Investigation of the mechanical work during ultrasonic fatigue loading using pulsed time-resolved X-ray diffraction.

In the energy production and transportation industries, numerous metallic structures may be subjected to at least several billions of cycles, i.e. loaded in the very high cycle fatigue domain (VHCF). Therefore, to design structures in the VHCF domain, a reliable methodology is necessary. One useful quantity to characterize plastic activity at the microscopic scale and fatigue damage evolution is the mechanical work supplied to a material. However, the estimation of this mechanical work in a metal during ultrasonic fatigue tests remains challenging. This paper aims to present an innovative methodology to quantify this. An experimental procedure was developed to estimate the mechanical work from stress and total strain evolution measurements during one loading cycle with a time accuracy of about 50 ns. This was achieved by conducting time-resolved X-ray diffraction coupled to strain gauge measurements at a synchrotron facility working in pulsed mode (single-bunch mode).

Genome-Wide Analysis of Yield in Europe: Allelic Effects Vary with Drought and Heat Scenarios.

Assessing the genetic variability of plant performance under heat and drought scenarios can contribute to reduce the negative effects of climate change. We propose here an approach that consisted of (1) clustering time courses of environmental variables simulated by a crop model in current (35 years × 55 sites) and future conditions into six scenarios of temperature and water deficit as experienced by maize (Zea mays L.) plants; (2) performing 29 field experiments in contrasting conditions across Europe with 244 maize hybrids; (3) assigning individual experiments to scenarios based on environmental conditions as measured in each field experiment; frequencies of temperature scenarios in our experiments corresponded to future heat scenarios (+5°C); (4) analyzing the genetic variation of plant performance for each environmental scenario. Forty-eight quantitative trait loci (QTLs) of yield were identified by association genetics using a multi-environment multi-locus model. Eight and twelve QTLs were associated to tolerances to heat and drought stresses because they were specific to hot and dry scenarios, respectively, with low or even negative allelic effects in favorable scenarios. Twenty-four QTLs improved yield in favorable conditions but showed nonsignificant effects under stress; they were therefore associated with higher sensitivity. Our approach showed a pattern of QTL effects expressed as functions of environmental variables and scenarios, allowing us to suggest hypotheses for mechanisms and candidate genes underlying each QTL. It can be used for assessing the performance of genotypes and the contribution of genomic regions under current and future stress situations and to accelerate breeding for drought-prone environments.

Dissecting quantitative trait variation in the resequencing era: complementarity of bi-parental, multi-parental and association panels.

Quantitative trait loci (QTL) have been identified using traditional linkage mapping and positional cloning identified several QTLs. However linkage mapping is limited to the analysis of traits differing between two lines and the impact of the genetic background on QTL effect has been underlined. Genome-wide association studies (GWAs) were proposed to circumvent these limitations. In tomato, we have shown that GWAs is possible, using the admixed nature of cherry tomato genomes that reduces the impact of population structure. Nevertheless, GWAs success might be limited due to the low decay of linkage disequilibrium, which varies along the genome in this species. Multi-parent advanced generation intercross (MAGIC) populations offer an alternative to traditional linkage and GWAs by increasing the precision of QTL mapping. We have developed a MAGIC population by crossing eight tomato lines whose genomes were resequenced. We showed the potential of the MAGIC population when coupled with whole genome sequencing to detect candidate single nucleotide polymorphisms (SNPs) underlying the QTLs. QTLs for fruit quality traits were mapped and related to the variations detected at the genome sequence and expression levels. The advantages and limitations of the three types of population, in the context of the available genome sequence and resequencing facilities, are discussed.

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.

Usefulness of multiparental populations of maize (Zea mays L.) for genome-based prediction.

