Microbial community dispersal from wheat grains to sourdoughs: A contribution of participatory research.

Understanding microbial dispersal is critical to understand the dynamics and evolution of microbial communities. However, microbial dispersal is difficult to study because of uncertainty about their vectors of migration. This applies to both microbial communities in natural and human-associated environments. Here, we studied microbial dispersal along the sourdoughs bread-making chain using a participatory research approach. Sourdough is a naturally fermented mixture of flour and water. It hosts a community of bacteria and yeasts whose origins are only partially known. We analysed the potential of wheat grains and flour to serve as an inoculum for sourdough microbial communities using 16S rDNA and ITS1 metabarcoding. First, in an experiment involving farmers, a miller and bakers, we followed the microbiota from grains to newly initiated and propagated sourdoughs. Second, we compared the microbiota of 46 sourdough samples collected everywhere in France, and of the flour used for their back-slopping. The core microbiota detected on the seeds, in the flour and in the sourdough was composed mainly of microbes known to be associated with plants and not living in sourdoughs. No sourdough yeast species were detected on grains and flours. Sourdough lactic acid bacteria were rarely found in flour. When they were, they did not have the same amplicon sequence variant (ASV) as found in the corresponding sourdough. However, the low sequencing depth for bacteria in flour did not allow us to draw definitive conclusion. Thus, our results showed that sourdough yeasts did not come from flour, and suggest that neither do sourdough LAB.

Plant functional trait variability and trait syndromes among wheat varieties: the footprint of artificial selection.

Although widely used in ecology, trait-based approaches are seldom used to study agroecosystems. In particular, there is a need to evaluate how functional trait variability among varieties of a crop species compares to the variability among wild plant species and how variety selection can modify trait syndromes. Here, we quantified 18 above- and below-ground functional traits for 57 varieties of common wheat representative of different modern selection histories. We compared trait variability among varieties and among Pooideae species, and analyzed the effect of selection histories on trait values and trait syndromes. For traits under strong selection, trait variability among varieties was less than 10% of the variability observed among Pooideae species. However, for traits not directly selected, such as root N uptake capacity, the variability was up to 75% of the variability among Pooideae species. Ammonium absorption capacity by roots was counter-selected for conventional varieties compared with organic varieties and landraces. Artificial selection also altered some trait syndromes classically reported for Pooideae. Identifying traits that have high or low variability among varieties and characterizing the hidden effects of selection on trait values and syndromes will benefit the selection of varieties to be used especially for lower N input agroecosystems.

Bayesian inference of natural selection from spatiotemporal phenotypic data.

Spatiotemporal variations of natural selection may influence the evolution of various features of organisms such as local adaptation or specialisation. This article develops a method for inferring how selection varies between locations and between generations from phenotypic data. It is assumed that generations are non-overlapping and that individuals reproduce by selfing or asexually. A quantitative genetics model taking account of the effects of stabilising natural selection, the environment and mutation on phenotypic means and variances is developed. Explicit results on the evolution of populations are derived and used to develop a Bayesian inference method. The latter is applied to simulated data and to data from a wheat participatory plant breeding programme. It has some ability to infer evolutionary parameters, but estimates may be sensitive to prior distributions, for example when phenotypic time series are short and when environmental effects are large. In such cases, sensitivity to prior distributions may be reported or more data may be collected.

WALTer: a three-dimensional wheat model to study competition for light through the prediction of tillering dynamics.

BACKGROUND AND AIMS: Branching is a main morphogenetic process involved in the adaptation of plants to the environment. In grasses, tillering is divided into three phases: tiller emergence, cessation of tillering and tiller regression. Understanding and prediction of the tillering process is a major challenge to better control cereal yields. In this paper, we present and evaluate WALTer, an individual-based model of wheat built on simple self-adaptive rules for predicting the tillering dynamics at contrasting sowing densities. METHODS: WALTer simulates the three-dimensional (3-D) development of the aerial architecture of winter wheat. Tillering was modelled using two main hypotheses: (H1) a plant ceases to initiate new tillers when a critical Green Area Index (GAIc) is reached, and (H2) the regression of a tiller occurs if its interception of light is below a threshold (PARt). The development of vegetative organs follows descriptive rules adapted from the literature. A sensitivity analysis was performed to evaluate the impact of each parameter on tillering and GAI dynamics. WALTer was parameterized and evaluated using an initial dataset providing an extensive description of GAI dynamics, and another dataset describing tillering dynamics under a wide range of sowing densities. KEY RESULTS: Sensitivity analysis indicated the predominant importance of GAIc and PARt. Tillering and GAI dynamics of expt 1 were well fit by WALTer. Once calibrated based on the agronomic density of expt 2, tillering parameters allowed an adequate prediction of tillering dynamics at contrasting sowing densities. CONCLUSIONS: Using simple rules and a small number of parameters, WALTer efficiently simulated the wheat tillering dynamics observed at contrasting densities in experimental data. These results show that the definition of a critical GAI and a threshold of PAR is a relevant way to represent, respectively, cessation of tillering and tiller regression under competition for light.

