Project description:Purpose: The goal of this study is to compare endothelial small RNA transcriptome to identify the target of OASL under basal or stimulated conditions by utilizing miRNA-seq. Methods: Endothelial miRNA profilies of siCTL or siOASL transfected HUVECs were generated by illumina sequencing method, in duplicate. After sequencing, the raw sequence reads are filtered based on quality. The adapter sequences are also trimmed off the raw sequence reads. rRNA removed reads are sequentially aligned to reference genome (GRCh38) and miRNA prediction is performed by miRDeep2. Results: We identified known miRNA in species (miRDeep2) in the HUVECs transfected with siCTL or siOASL. The expression profile of mature miRNA is used to analyze differentially expressed miRNA(DE miRNA). Conclusions: Our study represents the first analysis of endothelial miRNA profiles affected by OASL knockdown with biologic replicates.
Project description:A cDNA library was constructed by Novogene (CA, USA) using a Small RNA Sample Pre Kit, and Illumina sequencing was conducted according to company workflow, using 20 million reads. Raw data were filtered for quality as determined by reads with a quality score > 5, reads containing N < 10%, no 5' primer contaminants, and reads with a 3' primer and insert tag. The 3' primer sequence was trimmed and reads with a poly A/T/G/C were removed
Project description:Circadian behaviors are regulated by intrinsic biological clocks consisting of central molecular oscillators and output pathways. Despite significant progress in elucidating the central timekeeping mechanisms, the molecular pathways coupling the circadian pacemaker to overt rhythmic behavior and physiology remain elusive. The Drosophila LARK RNA-binding protein is a candidate for such a coupling factor. Previous research indicates that LARK functions downstream of the clock to mediate behavioral outputs. To better understand the roles of LARK in the Drosophila circadian system, we sought to identify RNA molecules associated with LARK in vivo, using a novel strategy that involves capturing the RNA ligands by immunoprecipitation, visualizing the captured RNAs using whole gene microarrays, and identifying functionally relevant targets through genetic screens. Experiment Overall Design: LARK-containing ribonucleoprotein complexes (LARK-RNPs) were precipitated from lysates of hand-dissected pharate adult brains using an affinity-purified anti-LARK antibody (around 1000 brains were used per immunoprecipitation experiment). A portion of each lysate was saved prior to immunoprecipitations (IPs) in order to measure the relative abundance of transcripts in a total RNA sample. RNAs extracted from the LARK-RNP and total RNA samples were labeled and hybridized to Drosophila whole-genome gene microarrays; signal intensities for individual genes were compared between samples to identify those RNAs that were enriched by immunoprecipitation (relative to their abundances in total RNA). RNAs that were selectively enriched in the LARK-RNP samples were considered to be potential targets of the RNA-binding protein. Experiment Overall Design: Due to the difficulty to dissect large amount of fly brains, only two such immunoprecipitation experiments were performed, each generating an IP RNA sample and a total RNA (control) sample. The amount of RNAs obtained from IP is very small thus only one array is used for each sample - i.e. there are only biological replicates and no technical replicate.
Project description:Circadian behaviors are regulated by intrinsic biological clocks consisting of central molecular oscillators and output pathways. Despite significant progress in elucidating the central timekeeping mechanisms, the molecular pathways coupling the circadian pacemaker to overt rhythmic behavior and physiology remain elusive. The Drosophila LARK RNA-binding protein is a candidate for such a coupling factor. Previous research indicates that LARK functions downstream of the clock to mediate behavioral outputs. To better understand the roles of LARK in the Drosophila circadian system, we sought to identify RNA molecules associated with LARK in vivo, using a novel strategy that involves capturing the RNA ligands by immunoprecipitation, visualizing the captured RNAs using whole gene microarrays, and identifying functionally relevant targets through genetic screens. Keywords: Association with RNA-binding protein
Project description:Whole exome sequencing of 5 HCLc tumor-germline pairs. Genomic DNA from HCLc tumor cells and T-cells for germline was used. Whole exome enrichment was performed with either Agilent SureSelect (50Mb, samples S3G/T, S5G/T, S9G/T) or Roche Nimblegen (44.1Mb, samples S4G/T and S6G/T). The resulting exome libraries were sequenced on the Illumina HiSeq platform with paired-end 100bp reads to an average depth of 120-134x. Bam files were generated using NovoalignMPI (v3.0) to align the raw fastq files to the reference genome sequence (hg19) and picard tools (v1.34) to flag duplicate reads (optical or pcr), unmapped reads, reads mapping to more than one location, and reads failing vendor QC.
Project description:The goal of this study is to identify, in the head of adult flies, mRNA species whose expresson level are altered by overexpression of the Drosophila RNA-binding protein LARK in CNS neurons. Experiment Overall Design: RNA samples from adult head of the LARK overexpression flies (elav-gal4; uas-lark/+) and control flies were compared. One total RNA sample was isolated from each genotype, of which three technical replicates (repeating the labeling and hybridization processes) were generated, respectively.
Project description:Recent developments in spatially resolved -omics have enabled studies linking gene expression and metabolite levels to tissue morphology, offering new insights into biological pathways. By capturing multiple modalities on matched tissue sections, one can better probe how different biological entities interact in a spatially coordinated manner. However, such cross-modality integration presents experimental and computational challenges. To align multimodal datasets into a shared coordinate system and facilitate enhanced integration and analysis, we propose MAGPIE (Multi-modal Alignment of Genes and Peaks for Integrated Exploration), a framework for co-registering spatially resolved transcriptomics, metabolomics, and tissue morphology from the same or consecutive sections. We illustrate the generalisability and scalability of MAGPIE on spatial multi-omics data from multiple tissues, combining Visium with both MALDI and DESI mass spectrometry imaging. MAGPIE was also applied to newly generated multimodal datasets created using a specialised experimental sampling strategy to characterise the metabolic and transcriptomic landscape in an in vivo model of drug-induced pulmonary fibrosis and to showcase the linking of small-molecule co-detection with endogenous responses in lung tissue. MAGPIE highlights the refined resolution and increased interpretability of spatial multimodal analyses in studying tissue injury, particularly in pharmacological contexts, and offers a modular, accessible computational workflow for data integration.