Project description:We used PacBio data to identify more reliable transcripts from hESC, based on which we can estimate gene/transcript abundance better from Illumina data. PacBio long reads and Illumina short reads were generated from the same hESC cell line H1. PacBio reads were error-corrected by Illumina reads to identify transcripts. rSeq is used to estimate gene/transcript abundance of the identified transcriptome.
Project description:Genome-wide transcriptome analyses have allowed for systems- level insights into gene regulatory networks. Due to the limited depth of quantitative proteomics, however, our understanding of post-transcriptional gene regulation and its effects on protein complex stoichiometry are lagging behind. Here, we employ deep sequencing and iTRAQ technology to determine transcript and protein expression changes of a Drosophila brain tumour model at near genome-wide resolution. In total, we quantify more than 6,200 tissue-specific proteins, corresponding to about 70% of all transcribed protein-coding genes. Using our integrated data set, we demonstrate that post-transcriptional gene regulation varies considerably with biological function and is surprisingly high for genes regulating transcription. We combine our quantitative data with protein-protein interaction data and show that post-transcriptional mechanisms significantly enhance co-regulation of protein complex subunits beyond transcriptional co-regulation. Interestingly, our results suggest that only about 11% of the annotated Drosophila protein complexes are co-regulated in the brain. Finally, we refine the composition of some of these core protein complexes by analysing the co-regulation of potential subunits. Our comprehensive transcriptome and proteome data provide a rich resource for quantitative biology and offer novel insights into understanding post- transcriptional gene regulation in a tumour model. Transcriptomes of 1-3 day old adult female Drosophila melanogaster heads of control and brat mutant were generated by deep sequencing, in triplicate, using Illumina GAIIx.
Project description:Analysis of transcriptome in a strand-specific manner to further refine previous genome annotation; RNA-seq was also combined with microarray and proteome analysis to further define the S. Typhi ompR regulon and identify novel ompR regulated transcripts.
Project description:Pioneering studies (PXD014844) have identified many interesting molecules in tick saliva by LC-MS/MS proteomics, but the protein databases used to assign mass spectra were based on short Illumina reads of the Amblyomma americanum transcriptome and may not have captured the diversity and complexity of longer transcripts. Here we apply long-read Pacific Bioscience technologies to complement the previously reported short-read Illumina transcriptome-based proteome in an effort to increase spectrum assignments. Our dataset reveals a small increase in assignable spectra to supplement the previously released short-read transcriptome-based proteome.
Project description:Pioneering studies (PXD014844) have identified many interesting molecules by LC-MS/MS proteomics, but the protein databases used to assign mass spectra were based on short Illumina reads of the Amblyomma americanum transcriptome and may not have captured the diversity and complexity of longer transcripts. Here we apply long-read Pacific Bioscience technologies to complement the previously reported short-read Illumina transcriptome-based proteome in an effort to increase spectrum assignments. Our dataset reveals a small increase in assignable spectra to supplement previously released short-read transcriptome-based proteome.
Project description:Genome-wide transcriptome analyses have allowed for systems- level insights into gene regulatory networks. Due to the limited depth of quantitative proteomics, however, our understanding of post-transcriptional gene regulation and its effects on protein complex stoichiometry are lagging behind. Here, we employ deep sequencing and iTRAQ technology to determine transcript and protein expression changes of a Drosophila brain tumour model at near genome-wide resolution. In total, we quantify more than 6,200 tissue-specific proteins, corresponding to about 70% of all transcribed protein-coding genes. Using our integrated data set, we demonstrate that post-transcriptional gene regulation varies considerably with biological function and is surprisingly high for genes regulating transcription. We combine our quantitative data with protein-protein interaction data and show that post-transcriptional mechanisms significantly enhance co-regulation of protein complex subunits beyond transcriptional co-regulation. Interestingly, our results suggest that only about 11% of the annotated Drosophila protein complexes are co-regulated in the brain. Finally, we refine the composition of some of these core protein complexes by analysing the co-regulation of potential subunits. Our comprehensive transcriptome and proteome data provide a rich resource for quantitative biology and offer novel insights into understanding post- transcriptional gene regulation in a tumour model.
Project description:Objectives: To perform long-read transcriptome and proteome profiling of pathogen-stimulated peripheral blood mononuclear cells (PBMCs) from healthy donors. We aim to discover new transcripts and protein isoforms expressed during immune responses to diverse pathogens. Methods: PBMCs were exposed to four microbial stimuli for 24 hours: the TLR4 ligand lipopolysaccharide (LPS), the TLR3 ligand Poly(I:C), heat-inactivated Staphylococcus aureus, Candida albicans, and RPMI medium as negative controls. Long-read sequencing (PacBio) of one donor and secretome proteomics and short-read sequencing of five donors were performed. IsoQuant was used for transcriptome construction, Metamorpheus/FlashLFQ for proteome analysis, and Illumina short-read 3’-end mRNA sequencing for transcript quantification. Results: Long-read transcriptome profiling reveals the expression of novel sequences and isoform switching induced upon pathogen stimulation, including transcripts that are difficult to detect using traditional short-read sequencing. We observe widespread loss of intron retention as a common result of all pathogen stimulations. We highlight novel transcripts of NFKB1 and CASP1 that may indicate novel immunological mechanisms. In general, RNA expression differences did not result in differences in the amounts of secreted proteins. Interindividual differences in the proteome were larger than the differences between stimulated and unstimulated PBMCs. Clustering analysis of secreted proteins revealed a correlation between chemokine (receptor) expression on the RNA and protein levels in C. albicans- and Poly(I:C)-stimulated PBMCs. Conclusion: Isoform aware long-read sequencing of pathogen-stimulated immune cells highlights the potential of these methods to identify novel transcripts, revealing a more complex transcriptome landscape than previously appreciated.
2023-09-16 | PXD045237 | Pride
Project description:Novel plastid genome characteristics in Fugacium kawagutii and accelerated evolution of plastid proteins in dinoflagellates
| PRJNA1032271 | ENA
Project description:Physiological and transcriptomic responses to N-deficiency and ammonium: nitrate shift in Fugacium kawagutii (Symbiodiniaceae)