Application of a partitioning procedure based on Rao quadratic entropy index to characterize the temporal evolution of in situ varietal and genetic diversity of bread wheat in France over the period 1981-2006.

KEY MESSAGE: We present and highlight a partitioning procedure based on the Rao quadratic entropy index to assess temporal in situ inter-annual varietal and genetic changes of crop diversity. For decades, Western-European agroecosystems have undergone profound changes, among which a reduction of crop genetic diversity. These changes have been highlighted in numerous studies, but no unified partitioning procedure has been proposed to compute the inter-annual variability in both varietal and genetic diversity. To fill this gap, we tested, adjusted and applied a partitioning procedure based on the Rao quadratic entropy index that made possible to describe the different components of crop diversity as well as to account for the relative acreages of varieties. To emphasize the relevance of this procedure, we relied on a case study focusing on the temporal evolution of bread wheat diversity in France over the period 1981-2006 at both national and district scales. At the national scale, we highlighted a decrease of the weighted genetic replacement indicating that varieties sown in the most recent years were more genetically similar than older ones. At the district scale, we highlighted sudden changes in weighted genetic replacement in some agricultural regions that could be due to fast shifts of successive leading varieties over time. Other regions presented a relatively continuous increase of genetic similarity over time, potentially due to the coexistence of a larger number of co-leading varieties that got closer genetically. Based on the partitioning procedure, we argue that a tendency of in situ genetic homogenization could be compared to some of its potential causes, such as a decrease in the speed of replacement or an increase in between-variety genetic similarity over time.

Diversifying mechanisms in the on-farm evolution of crop mixtures.

While modern agriculture relies on genetic homogeneity, diversifying practices associated with seed exchange and seed recycling may allow crops to adapt to their environment. This socio-genetic model is an original experimental evolution design referred to as on-farm dynamic management of crop diversity. Investigating such model can help in understanding how evolutionary mechanisms shape crop diversity submitted to diverse agro-environments. We studied a French farmer-led initiative where a mixture of four wheat landraces called 'Mélange de Touselles' (MDT) was created and circulated within a farmers' network. The 15 sampled MDT subpopulations were simultaneously submitted to diverse environments (e.g. altitude, rainfall) and diverse farmers' practices (e.g. field size, sowing and harvesting date). Twenty-one space-time samples of 80 individuals each were genotyped using 17 microsatellite markers and characterized for their heading date in a 'common-garden' experiment. Gene polymorphism was studied using four markers located in earliness genes. An original network-based approach was developed to depict the particular and complex genetic structure of the landraces composing the mixture. Rapid differentiation among populations within the mixture was detected, larger at the phenotypic and gene levels than at the neutral genetic level, indicating potential divergent selection. We identified two interacting selection processes: variation in the mixture component frequencies, and evolution of within-variety diversity, that shaped the standing variability available within the mixture. These results confirmed that diversifying practices and environments maintain genetic diversity and allow for crop evolution in the context of global change. Including concrete measurements of farmers' practices is critical to disentangle crop evolution processes.

Network impact on persistence in a finite population dynamic diffusion model: application to an emergent seed exchange network.

Dynamic extinction colonisation models (also called contact processes) are widely studied in epidemiology and in metapopulation theory. Contacts are usually assumed to be possible only through a network of connected patches. This network accounts for a spatial landscape or a social organization of interactions. Thanks to social network literature, heterogeneous networks of contacts can be considered. A major issue is to assess the influence of the network in the dynamic model. Most work with this common purpose uses deterministic models or an approximation of a stochastic Extinction-Colonisation model (sEC) which are relevant only for large networks. When working with a limited size network, the induced stochasticity is essential and has to be taken into account in the conclusions. Here, a rigorous framework is proposed for limited size networks and the limitations of the deterministic approximation are exhibited. This framework allows exact computations when the number of patches is small. Otherwise, simulations are used and enhanced by adapted simulation techniques when necessary. A sensitivity analysis was conducted to compare four main topologies of networks in contrasting settings to determine the role of the network. A challenging case was studied in this context: seed exchange of crop species in the Réseau Semences Paysannes (RSP), an emergent French farmers׳ organisation. A stochastic Extinction-Colonisation model was used to characterize the consequences of substantial changes in terms of RSP׳s social organization on the ability of the system to maintain crop varieties.