The efficiency of marker-assisted prediction of phenotypes has been studied intensively for different types of plant breeding populations. However, one remaining question is how to incorporate and counterbalance information from biparental and multiparental populations into model training for genome-wide prediction. To address this question, we evaluated testcross performance of 1652 doubled-haploid maize (Zea mays L.) lines that were genotyped with 56,110 single nucleotide polymorphism markers and phenotyped for five agronomic traits in four to six European environments. The lines are arranged in two diverse half-sib panels representing two major European heterotic germplasm pools. The data set contains 10 related biparental dent families and 11 related biparental flint families generated from crosses of maize lines important for European maize breeding. With this new data set we analyzed genome-based best linear unbiased prediction in different validation schemes and compositions of estimation and test sets. Further, we theoretically and empirically investigated marker linkage phases across multiparental populations. In general, predictive abilities similar to or higher than those within biparental families could be achieved by combining several half-sib families in the estimation set. For the majority of families, 375 half-sib lines in the estimation set were sufficient to reach the same predictive performance of biomass yield as an estimation set of 50 full-sib lines. In contrast, prediction across heterotic pools was not possible for most cases. Our findings are important for experimental design in genome-based prediction as they provide guidelines for the genetic structure and required sample size of data sets used for model training.

Intraspecific variation of recombination rate in maize.

BACKGROUND: In sexually reproducing organisms, meiotic crossovers ensure the proper segregation of chromosomes and contribute to genetic diversity by shuffling allelic combinations. Such genetic reassortment is exploited in breeding to combine favorable alleles, and in genetic research to identify genetic factors underlying traits of interest via linkage or association-based approaches. Crossover numbers and distributions along chromosomes vary between species, but little is known about their intraspecies variation. RESULTS: Here, we report on the variation of recombination rates between 22 European maize inbred lines that belong to the Dent and Flint gene pools. We genotype 23 doubled-haploid populations derived from crosses between these lines with a 50 k-SNP array and construct high-density genetic maps, showing good correspondence with the maize B73 genome sequence assembly. By aligning each genetic map to the B73 sequence, we obtain the recombination rates along chromosomes specific to each population. We identify significant differences in recombination rates at the genome-wide, chromosome, and intrachromosomal levels between populations, as well as significant variation for genome-wide recombination rates among maize lines. Crossover interference analysis using a two-pathway modeling framework reveals a negative association between re combination rate and interference strength. CONCLUSIONS: To our knowledge, the present work provides the most comprehensive study on intraspecific variation of recombination rates and crossover interference strength in eukaryotes. Differences found in recombination rates will allow for selection of high or low recombining lines in crossing programs. Our methodology should pave the way for precise identification of genes controlling recombination rates in maize and other organisms.

Phenotypic diversity and association mapping for fruit quality traits in cultivated tomato and related species.

Association mapping has been proposed as an efficient approach to assist in the identification of the molecular basis of agronomical traits in plants. For this purpose, we analyzed the phenotypic and genetic diversity of a large collection of tomato accessions including 44 heirloom and vintage cultivars (Solanum lycopersicum), 127 S. lycopersicum var. cerasiforme (cherry tomato) and 17 Solanum pimpinellifolium accessions. The accessions were genotyped using a SNPlex™ assay of 192 SNPs, among which 121 were informative for subsequent analysis. Linkage disequilibrium (LD) of pairwise loci and population structure were analyzed, and the association analysis between SNP genotypes and ten fruit quality traits was performed using a mixed linear model. High level of LD was found in the collection at the whole genome level. It was lower when considering only the 127 S. lycopersicum var. cerasiforme accessions. Genetic structure analysis showed that the population was structured into two main groups, corresponding to cultivated and wild types and many intermediates. The number of associations detected per trait varied, according to the way the structure was taken into account, with 0-41 associations detected per trait in the whole collection and a maximum of four associations in the S. lycopersicum var. cerasiforme accessions. A total of 40 associations (30 %) were co-localized with previously identified quantitative trait loci. This study thus showed the potential and limits of using association mapping in tomato populations.

Genome-wide association mapping in tomato (Solanum lycopersicum) is possible using genome admixture of Solanum lycopersicum var. cerasiforme.

