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

Involvement of CONSTANS-like Proteins in Plant Flowering and Abiotic Stress Response

The process of flowering in plants is a pivotal stage in their life cycle, and the CONSTANS-like (COL) protein family, known for its photoperiod sensing ability, plays a crucial role in regulating plant flowering. Over the past two decades, homologous genes of COL have been identified in various plant species, leading to significant advancements in comprehending their involvement in the flowering pathway and response to abiotic stress. This article presents novel research progress on the structural aspects of COL proteins and their regulatory patterns within transcription complexes. Additionally, we reviewed recent information about their participation in flowering and abiotic stress response, aiming to provide a more comprehensive understanding of the functions of COL proteins.

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.

Controlling flowering of Medicago sativa (alfalfa) by inducing dominant mutations

Breeding plants with polyploid genomes is challenging because functional redundancy hampers the identification of loss-of-function mutants. Medicago sativa is tetraploid and obligate outcrossing, which together with inbreeding depression complicates traditional breeding approaches in obtaining plants with a stable growth habit. Inducing dominant mutations would provide an alternative strategy to introduce domestication traits in plants with high gene redundancy. Here we describe two complementary strategies to induce dominant mutations in the M. sativa genome and how they can be relevant in the control of flowering time. First, we outline a genome-engineering strategy that harnesses the use of microProteins as developmental regulators. MicroProteins are small proteins that appeared during genome evolution from genes encoding larger proteins. Genome-engineering allows us to retrace evolution and create microProtein-coding genes de novo. Second, we provide an inventory of genes regulated by microRNAs that control plant development. Making respective gene transcripts microRNA-resistant by inducing point mutations can uncouple microRNA regulation. Finally, we investigated the recently published genomes of M. sativa and provide an inventory of breeding targets, some of which, when mutated, are likely to result in dominant traits.

Quantitative Control of Early Flowering in White Lupin (Lupinus albus L.)

White lupin (Lupinus albus L.) is a pulse annual plant cultivated from the tropics to temperate regions for its high-protein grain as well as a cover crop or green manure. Wild populations are typically late flowering and have high vernalization requirements. Nevertheless, some early flowering and thermoneutral accessions were found in the Mediterranean basin. Recently, quantitative trait loci (QTLs) explaining flowering time variance were identified in bi-parental population mapping, however, phenotypic and genotypic diversity in the world collection has not been addressed yet. In this study, a diverse set of white lupin accessions (n = 160) was phenotyped for time to flowering in a controlled environment and genotyped with PCR-based markers (n = 50) tagging major QTLs and selected homologs of photoperiod and vernalization pathway genes. This survey highlighted quantitative control of flowering time in white lupin, providing statistically significant associations for all major QTLs and numerous regulatory genes, including white lupin homologs of CONSTANS, FLOWERING LOCUS T, FY, MOTHER OF FT AND TFL1, PHYTOCHROME INTERACTING FACTOR 4, SKI-INTERACTING PROTEIN 1, and VERNALIZATION INDEPENDENCE 3. This revealed the complexity of flowering control in white lupin, dispersed among numerous loci localized on several chromosomes, provided economic justification for future genome-wide association studies or genomic selection rather than relying on simple marker-assisted selection.

Beyond Arabidopsis: BBX Regulators in Crop Plants

B-box proteins represent diverse zinc finger transcription factors and regulators forming large families in various plants. A unique domain structure defines them—besides the highly conserved B-box domains, some B-box (BBX) proteins also possess CCT domain and VP motif. Based on the presence of these specific domains, they are mostly classified into five structural groups. The particular members widely differ in structure and fulfill distinct functions in regulating plant growth and development, including seedling photomorphogenesis, the anthocyanins biosynthesis, photoperiodic regulation of flowering, and hormonal pathways. Several BBX proteins are additionally involved in biotic and abiotic stress response. Overexpression of some BBX genes stimulates various stress-related genes and enhanced tolerance to different stresses. Moreover, there is evidence of interplay between B-box and the circadian clock mechanism. This review highlights the role of BBX proteins as a part of a broad regulatory network in crop plants, considering their participation in development, physiology, defense, and environmental constraints. A description is also provided of how various BBX regulators involved in stress tolerance were applied in genetic engineering to obtain stress tolerance in transgenic crops.

Comparative transcriptome analysis revealed differential gene expression in multiple signaling pathways at flowering in polyploid Brassica rapa

BACKGROUND

Polyploidy is widespread in angiosperms and has a significant impact on plant evolution, diversity, and breeding program. However, the changes in the flower development regulatory mechanism in autotetraploid plants remains relatively limited. In this study, RNA-seq analysis was used to investigate changes in signaling pathways at flowering in autotetraploid Brassica rapa.

