Objectives: Characterization of the phenotypic diversity explaining adaptation to climatic variations and influence of genetic diversity on microbiota composition
Task 3.1: Germination phenotyping under stress conditions
Each population will be phenotyped on 100 seeds in four replicates (25 seeds per replicate) under each condition. Dry seeds (seed mass and maturity using chlorophyll fluorescence meter) will be monitored until the end of the germination process. Automated phenotyping will be realized under in vitro conditions at the French national seed testing station of GEVES, member of the Phenotypic platform. The total duration of the automated monitoring can vary from 7 days for control conditions (20°C –and 0 MPa) to 21 days when thermal and water stress are combined. The stress conditions have to be defined according to the species and the natural conditions where they were collected for wild populations and landraces. Parameters of germination (mean germination time MGT, germination rates at several times after sowing, time taken to reach 50% germination T50, final rate and uniformity of germination) will be extracted from automated curves in both species for all 100 population. Detailed information about the phenotyping system is given by Demilly et al. (2014). The populations will be ranked according to their susceptibility or efficiency to abiotic stress during the variousstages of development.
Task 3.2: Analysis of plants growth under cold temperature
Winter hardening and frost tolerance of the populations studied in the project will be assessed with freezing tests and monitoring of the damage with chlorophyll fluorescence, a method applicable to high numbers of individuals, as previously applied in several crop species. In a first phase, the methods will be tested on a small number of populations already available at the start of the project, selecting materials of different origin and lines known for contrasting sensitivity. The chlorophyll fluorescence indicator will be compared to survival rating. Furthermore, the applicability of a field-laboratory method, routinely in use, will be tested. The method consists in growing plants under natural acclimation conditions and subsequently applying a laboratory frost test on harvested leaves. In a second step, the populations chosen within WP2 will be phenotyped for frost tolerance. Phenotyping for leaf chlorophyll content, epidermal flavonoids, anthocyanins and a nitrogen balance index will be done with the Dualex optical sensor (Force A, Orsay, France) and for Vegetation Indexes with a hand held field spectrometer (ASD, Boulder; USA).
Task 3.3: Evaluation of a panel of candidate genes involved in cold response
Starting from data developed in Arabidopsis and in B. napus, a set of structural genes and regulators known to be involved in cold response, winter hardiness or vernalization or known to be modulated by low temperatures will be selected. Building on the sequencing data produced in WP2, the existence of allelic variants of key genes will be evaluated and correlated with phenotypic information. Moreover, starting from the consideration that copy number variation (CNV) have been found to impart large phenotypic influence in several plant species, including Arabidopsis, the existence of such genomic variants for selected genes will be evaluated in a panel of contasting genotypes with the aim to correlate variants and resistance level. In addition, cold response and genetic variability of a panel of regulatory (including miRNA) and structural genes involved in the synthesis of anthocyanins will also be analysed for its potential effects on stress resistance and impact on the nutraceutical value.
Task 3.4: Field experiment with all the populations sequenced
Field experiments will be performed per species. Three blocks containing each the 100 populations will be transplanted. At maturity, local varieties will be characterized for samples in each replicate, according to the varietal description for cauliflowers, broccoli, turnips and the wild populations by their flowering time, seed production and biomass. Each plant measurement phenotypes will be reported with regard to the standard vocabulary (stem, leaf, aboveground and grain biomass, pest damages) defined and registered by the Crop Ontology consortium (http://www.cropontology.org/). Then, all the partners will fill forms provided at BBIP.
Task 3.5: Microbiota analysis in relation with plant diversity
Plants obtained from the field trial described in task 3.4 will be used to investigate the impact of plant diversity on the root microbiota. For this, six root samples will be collected from three plants at three phenological stages (four-leaf rosette stage, bud and flowering time) and immediately placed into carbo ice to avoid modifications in the microbial diversity during field collection. Samples will be stored at -20°C prior total DNA extraction that will be performed with a phenol-chloroform protocol. Total DNA will be then used to characterize the bacterial microbiota diversity by amplifying the gyrB and rpoD marker genes and the ITS1 (Bartoli unpublished) marker for the fungal communities characterization. PCR amplicons will be purified and Illumina libraries will be performed as described in Bartoli et al., 2017. An equimolar pool for the amplicons will be sequenced by Illumina MiSeq at the INRA sequencing facilities GetPlage to obtain an average of 30,000 sequences per root sample. Sequences clustering will be performed with Mothur and Swarm and the resulting OTUs matrix will be further trimmed as described in Bartoli et al., 2017. The trimmed OTUs matrix will be used to determine microbiota descriptors for the α- (richness, Shannon’s index) and β-diversity (Hellinger distance matrix, relative abundance of the predominant OTUs) by vegan and microbiota R packages. Microbiota descriptors will be integrated in linear-mixed models to determine the Best Linear Unbiased Predictions (BLUPs) –and the heritability of the root microbiota descriptors. This will allow to identify whether plant diversity has a role in shaping the root microbiota.
Task 3.6: Analysis of plant growth under warm temperature – deep phenotyping of root architecture and of flowering parameters
A number of parameters related to root architecture and flowering time time as well as reproductive traits (inflorescence development) will be quantified in at least 20 plants from 50 selected populations covering both B. rapa and B. oleracea species under control conditions (20ºC) and warm temperature (28ºC). Phenotypic traits will be monitored in both conditions to assess the response of studied genotypes to growth under warmth. Genotypes with differential response to temperature in terms of root growth and/or flowering time will be selected for genetic studies (see task 3.7).
Task 3.7: Identification of genetic determinants mediating the response to warm temperature (P7) Transcriptome analyses (RNA-seq) will be performed on roots and aerial parts of selected populations that display differential responses to warm temperature. 4 populations will be analyzed in triplicate for root growth responses and 4 for flowering responses to warm temperatures (4 populations x 2 conditions x 3 replicas x 2 tissues, making 48 RNA-seq libraries). Bioinformatic analyses will deliver differentially expressed genes between warm temperature and control conditions for the varieties selected. These loci will represent candidates to mediate adaptation to warm temperature.
Task 3.8: Characterization of self-incompatibility
Manual pollinations (self-pollination and control crosses) will be applied to 30 plants per population and to 20 populations. 5 to 10 flowers per plant will be pollinated and repeated 2 times. The determination of the incompatibility phenotype will be made by counting the pollen tubes by fluorescence microscopy as described by Hadj-Arab et al. (2010). The identification of incompatibility alleles will be done by PCR-RFLP after individual DNA extraction of all phenotyped plants.
Task 3.9: Field experiments on core collections- Morphological and eco-physiological characterization
The same field design and morphological characterization as the ones described in task 3.4 will be performed from core collections in the different countries. When possible, eco-physiological traits such as leaf osmotic potential, chlorophyll content and leaf mass per area ratio (LMA) will be assessed under stress conditions.
