Find research datasets worth reusing

opencc-by-4.0Nov 2020View details →

Transcriptome analysis of the effect of over-expressing H2A.J mutants in proliferating WI38 fibroblasts for the paper entitled: The H2A.J histone variant contributes to Interferon-Stimulated Gene expression in senescence by its weak interaction with H1 and the derepression of repeated DNA sequences

Abstract for overall study: The histone variant H2A.J was previously shown to accumulate in senescent human fibroblasts with persistent DNA damage to promote inflammatory gene expression, but its mechanism of action was unknown. We show that H2A.J accumulation contributes to weakening the association of histone H1 to chromatin and increasing its turnover. Decreased H1 in senescence is correlated with increased expression of some repeated DNA sequences, increased expression of STAT/IRF transcription factors, and transcriptional activation of Interferon-Stimulated Genes (ISGs). The H2A.J-specific Val-11 moderates the transcriptional activity of H2A.J, and H2A.J-specific Ser-123 can be phosphorylated in response to DNA damage with potentiation of its transcriptional activity by the phospho-mimetic S123E mutation. Our work demonstrates the functional importance of H2A.J-specific residues and potential mechanisms for its function in promoting inflammatory gene expression in senescence. Specific description for this dataset: H2A.J differs from canonical H2A only by a valine at position 11 instead of alanine, and the 7 C-terminal amino acids containing a potential minimal phosphorylation site SQ for DNA-damage response kinases. To test the functional importance of these H2A.J-specific sequences, we mutated Val-11 to Ala as is found in all canonical H2A sequences, and we mutated Ser-123 to either Glu to mimic a phospho-serine residue or to Ala to prevent phosphorylation. We also substituted the C-terminus of H2A.J with the C-terminus of H2A. These mutants, WT-H2A.J and canonical H2A-type1 were ectopically expressed in proliferating fibroblasts, and their microarray transcriptomes were compared to that of proliferating and senescent fibroblasts without ectopic histone expression. Genome-wide transcriptome analysis indicated that senescent fibroblasts clustered distinctly from proliferating fibroblasts, and proliferating fibroblasts expressing the H2A.J-V11A and H2A.J-S123E mutants clustered distinctly from fibroblasts expressing the other H2A.J mutants, WT-H2A.J, and H2A. Hallmark gene set enrichment analysis of the transcriptomes of fibroblasts expressing H2A.J-V11A or H2A.J-S123E versus control proliferating fibroblasts indicated that they showed the same highly significant enrichment for the Epithelial-Mesenchyme Transition, TNF-Alpha Signaling Via NF-kB, and Inflammatory Response gene sets. Notable inflammatory genes including IL1A, IL1B, IL6, CXCL8, and CCL2 are contained in these gene sets and are often induced in senescence as part of the senescence-associated secretory phenotype. Heat maps showed that the H2A.J-V11A and H2A.J-S123E mutants were particularly apt at activating the expression of these inflammatory genes in proliferating fibroblasts

opencc-by-4.0Jan 2024View details →

MAGE: Multi-ancestry Analysis of Gene Expression

MAGE comprises RNA-seq data from lymphoblastoid cell lines derived from 731 individuals from the <a href="https://doi.org/10.1038/nature15393" rel="nofollow">1000 Genomes Project (1KGP)</a>, representing 26 globally-distributed populations across five continental groups. These data offer a large, geographically diverse, open access resource to facilitate studies of the distribution, genetic underpinnings, and evolution of variation in human transcriptomes and include data from several ancestry groups that were poorly represented in previous studies. Briefly, this repo contains the following data: <ol> <li>Sample metadata and sequencing metrics</li> <li>Gene expression and splicing matrices used for e/sQTL mapping and analyses of global trends of expression/splicing diversity</li> <li>cis-e/sQTL mapping results, including aFC estimates for cis-eQTLs</li> <li>Functional annotations of cis-e/sQTLs</li> <li>Results of colocalization analysis between MAGE e/sQTLs and complex trait GWAS from the <a href="https://doi.org/10.1038/s41586-019-1310-4" rel="nofollow">PAGE</a> study</li> <li>Results of analyses of global trends of expression/splicing diversity</li> <li>Jointly-generated top genotype PCs for samples in MAGE and other resources with paired WGS/RNA-seq data (Geuvadis, GTEx, AFGR)</li> </ol> READMEs are provided for all data in the repo.

