Identification of genomic regions associated with resistance to gastrointestinal parasites in an indigenous sheep by single- and multiple-locus methods.

We investigated the association between 157 SNPs located in 75 candidate genes involved in the immune system and proxy traits for resistance to gastrointestinal nematodes in sheep. A total of 211 lambs from eight flocks were sampled. Nematode eggs per gram were counted and classified as: (i) Strongyles, (ii) Nematodirus spp., (iii) Trichuris spp. and (iv) Marshallagia marshalli. Single- and multiple-locus models were used to test the marker-trait associations. Seven significant SNPs were identified on chromosomes OAR6, 15, 16, and 19. These findings provide insights for breeding nemarode-resistant traits in low-input production systems. General linear model, fixed and random model circulating probability unification, and Bayesian-information and linkage-disequilibrium iteratively nested keyway analyses identified a significant association between the eggs per gram of Strongyles nematodes and a specific variant of the PRLR gene.

Observational study on the associations between milk yield, composition, and coagulation properties with blood biomarkers of health in Holstein cows.

The considerable increase in the production capacity of individual cows owing to both selective breeding and innovations in the dairy sector has posed challenges to management practices in terms of maintaining the nutritional and metabolic health status of dairy cows. In this observational study, we investigated the associations between milk yield, composition, and technological traits and a set of 21 blood biomarkers related to energy metabolism, liver function or hepatic damage, oxidative stress, and inflammation or innate immunity in a population of 1,369 high-yielding Holstein-Friesian dairy cows. The milk traits investigated in this study included 4 production traits (milk yield, fat yield, protein yield, daily milk energy output), 5 traits related to milk composition (fat, protein, casein, and lactose percentages and urea), 11 milk technological traits (5 milk coagulation properties and 6 curd-firming traits). All milk traits (i.e., production, composition, and technological traits) were analyzed according to a linear mixed model that included the days in milk, the parity order, and the blood metabolites (tested one at a time) as fixed effects and the herd and date of sampling as random effects. Our findings revealed that milk yield and daily milk energy output were positively and linearly associated with total cholesterol, nonesterified fatty acids, urea, aspartate aminotransferase, γ-glutamyl transferase, total bilirubin, albumin, and ferric-reducing antioxidant power, whereas they were negatively associated with glucose, creatinine, alkaline phosphatase, total reactive oxygen metabolites, and proinflammatory proteins (ceruloplasmin, haptoglobin, and myeloperoxidase). Regarding composition traits, the protein percentage was negatively associated with nonesterified fatty acids and ß-hydroxybutyrate (BHB), while the fat percentage was positively associated with BHB, and negatively associated with paraoxonase. Moreover, we found that the lactose percentage increased with increasing cholesterol and albumin and decreased with increasing ceruloplasmin, haptoglobin, and myeloperoxidase. Milk urea increased with an increase in cholesterol, blood urea, nonesterified fatty acids, and BHB, and decreased with an increase in proinflammatory proteins. Finally, no association was found between the blood metabolites and milk coagulation properties and curd-firming traits. In conclusion, this study showed that variations in blood metabolites had strong associations with milk productivity traits, the lactose percentage, and milk urea, but no relationships with technological traits of milk. Specifically, increasing levels of proinflammatory and oxidative stress metabolites, such as ceruloplasmin, haptoglobin, myeloperoxidase, and total reactive oxygen metabolites, were shown to be associated with reductions in milk yield, daily milk energy output, lactose percentage, and milk urea. These results highlight the close connection between the metabolic and innate immunity status and production performance. This connection is not limited to specific clinical diseases or to the transition phase but manifests throughout the entire lactation. These outcomes emphasize the importance of identifying cows with subacute inflammatory and oxidative stress as a means of reducing metabolic impairments and avoiding milk fluctuations.

CpG DNA methylation changes during epididymal sperm maturation in bulls.