Vernalization treatment induces site-specific DNA hypermethylation at the VERNALIZATION-A1 (VRN-A1) locus in hexaploid winter wheat.

BACKGROUND: Certain temperate species require prolonged exposure to low temperature to initiate transition from vegetative growth to flowering, a process known as vernalization. In wheat, winter cultivars require vernalization to initiate flowering, making vernalization requirement a trait of key importance in wheat agronomy. The genetic bases of vernalization response have been largely studied in wheat, leading to the characterization of a regulation pathway that involves the key gene VERNALIZATION1 (VRN1). While previous studies in wheat and barley have revealed the functional role of histone modification in setting VRN1 expression, other mechanisms might also be involved. Here, we were interested in determining whether the cold-induced expression of the wheat VRN-A1 gene is associated with a change in DNA methylation. RESULTS: We provide the first DNA methylation analysis of the VRN-A1 gene, and describe the existence of methylation at CG but also at non CG sites. While CG sites show a bell-shape profile typical of gene-body methylation, non CG methylation is restricted to the large (8.5 kb) intron 1, in a region harboring fragments of transposable elements (TEs). Interestingly, cold induces a site-specific hypermethylation at these non CG sites. This increase in DNA methylation is transmitted through mitosis, and is reset to its original level after sexual reproduction. CONCLUSIONS: These results demonstrate that VRN-A1 has a particular DNA methylation pattern, exhibiting rapid shift within the life cycle of a winter wheat plant following exposure to particular environmental conditions. The finding that this shift occurs at non CG sites in a TE-rich region opens interesting questions onto the possible consequences of this type of methylation in gene expression.

Deciphering the genetics of flowering time by an association study on candidate genes in bread wheat (Triticum aestivum L.).

Earliness is very important for the adaptation of wheat to environmental conditions and the achievement of high grain yield. A detailed knowledge of key genetic components of the life cycle would enable an easier control by the breeders. The objective of the study was to investigate the effect of candidate genes on flowering time. Using a collection of hexaploid wheat composed of 235 lines from diverse geographical origins, we conducted an association study for six candidate genes for flowering time and its components (vernalization sensitivity and earliness per se). The effect on the variation of earliness components of polymorphisms within the copies of each gene was tested in ANOVA models accounting for the underlying genetic structure. The collection was structured in five groups that minimized the residual covariance. Vernalization requirement and lateness tend to increase according to the mean latitude of each group. Heading date for an autumnal sowing was mainly determined by the earliness per se. Except for the Constans (CO) gene orthologous of the barley HvCO3, all gene polymorphisms had a significant impact on earliness components. The three traits used to quantify vernalization requirement were primarily associated with polymorphisms at Vrn-1 and then at Vrn-3 and Luminidependens (LD) genes. We found a good correspondence between spring/winter types and genotypes at the three homeologous copies of Vrn-1. Earliness per se was mainly explained by polymorphisms at Vrn-3 and to a lesser extent at Vrn-1, Hd-1 and Gigantea (GI) genes. Vernalization requirement and earliness as a function of geographical origin, as well as the possible role of the breeding practices in the geographical distribution of the alleles and the hypothetical adaptive value of the candidate genes, are discussed.

SHiNeMaS: a web tool dedicated to seed lots history, phenotyping and cultural practices.

