MCQTL: multi-allelic QTL mapping in multi-cross design

Cruz PC, Borromeo TH, Lalusin AG, Mauleon R, McNally KL, Swamy BPM. Molecular dissection of connected rice populations revealed important genomic regions for agronomic and biofortification traits

Breeding staple crops with increased micronutrient concentration is a sustainable approach to address micronutrient malnutrition. We carried out Multi-Cross QTL analysis and Inclusive Composite Interval Mapping for 11 agronomic, yield and biofortification traits using four connected RILs populations of rice. Overall, MC-156 QTLs were detected for agronomic (115) and biofortification (41) traits, which were higher in number but smaller in effects compared to single population analysis. The MC-QTL analysis was able to detect important QTLs viz: qZn_5.2, qFe_7.1, qGY_10.1, qDF_7.1, qPH_1.1, qNT_4.1, qPT_4.1, qPL_1.2, qTGW_5.1, qGL_3.1 , and qGW_6.1 , which can be used in rice genomics assisted breeding. A major QTL (qZn_5.2 ) for grain Zn concentration has been detected on chromosome 5 that accounted for 13% of R². In all, 26 QTL clusters were identified on different chromosomes. qPH_6.1 epistatically interacted with qZn_5.1 and qGY_6.2 . Most of QTLs were co-located with functionally related candidate genes indicating the accuracy of QTL mapping. The genomic region of qZn_5.2 was co-located with putative genes such as OsZIP5, OsZIP9, and LOC_OS05G40490 that are involved in Zn uptake. These genes included polymorphic functional SNPs, and their promoter regions were enriched with cis-regulatory elements involved in plant growth and development, and biotic and abiotic stress tolerance. Major effect QTL identified for biofortification and agronomic traits can be utilized in breeding for Zn biofortified rice varieties.

A multi-locus linear mixed model methodology for detecting small-effect QTLs for quantitative traits in MAGIC, NAM, and ROAM populations

Although multi-parent populations (MPPs) integrate the advantages of linkage and association mapping populations in the genetic dissection of complex traits and especially combine genetic analysis with crop breeding, it is difficult to detect small-effect quantitative trait loci (QTL) for complex traits in multiparent advanced generation intercross (MAGIC), nested association mapping (NAM), and random-open-parent association mapping (ROAM) populations. To address this issue, here we proposed a multi-locus linear mixed model method, namely mppQTL, to detect QTLs, especially small-effect QTLs, in these MPPs. The new method includes two steps. The first is genome-wide scanning based on a single-locus linear mixed model; the P-values are obtained from likelihood-ratio test, the peaks of negative logarithm P-value curve are selected by group-lasso, and all the selected peaks are regarded as potential QTLs. In the second step, all the potential QTLs are placed on a multi-locus linear mixed model, all the effects are estimated using expectation-maximization empirical Bayes algorithm, and all the non-zero effect vectors are further evaluated via likelihood-ratio test for significant QTLs. In Monte Carlo simulation studies, the new method has higher power in QTL detection, lower false positive rate, lower mean absolute deviation for QTL position estimate, and lower mean squared error for the estimate of QTL size (r²) than existing methods because the new method increases the power of detecting small-effect QTLs. In real dataset analysis, the new method (19) identified five more known genes than the existing three methods (14). This study provides an effective method for detecting small-effect QTLs in any MPPs.

Co-Localization of Resistance and Metabolic Quantitative Trait Loci on Carrot Genome Reveals Fungitoxic Terpenes and Related Candidate Genes Associated with the Resistance to Alternaria dauci

Alternaria leaf blight, caused by the fungus Alternaria dauci, is the most damaging foliar disease of carrot. Some carrot genotypes exhibit partial resistance to this pathogen and resistance Quantitative Trait Loci (rQTL) have been identified. Co-localization of metabolic QTL and rQTL identified camphene, α-pinene, α-bisabolene, β-cubebene, caryophyllene, germacrene D and α-humulene as terpenes potentially involved in carrot resistance against ALB. By combining genomic and transcriptomic analyses, we identified, under the co-localization regions, terpene-related genes which are differentially expressed between a resistant and a susceptible carrot genotype. These genes include five terpene synthases and twenty transcription factors. In addition, significant mycelial growth inhibition was observed in the presence of α-humulene and caryophyllene.

A QTL approach in faba bean highlights the conservation of genetic control of frost tolerance among legume species

Frost is a major abiotic stress of winter type faba beans (Vica faba L.) and has adverse effects on crop yield. Climate change, far from reducing the incidence of frost events, is making these phenomena more and more common, severe, and prolonged. Despite the important interaction that the environment has in the tolerance of faba bean to frost, this trait seems to have good levels of heritability. Several QTLs for frost tolerance have already been reported, however, a more robust identification is needed to more precisely identify the genomic regions involved in faba bean tolerance to sub-zero temperatures. Several pea (Pisum sativum L.) and barrel medic (Medicago truncatula L.) frost tolerance QTLs appear to be conserved between these two species, furthering the hypothesis that the genetic control of frost tolerance in legume species might be more generally conserved. In this work, the QTL mapping in two faba bean recombinant inbred line (RIL) populations connected by a common winter-type parent has led to the identification of five genomic regions involved in the control of frost tolerance on linkage groups I, III, IV, and V. Among them, a major and robust QTL of great interest for marker-assisted selection was identified on the lower part of the long-arm of LGI. The synteny between the faba bean frost tolerance QTLs and those previously identified in other legume species such as barrel medic, pea or soybean highlighted at least partial conservation of the genetic control of frost tolerance among different faba bean genetic pools and legume species. Four novel RILs showing high and stable levels of tolerance and the ability to recover from freezing temperatures by accumulating frost tolerance QTLs are now available for breeding programs.

WGNAM: whole-genome nested association mapping

A powerful QTL analysis method for nested association mapping populations is presented. Based on a one-stage multi-locus model, it provides accurate predictions of founder specific QTL effects. Nested association mapping (NAM) populations have been created to enable the identification of quantitative trait loci (QTL) in different genetic backgrounds. A whole-genome nested association mapping (WGNAM) method is presented to perform QTL analysis in NAM populations. The WGNAM method is an adaptation of the multi-parent whole genome average interval mapping approach where the crossing design is incorporated through the probability of inheriting founder alleles for every marker across the genome. Based on a linear mixed model, this method provides a one-stage analysis of raw phenotypic data, molecular markers, and crossing design. It simultaneously scans the whole-genome through an iterative process leading to a model with all the identified QTL while keeping the false positive rate low. The WGNAM approach was assessed through a simulation study, confirming to be a powerful and accurate method for QTL analysis for a NAM population. This novel method can also accommodate a multi-reference NAM (MR-NAM) population where donor parents are crossed with multiple reference parents to increase genetic diversity. Therefore, a demonstration is presented using a MR-NAM population for wheat (Triticum aestivum L.) to perform a QTL analysis for plant height. The strength and size of the putative QTL were summarized enhancing the understanding of the QTL effects depending on the parental origin. Compared to other methods, the proposed methodology based on a one-stage analysis provides greater power to detect QTL and increased accuracy in the estimation of their effects. The WGNAM method establishes the basis for accurate QTL mapping studies for NAM and MR-NAM populations.

Modeling allelic diversity of multiparent mapping populations affects detection of quantitative trait loci

The search for quantitative trait loci that explain complex traits such as yield and drought tolerance has been ongoing in all crops. Methods such as biparental quantitative trait loci mapping and genome-wide association studies each have their own advantages and limitations. Multiparent advanced generation intercross populations contain more recombination events and genetic diversity than biparental mapping populations and are better able to estimate effect sizes of rare alleles than association mapping populations. Here, we discuss the results of using a multiparent advanced generation intercross population of doubled haploid maize lines created from 16 diverse founders to perform quantitative trait loci mapping. We compare 3 models that assume bi-allelic, founder, and ancestral haplotype allelic states for quantitative trait loci. The 3 methods have differing power to detect quantitative trait loci for a variety of agronomic traits. Although the founder approach finds the most quantitative trait loci, all methods are able to find unique quantitative trait loci, suggesting that each model has advantages for traits with different genetic architectures. A closer look at a well-characterized flowering time quantitative trait loci, qDTA8, which contains vgt1, highlights the strengths and weaknesses of each method and suggests a potential epistatic interaction. Overall, our results reinforce the importance of considering different approaches to analyzing genotypic datasets, and shows the limitations of binary SNP data for identifying multiallelic quantitative trait loci.

