Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR18368962_1.fastq.gz | Fastqsanger.gz | |||
| SRR18368962_2.fastq.gz | Fastqsanger.gz | |||
| SRR18368963_1.fastq.gz | Fastqsanger.gz | |||
| SRR18368963_2.fastq.gz | Fastqsanger.gz | |||
| SRR18368964_1.fastq.gz | Fastqsanger.gz |
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Project description:The primary objective of this prospective observational study is to characterize the gut and oral microbiome as well as the whole blood transcriptome in gastrointestinal cancer patients and correlate these findings with cancer type, treatment efficacy and toxicity. Participants will be recruited from existing clinical sites only, no additional clinical sites are needed.
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Project description:The intestinal epithelium is replaced weekly by non-quiescent stem cells with kinetics that rely on a rapid loss of stemness and choice for secretory or absorptive lineage differentiation. To determine how the cellular transcriptome and proteome changes during these transitions, we developed a new cell sorting method to purify stem cells, secretory and absorptive progenitor cells, and mature, differentiated cells. Transcriptome analyses revealed that as stem cells transition to the progenitor stage, alternative mRNA splicing and polyadenylation dominate changes in the transcriptome. In contrast, as progenitors differentiate into mature cell types, alterations in gene expression and mRNA levels drive the changes. RNA processing targets mRNAs encoding regulators of cell cycle, RNA regulators, cell adhesion, SUMOylation, and Wnt and Notch signaling. Additionally, carrier-assisted mass spectrometry of sorted cell populations detected >2,800 proteins and revealed RNA:protein patterns of abundance and correlation. Paired together, these data highlight new potentials for autocrine and feedback regulation and provide new insights into cell state transitions in the crypt.
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Project description:New tools for cell signaling pathway inference from multi-omics data that are independent of previous knowledge are needed. Here we propose a new de novo method, the de novo multi-omics pathway analysis (DMPA), to model and combine omics data into network modules and pathways. DMPA was validated with published omics data and was found accurate in discovering published molecular associations in transcriptome, interactome, phosphoproteome, methylome, and metabolomics data and signaling pathways in multi-omics data. DMPA was benchmarked against module discovery and multi-omics integration methods and outperformed previous methods in module and pathway discovery especially when applied to datasets with low sample sizes. Transcription factor, kinase, subcellular location and function prediction algorithms were devised for transcriptome, phosphoproteome and interactome regulatory complexes and pathways, respectively. To apply DMPA in a biologically relevant context, interactome, phosphoproteome, transcriptome and proteome data were collected from analyses carried out using melanoma cells to address gamma-secretase cleavage-dependent signaling characteristics of the receptor tyrosine kinase TYRO3. The pathways modeled with DMPA reflected the predicted function and its direction in validation experiments.
2024-02-21 | PXD046503 | Pride
Project description:This study intends to explore the clinicopathological characteristics and survival prognosis of locally recurrent colorectal cancer patients with different treatment modes by retrospectively analyzing the medical records of locally recurrent colorectal cancer patients who received hospitalization in our center. Transcriptome sequencing and public databases were used to screen for molecular markers related to locally recurrent colorectal cancer and to explore molecular markers’ regulatory role in the progression of locally recurrent colorectal cancer.
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Project description:Here we report the generation of a data-independent acquisition (DIA) assay library that enables simultaneous targeted proteomics of 1900 O. niloticus gill proteins using a label- and gel-free workflow that is well suited for ecologically relevant field samples. By determining alignment and mismatch between protein and mRNA regulation, the DIA assay library approach generates data that are complimentary rather than redundant to transcriptomics data. Transcript and protein abundance differences in gills of tilapia acclimated to freshwater and brackish water (25 g/kg) revealed non-linearity in salinity-dependent transcriptome versus proteome regulation. Non-linearity was more evident for specific functional groups of genes while other molecular functions/ cellular processes where more highly correlated regarding mRNA and protein regulation. Our study identifies specific salinity-dependent O. niloticus gill functions and processes that rely heavily on mRNA abundance regulation and others that rely more heavily on regulatory mechanisms beyond the transcriptome level. The DIA assay library approach presented here is shown to be a powerful means of complementing transcriptome data with corresponding quantitative proteome data to better discern mechanisms of regulation along the genome to phenome continuum.
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