Genome-wide genotyping data renew knowledge on genetic diversity of a worldwide alfalfa collection and give insights on genetic control of phenology traits.

China's and Europe's dependence on imported protein is a threat to the food self-sufficiency of these regions. It could be solved by growing more legumes, including alfalfa that is the highest protein producer under temperate climate. To create productive and high-value varieties, the use of large genetic diversity combined with genomic evaluation could improve current breeding programs. To study alfalfa diversity, we have used a set of 395 alfalfa accessions (i.e. populations), mainly from Europe, North and South America and China, with fall dormancy ranging from 3 to 7 on a scale of 11. Five breeders provided materials (617 accessions) that were compared to the 400 accessions. All accessions were genotyped using Genotyping-by-Sequencing (GBS) to obtain SNP allele frequency. These genomic data were used to describe genetic diversity and identify genetic groups. The accessions were phenotyped for phenology traits (fall dormancy and flowering date) at two locations (Lusignan in France, Novi Sad in Serbia) from 2018 to 2021. The QTL were detected by a Multi-Locus Mixed Model (mlmm). Subsequently, the quality of the genomic prediction for each trait was assessed. Cross-validation was used to assess the quality of prediction by testing GBLUP, Bayesian Ridge Regression (BRR), and Bayesian Lasso methods. A genetic structure with seven groups was found. Most of these groups were related to the geographical origin of the accessions and showed that European and American material is genetically distinct from Chinese material. Several QTL associated with fall dormancy were found and most of these were linked to genes. In our study, the infinitesimal methods showed a higher prediction quality than the Bayesian Lasso, and the genomic prediction achieved high (>0.75) predicting abilities in some cases. Our results are encouraging for alfalfa breeding by showing that it is possible to achieve high genomic prediction quality.

Genomic Prediction of Complex Traits in Forage Plants Species: Perennial Grasses Case.

The majority of forage grass species are obligate outbreeders. Their breeding classically consists of an initial selection on spaced plants for highly heritable traits such as disease resistances and heading date, followed by familial selection on swards for forage yield and quality traits. The high level of diversity and heterozygosity, and associated decay of linkage disequilibrium (LD) over very short genomic distances, has hampered the implementation of genomic selection (GS) in these species. However, next generation sequencing technologies in combination with the development of genomic resources have recently facilitated implementation of GS in forage grass species such as perennial ryegrass (Lolium perenne L.), switchgrass (Panicum virgatum L.), and timothy (Phleum pratense L.). Experimental work and simulations have shown that GS can increase significantly the genetic gain per unit of time for traits with different levels of heritability. The main reasons are (1) the possibility to select single plants based on their genomic estimated breeding values (GEBV) for traits measured at sward level, (2) a reduction in the duration of selection cycles, and less importantly (3) an increase in the selection intensity associated with an increase in the genetic variance used for selection. Nevertheless, several factors should be taken into account for the successful implementation of GS in forage grasses. For example, it has been shown that the level of relatedness between the training and the selection population is particularly critical when working with highly structured meta-populations consisting of several genetic groups. A sufficient number of markers should be used to estimate properly the kinship between individuals and to reflect the variability of major QTLs. It is also important that the prediction models are trained for relevant environments when dealing with traits with high genotype × environment interaction (G × E). Finally, in these outbreeding species, measures to reduce inbreeding should be used to counterbalance the high selection intensity that can be achieved in GS.

Divergent Selection for Seed Ability to Germinate at Extreme Temperatures in Perennial Ryegrass (Lolium perenne L.).

Various adaptive mechanisms can ensure that seedlings are established at the most favourable time and place. These mechanisms include seed dormancy i.e., incapacity to germinate in any environment without a specific environmental trigger and inhibition i.e., incapacity to germinate in an unfavourable environment (water availability, temperature: thermoinhibition and light). The objective of this research was to study in the temperate range for germination of forage and turf grass species perennial ryegrass, if the thermal requirements for germination are under genetic controlled and could be selectively bred. Two divergent selections of three cycles were realized on a natural population: one to select for the capacity to germinate at 10°C vs. the impossibility to germinate at 10°C, and one to select for the capacity to germinate at 32°C vs. the impossibility to germinate at 32°C. Seeds of all the lots obtained from the two divergent selections were then germinated at constant temperatures from 5 to 35°C to evaluate their germination ability. Concerning the positive selection, the first cycle of positive selection at 10°C was highly efficient with a very strong increase in the germination percentage. However, afterward no selection effect was observed during the next two cycles of positive selection. By contrast, the positive selection at 32°C was efficient during all cycles with a linear increase of the percentage of germination at 32°C. Concerning the negative selection, we observed only a large positive effect of the first cycle of selection at 10°C. These findings demonstrate that seed thermoinhibition at 10 and 32°C observed in a natural population of perennial ryegrass has a genetic basis and a single recessive gene seems to be involved at 10°C.