An IBD-based mixed model approach for QTL mapping in multiparental populations

The identity-by-descent (IBD)-based mixed model approach introduced in this study can detect quantitative trait loci (QTLs) referring to the parental origin and simultaneously account for multilevel relatedness of individuals within and across families. This unified approach is proved to be a powerful approach for all kinds of multiparental population (MPP) designs. Multiparental populations (MPPs) have become popular for quantitative trait loci (QTL) detection. Tools for QTL mapping in MPPs are mostly developed for specific MPPs and do not generalize well to other MPPs. We present an IBD-based mixed model approach for QTL mapping in all kinds of MPP designs, e.g., diallel, Nested Association Mapping (NAM), and Multiparental Advanced Generation Intercross (MAGIC) designs. The first step is to compute identity-by-descent (IBD) probabilities using a general Hidden Markov model framework, called reconstructing ancestry blocks bit by bit (RABBIT). Next, functions of IBD information are used as design matrices, or genetic predictors, in a mixed model approach to estimate variance components for multiallelic genetic effects associated with parents. Family-specific residual genetic effects are added, and a polygenic effect is structured by kinship relations between individuals. Case studies of simulated diallel, NAM, and MAGIC designs proved that the advanced IBD-based multi-QTL mixed model approach incorporating both kinship relations and family-specific residual variances (IBD.MQMkin_F) is robust across a variety of MPP designs and allele segregation patterns in comparison to a widely used benchmark association mapping method, and in most cases, outperformed or behaved at least as well as other tools developed for specific MPP designs in terms of mapping power and resolution. Successful analyses of real data cases confirmed the wide applicability of our IBD-based mixed model methodology.

Meta-analysis of QTL reveals the genetic control of yield-related traits and seed protein content in pea

Pea is one of the most important grain legume crops in temperate regions worldwide. Improving pea yield is a critical breeding target. Nine inter-connected pea recombinant inbred line populations were evaluated in nine environments at INRAE Dijon, France and genotyped using the GenoPea 13.2 K SNP array. Each population has been evaluated in two to four environments. A multi-population Quantitative Trait Loci (QTL) analysis for seed weight per plant (SW), seed number per plant (SN), thousand seed weight (TSW) and seed protein content (SPC) was done. QTL were then projected on the multi-population consensus map and a meta-analysis of QTL was performed. This analysis identified 17 QTL for SW, 16 QTL for SN, 35 QTL for TSW and 21 QTL for SPC, shedding light on trait relationships. These QTL were resolved into 27 metaQTL. Some of them showed small confidence intervals of less than 2 cM encompassing less than one hundred underlying candidate genes. The precision of metaQTL and the potential candidate genes reported in this study enable their use for marker-assisted selection and provide a foundation towards map-based identification of causal polymorphisms.

Multi-parent multi-environment QTL analysis: an illustration with the EU-NAM Flint population

Multi-parent populations multi-environment QTL experiments data should be analysed jointly to estimate the QTL effect variation within the population and between environments. Commonly, QTL detection in multi-parent populations (MPPs) data measured in multiple environments (ME) is done by analyzing genotypic values 'averaged' across environments. This method ignores the environment-specific QTL (QTLxE) effects. Running separate single environment analyses is a possibility to measure QTLxE effects, but those analyses do not model the genetic covariance due to the use of the same genotype in different environments. In this paper, we propose methods to analyse MPP-ME QTL experiments using simultaneously the data from several environments and modelling the genotypic covariance. Using data from the EU-NAM Flint population, we show that these methods estimate the QTLxE effects and that they can improve the quality of the QTL detection. Those methods also have a larger inference power. For example, they can be extended to integrate environmental indices like temperature or precipitation to better understand the mechanisms behind the QTLxE effects. Therefore, our methodology allows the exploitation of the full MPP-ME data potential: to estimate QTL effect variation (a) within the MPP between sub-populations due to different genetic backgrounds and (b) between environments.

Discovery of interesting new polymorphisms in a sugar beet (elite [Formula: see text] exotic) progeny by comparison with an elite panel

KEY MESSAGE

The comparison of QTL detection performed on an elite panel and an (elite [Formula: see text] exotic) progeny shows that introducing exotic germplasm into breeding programs can bring new interesting allelic diversity. Selection of stable varieties producing the highest amount of extractable sugar per hectare (ha), resistant to diseases, and respecting environmental criteria is undoubtedly the main target for sugar beet breeding. As sodium, potassium, and [Formula: see text]-amino nitrogen in sugar beets are the impurities that have the biggest negative impact on white sugar extraction, it is interesting to reduce their concentration in further varieties. However, domestication history and strong selection pressures have affected the genetic diversity needed to achieve this goal. In this study, quantitative trait locus (QTL) detection was performed on two populations, an (elite [Formula: see text] exotic) sugar beet progeny and an elite panel, to find potentially new interesting regions brought by the exotic accession. The three traits linked with impurities content were studied. Some QTLs were detected in both populations, the majority in the elite panel because of most statistical power. Some of the QTLs were colocated and had favorable effect in the progeny since the exotic allele was linked with a decrease in the impurity content. A few number of favorable QTLs were detected in the progeny, only. Consequently, introgressing exotic genetic material into sugar beet breeding programs can allow the incorporation of new interesting alleles.

The complex genetic architecture of shoot growth natural variation in Arabidopsis thaliana

One of the main outcomes of quantitative genetics approaches to natural variation is to reveal the genetic architecture underlying the phenotypic space. Complex genetic architectures are described as including numerous loci (or alleles) with small-effect and/or low-frequency in the populations, interactions with the genetic background, environment or age. Linkage or association mapping strategies will be more or less sensitive to this complexity, so that we still have an unclear picture of its extent. By combining high-throughput phenotyping under two environmental conditions with classical QTL mapping approaches in multiple Arabidopsis thaliana segregating populations as well as advanced near isogenic lines construction and survey, we have attempted to improve our understanding of quantitative phenotypic variation. Integrative traits such as those related to vegetative growth used in this work (highlighting either cumulative growth, growth rate or morphology) all showed complex and dynamic genetic architecture with respect to the segregating population and condition. The more resolutive our mapping approach, the more complexity we uncover, with several instances of QTLs visible in near isogenic lines but not detected with the initial QTL mapping, indicating that our phenotyping accuracy was less limiting than the mapping resolution with respect to the underlying genetic architecture. In an ultimate approach to resolve this complexity, we intensified our phenotyping effort to target specifically a 3Mb-region known to segregate for a major quantitative trait gene, using a series of selected lines recombined every 100kb. We discovered that at least 3 other independent QTLs had remained hidden in this region, some with trait- or condition-specific effects, or opposite allelic effects. If we were to extrapolate the figures obtained on this specific region in this particular cross to the genome- and species-scale, we would predict hundreds of causative loci of detectable phenotypic effect controlling these growth-related phenotypes.

Development and validation of whole genome-wide and genic microsatellite markers in oil palm (Elaeis guineensis Jacq.): First microsatellite database (OpSatdb)

The availability of large expressed sequence tag (EST) and whole genome databases of oil palm enabled the development of a data base of microsatellite markers. For this purpose, an EST database consisting of 40,979 EST sequences spanning 27 Mb and a chromosome-wise whole genome databases were downloaded. A total of 3,950 primer pairs were identified and developed from EST sequences. The tri and tetra nucleotide repeat motifs were most prevalent (each 24.75%) followed by di-nucleotide repeat motifs. Whole genome-wide analysis found a total of 245,654 SSR repeats across the 16 chromosomes of oil palm, of which 38,717 were compound microsatellite repeats. A web application, OpSatdb, the first microsatellite database of oil palm, was developed using the PHP and MySQL database ( https://ssr.icar.gov.in/index.php ). It is a simple and systematic web-based search engine for searching SSRs based on repeat motif type, repeat type, and primer details. High synteny was observed between oil palm and rice genomes. The mapping of ESTs having SSRs by Blast2GO resulted in the identification of 19.2% sequences with gene ontology (GO) annotations. Randomly, a set of ten genic SSRs and five genomic SSRs were used for validation and genetic diversity on 100 genotypes belonging to the world oil palm genetic resources. The grouping pattern was observed to be broadly in accordance with the geographical origin of the genotypes. The identified genic and genome-wide SSRs can be effectively useful for various genomic applications of oil palm, such as genetic diversity, linkage map construction, mapping of QTLs, marker-assisted selection, and comparative population studies.

