Identification of loci controlling forage yield and nutritive value in diploid alfalfa using GBS-GWAS

Pearl millet a promising fodder crop for changing climate: a review

The agricultural sector faces colossal challenges amid environmental changes and a burgeoning human population. In this context, crops must adapt to evolving climatic conditions while meeting increasing production demands. The dairy industry is anticipated to hold the highest value in the agriculture sector in future. The rise in the livestock population is expected to result in an increased demand for fodder feed. Consequently, it is crucial to seek alternative options, as crops demand fewer resources and are resilient to climate change. Pearl millet offers an apposite key to these bottlenecks, as it is a promising climate resilience crop with significantly low energy, water and carbon footprints compared to other crops. Numerous studies have explored its potential as a fodder crop, revealing promising performance. Despite its capabilities, pearl millet has often been overlooked. To date, few efforts have been made to document molecular aspects of fodder-related traits. However, several QTLs and candidate genes related to forage quality have been identified in other fodder crops, which can be harnessed to enhance the forage quality of pearl millet. Lately, excellent genomic resources have been developed in pearl millet allowing deployment of cutting-edge genomics-assisted breeding for achieving a higher rate of genetic gains. This review would facilitate a deeper understanding of various aspects of fodder pearl millet in retrospect along with the future challenges and their solution. This knowledge may pave the way for designing efficient breeding strategies in pearl millet thereby supporting sustainable agriculture and livestock production in a changing world.

A genome-wide association study reveals novel loci and candidate genes associated with plant height variation in Medicago sativa

BACKGROUND

Plant height (PH) is an important agronomic trait influenced by a complex genetic network. However, the genetic basis for the variation in PH in Medicago sativa remains largely unknown. In this study, a comprehensive genome-wide association analysis was performed to identify genomic regions associated with PH using a diverse panel of 220 accessions of M. sativa worldwide.

RESULTS

Our study identified eight novel single nucleotide polymorphisms (SNPs) significantly associated with PH evaluated in five environments, explaining 8.59-12.27% of the phenotypic variance. Among these SNPs, the favorable genotype of chr6__31716285 had a low frequency of 16.4%. Msa0882400, located proximal to this SNP, was annotated as phosphate transporter 3;1, and its role in regulating alfalfa PH was supported by transcriptome and candidate gene association analysis. In addition, 21 candidate genes were annotated within the associated regions that are involved in various biological processes related to plant growth and development.

CONCLUSIONS

Our findings provide new molecular markers for marker-assisted selection in M. sativa breeding programs. Furthermore, this study enhances our understanding of the underlying genetic and molecular mechanisms governing PH variations in M. sativa.

The chromosome-level assembly of the wild diploid alfalfa genome provides insights into the full landscape of genomic variations between cultivated and wild alfalfa

Alfalfa (Medicago sativa L.) is one of the most important forage legumes in the world, including autotetraploid (M. sativa ssp. sativa) and diploid alfalfa (M. sativa ssp. caerulea, progenitor of autotetraploid alfalfa). Here, we reported a high-quality genome of ZW0012 (diploid alfalfa, 769 Mb, contig N50 = 5.5 Mb), which was grouped into the Northern group in population structure analysis, suggesting that our genome assembly filled a major gap among the members of M. sativa complex. During polyploidization, large phenotypic differences occurred between diploids and tetraploids, and the genetic information underlying its massive phenotypic variations remains largely unexplored. Extensive structural variations (SVs) were identified between ZW0012 and XinJiangDaYe (an autotetraploid alfalfa with released genome). We identified 71 ZW0012-specific PAV genes and 1296 XinJiangDaYe-specific PAV genes, mainly involved in defence response, cell growth, and photosynthesis. We have verified the positive roles of MsNCR1 (a XinJiangDaYe-specific PAV gene) in nodulation using an Agrobacterium rhizobia-mediated transgenic method. We also demonstrated that MsSKIP23_1 and MsFBL23_1 (two XinJiangDaYe-specific PAV genes) regulated leaf size by transient overexpression and virus-induced gene silencing analysis. Our study provides a high-quality reference genome of an important diploid alfalfa germplasm and a valuable resource of variation landscape between diploid and autotetraploid, which will facilitate the functional gene discovery and molecular-based breeding for the cultivars in the future.

