WEGO 2.0: a web tool for analyzing and plotting GO annotations, 2018 update

Jia, Yali; Zhang, Yong; Cui, Huihai; Liu, Jiawei; Wu, Yuqing; Cheng, Yun; Xu, Huixing; Huang, Xingxin; Li, Shengting; Zhou, An Min; Zhang, Xiuqing; Bolund, Lars; Chen, Qiang; Wang, Jian; Yang, Huanming; Fang, Lin; Shi, Chunmei

doi:10.1093/nar/gky400

Cited by 486 publications

(328 citation statements)

References 36 publications

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“…Sequences corresponding to network nodes were extracted and Gene Ontology (GO) annotation of the proteins was performed by mapping the proteins to TAIR database [32] and AgriGO database [33] Cellular components (CC), biological processes (BP) and molecular functions (MF) were computed using WEGO tool [34]. To find the pathways regulated by the proteins participating in TeaGPIN, KEGG database [35] was used.…”

Section: Methodsmentioning

confidence: 99%

Genome-wide interologous interactome map (TeaGPIN) ofCamellia sinensis

Singh

2019

Preprint

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Tea, prepared from the young leaves of Camellia sinensis, is a non-alcoholic beverage globally consumed due to its antioxidant properties, strong taste and aroma. Although, the genomic data of this medicinally and commercially important plant is available, studies related to its sub-cellular interactomic maps are less explored. In this work, we propose a genome-wide interologous protein-protein interaction (PPI) network of tea, termed as TeaGPIN, consisting of 12,033 nodes and 216,107 interactions, developed using draft genome of tea and known PPIs exhaustively collected from 49 template plants. TeaGPIN interactions are prioritized using domain-domain interactions along with the interolog information. A high-confidence TeaGPIN consisting of 5,983 nodes and 58,867 edges is reported and its interactions are further evaluated using protein co-localization similarities. Based on three network centralities (degree, betweenness and eigenvector), 1,302 key proteins are reported in tea to have p-value < 0.01 by comparing the TeaGPIN with 10,000 realizations of Erdős-Rényi and Barabási-Albert based corresponding random network models. Functional content of TeaGPIN is assessed using KEGG and GO annotations and its modular architecture is explored. Network based characterization is carried-out on the transcription factors, and proteins involved flavonoid biosynthesis and photosynthesis pathways to find novel candidates involved in various regulatory processes. We believe the proposed TeaGPIN will impart useful insights in understanding various mechanisms related to growth and development as well as defence against biotic and abiotic perturbations.

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Section: Methodsmentioning

confidence: 99%

Genome-wide interologous interactome map (TeaGPIN) ofCamellia sinensis

Singh

2019

Preprint

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“…FHI method is based on the idea that interacting proteins perform more or less similar functions and hence GO functional annotation similarity or functional homogeneity can add an extra layer of confidence to the predicted interactions 38 . GO annotations for each protein of TulsiPIN were predicted using agriGO v2.0 39 and were visualized using WEGO v2.0 40 and REVIGO 41 . Jaccard coefficient was employed to estimate the functional homogeneity index for two interacting proteins that is defined as where G P1 ∩ G P2 are the GO terms shared by interacting proteins P 1 and P 2.…”

Section: Methodsmentioning

confidence: 99%

TulsiPIN: an interologous protein interactome ofOcimum tenuiflorum

Singh

2019

Preprint

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Ocimum tenuiflorum, commonly known as holy basil or tulsi, is globally recognized for its multitude of medicinal properties. However, a comprehensive study revealing the complex interplay among its constituent proteins at subcellular level is still lacking. To bridge this gap, a genome scale interologous protein-protein interaction (PPI) network, TulsiPIN, is developed using 49 template plants. The reported network consists of 13, 660 nodes and 327, 409 binary interactions. A high confidence PPI network consisting of 7, 719 nodes having 95, 532 interactions was inferred using domain-domain interaction information along with interolog based statistics, and its reliability was further assessed using functional homogeneity and protein colocalization. 1, 625 vital proteins are predicted by statistically evaluating this high confidence TulsiPIN with two ensembles of corresponding random networks, each consisting of 10, 000 realizations of Erdős-Rényi and Barabási-Albert models. Topological features of TulsiPIN including small-world, scale-free and modular architecture are inspected and found to resemble with other plant PPI networks. Finally, numerous regulatory proteins like transcription factors, transcription regulators and protein kinases are profiled in TulsiPIN and a sub-network of proteins participating in 10 secondary metabolite biosynthetic pathways is studied. We believe, the methodology developed and insights imparted would be useful in understanding regulatory mechanisms in various plant species.

