Cell cycle-dependent phosphorylation of pRb-like protein in root meristem cells of Vicia faba

The retinoblastoma tumor suppressor protein (pRb) regulates cell cycle progression by controlling the G1-to-S phase transition. As evidenced in mammals, pRb has three functionally distinct binding domains and interacts with a number of proteins including the E2F family of transcription factors, proteins with a conserved LxCxE motif (D-type cyclin), and c-Abl tyrosine kinase. CDK-mediated phosphorylation of pRb inhibits its ability to bind target proteins, thus enabling further progression of the cell cycle. As yet, the roles of pRb and pRb-binding factors have not been well characterized in plants. By using antibody which specifically recognizes phosphorylated serines (S807/811) in the c-Abl tyrosine kinase binding C-domain of human pRb, we provide evidence for the cell cycle-dependent changes in pRb-like proteins in root meristems cells of Vicia faba. An increased phosphorylation of this protein has been found correlated with the G1-to-S phase transition

PsRBR1 encodes a pea retinoblastoma-related protein that is phosphorylated in axillary buds during dormancy-to-growth transition

In intact plants, cells in axillary buds are arrested at the G1 phase of the cell cycle during dormancy. In mammalian cells, the cell cycle is suppressed at the G1 phase by the activities of retinoblastoma tumor suppressor gene (RB) family proteins, depending on their phosphorylation state. Here, we report the isolation of a pea cDNA clone encoding an RB-related protein (PsRBR1, Accession No. AB012024) with a high degree of amino acid conservation in comparison with RB family proteins. PsRBR1 protein was detected as two polypeptides using an anti-PsRBR1 antibody in dormant axillary buds, whereas it was detected as three polypeptides, which were the same two polypeptides and another larger polypeptide 2 h after terminal decapitation. Both in vitro-synthesized PsPRB1 protein and lambda protein phosphatase-treated PsRBR1 protein corresponded to the smallest polypeptide detected by anti-PsRBR1 antibody, suggesting that the three polypeptides correspond to non-phosphorylated form of PsRBR1 protein, and lower- and higher-molecular mass forms of phosphorylated PsRBR1 protein. Furthermore, in vivo labeling with [32P]-inorganic phosphate indicated that PsRBR1 protein was more phosphorylated before mRNA accumulation of cell cycle regulatory genes such as PCNA. Together these findings suggest that dormancy-to-growth transition in pea axillary buds is regulated by molecular mechanisms of cell cycle control similar to those in mammals, and that the PsRBR1 protein has an important role in suppressing the cell cycle during dormancy in axillary buds

Can Survival Prediction Be Improved By Merging Gene Expression Data Sets?

BACKGROUND:High-throughput gene expression profiling technologies generating a wealth of data, are increasingly used for characterization of tumor biopsies for clinical trials. By applying machine learning algorithms to such clinically documented data sets, one hopes to improve tumor diagnosis, prognosis, as well as prediction of treatment response. However, the limited number of patients enrolled in a single trial study limits the power of machine learning approaches due to over-fitting. One could partially overcome this limitation by merging data from different studies. Nevertheless, such data sets differ from each other with regard to technical biases, patient selection criteria and follow-up treatment. It is therefore not clear at all whether the advantage of increased sample size outweighs the disadvantage of higher heterogeneity of merged data sets. Here, we present a systematic study to answer this question specifically for breast cancer data sets. We use survival prediction based on Cox regression as an assay to measure the added value of merged data sets. RESULTS:Using time-dependent Receiver Operating Characteristic-Area Under the Curve (ROC-AUC) and hazard ratio as performance measures, we see in overall no significant improvement or deterioration of survival prediction with merged data sets as compared to individual data sets. This apparently was due to the fact that a few genes with strong prognostic power were not available on all microarray platforms and thus were not retained in the merged data sets. Surprisingly, we found that the overall best performance was achieved with a single-gene predictor consisting of CYB5D1. CONCLUSIONS:Merging did not deteriorate performance on average despite (a) The diversity of microarray platforms used. (b) The heterogeneity of patients cohorts. (c) The heterogeneity of breast cancer disease. (d) Substantial variation of time to death or relapse. (e) The reduced number of genes in the merged data sets. Predictors derived from the merged data sets were more robust, consistent and reproducible across microarray platforms. Moreover, merging data sets from different studies helps to better understand the biases of individual studies and can lead to the identification of strong survival factors like CYB5D1 expression

