Bioinformatics Center, Chang Gung University, Taoyuan, Taiwan.
Molecular Medicine Research Center, Chang Gung University, Taoyuan, Taiwan.
Sci Rep. 2017 Sep 5;7(1):10430. doi: 10.1038/s41598-017-10952-4.
Along with the constant improvement in high-throughput sequencing technology, an increasing number of transcriptome sequencing projects are carried out in organisms without decoded genome information and even on environmental biological samples. To study the biological functions of novel transcripts, the very first task is to identify their potential functions. We present a web-based annotation tool, FunctionAnnotator, which offers comprehensive annotations, including GO term assignment, enzyme annotation, domain/motif identification and predictions for subcellular localization. To accelerate the annotation process, we have optimized the computation processes and used parallel computing for all annotation steps. Moreover, FunctionAnnotator is designed to be versatile, and it generates a variety of useful outputs for facilitating other analyses. Here, we demonstrate how FunctionAnnotator can be helpful in annotating non-model organisms. We further illustrate that FunctionAnnotator can estimate the taxonomic composition of environmental samples and assist in the identification of novel proteins by combining RNA-Seq data with proteomics technology. In summary, FunctionAnnotator can efficiently annotate transcriptomes and greatly benefits studies focusing on non-model organisms or metatranscriptomes. FunctionAnnotator, a comprehensive annotation web-service tool, is freely available online at: http://fa.cgu.edu.tw/ . This new web-based annotator will shed light on field studies involving organisms without a reference genome.
随着高通量测序技术的不断提高,越来越多的转录组测序项目在没有解码基因组信息的生物中进行,甚至在环境生物样本上进行。为了研究新转录本的生物学功能,首先要确定它们的潜在功能。我们提出了一个基于网络的注释工具 FunctionAnnotator,它提供了全面的注释,包括 GO 术语分配、酶注释、结构域/基序识别和亚细胞定位预测。为了加速注释过程,我们优化了计算过程,并在所有注释步骤中使用并行计算。此外,FunctionAnnotator 设计为通用型,它生成各种有用的输出,以方便其他分析。在这里,我们展示了 FunctionAnnotator 如何有助于注释非模式生物。我们进一步说明,FunctionAnnotator 可以通过将 RNA-Seq 数据与蛋白质组学技术相结合,估计环境样本的分类组成,并帮助鉴定新的蛋白质。总之,FunctionAnnotator 可以有效地注释转录组,并极大地促进了非模式生物或宏转录组的研究。FunctionAnnotator 是一个全面的注释网络服务工具,可在以下网址免费获得:http://fa.cgu.edu.tw/。这个新的基于网络的注释器将为涉及无参考基因组的生物体的现场研究提供帮助。