Analyse génétique des réponses physiologiques du tournesol (Helianthus annuus L.) soumis à la sécheresse

Afin de progresser dans la compréhension des caractères clés impliqués dans les processus de tolérance à la sécheresse chez le tournesol, nous avons réalisé plusieurs expérimentations, en conditions contrôlées et au champ sur des populations de tournesol exprimant diverses sources de variabilité génétique : des lignées recombinantes (RILs) et des mutants. La variabilité génétique pour la tolérance à la sécheresse, à travers l'étude des relations hydriques et de caractères agronomiques, a été étudiée. Dans un premier temps, nous avons construit une carte génétique intégrée et à haute densité en utilisant une population de LIRs issue du croisement entre deux génotypes PAC2×RHA266. Les QTLs contrôlant les caractères associés à l'état hydrique des plantes (teneur en eau relative, potentiel hydrique et ses composantes) et à l'ajustement osmotique (AO) dans des conditions ‘irriguées' et de ‘contraintes hydriques' ont été identifiés. Parmi 24 QTLs détectés dans des conditions irriguées, cinq (environ 21%), ont été également détectés dans la condition contrainte hydrique. Ces QTLs sont considérés comme stables comparativement à ceux spécifiques aux différentes conditions hydriques. Un QTL majeur pour l'AO sur le groupe de liaison 5 est co-localisé avec les QTLs contrôlant plusieurs caractères de l'état hydrique des plantes. Ce QTL pourrait être utilisé pour la sélection assistée par marqueurs. Les LIRs et leurs parents ont été phenotypés en serre et au champ avec deux traitements hydriques (irrigué et sécheresse). Le phénotypage a porté sur des caractères agronomiques (phénologie, surface foliaire à la floraison, hauteur des plantes, sénescence, rendement et…). En utilisant notre carte génétique, les QTLs liés à ces caractères ont été identifiés et leurs colocalisations avec les QTLs contrôlant l'état hydrique des plantes et l'ajustement osmotique ont été analysées. Nous pouvons noter que certains QTLs associés à la tolérance au déficit hydrique sont situés dans les mêmes positions que ceux associés au rendement. Par exemple, le QTL majeur identifié pour l'AO est également détecté pour le rendement par plante, la surface foliaire et le poids du capitule. Ceci indique une base génétique commune pour la tolérance à la sécheresse et les caractères associés au rendement. Dans un deuxième temps, nous nous sommes intéressés à l'expression de gènes impliqués, d'une part dans la tolérance à la contrainte hydrique, et d'autre part dans les processus limitant les dommages oxydatifs, pour quatre génotypes ayant un comportement contrasté en situation de contrainte hydrique. L'expression des gènes étudiés a été mise en relation avec les caractères physiologiques mesurés concernant l'état hydrique, la photosynthèse et la photochimie étant impliquées dans les processus d'assimilation du carbone pour la croissance. Parmi les principaux résultats, on note une différence notable de l'expression des gènes impliqués dans l'état hydrique des différents génotypes, plus particulièrement de l'aquaporine. L'expression du gène de l'aquaporine est corrélée au caractère hydrique RWC. Pour les processus photochimiques, ce sont principalement les niveaux d'expression des gènes codant pour la superoxide dismutase, la catalase et la peroxidase qui différencient les génotypes soumis à la sécheresse. Les marqueurs moléculaires associés à l'ajustement osmotiques et à différents caractères agronomiques ont été identifiés chez une population de mutants M6. ABSTRACT : Recombinant inbred lines (RILs) coming from the cross "PAC2×RHA266" were used to develop an integrated and high density genetic-linkage map using SSR and AFLP markers. QTLs involved in the genetic control of water status traits (RWC, Yw, Ys, Yt and YsFT) and osmotic adjustment (OA) under well-watered and water-stressed conditions were identified. Among 24 QTLs detected under wellwatered conditions, 5 (about 21%) were also detected in the water-stressed treatment (stable QTLs) and the rests were specific. A major QTL for OA on linkage group 5 is overlapped with the QTLs for several water status traits. In order to understand the response of yield and related agronomic traits to different water treatments and growth conditions, RILs and their parents were phenotyped at greenhouse and fieldcondition with two water treatments. Using our saturated linkage map, the QTLs controlling agronomical traits were identified and their co-location with QTLs for plant water status and osmotic adjustment were investigated. Genotypic variation for water status and gas exchange parameters under different water treatments were studied and the differential expression of four water-stress associated genes were investigated. The expression level of aquaporin genes in leaves of four RILs and their parents was down regulated by water stress and was associated with relative water content (RWC). Down-regulation was also associated with genomic regions having alleles with negative effects on plant water status. Net photosynthesis rate (Pn) and the fructose-1,6 bisphosphatase gene expression levels were associated mainly after rehydration. The genomic regions involved in genetic variability for chlorophyll fluorescence parameters were mapped in RILs and the differential expression of various antioxidant genes were investigated by quantitative real-time RT-PCR in four selected RILs and their parental lines. Significant higher level of POD (66-fold) was observed. The putatively drought-tolerant genotype (C100) showed the highest transcript level for SOD, CAT, PSI P700 and PSII 32 Kda Protein resulting in the maintenance of photosynthesis under water stress. QTL mapping and graphical genotyping showed that the positive or negative alleles of some QTLs such as "NPQD.11.1" and "1-qPD.2.1" could be associated with the transcript abundance of SOD and CAT in the putatively drought-tolerant genotype (C100). Molecular markers associated with osmotic adjustment-related traits as well as with different agronomical traits were identified in well-watered and water-stressed plants for a population of M6 mutant lines

