Short communication: Genetic aspects of milk urea nitrogen and new indicators of nitrogen efficiency in dairy cows.

Milk urea nitrogen (MUN), a trait routinely measured in the national milk recording system, is a useful indicator of nitrogen utilization efficiency of dairy cows, and selection for MUN and MUN-derived traits could be a valid strategy to produce better animals with regard to efficiency of nitrogen utilization. Therefore, the aim of the present study was to explore the genetic aspects of MUN and new potential indicators of nitrogen efficiency, namely ratios of protein to MUN, casein to MUN, and whey protein to MUN, in the Italian Brown Swiss population. A total of 153,175 test-day records of 10,827 cows in 500 herds were used for genetic analysis. Variance components and heritability of the investigated traits were estimated using single-trait repeatability animal models, whereas genetic and phenotypic correlations between the traits were estimated through bivariate repeatability animal models, including fixed effects of herd-test-date, stage of lactation, parity, calving year, and calving season, and the random effects of additive genetic animal, cow permanent environment, and the residual. Heritability estimates for MUN (0.20 ± 0.01) and the 3 new indicators of nitrogen utilization efficiency (0.15 ± 0.01 for protein-to-MUN and casein-to-MUN ratios, and 0.12 ± 0.01 for ratio of whey protein to MUN) suggested that additive genetic variation exists for these traits, and thus there is potential to select for greater organic nitrogen and lower inorganic nitrogen in milk. Genetic association between MUN and the 3 ratios was high (-0.87 ± 0.01) but not unity, suggesting that ratios could provide some further information beyond that provided by MUN with regard to efficiency of nitrogen utilization. Genetic trend of the investigated traits by year of birth of Brown Swiss sires showed how the selection applied in the last 30 yr has led to an increase of both quantity and quality of milk, and a decrease of somatic cell score and MUN. The inclusion of MUN in breeding programs could speed up the process of increasing organic nitrogen such as protein, which is useful for cheese-making, and reducing inorganic nitrogen (MUN) in milk

Genetic parameters for casein and urea content in the Italian Brown Swiss dairy cattle

A total of 137,753 test day records of 20,745 Italian Brown Swiss dairy cows from 26 provinces of Italy were used to estimate heritability for casein and urea content in milk and their genetic correlations with other production traits and milk somatic cell score. Milk component values were obtained by Fourier Transformed Infrared (IR) Spectroscopy from milk samples collected during national routine recording and were analysed using test day repeatability animal models. Fixed effects included 1,001 levels of herd-test date, 15 classes of days in milk, and 13 classes of age at calving within parity. The variation among cows was large for most of the traits. The heritability value for casein content was 0.31, as for protein content, and genetic and phenotypic correlations between these two traits were large (0.99 and 0.97 respectively). Milk urea content had a heritability of 0.17 and a positive genetic relationship with fat (0.12), null with protein (0.03) and casein (0.002) content and a negative genetic correlation with milk yield (-0.17) suggesting that the genetic improvement for milk urea content would be possible, but genetic gain would be affected by other traits included as selection criteria in the economic index and by their relative economic emphasis

Proteome changes in the skin of the grape cultivar Barbera among different stages of ripening

<p>Abstract</p> <p>Background</p> <p>Grape ripening represents the third phase of the double sigmoidal curve of berry development and is characterized by deep changes in the organoleptic characteristics. In this process, the skin plays a central role in the synthesis of many compounds of interest (<it>e.g</it>. anthocyanins and aroma volatiles) and represents a fundamental protective barrier against damage by physical injuries and pathogen attacks. In order to improve the knowledge on the role of this tissue during ripening, changes in the protein expression in the skin of the red cultivar Barbera at five different stages from <it>véraison </it>to full maturation were studied by performing a comparative 2-DE analysis.</p> <p>Results</p> <p>The proteomic analysis revealed that 80 spots were differentially expressed throughout berry ripening. Applying a two-way hierarchical clustering analysis to these variations, a clear difference between the first two samplings (up to 14 days after <it>véraison</it>) and the following three (from 28 to 49 days after <it>véraison</it>) emerged, thus suggesting that the most relevant changes in protein expression occurred in the first weeks of ripening. By means of LC-ESI-MS/MS analysis, 69 proteins were characterized. Many of these variations were related to proteins involved in responses to stress (38%), glycolysis and gluconeogenesis (13%), C-compounds and carbohydrate metabolism (13%) and amino acid metabolism (10%).</p> <p>Conclusion</p> <p>These results give new insights to the skin proteome evolution during ripening, thus underlining some interesting traits of this tissue. In this view, we observed the ripening-related induction of many enzymes involved in primary metabolism, including those of the last five steps of the glycolytic pathway, which had been described as down-regulated in previous studies performed on whole fruit. Moreover, these data emphasize the relevance of this tissue as a physical barrier exerting an important part in berry protection. In fact, the level of many proteins involved in (a)biotic stress responses remarkably changed through the five stages taken into consideration, thus suggesting that their expression may be developmentally regulated.</p