BACKGROUND: During epididymal transit spermatozoa acquire specific morphological features which enhance their ability to swim in a progressive manner and interact with the oocytes. At the same time, sperm cells undergo specific molecular rearrangements essential for the fertilizing sperm to drive a correct embryo development. To assess epigenetic sperm changes during epididymal maturation, the caput, corpus and cauda epididymis sperm tracts were isolated from eight bulls and characterized for different sperm quality parameters and for CpG DNA methylation using Reduced Representation Bisulfite Sequencing (RRBS) able to identify differentially methylated regions (DMRs) in higher CpG density regions. RESULTS: Caput sperm showed significant variation in motility and sperm kinetics variables, whereas spermatozoa collected from the corpus presented morphology variation and significant alterations in variables related to acrosome integrity. A total of 57,583 methylated regions were identified across the eight bulls, showing a significantly diverse distribution for sperm collected in the three epididymal regions. Differential methylation was observed between caput vs corpus (n = 11,434), corpus vs cauda (n = 12,372) and caput vs cauda (n = 2790). During epididymal transit a high proportion of the epigenome was remodeled, showing several regions in which methylation decreases from caput to corpus and increases from corpus to cauda. CONCLUSIONS: Specific CpG DNA methylation changes in sperm isolated from the caput, corpus, and cauda epididymis tracts are likely to refine the sperm epigenome during sperm maturation, potentially impacting sperm fertilization ability and spatial organization of the genome during early embryo development.

Comparison between indicine and taurine cattle DNA methylation reveals epigenetic variation associated to differences in morphological adaptive traits.

Indicine and taurine subspecies present distinct morphological traits as a consequence of environmental adaptation and artificial selection. Although the two subspecies have been characterized and compared at genome-wide level and at specific loci, their epigenetic diversity has not yet been explored. In this work, Reduced Representation Bisulphite Sequencing (RRBS) profiling of the taurine Angus (A) and indicine Nellore (N) cattle breeds was applied to identify methylation differences between the two subspecies. Genotyping by sequencing (GBS) of the same animals was performed to detect single nucleotide polymorphisms (SNPs) at cytosines in CpG dinucleotides and remove them from the differential methylation analysis. A total of 660,845 methylated cytosines were identified within the CpG context (CpGs) across the 10 animals sequenced (5 N and 5 A). A total of 25,765 of these were differentially methylated (DMCs). Most DMCs clustered in CpG stretches nearby genes involved in cellular and anatomical structure morphogenesis. Also, sequences flanking DMC were enriched in SNPs compared to all other CpGs, either methylated or unmethylated in the two subspecies. Our data suggest a contribution of epigenetics to the regulation and divergence of anatomical morphogenesis in the two subspecies relevant for cattle evolution and sub-species differentiation and adaptation.

Predicting milk protein fractions using infrared spectroscopy and a gradient boosting machine for breeding purposes in Holstein cattle.

In recent years, increasing attention has been focused on the genetic evaluation of protein fractions in cow milk with the aim of improving milk quality and technological characteristics. In this context, advances in high-throughput phenotyping by Fourier transform infrared (FTIR) spectroscopy offer the opportunity for large-scale, efficient measurement of novel traits that can be exploited in breeding programs as indicator traits. We took milk samples from 2,558 Holstein cows belonging to 38 herds in northern Italy, operating under different production systems. Fourier transform infrared spectra were collected on the same day as milk sampling and stored for subsequent analysis. Two sets of data (i.e., phenotypes and FTIR spectra) collected in 2 different years (2013 and 2019-2020) were compiled. The following traits were assessed using HPLC: true protein, major casein fractions [αS1-casein (CN), αS2-CN, ß-CN, κ-CN, and glycosylated-κ-CN], and major whey proteins (ß-lactoglobulin and α-lactalbumin), all of which were measured both in grams per liter (g/L) and proportion of total nitrogen (% N). The FTIR predictions were calculated using the gradient boosting machine technique and tested by 3 different cross-validation (CRV) methods. We used the following CRV scenarios: (1) random 10-fold, which randomly split the whole into 10-folds of equal size (9-folds for training and 1-fold for validation); (2) herd/date-out CRV, which assigned 80% of herd/date as the training set with independence of 20% of herd/date assigned as the validation set; (3) forward/backward CRV, which split the data set in training and validation set according with the year of milk sampling (FTIR and gold standard data assessed in 2013 or 2019-2020) using the "old" and "new" databases for training and validation, and vice-versa with independence among them; (4) the CRV for genetic parameters (CRV-gen), where animals without pedigree as assigned as a fixed training population and animals with pedigree information was split in 5-folds, in which 1-fold was assigned to the fixed training population, and 4-folds were assigned to the validation set (independent from the training set). The results (i.e., measures and predictions) of CRV-gen were used to infer the genetic parameters for gold standard laboratory measurements (i.e., proteins assessed with HPLC) and FTIR-based predictions considering the CRV-gen scenario from a bi-trait animal model using single-step genomic BLUP. We found that the prediction accuracies of the gradient boosting machine equations differed according to the way in which the proteins were expressed, achieving higher accuracy when expressed in g/L than when expressed as % N in all CRV scenarios. Concerning the reproducibility of the equations over the different years, the results showed no relevant differences in predictive ability between using "old" data as the training set and "new" data as the validation set and vice-versa. Comparing the additive genetic variance estimates for milk protein fractions between the FTIR predicted and HPLC measures, we found reductions of -19.7% for milk protein fractions expressed in g/L, and -21.19% expressed as % N. Although we found reductions in the heritability estimates, they were small, with values ranging from -1.9 to -7.25% for g/L, and -1.6 to -7.9% for % N. The posterior distributions of the additive genetic correlations (ra) between the FTIR predictions and the laboratory measurements were generally high (>0.8), even when the milk protein fractions were expressed as % N. Our results show the potential of using FTIR predictions in breeding programs as indicator traits for the selection of animals to enhance milk protein fraction contents. We expect acceptable responses to selection due to the high genetic correlations between HPLC measurements and FTIR predictions.