RESULTS

The study findings showed that the key genes such as CO, CRY2, and FT which promotes floral formation were down-regulated, whereas floral transition genes FPF1 and FD were up-regulated in autotetraploid B. rapa. The data also demonstrated that the positive regulators GA1 and ELA1 in the gibberellin's biosynthesis pathway were negatively regulated by polyploidy in B. rapa. Furthermore, transcriptional factors (TFs) associated with flower development were significantly differentially expressed including the up-regulated CIB1 and AGL18, and the down-regulated AGL15 genes, and by working together such genes affected the expression of the down-stream flowering regulator FLOWERING LOCUS T in polyploid B. rapa. Compared with that in diploids autotetrapoid plants consist of differential expression within the signaling transduction pathway, with 13 TIFY gens up-regulated and 17 genes related to auxin pathway down-regulated.

CONCLUSION

Therefore, polyploidy is more likely to integrate multiple signaling pathways to influence flowering in B. rapa after polyploidization. In general, the present results shed new light on our global understanding of flowering regulation in polyploid plants during breeding program.

Construction of high-density genetic linkage map and mapping quantitative trait loci (QTL) for flowering time in autotetraploid alfalfa (Medicago sativa L.) using genotyping by sequencing

Flowering time is an important agronomic trait of alfalfa (Medicago sativa L.). Managing flowering time can produce economic benefits for farmers. To understand the genetic basis of this trait, quantitative trait loci (QTL) mapping was conducted in a full-sib population that consisted of 392 individuals segregating based on flowering time. High density linkage maps were constructed using single nucleotide polymorphism (SNP) markers generated by genotyping-by-sequencing (GBS). The linkage maps contained 3,818 SNP markers on 64 linkage groups in two parents. The average marker density was 4.33 cM for Parent 1 (P1) and 1.47 cM for Parent 2 (P2). Phenotypic data for flowering time was collected for three years at one location. Twenty-eight QTLs were identified associated with flowering time. Eleven QTLs explained more than 10% of the phenotypic variation. Among them, five main effect QTLs located on linkage group (LG) 7D of P1 and five main effect QTLs located on LG 6D of P2 were identified. Three QTLs were co-located with other QTLs. The identified linked markers to QTLs could be used for marker-assisted selection in breeding programs to develop new alfalfa varieties to modulate flowering time.

CmBBX8 accelerates flowering by targeting CmFTL1 directly in summer chrysanthemum

For a flowering plant, the transition from vegetative stage to reproductive growth is probably the most critical developmental switch. In the model plant Arabidopsis thaliana, the product of BBX7, group II member of BBX family, acts to delay floral transition. In this study, a presumed chrysanthemum homolog of a second group gene AtBBX8, designated CmBBX8, had been isolated and characterized. The transcription of CmBBX8 followed a diurnal rhythm as the chrysanthemum floral transition regulator. Overexpression of CmBBX8 accelerated flowering, while its (artificial microRNAs) amiR-enabled knockdown delayed flowering in plants grown under both long- and short-day conditions. Global expression analysis revealed that genes associated with photoperiod were down-regulated in amiR-CmBBX8 lines compared with the wild type, which were verified to be up-regulated in overexpressing lines (OX-CmBBX8) by RT-PCR. A number of in vitro assays were used to show that CmBBX8 targets CmFTL1. Furthermore, the function of CmFTL1 as a floral inducer under long-day conditions was confirmed by the behaviour of engineered summer-flowering chrysanthemum plants. The conclusion is that the BBX8-FT regulatory module is an important determinant of reproductive development in summer-flowering chrysanthemum.

QTL mapping of flowering time and biomass yield in tetraploid alfalfa (Medicago sativa L.)

BACKGROUND

The genetic and genomic basis of flowering time and biomass yield in alfalfa (Medicago sativa L.) remains poorly understood mainly due to the autopolyploid nature of the species and the lack of adequate genomic resources. We constructed linkage maps using genotyping-by-sequencing (GBS) based single dose allele (SDA) SNP and mapped alfalfa timing of flowering (TOF), spring yield (SY), and cumulative summer biomass (CSB) in a pseudo-testcross F1 population derived from a fall dormant (3010) and a non-dormant (CW 1010) cultivars. We analyzed the quantitative trait loci (QTL) to identify conserved genomic regions and detected molecular markers and potential candidate genes associated with the traits to improve alfalfa and provide genomic resources for the future studies.