Discovering new genes for alfalfa (Medicago sativa) growth and biomass resilience in combined salinity and Phoma medicaginis infection through GWAS

Salinity and Phoma medicaginis infection represent significant challenges for alfalfa cultivation in South Africa, Europe, Australia, and, particularly, Tunisia. These constraints have a severe impact on both yield and quality. The primary aim of this study was to establish the genetic basis of traits associated with biomass and growth of 129 Medicago sativa genotypes through genome-wide association studies (GWAS) under combined salt and P. medicaginis infection stresses. The results of the analysis of variance (ANOVA) indicated that the variation in these traits could be primarily attributed to genotype effects. Among the test genotypes, the length of the main stem, the number of ramifications, the number of chlorotic leaves, and the aerial fresh weight exhibited the most significant variation. The broad-sense heritability (H²) was relatively high for most of the assessed traits, primarily due to genetic factors. Cluster analysis, applied to morpho-physiological traits under the combined stresses, revealed three major groups of accessions. Subsequently, a GWAS analysis was conducted to validate significant associations between 54,866 SNP-filtered single-nucleotide polymorphisms (SNPs) and seven traits. The study identified 27 SNPs that were significantly associated with the following traits: number of healthy leaves (two SNPs), number of chlorotic leaves (five SNPs), number of infected necrotic leaves (three SNPs), aerial fresh weight (six SNPs), aerial dry weight (nine SNPs), number of ramifications (one SNP), and length of the main stem (one SNP). Some of these markers are related to the ionic transporters, cell membrane rigidity (related to salinity tolerance), and the NBS_LRR gene family (associated with disease resistance). These findings underscore the potential for selecting alfalfa genotypes with tolerance to the combined constraints of salinity and P. medicaginis infection.

In Vitro Collection for the Safe Storage of Grapevine Hybrids and Identification of the Presence of Plasmopara viticola Resistance Genes

This paper focuses on the creation of an in vitro collection of grapevine hybrids from the breeding program of the Kazakh Scientific Research Institute of Fruit Growing and Viticulture and investigates the presence of Plasmopara viticola resistance mediated by Rpv3 and Rpv12 loci. We looked at the optimization of in vitro establishment using either shoots taken directly from field-grown plants or from budwood cuttings forced indoors. We further screened for the presence of endophyte contamination in the initiated explants and optimized the multiplication stage. Finally, the presence of the resistance loci against P. viticola was studied. The shoots initiated from the field-sourced explants were the more effective method of providing plant sources for in vitro initiation once all plant accessions met the goal of in vitro establishment. The concentration of phytohormones and the acidity of the culture medium have a great effect on the multiplication rate and the quality of in vitro stock cultures. Out of 17 grapevine accessions, 16 showed the presence of single or combined resistance loci against P. viticola. The grapevine accessions identified as carrying Rpv3 and Rpv12 alleles represent important genetic resources for disease resistance breeding programs. These accessions may further contribute to the creation of new elite cultivars of economic interest.

Novel loci associated with resistance to downy and powdery mildew in grapevine

Among the main challenges in current viticulture, there is the increasing demand for sustainability in the protection from fungal diseases, such as downy mildew (DM) and powdery mildew (PM). Breeding disease-resistant grapevine varieties is a key strategy for better managing fungicide inputs. This study explores the diversity of grapevine germplasm (cultivated and wild) from Caucasus and neighboring areas to identify genotypes resistant to DM and PM, based on 13 Simple Sequence Repeat (SSR) loci and phenotypical (artificial pathogen inoculation) analysis, and to identify loci associated with DM and PM resistance, via Genome-Wide Association Analysis (GWAS) on Single Nucleotide Polymorphism (SNP) profiles. SSR analysis revealed resistant alleles for 16 out of 88 genotypes. Phenotypic data identified seven DM and 31 PM resistant genotypes. GWAS identified two new loci associated with DM resistance, located on chromosome 15 and 16 (designated as Rpv36 and Rpv37), and two with PM resistance, located on chromosome 6 and 17 (designated as Ren14 and Ren15). The four novel loci identified genomic regions rich in genes related to biotic stress response, such as genes involved in pathogen recognition, signal transduction and resistance response. This study highlights potential candidate genes associated with resistance to DM and PM, providing valuable insights for breeding programs for resistant varieties. To optimize their utilization, further functional characterization studies are recommended.

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.