The ß-casein (CSN2) A2 allelic variant alters milk protein profile and slightly worsens coagulation properties in Holstein cows.

Milk proteins genetic variants have long attracted interest as they are associated with important issues relating to milk composition and technological properties. An important debate has recently opened at an international level on the role of ß-casein (ß-CN) A1 and A2 polymorphisms, toward human health. For this reason, a lot of efforts has been put into the promotion of A2 milk by companies producing and selling A1-free milk, leading the farmers and breeders to switch toward A2 milk production without paying attention on the potential effect of the processability of milk into cheese. The aim of the present work was to evaluate the effects of ß-CN, specifically the A1 and A2 allelic variants, on the detailed milk protein profile and cheese-making traits in individual milk samples of 1,133 Holstein Friesian cows. The protein fractions were measured with reversed-phase (RP)-HPLC (expressed in g/L and % N), and the cheese-making traits, namely milk coagulation properties, cheese yield, and curd nutrient recoveries assessed at the individual level, with a nano-scale cheese-making procedure. The ß-CN (CSN2), κ-CN (CSN3), and ß-lactoglobulin (LGB) genetic variants were first identified through RP-HPLC and then confirmed through genotyping. Estimates of the effects of protein genotypes were obtained using a mixed inheritance model that considered, besides the standard nuisance variables (i.e., days in milk, parity, and herd-date), the milk protein genes located on chromosome 6 (CSN2, CSN3) and on chromosome 11 (LGB), and the polygenic background of the animals. Milk protein genes (CSN2, CSN3, and LGB) explained an important part of the additive genetic variance in the traits evaluated. The ß-CN A1A1 was associated with a significantly lower production of whey proteins, particularly of ß-lactoglobulin (-8.2 and -6.8% for g/L and % N, respectively) and α-lactalbumin (-4.7 and -4.4% for g/L and % N, respectively), and a higher production of ß-CN (6.8 and 6.1% for g/L and % N, respectively) with respect to the A2A2 genotype. Regarding milk cheese-making ability, the A2A2 genotype showed the worst performance compared with the other genotypes, particularly with respect to the BA1, with a higher rennet coagulation time (7.1 and 28.6% compared with A1A1 and BA1, respectively) and a lower curd firmness at 30 min. Changes in milk protein composition through an increase in the frequency of the A2 allele in the production process could lead to a worsening of the coagulation and curd firming traits.

Genetic parameters of differential somatic cell count, milk composition, and cheese-making traits measured and predicted using spectral data in Holstein cows.

