DiatOmicBase 是一个以基因为中心的平台,用于挖掘硅藻基因组中的功能性 omics 数据

Emilie Villar, Nathanael Zweig, Pierre Vincens, Helena Cruz de Carvalho, Carole Duchene, Shun Liu, Raphael Monteil, Richard G Dorrell, Michele Fabris, Klaas Vandepoele, Chris Bowler, Angela Falciatore
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摘要

硅藻是水生环境中常见的微藻类。在过去的 20 年里,由于基因组和遗传资源的可用性,硅藻物种(如三角藻)已成为探索从进化到细胞生物学、(生态)生理学和生物技术等课题的宝贵实验模型系统。自 2008 年首次基因组测序以来,基于 RNA-Seq 和蛋白质组学、表观基因组和生态型变异分析的基因组数据集层出不穷。遗憾的是,这些由不同实验室生成的资源通常格式各异,难以获取和分析。在此,我们介绍 DiatOmicBase,这是一个基因组门户网站,收集了来自三角柱虫和其他两种硅藻的全面的 omics 资源,以方便探索分散的公共数据集,并在现有技术的基础上设计新的实验。DiatOmicBase 提供基因注释、转录组图谱和基因组浏览器,其中包括生态型变异、组蛋白和甲基化标记、转座元件、非编码 RNA 和 RNA-Seq 实验的读密度。我们开发了一个半自动更新的转录组模块,用于探索公开的 RNA-Seq 实验和用户的私人数据集。利用基因水平的表达数据,用户可以进行探索性数据分析、差异表达、通路分析、双聚类和共表达网络分析。用户可以创建热图,直观显示选定基因子集的预计算比较结果。还可自动访问硅藻比较和功能基因组学的其他生物信息资源和工具。我们重点介绍了目前集中在三尖杉上的资源,并通过几个例子展示了 DiatOmicBase 如何加强硅藻分子研究,使这些生物能够为广大研究社区所利用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
DiatOmicBase, a gene-centered platform to mine functional omics data across diatom genomes
Diatoms are prominent microalgae found in all aquatic environments. Over the last 20 years, thanks to the availability of genomic and genetic resources, diatom species such as Phaeodactylum tricornutum have emerged as valuable experimental model systems for exploring topics ranging from evolution to cell biology, (eco)physiology and biotechnology. Since the first genome sequencing in 2008, numerous genome-enabled datasets have been generated, based on RNA-Seq and proteomics, epigenomes, and ecotype variant analysis. Unfortunately, these resources, generated by various laboratories, are often in disparate formats and challenging to access and analyze. Here we present DiatOmicBase, a genome portal gathering comprehensive omics resources from P. tricornutum and two other diatoms to facilitate the exploration of dispersed public datasets and the design of new experiments based on the prior-art. DiatOmicBase provides gene annotations, transcriptomic profiles and a genome browser with ecotype variants, histone and methylation marks, transposable elements, non-coding RNAs, and read densities from RNA-Seq experiments. We developed a semi-automatically updated transcriptomic module to explore both publicly available RNA-Seq experiments and users private datasets. Using gene-level expression data, users can perform exploratory data analysis, differential expression, pathway analysis, biclustering, and co-expression network analysis. Users can create heatmaps to visualize precomputed comparisons for selected gene subsets. Automatic access to other bioinformatic resources and tools for diatom comparative and functional genomics is also provided. Focusing on the resources currently centralized for P. tricornutum, we showcase several examples of how DiatOmicBase strengthens molecular research on diatoms, making these organisms accessible to a broad research community.
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