Browse
Submit Data
Databases
API
Help

Dataset Information

28 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Large-scale proteomic analysis of the human spliceosome.

ABSTRACT: In a previous proteomic study of the human spliceosome, we identified 42 spliceosome-associated factors, including 19 novel ones. Using enhanced mass spectrometric tools and improved databases, we now report identification of 311 proteins that copurify with splicing complexes assembled on two separate pre-mRNAs. All known essential human splicing factors were found, and 96 novel proteins were identified, of which 55 contain domains directly linking them to functions in splicing/RNA processing. We also detected 20 proteins related to transcription, which indicates a direct connection between this process and splicing. This investigation provides the most detailed inventory of human spliceosome-associated factors to date, and the data indicate a number of interesting links coordinating splicing with other steps in the gene expression pathway.

SUBMITTER: Rappsilber J

PROVIDER: S-EPMC186633 | biostudies-literature | 2002 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Large-scale proteomic analysis of the human spliceosome.

Rappsilber Juri J Ryder Ursula U Lamond Angus I AI Mann Matthias M

Genome research 20020801 8

In a previous proteomic study of the human spliceosome, we identified 42 spliceosome-associated factors, including 19 novel ones. Using enhanced mass spectrometric tools and improved databases, we now report identification of 311 proteins that copurify with splicing complexes assembled on two separate pre-mRNAs. All known essential human splicing factors were found, and 96 novel proteins were identified, of which 55 contain domains directly linking them to functions in splicing/RNA processing. W ...[more]

PMID: 12176931

Similar Datasets

A large-scale proteomic analysis of human embryonic stem cells.

Project description:BackgroundMuch of our current knowledge of the molecular expression profile of human embryonic stem cells (hESCs) is based on transcriptional approaches. These analyses are only partly predictive of protein expression however, and do not shed light on post-translational regulation, leaving a large gap in our knowledge of the biology of pluripotent stem cells.ResultsHere we describe the use of two large-scale western blot assays to identify over 600 proteins expressed in undifferentiated hESCs, and highlight over 40 examples of multiple gel mobility variants, which are suspected protein isoforms and/or post-translational modifications. Twenty-two phosphorylation events in cell signaling molecules, as well as potential new markers of undifferentiated hESCs were also identified. We confirmed the expression of a subset of the identified proteins by immunofluorescence and correlated the expression of transcript and protein for key molecules in active signaling pathways in hESCs. These analyses also indicated that hESCs exhibit several features of polarized epithelia, including expression of tight junction proteins.ConclusionOur approach complements proteomic and transcriptional analysis to provide unique information on human pluripotent stem cells, and is a framework for the continued analyses of self-renewal.

| S-EPMC2211323 | biostudies-literature

Large-scale and high-confidence proteomic analysis of human seminal plasma.

Project description:BACKGROUND: The development of mass spectrometric (MS) techniques now allows the investigation of very complex protein mixtures ranging from subcellular structures to tissues. Body fluids are also popular targets of proteomic analysis because of their potential for biomarker discovery. Seminal plasma has not yet received much attention from the proteomics community but its characterization could provide a future reference for virtually all studies involving human sperm. The fluid is essential for the survival of spermatozoa and their successful journey through the female reproductive tract. RESULTS: Here we report the high-confidence identification of 923 proteins in seminal fluid from a single individual. Fourier transform MS enabled parts per million mass accuracy, and two consecutive stages of MS fragmentation allowed confident identification of proteins even by single peptides. Analysis with GoMiner annotated two-thirds of the seminal fluid proteome and revealed a large number of extracellular proteins including many proteases. Other proteins originated from male accessory glands and have important roles in spermatozoan survival. CONCLUSION: This high-confidence characterization of seminal plasma content provides an inventory of proteins with potential roles in fertilization. When combined with quantitative proteomics methodologies, it should be useful for studies of fertilization, male infertility, and prostatic and testicular cancers.

| S-EPMC1779515 | biostudies-literature

Tag-Count Analysis of Large-Scale Proteomic Data.