Identification of genetic loci associated with five agronomic traits in alfalfa using multi-environment trials

The use of multi-environment trials to test yield-related traits in a diverse alfalfa panel allowed to find multiple molecular markers associated with complex agronomic traits. Yield is one of the most important target traits in alfalfa breeding; however, yield is a complex trait affected by genetic and environmental factors. In this study, we used multi-environment trials to test yield-related traits in a diverse panel composed of 200 alfalfa accessions and varieties. Phenotypic data of maturity stage measured as mean stage by count (MSC), dry matter content, plant height (PH), biomass yield (Yi), and fall dormancy (FD) were collected in three locations in Idaho, Oregon, and Washington from 2018 to 2020. Single-trial and stagewise analyses were used to obtain estimated trait means of entries by environment. The plants were genotyped using a genotyping by sequencing approach and obtained a genotypic matrix with 97,345 single nucleotide polymorphisms. Genome-wide association studies identified a total of 84 markers associated with the traits analyzed. Of those, 29 markers were in noncoding regions and 55 markers were in coding regions. Ten significant SNPs at the same locus were associated with FD and they were linked to a gene annotated as a nuclear fusion defective 4-like (NFD4). Additional SNPs associated with MSC, PH, and Yi were annotated as transcription factors such as Cysteine3Histidine (C3H), Hap3/NF-YB family, and serine/threonine-protein phosphatase 7 proteins, respectively. Our results provide insight into the genetic factors that influence alfalfa maturity, yield, and dormancy, which is helpful to speed up the genetic gain toward alfalfa yield improvement.

Large-scale population structure and genetic architecture of agronomic traits of garlic

Garlic, an asexually propagated crop, is the second important bulb crop after the onion and is used as a vegetable and medicinal plant. Abundant and diverse garlic resources have been formed over thousands of years of cultivation. However, genome variation, population structure and genetic architecture of garlic agronomic traits were still not well elucidated. Here, 1 100 258 single nucleotide polymorphisms (SNPs) were identified using genotyping-by-sequencing in 606 garlic accessions collected from 43 countries. Population structure, principal component and phylogenetic analysis showed that these accessions were divided into five subpopulations. Twenty agronomic traits, including above-ground growth traits, bulb-related and bolt-related traits in two consecutive years were implemented in a genome-wide association study. In total, 542 SNPs were associated with these agronomic traits, among which 188 SNPs were repeatedly associated with more than two traits. One SNP (chr6: 1896135972) was repeatedly associated with ten traits. These associated SNPs were located within or near 858 genes, 56 of which were transcription factors. Interestingly, one non-synonymous SNP (Chr4: 166524085) in ribosomal protein S5 was repeatedly associated with above-ground growth and bulb-related traits. Additionally, gene ontology enrichment analysis of candidate genes for genomic selection regions between complete-bolting and non-bolting accessions showed that these genes were significantly enriched in 'vegetative to reproductive phase transition of meristem', 'shoot system development', 'reproductive process', etc. These results provide valuable information for the reliable and efficient selection of candidate genes to achieve garlic genetic improvement and superior varieties.

Genetic diversity and local adaption of alfalfa populations (Medicago sativa L.) under long-term grazing

Genomic information on alfalfa adaptation to long-term grazing is useful for alfalfa genetic improvement. In this study, 14 alfalfa populations were collected from long-term grazing sites (> 25 years) across four soil zones in western Canada. Alfalfa cultivars released between 1926 and 1980 were used to compare degree of genetic variation of the 14 populations. Six agro-morphological and three nutritive value traits were evaluated from 2018 to 2020. The genotyping-by-sequencing (GBS) data of the alfalfa populations and environmental data were used for genotype-environment association (GEA). Both STRUCTURE and UPGMA based on 19,853 SNPs showed that the 14 alfalfa populations from long-term grazing sites had varying levels of parentages from alfalfa sub-species Medicago sativa and M. falcata. The linear regression of STRUCTURE membership probability on phenotypic data indicated genetic variations of forage dry matter yield, spring vigor and plant height were low, but genetic variations of regrowth, fall plant height, days to flower and crude protein were still high for the 14 alfalfa populations from long-term grazing sites. The GEA identified 31 SNPs associated with 13 candidate genes that were mainly associated with six environmental factors of. Candidate genes underlying environmental factors were associated with a variety of proteins, which were involved in plant responses to abiotic stresses, i.e., drought, cold and salinity-alkali stresses.

Outlier analyses and genome-wide association study identify glgC and ERD6-like 4 as candidate genes for foliar water-soluble carbohydrate accumulation in Trifolium repens

Increasing water-soluble carbohydrate (WSC) content in white clover is important for improving nutritional quality and reducing environmental impacts from pastoral agriculture. Elucidation of genes responsible for foliar WSC variation would enhance genetic improvement by enabling molecular breeding approaches. The aim of the present study was to identify single nucleotide polymorphisms (SNPs) associated with variation in foliar WSC in white clover. A set of 935 white clover individuals, randomly sampled from five breeding pools selectively bred for divergent (low or high) WSC content, were assessed with 14,743 genotyping-by-sequencing SNPs, using three outlier detection methods: PCAdapt, BayeScan and KGD-F_ST. These analyses identified 33 SNPs as discriminating between high and low WSC populations and putatively under selection. One SNP was located in the intron of ERD6-like 4, a gene coding for a sugar transporter located on the vacuole membrane. A genome-wide association study using a subset of 605 white clover individuals and 5,757 SNPs, identified a further 12 SNPs, one of which was associated with a starch biosynthesis gene, glucose-1-phosphate adenylyltransferase, glgC. Our results provide insight into genomic regions underlying WSC accumulation in white clover, identify candidate genomic regions for further functional validation studies, and reveal valuable information for marker-assisted or genomic selection in white clover.

