Multi-omics enrichment analysis using the GeneTrail2 web service

Stöckel, Daniel; Kehl, Tim; Trampert, Patrick; Schneider, Lara; Backes, Christina; Ludwig, Nicole; Gerasch, Andreas; Kaufmann, Michael; Gessler, Manfred; Graf, Norbert; Meese, Eckart; Keller, Andreas; Lenhof, Hans‐Peter

doi:10.1093/bioinformatics/btv770

Cited by 136 publications

(116 citation statements)

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“…We removed those genes whose positive selection signature was lost under the gene tree. Finally, the functional enrichment of these positively selected genes in GO terms and KEGG pathways was tested by using the GeneTrail2 method (55), with the 14,254 orthologous genes as the reference gene set. Significantly enriched category included at least two genes, and the hypergeometric test was used to estimate significance (P < 0.05).…”

Section: Methodsmentioning

confidence: 99%

Comparative genomics reveals convergent evolution between the bamboo-eating giant and red pandas

et al. 2017

Proc. Natl. Acad. Sci. U.S.A.

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Phenotypic convergence between distantly related taxa often mirrors adaptation to similar selective pressures and may be driven by genetic convergence. The giant panda (Ailuropoda melanoleuca) and red panda (Ailurus fulgens) belong to different families in the order Carnivora, but both have evolved a specialized bamboo diet and adaptive pseudothumb, representing a classic model of convergent evolution. However, the genetic bases of these morphological and physiological convergences remain unknown. Through de novo sequencing the red panda genome and improving the giant panda genome assembly with added data, we identified genomic signatures of convergent evolution. Limb development genes DYNC2H1 and PCNT have undergone adaptive convergence and may be important candidate genes for pseudothumb development. As evolutionary responses to a bamboo diet, adaptive convergence has occurred in genes involved in the digestion and utilization of bamboo nutrients such as essential amino acids, fatty acids, and vitamins. Similarly, the umami taste receptor gene TAS1R1 has been pseudogenized in both pandas. These findings offer insights into genetic convergence mechanisms underlying phenotypic convergence and adaptation to a specialized bamboo diet.de novo genome | phenotype convergence | amino acid convergence | positive selection | pseudogenization

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Section: Methodsmentioning

confidence: 99%

Comparative genomics reveals convergent evolution between the bamboo-eating giant and red pandas

et al. 2017

Proc. Natl. Acad. Sci. U.S.A.

202

199

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“…Target networks were constructed using an offline version of MiRTargetLink [22] and visualized in Cytoscape. miRNA target pathway analysis has been carried out using GeneTrai2 [23]. For the GeneTrail2 analysis, all available categories were analyzed, the minimal category size was set to 4 and all p values were adjusted using Benjamini-Hochberg adjustment.…”

Section: Methodsmentioning

confidence: 99%

cPAS-based sequencing on the BGISEQ-500 to explore small non-coding RNAs

et al. 2016

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BackgroundWe present the first sequencing data using the combinatorial probe-anchor synthesis (cPAS)-based BGISEQ-500 sequencer. Applying cPAS, we investigated the repertoire of human small non-coding RNAs and compared it to other techniques.ResultsStarting with repeated measurements of different specimens including solid tissues (brain and heart) and blood, we generated a median of 30.1 million reads per sample. 24.1 million mapped to the human genome and 23.3 million to the miRBase. Among six technical replicates of brain samples, we observed a median correlation of 0.98. Comparing BGISEQ-500 to HiSeq, we calculated a correlation of 0.75. The comparability to microarrays was similar for both BGISEQ-500 and HiSeq with the first one showing a correlation of 0.58 and the latter one correlation of 0.6. As for a potential bias in the detected expression distribution in blood cells, 98.6% of HiSeq reads versus 93.1% of BGISEQ-500 reads match to the 10 miRNAs with highest read count. After using miRDeep2 and employing stringent selection criteria for predicting new miRNAs, we detected 74 high-likely candidates in the cPAS sequencing reads prevalent in solid tissues and 36 candidates prevalent in blood.ConclusionsWhile there is apparently no ideal platform for all challenges of miRNome analyses, cPAS shows high technical reproducibility and supplements the hitherto available platforms.Electronic supplementary materialThe online version of this article (doi:10.1186/s13148-016-0287-1) contains supplementary material, which is available to authorized users.

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“…A selection of tools that provide solution for this task includes miRNApath (5) a Bioconductor package for enrichment of miRNA expression data, miTALOS (6) a web-server for the analysis of tissue specific regulation in signaling pathways or DIANA-miRPath (7,8), a broad target pathway analysis tool that is regularly updated. Similar functionality is also included in general ‘omics’ enrichment toolboxes such as GeneTrail2 (9) and in miRNA analysis pipelines such as Oasis (10). …”

Section: Introductionmentioning

confidence: 99%

“…In addition to miRNA resources, also pathway databases, gene ontologies and bioinformatics methods have been extended significantly in the past six years. With GeneTrail2 (9), we developed a comprehensive gene set analysis toolbox containing substantially increased functionality as compared to the original version GeneTrail (13). …”

Section: Introductionmentioning

confidence: 99%

“…The respective MTIs were then used to create three test sets with different experimental evidence levels (any, weak and strong). The third resource, functional categories, are obtained from the GeneTrail2 (9) data warehouse. This data warehouse includes functional categories from various third party resources including KEGG (17), Reactome (18), BioCarta (19), GO (20), cytogenetic bands, disease categories from the NCI Pathway Interaction Database (21) and the Small Molecule Pathway Database (22).…”

Section: Introductionmentioning

confidence: 99%

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miRPathDB: a new dictionary on microRNAs and target pathways

et al. 2016

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In the last decade, miRNAs and their regulatory mechanisms have been intensively studied and many tools for the analysis of miRNAs and their targets have been developed. We previously presented a dictionary on single miRNAs and their putative target pathways. Since then, the number of miRNAs has tripled and the knowledge on miRNAs and targets has grown substantially. This, along with changes in pathway resources such as KEGG, leads to an improved understanding of miRNAs, their target genes and related pathways. Here, we introduce the miRNA Pathway Dictionary Database (miRPathDB), freely accessible at https://mpd.bioinf.uni-sb.de/. With the database we aim to complement available target pathway web-servers by providing researchers easy access to the information which pathways are regulated by a miRNA, which miRNAs target a pathway and how specific these regulations are. The database contains a large number of miRNAs (2595 human miRNAs), different miRNA target sets (14 773 experimentally validated target genes as well as 19 281 predicted targets genes) and a broad selection of functional biochemical categories (KEGG-, WikiPathways-, BioCarta-, SMPDB-, PID-, Reactome pathways, functional categories from gene ontology (GO), protein families from Pfam and chromosomal locations totaling 12 875 categories). In addition to Homo sapiens, also Mus musculus data are stored and can be compared to human target pathways.

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Multi-omics enrichment analysis using the GeneTrail2 web service

Abstract: Supplementary data are available at Bioinformatics online.

Cited by 136 publications

References 46 publications

Comparative genomics reveals convergent evolution between the bamboo-eating giant and red pandas

Comparative genomics reveals convergent evolution between the bamboo-eating giant and red pandas

cPAS-based sequencing on the BGISEQ-500 to explore small non-coding RNAs

miRPathDB: a new dictionary on microRNAs and target pathways

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