Project description:http://www.sanger.ac.uk/resources/downloads/bacteria/These data are part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/
Project description:In this experiment we test our recently developed CLIP2C method for the identification of the RNA molecules bound by specific RNA binding proteins. CLIP2C, involves a first round of 2C, the treatment of the eluates with DNase I and an RNA fragmentation step. After this, a small aliquot is separated to be sequenced as an input, while the rest is subjected for immunoprecipitation of the protein of interest. Libraries from the input and the RNA isolated from the immunoprecipitation are generated and sequenced. In this particular experiment we used Pab1-TAP and Tdh3-Protein A tagged strains to be used in IgG-based pull-downs. An untagged WT strain was also included in the experiment as a negative control. Sequencing data from the inputs was used to address the variability in gene expression between strains and sequencing data from the IPs to detect enriched target genes or regions.
Project description:A systems-level understanding of a small but essential population of cells in development or adulthood (e.g., somatic stem cells) requires accurate quantitative monitoring of genome-wide gene expression, ideally from single cells. We report here a strategy to globally amplify mRNAs from single cells for highly quantitative high-density oligonucleotide microarray analysis that combines a small number of directional PCR cycles with subsequent linear amplification. Using this strategy, both the representation of gene expression profiles and reproducibility between individual experiments are unambiguously improved from the original method, along with high coverage and accuracy. Keywords: Method validation
Project description:MicroRNAs are important negative regulators of protein coding gene expression, and have been studied intensively over the last few years. To this purpose, different measurement platforms to determine their RNA abundance levels in biological samples have been developed. In this study, we have systematically compared 12 commercially available microRNA expression platforms by measuring an identical set of 20 standardized positive and negative control samples, including human universal reference RNA, human brain RNA and titrations thereof, human serum samples, and synthetic spikes from homologous microRNA family members. We developed novel quality metrics in order to objectively assess platform performance of very different technologies such as small RNA sequencing, RT-qPCR and (microarray) hybridization. We assessed reproducibility, sensitivity, quantitative performance, and specificity. The results indicate that each method has its strengths and weaknesses, which helps guiding informed selection of a quantitative microRNA gene expression platform in function of particular study goals.
Project description:Here we developed CapStarr-Seq, a novel high-throughput strategy to quantitatively assess enhancer activity in mammals. This approach couples capture of regions of interest to previously developed Starr-seq technique. Extensive assessment of CapStarr-seq demonstrated accurate quantification of enhancer activity. Furthermore, we found that enhancer strength correlates with binding complexity of tissue-specific transcription factors and super-enhancers, while additive enhancer activity isolates key genes involved in cell identity and function. CapStarr-seq analysis in P5424 cell line (2 replicates), 3T3 cell line and in the plasmid library before (Input) and after transfection