Genome-wide association studies using copy number variants in Brown Swiss Dairy cattle.

Detecting Copy Number Variation (CNV) in cattle provides the opportunity to study their association with quantitative traits (Winchester et al., 2009; Zhang et al., 2009; Hou et al., 2011; Clop et al., 2012; de Almeida et al., 2016;). The aim of this study was to map CNVs in 1,410 Brown Swiss males and females using Illumina BovineHD Genotyping BeadChip data and to perform a genome-wide association analysis for production functional and health traits. After quality control, CNVs were called with the GoldenHelix SVS 8.3.1 and PennCNV software and were summarized to CNV regions (CNVRs) at a population level, using BEDTools. Additionally, common CNVRs between the two software were set as consensus. CNV-association studies were executed with the CNVRuler software using a linear regression model. Genes within significant associated CNVRs for each trait were annotated with a GO analysis using the DAVID Bioinformatics Resources 6.7.The quality control filtered out 294 samples. The GoldenHelix SVS 8.3.1 software identified 25,030 CNVs summarized to 398 CNVRs while PennCNV identified 62,341 CNVs summarized to 5,578 CNVRs. A total of 127 CNVRs were identified to be significantly associated with one or more of the evaluated traits. The result of this study is a comprehensive genomic analysis of the Brown Swiss breed, which enriches the bovine CNV map in its genome. Finally, the results of the association studies deliver new information for quantitative traits considered in selection programs of the Brown Swiss breed

Genetic parameters of fatty acids in Italian Brown Swiss and Holstein cows

The aim of this study was to estimate the genetic parameters and to predict experimental breeding values (EBVs) for saturated (SFA), unsaturated (UFA), monounsaturated (MUFA) and polyunsaturated (PUFA) fatty acids, the ratio of fatty acids, and the productive traits in Italian Brown Swiss (BSW) and Holstein Friesian (HOL) cattle. Test-day yields from 235,658 HOL and 21,723 BSW cows were extracted from the Italian HOL and BSW Associations databases from November 2009 to October 2012 out of 3310 herds. The milk samples collected within the routine milk recording scheme were processed with the MilkoscanTM FT 6500 Plus (Foss, Hillerød, Denmark) for the identification of SFA, UFA, MUFA and PUFA composition in milk. Genetic parameters for fatty acids and productive traits were estimated on 1,765,552 records in HOL and 255,592 records in BSW. Heritability values estimated for SFA, UFA, MUFA and PUFA ranged from 0.06 to 0.18 for the BSW breed and from 0.10 to 0.29 for HOL. The genetic trends for the fatty acids were consistent between traits and breeds. Pearson's and Spearman's correlations among EBVs for SFA, UFA, MUFA and PUFA and official EBVs for fat percentage were in the range 0.32 to 0.54 for BSW and 0.44 to 0.64 for HOL. The prediction of specific EBVs for milk fatty acids and for the ratio among them may be useful to identify the best bulls to be selected with the aim to improve milk quality in terms of fat content and fatty acid ratios, achieving healthier dairy productions for consumers

