Repressor activator protein 1 (Rap1) performs multiple vital cellular functions in the budding yeast Saccharomyces cerevisiae. These include regulation of telomere length, transcriptional repression of both telomere-proximal genes and the silent mating type loci, and transcriptional activation of hundreds of mRNA-encoding genes, including the highly transcribed ribosomal protein- and glycolytic enzyme-encoding genes. Studies of the contributions of Rap1 to telomere length regulation and transcriptional repression have yielded significant mechanistic insights. However, the mechanism of Rap1 transcriptional activation remains poorly understood because Rap1 is encoded by a single copy essential gene and is involved in many disparate and essential cellular functions, preventing easy interpretation of attempts to directly dissect Rap1 structure-function relationships. Moreover, conflicting reports on the ability of Rap1-heterologous DNA-binding domain fusion proteins to serve as chimeric transcriptional activators challenge use of this approach to study Rap1. Described here is the development of an altered DNA-binding specificity variant of Rap1 (Rap1AS). We used Rap1AS to map and characterize a 41-amino acid activation domain (AD) within the Rap1 C terminus. We found that this AD is required for transcription of both chimeric reporter genes and authentic chromosomal Rap1 enhancer-containing target genes. Finally, as predicted for a bona fide AD, mutation of this newly identified AD reduced the efficiency of Rap1 binding to a known transcriptional coactivator TFIID-binding target, Taf5. In summary, we show here that Rap1 contains an AD required for Rap1-dependent gene transcription. The Rap1AS variant will likely also be useful for studies of the functions of Rap1 in other biological pathways. PMID:28196871
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The study of RNA has been dramatically improved by the introduction of Next Generation Sequencing platforms allowing massive and cheap sequencing of selected RNA fractions, also providing information on strand orientation (RNA-Seq). The complexity of transcriptomes and of their regulative pathways make RNA-Seq one of most complex field of NGS applications, addressing several aspects of the expression process (e.g. identification and quantification of expressed genes and transcripts, alternative splicing and polyadenylation, fusion genes and trans-splicing, post-transcriptional events, etc.). In order to provide researchers with an effective and friendly resource for analyzing RNA-Seq data, we present here RAP (RNA-Seq Analysis Pipeline), a cloud computing web application implementing a complete but modular analysis workflow. This pipeline integrates both state-of-the-art bioinformatics tools for RNA-Seq analysis and in-house developed scripts to offer to the user a comprehensive strategy for data analysis. RAP is able to perform quality checks (adopting FastQC and NGS QC Toolkit), identify and quantify expressed genes and transcripts (with Tophat, Cufflinks and HTSeq), detect alternative splicing events (using SpliceTrap) and chimeric transcripts (with ChimeraScan). This pipeline is also able to identify splicing junctions and constitutive or alternative polyadenylation sites (implementing custom analysis modules) and call for statistically significant differences in genes and transcripts expression, splicing pattern and polyadenylation site usage (using Cuffdiff2 and DESeq). Through a user friendly web interface, the RAP workflow can be suitably customized by the user and it is automatically executed on our cloud computing environment. This strategy allows to access to bioinformatics tools and computational resources without specific bioinformatics and IT skills. RAP provides a set of tabular and graphical results that can be helpful to browse, filter and export
Background The study of RNA has been dramatically improved by the introduction of Next Generation Sequencing platforms allowing massive and cheap sequencing of selected RNA fractions, also providing information on strand orientation (RNA-Seq). The complexity of transcriptomes and of their regulative pathways make RNA-Seq one of most complex field of NGS applications, addressing several aspects of the expression process (e.g. identification and quantification of expressed genes and transcripts, alternative splicing and polyadenylation, fusion genes and trans-splicing, post-transcriptional events, etc.). Moreover, the huge volume of data generated by NGS platforms introduces unprecedented computational and technological challenges to efficiently analyze and store sequence data and results. Methods In order to provide researchers with an effective and friendly resource for analyzing RNA-Seq data, we present here RAP (RNA-Seq Analysis Pipeline), a cloud computing web application implementing a complete but modular analysis workflow. This pipeline integrates both state-of-the-art bioinformatics tools for RNA-Seq analysis and in-house developed scripts to offer to the user a comprehensive strategy for data analysis. RAP is able to perform quality checks (adopting FastQC and NGS QC Toolkit), identify and quantify expressed genes and transcripts (with Tophat, Cufflinks and HTSeq), detect alternative splicing events (using SpliceTrap) and chimeric transcripts (with ChimeraScan). This pipeline is also able to identify splicing junctions and constitutive or alternative polyadenylation sites (implementing custom analysis modules) and call for statistically significant differences in genes and transcripts expression, splicing pattern and polyadenylation site usage (using Cuffdiff2 and DESeq). Results Through a user friendly web interface, the RAP workflow can be suitably customized by the user and it is automatically executed on our cloud computing environment. This strategy
An index of cerebrospinal compensatory reserve (RAP) has been introduced as a potential descriptor of neurological deterioration after head trauma. It is numerically computed as a linear correlation coefficient between the mean intracranial pressure and the pulse amplitude of the pressure waveform. We explore how RAP varies with different forms of physiological or nonphysiological intracranial volume loads in adult hydrocephalus, with and without a functioning cerebrospinal fluid (CSF) shunt. A database of intracranial pressure recordings during CSF infusion studies and overnight monitoring in hydrocephalic patients was reviewed for clinical comparison of homogeneous subgroups of patients with hypothetical differences of pressure-volume compensatory reserve. The database includes 980 patients of mixed etiology: idiopathic normal pressure hydrocephalus (NPH), 47%; postsubarachnoid hemorrhage NPH, 12%; noncommunicating hydrocephalus, 22%; others, 19%. All CSF compensatory parameters were calculated by using intracranial pressure waveforms. In NPH, RAP correlated strongly with the resistance to CSF outflow (r(s) = 0.35; P = 0.045), but weakly correlated with ventriculomegaly (r(s) = 0.13; P = 0.41). In idiopathic nonshunted NPH patients, RAP did not correlate significantly with elasticity calculated from the CSF infusion test (r(s) = 0.11; P = 0.21). During infusion studies, RAP increased in comparison to values recorded at baseline (from a median of 0.45-0.86, P = 0.14 * 10(-8)), indicating a narrowing of the volume-pressure compensatory reserve. During B-waves associated with the REM (rapid eye movement) phase of sleep, RAP increased from a median of 0.53 to 0.89; P = 1.2 * 10(-5). After shunting, RAP decreased (median before shunting, 0.59; median after shunting, 0.34; P = 0.0001). RAP also showed the ability to reflect the functional state of the shunt (patent shunt median, 0.36; blocked shunt median, 0.84; P = 0.0002). RAP appears to characterize pressure
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