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“…Gene Ontology (GO) analysis of the EVs proteomes was performed using the amino acid FASTA sequences of G. adiacens and G. elegans . For this, GO annotations were analyzed and plotted using the tools Blast2GO (https://www.blast2go.com/) [30], and WEGO, version 2.0 (http://wego.genomics.org.cn/) [31]. The EVs proteins were grouped based on functional association networks using the tool STRING (https://string-db.org/) [32].…”

Section: Methodsmentioning

confidence: 99%

Proteomics of Extracellular Vesicles Produced byGranulicatellaSpecies that cause Infective Endocarditis

Ellepola

et al. 2019

Preprint

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30When oral bacteria accidentally enter the bloodstream due to transient tissue 31 damage during dental procedures, they have the potential to attach to the endocardium 32 or an equivalent surface of an indwelling prosthesis and cause infection. Many bacterial 33 species produce extracellular vesicles (EVs) as part of normal physiology, but also use 34 it as a virulence strategy. In this study, it was hypothesized that Granulicatella species 35 produce EVs that possibly help them in virulence. Therefore, the objectives were to 36 isolate and characterize EVs produced by these species and to investigate their immune-37 stimulatory effects. The reference strains G. adiacens CCUG 27809 and G. elegans 38 CCUG 38949 were cultured on chocolate blood agar for 2 days. From subsequent broth 39 cultures, the EVs were isolated using differential centrifugation and filtration protocol 40 and then observed using scanning electron microscopy. Proteins in the vesicle 41 preparations were identified by nano LC-ESI-MS/MS. The EVs proteomes were 42 analyzed and characterized using different bioinformatics tools. The immune-43 stimulatory effect of the EVs was studied via ELISA quantification of IL-8, IL-1β and 44 CCL5, major proinflammatory cytokines, produced from stimulated human PBMCs. It 45 was revealed that both G. adiacens and G. elegans produced EVs, ranging in diameter 46 from 30 to 250 nm. Overall, G. adiacens EVs contained 160 proteins, and G. elegans 47 EVs contained 107 proteins. Both proteomes consist of several ribosomal proteins, 48DNA associated proteins, binding proteins, and metabolic enzymes. It was also shown 49 that these EVs carry putative virulence factors including moonlighting proteins. These 50 EVs were able to induce the production of IL-8, IL-1β and CCL5 from human PBMCs. 51The diversity in EVs content indicates that these vesicles could have possible roles in 3 52 bacterial survival, invasion, host immune modulation as well as infection. Further 53 functional characterization of the Granulicatella EVs may provide new insights into 54 virulence mechanisms of these important but less studied oral bacterial species. 55 56 57 Granulicatella species, formerly known as nutritionally variant streptococci 58 based on their characteristic dependence on pyridoxal or cysteine supplementation for 59 their growth in standard media [1], are catalase and oxidase negative, non-motile, non-60 spore-forming, facultatively anaerobic Gram-positive cocci [2, 3]. They are part of the 61 normal oral flora [4], but cause serious infections such as infective endocarditis. The 62 genus Granulicatella consists of 3 species: Granulicatella adiacens, Granulicatella 63 elegans and Granulicatella balaenopterae [3]. The species G. balaenopterae has not 64 been isolated from human samples, whereas both G. adiacens and G. elegans have been 65 reported from IE cases [5, 6]. In addition, these oral commensal cocci have been 66 associated with endodontic infections [7, 8], dental caries [9], and periodontitis [8, 10] 67 via DNA-based s...

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WEGO 2.0: a web tool for analyzing and plotting GO annotations, 2018 update

Cited by 486 publications

References 36 publications

Genome-wide interologous interactome map (TeaGPIN) ofCamellia sinensis

Genome-wide interologous interactome map (TeaGPIN) ofCamellia sinensis

TulsiPIN: an interologous protein interactome ofOcimum tenuiflorum

Proteomics of Extracellular Vesicles Produced byGranulicatellaSpecies that cause Infective Endocarditis

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