Application of machine learning to explore the genomic prediction accuracy of fall dormancy in autotetraploid alfalfa

Fall dormancy (FD) is an essential trait to overcome winter damage and for alfalfa (Medicago sativa) cultivar selection. The plant regrowth height after autumn clipping is an indirect way to evaluate FD. Transcriptomics, proteomics, and quantitative trait locus mapping have revealed crucial genes correlated with FD; however, these genes cannot predict alfalfa FD very well. Here, we conducted genomic prediction of FD using whole-genome SNP markers based on machine learning-related methods, including support vector machine (SVM) regression, and regularization-related methods, such as Lasso and ridge regression. The results showed that using SVM regression with linear kernel and the top 3000 genome-wide association study (GWAS)-associated markers achieved the highest prediction accuracy for FD of 64.1%. For plant regrowth height, the prediction accuracy was 59.0% using the 3000 GWAS-associated markers and the SVM linear model. This was better than the results using whole-genome markers (25.0%). Therefore, the method we explored for alfalfa FD prediction outperformed the other models, such as Lasso and ElasticNet. The study suggests the feasibility of using machine learning to predict FD with GWAS-associated markers, and the GWAS-associated markers combined with machine learning would benefit FD-related traits as well. Application of the methodology may provide potential targets for FD selection, which would accelerate genetic research and molecular breeding of alfalfa with optimized FD.

Improved drought tolerance of EMS mutagenized Alfalfa (Medicago sativa L.) mutants by in vitro screening at germination stage

The objectives of this study were to determine drought tolerant novel mutant of alfalfa (Medicago sativa L.) genotypes by screening EMS mutagenized 340675 M₃ seeds at germination stages in the presence of osmotic stress of 35% PEG₆₀₀₀. Root growth assay provided several drought tolerant candidate mutants. Of those, 4 mutants were further evaluated at water deficit conditions applied for 24 days after the first cutting at flowering bud stage. The results revealed that mutants determined as drought tolerant at germination stage were also tolerant to water deficit conditions. Protein content and superoxide dismutase values were found to be higher in all mutants than controls. Ascorbate peroxides, glutton reductase and lipid peroxidase values varied based on the mutant genotype and duration of drought stress. Drought stress significantly changed transcriptional levels of MtP5CS, MtDehyd, MseIF-2, MtRD2 and MsNAC genes. These results indicated that in vitro screening of alfalfa mutant seeds for osmatic tolerance at germination and early seedling growth stages was successfully able to determine the drought tolerant alfalfa mutants which were also tolerant to water deficit conditions after the first cutting at flowering bud stage.

Genotyping-by-sequencing and genome-wide association study reveal genetic diversity and loci controlling agronomic traits in triticale

The genetic diversity and loci underlying agronomic traits were analyzed by the reads coverage and genome-wide association study based genotyping-by-sequencing in a diverse population consisting of 199 accessions. Triticale (× Triticosecale Wittmack) is an economically important grain forage and energy crop planted worldwide for its high biomass. Little is known about the genetic diversity and loci underlying agronomic traits in triticale. We performed genotyping-by-sequencing of 199 cultivars and mapped reads to the A, B, D, and R genomes for karyotype analysis. These cultivars could mostly be grouped into five types. Some chromosome abnormalities occurred with high frequency, such as 2D (2R) substitution, deletion of the long arm of chromosome 2D or the short arm of 5R, and translocation of the long arms of 7D/7A, the short arms of 6D/6A, or the long arms of 1D/1A. We chose only widely planted hexaploid triticale cultivars (153) for genome-wide association study. These cultivars could be divided into nine distinct groups, and the linkage disequilibrium decay was 25.4 kb in this population. We identified 253 significant marker-trait associations (MTAs) on 20 chromosomes, except 7R. Twenty-one reliable MTAs were identified repeatedly over two environments. We predicted 16 putative candidate genes involved in plant growth and development using the genome sequences of wheat and rye. These results provide a basis for understanding the genetic mechanisms of agronomic traits and will benefit the breeding of improved hexaploid triticale.

