Assessment of Poly(ADP-ribose) Polymerase1 (PARP1) expression and activity in cells purified from blood and milk of dairy cattle

Poly(ADP-ribosyl)ation (PAR) is a post-translational protein modification catalysed by enzyme member of the poly(ADP-ribose) polymerases (PARPs) family. The activation of several PARPs is triggered by DNA strand breakage and the main PARP enzyme involved in this process is PARP1. Besides its involvement in DNA repair, PARP1 is involved in several cellular processes including transcription, epigenetics, chromatin re-modelling as well as in the maintenance of genomic stability. Moreover, several studies in human and animal models showed PARP1 activation in various inflammatory disorders. The aims of the study were (1) to characterize PARP1 expression in bovine peripheral blood mononuclear cells (PBMC) and (2) to evaluate PAR levels as a potential inflammatory marker in cells isolated from blood and milk samples following different types of infection, including mastitis. Our results show that (i) bovine PBMC express PARP1; (ii) lymphocytes exhibit higher expression of PARP1 than monocytes; (iii) PARP1 and PAR levels were higher in circulating PBMCs of infected cows; (iv) PAR levels were higher in cells isolated from milk with higher Somatic Cell Counts (SCC > 100,000 cells/mL) than in cells from milk with low SCCs. In conclusion, these findings suggest that PARP1 is activated during mastitis, which may prove to be a useful biomarker of mastitis

A genome wide association study for backfat thickness in Italian Large White pigs highlights new regions affecting fat deposition including neuronal genes.

open9noBACKGROUND: Carcass fatness is an important trait in most pig breeding programs. Following market requests, breeding plans for fresh pork consumption are usually designed to reduce carcass fat content and increase lean meat deposition. However, the Italian pig industry is mainly devoted to the production of Protected Designation of Origin dry cured hams: pigs are slaughtered at around 160 kg of live weight and the breeding goal aims at maintaining fat coverage, measured as backfat thickness to avoid excessive desiccation of the hams. This objective has shaped the genetic pool of Italian heavy pig breeds for a few decades. In this study we applied a selective genotyping approach within a population of ~ 12,000 performance tested Italian Large White pigs. Within this population, we selectively genotyped 304 pigs with extreme and divergent backfat thickness estimated breeding value by the Illumina PorcineSNP60 BeadChip and performed a genome wide association study to identify loci associated to this trait. RESULTS: We identified 4 single nucleotide polymorphisms with P≤5.0E-07 and additional 119 ones with 5.0E-07<P≤5.0E-05. These markers were located throughout all chromosomes. The largest numbers were found on porcine chromosomes 6 and 9 (n=15), 4 (n=13), and 7 (n=12) while the most significant marker was located on chromosome 18. Twenty-two single nucleotide polymorphisms were in intronic regions of genes already recognized by the Pre-Ensembl Sscrofa10.2 assembly. Gene Ontology analysis indicated an enrichment of Gene Ontology terms associated with nervous system development and regulation in concordance with results of large genome wide association studies for human obesity. CONCLUSIONS: Further investigations are needed to evaluate the effects of the identified single nucleotide polymorphisms associated with backfat thickness on other traits as a pre-requisite for practical applications in breeding programs. Reported results could improve our understanding of the biology of fat metabolism and deposition that could also be relevant for other mammalian species including humans, confirming the role of neuronal genes on obesity.To June 10, 2013 the paper is labelled as "Highly accessed" on the BMC genomics website http://www.biomedcentral.com/1471-2164/13/583openFontanesi L;Schiavo G;Galimberti G;Calò DG;Scotti E;Martelli PL;Buttazzoni L;Casadio R;Russo VFontanesi L;Schiavo G;Galimberti G;Calò DG;Scotti E;Martelli PL;Buttazzoni L;Casadio R;Russo

Novel SNPs and haplotypes identified in the<i>CD4</i>gene and their influence on deregressed MACE EBV indexes of milk-related traits in Simmental breed

