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The NAC family is one of the largest plant-specific transcription factor families, and some of its members are known to play major roles in plant development and response to biotic and abiotic stresses. Here, we inventoried 488 NAC members in bread wheat (Triticum aestivum). Using the recent release of the wheat genome (IWGS RefSeq v1.0), we studied duplication events focusing on genomic regions from 4B-4D-5A chromosomes as an example of the family expansion and neofunctionalization of TaNAC members. Differentially expressed TaNAC genes in organs and in response to abiotic stresses were identified using publicly available RNAseq data. Expression profiling of 23 selected candidate TaNAC genes was studied in leaf and grain from two bread wheat genotypes at two developmental stages in field drought conditions and revealed insights into their specific and/or overlapping expression patterns. This study showed that, of the 23 TaNAC genes, seven have a leaf-specific expression and five have a grain-specific expression. In addition, the grain-specific genes profiles in response to drought depend on the genotype. These genes may be considered as potential candidates for further functional validation and could present an interest for crop improvement programs in response to climate change. Globally, the present study provides new insights into evolution, divergence and functional analysis of NAC gene family in bread wheat.

Wheat grain yield is usually decomposed in the yield components: number of spikes / m2, number of grains / spike, number of grains / m2 and thousand kernel weight (TKW). These are correlated one with another due to yield component compensation. Under optimal conditions, the number of grains per m2 has been identified as the main determinant of yield. However, with increasing occurrences of post-flowering abiotic stress associated with climate change, TKW may become severely limiting and hence a target for breeding. TKW is usually studied at the plot scale as it represents the average mass of a grain. However, this view disregards the large intra-genotypic variance of individual grain mass and its effect on TKW. The aim of this study is to investigate the determinism of the variance of individual grain size. We measured yield components and individual grain size variances of two large genetic wheat panels grown in two environments. We also carried out a genome-wide association study using a dense SNPs array. We show that the variance of individual grain size partly originates from the pre-flowering components of grain yield; in particular it is driven by canopy structure via its negative correlation with the number of spikes per m2. But the variance of final grain size also has a specific genetic basis. The genome-wide analysis revealed the existence of QTL with strong effects on the variance of individual grain size, independently from the other yield components. Finally, our results reveal some interesting drivers for manipulating individual grain size variance either through canopy structure or through specific chromosomal regions.

In bread wheat (Triticum aestivum L.), the simultaneous improvement of both yield and grain protein is difficult because of the strong negative relationship between these two traits. However, some genotypes deviate positively from this relationship and this has been linked to their ability to take up nitrogen (N) during the post-flowering period, regardless of their N status at flowering. The physiological and genetic determinants of post-flowering N uptake relating to N satiety are poorly understood. This study uses semi-hydroponic culture of cv. Récital under controlled conditions to explore these controls. The first objective was to record the effects of contrasting N status at flowering on post-flowering nitrate (NO₃⁻) uptake under non-limiting NO₃⁻ conditions, while following the expression of key genes involved in NO₃⁻ uptake and assimilation. We found that post-flowering NO₃⁻ uptake was strongly influenced by plant N status at flowering during the first 300-400 degree-days after flowering, overlapping with a probable regulation of nitrate uptake exerted by N demand for growth. The uptake of NO₃⁻ correlated well with the expression of the gene TaNRT2.1, coding for a root NO₃⁻ transporter, which seems to play a major role in post-flowering NO₃⁻ uptake. These results provide a useful knowledge base for future investigation of genetic variability in post-flowering N uptake and may lead to concomitant gains in both grain yield and grain protein in wheat.

Thousand grain weight is one of the components determining wheat grain yield. It represents the average value of individual grain weights which depends on position within the ear and on positon within the spikelet. Our objective was to quantify the influences of individual floret anthesis date, of carpel weight at anthesis and of rate and duration of grain filling, on variation in individual final grain weight. Two bread wheat cultivars were grown in a greenhouse and their ears were sampled from anthesis through to harvest. Each ear was divided into three parts-basal, central and apical-where the two proximal grains were dissected from each of two spikelets. We analysed (i) the flowering time shift within the ear and within the spikelet; and (ii) the growth kinetics during grain filling in relation to position along the ear. For both cultivars, florets located in the central part of the ear were the first to reach anthesis followed by those in the apical part and then the basal part. Within a spikelet, the floret located nearest the rachis flowered first followed by the more distal ones. We found no significant systematic effect of flowering time-shift on final grain weight. Nevertheless, grains in the central part were heavier than the basal ones (9.75% smaller) and than the apical ones (18.25% smaller). These differences were explained mainly by differences in mean grain filling rates. Analysis of growth kinetics enabled an improved explanation of the variability of individual grain weight along the ear.

