Transcriptome and metabolome profiling of field-grown transgenic barley lack induced differences but show cultivar-specific variances

Abstract

The aim of the present study was to assess possible adverse effects of transgene expression in leaves of field-grown barley relative to the influence of genetic background and the effect of plant interaction with arbuscular mycorrhizal fungi. We conducted transcript profiling, metabolome profiling, and metabolic fingerprinting of wild-type accessions and barley transgenics with seed-specific expression of (1,3-1, 4)-β-glucanase (GluB) in Baronesse (B) as well as of transgenics in Golden Promise (GP) background with ubiquitous expression of codon-optimized Trichoderma harzianum endochitinase (ChGP). We found more than 1,600 differential transcripts between varieties GP and B, with defense genes being strongly overrepresented in B, indicating a divergent response to subclinical pathogen challenge in the field. In contrast, no statistically significant differences between ChGP and GP could be detected based on transcriptome or metabolome analysis, although 22 genes and 4 metabolites were differentially abundant when comparing GluB and B, leading to the distinction of these two genotypes in principle component analysis. The coregulation of most of these genes in GluB and GP, as well as simple sequence repeat-marker analysis, suggests that the distinctive alleles in GluB are inherited from GP. Thus, the effect of the two investigated transgenes on the global transcript profile is substantially lower than the effect of a minor number of alleles that differ as a consequence of crop breeding. Exposing roots to the spores of the mycorrhizal Glomus sp. had little effect on the leaf transcriptome, but central leaf metabolism was consistently altered in all genotypes.food safety | glucanase | chitinase | sustainability B reeding for improved grain weight, higher grain yield, disease resistance, and climatic adaptation by selection of spontaneous mutations shaped the modern barley (Hordeum vulgare L.) crop plant beginning as early as 10,000 years ago. With the technical advance to generate transgenic crops with improved agronomic performance, it has become necessary to assess the substantial equivalence of transgenic crop plants; that is, validate that no undesired side effect of the genetic modification has occurred relative to their parental lines (see ref. 1 for review). The availability of the "omics" techniques opens the possibility to probe substantial equivalence in nontargeted global analyses, providing unbiased results.We have recently developed a 44-K barley microarray based on the assembly of 444,652 barley ESTs into 28,001 contigs and 22,937 singletons, of which 13,265 are represented on the array (2). In contrast, a comprehensive analysis of the metabolome (i.e., all metabolites in a specimen) is not possible because of the immense diversity of primary and secondary plant metabolites (3, 4). Thus, investigating the metabolome requires the prioritization of metabolite subsets as defined by their physicochemical properties or abundance. Although approaches to metabolite profiling are fueled by a multitude of indiv...

High specificity in plant leaf metabolic responses to arbuscular mycorrhiza

“…The changes in catabolic processes may be related to the carbon sink strength imposed by the AMF. The contrary response of the grass, P. annua, regarding organic acids corresponds well with increases of organic acids of the citric acid cycle found in maize 30 and barley 31 (Poaceae) leaves under mycorrhizal conditions and may point to general differences in metabolism of dicots versus monocots. In addition, the lower fungal root colonization in the grass compared with the dicot species (Fig.…”

Maize Source Leaf Adaptation to Nitrogen Deficiency Affects Not Only Nitrogen and Carbon Metabolism But Also Control of Phosphate Homeostasis

“…2A). The strong influence of genotypic background on transcriptome pattern has been described for other species, such as barley (Hordeum vulgare; Kogel et al, 2010). Separation of data by developmental stage can be explained by the different age at time of harvest and the fact that early leaves of maize show differences in morphology, anatomy, cell wall composition, and transcriptome (Strable et al, 2008).…”

Metabolic Interaction between Anthocyanin and Lignin Biosynthesis Is Associated with Peroxidase FaPRX27 in Strawberry Fruit

“…Combining metabolite profiling data with gene expression analyses has provided unique and comprehensive overviews of the transcriptional regulation of metabolic shifts, responses to plant hormones, as well as adaption of stress tolerance mechanisms (YonekuraSakakibara et al, 2008;Janz et al, 2010;Kogel et al, 2010;Stushnoff et al, 2010;Rohrmann et al, 2011;Zifkin et al, 2012). In this study, a custom-made oligonucleotidebased microarray platform (Roche-NimbleGen) was employed for the comprehensive investigation of differential gene expression in strawberry varieties that were selected by metabolite profiling analysis due to their opposite levels of phenolics ( Fig.…”