Gene-Sharing Networks Reveal Organizing Principles of Transcriptomes in <i>Arabidopsis</i> and Other Multicellular Organisms

Li, Song; Pandey, Sona; Gookin, Timothy E.; Zhao, Zhixin; Wilson, Liza; Assmann, Sarah M.

doi:10.1105/tpc.111.094748

Cited by 24 publications

(19 citation statements)

References 42 publications

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“…However, one important message of the present study is that because PCC-based coexpression analysis relies on trends inferred from gene/metabolite expression levels, certain tissue-level genemetabolite associations are difficult to capture via this approach because they take place only in a few of the analyzed tissues, thereby resulting in a poor coexpression output. Consistent with this finding, a recent study on gene-sharing analysis in plants and animals demonstrated that an approach that puts emphasis on gene expression tissue specificities is significantly more efficient in identifying functional gene clusters than one that relies on the complete tissue-level expression dataset (20). Our kurtosis analyses show that this inference is likely to be more pronounced when incorporating metabolomics as another -omics dimension, because up to 97% of detected secondary metabolites exhibit tissue-specific expression in only a few of the tissue atlases.…”

Section: Cross-tissue Intensity Variationsupporting

confidence: 67%

“…2A, Center). In an attempt to assess the degree of association of an idMS/MS toward one or several tissues statistically, we analyzed idMS/MS expression distribution across tissues using reduction of kurtosis as developed by Li et al (20). The kurtosis analysis measures expression distribution patterns rather than frequencies and skirts the restriction of the number of tissues with which a given idMS/MS can be associated.…”

Section: Large-scale Inference Of Idms/ms Tissue Specificity Reveals mentioning

confidence: 99%

“…To retrieve tissue idMS/MS-specific associations, we defined a tissue relative expression threshold Z (Z = 2) through the calculation of a reduction of kurtosis according to the rationale proposed by Li et al (20) (Fig. 2C and SI Appendix, Fig.…”

Section: Large-scale Inference Of Idms/ms Tissue Specificity Reveals mentioning

confidence: 99%

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Illuminating a plant’s tissue-specific metabolic diversity using computational metabolomics and information theory

Heiling

Baldwin

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

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Secondary metabolite diversity is considered an important fitness determinant for plants' biotic and abiotic interactions in nature. This diversity can be examined in two dimensions. The first one considers metabolite diversity across plant species. A second way of looking at this diversity is by considering the tissue-specific localization of pathways underlying secondary metabolism within a plant. Although these cross-tissue metabolite variations are increasingly regarded as important readouts of tissue-level gene function and regulatory processes, they have rarely been comprehensively explored by nontargeted metabolomics. As such, important questions have remained superficially addressed. For instance, which tissues exhibit prevalent signatures of metabolic specialization? Reciprocally, which metabolites contribute most to this tissue specialization in contrast to those metabolites exhibiting housekeeping characteristics? Here, we explore tissue-level metabolic specialization in Nicotiana attenuata, an ecological model with rich secondary metabolism, by combining tissue-wide nontargeted mass spectral data acquisition, information theory analysis, and tandem MS (MS/MS) molecular networks. This analysis was conducted for two different methanolic extracts of 14 tissues and deconvoluted 895 nonredundant MS/MS spectra. Using information theory analysis, anthers were found to harbor the most specialized metabolome, and most unique metabolites of anthers and other tissues were annotated through MS/MS molecular networks. Tissuemetabolite association maps were used to predict tissue-specific gene functions. Predictions for the function of two UDP-glycosyltransferases in flavonoid metabolism were confirmed by virus-induced gene silencing. The present workflow allows biologists to amortize the vast amount of data produced by modern MS instrumentation in their quest to understand gene function.secondary metabolism | mass spectrometry | metabolomics | information theory | Nicotiana attenuata P lants are elegant synthetic chemists making use of their metabolic prowess to produce complex blends of structurally diverse chemicals. Commonly quoted estimates state that plants produce somewhere on the order of 200,000 chemical structures. Secondary metabolites, also referred to as specialized metabolites or natural products, contribute to the largest fraction of this structural diversity. Compared with their counterparts in central metabolism (primary metabolites), secondary metabolite groups have diversified to the extreme in plant lineages, likely as a result of the multiple ecological roles they fulfill (1). The high degree of plasticity of secondary metabolism pathways is consistent with the existence of large families of metabolism-related genes such as cytochrome P450s and UDP-glycosyltransferases in plant genomes that can create structural and chemical modifications almost without limits. The majority of metabolic gene functions remain unknown, however, either because the metabolites that they produce are unknown or signi...