MOTIVATION: In 2005, researchers from the French National Research Institute for Agriculture, Food and Environment (Institut national de recherche pour l'agriculture, l'alimentation et l'environnement, INRAE) started a collaboration with the French farmers' seed network Réseau Semences Paysannes (RSP) on bread wheat participatory breeding (PPB). The aims were: (1) to study on-farm management of crop diversity, (2) to develop population-varieties adapted to organic and low-inputs agriculture, (3) to co-develop tools and methods adapted to on-farm experiments. In this project, researchers and farmers' organizations needed to map the history and life cycle of the population-varieties using network formalism to represent relationships between seed lots. All this information had to be centralized and stored in a database. RESULTS: We describe here SHiNeMaS (Seeds History and Network Management System) a web tool database. SHiNeMaS aims to provide useful interfaces to track seed lot history and related data (phenotyping, environment, cultural practices). Although SHiNeMaS has been developed in the context of a bread wheat participatory breeding program, the database has been designed to manage any kind and even multiple cultivated plant species. SHiNeMaS is available under Affero GPL licence and uses free technologies such as the Python language, Django framework or PostgreSQL database management system (DBMS). CONCLUSION: We developed SHiNeMaS, a web tool database, dedicated to the management of the history of seed lots and related data like phenotyping, environmental information and cultural practices. SHiNeMaS has been used in production in our laboratory for 5 years and farmers' organizations facilitators manage their own information in the system.

Advances in Breeding for Mixed Cropping - Incomplete Factorials and the Producer/Associate Concept.

Mixed cropping has been suggested as a resource-efficient approach to meet high produce demands while maintaining biodiversity and minimizing environmental impact. Current breeding programs do not select for enhanced general mixing ability (GMA) and neglect biological interactions within species mixtures. Clear concepts and efficient experimental designs, adapted to breeding for mixed cropping and encoded into appropriate statistical models, are lacking. Thus, a model framework for GMA and SMA (specific mixing ability) was established. Results of a simulation study showed that an incomplete factorial design combines advantages of two commonly used full factorials, and enables to estimate GMA, SMA, and their variances in a resource-efficient way. This model was extended to the Producer (Pr) and Associate (As) concept to exploit additional information based on fraction yields. It was shown that the Pr/As concept allows to characterize genotypes for their contribution to total mixture yield, and, when relating to plant traits, allows to describe biological interaction functions (BIF) in a mixed crop. Incomplete factorial designs show the potential to drastically improve genetic gain by testing an increased number of genotypes using the same amount of resources. The Pr/As concept can further be employed to maximize GMA in an informed and efficient way. The BIF of a trait can be used to optimize species ratios at harvest as well as to extend our understanding of competitive and facilitative interactions in a mixed plant community. This study provides an integrative methodological framework to promote breeding for mixed cropping.

Experimental estimation of mutation rates in a wheat population with a gene genealogy approach.

Microsatellite markers are extensively used to evaluate genetic diversity in natural or experimental evolving populations. Their high degree of polymorphism reflects their high mutation rates. Estimates of the mutation rates are therefore necessary when characterizing diversity in populations. As a complement to the classical experimental designs, we propose to use experimental populations, where the initial state is entirely known and some intermediate states have been thoroughly surveyed, thus providing a short timescale estimation together with a large number of cumulated meioses. In this article, we derived four original gene genealogy-based methods to assess mutation rates with limited bias due to relevant model assumptions incorporating the initial state, the number of new alleles, and the genetic effective population size. We studied the evolution of genetic diversity at 21 microsatellite markers, after 15 generations in an experimental wheat population. Compared to the parents, 23 new alleles were found in generation 15 at 9 of the 21 loci studied. We provide evidence that they arose by mutation. Corresponding estimates of the mutation rates ranged from 0 to 4.97 x 10(-3) per generation (i.e., year). Sequences of several alleles revealed that length polymorphism was only due to variation in the core of the microsatellite. Among different microsatellite characteristics, both the motif repeat number and an independent estimation of the Nei diversity were correlated with the novel diversity. Despite a reduced genetic effective size, global diversity at microsatellite markers increased in this population, suggesting that microsatellite diversity should be used with caution as an indicator in biodiversity conservation issues.

Insight into the genetic bases of climatic adaptation in experimentally evolving wheat populations.

Experimental populations evolving under natural selection represent an interesting tool to study genetic bases of adaptation. Evolution of genes possibly involved in adaptive response can be followed together with the corresponding phenotypic traits. Using experimental populations of hexaploid wheat, we studied the evolution of flowering time, a major adaptive trait that synchronizes the initiation of reproduction and the occurrence of favourable environmental conditions. During 12 generations, three populations were grown in contrasted environments (Vervins North France, Le Moulon near Paris, Toulouse South France) under the influence of natural selection, drift, mutation and recombination. Evolution of diversity at the major gene VRN-1 involved in wheat vernalization response has been analysed jointly with earliness estimated in controlled conditions. Whatever the population, rapid phenotypic changes as well as parallel genotypic variations were observed in the first seven generations, probably as the result of selection acting on this major gene which explains 80% of the trait variation overall. Different allelic combinations at physically unlinked copies of VRN-1 located on distinct genomes (A, B and D) were selected between populations. As theoretically expected, due to population differentiation, a high level of genetic diversity was maintained overall in generation 12. Surprisingly, in two populations out of three, the emergence of new alleles by mutation or migration, coupled with temporal variable selection or frequency-dependent selection, allowed to maintain within-population diversity despite local genetic drift and natural selection. This result may plead for an evolutionary approach of wheat genetic resource conservation.