RESULTS

This study showed that both fall dormant and non-dormant alfalfa cultivars harbored QTL for early and late flowering, suggesting that flowering time in alfalfa is not an indicator of its fall dormancy (FD) levels. A weak phenotypic correlation between the flowering time and fall dormancy (FD) in F1 and checks also corroborated that alfalfa FD and TOF are not the predictors of one another. The relationship between flowering time and alfalfa biomass yield was not strong, but the non-dormant had relatively more SY than dormant. Therefore, selecting superior alfalfa cultivars that are non-dormant, winter-hardy, and early flowering would allow for an early spring harvest with enhanced biomass. In this study, we found 25 QTL for TOF, 17 for SY and six QTL for CSB. Three TOF related QTL were stable and four TOF QTL were detected in the corresponding genomic locations of the flowering QTL of M. truncatula, an indication of possible evolutionarily conserved regions. The potential candidate genes for the SNP sequences of QTL regions were identified for all three traits and these genes would be potential targets for further molecular studies.

CONCLUSIONS

This research showed that variation in alfalfa flowering time after spring green up has no association with dormancy levels. Here we reported QTL, markers, and potential candidate genes associated with spring flowering time and biomass yield of alfalfa, which constitute valuable genomic resources for improving these traits via marker-assisted selection (MAS).

Molecular improvement of alfalfa for enhanced productivity and adaptability in a changing environment

Due to an expanding world population and increased buying power, the demand for ruminant products such as meat and milk is expected to grow substantially in coming years, and high levels of forage crop production will therefore be a necessity. Unfortunately, urbanization of agricultural land, intensive agricultural practices, and climate change are all predicted to limit crop production in the future, which means that the development of forage cultivars with improved productivity and adaptability will be essential. Because alfalfa (Medicago sativa L.) is one of the most widely cultivated perennial forage crops, it has been the target of much research in this field. In this review, we discuss progress that has been made towards the improvement of productivity, abiotic stress tolerance, and nutrient-use efficiency, as well as disease and pest resistance, in alfalfa using biotechnological techniques. Furthermore, we consider possible future priorities and avenues for attaining further enhancements in this crop as a means of contributing to the realization of food security in a changing environment.

Improving the Yield and Nutritional Quality of Forage Crops

Despite being some of the most important crops globally, there has been limited research on forages when compared with cereals, fruits, and vegetables. This review summarizes the literature highlighting the significance of forage crops, the current improvements and some of future directions for improving yield and nutritional quality. We make the point that the knowledge obtained from model plant and grain crops can be applied to forage crops. The timely development of genomics and bioinformatics together with genome editing techniques offer great scope to improve forage crops. Given the social, environmental and economic importance of forage across the globe and especially in poorer countries, this opportunity has enormous potential to improve food security and political stability.

Identification of Single-Nucleotide Polymorphic Loci Associated with Biomass Yield under Water Deficit in Alfalfa (Medicago sativa L.) Using Genome-Wide Sequencing and Association Mapping

Alfalfa is a worldwide grown forage crop and is important due to its high biomass production and nutritional value. However, the production of alfalfa is challenged by adverse environmental factors such as drought and other stresses. Developing drought resistance alfalfa is an important breeding target for enhancing alfalfa productivity in arid and semi-arid regions. In the present study, we used genotyping-by-sequencing and genome-wide association to identify marker loci associated with biomass yield under drought in the field in a panel of diverse germplasm of alfalfa. A total of 28 markers at 22 genetic loci were associated with yield under water deficit, whereas only four markers associated with the same trait under well-watered condition. Comparisons of marker-trait associations between water deficit and well-watered conditions showed non-similarity except one. Most of the markers were identical across harvest periods within the treatment, although different levels of significance were found among the three harvests. The loci associated with biomass yield under water deficit located throughout all chromosomes in the alfalfa genome agreed with previous reports. Our results suggest that biomass yield under drought is a complex quantitative trait with polygenic inheritance and may involve a different mechanism compared to that of non-stress. BLAST searches of the flanking sequences of the associated loci against DNA databases revealed several stress-responsive genes linked to the drought resistance loci, including leucine-rich repeat receptor-like kinase, B3 DNA-binding domain protein, translation initiation factor IF2, and phospholipase-like protein. With further investigation, those markers closely linked to drought resistance can be used for MAS to accelerate the development of new alfalfa cultivars with improved resistance to drought and other abiotic stresses.

