Ontology highlight
ABSTRACT:
PROVIDER: PRJNA577972 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR10295915_1.fastq.gz | Fastqsanger.gz | |||
| SRR10295915_2.fastq.gz | Fastqsanger.gz | |||
| SRR10295916_1.fastq.gz | Fastqsanger.gz | |||
| SRR10295916_2.fastq.gz | Fastqsanger.gz | |||
| SRR10295917_1.fastq.gz | Fastqsanger.gz |
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Project description:Dendrobium officinale is a common and expensive traditional Chinese medicine used as a medicinal agent and food that has immunoregulatory and anti-inflammatory effects. Methods to authenticate D. officinale are lacking. Although chemical profiles of D. officinale were published, transcriptomic profiling is lacking. Here, we collected D. officinale from two regions (Yunnan and Miandian) and the analogue D. compactum. The Yunnan samples had three different quality levels. All samples were subjected to genome-wide biological response fingerprinting (BioReF) in RAW264.7 cells using RNA sequencing.
2024-04-07 | GSE171632 | GEO
Project description:Alfalfa, [Medicago sativa (L.) sativa], a widely-grown perennial forage has potential for development as a cellulosic ethanol feedstock. The application of genomic approaches would advance development of alfalfa as a cellulosic feedstock. However, the genomics of alfalfa, a non-model species, is still in its infancy. The recent advent of RNA-Seq, a massively parallel sequencing method for transcriptome analysis, provides an opportunity to expand the identification of alfalfa genes and polymorphisms, and conduct in-depth transcript profiling. Cell walls in stems of alfalfa genotype 708 have higher cellulose and lower lignin concentrations compared to cell walls in stems of genotype 773. Using the Illumina GA-II platform, a total of 198,861,304 expression sequence tags (ESTs, 76 bp in length) were generated from cDNA libraries derived from elongating stem (ES) and post-elongation stem (PES) internodes of 708 and 773. These ESTs were de novo assembled into 132,153 unique sequences. By combining the de novo assembled ESTs (132,153 sequences) with our previously identified EST sequences (341,984 sequences, unpublished data), and the ESTs available from GenBank (12,371 sequences), we built the first Alfalfa Gene Index (MSGI 1.0). MSGI 1.0 contains 124,025 unique sequences including 22,729 tentative consensus sequences (TCs), 22,315 singletons and 78,981 pseudo-singletons. We identified a total of 1, 294 simple sequence repeats (SSR) among the sequences in MSGI 1.0. In addition, a total of 10,826 single nucleotide polymorphisms (SNPs) were predicted between the two genotypes. Transcript profiling of stem internodes of genotypes 708 and 773 was conducted by quantifying the number of Illumina EST reads that were mapped to sequences in MSGI 1.0. We identified numerous candidate genes that may play a role in stem development as well as candidate genes that may contribute to the differences in cell wall composition in stems of the two genotypes. Our results demonstrate that RNA-Seq can be successfully used for gene identification, polymorphism detection and transcript profiling in alfalfa, a non-model, allogamous, autotetraploid species. The alfalfa gene index (MSGI 1.0) assembled in this study, and the SNPs, SSRs and candidate genes identified can be used to improve alfalfa as a cellulosic feedstock. Examination of 2 different tissue types at different developmental stages (Elongating vs. post-elongation stem internodes) in two alfalfa genotypes (708 and 773) with divergent cell wall composition in stems.
2011-04-21 | E-GEOD-26757 | biostudies-arrayexpress
Project description:Kilian2024 - Immune cell dynamics in Cue-Induced Extended Human Colitis Model
Single-cell technologies such as scRNA-seq and flow cytometry provide critical insights into immune cell behavior in inflammatory bowel disease (IBD). However, integrating these datasets into computational models for dynamic analysis remains challenging. Here, Kilian et al., (2024) developed a deterministic ODE-based model that incorporates these technologies to study immune cell population changes in murine colitis. The model parameters were optimized to fit experimental data, ensuring an accurate representation of immune cell behavior over time. It was then validated by comparing simulations with experimental data using Pearson’s correlation and further tested on independent datasets to confirm its robustness. Additionally, the model was applied to clinical bulk RNA-seq data from human IBD patients, providing valuable insights into immune system dynamics and potential therapeutic strategies.
Figure 4c, obtained from the simulation of human colitis model is highlighted here.
This model is described in the article:
Kilian, C., Ulrich, H., Zouboulis, V.A. et al. Longitudinal single-cell data informs deterministic modelling of inflammatory bowel disease. npj Syst Biol Appl 10, 69 (2024). https://doi.org/10.1038/s41540-024-00395-9
Abstract:
Single-cell-based methods such as flow cytometry or single-cell mRNA sequencing (scRNA-seq) allow deep molecular and cellular profiling of immunological processes. Despite their high throughput, however, these measurements represent only a snapshot in time. Here, we explore how longitudinal single-cell-based datasets can be used for deterministic ordinary differential equation (ODE)-based modelling to mechanistically describe immune dynamics. We derived longitudinal changes in cell numbers of colonic cell types during inflammatory bowel disease (IBD) from flow cytometry and scRNA-seq data of murine colitis using ODE-based models. Our mathematical model generalised well across different protocols and experimental techniques, and we hypothesised that the estimated model parameters reflect biological processes. We validated this prediction of cellular turnover rates with KI-67 staining and with gene expression information from the scRNA-seq data not used for model fitting. Finally, we tested the translational relevance of the mathematical model by deconvolution of longitudinal bulk mRNA-sequencing data from a cohort of human IBD patients treated with olamkicept. We found that neutrophil depletion may contribute to IBD patients entering remission. The predictive power of IBD deterministic modelling highlights its potential to advance our understanding of immune dynamics in health and disease.
This model was curated during the Hackathon hosted by BioMed X GmbH in 2024.
2025-03-07 | MODEL2502180001 | BioModels