Project description:Label-free quantitative methods are advantageous in bottom-up (shotgun) proteomics because they are robust and can easily be applied to different workflows without additional cost. Both label-based and label-free approaches are routinely applied to discovery-based proteomics experiments and are widely accepted as semiquantitative. Label-free quantitation approaches are segregated into two distinct approaches: peak-abundance-based approaches and spectral counting (SpC). Peak abundance approaches like MaxLFQ, which is integrated into the MaxQuant environment, require precursor peak alignment that is computationally intensive and cannot be routinely applied to low-resolution data. Not limited by these constraints, SpC approaches simply use the number of peptide identifications corresponding to a given protein as a measurement of protein abundance. We show here that spectral counts from multidimensional proteomic data sets have a mean-dispersion relationship that can be modeled in edgeR. Furthermore, by simulating spectral counts, we show that this approach can routinely be applied to large-scale discovery proteomics data sets to determine differential protein expression.

| S-EPMC6980212 | biostudies-literature

Large-scale proteomic analysis of human brain identifies proteins associated with cognitive trajectory in advanced age.

Project description:In advanced age, some individuals maintain a stable cognitive trajectory while others experience a rapid decline. Such variation in cognitive trajectory is only partially explained by traditional neurodegenerative pathologies. Hence, to identify new processes underlying variation in cognitive trajectory, we perform an unbiased proteome-wide association study of cognitive trajectory in a discovery (n = 104) and replication cohort (n = 39) of initially cognitively unimpaired, longitudinally assessed older-adult brain donors. We find 579 proteins associated with cognitive trajectory after meta-analysis. Notably, we present evidence for increased neuronal mitochondrial activities in cognitive stability regardless of the burden of traditional neuropathologies. Furthermore, we provide additional evidence for increased synaptic abundance and decreased inflammation and apoptosis in cognitive stability. Importantly, we nominate proteins associated with cognitive trajectory, particularly the 38 proteins that act independently of neuropathologies and are also hub proteins of protein co-expression networks, as promising targets for future mechanistic studies of cognitive trajectory.

| S-EPMC6453881 | biostudies-literature

Semiquantitative proteomic analysis of the human spliceosome via a novel two-dimensional gel electrophoresis method.

Project description:More than 200 proteins associate with human spliceosomes, but little is known about their relative abundances in a given spliceosomal complex. Here we describe a novel two-dimensional (2D) electrophoresis method that allows separation of high-molecular-mass proteins without in-gel precipitation and thus without loss of protein. Using this system coupled with mass spectrometry, we identified 171 proteins altogether on 2D maps of stage-specific spliceosomal complexes. By staining with a fluorescent dye with a wide linear intensity range, we could quantitate and categorize proteins as present in high, moderate, or low abundance. Affinity-purified human B, B(act), and C complexes contained 69, 63, and 72 highly/moderately abundant proteins, respectively. The recruitment and release of spliceosomal proteins were followed based on their abundances in A, B, B(act), and C spliceosomal complexes. Staining with a phospho-specific dye revealed that approximately one-third of the proteins detected in human spliceosomal complexes by 2D gel analyses are phosphorylated. The 2D gel electrophoresis system described here allows for the first time an objective view of the relative abundances of proteins present in a particular spliceosomal complex and also sheds additional light on the spliceosome's compositional dynamics and the phosphorylation status of spliceosomal proteins at specific stages of splicing.

