Monitoring drought responses of barley genotypes with semi-robotic phenotyping platform and association analysis between recorded traits and allelic variants of some stress genes

Genetic improvement of complex traits such as drought adaptation can be advanced by the combination of genomic and phenomic approaches. Semi-robotic phenotyping platform was used for computer-controlled watering, digital and thermal imaging of barley plants grown in greenhouse. The tested barley variants showed 0–76% reduction in green pixel-based shoot surface area in soil with 20% water content, compared to well-watered plants grown in soil with 60% water content. The barley HvA1 gene encoding the group 3 LEA (Late Embryogenesis Abundant) protein exhibited four (A–D) haplotypes as identified by the EcoTILLING and subsequent DNA sequencing. The green pixel mean value of genotypes with haplotype D was higher than the mean value of the remaining haplotypes, indicating a pivotal role of haplotype D in optimizing the green biomass production under drought condition. In water limitation, the canopy temperature of a highly sensitive genotype was 18.0°C, as opposed to 16.9°C of leaves from a tolerant genotype as measured by thermal imaging. Drought-induced changes in leaf temperature showed moderate correlation with the water use efficiency (r2 = 0.431). The haplotype/trait association analysis based on the t-test has revealed a positive effect of a haplotype B (SNPs:GCCCCTGC) in a gene encoding the barley fungal pathogen induced mRNA for pathogen-related protein (HvPPRPX), on harvest index, thousand grain weight, water use efficiency and grain yield. The presented pilot study established a basic methodology for the integrated use of phenotyping and haplotyping data in characterization of genotype-dependent drought responses in barley

Heterosis of Biomass Production in Arabidopsis. Establishment during Early Development

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 μmol m(−2) s(−1)), and 161% at high light intensity (240 μmol 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

Large-Scale Identification and Analysis of Genome-Wide Single-Nucleotide Polymorphisms for Mapping in Arabidopsis thaliana

Genetic markers such as single nucleotide polymorphisms (SNPs) are essential tools for positional cloning, association, or quantitative trait locus mapping and the determination of genetic relationships between individuals. We identified and characterized a genome-wide set of SNP markers by generating 10,706 expressed sequence tags (ESTs) from cDNA libraries derived from 6 different accessions, and by analysis of 606 sequence tagged sites (STS) from up to 12 accessions of the model flowering plant Arabidopsis thaliana. The cDNA libraries for EST sequencing were made from individuals that were stressed by various means to enrich for transcripts from genes expressed under such conditions. SNPs discovered in these sequences may be useful markers for mapping genes involved in interactions with the biotic and abiotic environment. The STS loci are distributed randomly over the genome. By comparison with the Col-0 genome sequence, we identified a total of 8051 SNPs and 637 insertion/deletion polymorphisms (InDel). Analysis of STS-derived SNPs shows that most SNPs are rare, but that it is possible to identify intermediate frequency framework markers that can be used for genetic mapping in many different combinations of accessions. A substantial proportion of SNPs located in ORFs caused a change of the encoded amino acid. A comparison of the density of our SNP markers among accessions in both the EST and STS datasets, revealed that Cvi-0 is the most divergent accession from Col-0 among the 12 accessions studied. All of these markers are freely available via the internet

The metabolic signature related to high plant growth rate in Arabidopsis thaliana

The decline of available fossil fuel reserves has triggered world-wide efforts to develop alternative energy sources based on plant biomass. Detailed knowledge of the relations of metabolism and biomass accumulation can be expected to yield powerful novel tools to accelerate and enhance energy plant breeding programs. We used metabolic profiling in the model Arabidopsis to study the relation between biomass and metabolic composition using a recombinant inbred line (RIL) population. A highly significant canonical correlation (0.73) was observed, revealing a close link between biomass and a specific combination of metabolites. Dividing the entire data set into training and test sets resulted in a median correlation between predicted and true biomass of 0.58. The demonstrated high predictive power of metabolic composition for biomass features this composite measure as an excellent biomarker and opens new opportunities to enhance plant breeding specifically in the context of renewable resources