Project description:RAW-Rv3722c and RAW-Vector cells were collected for RNA extraction and subject to transcriptome sequencing. Expression levels of all genes in the two cell lines were determined by Next Generation Sequencing (NGS)
Project description:Substantial evidence is now beginning to emerge that miRNAs, short, non-coding RNAs, which post-transcriptionally regulate gene expression, play a key role in the regulation of innate and adaptive immunity in humans and mice. Little is currently known, however, regarding the importance miRNAs in regulating the host response to infection in agriculturally important animals, such as cattle. Mastitis is an inflammatory disease of the mammary gland caused either by infection or physical damage, which is associated with substantial economic losses. In this study, we report a next generation sequencing approach to profile the expression of bovine miRNAs in primary bovine mammary epithelial (BMEs) cells challenged with a bovine mastitis pathogen, Streptococcus uberis (0140J). Computational analysis has been undertaken on 450 million raw sequence reads and revealed that 20% of known bovine miRNAs are expressed in BMEs. Furthermore, 22 miRNAs were found to be differentially expressed over the 6 hour time-course. We have completed miRNA target prediction analysis and found that the target genes of down-regulated miRNAs are enriched for having a role in innate immunity, and pathways associated with target genes of up-regulated miRNA correspond to previously reported mastitis-relevant pathways. In addition, we report 21 potentially novel bovine miRNAs that have not previously been described, two of which have close human orthologs. This study provides new insight into the regulation of miRNAs in the host response to infection at an unprecedented level in any species. 24 miRNAseq libraries were prepared from 3 infected and 3 control replicates at 1, 2, 4 and 6 hours.
Project description:Substantial evidence is now beginning to emerge that miRNAs, short, non-coding RNAs, which post-transcriptionally regulate gene expression, play a key role in the regulation of innate and adaptive immunity in humans and mice. Little is currently known, however, regarding the importance miRNAs in regulating the host response to infection in agriculturally important animals, such as cattle. Mastitis is an inflammatory disease of the mammary gland caused either by infection or physical damage, which is associated with substantial economic losses. In this study, we report a next generation sequencing approach to profile the expression of bovine miRNAs in primary bovine mammary epithelial (BMEs) cells challenged with a bovine mastitis pathogen, Streptococcus uberis (0140J). Computational analysis has been undertaken on 450 million raw sequence reads and revealed that 20% of known bovine miRNAs are expressed in BMEs. Furthermore, 22 miRNAs were found to be differentially expressed over the 6 hour time-course. We have completed miRNA target prediction analysis and found that the target genes of down-regulated miRNAs are enriched for having a role in innate immunity, and pathways associated with target genes of up-regulated miRNA correspond to previously reported mastitis-relevant pathways. In addition, we report 21 potentially novel bovine miRNAs that have not previously been described, two of which have close human orthologs. This study provides new insight into the regulation of miRNAs in the host response to infection at an unprecedented level in any species.
Project description:Next Generation Sequencing in cancer: a feasibility study in France to assess sample circuit and to perform analyzes within a limited time.
Project description:Mass spectrometry raw data for submitting manuscript entitled "Directed natural evolution generates a next-generation oncolytic virus with a high potency and safety profile for multiple solid tumors" to Nature Communications.
Project description:Purpose: Next-generation sequencing (NGS) provides for quantitation of RNA abundances and comparison of RNA abundances within tissues and cells in a manner not possible with previous microarray technologies. We have made widespread use of Illumina sequencing technologies for RNA quantitation in several publications involving mouse hearts, dating from 2010, and wish to share both high-quality raw sequencing data and data processed to quantitate mRNA abundances from wild-type mice, male and female, at a variety of ages. These data will provide a resource for investigators using microarrays to understand the concentration of transcripts of interest relative to other cardiac RNAs, and will permit deeper interpretation of previous microarray studies.
Project description:Purpose: Next-generation sequencing (NGS) provides for quantitation of RNA abundances and comparison of RNA abundances within tissues and cells in a manner not possible with previous microarray technologies. We have made widespread use of Illumina sequencing technologies for RNA quantitation in several publications involving mouse hearts, dating from 2010, and wish to share both high-quality raw sequencing data and data processed to quantitate mRNA abundances from wild-type mice, male and female, at a variety of ages. These data will provide a resource for investigators using microarrays to understand the concentration of transcripts of interest relative to other cardiac RNAs, and will permit deeper interpretation of previous microarray studies.
2014-03-12 | GSE55789 | GEO
Project description:Sweden next generation sequencing data
Project description:The objective of this study is to optimize the search by next-generation sequencing (NGS) mutations in the KRAS, BRAF and NRAS on circulating tumor DNA and compare the genetic profiles obtained with those from tumors embedded in paraffin
Project description:Development of an alternative method to ChIP for the identification of DNA bound by transcriptional complexes assayed using next-generation sequencing Next-generation sequencing data from sites identified by different Notch complexes using SpDamID-seq and compared against FAIRE and ChIP data