Genome-wide association mapping is an efficient way to identify quantitative trait loci controlling the variation of phenotypes, but the approach suffers severe limitations when one is studying inbred crops like cultivated tomato (Solanum lycopersicum). Such crops exhibit low rates of molecular polymorphism and high linkage disequilibrium, which reduces mapping resolution. The cherry type tomato (S. lycopersicum var. cerasiforme) genome has been described as an admixture between the cultivated tomato and its wild ancestor, S. pimpinellifolium. We have thus taken advantage of the properties of this admixture to improve the resolution of association mapping in tomato. As a proof of concept, we sequenced 81 DNA fragments distributed on chromosome 2 at different distances in a core collection of 90 tomato accessions, including mostly cherry type tomato accessions. The 81 Sequence Tag Sites revealed 352 SNPs and indels. Molecular diversity was greatest for S. pimpinellifolium accessions, intermediate for S. l. cerasiforme accessions, and lowest for the cultivated group. We assessed the structure of molecular polymorphism and the extent of linkage disequilibrium over genetic and physical distances. Linkage disequilibrium decreased under r(2) = 0.3 within 1 cM, and minimal estimated value (r(2) = 0.13) was reached within 20 kb over the physical regions studied. Associations between polymorphisms and fruit weight, locule number, and soluble solid content were detected. Several candidate genes and quantitative trait loci previously identified were validated and new associations detected. This study shows the advantages of using a collection of S. l. cerasiforme accessions to overcome the low resolution of association mapping in tomato.

Detection of QTL for flowering time in multiple families of elite maize.

Flowering time is a fundamental quantitative trait in maize that has played a key role in the postdomestication process and the adaptation to a wide range of climatic conditions. Flowering time has been intensively studied and recent QTL mapping results based on diverse founders suggest that the genetic architecture underlying this trait is mainly based on numerous small-effect QTL. Here, we used a population of 684 progenies from five connected families to investigate the genetic architecture of flowering time in elite maize. We used a joint analysis and identified nine main effect QTL explaining approximately 50 % of the genotypic variation of the trait. The QTL effects were small compared with the observed phenotypic variation and showed strong differences between families. We detected no epistasis with the genetic background but four digenic epistatic interactions in a full 2-dimensional genome scan. Our results suggest that flowering time in elite maize is mainly controlled by main effect QTL with rather small effects but that epistasis may also contribute to the genetic architecture of the trait.

Comparison of biometrical approaches for QTL detection in multiple segregating families.

Detection of QTL in multiple segregating families possesses many advantages over the classical QTL mapping in biparental populations. It has thus become increasingly popular, and different biometrical approaches are available to analyze such data sets. We empirically compared an approach based on linkage mapping methodology with an association mapping approach. To this end, we used a large population of 788 elite maize lines derived from six biparental families genotyped with 857 SNP markers. In addition, we constructed genetic maps with reduced marker densities to assess the dependency of the performance of both mapping approaches on the marker density. We used cross-validation and resample model averaging and found that while association mapping performed better under high marker densities, this was reversed under low marker densities. In addition to main effect QTL, we also detected epistatic interactions. Our results suggest that both approaches will profit from a further increase in marker density and that a cross-validation should be applied irrespective of the biometrical approach.

Impact of selective genotyping in the training population on accuracy and bias of genomic selection.

Estimating marker effects based on routinely generated phenotypic data of breeding programs is a cost-effective strategy to implement genomic selection. Truncation selection in breeding populations, however, could have a strong impact on the accuracy to predict genomic breeding values. The main objective of our study was to investigate the influence of phenotypic selection on the accuracy and bias of genomic selection. We used experimental data of 788 testcross progenies from an elite maize breeding program. The testcross progenies were evaluated in unreplicated field trials in ten environments and fingerprinted with 857 SNP markers. Random regression best linear unbiased prediction method was used in combination with fivefold cross-validation based on genotypic sampling. We observed a substantial loss in the accuracy to predict genomic breeding values in unidirectional selected populations. In contrast, estimating marker effects based on bidirectional selected populations led to only a marginal decrease in the prediction accuracy of genomic breeding values. We concluded that bidirectional selection is a valuable approach to efficiently implement genomic selection in applied plant breeding programs.

