Heterosis has been widely used in agriculture to increase yield and to broaden adaptability of hybrid varieties and is applied to an increasing number of crop species. We performed a systematic survey of the extent and degree of heterosis for dry biomass in 63 Arabidopsis accessions crossed to three reference lines (Col-0, C24, and Nd). We detected a high heritability (69%) for biomass production in Arabidopsis. Among the 169 crosses analyzed, 29 exhibited significant mid-parent-heterosis for shoot biomass. Furthermore, we analyzed two divergent accessions, C24 and Col-0, the F-1 hybrids of which were shown to exhibit hybrid vigor, in more detail. In the combination Col-0/C24, heterosis for biomass was enhanced at higher light intensities; we found 51% to 66% mid-parent-heterosis at low and intermediate light intensities (60 and 120 mumol m(-2) s(-1)), and 161% at high light intensity (240 mumol m(-2) s(-1)). While at the low and intermediate light intensities relative growth rates of the hybrids were higher only in the early developmental phase (0-15 d after sowing [DAS]), at high light intensity the hybrids showed increased relative growth rates over the entire vegetative phase (until 25 DAS). An important finding was the early onset of heterosis for biomass; in the cross Col-0/C24, differences between parental and hybrid lines in leaf size and dry shoot mass could be detected as early as 10 DAS. The widespread occurrence of heterosis in the model plant Arabidopsis opens the possibility to investigate the genetic basis of this phenomenon using the tools of genetical genomics
Application of metabolomics to plant genotype discrimination using statistics and machine learning
(2003)
Stomatal cell biology
(2003)
The nuclear SHL protein is composed of a N-terminal BAH domain and a C-terminal PHD finger. Both domains are found in transcriptional regulators and chromatin-modifying proteins. Arabidopsis plants over-expressing SHL showed earlier flowering and senescence phenotype. To identify SHL regulated genes, expression profiles of 35S::SHL plants were established with Affymetrix ATH1 microarrays. About 130 genes showed reduced transcript levels, and about 45 genes showed increased transcript levels in 35S:: SHL plants. The up-regulated genes included AGL20 and AGL9, which most likely cause the early flowering phenotype of 35S:: SHL plants. Late-flowering SHL-antisense lines showed reduced AGL20 mRNA levels, suggesting that AGL20 gene expression depends on the SHL protein. The stronger expression of senescence- and defence-related genes (such as DIN2, DIN11 and PR-1) is in line with the early senescence phenotype of SHL-over- expressing plants. SHL-down-regulated genes included stress response genes and the PSR3.2 gene (encoding a beta- glucosidase). SHL over-expression did not alter the tissue specificity of PSR3.2 gene expression, but resulted in reduced transcript levels in both shoots and roots. Plants with glucocorticoid-inducible SHL over-expression were established and used for expression profiling as well. A subset of genes was identified, which showed consistent changes in the inducible system and in plants with constitutive SHL over-expression
Detailed analysis of brassinosteroid (BR)-regulated genes can provide evidence of the molecular basis of BR effects. Classical techniques (such as subtractive cDNA cloning) as well as cDNA and oligonucleotide microarrays have been applied to identify genes which are upregulated or downregulated after BR treatment or are differently expressed in BR-deficient or -insensitive mutants compared with wild type plants. Genes encoding cell-wall-modifying enzymes, enzymes of the BR biosynthetic pathway, auxin response factors, and transcription factors are subject to BR regulation. Effects on several other metabolic pathways and interactions with other phytohormones have been reported as well, although some of these effects may depend on certain environmental conditions (for example, light/dark or stress), the developmental stage of the plants, and tissue types. The identification of components of the BR signal transduction pathway revealed different modes of transcriptional control in animals and plants. Steroid signaling in plants comprises the plasma membrane receptor kinases BRI1 and BAK1 and intracellular protein phosphorylations. Thus, BR signaling in plants is reminiscent of growth factor and TGF-beta signal transduction in animals. The phosphorylation cascade could be a basis of extensive signaling cross-talk and thereby explain the complexity of BR responses
Background: Natural accessions of Arabidopsis thaliana are characterized by a high level of phenotypic variation that can be used to investigate the extent and mode of selection on the primary metabolic traits. A collection of 54 A. thaliana natural accession-derived lines were subjected to deep genotyping through Single Feature Polymorphism (SFP) detection via genomic DNA hybridization to Arabidopsis Tiling 1.0 Arrays for the detection of selective sweeps, and identification of associations between sweep regions and growth-related metabolic traits. Results: A total of 1,072,557 high-quality SFPs were detected and indications for 3,943 deletions and 1,007 duplications were obtained. A significantly lower than expected SFP frequency was observed in protein-, rRNA-, and tRNA-coding regions and in non- repetitive intergenic regions, while pseudogenes, transposons, and non-coding RNA genes are enriched with SFPs. Gene families involved in plant defence or in signalling were identified as highly polymorphic, while several other families including transcription factors are depleted of SFPs. 198 significant associations between metabolic genes and 9 metabolic and growth-related phenotypic traits were detected with annotation hinting at the nature of the relationship. Five significant selective sweep regions were also detected of which one associated significantly with a metabolic trait. Conclusions: We generated a high density polymorphism map for 54 A. thaliana accessions that highlights the variability of resistance genes across geographic ranges and used it to identify selective sweeps and associations between metabolic genes and metabolic phenotypes. Several associations show a clear biological relationship, while many remain requiring further investigation.