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A subset of highly responsive transcription factors upon tomato infection by pepino mosaic virus

生物 拟南芥 病理系统 遗传学 基因 生物信息学 转录组 转录因子 植物病毒 计算生物学 基因表达 病毒 突变体
作者
Dikran Tsitsekian,Γεράσιμος Δάρας,Dimitris Templalexis,Fengoula Avgeri,L. Lotos,C. G. Orfanidou,Vardis Ntoukakis,Varvara I. Maliogka,Stamatis Rigas
出处
期刊:Plant Biology [Wiley]
卷期号:25 (4): 529-540 被引量:3
标识
DOI:10.1111/plb.13515
摘要

Plants have evolved well-tuned surveillance systems, including complex defence mechanisms, to constrain pathogens. TFs are master regulators of host molecular responses against plant pathogens. While PepMV constitutes a major threat to the global tomato production, there is still a lack of information on the key TFs that regulate host responses to this virus. A combinatorial research approach was applied relying on tomato transcriptome analysis, RT-qPCR validation, phylogenetic classification, comparative analysis of structural features, cis-regulatory element mining and in silico co-expression analysis to identify a set of 11 highly responsive TFs involved in the regulation of host responses to PepMV. An endemic PepMV isolate, generating typical mosaic symptoms, modified expression of ca. 3.3% of tomato genes, resulting in 1,120 DEGs. Functional classification of 502 upregulated DEGs revealed that photosynthesis, carbon fixation and gene silencing were widely affected, whereas 618 downregulated genes had an impact mainly on plant defence and carotenoid biosynthesis. Strikingly, all 11 highly responsive TFs carried abiotic stress response cis-regulatory elements, whereas five of them were better aligned with rice than with Arabidopsis gene homologues, suggesting that plant responses against viruses may predate divergence into monocots and dicots. Interestingly, tomato C2H2 family TFs, ZAT1-like and ZF2, may have distinct roles in plant defence due to opposite response patterns, similar to their Arabidopsis ZAT10 and ZAT12 homologues. These highly responsive TFs provide a basis to study in-depth molecular responses of the tomato-PepMV pathosystem, providing a perspective to better comprehend viral infections.

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