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      Integrated analyses of transcriptome and metabolome provides new insights into the primary and secondary metabolism in response to nitrogen deficiency and soil compaction stress in peanut roots

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          Abstract

          Peanut ( Arachis hypogaea L.) is an important oil crop globally because of its high edible and economic value. However, its yield and quality are often restricted by certain soil factors, especially nitrogen (N) deficiency, and soil compaction. To explore the molecular mechanisms and metabolic basis behind the peanut response to N deficiency and soil compaction stresses, transcriptome and metabolome analyses of peanut root were carried out. The results showed that N deficiency and soil compaction stresses clearly impaired the growth and development of peanut's aboveground and underground parts, as well as its root nodulation. A total of 18645 differentially expressed genes (DEGs) and 875 known differentially accumulated metabolites (DAMs) were identified in peanut root under differing soil compaction and N conditions. The transcriptome analysis revealed that DEGs related to N deficiency were mainly enriched in “amino acid metabolism”, “starch and sucrose metabolism”, and “TCA cycle” pathways, while DEGs related to soil compaction were mainly enriched in “oxidoreductase activity”, “lipids metabolism”, and “isoflavonoid biosynthesis” pathways. The metabolome analysis also showed significant differences in the accumulation of metabolisms in these pathways under different stress conditions. Then the involvement of genes and metabolites in pathways of “amino acid metabolism”, “TCA cycle”, “lipids metabolism”, and “isoflavonoid biosynthesis” under different soil compaction and N deficiency stresses were well discussed. This integrated transcriptome and metabolome analysis study enhances our mechanistic knowledge of how peanut plants respond to N deficiency and soil compaction stresses. Moreover, it provides new leads to further investigate candidate functional genes and metabolic pathways for use in improving the adaptability of peanut to abiotic stress and accelerating its breeding process of new stress-resistant varieties.

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          Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method.

          The two most commonly used methods to analyze data from real-time, quantitative PCR experiments are absolute quantification and relative quantification. Absolute quantification determines the input copy number, usually by relating the PCR signal to a standard curve. Relative quantification relates the PCR signal of the target transcript in a treatment group to that of another sample such as an untreated control. The 2(-Delta Delta C(T)) method is a convenient way to analyze the relative changes in gene expression from real-time quantitative PCR experiments. The purpose of this report is to present the derivation, assumptions, and applications of the 2(-Delta Delta C(T)) method. In addition, we present the derivation and applications of two variations of the 2(-Delta Delta C(T)) method that may be useful in the analysis of real-time, quantitative PCR data. Copyright 2001 Elsevier Science (USA).
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            HMDB 3.0—The Human Metabolome Database in 2013

            The Human Metabolome Database (HMDB) (www.hmdb.ca) is a resource dedicated to providing scientists with the most current and comprehensive coverage of the human metabolome. Since its first release in 2007, the HMDB has been used to facilitate research for nearly 1000 published studies in metabolomics, clinical biochemistry and systems biology. The most recent release of HMDB (version 3.0) has been significantly expanded and enhanced over the 2009 release (version 2.0). In particular, the number of annotated metabolite entries has grown from 6500 to more than 40 000 (a 600% increase). This enormous expansion is a result of the inclusion of both ‘detected’ metabolites (those with measured concentrations or experimental confirmation of their existence) and ‘expected’ metabolites (those for which biochemical pathways are known or human intake/exposure is frequent but the compound has yet to be detected in the body). The latest release also has greatly increased the number of metabolites with biofluid or tissue concentration data, the number of compounds with reference spectra and the number of data fields per entry. In addition to this expansion in data quantity, new database visualization tools and new data content have been added or enhanced. These include better spectral viewing tools, more powerful chemical substructure searches, an improved chemical taxonomy and better, more interactive pathway maps. This article describes these enhancements to the HMDB, which was previously featured in the 2009 NAR Database Issue. (Note to referees, HMDB 3.0 will go live on 18 September 2012.).
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              Primary metabolism and plant defense--fuel for the fire.

              Plants have the ability to recognize and respond to a multitude of microorganisms. Recognition of pathogens results in a massive reprogramming of the plant cell to activate and deploy defense responses to halt pathogen growth. Such responses are associated with increased demands for energy, reducing equivalents, and carbon skeletons that are provided by primary metabolic pathways. Although pathogen recognition and downstream resistance responses have been the focus of major study, an intriguing and comparatively understudied phenomenon is how plants are able to recruit energy for the defense response. To that end, this review will summarize current research on energy-producing primary metabolism pathways and their role in fueling the resistance response.
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                Author and article information

                Contributors
                Journal
                Front Plant Sci
                Front Plant Sci
                Front. Plant Sci.
                Frontiers in Plant Science
                Frontiers Media S.A.
                1664-462X
                28 September 2022
                2022
                : 13
                : 948742
                Affiliations
                Chinese National Peanut Engineering Research Center, Shandong Peanut Research Institute, Shandong Academy of Agricultural Sciences , Qingdao, China
                Author notes

                Edited by: Tingting Chen, South China Agricultural University, China

                Reviewed by: Mohd. Kamran Khan, Selcuk University, Turkey; Xinlei Yang, Hebei Agricultural University, China

                *Correspondence: Pu Shen shenpu2022@ 123456126.com

                This article was submitted to Plant Breeding, a section of the journal Frontiers in Plant Science

                Article
                10.3389/fpls.2022.948742
                9554563
                36247623
                e37a4fe3-f644-4059-b6e6-367c287a3130
                Copyright © 2022 Yang, Wu, Liang, Yin and Shen.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 20 May 2022
                : 25 July 2022
                Page count
                Figures: 10, Tables: 0, Equations: 0, References: 62, Pages: 18, Words: 10967
                Categories
                Plant Science
                Original Research

                Plant science & Botany
                peanut root,soil compaction stress,nitrogen deficiency,metabolome,transcriptome

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