Mastitis is one of the most prevalent diseases in dairy cattle and is the cause of considerable economic losses. Alongside somatic cell count (SCC), differential somatic cell count (DSCC) has been recently introduced as a new indicator of intramammary infection. The DSCC is expressed as a count or a proportion (%) of polymorphonuclear neutrophils plus lymphocytes (PMN-LYM) in milk somatic cells. These numbers are complemented to total somatic cell count or to 100 by macrophages (MAC). The aim of this study was to investigate the genetic variation and heritability of DSCC, and its correlation with milk composition, udder health indicators, milk composition, and technological traits in Holstein cattle. Data used in the analysis consisted in single test-day records from 2,488 Holstein cows reared in 36 herds located in northern Italy. Fourier-transform infrared (FTIR) spectroscopy was used to predict missing information for some milk coagulation and cheese-making traits, to increase sample size and improve estimation of the genetic parameters. Bayesian animal models were implemented via Gibbs sampling. Marginal posterior means of the heritability estimates were 0.13 for somatic cell score (SCS); 0.11 for DSCC, MAC proportion, and MAC count; and 0.10 for PMN-LYM count. Posterior means of additive genetic correlations between SCS and milk composition and udder health were low to moderate and unfavorable. All the relevant genetic correlations between the SCC traits considered and the milk traits (composition, coagulation, cheese yield and nutrients recovery) were unfavorable. The SCS showed genetic correlations of -0.30 with the milk protein proportion, -0.56 with the lactose proportion and -0.52 with the casein index. In the case of milk technological traits, SCS showed genetic correlations of 0.38 with curd firming rate (k20), 0.45 with rennet coagulation time estimated using the curd firming over time equation (RCTeq), -0.39 with asymptotic potential curd firmness, -0.26 with maximum curd firmness (CFmax), and of -0.31 with protein recovery in the curd. Differential somatic cell count expressed as proportion was correlated with SCS (0.60) but had only 2 moderate genetic correlations with milk traits: with lactose (-0.32) and CFmax (-0.33). The SCS was highly correlated with the log PMN-LYM count (0.79) and with the log MAC count (0.69). The 2 latter traits were correlated with several milk traits: fat (-0.38 and -0.43 with PMN-LYM and MAC counts, respectively), lactose percentage (-0.40 and -0.46), RCTeq (0.53 and 0.41), tmax (0.38 and 0.48). Log MAC count was correlated with k20 (+0.34), and log PMN-LYM count was correlated with CFmax (-0.26) and weight of water curd as percentage of weight of milk processed (-0.26). The results obtained offer new insights into the relationships between the indicators of udder health and the milk technological traits in Holstein cows.

Associations between differential somatic cell count and milk yield, quality, and technological characteristics in Holstein cows.

The aim of this study was to investigate the associations between differential somatic cell count (DSCC) and milk quality and udder health traits, and for the first time, between DSCC and milk coagulation properties and cheesemaking traits in a population of 1,264 Holstein cows reared in northern Italy. Differential somatic cell count represents the combined proportions of polymorphonuclear neutrophils plus lymphocytes (PMN-LYM) in the total somatic cell count (SCC), with macrophages (MAC) making up the remaining proportion. The milk traits investigated in this study were milk yield (MY), 8 traits related to milk composition and quality (fat, protein, casein, casein index, lactose, urea, pH, and milk conductivity), 9 milk coagulation traits [3 milk coagulation properties (MCP) and 6 curd firming (CF) traits], 7 cheesemaking traits, 3 cheese yield (CY) traits, and 4 milk nutrient recovery in the curd (REC) traits. A linear mixed model was fitted to explore the associations between SCS combined with DSCC and the aforementioned milk traits. An additional model was run, which included DSCC expressed as the PMN-LYM and MAC counts, obtained by multiplying the percentage of PMN-LYM and MAC by SCC in the milk for each cow in the data set. The unfavorable association between SCS and milk quality and technological traits was confirmed. Increased DSCC was instead associated with a linear increase in MY, casein index, and lactose proportion and a linear decrease in milk fat and milk conductivity. Accordingly, DSCC was favorably associated with all MCP and CF traits (with the exception of the time needed to achieve maximum, CF), particularly with rennet coagulation time, and it always displayed linear relationships. Differential somatic cell count was also positively associated with the recovery of milk nutrients in the curd (protein, fat, and energy), which increased linearly with increasing DSCC. The PMN-LYM count was rarely associated with milk traits, even though the pattern observed confirmed the results obtained when both SCS and DSCC were included in the model. The MAC count, however, showed the opposite pattern: MY, casein index, and lactose percentage decreased and milk conductivity increased with an increasing MAC count. No significant association was found between PMN-LYM count and MCP, CF, CY, and REC traits, whereas MAC count was unfavorably associated with MCP, CF traits, some CY traits, and all REC traits. Our results showed that the combined information derived from SCS and DSCC might be useful to monitor milk quality and cheesemaking-related traits.

