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DaCarVulg

ABSTRACT: Carlina vulgaris

PROVIDER: PRJEB81005 | ENA |

REPOSITORIES: ENA

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Dataset's files

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			Action	DRS
		Other
	ERR13800537.fastq.gz	Fastqsanger.gz
	ERR13800538.fastq.gz	Fastqsanger.gz
	ERR13800539.fastq.gz	Fastqsanger.gz
	ERR13800540.fastq.gz	Fastqsanger.gz

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Carlina vulgaris

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DNA Methylation Profile in Psoriasis Vulgaris and Generalized Pustular Psoriasis Patients

Project description:Epigenetics plays a role in the pathogenesis of psoriasis vulgaris and generalized pustular psoriasis (GPP) through DNA methylation modifications that cause changes in immune responses. Psoriasis vulgaris is dominated by autoimmune responses, driven by Th17 cells producing IL-17, whereas GPP is dominated by autoinflammatory responses resulting from IL-36 dysregulation and neutrophil hyperactivation. Objective: This study aims to determine the DNA methylation profile and analyze the differences in IL-17 and IL-36 levels in both psoriasis phenotypes and healthy controls. Method: This study employed a cross-sectional design, comprising 20 patients with psoriasis vulgaris, three patients with GPP, and 13 healthy controls. DNA methylation profiles were assessed using Reduced Representation Methylation Sequencing, while IL-17 and IL-36 levels were assessed using ELISA. Results: Increased 5-methyl cytosine (5mC) was identified in psoriasis vulgaris and GPP compared to healthy controls. Increased 5mC at the FOXP3 promoter was identified in GPP and psoriasis vulgaris with high IL-17 levels, while decreased 5mC at the CARD14 promoter was identified in psoriasis vulgaris with high IL-17 levels. GPP showed higher IL-17 levels than healthy controls (p<0.05). IL-17 levels in psoriasis vulgaris showed no significant difference compared to GPP and healthy controls (p>0.05). IL-36 levels did not differ significantly among the three groups, with the highest IL-36 levels observed in psoriasis vulgaris (p>0.05). Conclusion: Increased DNA methylation in the FOXP3 gene promoter is predicted to cause high IL- 17 levels in psoriasis vulgaris and GPP, while IL-36 levels are higher only in psoriasis vulgaris.

2025-08-07 | GSE304903 | GEO

Differential analysis of host small RNAs identified conserved and new miRNAs that affect nodulation and strain selectivity in the Phaseolus vulgaris- Rhizobium etli symbiosis

Project description:We report an small RNA sequencing (sRNA-seq) approach to identify host sRNAs involved in the nitrogen fixing symbiosis between Mesoamerican Phaseolus vulgaris and Rhizobium etli strains with different degrees in nodulation efficiency. This approach identified conserved and known microRNAs (miRNAs) differentially accumulated in Mesoamerican P. vulgaris roots in response to a highly efficient strain, to a less efficient one or to both strains.

2020-11-01 | GSE155414 | GEO

Genome-wide RNA sequencing of D. vulgaris respond to CuO nanoparticles exposure

Project description:Purpose: The objective of this study is to reveal the potential effects of CuO nanoparicles (NPs) on Desulfovibrio vulgaris Hildenborough (D. vulgaris) via genome-wide RNA sequencing Methods: RNA was harvested from D. vulgaris cultures in the presence and absence of CuO NPs (0, 1, 50, 250 mg CuO NPs/L) 8 h after cultivation.

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Spanish slug (Arion vulgaris) small RNA sequencing and annotation

Project description:Goal of the study is to characterize small RNAs in Spanish land slug, Arion vulgaris.

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Computational prediction of miRNAs and their targets in Phaseolus vulgaris using simple sequence repeat signatures

Project description:MicroRNAs (miRNAs) are endogenous, noncoding, short RNAs directly involved in regulating gene expression at the post-transcriptional level. In spite of immense importance, limited information of P. vulgaris miRNAs and their expression patterns prompted us to identify new miRNAs in P. vulgaris by computational methods. Besides conventional approaches, we have used the simple sequence repeat (SSR) signatures as one of the prediction parameter. Moreover, for all other parameters including normalized Shannon entropy, normalized base pairing index and normalized base-pair distance, instead of taking a fixed cut-off value, we have used 99% probability range derived from the available data. We have identified 208 mature miRNAs in P. vulgaris belonging to 118 families, of which 201 are novel. 97 of the predicted miRNAs in P. vulgaris were validated with the sequencing data obtained from the small RNA sequencing of P. vulgaris. Randomly selected predicted miRNAs were also validated using qRT-PCR. A total of 1305 target sequences were identified for 130 predicted miRNAs. Using 80% sequence identity cut-off, proteins coded by 563 targets were identified. The computational method developed in this study was also validated by predicting 229 miRNAs of A. thaliana and 462 miRNAs of G. max, of which 213 for A. thaliana and 397 for G. max are existing in miRBase 20. There is no universal SSR that is conserved among all precursors of Viridiplantae, but conserved SSR exists within a miRNA family and is used as a signature in our prediction method. Prediction of known miRNAs of A. thaliana and G. max validates the accuracy of our method. Our findings will contribute to the present knowledge of miRNAs and their targets in P. vulgaris. This computational method can be applied to any species of Viridiplantae for the successful prediction of miRNAs and their targets.

2015-04-28 | GSE68305 | GEO

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