Assessment of 29 candidate genes for milk traits in Italian dairy cattle

Several investigations have recently searched for significant association between gene polymorphisms and milk traits in livestock and model species. In several cases, it remains rather difficult to assess if the observed effects are caused by the mutation tested, by a nearby mutation in the same gene or by a mutation in a different gene or DNA region in linkage disequilibrium with the former. As a consequence, only in a few cases (e.g., κ-casein, SCD, DGAT1) the causative mutation seems to have been identified and, even when evidence is rather clear, genetic heterogeneity and genetic background may influence the size of allele substitution effects. Therefore, the significance of gene-trait associations and the estimate of their effect have to be verified in any new population in which this information is planned to be used, to estimate its actual utility in gene assisted breeding. In the SelMol project, we selected 29 candidate genes on the basis of known relationships between physiological or biochemical processes and evidence of significant association with milk traits in cattle, in related (e.g., sheep and goats) and model (e.g., mouse) species. A total of 106 SNPs were selected, using either information available in literature, or in silico, searching the NCBI dbSNP database. SNPs found significantly associated in other investigations were preferentially targeted. Otherwise non-synonymous SNPs and those in putative control regions (e.g., in promoter binding sites) were selected from dbSNP. If within a gene no SNP having one of these characteristics was available in dbSNP, synonymous SNPs, occurring in introns and untranslated non-control regions were chosen. DNA was extracted from semen of elite sires. SNPs polymorphism was confirmed by screening a panel of 32 individuals each of Pezzata Rossa (PR), Bruna Italiana (BI), and Frisona Italiana (FI) dairy cattle breeds. A total of 73 SNPs were confirmed as polymorphic in at least one breed: 63 in PR, 61 in BI, and 68 in FI. Polymorphic SNPs were genotyped on 400 individuals of PR and 600 of BI. Statistical tests were applied to detect selection sweeps, significant association to EBVs and phenotypic traits related to milk production and quality (milk yield, protein and fat yield and percentage), together with a number of functional traits (fertility, SCS as indicator of mastitis resistance, conformational traits, and milkability)

Deciphering the genetic basis of male fertility in Italian Brown Swiss dairy cattle

Improving reproductive performance remains a major goal in dairy cattle worldwide. Service sire has been recognized as an important factor affecting herd fertility. The main objective of this study was to reveal the genetic basis of male fertility in Italian Brown Swiss dairy cattle. Dataset included 1102 Italian Brown Swiss bulls with sire conception rate records genotyped with 454k single nucleotide polymorphisms. The analysis included whole-genome scans and gene-set analyses to identify genomic regions, individual genes and genetic mechanisms affecting Brown Swiss bull fertility. One genomic region on BTA1 showed significant additive effects. This region harbors gene RABL3 which is implicated cell proliferation and motility. Two genomic regions, located on BTA6 and BTA26, showed marked non-additive effects. These regions harbor genes, such as WDR19 and ADGRA1, that are directly involved in male fertility, including sperm motility, acrosome reaction, and embryonic development. The gene-set analysis revealed functional terms related to cell adhesion, cellular signaling, cellular transport, immune system, and embryonic development. Remarkably, a gene-set analysis also including Holstein and Jersey data, revealed significant processes that are common to the three dairy breeds, including cell migration, cell-cell interaction, GTPase activity, and the immune function. Overall, this comprehensive study contributes to a better understanding of the genetic basis of male fertility in cattle. In addition, our findings may guide the development of novel genomic strategies for improving service sire fertility in Brown Swiss cattle

A METHODOLOGY FOR THE PARENTAGE DIAGNOSIS OF THE ITALIAN BROWN BREED

Parentage is a measure of the genetic similarities between two related individuals: it is defined as the possession of genes identical by descent. Since the amount of common genes determines phenotypical similarities, e.g. morphological and production-related features, an accurate parentage test is crucial in the selection process. The advent of genomic analyses has paved the use of SNPs information to accurately investigate parentage. However, the current transition from traditional to genomic selection needs methods able to combine different sources of genetic information. In particular, since genomic information is not available for all animals, there is the practical and economic need to cross-examine parentage of genotyped offspring and parents with microsatellites information only. Two steps are necessary to overcome this issue: firstly, to assign microsatellite information from SNPs data of a genotyped animal and secondly, to use microsatellites for the lineage verification. The objective of this study was to design a method capable to analyse microsatellites data that validates pedigree information. The data was provided by National Brown Cattle Breeders’ Association (ANARB) and was made up of 49,828 cattle with microsatellite information from SNP data, 37,262 cattle with official microsatellite data and a pedigree database with 2,399,305 cattle. The first stage was to create an algorithm that cross-examined 12 microsatellites per animal along with the microsatellites from the presumed parents, to check the correctness of the pedigree. The procedure was developed by using the software R, which has permitted to deal with large databases. The conditions used for the parentage diagnosis followed the ISAG protocol and the ICAR guidelines. The accuracy of the method was checked by comparing the results obtained by microsatellite analysis with the official parentage data for the 37,262 animals where official analyses were available. The comparison of the results between the proposed method and the available official verifications led to an accuracy of 96.2%. Consequently, the procedure has allowed more than 12,000 new parentage verifications and the correction of 600 pedigree information. This procedure is useful for direct verification, without further external laboratory testing, of parentage compatibility when different sources of information are already available: SNPs and microsatellites