Genomic clues of the evolutionary history of Bos indicus cattle.

Together with their sister subspecies Bos taurus, zebu cattle (Bos indicus) have contributed to important socioeconomic changes that have shaped modern civilizations. Zebu cattle were domesticated in the Indus Valley 8000 years before present (YBP). From the domestication site, they expanded to Africa, East Asia, southwestern Asia and Europe between 4000 and 1300 YBP, intercrossing with B. taurus to form clinal variations of zebu ancestry across the landmass of Afro-Eurasia. In the past 150 years, zebu cattle reached the Americas and Oceania, where they have contributed to the prosperity of emerging economies. The zebu genome is characterized by two mitochondrial haplogroups (I1 and I2), one Y chromosome haplogroup (Y3) and three major autosomal ancestral groups (Indian-Pakistani, African and Chinese). Phenotypically, zebu animals are recognized by their hump, large ears and excess skin. They are rustic, resilient to parasites and capable of bearing the hot and humid climates of the tropics. Many resources are available to study the zebu genome, including commercial arrays of SNP, reference assemblies and publicly available genotypes and whole-genome sequences. Nevertheless, many of these resources were initially developed to support research and subsidize industrial applications in B. taurus, and therefore they can produce bias in data analysis. The combination of genomics with precision agriculture holds great promise for the identification of genetic variants affecting economically important traits such as tick resistance and heat tolerance, which were naturally selected for millennia and played a major role in the evolution of B. indicus cattle.

Genome-wide association study of milk fatty acid composition in Italian Simmental and Italian Holstein cows using single nucleotide polymorphism arrays.

Bovine milk is important for human nutrition, but its fat content is often criticized as a risk factor in cardiovascular disease. Selective breeding programs could be used to alter the fatty acid (FA) composition of bovine milk to improve the healthiness of dairy products for human consumption. Here, we performed a genome-wide association study (GWAS) on bovine milk to identify genomic regions or specific genes associated with FA profile and to investigate genetic differences between the Italian Simmental (IS) and Italian Holstein (IH) breeds. To achieve this, we first characterized milk samples from 416 IS cows and 436 IH cows for their fat profile by gas chromatography. Subjects were genotyped with single nucleotide polymorphism array and a single-marker regression model for GWAS was performed. Our findings confirm previously reported quantitative trait loci strongly associated with bovine milk fat composition. More specifically, our GWAS results revealed significant signals on chromosomes Bos taurus autosome 19 and 26 for milk FA. Further analysis using a gene-centric approach and pathway meta-analysis identified not only some well-known genes underlying quantitative trait loci for milk FA components, such as FASN, SCD, and DGAT1, but also other significant candidate genes, including some with functional roles in pathways related to "Lipid metabolism." Highlighted genes related to FA profile include ECI2, PCYT2, DCXR, G6PC3, PYCR1, and ALG12 in IS, and CYP17A1, ACO2, PI4K2A, GOT1, GPT, NT5C2, PDE6G, POLR3H, and COX15 in IH. Overall, the breed-specific association outcomes reflect differences in the genetic backgrounds of the IS and IH breeds and their selective breeding histories.

Derivation and genome-wide association study of a principal component-based measure of heat tolerance in dairy cattle.