Efficient QTL detection of flowering date in a soybean RIL population using the novel restricted two-stage multi-locus GWAS procedure

KEY MESSAGE

Eighty-six R1 QTLs accounting for 89.92% phenotypic variance in a soybean RIL population were identified using RTM-GWAS with SNPLDB marker which performed superior over CIM and MLM-GWAS with BIN/SNPLDB marker. A population (NJRIKY) composed of 427 recombinant inbred lines (RILs) derived from Kefeng-1 × NN1138-2 (MGII × MGV, MG maturity group) was applied for detecting flowering date (R1) quantitative trait locus (QTL) system in soybean. From a low-depth re-sequencing (~ 0.75 ×), 576,874 SNPs were detected and organized into 4737 BINs (recombination breakpoint determinations) and 3683 SNP linkage disequilibrium blocks (SNPLDBs), respectively. Using the association mapping procedures "Restricted Two-stage Multi-locus Genome-wide Association Study" (RTM-GWAS), "Mixed Linear Model Genome-wide Association Study" (MLM-GWAS) and the linkage mapping procedure "Composite Interval Mapping" (CIM), 67, 36 and 10 BIN-QTLs and 86, 14 and 23 SNPLDB-QTLs were detected with their phenotypic variance explained (PVE) 88.70-89.92% (within heritability 98.2%), 146.41-353.62% (overflowing) and 88.29-172.34% (overflowing), respectively. The RTM-GWAS with SNPLDBs which showed to be more efficient and reasonable than the others was used to identify the R1 QTL system in NJRIKY. The detected 86 SNPLDB-QTLs with their PVE from 0.02 to 30.66% in a total of 89.92% covered 51 out of 104 R1 QTLs in 18 crosses in SoyBase and 26 out of 139 QTLs in a nested association mapping population, while the rest 29 QTLs were novel ones. From the QTL system, 52 candidate genes were annotated, including the verified gene E1, E2, E9 and J, and grouped into 3 categories of biological processes, among which 24 genes were enriched into three protein-protein interaction networks, suggesting gene networks working together. Since NJRIKY involves only MGII and MGV, the QTL/gene system among MG000-MGX should be explored further.

Different genetic architectures underlie crop responses to the same pathogen: the {Helianthus annuus * Phoma macdonaldii} interaction case for black stem disease and premature ripening

BACKGROUND

Phoma macdonaldii has been reported as the causal agent of black stem disease (BS) and premature ripening (PR) on sunflower. PR is considered as the most widespread and detrimental disease on sunflower in France. While genetic variability and QTL mapping for partial resistance of sunflower to stem, collar and roots attacks have been reported on plantlets in controlled conditions, this work aims to describe the genetic variability in a subset of a sunflower lines, and for the first time to map QTL involved in PR resistance evaluated in field conditions using controlled inoculation.

RESULTS

An efficient and reliable method for inoculation used in field experiments induced stem base necrosis on up to 98% of all plants. A significant genetic variability for PR resistance in the field was detected among the 20 inbred lines of the core collection tested across the two years. For QTL mapping, the PR resistance evaluation was performed on two recombinant inbred lines (RIL) populations derived from the crosses XRQxPSC8 and FUxPAZ2 in two different years. QTL analyses were based on a newly developed consensus genetic map comprising 1007 non-redundant molecular markers. In each of the two RIL populations, different QTL involved in PR partial sunflower resistance were detected. The most significant QTL were detected 49 days post infection (DPI) on LG10 (LOD 7.7) and on LG7 (LOD 12.1) in the XRQxPSC8 and FUxPAZ2 RIL population, respectively. In addition, different QTL were detected on both populations for PR resistance measured between 14 and 35 DPI. In parallel, the incidence of natural attack of P. macdonaldii resulting in BS disease was recorded, showing that in these populations, the genetic of resistance to both diseases is not governed by the same factors.

CONCLUSION

This work provides the first insights on the genetic architecture of sunflower PR resistance in the field. Moreover, the separate studies of symptoms on different organs and in time series allowed the identification of a succession of genetic components involved in the sunflower resistance to PR and BS diseases caused by Phoma macdonaldii along the development of the {plant * pathogen} interaction.

How do the type of QTL effect and the form of the residual term influence QTL detection in multi-parent populations? A case study in the maize EU-NAM population

In the QTL analysis of multi-parent populations, the inclusion of QTLs with various types of effects can lead to a better description of the phenotypic variation and increased power. For the type of QTL effect in QTL models for multi-parent populations (MPPs), various options exist to define them with respect to their origin. They can be modelled as referring to close parental lines or to further away ancestral founder lines. QTL models for MPPs can also be characterized by the homo- or heterogeneity of variance for polygenic effects. The most suitable model for the origin of the QTL effect and the homo- or heterogeneity of polygenic effects may be a function of the genetic distance distribution between the parents of MPPs. We investigated the statistical properties of various QTL detection models for MPPs taking into account the genetic distances between the parents of the MPP. We evaluated models with different assumptions about the QTL effect and the form of the residual term using cross validation. For the EU-NAM data, we showed that it can be useful to mix in the same model QTLs with different types of effects (parental, ancestral, or bi-allelic). The benefit of using cross-specific residual terms to handle the heterogeneity of variance was less obvious for this particular data set.

Background controlled QTL mapping in pure-line genetic populations derived from four-way crosses

Pure lines derived from multiple parents are becoming more important because of the increased genetic diversity, the possibility to conduct replicated phenotyping trials in multiple environments and potentially high mapping resolution of quantitative trait loci (QTL). In this study, we proposed a new mapping method for QTL detection in pure-line populations derived from four-way crosses, which is able to control the background genetic variation through a two-stage mapping strategy. First, orthogonal variables were created for each marker and used in an inclusive linear model, so as to completely absorb the genetic variation in the mapping population. Second, inclusive composite interval mapping approach was implemented for one-dimensional scanning, during which the inclusive linear model was employed to control the background variation. Simulation studies using different genetic models demonstrated that the new method is efficient when considering high detection power, low false discovery rate and high accuracy in estimating quantitative trait loci locations and effects. For illustration, the proposed method was applied in a reported wheat four-way recombinant inbred line population.

Genome-wide association studies with proteomics data reveal genes important for synthesis, transport and packaging of globulins in legume seeds

Improving nutritional seed quality is an important challenge in grain legume breeding. However, the genes controlling the differential accumulation of globulins, which are major contributors to seed nutritional value in legumes, remain largely unknown. We combined a search for protein quantity loci with genome-wide association studies on the abundance of 7S and 11S globulins in seeds of the model legume species Medicago truncatula. Identified genomic regions and genes carrying polymorphisms linked to globulin variations were then cross-compared with pea (Pisum sativum), leading to the identification of candidate genes for the regulation of globulin abundance in this crop. Key candidates identified include genes involved in transcription, chromatin remodeling, post-translational modifications, transport and targeting of proteins to storage vacuoles. Inference of a gene coexpression network of 12 candidate transcription factors and globulin genes revealed the transcription factor ABA-insensitive 5 (ABI5) as a highly connected hub. Characterization of loss-of-function abi5 mutants in pea uncovered a role for ABI5 in controlling the relative abundance of vicilin, a sulfur-poor 7S globulin, in pea seeds. This demonstrates the feasibility of using genome-wide association studies in M. truncatula to reveal genes that can be modulated to improve seed nutritional value.

Genetic architecture of threshold reaction norms for male alternative reproductive tactics in Atlantic salmon (Salmo salar L.)

Alternative mating tactics have important ecological and evolutionary implications and are determined by complex interactions between environmental and genetic factors. Here, we study the genetic effect and architecture of the variability in reproductive tactics among Atlantic salmon males which can either mature sexually early in life in freshwater or more commonly only after completing a migration at sea. We applied the latent environmental threshold model (LETM), which provides a conceptual framework linking individual status to a threshold controlling the decision to develop alternative traits, in an innovative experimental design using a semi-natural river which allowed for ecologically relevant phenotypic expression. Early male parr maturation rates varied greatly across families (10 to 93%) which translated into 90% [64–100%] of the phenotypic variation explained by genetic variation. Three significant QTLs were found for the maturation status, however only one collocated with a highly significant QTL explaining 20.6% of the variability of the maturation threshold located on chromosome 25 and encompassing a locus previously shown to be linked to sea age at maturity in anadromous Atlantic salmon. These results provide new empirical illustration of the relevance of the LETM for a better understanding of alternative mating tactics evolution in natural populations.