Seasonal Differences in Structural and Genetic Control of Digestibility in Perennial Ryegrass.

Perennial ryegrass is an important forage crop in dairy farming, either for grazing or haying purposes. To further optimise the forage use, this study focused on understanding forage digestibility in the two most important cuts of perennial ryegrass, the spring cut at heading and the autumn cut. In a highly diverse collection of 592 Lolium perenne genotypes, the organic matter digestibility (OMD) and underlying traits such as cell wall digestibility (NDFD) and cell wall components (cellulose, hemicellulose, and lignin) were investigated for 2 years. A high genotype × season interaction was found for OMD and NDFD, indicating differences in genetic control of these forage quality traits in spring versus autumn. OMD could be explained by both the quantity of cell wall content (NDF) and the quality of the cell wall content (NDFD). The variability in NDFD in spring was mainly explained by differences in hemicellulose. A 1% increase of the hemicellulose content in the cell wall (HC.NDF) resulted in an increase of 0.81% of NDFD. In autumn, it was mainly explained by the lignin content in the cell wall (ADL.NDF). A 0.1% decrease of ADL.NDF resulted in an increase of 0.41% of NDFD. The seasonal traits were highly heritable and showed a higher variation in autumn versus spring, indicating the potential to select for forage quality in the autumn cut. In a candidate gene association mapping approach, in which 503 genes involved in cell wall biogenesis, plant architecture, and phytohormone biosynthesis and signalling, identified significant quantitative trait loci (QTLs) which could explain from 29 to 52% of the phenotypic variance in the forage quality traits OMD and NDFD, with small effects of each marker taken individually (ranging from 1 to 7%). No identical QTLs were identified between seasons, but within a season, some QTLs were in common between digestibility traits and cell wall composition traits confirming the importance of hemicellulose concentration for spring digestibility and lignin concentration in NDF for autumn digestibility.

Canonical correlations reveal adaptive loci and phenotypic responses to climate in perennial ryegrass.

Germplasm from perennial ryegrass (Lolium perenne L.) natural populations is useful for breeding because of its adaptation to a wide range of climates. Climate-adaptive genes can be detected from associations between genotype, phenotype and climate but an integrated framework for the analysis of these three sources of information is lacking. We used two approaches to identify adaptive loci in perennial ryegrass and their effect on phenotypic traits. First, we combined Genome-Environment Association (GEA) and GWAS analyses. Then, we implemented a new test based on a Canonical Correlation Analysis (CANCOR) to detect adaptive loci. Furthermore, we improved the previous perennial ryegrass gene set by de novo gene prediction and functional annotation of 39,967 genes. GEA-GWAS revealed eight outlier loci associated with both environmental variables and phenotypic traits. CANCOR retrieved 633 outlier loci associated with two climatic gradients, characterized by cold-dry winter versus mild-wet winter and long rainy season versus long summer, and pointed out traits putatively conferring adaptation at the extremes of these gradients. Our CANCOR test also revealed the presence of both polygenic and oligogenic climatic adaptations. Our gene annotation revealed that 374 of the CANCOR outlier loci were positioned within or close to a gene. Co-association networks of outlier loci revealed a potential utility of CANCOR for investigating the interaction of genes involved in polygenic adaptations. The CANCOR test provides an integrated framework to analyse adaptive genomic diversity and phenotypic responses to environmental selection pressures that could be used to facilitate the adaptation of plant species to climate change.

High-Throughput Genome-Wide Genotyping To Optimize the Use of Natural Genetic Resources in the Grassland Species Perennial Ryegrass (Lolium perenne L.).