Heat stress represents a key factor that negatively affects the productive and reproductive performance of farm animals. In the present work, a new measure of tolerance to heat stress for dairy cattle was developed using principal component analysis. Data were from 590,174 test-day records for milk yield, fat and protein percentages, and somatic cell score of 39,261 Italian Holstein cows. Test-day records adjusted for main systematic factors were grouped into 11 temperature-humidity index (THI) classes. Daughter trait deviations (DTD) were calculated for 1,540 bulls as means of the adjusted test-day records for each THI class. Principal component analysis was performed on the DTD for each bull. The first 2 principal components (PC) explained 42 to 51% of the total variance of the system across the 4 traits. The first PC, a measure of the level at which the curve is located, was interpreted as a measure of the level at which the DTD curve was located. The second PC, which shows the slope of increasing or decreases DTD curves, synthesized the behavior of the DTD pattern. Heritability of the 2 component scores was moderate to high for level across all traits (range = 0.23-0.82) and low to moderate for slope (range = 0.16-0.28). For each trait, phenotypic and genetic correlations between level and slope were equal to zero. A genome-wide association analysis was carried out on a subsample of 423 bulls genotyped with the Illumina 50K bovine bead chip (Illumina, San Diego, CA). Two single nucleotide polymorphisms were significantly associated with slope for milk yield, 4 with level for fat percentage, and 2 with level and slope of protein percentage, respectively. The gene discovery was carried out considering windows of 0.5 Mb surrounding the significant markers and highlighted some interesting candidate genes. Some of them have been already associated with the mechanism of heat tolerance as the heat shock transcription factor (HSF1) and the malonyl-CoA-acyl carrier protein transacylase (MCAT). The 2 PC were able to describe the overall level and the slope of response of milk production traits across increasing levels of THI index. Moreover, they exhibited genetic variability and were genetically uncorrelated. These features suggest their use as measures of thermotolerance in dairy cattle breeding schemes.

Potential neoplastic evolution of Vero cells: in vivo and in vitro characterization.

Vero cell lines are extensively employed in viral vaccine manufacturing. Similarly to all established cells, mutations can occur during Vero cells in vitro amplification which can result in adverse features compromising their biological safety. To evaluate the potential neoplastic evolution of these cells, in vitro transformation test, gene expression analysis and karyotyping were compared among low- (127 and 139 passages) and high-passage (passage 194) cell lines, as well as transformed colonies (TCs). In vivo tumorigenicity was also tested to confirm preliminary in vitro data obtained for low passage lines and TCs. Moreover, Vero cells cultivated in foetal bovine serum-free medium and derived from TCs were analysed to investigate the influence of cultivation methods on tumorigenic evolution. Low-passage Vero developed TCs in soft agar, without showing any tumorigenic evolution when inoculated in the animal model. Karyotyping showed a hypo-diploid modal chromosome number and rearrangements with no difference among Vero cell line passages and TCs. These abnormalities were reported also in serum-free cultivated Vero. Gene expression revealed that high-passage Vero cells had several under-expressed and a few over-expressed genes compared to low-passage ones. Gene ontology revealed no significant enrichment of pathways related to oncogenic risk. These findings suggest that in vitro high passage, and not culture conditions, induces Vero transformation correlated to karyotype and gene expression alterations. These data, together with previous investigations reporting tumour induction in high-passage Vero cells, suggest the use of low-passage Vero cells or cell lines other than Vero to increase the safety of vaccine manufacturing.

Multilocus genotypic data reveal high genetic diversity and low population genetic structure of Iranian indigenous sheep.

Iranian livestock diversity is still largely unexplored, in spite of the interest in the populations historically reared in this country located near the Fertile Crescent, a major livestock domestication centre. In this investigation, the genetic diversity and differentiation of 10 Iranian indigenous fat-tailed sheep breeds were investigated using 18 microsatellite markers. Iranian breeds were found to host a high level of diversity. This conclusion is substantiated by the large number of alleles observed across loci (average 13.83, range 7-22) and by the high within-breed expected heterozygosity (average 0.75, range 0.72-0.76). Iranian sheep have a low level of genetic differentiation, as indicated by the analysis of molecular variance, which allocated a very small proportion (1.67%) of total variation to the between-population component, and by the small fixation index (FST  = 0.02). Both Bayesian clustering and principal coordinates analysis revealed the absence of a detectable genetic structure. Also, no isolation by distance was observed through comparison of genetic and geographical distances. In spite of high within-breed variation, signatures of inbreeding were detected by the FIS indices, which were positive in all and statistically significant in three breeds. Possible factors explaining the patterns observed, such as considerable gene flow and inbreeding probably due to anthropogenic activities in the light of population management and conservation programmes, are discussed.

A method for single nucleotide polymorphism selection for parentage assessment in goats.

