TomAP: A multi-omics data analysis platform for advancing functional genomics research in tomatoes

Yaxin Cao , Jiajie She , Zhongqiu Li , Yue Liu, Tian Tian, Qi You, Hengyu Yan, Xuelian Ma, Wenying Xu, Zhen Su
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Abstract

Tomato (Solanum lycopersicum), belonging to the Solanaceae family, holds the distinction of being the second most important vegetable crop on a global scale. As a model plant renowned for its insights into fruit ripening and disease resistance, the collaborative analysis of multi-omics data takes on an indispensable role in advancing the flavor and genetic traits of this vital crop. In our endeavor, we have seamlessly integrated a staggering 343 transcriptome datasets to create a co-expression network, including global network and conditional network, offering a expression view for multi-dimensional insight into gene expression patterns. Simultaneously, we harnessed the power of 136 epigenomic datasets to define 35 distinct chromatin states, employing the sophisticated ChromHMM algorithm. Our pursuit of holistic understanding culminated in the fusion of multi-omics data, encompassing the genome, transcriptome, and epigenome. This comprehensive approach extends to functional identification, offering invaluable insights into the intricate web of biological interactions. Our offering goes beyond mere data analysis; it presents a platform for comparative network exploration, enabling users to draw meaningful comparisons between two networks. Additionally, we have thoughtfully included extensive annotation for gene sets, encompassing GO terms, KEGG pathways, plantCyc, gene families, literature references, miRNA targets, and functional modules. The culmination of our efforts is the Tomato multi-omics data Analysis Platform (TomAP, http://bioinformatics.cau.edu.cn/TomAP/). The co-expression network and the defined chromatin states open up a realm of possibilities, not only for investigating the commonalities and variations among co-expressed genes in the context of chromatin states but also for comparative functional assessments of orthologs across species. Our aspiration is that TomAP will become avaluable resource for the research community, enabling the identification of functional genes or modules that underpin critical tomato agronomic traits.

TomAP:推进番茄功能基因组学研究的多组学数据分析平台
番茄(Solanum lycopersicum)属于茄科,是全球第二重要的蔬菜作物。作为一种以洞察果实成熟和抗病性而闻名的模式植物,多组学数据的合作分析在促进这种重要作物的风味和遗传性状方面发挥着不可或缺的作用。在我们的工作中,我们无缝整合了多达 343 个转录组数据集,创建了共表达网络,包括全局网络和条件网络,为多维度洞察基因表达模式提供了表达视图。同时,我们利用 136 个表观基因组数据集的力量,采用复杂的 ChromHMM 算法,定义了 35 种不同的染色质状态。我们对整体理解的追求最终体现在多组学数据的融合上,包括基因组、转录组和表观基因组。这种全面的方法延伸到了功能鉴定,为错综复杂的生物相互作用网络提供了宝贵的见解。我们提供的不仅仅是数据分析,它还提供了一个比较网络探索平台,使用户能够在两个网络之间进行有意义的比较。此外,我们还贴心地为基因组添加了大量注释,包括 GO 术语、KEGG 通路、plantCyc、基因家族、文献参考、miRNA 靶标和功能模块。番茄多组学数据分析平台(TomAP,http://bioinformatics.cau.edu.cn/TomAP/)是我们努力的结晶。共表达网络和已定义的染色质状态开辟了一个可能性的领域,不仅可以在染色质状态的背景下研究共表达基因之间的共性和变异,还可以对不同物种的同源物进行比较功能评估。我们希望 TomAP 能够成为研究界的宝贵资源,帮助鉴定支撑番茄关键农艺性状的功能基因或模块。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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