Nested Association Mapping of Stem Rust Resistance in Wheat Using Genotyping by Sequencing

We combined the recently developed genotyping by sequencing (GBS) method with joint mapping (also known as nested association mapping) to dissect and understand the genetic architecture controlling stem rust resistance in wheat (Triticum aestivum). Ten stem rust resistant wheat varieties were crossed to the susceptible line LMPG-6 to generate F6 recombinant inbred lines. The recombinant inbred line populations were phenotyped in Kenya, South Africa, and St. Paul, Minnesota, USA. By joint mapping of the 10 populations, we identified 59 minor and medium-effect QTL (explained phenotypic variance range of 1% - 20%) on 20 chromosomes that contributed towards adult plant resistance to North American Pgt races as well as the highly virulent Ug99 race group. Fifteen of the 59 QTL were detected in multiple environments. No epistatic relationship was detected among the QTL. While these numerous small- to medium-effect QTL are shared among the families, the founder parents were found to have different allelic effects for the QTL. Fourteen QTL identified by joint mapping were also detected in single-population mapping. As these QTL were mapped using SNP markers with known locations on the physical chromosomes, the genomic regions identified with QTL could be explored more in depth to discover candidate genes for stem rust resistance. The use of GBS-derived de novo SNPs in mapping resistance to stem rust shown in this study could be used as a model to conduct similar marker-trait association studies in other plant species.

Sunflower Resistance to Broomrape (Orobanche cumana) Is Controlled by Specific QTLs for Different Parasitism Stages

Orobanche cumana (sunflower broomrape) is an obligatory and non-photosynthetic root parasitic plant that specifically infects the sunflower. It is located in Europe and in Asia, where it can cause yield losses of over 80%. More aggressive races have evolved, mainly around the Black Sea, and broomrape can rapidly spread to new areas. Breeding for resistance seems to be the most efficient and sustainable approach to control broomrape infestation. In our study, we used a population of 101 recombinant inbred lines (RILs), derived from a cross between the two lines HA89 and LR1 (a line derived from an interspecific cross with Helianthus debilis). Rhizotrons, pots and field experiments were used to characterize all RILs for their resistance to O. cumana race F parasitism at three post vascular connection life stages: (i) early attachment of the parasite to the sunflower roots, (ii) young tubercle and (iii) shoot emergence. In addition, RIL resistance to race G at young tubercle development stage was evaluated in pots. The entire population was genotyped, and QTLs were mapped. Different QTLs were identified for each race (F from Spain and G from Turkey) and for the three stages of broomrape development. The results indicate that there are several quantitative resistance mechanisms controlling the infection by O. cumana that can be used in sunflower breeding.

Choice of models for QTL mapping with multiple families and design of the training set for prediction of Fusarium resistance traits in maize

KEY MESSAGE

QTL analysis for Fusarium resistance traits with multiple connected families detected more QTL than single-family analysis. Prediction accuracy was tightly associated with the kinship of the validation and training set.

ABSTRACT

QTL mapping has recently shifted from analysis of single families to multiple, connected families and several biometric models have been suggested. Using a high-density consensus map with 2472 marker loci, we performed QTL mapping with five connected bi-parental families with 639 doubled-haploid (DH) lines in maize for ear rot resistance and analyzed traits DON, Gibberella ear rot severity (GER), and days to silking (DS). Five biometric models differing in the assumption about the number and effects of alleles at QTL were compared. Model 2 to 5 performing joint analyses across all families and using linkage and/or linkage disequilibrium (LD) information identified all and even further QTL than Model 1 (single-family analyses) and generally explained a higher proportion pG of the genotypic variance for all three traits. QTL for DON and GER were mostly family specific, but several QTL for DS occurred in multiple families. Many QTL displayed large additive effects and most alleles increasing resistance originated from a resistant parent. Interactions between detected QTL and genetic background (family) occurred rarely and were comparatively small. Detailed analysis of three fully connected families yielded higher pG values for Model 3 or 4 than for Model 2 and 5, irrespective of the size NTS of the training set (TS). In conclusion, Model 3 and 4 can be recommended for QTL-based prediction with larger families. Including a sufficiently large number of full sibs in the TS helped to increase QTL-based prediction accuracy (rVS) for various scenarios differing in the composition of the TS.

A Random-Model Approach to QTL Mapping in Multiparent Advanced Generation Intercross (MAGIC) Populations

Most standard QTL mapping procedures apply to populations derived from the cross of two parents. QTL detected from such biparental populations are rarely relevant to breeding programs because of the narrow genetic basis: only two alleles are involved per locus. To improve the generality and applicability of mapping results, QTL should be detected using populations initiated from multiple parents, such as the multiparent advanced generation intercross (MAGIC) populations. The greatest challenges of QTL mapping in MAGIC populations come from multiple founder alleles and control of the genetic background information. We developed a random-model methodology by treating the founder effects of each locus as random effects following a normal distribution with a locus-specific variance. We also fit a polygenic effect to the model to control the genetic background. To improve the statistical power for a scanned marker, we release the marker effect absorbed by the polygene back to the model. In contrast to the fixed-model approach, we estimate and test the variance of each locus and scan the entire genome one locus at a time using likelihood-ratio test statistics. Simulation studies showed that this method can increase statistical power and reduce type I error compared with composite interval mapping (CIM) and multiparent whole-genome average interval mapping (MPWGAIM). We demonstrated the method using a public Arabidopsis thaliana MAGIC population and a mouse MAGIC population.

QTL mapping of carrot resistance to leaf blight with connected populations: stability across years and consequences for breeding

Combining biparental and multiparental connected population analyses was useful for the identification of 11 QTLs in two new genetic backgrounds of carrot resistance to Alternaria dauci and for breeding recommendations. Leaf blight due to the fungus Alternaria dauci is the major carrot foliar disease worldwide. Some resistance QTLs have been previously identified in one population, but the evaluation of additional genetic backgrounds with higher level of resistance would give opportunities for breeders to combine them by pyramiding. For this purpose, two segregating populations were evaluated twice across 4 years in the same environment (1) to compare the efficiency of the single vs. the connected populations approach for characterizing the new sources of carrot resistance to Alternaria dauci; (2) to evaluate the stability of QTLs over the years; and (3) to give recommendations to breeders for marker-assisted selection. Single and connected analyses were complementary; their combination allowed the detection of 11 QTLs. Connected analyses allowed the identification of common and specific QTLs among the two populations and the most favorable allele at each QTL. Important contrasts between allelic effects were observed with four and five most favorable alleles coming from the two resistant parental lines, whereas two other favorable alleles came from the susceptible parental line. While four QTLs were consistent across years, seven were detected within a single year. The heritabilities for both populations PC2 and PC3 were high (75 and 78%, respectively), suggesting that the resistance of carrot to A. dauci was little affected by these environmental conditions, but the instability of QTL over years may be due to changing environmental conditions. The complementarity between these parental lines in terms of interesting allelic combinations is also discussed.

Genetic architecture of pollination syndrome transition between hummingbird-specialist and generalist species in the genus Rhytidophyllum (Gesneriaceae)

Adaptation to pollinators is a key factor of diversification in angiosperms. The Caribbean sister genera Rhytidophyllum and Gesneria present an important diversification of floral characters. Most of their species can be divided in two major pollination syndromes. Large-open flowers with pale colours and great amount of nectar represent the generalist syndrome, while the hummingbird-specialist syndrome corresponds to red tubular flowers with a less important nectar volume. Repeated convergent evolution toward the generalist syndrome in this group suggests that such transitions rely on few genes of moderate to large effect. To test this hypothesis, we built a linkage map and performed a QTL detection for divergent pollination syndrome traits by crossing one specimen of the generalist species Rhytidophyllum auriculatum with one specimen of the hummingbird pollinated R. rupincola. Using geometric morphometrics and univariate traits measurements, we found that floral shape among the second-generation hybrids is correlated with morphological variation observed between generalist and hummingbird-specialist species at the genus level. The QTL analysis showed that colour and nectar volume variation between syndromes involve each one major QTL while floral shape has a more complex genetic basis and rely on few genes of moderate effect. Finally, we did not detect any genetic linkage between the QTLs underlying those traits. This genetic independence of traits could have facilitated evolution toward optimal syndromes.

QTL for fatty acid composition and yield in linseed (Linum usitatissimum L.)

