Project description:To unravel the fine architecture of neocentromeres found in three well-differentiated liposarcoma (WDLPS) cell lines as patchworks of multiple short amplified sequences, disclosing a much more higher complexity than previously reported. Next generation sequencing data (WGS, RNA-seq, CENP-A/ChIP-seq) are available at the Sequence Read Archive (BioProject ID: PRJNA378952).
Project description:MicroRNAs (miRNAs) post-transcriptionally regulate gene expression by inhibiting protein synthesis of target messenger RNAs (mRNAs). MicroRNA-142 (miR-142), which has tumor-suppressive properties, was functionally deleted by CRISPR/Cas9 knockout in cell lines derived from diffuse large B-cell lymphoma (DLBCL), a highly aggressive tumor that represents about 30% of non-Hodgkin lymphoma worldwide. Mutations in miR-142 affect about 20% of all cases of DLBCL. By proteome analyses, the miR-142 knockout resulted in a consistent up-regulation of 52 but also down-regulation of 41 proteins in the GC-DLBCL lines BJAB and SUDHL4. Various mitochondrial ribosomal proteins were up-regulated in line with their pro-tumorigenic properties, while proteins necessary for MHC-I presentation were down-regulated in accordance with the finding that miR-142 knockout mice have a defective immune response. Of the deregulated proteins/genes, CFL2, CLIC4, STAU1, and TWF1 are known targets of miR-142, and we could additionally confirm AKT1S1, CCNB1, LIMA1, and TFRC as new targets of miR-142-3p or -5p. We further show that seed-sequence mutations of miR-142 can be used to confirm potential targets and that miRNA knockout cell lines might thus be used to identify novel targets of miRNAs. Due to the complex contribution of miRNAs within cellular regulatory networks, in particular when a miRNA highly present in the RISC complex is deleted and can be replaced by other endogenous miRNAs, primary effects on gene expression may be covered by secondary layers of regulation
Project description:Whole genome sequencing (WGS) of tongue cancer samples and cell line was performed to identify the fusion gene translocation breakpoint. WGS raw data was aligned to human reference genome (GRCh38.p12) using BWA-MEM (v0.7.17). The BAM files generated were further analysed using SvABA (v1.1.3) tool to identify translocation breakpoints. The translocation breakpoints were annotated using custom scripts, using the reference GENCODE GTF (v30). The fusion breakpoints identified in the SvABA analysis were additionally confirmed using MANTA tool (v1.6.0).
Project description:The miR-17-92 microRNA cluster is often activated in cancer cells, but the identity of its targets remains largely elusive. Here we examined the effects of activation of the entire miR-17-92 cluster on global protein expression in neuroblastoma cells. In this dataset we deposit global mRNA expression data obtained form primary neuroblastoma tumour cells. This data was used to demonstrate negative correlation between TGFB target gene expression and expression of the miR-17-92 cluster.
Project description:Recombinant inbred lines were created by crossing the alpha-synuclein containing Caenorhabditis elegans strains NL5901 and SCH4856. These strains contain the human alpha-synuclein gene fused to YFP and under the control of an unc-54 promotor (unc-54p::alpha-synnuclein::YFP) in an N2 and CB4856 genetic background, respectively. These two strains were used to generate a total of 212 recombinant inbred lines, of which 88 were genotyped by whole-genome sequencing using a MiSeq. These recombinant inbred lines can be used for mapping genetic modifiers affecting protein accumulation.
Project description:A large panel of 81 liver cancer cell models, designated as LIver cancer MOdel REpository (LIMORE) was constructed. These cell lines include 31 public cell lines and 50 new cell models establishend from Chinese liver cancer patients. Whole genome sequencing (WGS), exome sequencing (WES) and RNA sequencing (RNAseq) were performed to obtain the genetic information for these cell lines. These cell lines and associated data provide new models and also a rich resource for liver cancer.