Genetic parameters for functional longevity, type traits, SCS, milk flow and production in the Italian Brown Swiss

The aim of this study was to estimate genetic parameters for a set of new traits and to update values for production and morphological traits to be used in the selection index of Italian Brown Swiss dairy cattle. Longevity, milking speed and somatic cell scores (SCS) were considered for inclusion in the selection index, and (co)variances with all traits of the selection index were estimated. SCS was considered on a lactation basis while milk flow as the amount of milk (kg) released per time unit (minute) measured with a flowmeter. Cow functional longevity was the total herd life corrected for the production level. A total of 127,416 first lactation records of cows calving from 1985 to 2003 were considered. In order to maximize the number of records available for each combination of traits, 9 data sets were created. Estimates were obtained from multivariate linear sire models with equal design matrix in subsequent separated analysis. REML algorithms and canonical transformation were used to calculate (co)variance estimates among all traits: functional longevity, milking speed, SCS, 5 production traits (milk, fat and protein yields, fat and protein percent), and 19 type traits. Heritabilities estimated were 0.14 ± 0.02 for SCS, 0.33 ± 0.07 for milk flow, and 0.04 ± 0.01 for functional longevity. Genetic correlation values between SCS and milk yield, fat percent and protein percent resulted of 0.18 ± 0.09, -0.19 ± 0.08, and -0.22 ± 0.08 respectively. Functional longevity had a strong positive genetic correlation with udder depth (0.42 ± 0.10) while a negative correlation with rear legs set (-0.56 ± 0.10). Milk flow was positively correlated with most of the production measures: 0.30 ± 0.18 with milk yield, 0.24 ± 0.17 with fat yields 0.16 ± 0.20 with protein yield. Additionally milk flow resulted largely genetically correlated with some type traits (0.53 ± 0.14 rear udder width, 0.40 ± 0.16 hock quality, 0.32 ± 0.15 rump angle, -0.25 ± 0.19 with udder depth). The correlation between SCS and milk flow showed a value of 0.46 ± 0.26 indicating that faster cows are more susceptible to mastitis

Evaluation of bull fertility in Italian Brown Swiss dairy cattle using cow field data

Dairy bull fertility is traditionally evaluated using semen production and quality traits; however, these attributes explain only part of the differences observed in fertility among bulls. Alternatively, bull fertility can be directly evaluated using cow field data. The main objective of this study was to investigate bull fertility in the Italian Brown Swiss dairy cattle population using confirmed pregnancy records. The data set included a total of 397,926 breeding records from 1,228 bulls and 129,858 lactating cows between first and fifth lactation from 2000 to 2019. We first evaluated cow pregnancy success, including factors related to the bull under evaluation, such as bull age, bull inbreeding, and AI organization, and factors associated with the cow that receives the dose of semen, including herd-year-season, cow age, parity, and milk yield. We then estimated sire conception rate using only factors related to the bull. Model predictive ability was evaluated using 10-fold cross-validation with 10 replicates. Interestingly, our analyses revealed that there is a substantial variation in conception rate among Brown Swiss bulls, with more than 20% conception rate difference between high fertility and low-fertility bulls. We also showed that the prediction of bull fertility is feasible as our cross -validation analyses achieved predictive correlations equal to 0.30 for sire conception rate. Improving reproduction performance is one of the major challenges of the dairy industry worldwide, and for this, it is essential to have accurate predictions of service sire fertility. This study represents the foundation for the development of novel tools that will allow dairy producers, breeders, and artificial insemination companies to make enhanced management and selection decisions on Brown Swiss male fertility