6 resultados para Cento anni fa

em eResearch Archive - Queensland Department of Agriculture


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Farnesoic acid O-methyltransferase (FaMeT) is the enzyme responsible for the conversion of farnesoic acid (FA) to methyl farnesoate (MF) in the final step of MF synthesis. Multiple isoforms of putative FaMeT were isolated from six crustacean species belonging to the families Portunidae, Penaeidae, Scyllaridae and Parastacidae. The portunid crabs Portunus pelagicus and Scylla serrata code for three forms: short, intermediate and long. Two isoforms (short and long) were isolated from the penaeid prawns Penaeus monodon and Fenneropenaeus merguiensis. Two isoforms were also identified in the scyllarid Thenus orientalis and parastacid Cherax quadricarinatus. Putative FaMeT sequences were also amplified from the genomic DNA of P. pelagicus and compared to the putative FaMeT transcripts expressed. Each putative FaMeT cDNA isoform was represented in the genomic DNA, indicative of a multi-gene family. Various tissues from P. pelagicus were individually screened for putative FaMeT expression using PCR and fragment analysis. Each tissue type expressed all three isoforms of putative FaMeT irrespective of sex or moult stage. Protein domain analysis revealed the presence of a deduced casein kinase II phosphorylation site present only in the long isoform of putative FaMeT.

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Modeling of cultivar x trial effects for multienvironment trials (METs) within a mixed model framework is now common practice in many plant breeding programs. The factor analytic (FA) model is a parsimonious form used to approximate the fully unstructured form of the genetic variance-covariance matrix in the model for MET data. In this study, we demonstrate that the FA model is generally the model of best fit across a range of data sets taken from early generation trials in a breeding program. In addition, we demonstrate the superiority of the FA model in achieving the most common aim of METs, namely the selection of superior genotypes. Selection is achieved using best linear unbiased predictions (BLUPs) of cultivar effects at each environment, considered either individually or as a weighted average across environments. In practice, empirical BLUPs (E-BLUPs) of cultivar effects must be used instead of BLUPs since variance parameters in the model must be estimated rather than assumed known. While the optimal properties of minimum mean squared error of prediction (MSEP) and maximum correlation between true and predicted effects possessed by BLUPs do not hold for E-BLUPs, a simulation study shows that E-BLUPs perform well in terms of MSEP.

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Genetic models partitioning additive and non-additive genetic effects for populations tested in replicated multi-environment trials (METs) in a plant breeding program have recently been presented in the literature. For these data, the variance model involves the direct product of a large numerator relationship matrix A, and a complex structure for the genotype by environment interaction effects, generally of a factor analytic (FA) form. With MET data, we expect a high correlation in genotype rankings between environments, leading to non-positive definite covariance matrices. Estimation methods for reduced rank models have been derived for the FA formulation with independent genotypes, and we employ these estimation methods for the more complex case involving the numerator relationship matrix. We examine the performance of differing genetic models for MET data with an embedded pedigree structure, and consider the magnitude of the non-additive variance. The capacity of existing software packages to fit these complex models is largely due to the use of the sparse matrix methodology and the average information algorithm. Here, we present an extension to the standard formulation necessary for estimation with a factor analytic structure across multiple environments.

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The effect of partially replacing rolled barley (86.6% of control diet) with 20% wheat dried distillers grains plus solubles (DDGS), 40% wheat DDGS, 20% corn DDGS, or 40% corn DDGS (dietary DM basis) on rumen fluid fatty acid (FA) composition and some rumen bacterial communities was evaluated using 100 steers (20 per treatment). Wheat DDGS increased the 11t-to 10t-18:1 ratio (P < 0.05) in rumen fluid and there was evidence that the conversion of trans-18:1 to 18:0 was reduced in the control and wheat DDGS diets but not in the corn DDGS diet. Bacterial community profiles obtained using denaturing gradient gel electrophoresis and evaluated by Pearson correlation similarity matrices were not consistent for diet and, therefore, these could not be linked to different specific rumen FA. This inconsistency may be related to the nature of diets fed (dominant effect of barley), limited change in dietary composition as the result of DDGS inclusion, large animal-to-animal variation, and possibly additional stress as a result of transport just before slaughter. Ruminal densities of a key fiber-digesting bacteria specie that produces 11t-18:1 from linoleic and linolenic acids (Butyrivibrio fibrisolvens), and a lactate producer originally thought responsible for production of 10t, 12c-18:2 (Megasphaera elsdenii) were not influenced by diet (P > 0.05).

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Bats have been found to harbor a number of new emerging viruses with zoonotic potential and there has been a great deal of interest in identifying novel bat pathogens to determine risk to human and animal health. Many groups have identified novel viruses in bats by detection of viral nucleic acid, however virus isolation is still a challenge and there are few reports of viral isolates from bats. In recent years, our group has developed optimized procedures for virus isolation from bat urine, including the use of primary bat cells. In previous reports we have described the isolation of Hendra virus, Menangle virus and Cedar virus, in Queensland, Australia. Here, we report the isolation of four additional novel bat paramyxoviruses from urine collected from beneath pteropid bat (flying fox) colonies in Queensland and New South Wales during 2009-2011.