The natural genetic diversity of agricultural species is an essential genetic resource for breeding programs aiming to improve their ecosystem and production services. A large natural ecotype diversity is usually available for most grassland species. This could be used to recombine natural climatic adaptations and agronomic value to create improved populations of grassland species adapted to future regional climates. However describing natural genetic resources can be long and costly. Molecular markers may provide useful information to help this task. This opportunity was investigated for Lolium perenne L., using a set of 385 accessions from the natural diversity of this species collected right across Europe and provided by genebanks of several countries. For each of these populations, genotyping provided the allele frequencies of 189,781 SNP markers. GWAS were implemented for over 30 agronomic and/or putatively adaptive traits recorded in three climatically contrasted locations (France, Belgium, Germany). Significant associations were detected for hundreds of markers despite a strong confounding effect of the genetic background; most of them pertained to phenology traits. It is likely that genetic variability in these traits has had an important contribution to environmental adaptation and ecotype differentiation. Genomic prediction models calibrated using natural diversity were found to be highly effective to describe natural populations for almost all traits as well as commercial synthetic populations for some important traits such as disease resistance, spring growth or phenological traits. These results will certainly be valuable information to help the use of natural genetic resources of other species.

Evaluation of cocksfoot (Dactylis glomerata L.) population for drought survival and behavior.

Climate change models predict frequent and intense droughts in the world. Development of drought-tolerant species and cultivars is necessary to cope with such changes. Forage grass species are affected, especially in the Mediterranean region. The aim of the present study was to investigate the diversity for drought survival, summer dormancy, and productivity within a cocksfoot population. The study was conducted in Morocco, under field conditions from 2011 to 2013. 283 genotypes of cocksfoot and parents were tested, characterized for dry matter yield, heading date, plant height, senescence, summer dormancy, and drought survival. Results exhibited a large variability between traits. 79% of the population had survived after severe drought summer while 57% yielded more than both parents. Also, 63% of the progeny had an intermediate score of summer dormancy estimated by senescence score. Large variability was also noticed for heading date and plant height. Several accessions combined a high yield and persistence under severe summer drought. Which explain the significant correlation (r = 0.18, P < 0.005) founded between total dry matter accumulated in 2013 and plant survival. Accordingly, our results showed that we can rise persistent and resilient genotypes among population with a good level of biomass.

Five species, many genotypes, broad phenotypic diversity: When agronomy meets functional ecology.

PREMISE OF THE STUDY: Current ecological theory can provide insight into the causes and impacts of plant domestication. However, just how domestication has impacted intraspecific genetic variability (ITV) is unknown. We used 50 ecotypes and 35 cultivars from five grassland species to explore how selection drives functional trait coordination and genetic differentiation. METHODS: We quantified the extent of genetic diversity among different sets of functional traits and determined how much genetic diversity has been generated within populations of natural ecotypes and selected cultivars. KEY RESULTS: In general, the cultivars were larger (e.g., greater height, faster growth rates) and had larger and thinner leaves (greater SLA). We found large (average 63%) and trait-dependent (ranging from 14% for LNC to 95.8% for growth rate) genetic variability. The relative extent of genetic variability was greater for whole-plant than for organ-level traits. This pattern was consistent within ecotypes and within cultivars. However, ecotypes presented greater ITV variability. CONCLUSIONS: The results indicated that genetic diversity is large in domesticated species with contrasting levels of heritability among functional traits and that selection for high yield has led to indirect selection of some associated leaf traits. These findings open the way to define which target traits should be the focus in selection programs, especially in the context of community-level selection.

High-throughput phenotyping of lateral expansion and regrowth of spaced Lolium perenne plants using on-field image analysis.

BACKGROUND: Genetic studies and breeding of agricultural crops frequently involve phenotypic characterization of large collections of genotypes grown in field conditions. These evaluations are typically based on visual observations and manual (destructive) measurements. Robust image capture and analysis procedures that allow phenotyping large collections of genotypes in time series during developmental phases represent a clear advantage as they allow non-destructive monitoring of plant growth and performance. A L. perenne germplasm panel including wild accessions, breeding material and commercial varieties has been used to develop a low-cost, high-throughput phenotyping tool for determining plant growth based on images of individual plants during two consecutive growing seasons. Further we have determined the correlation between image analysis-based estimates of the plant's base area and the capacity to regrow after cutting, with manual counts of tiller number and measurements of leaf growth 2 weeks after cutting, respectively. When working with field-grown plants, image acquisition and image segmentation are particularly challenging as outdoor light conditions vary throughout the day and the season, and variable soil colours hamper the delineation of the object of interest in the image. Therefore we have used several segmentation methods including colour-, texture- and edge-based approaches, and factors derived after a fast Fourier transformation. The performance of the procedure developed has been analysed in terms of effectiveness across different environmental conditions and time points in the season. RESULTS: The procedure developed was able to analyse correctly 77.2 % of the 24,048 top view images processed. High correlations were found between plant's base area (image analysis-based) and tiller number (manual measurement) and between regrowth after cutting (image analysis-based) and leaf growth 2 weeks after cutting (manual measurement), with r values up to 0.792 and 0.824, respectively. Nevertheless, these relations depend on the origin of the plant material (forage breeding lines, current forage varieties, current turf varieties, and wild accessions) and the period in the season. CONCLUSIONS: The image-derived parameters presented here deliver reliable, objective data, complementary to the breeders' scores, and are useful for genetic studies. Furthermore, large variation was shown among genotypes for the parameters investigated.

