Integration of transcriptomic and metabolic data reveals hub transcription factors involved in drought stress response in sunflower (Helianthus annuus L.)

Moschen, Sebastián; Rienzo, Julio A. Di; Higgins, Janet; Tohge, Takayuki; Watanabe, Mutsumi; González, Sergio; Rivarola, Máximo Lisandro; García‐García, Francisco; Dopazo, Joaquín; Hopp, H. Esteban; Hoefgen, Rainer; Fernie, Alisdair R.; Paniego, Norma; Fernández, Paula; Heinz, Ruth Amelia

doi:10.1007/s11103-017-0625-5

Cited by 57 publications

(39 citation statements)

References 94 publications

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“…However, few metabolomic data are available to date concerning both its primary and specialized metabolism. We now present one of the largest sets of primary metabolites in adult sunflower leaf, with absolute quantification of 38 metabolites and with several compounds not quantified by Moschen et al ( 2017 ) using GC–MS.…”

Section: Discussionmentioning

confidence: 99%

Metabolomic characterization of sunflower leaf allows discriminating genotype groups or stress levels with a minimal set of metabolic markers

et al. 2019

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Introduction Plant and crop metabolomic analyses may be used to study metabolism across genetic and environmental diversity. Complementary analytical strategies are useful for investigating metabolic changes and searching for biomarkers of response or performance. Methods and objectives The experimental material consisted in eight sunflower lines with two line status, four restorers (R, used as males) and four maintainers (B, corresponding to females) routinely used for sunflower hybrid varietal production, respectively to complement or maintain the cytoplasmic male sterility PET1. These lines were either irrigated at full soil capacity (WW) or submitted to drought stress (DS). Our aim was to combine targeted and non-targeted metabolomics to characterize sunflower leaf composition in order to investigate the effect of line status genotypes and environmental conditions and to find the best and smallest set of biomarkers for line status and stress response using a custom-made process of variables selection. Results Five hundred and eighty-eight metabolic variables were measured by using complementary analytical methods such as 1 H-NMR, MS-based profiles and targeted analyses of major metabolites. Based on statistical analyses, a limited number of markers were able to separate WW and DS samples in a more discriminant manner than previously published physiological data. Another metabolic marker set was able to discriminate line status. Conclusion This study underlines the potential of metabolic markers for discriminating genotype groups and environmental conditions. Their potential use for prediction is discussed. Electronic supplementary material The online version of this article (10.1007/s11306-019-1515-4) contains supplementary material, which is available to authorized users.

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Section: Discussionmentioning

confidence: 99%

Metabolomic characterization of sunflower leaf allows discriminating genotype groups or stress levels with a minimal set of metabolic markers

et al. 2019

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“…On the other hand, glycolysis and tricarboxylic acid cycle (TCA) metabolites as well as all the detected carbohydrates showed higher levels under drought conditions. Overall, these results indicated the putative role of these metabolites during stress response in sunflower [56].…”

Section: Metabolite Responses To Drought Stressmentioning

confidence: 52%

Plant Metabolomics in a Changing World: Metabolite Responses to Abiotic Stress Combinations

Jorge¹,

António²

2018

Plant, Abiotic Stress and Responses to Climate Change

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Climate change constitutes a real threat to the global landscape. Current climate models predict an increased occurrence of coastal floods associated to sea level rise and longterm droughts associated to changes in the intra-and inter-year rainfall variability. Under natural environmental conditions, plants are routinely exposed to abiotic stresses, and must develop different strategies to cope with this multitude of climate change factors. Mass spectrometry (MS)-based plant metabolomics approaches are finding an increasing number of applications to investigate the molecular and biochemical mechanisms that underlie plant responses to changing environments. These studies provide a promising basis for facilitating our understanding of the plant's flexibility to reconfigure central metabolic pathways (i.e., carbon, nitrogen and energy metabolism) as well as the degree by which plants tolerate and/or are susceptible to a climate change scenario. In this chapter, we will provide an update on the recent MS-based metabolomics strategies to study plant responses to drought, salt and heat stress as well as combinations thereof. We will describe how these stresses activate and coordinate several different signalling pathways, for example, through the synthesis of osmolytes.

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“…WGCNA is an effective method for co-expression network analysis, which can speci cally screen out coexpression modules with high biological signi cance to target traits. It has been proved to be an e cient data mining method in rice [45], Brassica rapa [46], and sun ower [47]. In this study, the WGCNA method was used to construct a weighted gene co-expression network based on the sequencing data of 28 drought stress transcriptomes of Jerusalem artichoke.…”

Section: Wgcna Analysismentioning

confidence: 99%

Transcriptome changes induced by drought stress in Jerusalem artichoke (Helianthus tuberosus L.) and weighted gene co-expression network analysis (WGCNA)

Yang¹,

Wang²,

Zhong³

et al. 2020

Preprint

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Background: Jerusalem artichoke (Helianthus tuberosus L.) is strongly resistant to stress and an important plant used for ecological management in northern China in recent years. Currently, Jerusalem artichoke has been widely planted in the area around Qinghai Lake in Qinghai Province, China. Jerusalem artichoke can not only prevent land desertification but also has maintain most of its level of production. However, there is little research on the mechanism of drought resistance of Jerusalem artichoke.Results: We conducted transcriptome sequencing under drought stress and normal watering treatment for two varieties, QY1 and QY3, with differing degrees of drought tolerance. In the three stress periods of QY1 and QY3, 5,613, 12,985 and 24,923 differentially expressed genes (DEGs) were identified, respectively. GO analysis showed that there were more DEGs in QY1 than in QY3, but there were more up-regulated genes in QY3 than in QY1. Based on an additional analysis of the metabolic pathways under drought stress using MapMan, the most different types of metabolism included secondary metabolism, light reaction metabolism and cell wall. The up-regulated genes in QY3 were significantly more prevalent than those in QY1 and were primarily concentrated in flavor IDS, phenylpropanoids, and the shikimate and terpenoids pathway. As a whole, QY1 and QY3 both had a large number of up-regulated genes in the flavor pathway. In addition, the gene analysis of the ABA key metabolic pathway showed that QY3 had more genes in NAC and WRKY than QY1. A weighted gene co-expression network was constructed and divided into modules. By specifically analyzing the expressed modules, four modules were found to have the highest correlation with drought. Further research on the genes revealed that all 16 genes related to histone, ABA and protein kinase were the most significant in these pathways.Conclusions: In summary, these findings represent the first RNA-Seq analysis of drought stress in Jerusalem artichoke, which is of substantial significance to explore the function of drought resistance in Jerusalem artichoke and the unearthing of related genes.

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Integration of transcriptomic and metabolic data reveals hub transcription factors involved in drought stress response in sunflower (Helianthus annuus L.)

Cited by 57 publications

References 94 publications

Metabolomic characterization of sunflower leaf allows discriminating genotype groups or stress levels with a minimal set of metabolic markers

Metabolomic characterization of sunflower leaf allows discriminating genotype groups or stress levels with a minimal set of metabolic markers

Plant Metabolomics in a Changing World: Metabolite Responses to Abiotic Stress Combinations

Transcriptome changes induced by drought stress in Jerusalem artichoke (Helianthus tuberosus L.) and weighted gene co-expression network analysis (WGCNA)

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