHC-Ovine Lymphocyte Antigen-DRA, two C-type lectin domain families, the Interleukin 2 receptor ß, the Toll-like receptor 10, the Mannan binding lectin serine peptidase 2, and the NLR family, CARD domain containing 4 genes. On Pampinta lambs under natural challenge, we found three significant SNPs, located in the TIMP metallopeptidase inhibitor 3, the FBJ murine osteosarcoma viral oncogene homolog, and the Interleukin 20 receptor alpha genes, on OARs 3, 7, and 8, respectively. The results obtained herein confirm genomic regions previously reported as associated with nematode resistance in other sheep breeds, reinforcing their role in host response to parasites. These findings contribute to gain knowledge on parasite resistance and resilience in Corriedale sheep and report for the first time SNPs associated with resistance to gastrointestinal parasite infections in Pampinta breed.

Generalized glycogenosis in Brahman-derived breeds: diagnosis and prevalence in Argentina.

Generalized glycogenosis is a lethal autosomal recessive disease caused by a deficient activity of the acidic 1,4-α-glucosidase enzyme and characterized by an accumulation of glycogen within lysosomes. Three mutations in the GAA gene causing bovine generalized glycogenosis have been identified in two cattle breeds, Brahman and Shorthorn. The objective of this study was to evaluate the prevalence of carriers of the E7 mutation in the GAA gene in Argentinean Brahman-derived herds. A total of 930 Braford, 94 Brangus, and 8 Brahman samples were analyzed. The genotyping was done by polymerase chain reaction and restriction fragment length polymorphism (PCR/RFLP). We found that 12.02% (95% CI 12.00-12.04) of the total number of samples received were heterozygous (i.e., carriers) for the E7 mutation, while 12.58% (95% CI 12.56-12.60) of the Braford, 6.38% (95% CI 6.26-6.51) of the Brangus, and 12.50% (95% CI 9.82-15.18) of the Brahman samples were carriers of this loss-of-function allele. Neither breed nor sex were significantly associated to the presence of the mutation. The prevalence informed in this study is similar to the average prevalence reported for Australian Brahmans. The finding of heterozygous animals suggests that breeders and insemination centers should continue screening their herds to minimize the dissemination of this deleterious allele.

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.