The combined SSR-SNP map and 20 QTL for agronomic and quality traits will assist in marker assisted breeding as well as map-based cloning of key genes in linseed. Flax is an important nutraceutical crop mostly because it is a rich source of omega-3 fatty acids and antioxidant compounds. Canada is the largest producer and exporter of oilseed flax (or linseed), creating a growing need to improve crop productivity and quality. In this study, a genetic map was constructed based on selected 329 single nucleotide polymorphic markers and 362 simple sequence repeat markers using a recombinant inbred line population of 243 individuals from a cross between the Canadian varieties CDC Bethune and Macbeth. The genetic map consisted of 15 linkage groups comprising 691 markers with an average marker density of one marker every 1.9 cM. A total of 20 quantitative trait loci (QTL) were identified corresponding to 14 traits. Three QTL each for oleic acid and stearic acid, two QTL each for linoleic acid and iodine value and one each for palmitic acid, linolenic acid, oil content, seed protein, cell wall, straw weight, thousand seed weight, seeds per boll, yield and days to maturity were identified. The QTL for cell wall, straw weight, seeds per boll, yield and days to maturity all co-located on linkage group 4. Analysis of the candidate gene regions underlying the QTL identified proteins involved in cell wall and fibre synthesis, fatty acid biosynthesis as well as their metabolism and yield component traits. This study provides the foundation for assisting in map-based cloning of the QTL and marker assisted selection of a wide range of quality and agronomic traits in linseed and potentially fibre flax.

Improving resistance to the European corn borer: a comprehensive study in elite maize using QTL mapping and genome-wide prediction

The efficiency of marker-assisted selection for native resistance to European corn borer stalk damage can be increased when progressing from a QTL-based towards a genome-wide approach. Marker-assisted selection (MAS) has been shown to be effective in improving resistance to the European corn borer (ECB) in maize. In this study, we investigated the performance of whole-genome-based selection, relative to selection based on individual quantitative trait loci (QTL), for resistance to ECB stalk damage in European elite maize. Three connected biparental populations, comprising 590 doubled haploid (DH) lines, were genotyped with high-density single nucleotide polymorphism markers and phenotyped under artificial and natural infestation in 2011. A subset of 195 DH lines was evaluated in the following year as lines per se and as testcrosses. Resistance was evaluated based on stalk damage ratings, the number of feeding tunnels in the stalk and tunnel length. We performed individual- and joint-population QTL analyses and compared the cross-validated predictive abilities of the QTL models with genomic best linear unbiased prediction (GBLUP). For all traits, the GBLUP model consistently outperformed the QTL model despite the detection of QTL with sizeable effects. For stalk damage rating, GBLUP's predictive ability exceeded at times 0.70. Model training based on DH line per se performance was efficient in predicting stalk breakage in testcrosses. We conclude that the efficiency of MAS for ECB stalk damage resistance can be increased considerably when progressing from a QTL-based towards a genome-wide approach. With the availability of native ECB resistance in elite European maize germplasm, our results open up avenues for the implementation of an integrated genome-based selection approach for the simultaneous improvement of yield, maturity and ECB resistance.

Linkage mapping of Barley yellow dwarf virus resistance in connected populations of maize

BACKGROUND

With increasing winter temperatures, Barley yellow dwarf virus (BYDV) is expected to become an increasing problem in maize cultivation in Germany. Earlier studies revealed that BYDV has a negative impact on maize performance. Molecular markers would accelerate the development of BYDV resistant maize. Therefore, the objectives of this study were (i) the identification of quantitative trait loci (QTL) for BYDV resistance in five connected segregating maize populations in a field experiment and (ii) their comparison with the QTL detected under greenhouse conditions.

RESULTS

In linkage analyses of the traits virus extinction, infection rate, and the symptom red edges, a highly associated major QTL was identified on chromosome 10. This QTL explained 45% of the phenotypic variance for the traits virus extinction and infection rate and 30% for the symptom red edges.

CONCLUSION

We could show that BYDV resistance traits are oligogenically inherited. The QTL on chromosome 10 could be observed in the connected linkage analyses and in the single population analyses. Furthermore, this QTL could also be confirmed in the greenhouse experiment. Our results let suggest that this QTL is involved in multiple virus resistance and the markers are promising for marker assisted selection.

Linkage disequilibrium with linkage analysis of multiline crosses reveals different multiallelic QTL for hybrid performance in the flint and dent heterotic groups of maize

Multiparental designs combined with dense genotyping of parents have been proposed as a way to increase the diversity and resolution of quantitative trait loci (QTL) mapping studies, using methods combining linkage disequilibrium information with linkage analysis (LDLA). Two new nested association mapping designs adapted to European conditions were derived from the complementary dent and flint heterotic groups of maize (Zea mays L.). Ten biparental dent families (N = 841) and 11 biparental flint families (N = 811) were genotyped with 56,110 single nucleotide polymorphism markers and evaluated as test crosses with the central line of the reciprocal design for biomass yield, plant height, and precocity. Alleles at candidate QTL were defined as (i) parental alleles, (ii) haplotypic identity by descent, and (iii) single-marker groupings. Between five and 16 QTL were detected depending on the model, trait, and genetic group considered. In the flint design, a major QTL (R(2) = 27%) with pleiotropic effects was detected on chromosome 10, whereas other QTL displayed milder effects (R(2) < 10%). On average, the LDLA models detected more QTL but generally explained lower percentages of variance, consistent with the fact that most QTL display complex allelic series. Only 15% of the QTL were common to the two designs. A joint analysis of the two designs detected between 15 and 21 QTL for the five traits. Of these, between 27 for silking date and 41% for tasseling date were significant in both groups. Favorable allelic effects detected in both groups open perspectives for improving biomass production.

Genetic control of water use efficiency and leaf carbon isotope discrimination in sunflower (Helianthus annuus L.) subjected to two drought scenarios

High water use efficiency (WUE) can be achieved by coordination of biomass accumulation and water consumption. WUE is physiologically and genetically linked to carbon isotope discrimination (CID) in leaves of plants. A population of 148 recombinant inbred lines (RILs) of sunflower derived from a cross between XRQ and PSC8 lines was studied to identify quantitative trait loci (QTL) controlling WUE and CID, and to compare QTL associated with these traits in different drought scenarios. We conducted greenhouse experiments in 2011 and 2012 by using 100 balances which provided a daily measurement of water transpired, and we determined WUE, CID, biomass and cumulative water transpired by plants. Wide phenotypic variability, significant genotypic effects, and significant negative correlations between WUE and CID were observed in both experiments. A total of nine QTL controlling WUE and eight controlling CID were identified across the two experiments. A QTL for phenotypic response controlling WUE and CID was also significantly identified. The QTL for WUE were specific to the drought scenarios, whereas the QTL for CID were independent of the drought scenarios and could be found in all the experiments. Our results showed that the stable genomic regions controlling CID were located on the linkage groups 06 and 13 (LG06 and LG13). Three QTL for CID were co-localized with the QTL for WUE, biomass and cumulative water transpired. We found that CID and WUE are highly correlated and have common genetic control. Interestingly, the genetic control of these traits showed an interaction with the environment (between the two drought scenarios and control conditions). Our results open a way for breeding higher WUE by using CID and marker-assisted approaches and therefore help to maintain the stability of sunflower crop production.

QTL analysis of frost damage in pea suggests different mechanisms involved in frost tolerance

KEY MESSAGE

Avoidance mechanisms and intrinsic resistance are complementary strategies to improve winter frost tolerance and yield potential in field pea. The development of the winter pea crop represents a major challenge to expand plant protein production in temperate areas. Breeding winter cultivars requires the combination of freezing tolerance as well as high seed productivity and quality. In this context, we investigated the genetic determinism of winter frost tolerance and assessed its genetic relationship with yield and developmental traits. Using a newly identified source of frost resistance, we developed a population of recombinant inbred lines and evaluated it in six environments in Dijon and Clermont-Ferrand between 2005 and 2010. We developed a genetic map comprising 679 markers distributed over seven linkage groups and covering 947.1 cM. One hundred sixty-one quantitative trait loci (QTL) explaining 9-71 % of the phenotypic variation were detected across the six environments for all traits measured. Two clusters of QTL mapped on the linkage groups III and one cluster on LGVI reveal the genetic links between phenology, morphology, yield-related traits and frost tolerance in winter pea. QTL clusters on LGIII highlighted major developmental gene loci (Hr and Le) and the QTL cluster on LGVI explained up to 71 % of the winter frost damage variation. This suggests that a specific architecture and flowering ideotype defines frost tolerance in winter pea. However, two consistent frost tolerance QTL on LGV were independent of phenology and morphology traits, showing that different protective mechanisms are involved in frost tolerance. Finally, these results suggest that frost tolerance can be bred independently to seed productivity and quality.

