Comparative transcriptomics of drought responses in Populus: a meta-analysis of genome-wide expression profiling in mature leaves and root apices across two genotypes

<p>Abstract</p> <p>Background</p> <p>Comparative genomics has emerged as a promising means of unravelling the molecular networks underlying complex traits such as drought tolerance. Here we assess the genotype-dependent component of the drought-induced transcriptome response in two poplar genotypes differing in drought tolerance. Drought-induced responses were analysed in leaves and root apices and were compared with available transcriptome data from other <it>Populus </it>species.</p> <p>Results</p> <p>Using a multi-species designed microarray, a genomic DNA-based selection of probesets provided an unambiguous between-genotype comparison. Analyses of functional group enrichment enabled the extraction of processes physiologically relevant to drought response. The drought-driven changes in gene expression occurring in root apices were consistent across treatments and genotypes. For mature leaves, the transcriptome response varied weakly but in accordance with the duration of water deficit. A differential clustering algorithm revealed similar and divergent gene co-expression patterns among the two genotypes. Since moderate stress levels induced similar physiological responses in both genotypes, the genotype-dependent transcriptional responses could be considered as intrinsic divergences in genome functioning. Our meta-analysis detected several candidate genes and processes that are differentially regulated in root and leaf, potentially under developmental control, and preferentially involved in early and long-term responses to drought.</p> <p>Conclusions</p> <p>In poplar, the well-known drought-induced activation of sensing and signalling cascades was specific to the early response in leaves but was found to be general in root apices. Comparing our results to what is known in arabidopsis, we found that transcriptional remodelling included signalling and a response to energy deficit in roots in parallel with transcriptional indices of hampered assimilation in leaves, particularly in the drought-sensitive poplar genotype.</p

A species-specific critical nitrogen dilution curve for sunflower (Helianthus annuus L.)

For annual and perennial crops, mathematical models have been developed to describe tissue nitrogen (N) dilution during crop growth and to estimate the plant N status applying the N nutrition index (NNI), the ratio between the actual tissue N concentration ([N]) and the tissue N concentration needed to obtain the maximum instantaneous crop growth rate (critical tissue N concentration, [N] ). The relationship between shoot [N] and shoot dry matter (DM, tha ) can be described by an allometric power equation: [N] =aDM , where a and b are crop-specific parameters. Critical N dilution curves (CNDC) have been determined for several C crops but not specifically for sunflower (Helianthus annuus L.). The objectives of this work were to (i) determine and validate the N dilution curves for critical, minimum, and maximum [N] for sunflower from the juvenile stages to the end of flowering, (ii) compare the critical curve with published CNDCs for other C crops, and (iii) estimate the range of variation of NNI for different levels of N fertilization and irrigation. A wide range of field experiments from Argentina, Australia, France, Italy, and Spain was used to establish the dilution curve for sunflower and to independently validate it. The fitted CNDC [N] =4.53DM yielded lower values for [N] than references used until now for diagnosis and decision making in sunflower. The value of parameter a was generally similar to that of other C species, but the value for parameter b differed. This was possibly associated with species differences in dry mass partitioning, and justified the development of a sunflower-specific CNDC. A preliminary reference curve for maximum [N] suggested an evolution from the juvenile stages to the end of flowering similar to that of [N] . Minimum [N], in contrast, appeared to be more constant over time. Relationships between relative grain yield and NNI across a range of locations indicated that in general, maximum grain yield was reached around NNI=0.8, although at one location this was around NNI=1.0. The CNDC can provide useful applications for crop modeling, N status diagnosis, and N fertilization decision