Institute of Tropical Plant Sciences, National Cheng Kung University, Tainan 70101, Taiwan.
BMC Genomics. 2014 Mar 14;15(1):196. doi: 10.1186/1471-2164-15-196.
Algae are important non-vascular plants that have many research applications, including high species diversity, biofuel sources, and adsorption of heavy metals and, following processing, are used as ingredients in health supplements. The increasing availability of next-generation sequencing (NGS) data for algae genomes and transcriptomes has made the development of an integrated resource for retrieving gene expression data and metabolic pathway essential for functional analysis and systems biology. In a currently available resource, gene expression profiles and biological pathways are displayed separately, making it impossible to easily search current databases to identify the cellular response mechanisms. Therefore, in this work the novel AlgaePath database was developed to retrieve transcript abundance profiles efficiently under various conditions in numerous metabolic pathways.
AlgaePath is a web-based database that integrates gene information, biological pathways, and NGS datasets for the green algae Chlamydomonas reinhardtii and Neodesmus sp. UTEX 2219-4. Users can search this database to identify transcript abundance profiles and pathway information using five query pages (Gene Search, Pathway Search, Differentially Expressed Genes (DEGs) Search, Gene Group Analysis, and Co-expression Analysis). The transcript abundance data of 45 and four samples from C. reinhardtii and Neodesmus sp. UTEX 2219-4, respectively, can be obtained directly on pathway maps. Genes that are differentially expressed between two conditions can be identified using Folds Search. The Gene Group Analysis page includes a pathway enrichment analysis, and can be used to easily compare the transcript abundance profiles of functionally related genes on a map. Finally, the Co-expression Analysis page can be used to search for co-expressed transcripts of a target gene. The results of the searches will provide a valuable reference for designing further experiments and for elucidating critical mechanisms from high-throughput data.
AlgaePath is an effective interface that can be used to clarify the transcript response mechanisms in different metabolic pathways under various conditions. Importantly, AlgaePath can be mined to identify critical mechanisms based on high-throughput sequencing. To our knowledge, AlgaePath is the most comprehensive resource for integrating numerous databases and analysis tools in algae. The system can be accessed freely online at http://algaepath.itps.ncku.edu.tw.
藻类是重要的非维管束植物，具有许多研究应用，包括物种多样性高、生物燃料来源和重金属吸附等。经过加工后，藻类被用作保健品的成分。随着藻类基因组和转录组的下一代测序（NGS）数据的不断增加，开发一个用于检索基因表达数据和代谢途径的综合资源对于功能分析和系统生物学至关重要。在现有的资源中，基因表达谱和生物途径是分开显示的，因此不可能轻松地在当前数据库中搜索以识别细胞反应机制。因此，在这项工作中，开发了新型的 AlgaePath 数据库，以在众多代谢途径的各种条件下高效检索转录丰度谱。
AlgaePath 是一个基于网络的数据库，它集成了绿藻莱茵衣藻和 Neodesmus sp. UTEX 2219-4 的基因信息、生物途径和 NGS 数据集。用户可以使用五个查询页面（基因搜索、途径搜索、差异表达基因（DEGs）搜索、基因组分析和共表达分析）在该数据库中搜索以识别转录丰度谱和途径信息。可以直接在途径图谱上获取来自 C. reinhardtii 和 Neodesmus sp. UTEX 2219-4 的 45 个和 4 个样本的转录丰度数据。使用 Folds Search 可以识别两个条件之间差异表达的基因。基因组分析页面包括途径富集分析，可用于轻松在图谱上比较功能相关基因的转录丰度谱。最后，共表达分析页面可用于搜索目标基因的共表达转录本。搜索结果将为设计进一步的实验和阐明高通量数据中的关键机制提供有价值的参考。
AlgaePath 是一个有效的接口，可以用于阐明不同代谢途径在不同条件下的转录反应机制。重要的是，AlgaePath 可以用于挖掘基于高通量测序的关键机制。据我们所知，AlgaePath 是整合藻类中众多数据库和分析工具的最全面资源。该系统可免费在线访问，网址为 http://algaepath.itps.ncku.edu.tw。