Clusthaplo: a plug-in for MCQTL to enhance QTL detection using ancestral alleles in multi-cross design

We enhance power and accuracy of QTL mapping in multiple related families, by clustering the founders of the families on their local genomic similarity. MCQTL is a linkage mapping software application that allows the joint QTL mapping of multiple related families. In its current implementation, QTLs are modeled with one or two parameters for each parent that is a founder of the multi-cross design. The higher the number of parents, the higher the number of model parameters which can impact the power and the accuracy of the mapping. We propose to make use of the availability of denser and denser genotyping information on the founders to lessen the number of MCQTL parameters and thus boost the QTL discovery. We developed clusthaplo, an R package ( http://cran.r-project.org/web/packages/clusthaplo/index.html ), which aims to cluster haplotypes using a genomic similarity that reflects the probability of sharing the same ancestral allele. Computed in a sliding window along the genome and followed by a clustering method, the genomic similarity allows the local clustering of the parent haplotypes. Our assumption is that the haplotypes belonging to the same class transmit the same ancestral allele. So their putative QTL allelic effects can be modeled with the same parameter, leading to a parsimonious model, that is plugged in MCQTL. Intensive simulations using three maize data sets showed the significant gain in power and in accuracy of the QTL mapping with the ancestral allele model compared to the classical MCQTL model. MCQTL_LD (clusthaplo outputs plug in MCQTL) is a versatile and powerful tool for QTL mapping in multiple related families that makes use of linkage and linkage disequilibrium (web site http://carlit.toulouse.inra.fr/MCQTL/ ).

Quantitative trait loci from the host genetic background modulate the durability of a resistance gene: a rational basis for sustainable resistance breeding in plants

The combination of major resistance genes with quantitative resistance factors is hypothesized as a promising breeding strategy to preserve the durability of resistant cultivar, as recently observed in different pathosystems. Using the pepper (Capsicum annuum)/Potato virus Y (PVY, genus Potyvirus) pathosystem, we aimed at identifying plant genetic factors directly affecting the frequency of virus adaptation to the major resistance gene pvr2(3) and at comparing them with genetic factors affecting quantitative resistance. The resistance breakdown frequency was a highly heritable trait (h(2)=0.87). Four loci including additive quantitative trait loci (QTLs) and epistatic interactions explained together 70% of the variance of pvr2(3) breakdown frequency. Three of the four QTLs controlling pvr2(3) breakdown frequency were also involved in quantitative resistance, strongly suggesting that QTLs controlling quantitative resistance have a pleiotropic effect on the durability of the major resistance gene. With the first mapping of QTLs directly affecting resistance durability, this study provides a rationale for sustainable resistance breeding. Surprisingly, a genetic trade-off was observed between the durability of PVY resistance controlled by pvr2(3) and the spectrum of the resistance against different potyviruses. This trade-off seemed to have been resolved by the combination of minor-effect durability QTLs under long-term farmer selection.

MAPfastR: quantitative trait loci mapping in outbred line crosses

MAPfastR is a software package developed to analyze quantitative trait loci data from inbred and outbred line-crosses. The package includes a number of modules for fast and accurate quantitative trait loci analyses. It has been developed in the R language for fast and comprehensive analyses of large datasets. MAPfastR is freely available at: http://www.computationalgenetics.se/?page_id=7

Emerging paradigms in genomics-based crop improvement

Next generation sequencing platforms and high-throughput genotyping assays have remarkably expedited the pace of development of genomic tools and resources for several crops. Complementing the technological developments, conceptual shifts have also been witnessed in designing experimental populations. Availability of second generation mapping populations encompassing multiple alleles, multiple traits, and extensive recombination events is radically changing the phenomenon of classical QTL mapping. Additionally, the rising molecular breeding approaches like marker assisted recurrent selection (MARS) that are able to harness several QTLs are of particular importance in obtaining a "designed" genotype carrying the most desirable combinations of favourable alleles. Furthermore, rapid generation of genome-wide marker data coupled with easy access to precise and accurate phenotypic screens enable large-scale exploitation of LD not only to discover novel QTLs via whole genome association scans but also to practise genomic estimated breeding value (GEBV)-based selection of genotypes. Given refinements being experienced in analytical methods and software tools, the multiparent populations will be the resource of choice to undertake genome wide association studies (GWAS), multiparent MARS, and genomic selection (GS). With this, it is envisioned that these high-throughput and high-power molecular breeding methods would greatly assist in exploiting the enormous potential underlying breeding by design approach to facilitate accelerated crop improvement.

Genetic, physiological, and gene expression analyses reveal that multiple QTL enhance yield of rice mega-variety IR64 under drought

Background

Rice (Oryza sativa L.) is a highly drought sensitive crop, and most semi dwarf rice varieties suffer severe yield losses from reproductive stage drought stress. The genetic complexity of drought tolerance has deterred the identification of agronomically relevant quantitative trait loci (QTL) that can be deployed to improve rice yield under drought in rice. Convergent evidence from physiological characterization, genetic mapping, and multi-location field evaluation was used to address this challenge.

Methodology/Principal Findings

Two pairs of backcross inbred lines (BILs) from a cross between drought-tolerant donor Aday Sel and high-yielding but drought-susceptible rice variety IR64 were produced. From six BC₄F₃ mapping populations produced by crossing the +QTL BILs with the −QTL BILs and IR64, four major-effect QTL - one each on chromosomes 2, 4, 9, and 10 - were identified. Meta-analysis of transcriptome data from the +QTL/−QTL BILs identified differentially expressed genes (DEGs) significantly associated with QTL on chromosomes 2, 4, 9, and 10. Physiological characterization of BILs showed increased water uptake ability under drought. The enrichment of DEGs associated with root traits points to differential regulation of root development and function as contributing to drought tolerance in these BILs. BC₄F₃-derived lines with the QTL conferred yield advantages of 528 to 1875 kg ha⁻¹ over IR64 under reproductive-stage drought stress in the targeted ecosystems of South Asia.

Conclusions/Significance

Given the importance of rice in daily food consumption and the popularity of IR64, the BC₄F₃ lines with multiple QTL could provide higher livelihood security to farmers in drought-prone environments. Candidate genes were shortlisted for further characterization to confirm their role in drought tolerance. Differential yield advantages of different combinations of the four QTL reported here indicate that future research should include optimizing QTL combinations in different genetic backgrounds to maximize yield advantage under drought.

Combined linkage and association mapping of flowering time in Sunflower (Helianthus annuus L.)

Association mapping and linkage mapping were used to identify quantitative trait loci (QTL) and/or causative mutations involved in the control of flowering time in cultivated sunflower Helianthus annuus. A panel of 384 inbred lines was phenotyped through testcrosses with two tester inbred lines across 15 location × year combinations. A recombinant inbred line (RIL) population comprising 273 lines was phenotyped both per se and through testcrosses with one or two testers in 16 location × year combinations. In the association mapping approach, kinship estimation using 5,923 single nucleotide polymorphisms was found to be the best covariate to correct for effects of panel structure. Linkage disequilibrium decay ranged from 0.08 to 0.26 cM for a threshold of 0.20, after correcting for structure effects, depending on the linkage group (LG) and the ancestry of inbred lines. A possible hitchhiking effect is hypothesized for LG10 and LG08. A total of 11 regions across 10 LGs were found to be associated with flowering time, and QTLs were mapped on 11 LGs in the RIL population. Whereas eight regions were demonstrated to be common between the two approaches, the linkage disequilibrium approach did not detect a documented QTL that was confirmed using the linkage mapping approach.

Paths to selection on life history loci in different natural environments across the native range of Arabidopsis thaliana

Selection on quantitative trait loci (QTL) may vary among natural environments due to differences in the genetic architecture of traits, environment-specific allelic effects or changes in the direction and magnitude of selection on specific traits. To dissect the environmental differences in selection on life history QTL across climatic regions, we grew a panel of interconnected recombinant inbred lines (RILs) of Arabidopsis thaliana in four field sites across its native European range. For each environment, we mapped QTL for growth, reproductive timing and development. Several QTL were pleiotropic across environments, three colocalizing with known functional polymorphisms in flowering time genes (CRY2, FRI and MAF2-5), but major QTL differed across field sites, showing conditional neutrality. We used structural equation models to trace selection paths from QTL to lifetime fitness in each environment. Only three QTL directly affected fruit number, measuring fitness. Most QTL had an indirect effect on fitness through their effect on bolting time or leaf length. Influence of life history traits on fitness differed dramatically across sites, resulting in different patterns of selection on reproductive timing and underlying QTL. In two oceanic field sites with high prereproductive mortality, QTL alleles contributing to early reproduction resulted in greater fruit production, conferring selective advantage, whereas alleles contributing to later reproduction resulted in larger size and higher fitness in a continental site. This demonstrates how environmental variation leads to change in both QTL effect sizes and direction of selection on traits, justifying the persistence of allelic polymorphism at life history QTL across the species range.