On the Accuracy of Genomic Selection.

Genomic selection is focused on prediction of breeding values of selection candidates by means of high density of markers. It relies on the assumption that all quantitative trait loci (QTLs) tend to be in strong linkage disequilibrium (LD) with at least one marker. In this context, we present theoretical results regarding the accuracy of genomic selection, i.e., the correlation between predicted and true breeding values. Typically, for individuals (so-called test individuals), breeding values are predicted by means of markers, using marker effects estimated by fitting a ridge regression model to a set of training individuals. We present a theoretical expression for the accuracy; this expression is suitable for any configurations of LD between QTLs and markers. We also introduce a new accuracy proxy that is free of the QTL parameters and easily computable; it outperforms the proxies suggested in the literature, in particular, those based on an estimated effective number of independent loci (Me). The theoretical formula, the new proxy, and existing proxies were compared for simulated data, and the results point to the validity of our approach. The calculations were also illustrated on a new perennial ryegrass set (367 individuals) genotyped for 24,957 single nucleotide polymorphisms (SNPs). In this case, most of the proxies studied yielded similar results because of the lack of markers for coverage of the entire genome (2.7 Gb).

Combining Drought Survival via Summer Dormancy and Annual Biomass Productivity in Dactylis glomerata L.

Under Mediterranean climates, the best strategy to produce rain-fed fodder crops is to develop perennial drought resistant varieties. Summer dormancy present in native germplasm has been shown to confer a high level of survival under severe drought. Nevertheless it has also been shown to be negatively correlated with annual biomass productivity. The aim of this study was to analyze the correlations between summer dormancy and annual biomass productivity related traits and to identify quantitative trait loci (QTL) for these traits in a progeny of a summer dormant cocksfoot parent (Kasbah) and a summer active parent (Medly). A total of 283 offspring and the parents were phenotyped for summer dormancy, plant growth rate (PGR) and heading date in Morocco and for maximum leaf elongation rate (LERm) in France. The individuals were genotyped with a total of 325 markers including 59 AFLP, 64 SSR, and 202 DArT markers. The offspring exhibited a large quantitative variation for all measured traits. Summer dormancy showed a negative correlation with both PGR (-0.34 p < 0.005) and LERm (-0.27 p < 0.005). However, genotypes with both a high level of summer dormancy and a high level of PGR were detected in the progeny. One genetic map per parent was built with a total length of 377 and 423 cM for Kasbah and Medly, respectively. Both different and co-localized QTL for summer dormancy and PGR were identified. These results demonstrate that it should be possible to create summer dormant cocksfoot varieties with a high annual biomass productivity.

Complementary effects of species and genetic diversity on productivity and stability of sown grasslands.

Plant species diversity regulates the productivity(1-3) and stability(2,4) of natural ecosystems, along with their resilience to disturbance(5,6). The influence of species diversity on the productivity of agronomic systems is less clear(7-10). Plant genetic diversity is also suspected to influence ecosystem function(3,11-14), although empirical evidence is scarce. Given the large range of genotypes that can be generated per species through artificial selection, genetic diversity is a potentially important leverage of productivity in cultivated systems. Here we assess the effect of species and genetic diversity on the production and sustainable supply of livestock fodder in sown grasslands, comprising single and multispecies assemblages characterized by different levels of genetic diversity, exposed to drought and non-drought conditions. Multispecies assemblages proved more productive than monocultures when subject to drought, regardless of the number of genotypes per species present. Conversely, the temporal stability of production increased only with the number of genotypes present under both drought and non-drought conditions, and was unaffected by the number of species. We conclude that taxonomic and genetic diversity can play complementary roles when it comes to optimizing livestock fodder production in managed grasslands, and suggest that both levels of diversity should be considered in plant breeding programmes designed to boost the productivity and resilience of managed grasslands in the face of increasing environmental hazards.

