RDAVIDWebService: a versatile <i>R</i> interface to DAVID

Fresno, Cristóbal; Fernández, Elmer

doi:10.1093/bioinformatics/btt487

Cited by 183 publications

(160 citation statements)

References 5 publications

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“…For GO enrichment in DE genes targeted by categories of dynamic binding peaks (Figure 2D), we defined the genes in distinct DREM paths as foreground, and all expressed genes as background, and retrieved the Functional Annotation Chart with EASE score (modified p-value) threshold of 0.1 and count threshold of 2, using functionalities provided by the R BioConductor package RDAVIDWebService (59) to query the DAVID web service (60). The GO terms in GO_TERM_BP_FAT with FDR<=1% from all target gene sets are combined, and the enrichment p-values of these terms are retrieved for each gene set to create the heatmap in Figure 2D.…”

Section: Methodsmentioning

confidence: 99%

A transcription factor hierarchy defines an environmental stress response network

Song

Huang

Wise

et al. 2016

Science

425

444

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Environmental stresses are universally encountered by microbes, plants and animals. Yet systematic studies of stress-responsive transcription factor (TF) networks in multi-cellular organisms have been limited. The phytohormone abscisic acid (ABA) influences the expression of thousands of genes, allowing us to characterize complex stress-responsive regulatory networks. Using chromatin immunoprecipitation sequencing, we identified genome-wide targets of 21 ABA-related TFs to construct a comprehensive regulatory network in Arabidopsis thaliana. Determinants of dynamic TF binding and a hierarchy among TFs were defined, illuminating the relationship between differential gene expression patterns and ABA pathway feedback regulation. By extrapolating regulatory characteristics of observed canonical ABA pathway components, we identified a new family of transcriptional regulators modulating ABA and salt responsiveness and demonstrated their utility to modulate plant resilience to osmotic stress.

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Section: Methodsmentioning

confidence: 99%

A transcription factor hierarchy defines an environmental stress response network

Song

Huang

Wise

et al. 2016

Science

425

444

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“…to indicate ranked likelihood of being a true target. Gene targets were analysed through enrichment analysis using the DAVID33 web service and the RDAVIDWebService62 BioConductor package in R. Targets were submitted in the form of their main protein product (UniProt Identifiers). Statistical evidence of enrichment was assessed by a modified Fisher’s Exact Test within DAVID with false discovery rate of 0.05 and Benjamini-Hochberg correction for multiple testing.…”

Section: Methodsmentioning

confidence: 99%

Urinary Exosomes Contain MicroRNAs Capable of Paracrine Modulation of Tubular Transporters in Kidney

