A complete set of nascent transcription rates for yeast genes

The amount of mRNA in a cell is the result of two opposite reactions: transcription and mRNA degradation. These reactions are governed by kinetics laws, and the most regulated step for many genes is the transcription rate. The transcription rate, which is assumed to be exercised mainly at the RNA polymerase recruitment level, can be calculated using the RNA polymerase densities determined either by run-on or immunoprecipitation using specific antibodies. The yeast Saccharomyces cerevisiae is the ideal model organism to generate a complete set of nascent transcription rates that will prove useful for many gene regulation studies. By combining genomic data from both the GRO (Genomic Run-on) and the RNA pol ChIP-on-chip methods we generated a new, more accurate nascent transcription rate dataset. By comparing this dataset with the indirect ones obtained from the mRNA stabilities and mRNA amount datasets, we are able to obtain biological information about posttranscriptional regulation processes and a genomic snapshot of the location of the active transcriptional machinery. We have obtained nascent transcription rates for 4,670 yeast genes. The median RNA polymerase II density in the genes is 0.078 molecules/kb, which corresponds to an average of 0.096 molecules/gene. Most genes have transcription rates of between 2 and 30 mRNAs/hour and less than 1% of yeast genes have >1 RNA polymerase molecule/gene. Histone and ribosomal protein genes are the highest transcribed groups of genes and other than these exceptions the transcription of genes is an infrequent phenomenon in a yeast cell

Selective gene silencing by viral delivery of short hairpin RNA

RNA interference (RNAi) technology has not only become a powerful tool for functional genomics, but also allows rapid drug target discovery and in vitro validation of these targets in cell culture. Furthermore, RNAi represents a promising novel therapeutic option for treating human diseases, in particular cancer. Selective gene silencing by RNAi can be achieved essentially by two nucleic acid based methods: i) cytoplasmic delivery of short double-stranded (ds) interfering RNA oligonucleotides (siRNA), where the gene silencing effect is only transient in nature, and possibly not suitable for all applications; or ii) nuclear delivery of gene expression cassettes that express short hairpin RNA (shRNA), which are processed like endogenous interfering RNA and lead to stable gene down-regulation. Both processes involve the use of nucleic acid based drugs, which are highly charged and do not cross cell membranes by free diffusion. Therefore, in vivo delivery of RNAi therapeutics must use technology that enables the RNAi therapeutic to traverse biological membrane barriers in vivo. Viruses and the vectors derived from them carry out precisely this task and have become a major delivery system for shRNA. Here, we summarize and compare different currently used viral delivery systems, give examples of in vivo applications, and indicate trends for new developments, such as replicating viruses for shRNA delivery to cancer cells

Challenging the Wigglesworthia, Sodalis, Wolbachia symbiosis dogma in tsetse flies : Spiroplasma is present in both laboratory and natural populations

Profiling of wild and laboratory tsetse populations using 16S rRNA gene amplicon sequencing allowed us to examine whether the “Wigglesworthia-Sodalis-Wolbachia dogma” operates across species and populations. The most abundant taxa, in wild and laboratory populations, were Wigglesworthia (the primary endosymbiont), Sodalis and Wolbachia as previously characterized. The species richness of the microbiota was greater in wild than laboratory populations. Spiroplasma was identified as a new symbiont exclusively in Glossina fuscipes fuscipes and G. tachinoides, members of the palpalis sub-group, and the infection prevalence in several laboratory and natural populations was surveyed. Multi locus sequencing typing (MLST) analysis identified two strains of tsetse-associated Spiroplasma, present in G. f. fuscipes and G. tachinoides. Spiroplasma density in G. f. fuscipes larva guts was significantly higher than in guts from teneral and 15-day old male and female adults. In gonads of teneral and 15-day old insects, Spiroplasma density was higher in testes than ovaries, and was significantly higher density in live versus prematurely deceased females indicating a potentially mutualistic association. Higher Spiroplasma density in testes than in ovaries was also detected by fluorescent in situ hybridization in G. f. fuscipe

Nucleosome free regions in yeast promoters result from competitive binding of transcription factors that interact with chromatin modifiers

Because DNA packaging in nucleosomes modulates its accessibility to transcription factors (TFs), unraveling the causal determinants of nucleosome positioning is of great importance to understanding gene regulation. Although there is evidence that intrinsic sequence specificity contributes to nucleosome positioning, the extent to which other factors contribute to nucleosome positioning is currently highly debated. Here we obtained both in vivo and in vitro reference maps of positions that are either consistently covered or free of nucleosomes across multiple experimental data-sets in Saccharomyces cerevisiae. We then systematically quantified the contribution of TF binding to nucleosome positioning using a rigorous statistical mechanics model in which TFs compete with nucleosomes for binding DNA. Our results reconcile previous seemingly conflicting results on the determinants of nucleosome positioning and provide a quantitative explanation for the difference between in vivo and in vitro positioning. On a genome-wide scale, nucleosome positioning is dominated by the phasing of nucleosome arrays over gene bodies, and their positioning is mainly determined by the intrinsic sequence preferences of nucleosomes. In contrast, larger nucleosome free regions in promoters, which likely have a much more significant impact on gene expression, are determined mainly by TF binding. Interestingly, of the 158 yeast TFs included in our modeling, we find that only 10-20 significantly contribute to inducing nucleosome-free regions, and these TFs are highly enriched for having direct interactions with chromatin remodelers. Together our results imply that nucleosome free regions in yeast promoters results from the binding of a specific class of TFs that recruit chromatin remodelers