Diet quality in a wild grazer declines under the threat of an ambush predator.

Predators influence prey populations not only through predation itself, but also indirectly through prompting changes in prey behaviour. The behavioural adjustments of prey to predation risk may carry nutritional costs, but this has seldom been studied in the wild in large mammals. Here, we studied the effects of an ambush predator, the African lion (Panthera leo), on the diet quality of plains zebras (Equus quagga) in Hwange National Park, Zimbabwe. We combined information on movements of both prey and predators, using GPS data, and measurements of faecal crude protein, an index of diet quality in the prey. Zebras which had been in close proximity to lions had a lower quality diet, showing that adjustments in behaviour when lions are within short distance carry nutritional costs. The ultimate fitness cost will depend on the frequency of predator-prey encounters and on whether bottom-up or top-down forces are more important in the prey population. Our finding is the first attempt to our knowledge to assess nutritionally mediated risk effects in a large mammalian prey species under the threat of an ambush predator, and brings support to the hypothesis that the behavioural effects of predation induce important risk effects on prey populations.

A fungal endophyte reinforces population adaptive differentiation in its host grass species.

Hereditary symbioses between fungal endophytes and grasses are relatively recent in the history of plant life. Given < 80 million yr of co-evolution, symbioses are likely to have impacted plant microevolutionary rather than macroevolutionary processes. Therefore, we investigated the microevolutionary role of the fungal endophyte Neotyphodium lolii in the adaptive differentiation of its host species Lolium perenne. Endophyte frequency in 22 natural L. perenne populations was established across a water availability gradient. Adaptive differentiation among five populations, and between symbiotic (S) and nonsymbiotic (NS) plants, was examined in a glasshouse experiment under nonlimiting and limiting water conditions. Genetic differentiation was subsequently assessed among populations, and between S and NS individuals, using 14 simple sequence repeats (SSR). Symbiosis frequencies were positively correlated to water availability. Adaptive population differentiation occurred following a trade-off between biomass production under nonlimiting water conditions and survivorship under water stress. Endophytic symbiosis increased plant survival in xeric populations, and reinforced competitiveness in mesic populations. No genetic difference was detected between S and NS plants within populations. Therefore, we conclude that the endophyte relationship is responsible for these effects. Local adaptation of the host plant, appears to be supported by the fungal endophyte.

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.

Association study between the gibberellic acid insensitive gene and leaf length in a Lolium perenne L. synthetic variety.

BACKGROUND: Association studies are of great interest to identify genes explaining trait variation since they deal with more than just a few alleles like classical QTL analyses. They are usually performed using collections representing a wide range of variability but which could present a genetic substructure. The aim of this paper is to demonstrate that association studies can be performed using synthetic varieties obtained after several panmictic generations. This demonstration is based on an example of association between the gibberellic acid insensitive gene (GAI) polymorphism and leaf length polymorphism in 'Herbie', a synthetic variety of perennial ryegrass. METHODS: Leaf growth parameters, consisted of leaf length, maximum leaf elongation rate (LERmax) and leaf elongation duration (LED), were evaluated in spring and autumn on 216 plants of Herbie with three replicates. For each plant, a sequence of 370 bp in GAI was analysed for polymorphism. RESULTS: Genetic effect was highly significant for all traits. Broad sense heritabilities were higher for leaf length and LERmax with about 0.7 in each period and 0.5 considering both periods than for LED with about 0.4 in each period and 0.3 considering both periods. GAI was highly polymorphic with an average of 12 bp between two consecutive SNPs and 39 haplotypes in which 9 were more frequent. Linkage disequilibrium declined rapidly with distance with r 2 values lower than 0.2 beyond 150 bp. Sequence polymorphism of GAI explained 8-14% of leaf growth parameter variation. A single SNP explained 4% of the phenotypic variance of leaf length in both periods which represents a difference of 33 mm on an average of 300 mm. CONCLUSIONS: Synthetic varieties in which linkage disequilibrium declines rapidly with distance are suitable for association studies using the "candidate gene" approach. GAI polymorphism was found to be associated with leaf length polymorphism which was more correlated to LERmax than to LED in Herbie. It is a good candidate to explain leaf length variation in other plant material.