Accuracy of genomic selection in European maize elite breeding populations.

Genomic selection is a promising breeding strategy for rapid improvement of complex traits. The objective of our study was to investigate the prediction accuracy of genomic breeding values through cross validation. The study was based on experimental data of six segregating populations from a half-diallel mating design with 788 testcross progenies from an elite maize breeding program. The plants were intensively phenotyped in multi-location field trials and fingerprinted with 960 SNP markers. We used random regression best linear unbiased prediction in combination with fivefold cross validation. The prediction accuracy across populations was higher for grain moisture (0.90) than for grain yield (0.58). The accuracy of genomic selection realized for grain yield corresponds to the precision of phenotyping at unreplicated field trials in 3-4 locations. As for maize up to three generations are feasible per year, selection gain per unit time is high and, consequently, genomic selection holds great promise for maize breeding programs.

Increase in tomato locule number is controlled by two single-nucleotide polymorphisms located near WUSCHEL.

In tomato (Solanum lycopersicum) fruit, the number of locules (cavities containing seeds that are derived from carpels) varies from two to up to 10 or more. Locule number affects fruit shape and size and is controlled by several quantitative trait loci (QTLs). The large majority of the phenotypic variation is explained by two of these QTLs, fasciated (fas) and locule number (lc), that interact epistatically with one another. FAS has been cloned, and mutations in the gene are described as key factors leading to the increase in fruit size in modern varieties. Here, we report the map-based cloning of lc. The lc QTL includes a 1,600-bp region that is located 1,080 bp from the 3' end of WUSCHEL, which encodes a homeodomain protein that regulates stem cell fate in plants. The molecular evolution of lc showed a reduction of diversity in cultivated accessions with the exception of two single-nucleotide polymorphisms. These two single-nucleotide polymorphisms were shown to be responsible for the increase in locule number. An evolutionary model of locule number is proposed herein, suggesting that the fas mutation appeared after the mutation in the lc locus to confer the extreme high-locule-number phenotype.

A clarified position for Solanum lycopersicum var. cerasiforme in the evolutionary history of tomatoes (solanaceae).

BACKGROUND: The natural phenotypic variability present in the germplasm of cultivated plants can be linked to molecular polymorphisms using association genetics. However it is necessary to consider the genetic structure of the germplasm used to avoid false association. The knowledge of genetic structure of plant populations can help in inferring plant evolutionary history. In this context, we genotyped 360 wild, feral and cultivated accessions with 20 simple sequence repeat markers and investigated the extent and structure of the genetic variation. The study focused on the red fruited tomato clade involved in the domestication of tomato and confirmed the admixture status of cherry tomatoes (Solanum lycopersicum var. cerasiforme). We used a nested sample strategy to set-up core collection maximizing the genetic diversity with a minimum of individuals. RESULTS: Molecular diversity was considerably lower in S. lycopersicum i.e. the domesticated form. Model-based analysis showed that the 144 S. lycopersicum var. cerasiforme accessions were structured into two groups: one close to the domesticated group and one resulting from the admixture of the S. lycopersicum and S. pimpinellifolium genomes. SSR genotyping also indicates that domesticated and wild tomatoes have evolved as a species complex with intensive level of hybridization. We compiled genotypic and phenotypic data to identify sub-samples of 8, 24, 32 and 64 cherry tomato accessions that captured most of the genetic and morphological diversity present in the entire S. lycopersicum var. cerasiforme collection. CONCLUSION: The extent and structure of allelic variation is discussed in relation to historical events like domestication and modern selection. The potential use of the admixed group of S. lycopersicum var. cerasiforme for association genetics studies is also discussed. Nested core collections sampled to represent tomato diversity will be useful in diversity studies. Molecular and phenotypic variability of these core collections is defined. These collections are available for the scientific community and can be used as standardized panels for coordinating efforts on identifying novel interesting genes and on examining the domestication process in more detail.