Allelic heterogeneity and trade-off shape natural variation for response to soil micronutrient

Peer reviewedPublisher PD

Use of GGEbiplot methodology and Griffing's diallel method for genetic analysis of partial resistance to phoma black stem disease in sunflower

The objectives of the present study were to estimate the general combining ability (GCA) and specific combining ability (SCA) for partial resistance to phoma black stem and to identify the most promising combination for the selection of improved breeding lines. The response of five parental genotypes and their F1 hybrids to a phoma black stem isolate (MA6) were evaluated in a diallel programme under controlled growth chamber conditions. Significant GCA and SCA indicate that both additive and non-additive gene effects contributed in the inheritance of partial resistance to phoma black stem, however, the Baker ratio showed that the additive genetic effects were more important than nonadditive ones. It is recommended that the GGEbiplot methodology could be an excellent tool for visualizing entry by tester (diallel) data. By using this technique to analyse black stem severity data, interaction among the sunflower genotypes in providing partial resistance to phoma black stem was clearly identified. Based on GGEbiplot presentation and Griffing's diallel analysis, the mutant line ‘M6-54-1’ showed the largest GCA, indicating contribution towards partial resistance, and the genotype B454/03 presented the smallest GCA, indicating contribution towards susceptibility. Our results show that the F1 hybrids ‘SDR18×B454/03’ and ‘M6-54-1×B454/03’ showing heterosis for partial resistance to phoma black stem come from the crosses between a susceptible genotype ‘B454/03’ and two partially resistant genotypes (SDR18 and M6-54-1), originated from different breeding programmes. We conclude therefore that these genotypes possess at least some different resistance genes, which were expressed in the hybrids and led to the observed effects

Quantitative trait loci associated with isolate specific and isolate nonspecific partial resistance to Phoma macdonaldii in sunflower

Black stem, caused by Phoma macdonaldii, is one of the most important diseases of sunflower in the world. Quantitative trait loci (QTLs) implicated in partial resistance to two single pycnidiospore isolates of P. macdonaldii (MP8 and MP10) were investigated using 99 recombinant inbred lines (RILs) from the cross between sunflower parental lines PAC2 and RHA266. The experimental design was a randomized complete block with three replications. High genetic variability and transgressive segregation were observed among RILs for partial resistance to P. macdonaldii isolates. QTL‐mapping was performed using a recently developed high‐density SSR/AFLP sunflower linkage map. A total of 10 QTLs were detected for black stem resistance. The phenotypic variance explained by each QTL (R2) was moderate, ranging from 6 to 20%. Four QTLs were common between two isolates on linkage group 5 and 15 whereas the others were specific for each isolate. Regarding isolate‐specific and isolate‐nonspecific QTLs detected for partial resistance, it is evident that both genetic effects control partial resistance to the disease isolates. This confirms the need to consider different isolates in the black stem resistance breeding programmes. The four SSR markers HA3700, SSU25, ORS1097 and ORS523_1 encompassing the QTLs for partial resistance to black stem isolates could be good candidates for marker assisted selection

QTL mapping of partial resistance to Phoma basal stem and root necrosis in sunflower (Helianthus annuus L.)

Phoma macdonaldii infects different tissues of sunflower and causes reduction in yield and oil content. The aim of present research was to identify genomic regions involved in partial resistance of sunflower to four Phoma macdonaldii basal stem and root necrosis isolates using our improved map constructed with 191 SSR and 304 AFLP markers. The experiment was conducted using F9 recombinant inbred lines (RILs) from a cross between ‘PAC2’ and ‘RHA266’. Results showed that ‘PAC2’ was more resistant than ‘RHA266’ to basal stem necrosis isolate ‘TA6’ and root necrosis isolate ‘TA4’. By contrast ‘RHA266’ was more resistant than ‘PAC2’ to basal stem necrosis isolate ‘TA9’ and root necrosis isolate ‘TA2’. Transgressive segregation was observed for partial resistance to all four isolates. Some recombinant lines presented partial resistance or susceptibility to all isolates. Twenty-seven QTL with phenotypic variance ranging from 7 to 29% were detected. Among them 13 were ‘isolate-specific’ and others were common for partial resistance to different isolates (isolate-non-specific). Most of the QTLs in common have major effects for resistance to each isolate. The ‘isolate-non-specific’ QTLs were located on linkage groups (LG) 5, 6, 8, 12, 13 and 15. The markers ‘HA3555’ on LG12 and ‘E33M48_26’ on LG6 as well as ‘E33M48_20’ on LG13, which are each linked to QTLs of different basal stem and root necrosis isolates, could be used in marker-assisted selection to introduce tolerance to four Phoma macdonaldii isolates into elite sunflower breeding lines

