Current status and future possibilities of molecular genetics techniques in <Emphasis Type="Italic">Brassica napus</Emphasis>

As PCR methods have improved over the last 15 years, there has been an upsurge in the number of new DNA marker tools, which has allowed the generation of high-density molecular maps for all the key Brassica crop types. Biotechnology and molecular plant breeding have emerged as a significant tool for molecular understanding that led to a significant crop improvement in the Brassica napus species. Brassica napus possess a very complicated polyploidy-based genomics. The quantitative trait locus (QTL) is not sufficient to develop effective markers for trait introgression. In the coming years, the molecular marker techniques will be more effective to determine the whole genome impairing desired traits. Available genetic markers using the single-nucleotide sequence (SNP) technique and high-throughput sequencing are effective in determining the maps and genome polymorphisms amongst candidate genes and allele interactions. High-throughput sequencing and gene mapping techniques are involved in discovering new alleles and gene pairs, serving as a bridge between the gene map and genome evaluation. The decreasing cost for DNA sequencing will help in discovering full genome sequences with less resources and time. This review describes (1) the current use of integrated approaches, such as molecular marker technologies, to determine genome arrangements and interspecific outcomes combined with cost-effective genomes to increase the efficiency in prognostic breeding efforts. (2) It also focused on functional genomics, proteomics and field-based breeding practices to achieve insight into the genetics underlying both simple and complex traits in canola.     

The control of actin nucleotide exchange by thymosin beta 4 and profilin. A potential regulatory mechanism for actin polymerization in cells.

We present evidence for a new mechanism by which two major actin monomer binding proteins, thymosin beta 4 and profilin, may control the rate and the extent of actin polymerization in cells. Both proteins bind actin monomers transiently with a stoichiometry of 1:1. When bound to actin, thymosin beta 4 strongly inhibits the exchange of the nucleotide bound to actin by blocking its dissociation, while profilin catalytically promotes nucleotide exchange. Because both proteins exchange rapidly between actin molecules, low concentrations of profilin can overcome the inhibitory effects of high concentrations of thymosin beta 4 on the nucleotide exchange. These reactions may allow variations in profilin concentration (which may be regulated by membrane polyphosphoinositide metabolism) to control the ratio of ATP-actin to ADP-actin. Because ATP-actin subunits polymerize more readily than ADP-actin subunits, this ratio may play a key regulatory role in the assembly of cellular actin structures, particularly under circumstances of rapid filament turnover.     

An adenovirus mutant unable to express VAI RNA displays different growth responses and sensitivity to interferon in various host cell lines.

The VAI RNA of adenovirus is a small, RNA polymerase III-transcribed species required for the efficient translation of host cell and viral mRNAs late after infection. VAI RNA prevented activation of the interferon-induced P1/eIF-2 alpha kinase. In its absence the kinase was activated, eIF-2 alpha was phosphorylated, and translational initiation was inhibited. H5dl331 (dl331), a mutant which cannot express VAI RNA, grew poorly in 293 cells but generated wild-type yields in KB cells. The growth phenotype of the mutant appeared to correlate with the kinetics of kinase induction and activation. Active kinase appeared more rapidly in cell extracts prepared from infected 293 cells, in which dl331 grew poorly, than in extracts of KB cells, in which the mutant grew well. However, when kinase was induced in KB cells by interferon treatment and then activated subsequent to dl331 infection, viral protein synthesis was less severely inhibited than in interferon-treated 293 cells. Thus, activated kinase per se is insufficient to severely inhibit dl331 protein synthesis in KB cells.     

Interaction of thymosin beta 4 with muscle and platelet actin: implications for actin sequestration in resting platelets.

Quantitative measurements of the interactions of T beta 4 with muscle actin suggest that its only physiological role is monomer sequestration. T beta 4 forms a 1:1 complex with monomeric actin under physiological salt conditions. Its Kd for actin is not affected by calcium. T beta 4 binds only to actin monomers and not to filament ends or alongside the filament. T beta 4-actin complexes do not elongate actin filaments at either the barbed or the pointed end, and, unlike actobindin, T beta 4 does not specifically suppress the nucleation of polymerization. We assessed the fraction of monomeric actin that can be sequestered by T beta 4 in resting platelets. This was done on the basis of (a) its Kd of 0.4-0.7 microM for platelet actin, which had been prepared by a newly devised simpler method, and (b) the values for the concentrations of monomeric actin and of T beta 4 which we measured as 280 and 560 microM, respectively. Using the higher Kd value of 0.7 microM, the T beta 4-complexed actin is calculated to be between 70 and 240 microM, depending on the steady-state free G-actin concentration. This may vary from 0.1 to 0.5 microM, the critical concentrations for uncapped and for fully barbed-end-capped actin filaments. If the Kd in the platelet is the same as in vitro, most of the sequestered actin would be bound to T beta 4 if more than 95% of the actin filaments are capped at their barbed ends in resting platelets.     

Radial basis function neural networks for modeling growth rates of the basidiomycetes Physisporinus vitreus and Neolentinus lepideus

A radial basis function (RBF) neural network was developed and compared against a quadratic response surface (RS) model for predicting the specific growth rates of the biotechnologically important basidiomycetous fungi, Physisporinus vitreus and Neolentinus lepideus, under three environmental conditions: temperature (10–30 °C), water activity (0.950–9.998), and pH (4–6). Both the RBF network and polynomial RS model were mathematically evaluated against experimental data using graphical plots and several statistical indices. The evaluation showed that both models gave reasonably good predictions, but the performance of the RBF neural network was superior to that of the classical statistical method for all three data sets used (training, testing, full). Sensitivity analysis revealed that of the three experimental factors the most influential on the growth rate of P. vitreus was water activity, followed by temperature and pH to a lesser extent. In contrast, temperature in particular and then water activity were the key determinants of the development of N. lepideus. RBF neural networks could be a powerful technique for modeling fungal growth behavior under certain parameters and an alternative to time-consuming, traditional microbiological techniques.