Implications of High Temperature and Elevated CO2 on Flowering Time in Plants

Flowering is a crucial determinant for plant reproductive success and seed-set. Increasing temperature and elevated carbon-dioxide (e[CO2]) are key climate change factors that could affect plant fitness and flowering related events. Addressing the effect of these environmental factors on flowering events such as time of day of anthesis (TOA) and flowering time (duration from germination till flowering) is critical to understand the adaptation of plants/crops to changing climate and is the major aim of this review. Increasing ambient temperature is the major climatic factor that advances flowering time in crops and other plants, with a modest effect of e[CO2].Integrated environmental stimuli such as photoperiod, temperature and e[CO2] regulating flowering time is discussed. The critical role of plant tissue temperature influencing TOA is highlighted and crop models need to substitute ambient air temperature with canopy or floral tissue temperature to improve predictions. A complex signaling network of flowering regulation with change in ambient temperature involving different transcription factors (PIF4, PIF5), flowering suppressors (HvODDSOC2, SVP, FLC) and autonomous pathway (FCA, FVE) genes, mainly from Arabidopsis, provides a promising avenue to improve our understanding of the dynamics of flowering time under changing climate. Elevated CO2 mediated changes in tissue sugar status and a direct [CO2]-driven regulatory pathway involving a key flowering gene, MOTHER OF FT AND TFL1 (MFT), are emerging evidence for the role of e[CO2] in flowering time regulation.

Accuracy of genomic selection for alfalfa biomass yield in different reference populations

BACKGROUND

Genomic selection based on genotyping-by-sequencing (GBS) data could accelerate alfalfa yield gains, if it displayed moderate ability to predict parent breeding values. Its interest would be enhanced by predicting ability also for germplasm/reference populations other than those for which it was defined. Predicting accuracy may be influenced by statistical models, SNP calling procedures and missing data imputation strategies.

RESULTS

Landrace and variety material from two genetically-contrasting reference populations, i.e., 124 elite genotypes adapted to the Po Valley (sub-continental climate; PV population) and 154 genotypes adapted to Mediterranean-climate environments (Me population), were genotyped by GBS and phenotyped in separate environments for dry matter yield of their dense-planted half-sib progenies. Both populations showed no sub-population genetic structure. Predictive accuracy was higher by joint rather than separate SNP calling for the two data sets, and using random forest imputation of missing data. Highest accuracy was obtained using Support Vector Regression (SVR) for PV, and Ridge Regression BLUP and SVR for Me germplasm. Bayesian methods (Bayes A, Bayes B and Bayesian Lasso) tended to be less accurate. Random Forest Regression was the least accurate model. Accuracy attained about 0.35 for Me in the range of 0.30-0.50 missing data, and 0.32 for PV at 0.50 missing data, using at least 10,000 SNP markers. Cross-population predictions based on a smaller subset of common SNPs implied a relative loss of accuracy of about 25% for Me and 30% for PV. Genome-wide association analyses based on large subsets of M. truncatula-aligned markers revealed many SNPs with modest association with yield, and some genome areas hosting putative QTLs. A comparison of genomic vs. conventional selection for parent breeding value assuming 1-year vs. 5-year selection cycles, respectively, indicated over three-fold greater predicted yield gain per unit time for genomic selection.

CONCLUSIONS

Genomic selection for alfalfa yield is promising, based on its moderate prediction accuracy, moderate value of cross-population predictions, and lack of sub-population structure. There is limited scope for searching individual QTLs with overwhelming effect on yield. Some of our results can contribute to better design of genomic selection experiments for alfalfa and other crops with similar mating systems.

Accuracy of genomic selection for alfalfa biomass yield in different reference populations

BACKGROUND

Genomic selection based on genotyping-by-sequencing (GBS) data could accelerate alfalfa yield gains, if it displayed moderate ability to predict parent breeding values. Its interest would be enhanced by predicting ability also for germplasm/reference populations other than those for which it was defined. Predicting accuracy may be influenced by statistical models, SNP calling procedures and missing data imputation strategies.

RESULTS

Landrace and variety material from two genetically-contrasting reference populations, i.e., 124 elite genotypes adapted to the Po Valley (sub-continental climate; PV population) and 154 genotypes adapted to Mediterranean-climate environments (Me population), were genotyped by GBS and phenotyped in separate environments for dry matter yield of their dense-planted half-sib progenies. Both populations showed no sub-population genetic structure. Predictive accuracy was higher by joint rather than separate SNP calling for the two data sets, and using random forest imputation of missing data. Highest accuracy was obtained using Support Vector Regression (SVR) for PV, and Ridge Regression BLUP and SVR for Me germplasm. Bayesian methods (Bayes A, Bayes B and Bayesian Lasso) tended to be less accurate. Random Forest Regression was the least accurate model. Accuracy attained about 0.35 for Me in the range of 0.30-0.50 missing data, and 0.32 for PV at 0.50 missing data, using at least 10,000 SNP markers. Cross-population predictions based on a smaller subset of common SNPs implied a relative loss of accuracy of about 25% for Me and 30% for PV. Genome-wide association analyses based on large subsets of M. truncatula-aligned markers revealed many SNPs with modest association with yield, and some genome areas hosting putative QTLs. A comparison of genomic vs. conventional selection for parent breeding value assuming 1-year vs. 5-year selection cycles, respectively, indicated over three-fold greater predicted yield gain per unit time for genomic selection.

