Contents of Volume 53

Plant Molecular Biology -     

The p53 isoforms are differentially modified by Mdm2

The discovery that the single p53 gene encodes several different p53 protein isoforms has initiated a flurry of research into the function and regulation of these novel p53 proteins. Full-length p53 protein level is primarily regulated by the E3-ligase Mdm2, which promotes p53 ubiquitination and degradation. Here, we report that all of the novel p53 isoforms are ubiquitinated and degraded to varying degrees in an Mdm2-dependent and -independent manner, and that high-risk human papillomavirus can degrade some but not all of the novel isoforms, demonstrating that full-length p53 and the p53 isoforms are differentially regulated. In addition, we provide the first evidence that Mdm2 promotes the NEDDylation of p53β. Altogether, our data indicates that Mdm2 can distinguish between the p53 isoforms and modify them differently.     

Absorption of light in photoreceptors: Effect of waveguiding property

The effect of waveguiding property (i.e., the intensity distribution) of the photoreceptor on the number of photons absorbed in a photoreceptor has been studied. It has been found that the effect is significant only for large values of the exposure and the maximum effect is less than 11% in the case of human rod photoreceptor. In the analysis, the funnelling effect, which follows from the coupling between the interior and exterior fields, has not been considered.Work partially supported by the Department of Science and Technology (India)B. D. Gupta is associated with the School of Bioscience Studies     

Identifying common prognostic factors in genomic cancer studies: A novel index for censored outcomes

Background  

With the growing number of public repositories for high-throughput genomic data, it is of great interest to combine the results produced by independent research groups. Such a combination allows the identification of common genomic factors across multiple cancer types and provides new insights into the disease process. In the framework of the proportional hazards model, classical procedures, which consist of ranking genes according to the estimated hazard ratio or the p-value obtained from a test statistic of no association between survival and gene expression level, are not suitable for gene selection across multiple genomic datasets with different sample sizes. We propose a novel index for identifying genes with a common effect across heterogeneous genomic studies designed to remain stable whatever the sample size and which has a straightforward interpretation in terms of the percentage of separability between patients according to their survival times and gene expression measurements.