On the distribution of temporal variations in allele frequency: consequences for the estimation of effective population size and the detection of loci undergoing selection.

The effective population size (Ne) is frequently estimated using temporal changes in allele frequencies at neutral markers. Such temporal changes in allele frequencies are usually estimated from the standardized variance in allele frequencies (Fc). We simulate Wright-Fisher populations to generate expected distributions of Fc and of Fc (Fc averaged over several loci). We explore the adjustment of these simulated Fc distributions to a chi-square distribution and evaluate the resulting precision on the estimation of Ne for various scenarios. Next, we outline a procedure to test for the homogeneity of the individual Fc across loci and identify markers exhibiting extreme Fc-values compared to the rest of the genome. Such loci are likely to be in genomic areas undergoing selection, driving Fc to values greater (or smaller) than expected under drift alone. Our procedure assigns a P-value to each locus under the null hypothesis (drift is homogeneous throughout the genome) and simultaneously controls the rate of false positive among loci declared as departing significantly from the null. The procedure is illustrated using two published data sets: (i) an experimental wheat population subject to natural selection and (ii) a maize population undergoing recurrent selection.

Efficiently tracking selection in a multiparental population: the case of earliness in wheat.

Multiparental populations are innovative tools for fine mapping large numbers of loci. Here we explored the application of a wheat Multiparent Advanced Generation Inter-Cross (MAGIC) population for QTL mapping. This population was created by 12 generations of free recombination among 60 founder lines, following modification of the mating system from strict selfing to strict outcrossing using the ms1b nuclear male sterility gene. Available parents and a subset of 380 SSD lines of the resulting MAGIC population were phenotyped for earliness and genotyped with the 9K i-Select SNP array and additional markers in candidate genes controlling heading date. We demonstrated that 12 generations of strict outcrossing rapidly and drastically reduced linkage disequilibrium to very low levels even at short map distances and also greatly reduced the population structure exhibited among the parents. We developed a Bayesian method, based on allelic frequency, to estimate the contribution of each parent in the evolved population. To detect loci under selection and estimate selective pressure, we also developed a new method comparing shifts in allelic frequency between the initial and the evolved populations due to both selection and genetic drift with expectations under drift only. This evolutionary approach allowed us to identify 26 genomic areas under selection. Using association tests between flowering time and polymorphisms, 6 of these genomic areas appeared to carry flowering time QTL, 1 of which corresponds to Ppd-D1, a major gene involved in the photoperiod sensitivity. Frequency shifts at 4 of 6 areas were consistent with earlier flowering of the evolved population relative to the initial population. The use of this new outcrossing wheat population, mixing numerous initial parental lines through multiple generations of panmixia, is discussed in terms of power to detect genes under selection and association mapping. Furthermore we provide new statistical methods for use in future analyses of multiparental populations.

Experimental demonstration of a causal relationship between heterogeneity of selection and genetic differentiation in quantitative traits.

Comparisons of estimates of genetic differentiation at molecular markers (F(ST)) and at quantitative traits (Q(ST)) are a means of inferring the level and heterogeneity of selection in natural populations. However, such comparisons are questionable because they require that the influence of drift and selection on Q(ST) be detectable over possible background influences of environmental or nonadditive genetic effects on Q(ST)-values. Here we test this using an experimental evolution approach in metapopulations of Arabidopsis thaliana experiencing different levels of drift and selection heterogeneity. We estimated the intensity and heterogeneity of selection on morphological and phenological traits via selection differentials. We demonstrate that Q(ST)-values increased with increasing selection heterogeneity when genetic drift was limited. The effect of selection on Q(ST) was thus detectable despite significant genotype-by-environment interactions that most probably biased the estimates of genetic differentiation. Although they cannot be used as a direct validation of the conclusions of prior studies, our results strongly support both the relevance of Q(ST) as an estimator of genetic differentiation and the role of local selection in shaping the genetic differentiation of natural populations.

