Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to analysis the differiational genes and pathways in CON and PMB treatment cells by using RNA-seq Methods: CON and PMB treatment cells mRNA profiles were generated by deep sequencing, using Illumina Novaseq. The sequence reads that passed quality filters were analyzed at the transcript isoform level with following methods: Alignment by using HISAT2 , IGV was used to to view the mapping result by the Heatmap, histogram, scatter plot or other stytle, FPKM was then calculated to estimate the expression level of genes in each sample, EdgeR software was used for differential gene expression analysis and Function Enrichment Analysis including GO enrichment analysis and KEGG . Conclusions: Our study represents detailed analysis of CON and PMB cells transcriptomes, with biologic replicates, generated by RNA-seq technology. The optimized data analysis workflows reported here should provide a framework for comparative investigations of expression profiles. Our results show that NGS offers a comprehensive and more accurate quantitative and qualitative evaluation of mRNA content within a cell or tissue. We conclude that RNA-seq based transcriptome characterization would expedite genetic network analyses and permit the dissection of complex biologic functions.
Project description:Congenital obstructive nephropathy (CON) is the leading cause of chronic kidney disease (CKD) in children. CON is a complex disease process involving pathological changes in kidney development and function that occur as a result of obstructed antegrade urine flow beginning in utero. The megabladder (mgb-/-) mouse is an animal model of CON that develops kidney disease secondary to a bladder-specific defect in smooth muscle development. Expression levels of specific microRNAs were compared by microarray analysis on the Agilent platform and by quantitative PCR (qPCR) of kidney samples from wild type and mgb-/- mice.
Project description:Compared the global gene expression profiles of HD- and CON-iPSC-derived neurons We used microarrays to detail the global programme of gene expression for comparing the global gene expression profiles of HD- and CON-iPSC-derived neurons and facilitating studies of medium spiny neurons (MSN)-degenerative processes of Huntington's Disease (HD).
Project description:Purpose: The goals of this study are to find the mechanisms of mesenchymal stem cells (MSC) ameliorating concanavalin A (Con A) induced inflammatory mice Methods: Liver tissues were harvested at 6h, 12h after Con A injected with/without MSC (n = 3 per group) for transcriptome profiling. Results: Filter the raw data obtained fromDNBSEQ-G400, and compare the filtered clean reads to the reference sequence. Quantitative analysis of known genes and new genes, differential expression analysis based on gene expression in different sample groups, GO function analysis, Pathway function analysis, cluster analysis, and protein interaction for the selected differentially expressed genes Network, transcription factor coding ability prediction and other in-depth mining analysis. Conclusions: Our study discoveres following processes were significantly affected: apoptosis, MAPK signaling pathway and cytokine-cytokine receptor interaction.
Project description:This study includes raw data of testis RNA-seq profiles from treated (nABX & LPHS, with nABX: non-absorbable antibiotics LPHS: low-protein, high sugar diet) and control (CON) males of young (10-11 weeks) FVB background. Sequencing was done using 40bp paired-end reads on a NextSeq500 sequencer, obtaining an average of 25 million reads per sample.
Project description:This study includes raw data of testis RNA-seq profiles from treated (nABX & LPHS, with nABX: non-absorbable antibiotics and LPHS: low-protein, high sugar diet) and control (CON) males of mature (57-62 weeks) and young (9-11 weeks) FVB & C57BL/6J backgrounds. Sequencing was done using 40bp paired-end reads on a NextSeq500 sequencer, obtaining an average of 25 million reads per sample.