Differential selection pressures exerted by host resistance quantitative trait loci on a pathogen population: a case study in an apple × Venturia inaequalis pathosystem

Understanding how pathogens evolve according to pressures exerted by their plant hosts is essential for the derivation of strategies aimed at the durable management of resistant cultivars. The spectrum of action of the resistance factors in the partially resistant cultivars is thought to be an important determinant of resistance durability. However, it has not yet been demonstrated whether the pressures exerted by quantitative resistance are different according to their spectrum of action. To investigate selection pressures exerted by apple genotypes harbouring various resistance quantitative trait loci (QTLs) on a mixed inoculum of the scab disease agent, Venturia inaequalis, we monitored V. inaequalis isolate proportions on diseased apple leaves of an F1 progeny using quantitative pyrosequencing technology and QTL mapping. Broad-spectrum resistances did not exert any differential selection pressures on the mixed inoculum, whereas narrow-spectrum resistances decreased the frequencies of some isolates in the mixture relative to the susceptible host genotypes. Our results suggest that the management of resistant cultivars should be different according to the spectrum of action of their resistance factors. The pyramiding of broad-spectrum factors or the use of a mixture of apple genotypes that carry narrow-spectrum resistance factors are two possible strategies for the minimization of resistance erosion.

QTL detection for forage quality and stem histology in four connected mapping populations of the model legume Medicago truncatula

Forage quality combines traits related to protein content and energy value. High-quality forages contribute to increase farm autonomy by reducing the use of energy or protein-rich supplements. Genetic analyses in forage legume species are complex because of their tetraploidy and allogamy. Indeed, no genetic studies of quality have been published at the molecular level on these species. Nonetheless, mapping populations of the model species M. truncatula can be used to detect QTL for forage quality. Here, we studied a crossing design involving four connected populations of M. truncatula. Each population was composed of ca. 200 recombinant inbred lines (RIL). We sought population-specific QTL and QTL explaining the whole design variation. We grew parents and RIL in a greenhouse for 2 or 3 seasons and analysed plants for chemical composition of vegetative organs (protein content, digestibility, leaf-to-stem ratio) and stem histology (stem cross-section area, tissue proportions). Over the four populations and all the traits, QTL were found on all chromosomes. Among these QTL, only four genomic regions, on chromosomes 1, 3, 7 and 8, contributed to explaining the variations in the whole crossing design. Surprisingly, we found that quality QTL were located in the same genomic regions as morphological QTL. We thus confirmed the quantitative inheritance of quality traits and tight relationships between quality and morphology. Our findings could be explained by a co-location of genes involved in quality and morphology. This study will help to detect candidate genes involved in quantitative variation for quality in forage legume species.

Genetic analysis of phytosterol content in sunflower seeds

Interest in phytosterol contents due to their potential benefits for human health has been largely documented in several crop species. Studies were focused mainly on total sterol content and their concentration or distribution in seed. This study aimed at providing new insight into the genetic control of total and individual sterol contents in sunflower seed through QTL analyses in a RIL population characterized over 2 years showing contrasted rainfall during seed filling. Results indicated that 13 regions on 9 linkage groups were involved in different phytosterol traits. Most of the QTL mapped were stable across years in spite of contrasted growing conditions. Some of them explained up to 30 % of phenotypic variation. Two QTL, located on LG10, near b1, and on LG14, were found to co-localize with QTL for oil content, indicating that likely, a part of the genetic variation for sterol content is only the result of genetic variation for oil content. However, three other QTL, stable over the 2 years, were found on LG1, LG4 and LG7 each associated with a particular class of sterols, suggesting that some enzymes known to be involved in the sterol metabolic pathway may determine the specificity of sterol profiles in sunflower seeds. These results suggest that it may be possible to introduce these traits as criteria in breeding programmes for quality in sunflower. The molecular markers linked to genetic factors controlling phytosterol contents could help selection during breeding programs.

Consensus mapping of major resistance genes and independent QTL for quantitative resistance to sunflower downy mildew

Major gene resistance to sunflower downy mildew (Plasmopara halstedii) races 304 and 314 was found to segregate independently from the resistance to races 334, 307 and 304 determined by the gene Pl2, already positioned on Linkage Group (LG) 8 of sunflower molecular maps. Using a consensus SSR-SNP map constructed from the INEDI RIL population and a new RIL population FU × PAZ2, the positions of Pl2 and Pl5 were confirmed and the new gene, denoted Pl21, was mapped on LG13, at 8 cM from Pl5. The two RIL populations were observed for their quantitative resistance to downy mildew in the field and both indicated the existence of a QTL on LG8 at 20-40 cM from the major resistance gene cluster. In addition, for the INEDI population, a strong QTL on LG10, reported previously, was confirmed and a third QTL was mapped on LG7. A growth chamber test methodology, significantly correlated with field results, also revealed the major QTL on LG10, explaining 65 % of variability. This QTL mapped in the same area as a gene involved in stomatal opening and root growth, which may be suggested as a possible candidate to explain the control of this character. These results indicate that it should be possible to combine major genes and other resistance mechanisms, a strategy that could help to improve durability of sunflower resistance to downy mildew.

Detection of favorable alleles for plant height and crown rust tolerance in three connected populations of perennial ryegrass (Lolium perenne L.)

Plant height, which is an estimator of vegetative yield, and crown rust tolerance are major criteria for perennial ryegrass breeding. Genetic improvement has been achieved through phenotypic selection but it should be speeded up using marker-assisted selection, especially in this heterozygous species suffering from inbreeding depression. Using connected multiparental populations should increase the diversity studied and could substantially increase the power of quantitative trait loci (QTL) detection. The objective of this study was to detect the best alleles for plant height and rust tolerance among three connected populations derived from elite material by comparing an analysis per parent and a multipopulation connected analysis. For the studied traits, 17 QTL were detected with the analysis per parent while the additive and dominance models of the multipopulation connected analysis made it possible to detect 33 and 21 QTL, respectively. Favorable alleles have been detected in all parents. Only a few dominance effects were detected and they generally had lower values than the additive effects. The additive model of the multipopulation connected analysis was the most powerful as it made it possible to detect most of the QTL identified in the other analyses and 11 additional QTL. Using this model, plant growth QTL and rust tolerance QTL explained up to 19 and 38.6% of phenotypic variance, respectively. This example involving three connected populations is promising for an application on polycross progenies, traditionally used in breeding programs. Indeed, polycross progenies actually are a set of several connected populations.

Multi-population QTL detection for aerial morphogenetic traits in the model legume Medicago truncatula

Medicago truncatula, as a model species, is useful to study the genetic control of traits of agronomic interest in legumes species. Aerial morphogenesis is a key component of forage and seed yield. It was measured in four mapping populations originating from five parental lines. Single and multi-population quantitative trait locus (QTL) detections were carried out. A large variation was observed within populations and transgressive segregation was noted. Most traits showed high heritabilities in all seasons. Length of primary branches (LPB, cm) was positively correlated to branch elongation rate (BER, cm day(-1)) and aerial dry matter (ADM, g). Flowering time (FT, °C day(-1)) showed negative correlations with length of main stem (LMS, cm) and BER. One hundred and forty-one QTLs for BER, LMS, FT, LPB, diameter of primary branches (DPB), number of primary branches (NPB), number of nodes (NI) and ADM were identified and localized over all eight chromosomes. Single and multi-population analyses showed that the most important regions for aerial morphogenetic traits were chromosomes 1, 2, 7 and 8. Multi-population analysis revealed three regions of major QTLs affecting aerial morphogenetic traits (LPB, LMS, NPB, BER and FT). A region involved in flowering time variation was revealed on chromosome 6 on a single population. These results were used to identify candidate genes that could control variation for aerial morphogenesis traits in this species and in related crop legume species.

