The rice nucleotide-dependent heterotrimeric G-protein interactome
Ontology highlight
ABSTRACT: The α-subunit of the rice heterotrimeric G-protein (RGA1) was used as bait to screen for guanine nucleotide-dependent protein partners by affinity purification-mass spectrometry (AP-MS).
Project description:Protein lysine acetylation (KAC) is a dynamic and reversible post-translational modification, playing important biological roles in many organisms.Here, we reported results from a proteomic investigation to detect KAC status of the developing rice anthers near the time of meiosis (RAM), providing strong biochemical evidence for roles of many KAC-affected proteins during rice anther development and meiosis. We identified a total of 1,354 KAC sites in 676 proteins.
Project description:Homeostatic control of intracellular ionic strength is essential for protein, organelle and genome function, yet mechanisms that sense and enable adaptation to ionic stress remain poorly understood in animals. We find that the transcription factor NFAT5 directly senses solution ionic strength using a C-terminal intrinsically disordered region. Both in intact cells and in a purified system, NFAT5 forms dynamic, reversible biomolecular condensates in response to increasing ionic strength. This self-associative property, conserved from insects to mammals, allows NFAT5 to accumulate in the nucleus and activate genes that restore cellular ion content. Mutations that reduce condensation or those that promote aggregation both reduce NFAT5 activity, highlighting the importance of optimally tuned associative interactions. To investigate the composition of NFAT5 condensates in response to hypertonic stress, proteins in close proximity of NFAT5 were identified using a variant of NFAT5 fused to TurboID as bait. Hypertonic stress increases NFAT5 proximity to protein complexes belonging to the GO gene sets of “transcription coactivator activity” and “positive regulation of DNA templated transcription initiation.” Closer inspection revealed that the association between NFAT5 and two transcriptional co-activators (the mediator complex and BRD4) and RNAPII itself increased in response to hypertonic stress.
Project description:Heterotrimeric guanine nucleotide-binding proteins (G proteins) transmit extracellular signals from cell surface G protein-coupled receptors to intracellular effector molecules. Of the G proteins, Gα12 has attracted particular interest as the gep oncogene in cancer research because it promotes the growth and oncogenic transformation of fibroblasts and is invoked in tumorigenesis. In our findings, Gα12 expression was higher in HCC than surrounding non-tumorous tissue. Results provide information on the role of Gα12 in HCC progression. cDNA microarrays analyses using liver samples obtained from WT and Gα12-knockout mice enabled us to extract the predominant processes affected by a deficiency of Gα12, which include cellular response to stress, cell proliferation, actin cytoskeleton organization, and cellular component biogenesis.
Project description:DNA methylation profiles of primary human leukocyte subsets. Complementary MeDIP-seq data for the same samples have been deposited in ArrayExpress under accession number E-ERAD-179 (https://www.ebi.ac.uk/arrayexpress/experiments/E-ERAD-179/) .
Project description:We present a meta-dataset comprising of a total of 178 samples including both primary tumors and tumor-free pancreatic tissues from four independent GEO datasets. To minimise inter-platform variation, only datasets generated from the GPL570 platform (Affymetrix Human Genome U133 Plus 2.0 Array) were processed to develop the meta-dataset. Using multiple open source R packages implemented in our previously developed bioinformatics pipeline, each dataset has been preprocessed with RMA normalisation, merged, and batch effect-corrected via Combat method. With increased sample size, the present meta-dataset serves an excellent 'discovery cohort' for discovering differentially expressed in diseased phenotype.
Project description:We present a meta-dataset comprising of a total of 212 samples including both primary tumors and tumor-free bladder tissues from four independent GEO datasets. To minimise inter-platform variation, only datasets generated from the GPL570 platform (Affymetrix Human Genome U133 Plus 2.0 Array) were processed to develop the meta-dataset. Using multiple open source R packages implemented in our previously developed bioinformatics pipeline, each dataset has been preprocessed with RMA normalisation, merged, and batch effect-corrected via Combat method. With increased sample size, the present meta-dataset serves an excellent 'discovery cohort' for discovering differentially expressed in diseased phenotype.
Project description:We present a meta-dataset comprising of a total of 214 samples including both primary tumors and tumor-free melanoma tissues from four independent GEO datasets. To minimise inter-platform variation, only datasets generated from the GPL570 platform (Affymetrix Human Genome U133 Plus 2.0 Array) were processed to develop the meta-dataset. Using multiple open source R packages implemented in our previously developed bioinformatics pipeline, each dataset has been preprocessed with RMA normalisation, merged, and batch effect-corrected via Combat method. With increased sample size, the present meta-dataset serves an excellent 'discovery cohort' for discovering differentially expressed in diseased phenotype.
Project description:We present a meta-dataset comprising of a total of 347 samples including both primary tumors and tumor-free renal tissues from six independent GEO datasets. To minimise inter-platform variation, only datasets generated from the GPL570 platform (Affymetrix Human Genome U133 Plus 2.0 Array) were processed to develop the meta-dataset. Using multiple open source R packages implemented in our previously developed bioinformatics pipeline, each dataset has been preprocessed with RMA normalisation, merged, and batch effect-corrected via Combat method. With increased sample size, the present meta-dataset serves an excellent 'discovery cohort' for discovering differentially expressed in diseased phenotype.
Project description:We present a meta-dataset comprising of a total of 237 samples including both primary tumors and tumor-free prostate tissues from six independent GEO datasets. To minimise inter-platform variation, only datasets generated from the GPL570 platform (Affymetrix Human Genome U133 Plus 2.0 Array) were processed to develop the meta-dataset. Using multiple open source R packages implemented in our previously developed bioinformatics pipeline, each dataset has been preprocessed with RMA normalisation, merged, and batch effect-corrected via Combat method. With increased sample size, the present meta-dataset serves an excellent 'discovery cohort' for discovering differentially expressed in diseased phenotype.
Project description:We present a meta-dataset comprising of a total of 737 samples including both primary tumors and tumor-free gastric tissues from seven independent GEO datasets. To minimise inter-platform variation, only datasets generated from the GPL570 platform (Affymetrix Human Genome U133 Plus 2.0 Array) were processed to develop the meta-dataset. Using multiple open source R packages implemented in our previously developed bioinformatics pipeline, each dataset has been preprocessed with RMA normalisation, merged, and batch effect-corrected via Combat method. With increased sample size, the present meta-dataset serves an excellent 'discovery cohort' for discovering differentially expressed in diseased phenotype.