Accurate pedigrees are essential to optimize genetic improvement and conservation of animal genetic resources. In goats, the use of mating groups and kidding management procedures hamper the identification of parentage. Small panels of single nucleotide polymorphisms (SNP) have been proposed in other species to substitute microsatellites for parentage assessment. Using data from the current GoatSNP50 chip, we developed a new 3-step procedure to identify a low-density SNP panel for highly accurate parentage assessment. Methodologies for SNP selection used in other species are less suitable in the goat because of uncertainties in the genome assembly. The procedure developed in this study is based on parent-offspring identification and on estimation of Mendelian errors, followed by canonical discriminant analysis identification and stepwise regression reduction. Starting from a reference sample of 109 Alpine goats with known pedigree relationships, we first identified a panel of 200 SNP that was further reduced to 2 final panels of 130 and 114 SNP with random coincidental match inclusion of 1.51×10(-57) and 2.94×10(-34), respectively. In our reference data set, all panels correctly identified all parent-offspring combinations, revealing a 40% pedigree error rate in the information provided by breeders. All reference trios were confirmed by official tests based on microsatellites. Panels were also tested on Saanen and Teramana breeds. Although the testing on a larger set of breeds in the reference population is still needed to validate these results, our findings suggest that our procedure could identify SNP panels for accurate parentage assessment in goats or in other species with unreliable marker positioning.

Inbreeding and purging at the genomic Level: the Chillingham cattle reveal extensive, non-random SNP heterozygosity.

Local breeds of livestock are of conservation significance as components of global biodiversity and as reservoirs of genetic variation relevant to the future sustainability of agriculture. One such rare historic breed, the Chillingham cattle of northern England, has a 350-year history of isolation and inbreeding yet shows no diminution of viability or fertility. The Chillingham cattle have not been subjected to selective breeding. It has been suggested previously that the herd has minimal genetic variation. In this study, high-density SNP genotyping with the 777K SNP chip showed that 9.1% of loci on the chip are polymorphic in the herd, compared with 62-90% seen in commercial cattle breeds. Instead of being homogeneously distributed along the genome, these loci are clustered at specific chromosomal locations. A high proportion of the Chillingham individuals examined were heterozygous at many of these polymorphic loci, suggesting that some loci are under balancing selection. Some of these frequently heterozygous loci have been implicated as sites of recessive lethal mutations in cattle. Linkage disequilibrium equal or close to 100% was found to span up to 1350 kb, and LD was above r(2) = 0.25 up to more than 5000 kb. This strong LD is consistent with the lack of polymorphic loci in the herd. The heterozygous regions in the Chillingham cattle may be the locations of genes relevant to fitness or survival, which may help elucidate the biology of local adaptation in traditional breeds and facilitate selection for such traits in commercial cattle.

Genome-wide association analysis in Italian Simmental cows for lactation curve traits using a low-density (7K) SNP panel.

High-throughput cow genotyping has opened new perspectives for genome-wide association studies (GWAS). Directly recorded phenotypes and several records per animal could be used. In this study, a GWAS on lactation curve traits of 337 Italian Simmental cows genotyped with the Illumina (San Diego, CA) low-density BeadChip (7K) was carried out. Scores of the first 2 principal components extracted from test-day records (7 for each lactation) for milk yield, fat and protein percentages, and somatic cell score were used as phenotypes. The first component described the average level of the lactation curve, whereas the second summarized its shape. Data were analyzed with a mixed linear model that included fixed effects of herd, calving month, calving year, parity, SNP genotype, and random effects of animal and permanent environment. All statistically significant markers (Bonferroni corrected) were associated with the average level component (2 for milk yield, 9 for fat percentage, 6 for protein percentages, and 1 for somatic cell score). No markers were found to be associated with the lactation curve shape. Gene discovery was performed using windows of variable size, according to the linkage disequilibrium level of the specific genomic region. Several suggestive candidate genes were identified, some of which already reported to be associated with dairy traits, such as DGAT1. Others were involved in lipid metabolism, in protein synthesis, in the immune response, in cellular processes, and in early development. The large number of genes flagged in the present study suggests interesting perspectives for the use of low-density genotyped females for GWAS, also for novel phenotypes that are not currently considered as breeding goals.

MUGBAS: a species free gene-based programme suite for post-GWAS analysis.

UNLABELLED: Genome Wide Association Studies between molecular markers and phenotypes are now routinely run in model and non-model species. However, tools to estimate the probability of association of functional units (e.g. genes) containing multiple markers are not developed for species other than humans. Here we introduce MUGBAS (MUlti species Gene-Based Association Suite), software that estimates the P-value of a gene using information on annotation, single marker GWA results and genotype. The software is species and annotation independent, fast, highly parallelized and ready for high-density marker studies. AVAILABILITY AND IMPLEMENTATION: https://bitbucket.org/capemaster/mugbas

Multiple-breed genomic evaluation by principal component analysis in small size populations.

