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

Research output: Contribution to journalArticlepeer-review

45 Scopus citations

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. Significance Statement In the current study we have effectively identified loci for branched chain amino acid, serene, glycine, threonine and proline metabolism for seeds of a tomato Introgression Line mapping population. We did so by applying a combined correlation based network approach with quantitative trait locus mapping.

Original languageEnglish
Pages (from-to)121-133
Number of pages13
JournalPlant Journal
Volume81
Issue number1
DOIs
StatePublished - 1 Jan 2015

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

ASJC Scopus subject areas

  • Genetics
  • Plant Science
  • Cell Biology

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