CONCLUSIONS

Genomic selection for alfalfa yield is promising, based on its moderate prediction accuracy, moderate value of cross-population predictions, and lack of sub-population structure. There is limited scope for searching individual QTLs with overwhelming effect on yield. Some of our results can contribute to better design of genomic selection experiments for alfalfa and other crops with similar mating systems.

Evidence for selection on a CONSTANS-like gene between two red oak species

BACKGROUND AND AIMS

Hybridizing species such as oaks may provide a model to study the role of selection in speciation with gene flow. Discrete species' identities and different adaptations are maintained among closely related oak species despite recurrent gene flow. This is probably due to ecologically mediated selection at a few key genes or genomic regions. Neutrality tests can be applied to identify so-called outlier loci, which demonstrate locus-specific signatures of divergent selection and are candidate genes for further study.

METHODS

Thirty-six genic microsatellite markers, some with putative functions in flowering time and drought tolerance, and eight non-genic microsatellite markers were screened in two population pairs (n = 160) of the interfertile species Quercus rubra and Q. ellipsoidalis, which are characterized by contrasting adaptations to drought. Putative outliers were then tested in additional population pairs from two different geographic regions (n = 159) to support further their potential role in adaptive divergence.

KEY RESULTS

A marker located in the coding sequence of a putative CONSTANS-like (COL) gene was repeatedly identified as under strong divergent selection across all three geographically disjunct population pairs. COL genes are involved in the photoperiodic control of growth and development and are implicated in the regulation of flowering time.

CONCLUSIONS

The location of the polymorphism in the Quercus COL gene and given the potential role of COL genes in adaptive divergence and reproductive isolation makes this a promising candidate speciation gene. Further investigation of the phenological characteristics of both species and flowering time pathway genes is suggested in order to elucidate the importance of phenology genes for the maintenance of species integrity. Next-generation sequencing in multiple population pairs in combination with high-density genetic linkage maps could reveal the genome-wide distribution of outlier genes and their potential role in reproductive isolation between these species.

Expression of the alfalfa CCCH-type zinc finger protein gene MsZFN delays flowering time in transgenic Arabidopsis thaliana

Zinc finger proteins comprise a large family and function in various developmental processes. CCCH type zinc finger protein is one kind of zinc finger protein, which function is little known. MsZFN gene encoding a CCCH type zinc finger protein was first discovered by its elevated transcript level in a salt-induced alfalfa SSH cDNA library. The previous experiment had showed that MsZFN protein was localized to the nucleus and little is known about the function of MsZFN protein and its homologous proteins in other plants including model plant, Arabidopsis thaliana. In the current study, we found that MsZFN transcript levels increased in alfalfa under continuous dark conditions and that expression was strongest in leaves and weakest in unopened flowers under light/dark conditions. Expression of MsZFN in transgenic Arabidopsis plants resulted in late flowering phenotypes under long day conditions. Yeast two-hybrid and bimolecular fluorescence complementation assays indicated that MsZFN protein can interact with itself. Transcript analyses of floral regulatory genes in MsZFN(+) transgenic Arabidopsis showed enhanced expression of the flowering repressor FLOWERING LOCUS C and decreased expression of three key flowering time genes, FLOWERING LOCUS T, SUPPRESSOR OF OVEREXPRESSION OF CONSTANS and GIGANTEA. These results suggest that MsZFN primarily controls flowering time by repressing flowering genes expression under long day conditions.

Molecular polymorphism related to flowering trait variation in a Phaseolus vulgaris L. collection

The aim of this study was to investigate the flowering variation and the molecular polymorphism in key regulatory genes that control flowering in a Phaseolus vulgaris L. collection of 94 accessions from Europe and the Americas. The analysis of variance revealed that the difference in days-to-flowering between accessions was significant, with European accessions characterized by flowering precocity. Population structure analysis corroborated previous data on the genetic distinction between the Andean and Mesoamerican gene pools. A low level of admixture was detected. Genomic sequences of 15 gene fragments were obtained. About 7.0 kb per accession were sequenced and a total of 48 nucleotide substitutions identified. A Mixed Linear Model analysis, including population structure and kinship, was used to identify marker-trait associations. Haplotype tagging single nucleotide polymorphisms (htSNPs) associated with the studied traits were detected: in PvVRN1 and PvPHYB with days-to-flowering, in PvMYB29 with number of flower buds per inflorescence and in PvTFL1z and PvFCA with inflorescence length. The two genes associated with days-to-flowering control belong to the photoperiod and vernalization pathways. In particular, the PvVRN1 gene appears to play an important role in regulating the adaptation process of common bean.