AbstractCluster of differentiation 4 (CD4) is the accessory protein non-covalently bound to the T cell receptor that recognizes an invariant region of MHC class II on antigen presenting cells. Its cytoplasmic tail, physically associated with a protein tyrosine kinase, is important in the activation of helper/inducer T lymphocytes. InBos taurus,CD4gene is located on chromosome 5 from which two isoforms are transcribed, with a different number of amino acids due to splicing of exon 7 and variation in the reading frame. The aim of this study was to investigate the sequence of the entireCD4gene in Simmental sires to evaluate the effects of genomic variants on the indexes of the bulls for milk, fat and protein yields, as well as somatic cell score. The associations among genomic variants and indexes were analysed using the Allele and GLM procedures of SAS 9.4. The analysis indicated that only four of the thirty-one identified SNPs influenced the considered traits. Identified variants insist on coding zones and intronic sequences, where we revealed the presence of sites for transcription factors. To evaluate the existence of haplotypic effects, combinations among the four genomic variants (SNP 3, SNP 8, SNP 11 and SNP 19) were investigated. Six different haplotypic alleles were identified, but only four of them were frequent enough to allow for an evaluation of any haplotypic effect (at least six copies in the examined sample): Hap1, Hap2, Hap3 and Hap6. The analysis of associations between the selected haplotypes in theCD4gene with milk related indexes showed that bulls with Hap2 (T-A-C-C) had better indexes for milk and protein yields (P< 0.05), whereas the presence of the Hap1 haplotype (A-G-A-T) caused a significant decrease of the index for protein yield (P< 0.05). Frequencies of the two alleles Hap1 and Hap2 (9 and 36% respectively) make them of interest for their possible inclusion in breeding schemes and support the hypothesis of considering this gene as a candidate for the improvement of milk-related traits in the Simmental breed

Flow Cytometry-Detected Immunological Markers and on Farm Recorded Parameters in Composite Cow Milk as Related to Udder Health Status

Flow cytometry is a powerful technology used in many fields of cell biology. It is also used as a routine method to count somatic cells in milk and to characterize bovine milk leukocytes. In this study, we used flow cytometry to simultaneously assess the viability, the percentage of the single subsets of leukocytes and to quantify the expression of CD11b, an immunological marker of cell activation status. Immunological markers were then related with on farm recorded parameters as milk electrical conductivity (MEC) and average milk flow rate (MFR). Composite milk samples were collected from 43 cows, nine of which had naturally infected udders and 34 of which had no infected udders. First, the milk samples were classified according to bacteriological test in positive and negative. The results showed that the negative samples to bacteriological test had: (i) significantly higher percentages of live lymphocytes; (ii) significantly lower percentages of CD11b+ leukocytes; (iii) significantly lower MEC and higher MFR values. Then, samples were classified in three groups according to somatic cell count (SCC): Group A (n = 15), samples with SCC &le; 100,000 cells/mL, all negative to bacteriological analysis; Group B (n = 11), samples with 100,000 &lt; SCC &lt; 300,000 cells/m, with four samples positive to bacteriological analysis; Group C (n = 17), samples with SCC &ge; 300,000 cell/mL with five samples positive to bacteriological analysis. Multivariate discriminant analysis was used to verify which flow cytometry immunological markers and on farm recorded parameters could better discriminate among the different groups of SCCs. Linear discriminant analysis (LDA) indicated that 5 of the 10 parameters could best be used to reveal the differences between positive and negative samples among the considered groups of SCCs. Furthermore, the Canonical discriminant analysis (CDA) indicated that composite milk samples with different SCC and infection status were clearly separated from each other in a two-dimensional space. In conclusion, the study highlighted that: (1) the conventional flow cytometry analysis applied on milk samples is a useful tool to investigate immunological parameters as potential indicators of udder health; (2) the combined evaluation of live milk leukocytes and recorded farm parameters could be useful to assess udder health status in dairy cows. The results obtained from this pilot study on few data require new and larger trials to be confirmed

Disparities in COVID-19 hospitalization at the intersection of race and ethnicity and income