opencc-by-4.0Sep 2024View details →

Association of GDF-15 expression with immune parameter in a pan-cancer analysis

Immunotherapy with checkpoint blockers has significantly revolutionized the treatment landscape for many cancer patients. However, despite their success, checkpoint inhibitors have limitations that affect their effectiveness across a broader patient population. Soluble and cell-bound factors in the tumor microenvironment negatively impact cancer immunity. GDF15, a member of the TGF-β superfamily is associated with various physiological and pathological conditions, including cancer. Its overexpression in certain cancers has been linked to immune evasion. In this study we investigated the relationship between high GDF15 expression with various immune parameter in an in-silico analysis of 11,000 tumors from the TCGA database. Patients with non-small cell lung cancer and urothelial cancer was identified frequently GDF-15 immunosuppressed. Processed RNA sequencing data (TPM) obtained from firebrowse.org and the corresponding immune parameters were included in this dataset.

opencc-by-4.0Sep 2021View details →

Mammary single-cell RNA-seq analysis and prostate cancer survival as a function of H2AFJ expression for the paper entitled: The histone variant H2A.J is enriched in luminal epithelial cells

H2A.J is a poorly studied mammalian-specific variant of histone H2A. We used immunohistochemistry to study its localization in various human and mouse tissues. H2A.J showed cell-type specific expression with a striking enrichment in luminal epithelial cells of multiple glands including those of breast, prostate, pancreas, thyroid, stomach, and salivary glands. H2A.J was also highly expressed in many carcinoma cell lines and in particular, those derived from luminal breast and prostate cancer. H2A.J thus appears to be a novel marker for luminal epithelial cancers. Knocking-out the H2AFJ gene in T47D luminal breast cancer cells reduced the expression of several estrogen-responsive genes which may explain its putative tumorigenic role in luminal-B breast cancer.

opencc-by-4.0Apr 2023View details →

Master Coral database used in USVI SCTLD Transmission Experiment Gene Expression Analysis

The Master Coral Database fasta file is comprised of previously published genome-derived predicted gene models and transcriptomes spanning a wide diversity of coral families. Transcriptomes are from Davies et al., 2016 (doi: 10.3389/fmars.2016.00112), Kirk et al., 2018 (DOI: 10.1111/mec.14934); Moya et al., 2012 (doi: 10.1111/j.1365-294X.2012.05554.x); van de Water et al., 2018 (DOI: 10.1111/mec.14489).

opencc-by-4.0May 2022View details →

Datasets, reproducible codes, and results for evaluating differential expression analysis methods on population-level RNA-seq data

This upload contains the necessary R codes and data to reproduce the FDR and Power results described in our correspondence "Neglecting normalization impact in semi-synthetic RNA-seq data simulation generates artificial false positives" to Li Y, Ge X, Peng F, Li W, Li JJ, Exaggerated false positives by popular differential expression methods when analyzing human population samples, Genome Biology 23, 79, 2022, DOI: 10.1186/s13059-022-02648-4.

opencc-by-4.0Aug 2020View details →

Extensive qPCR analysis reveals altered gene expression in middle ear mucosa from cholesteatoma patients

Abstract The middle ear is a small and hard to reach compartment, limiting the amount of tissue that can be extracted and the possibilities for studying the molecular mechanisms behind diseases like cholesteatoma. In this paper 14 reference gene candidates were evaluated in the middle ear mucosa of cholesteatoma patients and two different control tissues. ACTB and GAPDH were shown to be the optimal genes for the normalisation of target gene expression when investigating middle ear mucosa in multiplex qPCR analysis. Validation of reference genes using c-MYC expression confirmed the suitability of ACTB and GAPDH as reference genes and showed an upregulation of c-MYC in middle ear mucosa during cholesteatoma. The occurrence of participants of the innate immunity, TLR2 and TLR4, were analysed in order to compare healthy middle ear mucosa to cholesteatoma. Analysis of TLR2 and TLR4 showed variable results depending on control tissue used, highlighting the importance of selecting relevant control tissue when investigating causes for disease. It is our belief that a consensus regarding reference genes and control tissue will contribute to the comparability and reproducibility of studies within the field.

opencc-zeroAug 2014View details →

Data from "Corset: enabling differential gene expression analysis for de novo assembled transcriptomes"

This dataset contains de novo transcriptome assemblies for three publicly available RNA-seq dataset (SRA055442, SRR453566-SRR453571 and GSE37704 ). For each assembly we also provide a table with the read counts per contig, the output from corset (clusters and counts), and the results from a genome-based analysis. This dataset was used to assess the performance of the corset software. More detail is provided in the paper: Nadia M Davidson and Alicia Oshlack, Corset: enabling differential gene expression analysis for de novo assembled transcriptomes, Genome Biology 2014, 15:410. http://genomebiology.com/2014/15/7/410/abstract

opencc-by-4.0Aug 2016View details →

Proteomic analysis of silenced cathepsin B expression suggests non-proteolytic cathepsin B functionality.