Functional and evolutionary characterization of the CONSTANS gene family in short-day photoperiodic flowering in soybean

CONSTANS (CO) plays a central role in photoperiodic flowering control of plants. However, much remains unknown about the function of the CO gene family in soybean and the molecular mechanisms underlying short-day photoperiodic flowering of soybean. We identified 26 CO homologs (GmCOLs) in the soybean genome, many of them previously unreported. Phylogenic analysis classified GmCOLs into three clades conserved among flowering plants. Two homeologous pairs in Clade I, GmCOL1a/GmCOL1b and GmCOL2a/GmCOL2b, showed the highest sequence similarity to Arabidopsis CO. The mRNA abundance of GmCOL1a and GmCOL1b exhibited a strong diurnal rhythm under flowering-inductive short days and peaked at dawn, which coincided with the rise of GmFT5a expression. In contrast, the mRNA abundance of GmCOL2a and GmCOL2b was extremely low. Our transgenic study demonstrated that GmCOL1a, GmCOL1b, GmCOL2a and GmCOL2b fully complemented the late flowering effect of the co-1 mutant in Arabidopsis. Together, these results indicate that GmCOL1a and GmCOL1b are potential inducers of flowering in soybean. Our data also indicate rapid regulatory divergence between GmCOL1a/GmCOL1b and GmCOL2a/GmCOL2b but conservation of their protein function. Dynamic evolution of GmCOL regulatory mechanisms may underlie the evolution of photoperiodic signaling in soybean.

Development of an alfalfa SNP array and its use to evaluate patterns of population structure and linkage disequilibrium

A large set of genome-wide markers and a high-throughput genotyping platform can facilitate the genetic dissection of complex traits and accelerate molecular breeding applications. Previously, we identified about 0.9 million SNP markers by sequencing transcriptomes of 27 diverse alfalfa genotypes. From this SNP set, we developed an Illumina Infinium array containing 9,277 SNPs. Using this array, we genotyped 280 diverse alfalfa genotypes and several genotypes from related species. About 81% (7,476) of the SNPs met the criteria for quality control and showed polymorphisms. The alfalfa SNP array also showed a high level of transferability for several closely related Medicago species. Principal component analysis and model-based clustering showed clear population structure corresponding to subspecies and ploidy levels. Within cultivated tetraploid alfalfa, genotypes from dormant and nondormant cultivars were largely assigned to different clusters; genotypes from semidormant cultivars were split between the groups. The extent of linkage disequilibrium (LD) across all genotypes rapidly decayed to 26 Kbp at r(2) = 0.2, but the rate varied across ploidy levels and subspecies. A high level of consistency in LD was found between and within the two subpopulations of cultivated dormant and nondormant alfalfa suggesting that genome-wide association studies (GWAS) and genomic selection (GS) could be conducted using alfalfa genotypes from throughout the fall dormancy spectrum. However, the relatively low LD levels would require a large number of markers to fully saturate the genome.

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.

Anti-microbial peptide (AMP): nucleotide variation, gene expression, and host resistance in the white pine blister rust (WPBR) pathosystem

Pinus monticola antimicrobial peptide (PmAMP1) inhibits growth of Cronartium ribicola and other fungal pathogens. C. ribicola causes white pine blister rust and has resulted in a dramatic reduction of native white pines across North America. Quantitative disease resistance (QDR) is a highly desirable trait screened in breeding programs for durable resistance against C. ribicola. Along with phenotyping on a collection of germplasms, we analyzed PmAMP1 transcript and protein expression and re-sequenced the full-length gene including its promoter region. A mixed linear model was used to identify the association of single nucleotide polymorphisms (SNPs) with accumulated protein and stem QDR levels. Among 16 PmAMP1 SNPs identified in the present study, we found an association of protein levels with 6 SNPs (P < 0.05), including 2 in the 5'-untranslated region (UTR), 3 in the open reading frame (ORF) region with 2 nonsynonymous SNPs, and 1 SNP in the 3'-UTR. Another set of six SNPs was associated with stem QDR levels (P < 0.05), with one localized in the promoter region and the other five in the ORF region with four nonsynonymous changes, suggesting that multiple isoforms may have antifungal activity to differing degrees. Of three common PmAMP1 haplotypes, the trees with haplotype 2 showed high QDR levels with moderate protein abundance while those trees with haplotype 3 exhibited low QDR levels in the susceptible range and the lowest level of protein accumulation. Thus, an association of gene variations with protein abundance and resistance-related traits may facilitate elucidation of physiological contribution of PmAMP1 to host resistance.

