Diversity in expression of phosphorus (P) responsive genes in Cucumis melo L.

BACKGROUND: Phosphorus (P) is a major limiting nutrient for plant growth in many soils. Studies in model species have identified genes involved in plant adaptations to low soil P availability. However, little information is available on the genetic bases of these adaptations in vegetable crops. In this respect, sequence data for melon now makes it possible to identify melon orthologues of candidate P responsive genes, and the expression of these genes can be used to explain the diversity in the root system adaptation to low P availability, recently observed in this species. METHODOLOGY AND FINDINGS: Transcriptional responses to P starvation were studied in nine diverse melon accessions by comparing the expression of eight candidate genes (Cm-PAP10.1, Cm-PAP10.2, Cm-RNS1, Cm-PPCK1, Cm-transferase, Cm-SQD1, Cm-DGD1 and Cm-SPX2) under P replete and P starved conditions. Differences among melon accessions were observed in response to P starvation, including differences in plant morphology, P uptake, P use efficiency (PUE) and gene expression. All studied genes were up regulated under P starvation conditions. Differences in the expression of genes involved in P mobilization and remobilization (Cm-PAP10.1, Cm-PAP10.2 and Cm-RNS1) under P starvation conditions explained part of the differences in P uptake and PUE among melon accessions. The levels of expression of the other studied genes were diverse among melon accessions, but contributed less to the phenotypical response of the accessions. CONCLUSIONS: This is the first time that these genes have been described in the context of P starvation responses in melon. There exists significant diversity in gene expression levels and P use efficiency among melon accessions as well as significant correlations between gene expression levels and phenotypical measurements.

Gene expression changes in phosphorus deficient potato (Solanum tuberosum L.) leaves and the potential for diagnostic gene expression markers.

BACKGROUND: There are compelling economic and environmental reasons to reduce our reliance on inorganic phosphate (Pi) fertilisers. Better management of Pi fertiliser applications is one option to improve the efficiency of Pi fertiliser use, whilst maintaining crop yields. Application rates of Pi fertilisers are traditionally determined from analyses of soil or plant tissues. Alternatively, diagnostic genes with altered expression under Pi limiting conditions that suggest a physiological requirement for Pi fertilisation, could be used to manage Pifertiliser applications, and might be more precise than indirect measurements of soil or tissue samples. RESULTS: We grew potato (Solanum tuberosum L.) plants hydroponically, under glasshouse conditions, to control their nutrient status accurately. Samples of total leaf RNA taken periodically after Pi was removed from the nutrient solution were labelled and hybridised to potato oligonucleotide arrays. A total of 1,659 genes were significantly differentially expressed following Pi withdrawal. These included genes that encode proteins involved in lipid, protein, and carbohydrate metabolism, characteristic of Pi deficient leaves and included potential novel roles for genes encoding patatin like proteins in potatoes. The array data were analysed using a support vector machine algorithm to identify groups of genes that could predict the Pi status of the crop. These groups of diagnostic genes were tested using field grown potatoes that had either been fertilised or unfertilised. A group of 200 genes could correctly predict the Pi status of field grown potatoes. CONCLUSIONS: This paper provides a proof-of-concept demonstration for using microarrays and class prediction tools to predict the Pi status of a field grown potato crop. There is potential to develop this technology for other biotic and abiotic stresses in field grown crops. Ultimately, a better understanding of crop stresses may improve our management of the crop, improving the sustainability of agriculture.

Regulatory hotspots are associated with plant gene expression under varying soil phosphorus supply in Brassica rapa.

Gene expression is a quantitative trait that can be mapped genetically in structured populations to identify expression quantitative trait loci (eQTL). Genes and regulatory networks underlying complex traits can subsequently be inferred. Using a recently released genome sequence, we have defined cis- and trans-eQTL and their environmental response to low phosphorus (P) availability within a complex plant genome and found hotspots of trans-eQTL within the genome. Interval mapping, using P supply as a covariate, revealed 18,876 eQTL. trans-eQTL hotspots occurred on chromosomes A06 and A01 within Brassica rapa; these were enriched with P metabolism-related Gene Ontology terms (A06) as well as chloroplast- and photosynthesis-related terms (A01). We have also attributed heritability components to measures of gene expression across environments, allowing the identification of novel gene expression markers and gene expression changes associated with low P availability. Informative gene expression markers were used to map eQTL and P use efficiency-related QTL. Genes responsive to P supply had large environmental and heritable variance components. Regulatory loci and genes associated with P use efficiency identified through eQTL analysis are potential targets for further characterization and may have potential for crop improvement.

Shoot calcium and magnesium concentrations differ between subtaxa, are highly heritable, and associate with potentially pleiotropic loci in Brassica oleracea.

Calcium (Ca) and magnesium (Mg) are the most abundant group II elements in both plants and animals. Genetic variation in shoot Ca and shoot Mg concentration (shoot Ca and Mg) in plants can be exploited to biofortify food crops and thereby increase dietary Ca and Mg intake for humans and livestock. We present a comprehensive analysis of within-species genetic variation for shoot Ca and Mg, demonstrating that shoot mineral concentration differs significantly between subtaxa (varietas). We established a structured diversity foundation set of 376 accessions to capture a high proportion of species-wide allelic diversity within domesticated Brassica oleracea, including representation of wild relatives (C genome, 1n = 9) from natural populations. These accessions and 74 modern F(1) hybrid cultivars were grown in glasshouse and field environments. Shoot Ca and Mg varied 2- and 2.3-fold, respectively, and was typically not inversely correlated with shoot biomass, within most subtaxa. The closely related capitata (cabbage) and sabauda (Savoy cabbage) subtaxa consistently had the highest mean shoot Ca and Mg. Shoot Ca and Mg in glasshouse-grown plants was highly correlated with data from the field. To understand and dissect the genetic basis of variation in shoot Ca and Mg, we studied homozygous lines from a segregating B. oleracea mapping population. Shoot Ca and Mg was highly heritable (up to 40%). Quantitative trait loci (QTL) for shoot Ca and Mg were detected on chromosomes C2, C6, C7, C8, and, in particular, C9, where QTL accounted for 14% to 55% of the total genetic variance. The presence of QTL on C9 was substantiated by scoring recurrent backcross substitution lines, derived from the same parents. This also greatly increased the map resolution, with strong evidence that a 4-cM region on C9 influences shoot Ca. This region corresponds to a 0.41-Mb region on Arabidopsis (Arabidopsis thaliana) chromosome 5 that includes 106 genes. There is also evidence that pleiotropic loci on C8 and C9 affect shoot Ca and Mg. Map-based cloning of these loci will reveal how shoot-level phenotypes relate to Ca(2+) and Mg(2+) uptake and homeostasis at the molecular level.