A list of human protein uniprot IDs. The proteins were identified by LC-MS/MS in the cellular supernatant of MDA-MB-231 cells, originally published in: F.C. Sigloch, J.D. Knopf, J. Weißer, A. Gomez-Auli, M.L. Biniossek, A. Petrera, et al., Proteomic analysis of silenced cathepsin B expression suggests non-proteolytic cathepsin B functionality, Biochim. Biophys. Acta - Mol. Cell Res. 1863 (2016) 2700–2709. doi:10.1016/j.bbamcr.2016.08.005. https://www.ncbi.nlm.nih.gov/pubmed/27526672

opencc-by-4.0Dec 2022View details →

Dataset from the analysis of biological activity of endophytic strain Serratia quinivorans KP32, the expression of biocontrol-related genes and the activity of antioxidant enzymes in bacterial cells treated with pathogenic fungi filtrates

This dataset contains the data from the analyses published in the article entitled "Genetic Determinants of Antagonistic Interactions and the Response of New Endophytic Strain Serratia quinivorans KP32 to Fungal Phytopathogens" in the International Journal of Molecular Sciences (https://doi.org/10.3390/ijms232415561). The data consist of results collected for studies on the antifungal activity of KP32 strain towards four fungal phytopathogens, results of primer efficiency determination and studies on the expression of genes potentially involved in biocontrol after treatment of KP32 strain with the fungal phytopathogens filtrates. Additionally, absorbances from activity tests for catalase (CAT) and superoxide dismutase (SOD) in the strain treated with fungal pathogens are included.

opencc-by-4.0Aug 2023View details →

Decoding host-microbiome interactions through co-expression network analysis within the non-human primate intestine

Supplementary Table Captions: Supplementary Table S9. Evaluation and parameter determination of host and microbiome RNA read classification using simulation datasets Supplementary Table S10. 40 pathways significantly upregulated in the cecum as compared to the transverse colon Supplementary Table S11. Host-microbiome gene co-expression network edges Supplementary Table S12. Host-host gene co-expression network edges Supplementary Table S13. Microbiome-microbiome gene co-expression network edges Supplementary Table S14. List of genes included in each gene module identified from the gene co-expression network Supplementary Table S15. Results of enrichment analysis for each gene module identified from the gene co-expression network Supplementary Table S16. The top 32 bacterial species in terms of expression abundance based on metatranscriptome profiles Supplementary Table S17. Number of microbiome RNA reads annotated by the KEGG database Supplementary Table S18. Results of enrichment analysis of gene modules for each parameter Supplementary Table S19. Evaluation of modules in each parameter of Newman algorithm Supplementary Table S20. Evaluation of modules in each parameter of Louvain algorithm Supplementary Table S21. Evaluation of modules in each parameter of Leiden algorithm Supplementary Table S22. Evaluation of modules in each parameter of WGCNA

opencc-by-4.0Jan 2022View details →

Dataset Klussmeier et al., Secretin receptor as a target in gastrointestinal cancer: expression analysis and ligand development

Numerical dataset for the manuscript by Klussmeier et al., Secretin receptor as a target in gastrointestinal cancer: expression analysis and ligand development.

opencc-by-4.0Mar 2022View details →

Integrating differential expression and weighted correlation network analysis for identifying genes controlling shoot development in Sorghum bicolor

Supplementery materials of journal article "Integrating differential expression and weighted correlation network analysis for identifying genes controlling shoot development in Sorghum bicolor"

opencc-by-4.0Jul 2022View details →

Transcriptomic analysis of deceptively pollinated Arum maculatum (Araceae) reveals association between terpene synthase expression in floral trap chamber and species-specific pollinator attraction

