Project description:We analyzed transcriptomic data from infected and uninfected T-cells to identify pseudogenes and their parent genes showing differential expression in HIV-1 infection H9 T-cell line was infected with NL4-3 strain of HIV-1 obtained by transfection of 293T cells. RNA from infected and uninfected cells was extracted 7 days post infection.
Project description:Identifying the differentially expressed miRNAs in Cervical cancer patients infected with only one virus i.e. either HIV or HPV-16 and patients infected with both viruses HIV and HPV-16 with respect to their controls which is the healthy population not infected by either HIV or any HPV The miRNA array was performed using the affymetrix GeneChip® miRNA 3.0 Array (Affymetrix, Santa Clara, California, United States). The chip was processed using a commercial Affymetrix array service (GeneTech Biotechnology Limited Company, Shanghai, China). The affymetrix GeneChip® miRNA 3.0 Array contains 2,999 probe sets unique to human, mouse and rat pre-miRNA hairpin sequences, 2,216 human snoRNA and scaRNA probe sets and covers 153 organisms (19,724 probe sets). Raw data sets were extracted from all Cel files (raw intensity file) after scanning of slides. These raw data sets were separately analyzed using Expression Console and GeneSpring GX12.5 software followed by differential miRNA expression, fold change & cluster analysis.
Project description:Purpose: To ensure that ABX464 acted specifically on HIV splicing and did not significantly or globally affect the splicing events of human genes, we used an assembly approach of HIV (YU2 strain) putative transcripts and human long non-coding sequences from paired-reads (2x75bp) captured on a NimbleGen SeqCap® EZ Developer Library (Roche/NimbleGen). Methods: Cells were infected with 80 ng of p24/106 cells of the YU-2 strain for 4 to 6 hours and then rinsed with PBS before medium renewal, followed by high-throughput RNAseq from custom SeqCap EZ capture libraries. Each raw dataset of the samples contained between 5 and 30 million paired-end reads (75 bp), with an average of approximately 12 million raw reads per sample. Results: The raw reads were then cleaned and assembled per library to generate contigs, giving an average of 930 contigs per sample for further analyses. Conclusions: Our results show that high-throughput analyses coupled with bioinformatics-specific tools offers a comprehensive and more accurate view of mRNA splicing within a cell.
Project description:We report deep mutational scanning data for the Env protein's LLP-2 domain in the NL4-3 strain HIV-1 Env. Processed Data repersents counts for each amino acid pre and post spread
