Unitride Unioplar Nitride Photonic Devices

AbstractWe present a review of the latest achievements of the UNITRIDE project in terms of GaN-based quantum engineered photonic devices operating in the near- to far-infrared spectral range

Impact of the use of cryobank samples in a selected cattle breed: a simulation study

<p>Abstract</p> <p>Background</p> <p>High selection pressure on domestic cattle has led to an undesirable increase in inbreeding, as well as to the deterioration of some functional traits which are indirectly selected. Semen stored in a cryobank may be a useful way to redirect selection or limit the loss of genetic diversity in a selected breed. The purpose of this study was to analyse the efficiency of current cryobank sampling methods, by investigating the benefits of using cryopreserved semen in a selection scheme several generations after the semen was collected.</p> <p>Methods</p> <p>The theoretical impact of using cryopreserved semen in a selection scheme of a dairy cattle breed was investigated by simulating various scenarios involving two negatively correlated traits and a change in genetic variability of the breed.</p> <p>Results</p> <p>Our results indicate that using cryopreserved semen to redirect selection will have an impact on negatively selected traits only if it is combined with major changes in selection objectives or practices. If the purpose is to increase genetic diversity in the breed, it can be a viable option.</p> <p>Conclusions</p> <p>Using cryopreserved semen to redirect selection or to improve genetic diversity should be carried out with caution, by considering the pros and cons of prospective changes in genetic diversity and the value of the selected traits. However, the use of genomic information should lead to more interesting perspectives to choose which animals to store in a cryobank and to increase the value of cryobank collections for selected breeds.</p

Cubic-spline interpolation to estimate effects of inbreeding on milk yield in first lactation Holstein cows

Milk yield records (305d, 2X, actual milk yield) of 123,639 registered first lactation Holstein cows were used to compare linear regression (y = β0 + β1X + e), quadratic regression, (y = β0 + β1X + β2X2 + e) cubic regression (y = β0 + β1X + β2X2 + β3X3 +e) and fixed factor models, with cubic-spline interpolation models, for estimating the effects of inbreeding on milk yield. Ten animal models, all with herd-year-season of calving as fixed effect, were compared using the Akaike corrected-Information Criterion (AICc). The cubic-spline interpolation model with seven knots had the lowest AICc, whereas for all those labeled as “traditional”, AICc was higher than the best model. Results from fitting inbreeding using a cubic-spline with seven knots were compared to results from fitting inbreeding as a linear covariate or as a fixed factor with seven levels. Estimates of inbreeding effects were not significantly different between the cubic-spline model and the fixed factor model, but were significantly different from the linear regression model. Milk yield decreased significantly at inbreeding levels greater than 9%. Variance component estimates were similar for the three models. Ranking of the top 100 sires with daughter records remained unaffected by the model used

Rickettsia Phylogenomics: Unwinding the Intricacies of Obligate Intracellular Life

BACKGROUND: Completed genome sequences are rapidly increasing for Rickettsia, obligate intracellular alpha-proteobacteria responsible for various human diseases, including epidemic typhus and Rocky Mountain spotted fever. In light of phylogeny, the establishment of orthologous groups (OGs) of open reading frames (ORFs) will distinguish the core rickettsial genes and other group specific genes (class 1 OGs or C1OGs) from those distributed indiscriminately throughout the rickettsial tree (class 2 OG or C2OGs). METHODOLOGY/PRINCIPAL FINDINGS: We present 1823 representative (no gene duplications) and 259 non-representative (at least one gene duplication) rickettsial OGs. While the highly reductive (approximately 1.2 MB) Rickettsia genomes range in predicted ORFs from 872 to 1512, a core of 752 OGs was identified, depicting the essential Rickettsia genes. Unsurprisingly, this core lacks many metabolic genes, reflecting the dependence on host resources for growth and survival. Additionally, we bolster our recent reclassification of Rickettsia by identifying OGs that define the AG (ancestral group), TG (typhus group), TRG (transitional group), and SFG (spotted fever group) rickettsiae. OGs for insect-associated species, tick-associated species and species that harbor plasmids were also predicted. Through superimposition of all OGs over robust phylogeny estimation, we discern between C1OGs and C2OGs, the latter depicting genes either decaying from the conserved C1OGs or acquired laterally. Finally, scrutiny of non-representative OGs revealed high levels of split genes versus gene duplications, with both phenomena confounding gene orthology assignment. Interestingly, non-representative OGs, as well as OGs comprised of several gene families typically involved in microbial pathogenicity and/or the acquisition of virulence factors, fall predominantly within C2OG distributions. CONCLUSION/SIGNIFICANCE: Collectively, we determined the relative conservation and distribution of 14354 predicted ORFs from 10 rickettsial genomes across robust phylogeny estimation. The data, available at PATRIC (PathoSystems Resource Integration Center), provide novel information for unwinding the intricacies associated with Rickettsia pathogenesis, expanding the range of potential diagnostic, vaccine and therapeutic targets