Molecular physiology and breeding at the crossroads of cold hardiness improvement

Alfalfa (Medicago sativa L.) is a major forage legume grown extensively worldwide with important agronomic and environmental attributes. Insufficient cold hardiness is a major impediment to its reliable production in northern climates. Improvement of freezing tolerance using conventional breeding approaches is slowed by the quantitative nature of inheritance and strong interactions with the environment. The development of gene-based markers would facilitate the identification of genotypes with superior stress tolerance. Successive cycles of recurrent selection were applied using an indoor screening method to develop populations with significantly higher tolerance to freezing (TF). Bulk segregant analysis of heterogeneous TF populations identified DNA variations that are progressively enriched in frequency in response to selection. Polymorphisms resulting from intragenic variations within a dehydrin gene were identified and could potentially lead to the development of robust selection tools. Our results illustrate the benefits of feedback interactions between germplasm development programs and molecular physiology for a deeper understanding of the molecular and genetic bases of cold hardiness.

Comparative analysis of kabuli chickpea transcriptome with desi and wild chickpea provides a rich resource for development of functional markers

Chickpea (Cicer arietinum L.) is an important crop legume plant with high nutritional value. The transcriptomes of desi and wild chickpea have already been sequenced. In this study, we sequenced the transcriptome of kabuli chickpea, C. arietinum (genotype ICCV2), having higher commercial value, using GS-FLX Roche 454 and Illumina technologies. The assemblies of both Roche 454 and Illumina datasets were optimized using various assembly programs and parameters. The final optimized hybrid assembly generated 43,389 transcripts with an average length of 1065 bp and N50 length of 1653 bp representing 46.2 Mb of kabuli chickpea transcriptome. We identified a total of 5409 simple sequence repeats (SSRs) in these transcript sequences. Among these, at least 130 and 493 SSRs were polymorphic with desi (ICC4958) and wild (PI489777) chickpea, respectively. In addition, a total of 1986 and 37,954 single nucleotide polymorphisms (SNPs) were predicted in kabuli/desi and kabuli/wild genotypes, respectively. The SNP frequency was 0.043 SNP per kb for kabuli/desi and 0.821 SNP per kb for kabuli/wild, reflecting very low genetic diversity in chickpea. Further, SSRs and SNPs present in tissue-specific and transcription factor encoding transcripts have been identified. The experimental validation of a selected set of polymorphic SSRs and SNPs exhibited high intra-specific polymorphism potential between desi and kabuli chickpea, suggesting their utility in large-scale genotyping applications. The kabuli chickpea gene index assembled, and SSRs and SNPs identified in this study will serve as useful genomic resource for genetic improvement of chickpea.

Patterns of linkage disequilibrium and association mapping in diploid alfalfa (M. sativa L.)

Association mapping enables the detection of marker-trait associations in unstructured populations by taking advantage of historical linkage disequilibrium (LD) that exists between a marker and the true causative polymorphism of the trait phenotype. Our first objective was to understand the pattern of LD decay in the diploid alfalfa genome. We used 89 highly polymorphic SSR loci in 374 unimproved diploid alfalfa (Medicago sativa L.) genotypes from 120 accessions to infer chromosome-wide patterns of LD. We also sequenced four lignin biosynthesis candidate genes (caffeoyl-CoA 3-O-methyltransferase (CCoAoMT), ferulate-5-hydroxylase (F5H), caffeic acid-O-methyltransferase (COMT), and phenylalanine amonialyase (PAL 1)) to identify single nucleotide polymorphisms (SNPs) and infer within gene estimates of LD. As the second objective of this study, we conducted association mapping for cell wall components and agronomic traits using the SSR markers and SNPs from the four candidate genes. We found very little LD among SSR markers implying limited value for genomewide association studies. In contrast, within gene LD decayed within 300 bp below an r (2) of 0.2 in three of four candidate genes. We identified one SSR and two highly significant SNPs associated with biomass yield. Based on our results, focusing association mapping on candidate gene sequences will be necessary until a dense set of genome-wide markers is available for alfalfa.