In this study, the effects of breed composition and predictor dimensionality on the accuracy of direct genomic values (DGV) in a multiple breed (MB) cattle population were investigated. A total of 3559 bulls of three breeds were genotyped at 54 001 single nucleotide polymorphisms: 2093 Holstein (H), 749 Brown Swiss (B) and 717 Simmental (S). DGV were calculated using a principal component (PC) approach for either single (SB) or MB scenarios. Moreover, DGV were computed using all SNP genotypes simultaneously with SNPBLUP model as comparison. A total of seven data sets were used: three with a SB each, three with different pairs of breeds (HB, HS and BS), and one with all the three breeds together (HBS), respectively. Editing was performed separately for each scenario. Reference populations differed in breed composition, whereas the validation bulls were the same for all scenarios. The number of SNPs retained after data editing ranged from 36 521 to 41 360. PCs were extracted from actual genotypes. The total number of retained PCs ranged from 4029 to 7284 in Brown Swiss and HBS respectively, reducing the number of predictors by about 85% (from 82% to 89%). In all, three traits were considered: milk, fat and protein yield. Correlations between deregressed proofs and DGV were used to assess prediction accuracy in validation animals. In the SB scenarios, average DGV accuracy did not substantially change when either SNPBLUP or PC were used. Improvement of DGV accuracy were observed for some traits in Brown Swiss, only when MB reference populations and PC approach were used instead of SB-SNPBLUP (+10% HBS, +16%HB for milk yield and +3% HBS and +7% HB for protein yield, respectively). With the exclusion of the abovementioned cases, similar accuracies were observed using MB reference population, under the PC or SNPBLUP models. Random variation owing to sampling effect or size and composition of the reference population may explain the difficulty in finding a defined pattern in the results.

Imputation accuracy is robust to cattle reference genome updates.

Genotype imputation is routinely applied in a large number of cattle breeds. Imputation has become a need due to the large number of SNP arrays with variable density (currently, from 2900 to 777,962 SNPs). Although many authors have studied the effect of different statistical methods on imputation accuracy, the impact of a (likely) change in the reference genome assembly on imputation from lower to higher density has not been determined so far. In this work, 1021 Italian Simmental SNP genotypes were remapped on the three most recent reference genome assemblies. Four imputation methods were used to assess the impact of an update in the reference genome. As expected, the four methods behaved differently, with large differences in terms of accuracy. Updating SNP coordinates on the three tested cattle reference genome assemblies determined only a slight variation on imputation results within method.

A candidate gene association study for nine economically important traits in Italian Holstein cattle.

We genotyped 58 single nucleotide polymorphisms (SNPs) in 25 candidate genes in about 800 Italian Holstein sires. Fifty-six (minor allele frequency >0.02) were used to evaluate their association with single traits: milk yield (MY), milk fat yield (FY), milk protein yield (PY), milk fat percentage (FP), milk protein percentage (PP), milk somatic cell count (MSCC); and complex indexes: longevity, fertility and productivity-functionality type (PFT), using deregressed proofs, after adjustment for familial relatedness. Thirty-two SNPs were significantly associated (proportion of false positives <0.05) with different traits: 16 with MSCC, 15 with PY, 14 with MY, 12 with PFT, eight with longevity, eight with FY, eight with PP, five with FP and two with fertility. In particular, a SNP in the promoter region of the PRLR gene was associated with eight of nine traits. DGAT1 polymorphisms were highly associated with FP and FY. Casein gene markers were associated with several traits, confirming the role of the casein gene cluster in affecting milk yield, milk quality and health traits. Other SNPs in genes located on chromosome 6 were associated with PY, PP, PFT, MY (PPARGC1A) and MSCC (KIT). This latter association may suggest a biological link between the degree of piebaldism in Holstein and immunological functions affecting somatic cell count and mastitis resistance. Other significant SNPs were in the ACACA, CRH, CXCR1, FASN, GH1, LEP, LGB (also known as PAEP), MFGE8, SRC, TG, THRSP and TPH1 genes. These results provide information that can complement QTL mapping and genome-wide association studies in Holstein.