WEGO (Web Gene Ontology Annotation Plot) is a simple but useful tool for visualizing, comparing and plotting GO (Gene Ontology) annotation results. As the GO vocabulary was more and more popular, WEGO became widely adopted and used in many researches. Therefore, we have updated WEGO 2.0 in 2018.
The changes made in this update are as following:
1. The limit of input file numbers was cancelled. Now the users could upload files as many as they want in one operation.
2. We have added the reference data of 9 species for users to choose.
3. Besides the traditional WEGO histogram, WEGO 2.0 outputs an additional type of bar graph showing GO terms with significant gene number differences.
The two types of WEGO outputs shown (Fig 1 & Fig 2) are commonly used in a lot of De novo genome projects [1-4] as well as comparative genome projects [5-6] and De novo transcriptome analysis [7-10].
Fig 1. Traditional WEGO histogram. X-axis shows user selected GO terms; y-axis shows the percentages of genes (number of a particular gene divided by total gene number).
Fig 2. X-axis shows user selected GO terms; y-axis shows the log of the P-values from Chi-square tests (of all the datasets uploaded for a particular GO term).
There are three steps to work with WEGO:
1.Upload files: Upload annotation result(s) and choose the file format. The input file(s) can be in WEGO native format, GOA format, or three types of InterProScan output files. InterProScan text, raw and XML output formats are supported as input formats. In order to support multiple dataset analysis, in WEGO 2.0, the number of input files is unlimited.
2.Choose GO term: Select GO terms for the output. The user will be automatically redirected to a webpage with a hierarchical GO tree, in which all GO terms in the files uploaded are included. There are three methods of selecting GO terms for the output: 1) by choosing the number of GO level, the default and most commonly chosen GO level is the 2nd level; 2) by clicking on the “star” button to select the GO terms with most significant differences; 3) by ticking the boxes at the beginning of each line, any GO terms of the user’s interest could be selected.
3.Figure Output:Switch to the “graph” tab for the output figures. The figures could be edited such as the figure caption, colors of the graphs and legend description. Currently WEGO exports figures in SVG. Both graphs are automatically updated if the GO terms selected are changed by user. Sometimes different sets of GO terms are required for each graph, so in order to create desired graphs it might be necessary for the users to go back and reselect GO terms.
Reference:
1. Xia, Q., Zhou, Z., Lu, C., Cheng, D., Dai, F., & Li, B., et al. (2005). Xia q, zhou z, lu c, et al. a draft sequence for the genome of the domesticated silkworm (bombyx mori). science. Science, 306(5703), 1937-1940.
2. Yu, J. Yang H., et al.(2002) A draft sequence of the rice genome (Oryza sativa L. ssp. indica). Science 296(5565), 1937-1942.
3. Xia, Q., Guo, Y., Zhang, Z., Li, D., Xuan, Z., & Li, Z., et al. (2009). Complete resequencing of 40 genomes reveals domestication events and genes in silkworm (bombyx). Science, 326(5951), 433.
4. Wang, L., Tang, N., Gao, X., Chang, Z., Zhang, L., & Zhou, G., et al. (2017). Genome sequence of a rice pest, the white-backed planthopper (sogatella furcifera):. Gigascience, 6(1), 1-9.
5. Li, W., Zhang, L., Ding, Z., Wang, G., Zhang, Y., & Gong, H., et al. (2017). De novo, sequencing and comparative transcriptome analysis of the male and hermaphroditic flowers provide insights into the regulation of flower formation in andromonoecious taihangia rupestris. Bmc Plant Biology,17(1), 54.
6. Krosch, M. N., Bryant, L. M., & Vink, S. (2017). Differential gene expression of australiancricotopus draysoni(diptera: chironomidae) populations reveals seasonal association in detoxification gene regulation:. Scientific Reports, 7(1).
7. Pearce, S. L., Clarke, D. F., East, P. D., Elfekih, S., Gordon, K. H. J., & Jermiin, L. S., et al. (2017). Erratum to: genomic innovations, transcriptional plasticity and gene loss underlying the evolution and divergence of two highly polyphagous and invasive helicoverpa pest species. Bmc Biology, 15(1), 63.
8. Sheng, J., Zheng, X., Wang, J., Zeng, X., Zhou, F., & Jin, S., et al. (2017). Transcriptomics and proteomics reveal genetic and biological basis of superior biomass crop miscanthus. Scientific Reports, 7(1).
9. Wang, Z., Fang, B., Chen, J., Zhang, X., Luo, Z., & Huang, L., et al. (2010). De novo, assembly and characterization of root transcriptome using illumina paired-end sequencing and development of cssr markers in sweetpotato ( ipomoea batatas ). Bmc Genomics, 11(1), 726.
10. Jin, J., Sun, J. B., Park, J. S., Park, Y. K., Arasu, M. V., & Aldhabi, N. A., et al. (2017). De novo transcriptome analysis and glucosinolate profiling in watercress (nasturtium officinale r. br.). Bmc Genomics, 18(1), 401.