Intron-length polymorphism identifies a Y2K4 dehydrin variant linked to superior freezing tolerance in alfalfa

Breeding alfalfa (Medicago sativa L.) with superior freezing tolerance could be accelerated by the identification of molecular markers associated to that trait. Dehydrins are a group of highly hydrophilic proteins that have been related to low temperature tolerance. We previously identified a dehydrin restriction fragment length polymorphism (RFLP) among populations recurrently selected for superior tolerance to freezing (TF). Analysis of crosses between genotypes with (D+) or without (D-) that RFLP revealed a significant impact on freezing tolerance. In this study, we sought to develop a PCR marker for freezing tolerance based on prior evidence of a relationship between size variation in Y(2)K(4) dehydrins and the RFLP. Results confirm the enrichment of Y(2)K(4) sequences of intermediate size (G2 group) in response to recurrent selection and in the D+ progeny. Analysis of genomic sequences revealed significant intron-length polymorphism (ILP) within the G2 group. G2 sequences with a characteristic short intron were more frequently found in D+ genotypes. Amplification using sequence-characterized amplified region (SCAR) primers bordering the intron confirmed an increase in the number of fragments with small introns in the D+ progeny and in the ATF5 population obtained after five cycles of recurrent selection for superior TF within the cultivar Apica (ATF0). Conversely, there was a reduction in the number of fragments with long introns in the D+ progeny and in ATF5 as compared to ATF0. Recurrent selection for superior tolerance to freezing in combination with ILP identified a sequence variant of Y(2)K(4) dehydrins associated to the phenotypic response to selection.

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.

Towards the adaptation of grapevine varieties to climate change: QTLs and candidate genes for developmental stages

The genetic determinism of developmental stages in grapevine was studied in the progeny of a cross between grapevine cultivars Riesling and Gewurztraminer by combining ecophysiological modelling, genetic analysis and data mining of the grapevine whole genome sequence. The dates of three phenological stages, budbreak, flowering and veraison, were recorded during four successive years for 120 genotypes in the vineyard. The phenotypic data analysed were the duration of three periods expressed in thermal time (degree-days): 15 February to budbreak (Bud), budbreak to flowering (Flo) and flowering to veraison (Ver). Parental and consensus genetic maps were built using 153 microsatellite markers on 188 individuals. Six independent quantitative trait loci (QTLs) were detected for the three phases. They were located on chromosomes 4 and 19 for Bud, chromosomes 7 and 14 for Flo and chromosomes 16 and 18 for Ver. Interactions were detected between loci and also between alleles at the same locus. Using the available grapevine whole-genome sequences, candidate genes underlying the QTLs were identified. VvFT, on chromosome 7, and a CONSTANS-like gene, on chromosome 14, were found to colocalise with the QTLs for flowering time. Genes related to the abscisic acid response and to sugar metabolism were detected within the confidence intervals of QTLs for veraison time. Their possible roles in the developmental process are discussed. These results raise new hypotheses for a better understanding of the physiological processes governing grapevine phenology and provide a framework for breeding new varieties adapted to the future predicted climatic conditions.

SNiPlay: a web-based tool for detection, management and analysis of SNPs. Application to grapevine diversity projects

BACKGROUND

High-throughput re-sequencing, new genotyping technologies and the availability of reference genomes allow the extensive characterization of Single Nucleotide Polymorphisms (SNPs) and insertion/deletion events (indels) in many plant species. The rapidly increasing amount of re-sequencing and genotyping data generated by large-scale genetic diversity projects requires the development of integrated bioinformatics tools able to efficiently manage, analyze, and combine these genetic data with genome structure and external data.

RESULTS

In this context, we developed SNiPlay, a flexible, user-friendly and integrative web-based tool dedicated to polymorphism discovery and analysis. It integrates:1) a pipeline, freely accessible through the internet, combining existing softwares with new tools to detect SNPs and to compute different types of statistical indices and graphical layouts for SNP data. From standard sequence alignments, genotyping data or Sanger sequencing traces given as input, SNiPlay detects SNPs and indels events and outputs submission files for the design of Illumina's SNP chips. Subsequently, it sends sequences and genotyping data into a series of modules in charge of various processes: physical mapping to a reference genome, annotation (genomic position, intron/exon location, synonymous/non-synonymous substitutions), SNP frequency determination in user-defined groups, haplotype reconstruction and network, linkage disequilibrium evaluation, and diversity analysis (Pi, Watterson's Theta, Tajima's D).Furthermore, the pipeline allows the use of external data (such as phenotype, geographic origin, taxa, stratification) to define groups and compare statistical indices.2) a database storing polymorphisms, genotyping data and grapevine sequences released by public and private projects. It allows the user to retrieve SNPs using various filters (such as genomic position, missing data, polymorphism type, allele frequency), to compare SNP patterns between populations, and to export genotyping data or sequences in various formats.

CONCLUSIONS

Our experiments on grapevine genetic projects showed that SNiPlay allows geneticists to rapidly obtain advanced results in several key research areas of plant genetic diversity. Both the management and treatment of large amounts of SNP data are rendered considerably easier for end-users through automation and integration. Current developments are taking into account new advances in high-throughput technologies.SNiPlay is available at: http://sniplay.cirad.fr/.