Gracia

Wang

et al. 2017

Sci Rep

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Exosomes derived from all nephron segments are present in human urine, where their functionality is incompletely understood. Most studies have focused on biomarker discovery rather than exosome function. Through sequencing we identified the miRNA repertoire of urinary exosomes from healthy volunteers; 276 mature miRNAs and 345 pre-miRNAs were identified (43%/7% of reads). Among the most abundant were members of the miR-10, miR-30 and let-7 families. Targets for the identified miRNAs were predicted using five different databases; genes encoding membrane transporters and their regulators were enriched, highlighting the possibility that these miRNAs could modulate key renal tubular functions in a paracrine manner. As proof of concept, cultured renal epithelial cells were exposed to urinary exosomes and cellular exosomal uptake was confirmed; thereafter, reduced levels of the potassium channel ROMK and kinases SGK1 and WNK1 were observed in a human collecting duct cell line, while SPAK was unaltered. In proximal tubular cells, mRNA levels of the amino acid transporter gene SLC38A2 were diminished and reflected in a significant decrement of its encoded protein SNAT2. Protein levels of the kinase SGK1 did not change. Thus we demonstrated a novel potential function for miRNA in urinary exosomes.Urinary exosomes are lipid membrane-bound nanovesicles released from intracellular multivesicular bodies (MVBs) 1,2 and derived from all cells in the urinary tract [3][4][5] . During the inward budding of endosomes that give origin to exosomes, proteins 2 , mRNAs 6 , microRNAs (miRNAs) 7 , noncoding RNA (ncRNA) 8 , transcription factors 9 and other biomolecules present in the cytosol can be incorporated. The lipid bi-layer of these nanovesicles provides the cargo with stable storage conditions and protects it from degradation by extracellular proteases and ribonucleases 10. Studies in other tissues have shown that once exosomes and other microvesicles are released into the extracellular environment, interactions with cells can occur by direct ligand-receptor signalling, by exosomal fusion to the target cell membrane and discharge of exosomal content directly into the cytoplasm, or via phagocytosis/macropinocytosis 11,12 . Exosomes are known to deliver biologic cargo not only to neighbouring cells but also long distance 13 . The majority of studies concerning urinary exosomes have focused on their potential as biomarkers of disease pathology and progression, including prostate and bladder cancers [14][15][16][17] , but their functional significance is now being addressed. Inter-cellular signalling by exosomes in cultured murine renal epithelial cells was demonstrated for the first time by Street et al. 18 , who suggested that collecting duct cell-derived exosomes can transfer the ability to express AQP2. Our previous studies revealed that urinary exosomes inhibit bacterial growth of both commensal and uropathogenic E. coli by inducing bacterial lysis 19 . Bruschi and colleagues demonstrated that urinary exosomes can consume ...

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“…W. Huang et al, 2009a; 2009b) with the RDAVIDWebService interface (Fresno and Fernández, 2013). GO-BP terms for Tables 1–3 were re-ranked for ‘interestingness’ using the sum of their p-value rank and number of genes associated with that term (Pop.Hits), a formula that performed better than a variety of alternatives.…”

Section: Methodsmentioning

confidence: 99%

Systems biology of facial development: contributions of ectoderm and mesenchyme

Hooper

Feng

et al. 2017

Developmental Biology

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The rapid increase in gene-centric biological knowledge coupled with analytic approaches for genomewide data integration provides an opportunity to develop systems-level understanding of facial development. Experimental analyses have demonstrated the importance of signaling between the surface ectoderm and the underlying mesenchyme in coordinating facial patterning. However, current transcriptome data from the developing vertebrate face is dominated by the mesenchymal component, and the contributions of the ectoderm are not easily identified. We have generated transcriptome datasets from critical periods of mouse face formation that enable gene expression to be analyzed with respect to time, prominence, and tissue layer. Notably, by separating the ectoderm and mesenchyme we considerably improved the sensitivity compared to data obtained from whole prominences, with more genes detected over a wider dynamic range. From these data we generated a detailed description of ectoderm-specific developmental programs, including pan-ectodermal programs, prominence- specific programs and their temporal dynamics. The genes and pathways represented in these programs provide mechanistic insights into several aspects of ectodermal development. We also used these data to identify co-expression modules specific to facial development. We then used 14 co-expression modules enriched for genes involved in orofacial clefts to make specific mechanistic predictions about genes involved in tongue specification, in nasal process patterning and in jaw development. Our multidimensional gene expression dataset is a unique resource for systems analysis of the developing face; our co-expression modules are a resource for predicting functions of poorly annotated genes, or for predicting roles for genes that have yet to be studied in the context of facial development; and our analytic approaches provide a paradigm for analysis of other complex developmental programs.

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RDAVIDWebService: a versatile R interface to DAVID

Abstract: cfresno@bdmg.com.ar or efernandez@bdmg.com.ar.

Cited by 183 publications

References 5 publications

A transcription factor hierarchy defines an environmental stress response network

A transcription factor hierarchy defines an environmental stress response network

Urinary Exosomes Contain MicroRNAs Capable of Paracrine Modulation of Tubular Transporters in Kidney

Systems biology of facial development: contributions of ectoderm and mesenchyme

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