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Section: Cross-tissue Intensity Variationsupporting

confidence: 67%

Section: Large-scale Inference Of Idms/ms Tissue Specificity Reveals mentioning

confidence: 99%

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Illuminating a plant’s tissue-specific metabolic diversity using computational metabolomics and information theory

Heiling

Baldwin

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

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“…To gain more insight into the developmental context of GPA, we used the microarray data generated in our study to construct gene-sharing networks (Li et al, 2012) by adding publicly available datasets from various developmental stages and plant parts ( Fig. 3; datasets described by Ó' Maoiléidigh et al [2013]).…”

Section: Meristems But Not Whole Inflorescences Retain Basic Functionmentioning

confidence: 99%

“…Gene-sharing networks were constructed as described (Li et al, 2012), and edges between tissues were retained if they contained more genes than expected from the sizes of the respective nodes (as determined by a one-sided Fisher's exact test and P value cutoff , 1e-10). The resulting gene-sharing network was visualized using the Rgraphviz package (Hansen et al, 2015).…”

Section: Analyses Of Microarray Datasetsmentioning

confidence: 99%

Seed Production Affects Maternal Growth and Senescence in Arabidopsis

Wuest

Philipp²,

Guthörl³

et al. 2016

Plant Physiol.

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Correlative control (influence of one organ over another organ) of seeds over maternal growth is one of the most obvious phenotypic expressions of the trade-off between growth and reproduction. However, the underlying molecular mechanisms are largely unknown. Here, we characterize the physiological and molecular effects of correlative inhibition by seeds on Arabidopsis (Arabidopsis thaliana) inflorescences, i.e. global proliferative arrest (GPA) during which all maternal growth ceases upon the production of a given number of seeds. We observed transcriptional responses to growth-and branching-inhibitory hormones, and low mitotic activity in meristems upon GPA, but found that meristems retain their identity and proliferative potential. In shoot tissues, we detected the induction of stress-and senescence-related gene expression upon fruit production and GPA, and a drop in chlorophyll levels, suggestive of altered source-sink relationships between vegetative shoot and reproductive tissues. Levels of shoot reactive oxygen species, however, strongly decreased upon GPA, a phenomenon that is associated with bud dormancy in some perennials. Indeed, gene expression changes in arrested apical inflorescences after fruit removal resembled changes observed in axillary buds following release from apical dominance. This suggests that GPA represents a form of bud dormancy, and that dominance is gradually transferred from growing inflorescences to maturing seeds, allowing offspring control over maternal resources, simultaneously restricting offspring number. This would provide a mechanistic explanation for the constraint between offspring quality and quantity.

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Heterotrimeric G-Protein Signaling in Plants

Pandey

2019

Sensory Biology of Plants

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Gene-Sharing Networks Reveal Organizing Principles of Transcriptomes in Arabidopsis and Other Multicellular Organisms

Cited by 24 publications

References 42 publications

Illuminating a plant’s tissue-specific metabolic diversity using computational metabolomics and information theory

Illuminating a plant’s tissue-specific metabolic diversity using computational metabolomics and information theory

Seed Production Affects Maternal Growth and Senescence in Arabidopsis

Heterotrimeric G-Protein Signaling in Plants

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