| S-EPMC3133382 | biostudies-literature

Large-scale analysis of the human transcriptome

Project description:High-throughput gene expression profiling has become an important tool for investigating transcriptional activity in a variety of biological samples. To date, the vast majority of these experiments have focused on specific biological processes and perturbations. Here, we have generated and analyzed gene expression from a set of samples spanning a broad range of biological conditions. Specifically, we profiled gene expression from 91 human and mouse samples across a diverse array of tissues, organs, and cell lines. Because these samples predominantly come from the normal physiological state in the human and mouse, this dataset represents a preliminary, but substantial, description of the normal mammalian transcriptome. We have used this dataset to illustrate methods of mining these data, and to reveal insights into molecular and physiological gene function, mechanisms of transcriptional regulation, disease etiology, and comparative genomics. Finally, to allow the scientific community to use this resource, we have built a free and publicly accessible website (http://expression.gnf.org) that integrates data visualization and curation of current gene annotations. Keywords: other

2002-12-06 | GSE96 | GEO

Large scale proteomic studies create novel privacy considerations.

Project description:Privacy protection is a core principle of genomic but not proteomic research. We identified independent single nucleotide polymorphism (SNP) quantitative trait loci (pQTL) from COPDGene and Jackson Heart Study (JHS), calculated continuous protein level genotype probabilities, and then applied a naïve Bayesian approach to link SomaScan 1.3K proteomes to genomes for 2812 independent subjects from COPDGene, JHS, SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS) and Multi-Ethnic Study of Atherosclerosis (MESA). We correctly linked 90-95% of proteomes to their correct genome and for 95-99% we identify the 1% most likely links. The linking accuracy in subjects with African ancestry was lower (~ 60%) unless training included diverse subjects. With larger profiling (SomaScan 5K) in the Atherosclerosis Risk Communities (ARIC) correct identification was > 99% even in mixed ancestry populations. We also linked proteomes-to-proteomes and used the proteome only to determine features such as sex, ancestry, and first-degree relatives. When serial proteomes are available, the linking algorithm can be used to identify and correct mislabeled samples. This work also demonstrates the importance of including diverse populations in omics research and that large proteomic datasets (> 1000 proteins) can be accurately linked to a specific genome through pQTL knowledge and should not be considered unidentifiable.

| S-EPMC10247808 | biostudies-literature

Molecular signatures of normal pressure hydrocephalus: a large-scale proteomic analysis of cerebrospinal fluid.

Project description:Given the persistent challenge of differentiating idiopathic Normal Pressure Hydrocephalus (iNPH) from similar clinical entities, we conducted an in-depth proteomic study of cerebrospinal fluid (CSF) in 28 shunt-responsive iNPH patients, 38 Mild Cognitive Impairment (MCI) due to Alzheimer's disease, and 49 healthy controls. Utilizing the Olink Explore 3072 panel, we identified distinct proteomic profiles in iNPH that highlight significant downregulation of synaptic markers and cell-cell adhesion proteins. Alongside vimentin and inflammatory markers upregulation, these results suggest ependymal layer and transependymal flow dysfunction. Moreover, downregulation of multiple proteins associated with congenital hydrocephalus (e.g., L1CAM, PCDH9, ISLR2, ADAMTSL2, and B4GAT1) points to a possible shared molecular foundation between congenital hydrocephalus and iNPH. Through orthogonal partial least squares discriminant analysis (OPLS-DA), a panel comprising 13 proteins has been identified as potential diagnostic biomarkers of iNPH, pending external validation. These findings offer novel insights into the pathophysiology of iNPH, with implications for improved diagnosis.

| S-EPMC11312837 | biostudies-literature

Large-scale analysis of network bistability for human cancers.

Project description:Protein-protein interaction and gene regulatory networks are likely to be locked in a state corresponding to a disease by the behavior of one or more bistable circuits exhibiting switch-like behavior. Sets of genes could be over-expressed or repressed when anomalies due to disease appear, and the circuits responsible for this over- or under-expression might persist for as long as the disease state continues. This paper shows how a large-scale analysis of network bistability for various human cancers can identify genes that can potentially serve as drug targets or diagnosis biomarkers.

| S-EPMC2900289 | biostudies-literature

Large-scale analysis of the human and mouse transcriptomes.

| S-EPMC123671 | biostudies-literature