Standard errors of solutions in large scale mixed models, application to linear and curvilinear effects of inbreeding on production traits.

Many approaches for using linear mixed models do not produce standard errors of solutions. However, knowing the standard errors allows for statistical tests. Even if exact estimation of standard errors is not feasible in large mixed models, there are methods to approximate them. We based this on Mixed Model Conjugate Normal Equations associated with a Preconditioned Conjugate Gradient (PCG) solver. The advantage of associating both methods is that the right hand side vector normally accumulated by PCG can be easily changed to a function of solutions vector k allowing direct solution for Φ=C-1k using regular PCG solving programs. The square root of k’Φ=k’C-1k gives the standard error associated with the function of solutions described by k. Often a block of C-1 is needed. Its elements were obtained by computing linear functions of element of this block and by backsolving to obtain the needed elements. In matrix notation let K be the coefficients of the linear functions and D a matrix containing the values obtained by computing K’C-1K. The elements of the block were then obtained as (KK’)-1KDK’(KK’)-1. This method was applied to study linearity of inbreeding depression on milk, fat and protein test-day yields. Inbreeding effects were estimated using linear, quadratic and cubic regressions on inbreeding coefficients inside breeds in a test-day model similar to the one used in the Walloon Region of Belgium. The pedigree contained 956,516 animals. A total of 5,596,038 first lactations test-day records from 660,407 cows were used. Results had contrasting behaviors, however evaluation of plotted inbreeding effect and the associated confidence interval showed that between 0 an 10% inbreeding differences among evaluations of inbreeding depression were small

A useful new type of random regressions based on biological differences among repeated records, application to longevity.

peer reviewedA major problem in random regression models is that it is not always obvious what type of regressions to use. Different types of functions were identified and use. The first type used where functions that described lactation shapes. These functions did an excellent job to describe the mean, however were very poor in modeling of (co)variance structures. The second group of functions was based on strictly mathematical ones as polynomials. Polynomials were excellent for modeling the (co)variances as long as high order polynomials could be used. Different alternative functions were proposed over time (e.g., splines). Recently another alternative method was proposed by Wiggans and Van Raden (2004) based on the concept of parity differences (PD). Instead of using predefined functions they defined as regressions differences among repeated records. This can be considered an approximation of expected a priory change in genetic merit across those repetitions where the relative size of genetic differences by parity were derived from genetic correlations. We will use the word biological differences as the idea is to base it on individual difference corrected for the environment. The following example might clarify the general idea. Wiggans and Van Raden (2004) defined relative PD among the first five lactation for milk yield as -0.9, 0.1, 0.4, 0.6 and 0.7 which means that differences from second to third, from third to fourth and from fourth to five represent 30%, 20% respectively 10% of the difference from first to second. This has the side effect that (co)variance structures are modelled as quadratic functions of regressors. Through the use of these PD they linearized changes from one lactation to the next. The objective of this paper was to present this idea and to use it for multi-lactation longevity evaluations