On-farm dynamic management of genetic diversity: the impact of seed diffusions and seed saving practices on a population-variety of bread wheat.

Since the domestication of crop species, humans have derived specific varieties for particular uses and shaped the genetic diversity of these varieties. Here, using an interdisciplinary approach combining ethnobotany and population genetics, we document the within-variety genetic structure of a population-variety of bread wheat (Triticum aestivum L.) in relation to farmers' practices to decipher their contribution to crop species evolution. Using 19 microsatellites markers, we conducted two complementary graph theory-based methods to analyze population structure and gene flow among 19 sub-populations of a single population-variety [Rouge de Bordeaux (RDB)]. The ethnobotany approach allowed us to determine the RDB history including diffusion and reproduction events. We found that the complex genetic structure among the RDB sub-populations is highly consistent with the structure of the seed diffusion and reproduction network drawn based on the ethnobotanical study. This structure highlighted the key role of the farmer-led seed diffusion through founder effects, selection and genetic drift because of human practices. An important result is that the genetic diversity conserved on farm is complementary to that found in the genebank indicating that both systems are required for a more efficient crop diversity conservation.

Dynamic management of crop diversity: From an experimental approach to on-farm conservation.

In agricultural systems, biodiversity includes diversity within species and among species and provides many benefits for production, resilience and conservation. This article addresses the effects of a strategy of in situ conservation called dynamic management (DM) on population evolution, adaptation and diversity. Two French DM initiatives are considered, the first one corresponding to an experimental context, the second to an on-farm management. Results from a study over 26 years of experimental DM of bread wheat (Triticum aestivum L.) are first presented, including the evolution of agronomic traits and genetic diversity at neutral and fitness related loci. While this experiment greatly increased scientific knowledge of the effects of natural selection on cultivated populations, it also showed that population conservation cannot rely only on a network of experimental stations. In collaboration with a farmers' network in France, researchers have begun studying the effects of on-farm DM (conservation and selection) on diversity and adaptation. Results from these studies show that on-farm DM is a key element for the long-term conservation and use of agricultural biodiversity. This method of in situ conservation deserves more attention in industrialised countries.

Evolution of flowering time in experimental wheat populations: a comprehensive approach to detect genetic signatures of natural selection.

In annual plant species, flowering time is a major adaptive trait that synchronizes the initiation of reproduction with favorable environmental conditions. Here, we aimed at studying the evolution of flowering time in three experimental populations of bread wheat, grown in contrasting environments (Northern to Southern France) for 12 generations. By comparing the distribution of phenotypic and presumably neutral variation, we first showed that flowering time responded to selection during the 12 generations of the experiment. To get insight into the genetic architecture of that trait, we then tested whether the distribution of genetic polymorphisms at six candidate genes, presumably involved in the trait expression, departed from neutral expectation. To that end, we focused on the temporal variation during the course of the experiment, and on the spatial differentiation at the end of the experiment, using previously published methods adapted to our experimental design. Only those genes that were strongly associated with flowering time variation were detected as responding to selection. For genes that had low-to-moderate phenotypic effects, or when there was interaction across different genes, we did not find evidence of selection using methods based on the distribution of temporal or spatial variation. In such cases, it might be more informative to consider multilocus and multiallelic combinations across genes, which could be the targets of selection.

FT genome A and D polymorphisms are associated with the variation of earliness components in hexaploid wheat.

The transition from vegetative to floral meristems in higher plants is determined by the coincidence of internal and environmental signals. Contrary to the photoperiod pathway, convergent evolution of the cold-dependent pathway has implicated different genes between dicots and monocots. Whereas no association between natural variation in vernalization requirement and Flowering time locus T (FT) gene polymorphism has been described in Arabidopsis, recent studies in Triticeae suggest implication of orthologous copies of FT in the cold response. In our study, we show that nucleotide polymorphisms on A and D copies of the wheat FT gene were associated with variations for heading date in a collection of 239 lines representing diverse geographical origins and status (landraces, old or recent cultivars). Interestingly, polymorphisms in the non-coding intronic region were strongly associated to flowering variation observed on plants grown without vernalization. But differently from VRN1, no epistatic interaction between FT homeologous copies was revealed. In agreement with the results of association study, the A and D copies of FT were mapped in regions including major QTLs for earliness traits in hexaploid wheat. This work, by identifying additional homeoalleles involved in wheat vernalization pathway, will contribute to a better understanding of the control of flowering, hence providing tools for the breeding of varieties with enhanced adaptation to changing environments.