In ecology, an increase in genetic diversity within a community in natural ecosystems increases its productivity, while in evolutionary biology, kinship selection predicts that relatedness on social traits improves fitness. Varietal mixtures, where different genotypes are grown together, show contrasting results, especially for grain yield where both positive and negative effects of mixtures have been reported. To understand the effect of diversity on field performance, we grew 96 independent mixtures each composed with 12 durum wheat (Triticum turgidum ssp. durum Thell.) inbred lines, under two contrasting environmental conditions for water availability. Using dense genotyping, we imputed allelic frequencies and a genetic diversity index on more than 96000 loci for each mixture. We then analyzed the effect of genetic diversity on agronomic performance using a genome-wide approach. We explored the stress gradient hypothesis, which proposes that the greater the unfavourable conditions, the more beneficial the effect of diversity on mixture performance. We found that diversity on average had a negative effect on yield and its components while it was beneficial on grain weight. There was little support for the stress gradient theory. We discuss how to use genomic data to improve the assembly of varietal mixtures.

The strong negative correlation between grain protein concentration (GPC) and grain yield (GY) in bread wheat complicates the simultaneous improvement of these traits. However, earlier studies have concluded that the deviation from this relationship (grain protein deviation or GPD) has strong genetic basis. Genotypes with positive GPD have an increased ability to uptake nitrogen (N) during the post-flowering period independently of the amount of N taken up before flowering, suggesting that genetic variability for N satiety could enable the breakage of the negative relationship. This study is based on two genotypes markedly contrasted for GPD grown under semi-hydroponic conditions differentiated for nitrate availability both before and after flowering. This allows exploration of the genetic determinants of post-flowering N uptake (PANU) by combining whole plant sampling and targeted gene expression approaches. The results highlights the correlation (r² = 0.81) with GPC of PANU occurring early during grain development (flowering-flowering + 250 degree-days) independently of GY. Early PANU was in turn correlated (r² = 0.80) to the stem-biomass increment after flowering through its effect on N sink activity. Differences in early PANU between genotypes, despite comparable N statuses at flowering, suggest that genetic differences in N satiety could be involved in the establishment of the GPC. Through its strong negative correlation with genes implied in N assimilation, root nitrate concentration appears to be a good marker for evaluating instantaneous plant N demand, and may provide valuable information on the genotypic N satiety level. This trait may help breeders to identify genotypes having high GPC independently of their GY.

The genetic variability of the duration of leaf senescence during grain filling has been shown to affect both carbon and nitrogen acquisition. In particular, maintaining green leaves during grain filling possibly leads to increased grain yield, but its associated effect on grain protein concentration has not been studied. The aim of this study was to dissect the genetic factors contributing to correlations observed at the phenotypic level between leaf senescence during grain filling, grain protein concentration, and grain yield in winter wheat. With this aim in view, an analysis of quantitative trait locus (QTL) co-locations for these traits was carried out on a doubled haploid mapping population grown in a large multienvironment trial network. Pleiotropic QTLs affecting leaf senescence and grain yield and/or grain protein concentration were identified on chromosomes 2D, 2A, and 7D. These were associated with QTLs for anthesis date, showing that the phenotypic correlations with leaf senescence were mainly explained by flowering time in this wheat population. Study of the allelic effects of these pleiotropic QTLs showed that delaying leaf senescence was associated with increased grain yield or grain protein concentration depending on the environments considered. It is proposed that this differential effect of delaying leaf senescence on grain yield and grain protein concentration might be related to the nitrogen availability during the post-anthesis period. It is concluded that the benefit of using leaf senescence as a selection criterion to improve grain protein concentration in wheat cultivars may be limited and would largely depend on the targeted environments, particularly on their nitrogen availability during the post-anthesis period.

