9 research outputs found

    Copy number variation mapping and genomic variation of autochthonous and commercial turkey populations

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    This study aims at investigating genomic diversity of several turkey populations using Copy Number Variants (CNVs). A total of 115 individuals from six Italian breeds (Colle Euganei, Bronzato Comune Italiano, Parma e Piacenza, Brianzolo, Nero d\u2019Italia, and Ermellinato di Rovigo), seven Narragansett, 38 commercial hybrids, and 30 Mexican turkeys, were genotyped with the Affymetrix 600K single nucleotide polymorphism (SNP) turkey array. The CNV calling was performed with the Hidden Markov Model of PennCNV software and with the Copy Number Analysis Module of SVS 8.4 by Golden Helix\uae. CNV were summarized into CNV regions (CNVRs) at population level using BEDTools. Variability among populations has been addressed by hierarchical clustering (pvclust R package) and by principal component analysis (PCA). A total of 2,987 CNVs were identified covering 4.65% of the autosomes of the Turkey_5.0/melGal5 assembly. The CNVRs identified in at least two individuals were 362\u2014189 gains, 116 losses, and 57 complexes. Among these regions the 51% contain annotated genes. This study is the first CNV mapping of turkey population using 600K chip. CNVs clustered the individuals according to population and their geographical origin. CNVs are known to be indicators also of adaptation, as some researches in different species are suggesting

    Genome-wide association studies for methane production in dairy cattle

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    © 2019 by the authors. Licensee MDPI, Basel, Switzerland. Genomic selection has been proposed for the mitigation of methane (CH4) emissions by cattle because there is considerable variability in CH4 emissions between individuals fed on the same diet. The genome-wide association study (GWAS) represents an important tool for the detection of candidate genes, haplotypes or single nucleotide polymorphisms (SNP) markers related to characteristics of economic interest. The present study included information for 280 cows in three dairy production systems in Mexico: 1) Dual Purpose (n = 100), 2) Specialized Tropical Dairy (n = 76), 3) Familiar Production System (n = 104). Concentrations of CH4 in a breath of individual cows at the time of milking (MEIm) were estimated through a system of infrared sensors. After quality control analyses, 21,958 SNPs were included. Associations of markers were made using a linear regression model, corrected with principal component analyses. In total, 46 SNPs were identified as significant for CH4 production. Several SNPs associated with CH4 production were found at regions previously described for quantitative trait loci of composition characteristics of meat, milk fatty acids and characteristics related to feed intake. It was concluded that the SNPs identified could be used in genomic selection programs in developing countries and combined with other datasets for global selection

    Economical and Biological Efficiencies of Beef Cattle Differing in Level of Milk Production

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    Economical and biological efficiencies of beef production to weaning and to slaughter were estimated in three groups, different in milk available (low, medium, and high) to the calves but with the same potential for growth. Data from different breed groups of cows (low [L] = Hereford x Angus, medium [M] = Red Poll x Angus, and high [H] = Milking Shorthorn x Angus) were used. Economical efficiency was the ratio of income to expenses and biological efficiency was the ratio of calf weight to total feed energy required. Income was derived from cull cows and calves at weaning or carcasses of calves fed to slaughter. Feed and non-feed expenses for the cowherd and for calves to weaning or to slaughter were included in economical efficiency. Efficiencies were estimated assuming observed reproductive rates and energy requirements for maintenance, as well as for equal reproductive rates and equal energy requirements for maintenance in the M and H groups. With slaughter were 28.1, 27.2, and 27.5 g of weaning weight and 22.0, 20.4, and 20.3 g of carcass weight per megacalorie of ME for L, M, and H, respectively; the corresponding values using equal reproduction and equal maintenance in M and H were 28.3, 27.2, and 27.4 g of weaning weight and 22.1, 20.5, and 20.5 g of carcass weight per megacalorie of ME. Economical efficiencies (dollars of income x 100/dollars of expense) under the observed reproductive rates and maintenance requirements were 90.3, 89.2, and 88.1 to weaning and were 99.5, 96.5, and 95.3 to slaughter for L, M, and H, respectively; under equal reproduction and equal maintenance in M and H, the efficiencies at weaning were 91.0, 88.4, and 88.9 and at slaughter were 100.0, 95.7, and 95.1. Across the two scenarios, L was always the most economically efficient, especially when evaluated at slaughter of calves. Economical efficiency comparisons agreed closely with the observed reproductive rates and maintenance biological efficiency comparisons of the three cattle requirements, biological efficiencies to weaning and to groups

    Particulate matter air pollution and respiratory impact on humans and animals

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    Air pollution is now fully acknowledged to be a public health problem and a social issue. Particulate matter (PM) concentration has been linked with several clinical manifestations of pulmonary and cardiovascular diseases and is associated with morbidity and mortality induced by respiratory diseases both in human and animals. Current research on airborne particle-induced health effects investigates the critical characteristics of particulate matter that determine their biological effects. Scientific evidence assessed that the size of the airborne particles and their surface area determine the potential to elicit inflammatory injury, oxidative damage, and other biological effects. Thus, the present review paper aims to summarize the current evidences and findings on the effect of air pollution on lung function in both humans and animal

    Risk of COVID-19 after natural infection or vaccinationResearch in context

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    Summary: Background: While vaccines have established utility against COVID-19, phase 3 efficacy studies have generally not comprehensively evaluated protection provided by previous infection or hybrid immunity (previous infection plus vaccination). Individual patient data from US government-supported harmonized vaccine trials provide an unprecedented sample population to address this issue. We characterized the protective efficacy of previous SARS-CoV-2 infection and hybrid immunity against COVID-19 early in the pandemic over three-to six-month follow-up and compared with vaccine-associated protection. Methods: In this post-hoc cross-protocol analysis of the Moderna, AstraZeneca, Janssen, and Novavax COVID-19 vaccine clinical trials, we allocated participants into four groups based on previous-infection status at enrolment and treatment: no previous infection/placebo; previous infection/placebo; no previous infection/vaccine; and previous infection/vaccine. The main outcome was RT-PCR-confirmed COVID-19 >7–15 days (per original protocols) after final study injection. We calculated crude and adjusted efficacy measures. Findings: Previous infection/placebo participants had a 92% decreased risk of future COVID-19 compared to no previous infection/placebo participants (overall hazard ratio [HR] ratio: 0.08; 95% CI: 0.05–0.13). Among single-dose Janssen participants, hybrid immunity conferred greater protection than vaccine alone (HR: 0.03; 95% CI: 0.01–0.10). Too few infections were observed to draw statistical inferences comparing hybrid immunity to vaccine alone for other trials. Vaccination, previous infection, and hybrid immunity all provided near-complete protection against severe disease. Interpretation: Previous infection, any hybrid immunity, and two-dose vaccination all provided substantial protection against symptomatic and severe COVID-19 through the early Delta period. Thus, as a surrogate for natural infection, vaccination remains the safest approach to protection. Funding: National Institutes of Health
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