A compressed folder containing the R script and input files required to replicate the results in our manuscript entitled "Transcriptomic analysis of deceptively pollinated Arum maculatum (Araceae) reveals association between terpene synthase expression in floral trap chamber and species-specific pollinator attraction". Note: Raw Illumina sequencing files associated with this study have been uploaded to NCBI SRA, under the BioProject accession PRJNA856436. ABSTRACT Deceptive pollination often involves volatile organic compound (VOC) emissions that mislead insects into performing non-rewarding pollination. Among deceptively pollinated plants, Arum maculatum is particularly well-known for its potent dung-like VOC emissions and specialized floral chamber, which traps pollinators – mainly Psychoda phalaenoidesand P. grisescens – overnight. However, little is known about the genes underlying the production of many A. maculatumVOCs, and their influence on variation in pollinator attraction rates. Therefore, we performed de novo transcriptome sequencing of A. maculatum appendix and male floret tissue collected during- and post-anthesis, from ten natural populations across Europe. These RNA-seq data were paired with GC-MS analyses of floral scent composition and pollinator data collected from the same inflorescences. Differential expression analyses revealed candidate transcripts in appendix tissue linked to malodourous VOCs including indole, p-cresol, and 2-heptanone. Additionally, we found that terpene synthase expression in male floret tissue during anthesis significantly covaried with sex- and species-specific attraction of Psychoda phalaenoides and P. grisescens. Taken together, our results provide the first insights into molecular mechanisms underlying pollinator attraction patterns in A. maculatum, and highlight floral chamber sesquiterpene (e.g.bicyclogermacrene) synthases as interesting candidate genes for further study.

opencc-by-4.0Oct 2022View details →

Supplementary Tables for "Immune cell-specific smoking-related expression characteristics are revealed by re-analysis of transcriptomes from the CEDAR cohort"

Supplementary Tables from "Immune cell-specific smoking-related expression characteristics are revealed by re-analysis of transcriptomes from the CEDAR cohort".

Figure 7. T in Bioinformatics and expression analysis of the Xeroderma Pigmentosum complementation group C (XPC) of Trypanosoma evansi in Trypanosoma cruzi cells

Figure 7. T. cruzi growth assessment after cisplatin treatment (300 ΜM). (a) Wild type (WT). (b) TcXPC superexpressor (Tc-TcXPC). (c) TevXPC expressor (Tc-TevXPC). The solid lines represent the untreated cells, while the dotted lines represent the cells treated with cisplatin. Statistical student's t test: (*) On that point, cells treated with cisplatin presented a statistically significant lower growth in relation to untreated cells (p <0.05). Representative results of three independent experiments.

Figure 6 in Bioinformatics and expression analysis of the Xeroderma Pigmentosum complementation group C (XPC) of Trypanosoma evansi in Trypanosoma cruzi cells

Figure 6. Growth assessment of T. cruzi: wild type (WT), TcXPC superexpressor (Tc-TcXPC) and TevXPC expressor (Tc-TevXPC). Statistical student's t test: (*) On that point, only Tc-TevXPC presented a statistically significant lower growth in relation to WT (p <0.05); (**) On that point, both Tc-TcXPC and Tc-TevXPC presented a significant lower growth in relation to WT (p <0.05). All parasites were at same initial concentration, grown on LIT medium and were counted daily. Representative results of three independent experiments.

Figure 5 in Bioinformatics and expression analysis of the Xeroderma Pigmentosum complementation group C (XPC) of Trypanosoma evansi in Trypanosoma cruzi cells

Figure 5. TevXPC amplification by RT-PCR with the cDNA from cell cultures. Lanes: (1) 1Kb DNA Ladder; (2) WT; (3) Tc-TcXPC; (4 and 5) Tc-TevXPC; (6) positive control (DNA from T. evansi); (7) negative control.

Figure 4 in Bioinformatics and expression analysis of the Xeroderma Pigmentosum complementation group C (XPC) of Trypanosoma evansi in Trypanosoma cruzi cells

Figure 4. (a) TcXPB-R protein model. (b) TevXPB-R protein model. (c) TcXPB-R (blue) and TevXPB-R (orange) models overlay.

Figure 2 in Bioinformatics and expression analysis of the Xeroderma Pigmentosum complementation group C (XPC) of Trypanosoma evansi in Trypanosoma cruzi cells

Figure 2. (a) Alignment between TcXPC and TevXPC proteins (mismatches highlighted) and its domains. Green: RAD4/PNGase transglutaminase-like fold. Blue: RAD4 beta-hairpin domain 1. Red: RAD4 beta-hairpin domain 2. Yellow: RAD4 beta-hairpin domain 3. (b) Candidate sequence motif involved in p62 interaction (highlighted by brown rectangle) found in TcXPC and TevXPC. This sequence is suggested based on the sequence motif described for Human XPC and yeast RAD4: D/E-F/W-E-D/E-V.