Short-term transcriptomic analysis at organ scale reveals candidate genes involved in low N responses in NUE-contrasting tomato genotypes

Abstract

BackgroundUnderstanding the complex regulatory network underlying plant nitrogen (N) responses associated with high Nitrogen Use Efficiency (NUE) is one of the main challenges for sustainable cropping systems. Nitrate (NO3-), acting as both an N source and a signal molecule, provokes very fast transcriptome reprogramming, allowing plants to adapt to its availability. These changes are genotype- and tissue-specific; thus, the comparison between contrasting genotypes is crucial to uncovering high NUE mechanisms.MethodsHere, we compared, for the first time, the spatio-temporal transcriptome changes in both root and shoot of two NUE contrasting tomato genotypes, Regina Ostuni (high-NUE) and UC82 (low-NUE), in response to short-term (within 24 h) low (LN) and high (HN) NO3- resupply. ResultsUsing time-series transcriptome data (0, 8, and 24 h), we identified 395 and 482 N-responsive genes differentially expressed (DEGs) between RO and UC82 in shoot and root, respectively. Protein kinase signaling plant hormone signal transduction, and phenylpropanoid biosynthesis were the main enriched metabolic pathways in shoot and root, respectively, and were upregulated in RO compared to UC82. Interestingly, several N transporters belonging to NRT and NPF families, such as NRT2.3, NRT2.4, NPF1.2, and NPF8.3, were found differentially expressed between RO and UC82 genotypes, which might explain the contrasting NUE performances. Transcription factors (TFs) belonging to several families, such as ERF, LOB, GLK, NFYB, ARF, Zinc-finger, and MYB, were differentially expressed between genotypes in response to LN. A complementary Weighted Gene Co-expression Network Analysis (WGCNA) allowed the identification of LN-responsive co-expression modules in RO shoot and root. The regulatory network analysis revealed candidate genes that might have key functions in short-term LN regulation. In particular, an asparagine synthetase (ASNS), a CBL-interacting serine/threonine-protein kinase 1 (CIPK1), a cytokinin riboside 5’-monophosphate phosphoribohydrolase (LOG8), a glycosyltransferase (UGT73C4), and an ERF2 were identified in the shoot, while an LRR receptor-like serine/threonine-protein kinase (FEI1) and two TFs NF-YB5 and LOB37 were identified in the root. DiscussionOur results revealed potential candidate genes that independently and/or concurrently may regulate short-term low-N response, suggesting a key role played by cytokinin and ROS balancing in early LN regulation mechanisms adopted by the N-use efficient genotype RO.

Integration of QTL and transcriptome approaches for the identification of genes involved in tomato response to nitrogen deficiency

“…Overall, they identified 7,667 and 6,015 unique DEGs in shoot and root, respectively. In this study, they identified a number of DEGs consistent with our study but their results also underlined the importance of considering the kinetic of gene expression (Sunseri et al 2023). One of the hypotheses for our results might be that the long duration of the stress ended homogenising the plant's responses or allowed compensation by other unknown mechanisms.…”

“…The transcriptome response of 35-days plant of the cultivar Moneymaker was assessed when cultivated with a solution containing 4 mM (stress) or 8 mM (control) of nitrogen (Renau-Morata et al, 2021). The other study focused on the short term (8h - 24h) transcriptome response differences in shoot and root between a pair of high-NUE (Regina Ostuni) and low-NUE (UC82) cultivars (Sunseri et al, 2023). The plants were grown for 20 days and then stressed (0.5 mM N) or maintained in controlled conditions (10 mM).…”

“…However, at low N, Solyc09g090570 was up-regulated in fruits and down-regulated in leaves. Sunseri et al (2023) identified 297 and 154 DEGs in response to N treatment in shoot and root, respectively, which must be compared to the 923 (154) DEGs for the genotype by treatment interaction, 5,102 (3,800) DEGs for the time x treatment interaction and finally 5,480 (4,054) DEGs for the genotype x treatment x time interaction. Overall, they identified 7,667 and 6,015 unique DEGs in shoot and root, respectively.…”

“…Reverse genetic approaches have been used to characterise several genes involved in N uptake (Fu et al, 2015), assimilation (Vallarino et al 2022) or remobilization (Cao et al, 2022). In addition, many transcriptomic (Renau-Morata et al 2021, Sunseri et al 2023), proteomic (Xun et al, 2020) and metabolomic (Urbanczyk-Wochniak and Fernie, 2005; Larbat et al, 2014; Sung et al, 2015) approaches have identified differentially expressed genes and metabolic pathways involved in nitrogen metabolisms. Previous studies made progress in identifying nitrogen uptake efficiency (NUpE) QTLs in tomato.…”

Bulk segregant analysis of tomato to identify polymorphism associated with tomato-Phytoplasma solani interaction using RNA-sequencing data

“…Solyc07g008240 was found downregulated which is responsible for scavenging NO [94]. Solyc02g090210 is reported for low nitrogen tolerance [59] and it was downregulated while Solyc03g026040 is involved in tomato response to low nitrogen [42,43] and it was upregulated. Solyc02g076980 reported for resistance to Cladosporium fulvum [40] and Solyc03g095650 involved in plant resistance, such as Ralstonia solanacearum infection in tomato, Pseudomonas syringae infection in Arabidopsis and Phytophthora parasitica infection in tomato [44].…”