EST-derived SSR markers used as anchor loci for the construction of a consensus linkage map in ryegrass (Lolium spp.).

BACKGROUND: Genetic markers and linkage mapping are basic prerequisites for marker-assisted selection and map-based cloning. In the case of the key grassland species Lolium spp., numerous mapping populations have been developed and characterised for various traits. Although some genetic linkage maps of these populations have been aligned with each other using publicly available DNA markers, the number of common markers among genetic maps is still low, limiting the ability to compare candidate gene and QTL locations across germplasm. RESULTS: A set of 204 expressed sequence tag (EST)-derived simple sequence repeat (SSR) markers has been assigned to map positions using eight different ryegrass mapping populations. Marker properties of a subset of 64 EST-SSRs were assessed in six to eight individuals of each mapping population and revealed 83% of the markers to be polymorphic in at least one population and an average number of alleles of 4.88. EST-SSR markers polymorphic in multiple populations served as anchor markers and allowed the construction of the first comprehensive consensus map for ryegrass. The integrated map was complemented with 97 SSRs from previously published linkage maps and finally contained 284 EST-derived and genomic SSR markers. The total map length was 742 centiMorgan (cM), ranging for individual chromosomes from 70 cM of linkage group (LG) 6 to 171 cM of LG 2. CONCLUSIONS: The consensus linkage map for ryegrass based on eight mapping populations and constructed using a large set of publicly available Lolium EST-SSRs mapped for the first time together with previously mapped SSR markers will allow for consolidating existing mapping and QTL information in ryegrass. Map and markers presented here will prove to be an asset in the development for both molecular breeding of ryegrass as well as comparative genetics and genomics within grass species.

Association of a CONSTANS-LIKE gene to flowering and height in autotetraploid alfalfa.

In alfalfa (Medicago sativa), an autotetraploid forage legume, stem length is a major component of forage yield, quality and competing ability. In this species, flowering date is not a breeding criterion. Association mapping based on a candidate gene approach has given good results in plants, including autotetraploid species for which genetic analyses are complex. The role of a CONSTANS-LIKE gene, identified as a candidate for stem elongation and flowering date in the model legume M. truncatula, was tested for association with the same traits in alfalfa. Four hundred genotypes from ten cultivars were evaluated for stem height and flowering date in two locations during 4 years. They were genotyped with simple sequence repeat markers and a low structuration was noticed. Primers were designed to amplify and sequence two regions of the alfalfa gene homologous to CONSTANS-LIKE. Single nucleotide polymorphisms (SNPs) were detected and their allelic dose in each genotype was scored. Linkage disequilibrium within CONSTANS-LIKE rapidly decreased as expected. Eight SNPs with a frequency above 10% were detected over 1,010 bp (one SNP every 126 bp on average) in the 400 genotypes. This number was lower than observed in a neutral gene (a SNP every 31 bp on average). Highly significant associations of three SNPs to flowering date and stem height were identified. Each SNP explained up to 4.2% of the genetic variance. Thus, as in the model species, the CONSTANS-LIKE gene was shown to be involved in flowering date and stem height in alfalfa.

Detection of QTLs for flowering date in three mapping populations of the model legume species Medicago truncatula.

Adaptation to the environment and reproduction are dependent on the date of flowering in the season. The objectives of this paper were to evaluate the effect of photoperiod on flowering date of the model species for legume crops, Medicago truncatula and to describe genetic architecture of this trait in multiple mapping populations. The effect of photoperiod (12 and 18 h) was analysed on eight lines. Quantitative variation in three recombinant inbred lines (RILs) populations involving four parental lines was evaluated, and QTL detection was carried out. Flowering occurred earlier in long than in short photoperiods. Modelling the rate of progression to flowering with temperature and photoperiod gave high R2, with line-specific parameters that indicated differential responses of the lines to both photoperiod and temperature. QTL detection showed a QTL on chromosome 7 that was common to all populations and seasons. Taking advantage of the multiple mapping populations, it was condensed into a single QTL with a support interval of only 0.9 cM. In a bioanalysis, six candidate genes were identified in this interval. This design also indicated other genomic regions that were involved in flowering date variation more specifically in one population or one season. The analysis on three different mapping populations detected more QTLs than on a single population, revealed more alleles and gave a more precise position of the QTLs that were common to several populations and/or seasons. Identification of candidate genes was a result of integration of QTL analysis and genomics in M. truncatula.