A network linking scene perception and spatial memory systems in posterior cerebral cortex

The neural systems supporting scene-perception and spatial-memory systems of the human brain are well-described. But how do these neural systems interact? Here, using fine-grained individual-subject fMRI, we report three cortical areas of the human brain, each lying immediately anterior to a region of the scene perception network in posterior cerebral cortex, that selectively activate when recalling familiar real-world locations. Despite their close proximity to the scene-perception areas, network analyses show that these regions constitute a distinct functional network that interfaces with spatial memory systems during naturalistic scene understanding. These “place-memory areas” offer a new framework for understanding how the brain implements memory-guided visual behaviors, including navigation

Dosage-Sensitive Function of RETINOBLASTOMA RELATED and Convergent Epigenetic Control Are Required during the Arabidopsis Life Cycle

The plant life cycle alternates between two distinct multi-cellular generations, the reduced gametophytes and the dominant sporophyte. Little is known about how generation-specific cell fate, differentiation, and development are controlled by the core regulators of the cell cycle. In Arabidopsis, RETINOBLASTOMA RELATED (RBR), an evolutionarily ancient cell cycle regulator, controls cell proliferation, differentiation, and regulation of a subset of Polycomb Repressive Complex 2 (PRC2) genes and METHYLTRANSFERASE 1 (MET1) in the male and female gametophytes, as well as cell fate establishment in the male gametophyte. Here we demonstrate that RBR is also essential for cell fate determination in the female gametophyte, as revealed by loss of cell-specific marker expression in all the gametophytic cells that lack RBR. Maintenance of genome integrity also requires RBR, because diploid plants heterozygous for rbr (rbr/RBR) produce an abnormal portion of triploid offspring, likely due to gametic genome duplication. While the sporophyte of the diploid mutant plants phenocopied wild type due to the haplosufficiency of RBR, genetic analysis of tetraploid plants triplex for rbr (rbr/rbr/rbr/RBR) revealed that RBR has a dosage-dependent pleiotropic effect on sporophytic development, trichome differentiation, and regulation of PRC2 subunit genes CURLY LEAF (CLF) and VERNALIZATION 2 (VRN2), and MET1 in leaves. There were, however, no obvious cell cycle and cell proliferation defects in these plant tissues, suggesting that a single functional RBR copy in tetraploids is capable of maintaining normal cell division but is not sufficient for distinct differentiation and developmental processes. Conversely, in leaves of mutants in sporophytic PRC2 subunits, trichome differentiation was also affected and expression of RBR and MET1 was reduced, providing evidence for a RBR-PRC2-MET1 regulatory feedback loop involved in sporophyte development. Together, dosage-sensitive RBR function and its genetic interaction with PRC2 genes and MET1 must have been recruited during plant evolution to control distinct generation-specific cell fate, differentiation, and development

Identification of Host Genes Involved in Geminivirus Infection Using a Reverse Genetics Approach

Geminiviruses, like all viruses, rely on the host cell machinery to establish a successful infection, but the identity and function of these required host proteins remain largely unknown. Tomato yellow leaf curl Sardinia virus (TYLCSV), a monopartite geminivirus, is one of the causal agents of the devastating Tomato yellow leaf curl disease (TYLCD). The transgenic 2IRGFP N. benthamiana plants, used in combination with Virus Induced Gene Silencing (VIGS), entail an important potential as a tool in reverse genetics studies to identify host factors involved in TYLCSV infection. Using these transgenic plants, we have made an accurate description of the evolution of TYLCSV replication in the host in both space and time. Moreover, we have determined that TYLCSV and Tobacco rattle virus (TRV) do not dramatically influence each other when co-infected in N. benthamiana, what makes the use of TRV-induced gene silencing in combination with TYLCSV for reverse genetic studies feasible. Finally, we have tested the effect of silencing candidate host genes on TYLCSV infection, identifying eighteen genes potentially involved in this process, fifteen of which had never been implicated in geminiviral infections before. Seven of the analyzed genes have a potential anti-viral effect, whereas the expression of the other eleven is required for a full infection. Interestingly, almost half of the genes altering TYLCSV infection play a role in postranslational modifications. Therefore, our results provide new insights into the molecular mechanisms underlying geminivirus infections, and at the same time reveal the 2IRGFP/VIGS system as a powerful tool for functional reverse genetics studies