Grain yield (GY) and grain protein concentration (GPC) are two major traits contributing to the economic value of the wheat crop. These are, consequently, major targets in wheat breeding programs, but their simultaneous improvement is hampered by the negative correlation between GPC and GY. Identifying the genetic determinants of GPC and GY through quantitative trait loci (QTL) analysis would be one way to identify chromosomal regions, allowing improvement of GPC without reducing GY using marker-assisted selection. Therefore, QTL detection was carried out for GY and GPC using three inter-connected doubled haploid populations grown in a large multi-environment trial network. Chromosomes 2A, 2D, 3B, 7B and 7D showed co-location of QTL for GPC and GY with antagonistic effects, thus contributing to the negative GPC–GY relationship. Nonetheless, genomic regions determining GPC independently of GY across experiments were found on chromosomes 3A and 5D and could help breeders to move the GPC–GY relationship in a desirable direction.

After the heatwave The European heatwave in the summer of 2003 was probably the hottest in the region since AD 1500. Its immediate effects are well documented: the Earth Policy Institute has estimated that it caused at least 35,000 deaths. Now the longer-term effects are beginning to emerge. Based on measurements of ecosystem CO 2 flux, radiation absorption by plants, crop yields and a model simulating the terrestrial biosphere, a multinational team of researchers has found that during July and August 2003, 500 million tonnes of carbon escaped from the forests and fields across Europe as a result of extreme heat and drought. The model results and historical data suggest that this dramatic fall in primary productivity is unprecedented during the past century. If the incidence of extreme droughts like this were to increase, temperate ecosystems could become carbon sources with the potential to accelerate global warming, as has been anticipated for the tropics. Future climate warming is expected to enhance plant growth in temperate ecosystems and to increase carbon sequestration 1 , 2 . But although severe regional heatwaves may become more frequent in a changing climate 3 , 4 , their impact on terrestrial carbon cycling is unclear. Here we report measurements of ecosystem carbon dioxide fluxes, remotely sensed radiation absorbed by plants, and country-level crop yields taken during the European heatwave in 2003. We use a terrestrial biosphere simulation model 5 to assess continental-scale changes in primary productivity during 2003, and their consequences for the net carbon balance. We estimate a 30 per cent reduction in gross primary productivity over Europe, which resulted in a strong anomalous net source of carbon dioxide (0.5 Pg C yr -1 ) to the atmosphere and reversed the effect of four years of net ecosystem carbon sequestration 6 . Our results suggest that productivity reduction in eastern and western Europe can be explained by rainfall deficit and extreme summer heat, respectively. We also find that ecosystem respiration decreased together with gross primary productivity, rather than accelerating with the temperature rise. Model results, corroborated by historical records of crop yields, suggest that such a reduction in Europe's primary productivity is unprecedented during the last century. An increase in future drought events could turn temperate ecosystems into carbon sources, contributing to positive carbon-climate feedbacks already anticipated in the tropics and at high latitudes 1 , 2 .

Genotype × environment interactions (GEI) are common in plant multi-environment trials (METs). In this context, models developed for genomic selection (GS) that refers to the use of genome-wide information for predicting breeding values of selection candidates need to be adapted. One promising way to increase prediction accuracy in various environments is to combine ecophysiological and genetic modelling thanks to crop growth models (CGM) incorporating genetic parameters. The efficiency of this approach relies on the quality of the parameter estimates, which depends on the environments composing this MET used for calibration. The objective of this study was to determine a method to optimize the set of environments composing the MET for estimating genetic parameters in this context. A criterion called OptiMET was defined to this aim, and was evaluated on simulated and real data, with the example of wheat phenology. The MET defined with OptiMET allowed estimating the genetic parameters with lower error, leading to higher QTL detection power and higher prediction accuracies. MET defined with OptiMET was on average more efficient than random MET composed of twice as many environments, in terms of quality of the parameter estimates. OptiMET is thus a valuable tool to determine optimal experimental conditions to best exploit MET and the phenotyping tools that are currently developed.