QTL analysis of yield-related traits in sunflower under different water treatments

A set of sunflower recombinant inbred lines (RILs) was used to study agronomical traits under greenhouse and field conditions each with two water treatments and three replications. The difference among RILs was significant for all the traits studied in all conditions; and water treatment × RILs interaction was also observed for most of the traits in both field and greenhouse conditions. Because of the low rate of drought stress, this part of field data are not informative. Several quantitative trait loci (QTLs) were identified for yield‐related traits with the percentage of phenotypic variance explained by QTLs (R 2) ranging from 4% to 40%. Several QTLs for grain yield per plant (GYP) under four water treatments were identified on different linkage groups, among which two were specific to a single treatment (GYPN.4.1 , GYPI.7.1 ). Three QTLs for GYP were overlapped with several QTLs for drought‐adaptative traits detected in our previous study (Poormohammad Kiani et al. 2007b). The whole results do highlight interesting genomic regions for marker‐based breeding programmes for drought tolerance in sunflower

AtHMA4 drives natural variation in leaf Zn concentration of Arabidopsis thaliana

Zinc (Zn) is an essential element for plant growth and development, and Zn derived from crop plants in the diet is also important for human health. Here, we report that genetic variation in Heavy Metal-ATPase 4 (HMA4) controls natural variation in leaf Zn content. Investigation of the natural variation in leaf Zn content in a world-wide collection of 349 Arabidopsis thaliana wild collected accessions identified two accessions, Van-0 and Fab-2, which accumulate significantly lower Zn when compared with Col-0. Both quantitative trait loci (QTL) analysis and bulked segregant analysis (BSA) identified HMA4 as a strong candidate accounting for this variation in leaf Zn concentration. Genetic complementation experiments confirmed this hypothesis. Sequence analysis revealed that a 1-bp deletion in the third exon of HMA4 from Fab-2 is responsible for the lose of function of HMA4 driving the low Zn observed in Fab-2. Unlike in Fab-2 polymorphisms in the promoter region were found to be responsible for the weak function of HMA4 in Van-0. This is supported by both an expression analysis of HMA4 in Van-0 and through a series of T-DNA insertion mutants which generate truncated HMA4 promoters in the Col-0 background. In addition, we also observed that Fab-2, Van-0 and the hma4-2 null mutant in the Col-0 background show enhanced resistance to a combination of high Zn and high Cd in the growth medium, raising the possibility that variation at HMA4 may play a role in environmental adaptation

Sunflower Hybrid Breeding: From Markers to Genomic Selection

In sunflower, molecular markers for simple traits as, e.g., fertility restoration, high oleic acid content, herbicide tolerance or resistances to Plasmopara halstedii, Puccinia helianthi, or Orobanche cumana have been successfully used in marker-assisted breeding programs for years. However, agronomically important complex quantitative traits like yield, heterosis, drought tolerance, oil content or selection for disease resistance, e.g., against Sclerotinia sclerotiorum have been challenging and will require genome-wide approaches. Plant genetic resources for sunflower are being collected and conserved worldwide that represent valuable resources to study complex traits. Sunflower association panels provide the basis for genome-wide association studies, overcoming disadvantages of biparental populations. Advances in technologies and the availability of the sunflower genome sequence made novel approaches on the whole genome level possible. Genotype-by-sequencing, and whole genome sequencing based on next generation sequencing technologies facilitated the production of large amounts of SNP markers for high density maps as well as SNP arrays and allowed genome-wide association studies and genomic selection in sunflower. Genome wide or candidate gene based association studies have been performed for traits like branching, flowering time, resistance to Sclerotinia head and stalk rot. First steps in genomic selection with regard to hybrid performance and hybrid oil content have shown that genomic selection can successfully address complex quantitative traits in sunflower and will help to speed up sunflower breeding programs in the future. To make sunflower more competitive toward other oil crops higher levels of resistance against pathogens and better yield performance are required. In addition, optimizing plant architecture toward a more complex growth type for higher plant densities has the potential to considerably increase yields per hectare. Integrative approaches combining omic technologies (genomics, transcriptomics, proteomics, metabolomics and phenomics) using bioinformatic tools will facilitate the identification of target genes and markers for complex traits and will give a better insight into the mechanisms behind the traits

Plant ionomics: from elemental profiling to environmental adaptation

Ionomics is a high-throughput elemental profiling approach to study the molecular mechanistic basis underlying mineral nutrient and trace element composition (also known as the ionome) of living organisms. Since the concept of ionomics was first introduced more than 10 years ago, significant progress has been made in the identification of genes and gene networks that control the ionome. In this update, we summarize the progress made in using the ionomics approach over the last decade, including the identification of genes by forward genetics and the study of natural ionomic variation. We further discuss the potential application of ionomics to the investigation of the ecological functions of ionomic alleles in adaptation to the environment