Using a physiological framework for improving the detection of quantitative trait loci related to nitrogen nutrition in Medicago truncatula

Medicago truncatula is used as a model plant for exploring the genetic and molecular determinants of nitrogen (N) nutrition in legumes. In this study, our aim was to detect quantitative trait loci (QTL) controlling plant N nutrition using a simple framework of carbon/N plant functioning stemming from crop physiology. This framework was based on efficiency variables which delineated the plant's efficiency to take up and process carbon and N resources. A recombinant inbred line population (LR4) was grown in a glasshouse experiment under two contrasting nitrate concentrations. At low nitrate, symbiotic N(2) fixation was the main N source for plant growth and a QTL with a large effect located on linkage group (LG) 8 affected all the traits. Significantly, efficiency variables were necessary both to precisely localize a second QTL on LG5 and to detect a third QTL involved in epistatic interactions on LG2. At high nitrate, nitrate assimilation was the main N source and a larger number of QTL with weaker effects were identified compared to low nitrate. Only two QTL were common to both nitrate treatments: a QTL of belowground biomass located at the bottom of LG3 and another one on LG6 related to three different variables (leaf area, specific N uptake and aboveground:belowground biomass ratio). Possible functions of several candidate genes underlying QTL of efficiency variables could be proposed. Altogether, our results provided new insights into the genetic control of N nutrition in M. truncatula. For instance, a novel result for M. truncatula was identification of two epistatic interactions in controlling plant N(2) fixation. As such this study showed the value of a simple conceptual framework based on efficiency variables for studying genetic determinants of complex traits and particularly epistatic interactions.

The genetic basis of heterosis: multiparental quantitative trait loci mapping reveals contrasted levels of apparent overdominance among traits of agronomical interest in maize (Zea mays L.)

Understanding the genetic bases underlying heterosis is a major issue in maize (Zea mays L.). We extended the North Carolina design III (NCIII) by using three populations of recombinant inbred lines derived from three parental lines belonging to different heterotic pools, crossed with each parental line to obtain nine families of hybrids. A total of 1253 hybrids were evaluated for grain moisture, silking date, plant height, and grain yield. Quantitative trait loci (QTL) mapping was carried out on the six families obtained from crosses to parental lines following the “classical” NCIII method and with a multiparental connected model on the global design, adding the three families obtained from crosses to the nonparental line. Results of the QTL detection highlighted that most of the QTL detected for grain yield displayed apparent overdominance effects and limited differences between heterozygous genotypes, whereas for grain moisture predominance of additive effects was observed. For plant height and silking date results were intermediate. Except for grain yield, most of the QTL identified showed significant additive-by-additive epistatic interactions. High correlation observed between heterosis and the heterozygosity of hybrids at markers confirms the complex genetic basis and the role of dominance in heterosis. An important proportion of QTL detected were located close to the centromeres. We hypothesized that the lower recombination in these regions favors the detection of (i) linked QTL in repulsion phase, leading to apparent overdominance for heterotic traits and (ii) linked QTL in coupling phase, reinforcing apparent additive effects of linked QTL for the other traits.

Characterization of a dual-affinity nitrate transporter MtNRT1.3 in the model legume Medicago truncatula

Primary root growth in the absence or presence of exogenous NO(3)(-) was studied by a quantitative genetic approach in a recombinant inbred line (RIL) population of Medicago truncatula. A quantitative trait locus (QTL) on chromosome 5 appeared to be particularly relevant because it was seen in both N-free medium (LOD score 5.7; R(2)=13.7) and medium supplied with NO(3)(-) (LOD score, 9.5; R(2)=21.1) which indicates that it would be independent of the general nutritional status. Due to its localization exactly at the peak of this QTL, the putative NRT1-NO(3)(-) transporter (Medtr5g093170.1), closely related to Arabidopsis AtNRT1.3, a putative low-affinity nitrate transporter, appeared to be a significant candidate involved in the control of primary root growth and NO(3)(-) sensing. Functional characterization in Xenopus oocytes using both electrophysiological and (15)NO(3)(-) uptake approaches showed that Medtr5g093170.1, named MtNRT1.3, encodes a dual-affinity NO(3)(-) transporter similar to the AtNRT1.1 'transceptor' in Arabidopsis. MtNRT1.3 expression is developmentally regulated in roots, with increasing expression after completion of germination in N-free medium. In contrast to members of the NRT1 superfamily characterized so far, MtNRT1.3 is environmentally up-regulated by the absence of NO(3)(-) and down-regulated by the addition of the ion to the roots. Split-root experiments showed that the increased expression stimulated by the absence of NO(3)(-) was not the result of a systemic signalling of plant N status. The results suggest that MtNRT1.3 is involved in the response to N limitation, which increases the ability of the plant to acquire NO(3)(-) under N-limiting conditions.

Use of Mutant-Assisted Gene Identification and Characterization (MAGIC) to identify novel genetic loci that modify the maize hypersensitive response

The partially dominant, autoactive maize disease resistance gene Rp1-D21 causes hypersensitive response (HR) lesions to form spontaneously on leaves and stems in the absence of pathogen recognition. The maize nested association mapping (NAM) population consists of 25 200-line subpopulations each derived from a cross between the maize line B73 and one of 25 diverse inbred lines. By crossing a line carrying the Rp1-D21 gene with lines from three of these subpopulations and assessing the F(1) progeny, we were able to map several novel loci that modify the maize HR, using both single-population quantitative trait locus (QTL) and joint analysis of all three populations. Joint analysis detected QTL in greater number and with greater confidence and precision than did single population analysis. In particular, QTL were detected in bins 1.02, 4.04, 9.03, and 10.03. We have previously termed this technique, in which a mutant phenotype is used as a "reporter" for a trait of interest, Mutant-Assisted Gene Identification and Characterization (MAGIC).

Quantitative trait loci analysis reveals a correlation between the ratio of sucrose/raffinose family oligosaccharides and seed vigour in Medicago truncatula

Seed vigour is important for successful establishment and high yield, especially under suboptimal environmental conditions. In legumes, raffinose oligosaccharide family (RFO) sugars have been proposed as an easily available energy reserve for seedling establishment. In this study, we investigated whether the composition or amount of soluble sugars (sucrose and RFO) is part of the genetic determinants of seed vigour of Medicago truncatula using two recombinant inbred line (RIL) populations. Quantitative trait loci (QTL) mapping for germination rate, hypocotyl and radicle growth under water deficit and nutritional stress, seed weight and soluble sugar content was performed using RIL populations LR1 and LR4. Seven of the 12 chromosomal regions containing QTL for germination rate or post-germinative radicle growth under optimal or stress conditions co-located with Suc/RFO QTL. A significant negative correlation was also found between seed vigour traits and Suc/RFO. In addition, one QTL that explained 80% of the variation in the ratio stachyose/verbascose co-located with a stachyose synthase gene whose expression profile in the parental lines could explain the variation in oligosaccharide composition. The correlation and co-location of Suc/RFO ratio with germination and radicle growth QTL suggest that an increased Suc/RFO ratio in seeds of M. truncatula might negatively affect seed vigour.

New consistent QTL in pea associated with partial resistance to Aphanomyces euteiches in multiple French and American environments

Partial resistances, often controlled by quantitative trait loci (QTL), are considered to be more durable than monogenic resistances. Therefore, a precursor to developing efficient breeding programs for polygenic resistance to pathogens should be a greater understanding of genetic diversity and stability of resistance QTL in plants. In this study, we deciphered the diversity and stability of resistance QTL to Aphanomyces euteiches in pea towards pathogen variability, environments and scoring criteria, from two new sources of partial resistance (PI 180693 and 552), effective in French and USA infested fields. Two mapping populations of 178 recombinant inbred lines each, derived from crosses between 552 or PI 180693 (partially resistant) and Baccara (susceptible), were used to identify QTL for Aphanomyces root rot resistance in controlled and in multiple French and USA field conditions using several resistance criteria. We identified a total of 135 additive-effect QTL corresponding to 23 genomic regions and 13 significant epistatic interactions associated with partial resistance to A. euteiches in pea. Among the 23 additive-effect genomic regions identified, five were consistently detected, and showed highly stable effects towards A. euteiches strains, environments, resistance criteria, condition tests and RIL populations studied. These results confirm the complexity of inheritance of partial resistance to A. euteiches in pea and provide good bases for the choice of consistent QTL to use in marker-assisted selection schemes to increase current levels of resistance to A. euteiches in pea breeding programs.