Phosphorylation of Opaque2 changes diurnally and impacts its DNA binding activity.

In the maize endosperm, the Opaque2 (O2) basic leucine zipper transcriptional activator regulates the expression of a subset of the zein seed storage protein gene family. Immunodetection of wild-type or mutant O2 polypeptides fractionated by SDS-PAGE resolved a closely spaced doublet migrating in the 68- to 72-kD range, whereas by using isoelectric focusing, seven to nine isoforms were detected for each allele. Phosphatase treatment simplified the protein patterns to a single band corresponding to the nonphosphorylated component. In vivo and in vitro labeling confirmed that O2 can be phosphorylated. In protein gel blots probed with DNA, only the nonphosphorylated and hypophosphorylated O2 polypeptides were able to bind an oligonucleotide containing the O2 binding sequence. Upon in situ dephosphorylation of the focused isoforms by phosphatase treatment of the isoelectric focusing filter, the hyperphosphorylated forms acquired DNA binding activity. The ratio among the various isoforms remained constant throughout the developmental stages of endosperm growth but changed from daytime to nighttime, with a significant increase of the hyperphosphorylated forms during the night period. These results indicate that O2 exists in vivo as a pool of differently phosphorylated polypeptides and demonstrate that O2 DNA binding activity is modulated by a phosphorylation/dephosphorylation mechanism that appears to be influenced by environmental conditions

Simultaneous Scheduling of Replication and Computation for Bioinformatic Applications on the Grid

One of the first motivations of using grids comes from applications managing large data sets like for example in High Energy Physic or Life Sciences. To improve the global throughput of software environments, replicas are usually put at wisely selected sites. Moreover, computation requests have to be scheduled among the available resources. To get the best performance, scheduling and data replication have to be tightly coupled which is not always the case in existing approaches. This paper presents an algorithm that combines data management and scheduling at the same time using a steady-state approach. Our theoretical results are validated using simulation and logs from a large life science application (ACI GRID GriPPS). The PattInProt application searches sites and signatures of proteins into databanks of protein sequences