Literature DB >> 25359542

Combined correlation-based network and mQTL analyses efficiently identified loci for branched-chain amino acid, serine to threonine, and proline metabolism in tomato seeds.

David Toubiana1, Albert Batushansky, Oren Tzfadia, Federico Scossa, Asif Khan, Simon Barak, Daniel Zamir, Alisdair Robert Fernie, Zoran Nikoloski, Aaron Fait.   

Abstract

Correlation-based network analysis (CNA) of the metabolic profiles of seeds of a tomato introgression line mapping population revealed a clique of proteinogenic amino acids: Gly, Ile, Pro, Ser, Thr, and Val. Correlations between profiles of these amino acids exhibited a statistically significant average correlation coefficient of 0.84 as compared with an average correlation coefficient of 0.39 over the 16 119 other metabolite cliques containing six metabolites. In silico removal of cliques was used to quantify their importance in determining seminal network properties, highlighting the strong effects of the amino acid clique. Quantitative trait locus analysis revealed co-localization for the six amino acids on chromosome 2, 4 and 10. Sequence analysis identified a unique set of 10 genes on chromosome 2 only, which were associated with amino acid metabolism and specifically the metabolism of Ser-Gly and their conversion into branched-chain amino acids. Metabolite profiling of a set of sublines, with introgressions on chromosome 2, identified a significant change in the abundance of the six amino acids in comparison with M82. Expression analysis of candidate genes affecting Ser metabolism matched the observation from the metabolite data, suggesting a coordinated behavior of the level of these amino acids at the genetic level. Analysis of transcription factor binding sites in the promoter regions of the identified genes suggested combinatorial response to light and the circadian clock.
© 2014 The Authors The Plant Journal © 2014 John Wiley & Sons Ltd.

Entities:  

Keywords:  Solanum lycopersicum cv. M82; Solanum pennellii accession LA0716; amino acid regulator genes; correlation-based network analysis; metabolic profiling; network properties; sequence analysis; serine-glycine metabolism; tomato introgression line

Mesh:

Substances:

Year:  2014        PMID: 25359542     DOI: 10.1111/tpj.12717

Source DB:  PubMed          Journal:  Plant J        ISSN: 0960-7412            Impact factor:   6.417


  18 in total

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Journal:  Plant Cell       Date:  2015-07-17       Impact factor: 11.277

2.  Network-Guided GWAS Improves Identification of Genes Affecting Free Amino Acids.

Authors:  Ruthie Angelovici; Albert Batushansky; Nicholas Deason; Sabrina Gonzalez-Jorge; Michael A Gore; Aaron Fait; Dean DellaPenna
Journal:  Plant Physiol       Date:  2016-11-21       Impact factor: 8.340

3.  Observability of Plant Metabolic Networks Is Reflected in the Correlation of Metabolic Profiles.

Authors:  Kevin Schwahn; Anika Küken; Daniel J Kliebenstein; Alisdair R Fernie; Zoran Nikoloski
Journal:  Plant Physiol       Date:  2016-08-26       Impact factor: 8.340

4.  Elucidation of salt-tolerance metabolic pathways in contrasting rice genotypes and their segregating progenies.

Authors:  Pragya Mishra; Vagish Mishra; Teruhiro Takabe; Vandna Rai; Nagendra Kumar Singh
Journal:  Plant Cell Rep       Date:  2016-03-18       Impact factor: 4.570

5.  The Contribution of Metabolomics to Systems Biology: Current Applications Bridging Genotype and Phenotype in Plant Science.

Authors:  Marina C M Martins; Valeria Mafra; Carolina C Monte-Bello; Camila Caldana
Journal:  Adv Exp Med Biol       Date:  2021       Impact factor: 2.622

6.  Combined Use of Genome-Wide Association Data and Correlation Networks Unravels Key Regulators of Primary Metabolism in Arabidopsis thaliana.

Authors:  Si Wu; Saleh Alseekh; Álvaro Cuadros-Inostroza; Corina M Fusari; Marek Mutwil; Rik Kooke; Joost B Keurentjes; Alisdair R Fernie; Lothar Willmitzer; Yariv Brotman
Journal:  PLoS Genet       Date:  2016-10-19       Impact factor: 5.917

7.  Environmental and genetic effects on tomato seed metabolic balance and its association with germination vigor.

Authors:  Leah Rosental; Adi Perelman; Noa Nevo; David Toubiana; Talya Samani; Albert Batushansky; Noga Sikron; Yehoshua Saranga; Aaron Fait
Journal:  BMC Genomics       Date:  2016-12-19       Impact factor: 3.969

Review 8.  Beyond the Canon: Within-Plant and Population-Level Heterogeneity in Jasmonate Signaling Engaged by Plant-Insect Interactions.

Authors:  Dapeng Li; Ian T Baldwin; Emmanuel Gaquerel
Journal:  Plants (Basel)       Date:  2016-03-16

9.  Correlation-Based Network Analysis of Metabolite and Enzyme Profiles Reveals a Role of Citrate Biosynthesis in Modulating N and C Metabolism in Zea mays.

Authors:  David Toubiana; Wentao Xue; Nengyi Zhang; Karl Kremling; Amit Gur; Shai Pilosof; Yves Gibon; Mark Stitt; Edward S Buckler; Alisdair R Fernie; Aaron Fait
Journal:  Front Plant Sci       Date:  2016-07-12       Impact factor: 5.753

Review 10.  Expanding Omics Resources for Improvement of Soybean Seed Composition Traits.

Authors:  Juhi Chaudhary; Gunvant B Patil; Humira Sonah; Rupesh K Deshmukh; Tri D Vuong; Babu Valliyodan; Henry T Nguyen
Journal:  Front Plant Sci       Date:  2015-11-24       Impact factor: 5.753

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