Background: Existing studies have elucidated racial and ethnic disparities in COVID-19 hospitalizations, but few have examined disparities at the intersection of race and ethnicity and income. Methods: We used a population-based probability survey of non-institutionalized adults in Michigan with a polymerase chain reaction-positive SARS-CoV-2 test before November 16, 2020. We categorized respondents by race and ethnicity and annual household income: low-income (\u3c $50,000) Non-Hispanic (NH) Black, high-income (≥$50,000) NH Black, low-income Hispanic, high-income Hispanic, low-income NH White, and high-income NH White. We used modified Poisson regression models, adjusting for sex, age group, survey mode, and sample wave, to estimate COVID-19 hospitalization prevalence ratios by race and ethnicity and income. Results: Over half of the analytic sample (n = 1593) was female (54.9%) and age 45 or older (52.5%), with 14.5% hospitalized for COVID-19. Hospitalization was most prevalent among low-income (32.9%) and high-income (31.2%) Non-Hispanic (NH) Black adults, followed by low-income NH White (15.3%), low-income Hispanic (12.9%), high-income NH White (9.6%), and high-income Hispanic adults (8.8%). In adjusted models, NH Black adults, regardless of income (low-income prevalence ratio [PR]: 1.86, 95% CI: 1.36-2.54; high-income PR: 1.57, 95% CI: 1.07-2.31), and low-income NH White adults (PR: 1.52, 95% CI: 1.12-2.07), had higher prevalence of hospitalization compared to high-income NH White adults. We observed no significant difference in the prevalence of hospitalization among Hispanic adults relative to high-income NH White adults. Conclusions: We observed disparities in COVID-19 hospitalization at the intersection of race and ethnicity and income for NH Black adults and low-income NH White adults relative to high-income NH White adults, but not for Hispanic adults

Twenty years of artificial directional selection have shaped the genome of the Italian Large White pig breed.

In this study, we investigated at the genome-wide level if 20 years of artificial directional selection based on boar genetic evaluation obtained with a classical BLUP animal model shaped the genome of the Italian Large White pig breed. The most influential boars of this breed (n = 192), born from 1992 (the beginning of the selection program of this breed) to 2012, with an estimated breeding value reliability of >0.85, were genotyped with the Illumina Porcine SNP60 BeadChip. After grouping the boars in eight classes according to their year of birth, filtered single nucleotide polymorphisms (SNPs) were used to evaluate the effects of time on genotype frequency changes using multinomial logistic regression models. Of these markers, 493 had a P-Bonferroni < 0.10. However, there was an increasing number of SNPs with a decreasing level of allele frequency changes over time, representing a continuous profile across the genome. The largest proportion of the 493 SNPs was on porcine chromosome (SSC) 7, SSC2, SSC8 and SSC18 for a total of 204 haploblocks. Functional annotations of genomic regions, including the 493 shifted SNPs, reported a few Gene Ontology terms that might underly the biological processes that contributed to increase performances of the pigs over the 20 years of the selection program. The obtained results indicated that the genome of the Italian Large White pigs was shaped by a directional selection program derived by the application of methodologies assuming the infinitesimal model that captured a continuous trend of allele frequency changes in the boar population

Genome wide perspective of genetic variation in pig metabolism and production traits

In this study we present a first genomics-metabolomics approach in pigs. About 900 performance tested Italian Large White pigs were genotyped with the Illumina PorcineSNP60 BeadChip. Blood was collected at slaughtering for haematological analyses. Plasma was used for the determination of 186 metabolites using mass spectrometry. Performance and carcass traits were measured on the same animals. Heritability of metabotypes and haematological parameters ranged from 0.04 to 0.93. A Graphical Gaussian Model (GGM) was generated including partial correlation coefficients. The structure of the obtained network represent clearly the general biological relationships among metabolites. GGM analyses suggested that pig metabolism is very close to the human metabolism. Genome wide association studies, carried out for a total of 153 traits, identified genetic variation in genes directly involved in the metabolism of several metabolites that could open interesting applications in pig nutrigenomics