Genome assembly of alfalfa cultivar zhongmu-4 and identification of SNPs associated with agronomic traits

Alfalfa (Medicago sativa L.) is the most important legume forage crop worldwide with high nutritional value and yield. For a long time, the breeding of alfalfa was hampered by lacking reliable information on the autotetraploid genome and molecular markers linked to important agronomic traits. We herein reported the de novo assembly of the allele-aware chromosome-level genome of Zhongmu-4, a cultivar widely cultivated in China, and a comprehensive database of genomic variations based on resequencing of 220 germplasms. Approximate 2.74 Gb contigs (N50 of 2.06 Mb), accounting for 88.39% of the estimated genome, were assembled, and 2.56 Gb contigs were anchored to 32 pseudo-chromosomes. A total of 34,922 allelic genes were identified from the allele-aware genome. We observed the expansion of gene families, especially those related to the nitrogen metabolism, and the increase of repetitive elements including transposable elements, which probably resulted in the increase of Zhongmu-4 genome compared with Medicago truncatula. Population structure analysis revealed that the accessions from Asia and South America had relatively lower genetic diversity than those from Europe, suggesting that geography may influence alfalfa genetic divergence during local adaption. Genome-wide association studies identified 101 single nucleotide polymorphisms (SNPs) associated with 27 agronomic traits. Two candidate genes were predicted to be correlated with fall dormancy and salt response. We believe that the allele-aware chromosome-level genome sequence of Zhongmu-4 combined with the resequencing data of the diverse alfalfa germplasms will facilitate genetic research and genomics-assisted breeding in variety improvement of alfalfa.

Major effect loci for plant size before onset of nitrogen fixation allow accurate prediction of yield in white clover

Accurate genomic prediction of yield within and across generations was achieved by estimating the genetic merit of individual white clover genotypes based on extensive genetic replication using cloned material. White clover is an agriculturally important forage legume grown throughout temperate regions as a mixed clover-grass crop. It is typically cultivated with low nitrogen input, making yield dependent on nitrogen fixation by rhizobia in root nodules. Here, we investigate the effects of clover and rhizobium genetic variation by monitoring plant growth and quantifying dry matter yield of 704 combinations of 145 clover genotypes and 170 rhizobium inocula. We find no significant effect of rhizobium variation. In contrast, we can predict yield based on a few white clover markers strongly associated with plant size prior to nitrogen fixation, and the prediction accuracy for polycross offspring yield is remarkably high. Several of the markers are located near a homolog of Arabidopsis thaliana GIGANTUS 1, which regulates growth rate and biomass accumulation. Our work provides fundamental insight into the genetics of white clover yield and identifies specific candidate genes as breeding targets.

Identification of Novel Quantitative Trait Nucleotides and Candidate Genes for Bacterial Wilt Resistance in Tobacco (Nicotiana tabacum L.) Using Genotyping-by-Sequencing and Multi-Locus Genome-Wide Association Studies

Tobacco bacterial wilt (TBW) is a devastating soil-borne disease threatening the yield and quality of tobacco. However, its genetic foundations are not fully understood. In this study, we identified 126,602 high-quality single-nucleotide polymorphisms (SNPs) in 94 tobacco accessions using genotyping-by-sequencing (GBS) and a 94.56 KB linkage disequilibrium (LD) decay rate for candidate gene selection. The population structure analysis revealed two subpopulations with 37 and 57 tobacco accessions. Four multi-locus genome-wide association study (ML-GWAS) approaches identified 142 quantitative trait nucleotides (QTNs) in E1-E4 and the best linear unbiased prediction (BLUP), explaining 0.49-22.52% phenotypic variance. Of these, 38 novel stable QTNs were identified across at least two environments/methods, and their alleles showed significant TBW-DI differences. The number of superior alleles associated with TBW resistance for each accession ranged from 4 to 24; eight accessions had more than 18 superior alleles. Based on TBW-resistant alleles, the five best cross combinations were predicted, including MC133 × Ruyuan No. 1 and CO258 × ROX28. We identified 52 candidate genes around 38 QTNs related to TBW resistance based on homologous functional annotation and KEGG enrichment analysis, e.g., CYCD3;2, BSK1, Nitab4.5_0000641g0050, Nitab4.5_0000929g0030. To the best of our knowledge, this is the first comprehensive study to identify QTNs, superior alleles, and their candidate genes for breeding TBW-resistant tobacco varieties. The results provide further insight into the genetic architecture, marker-assisted selection, and functional genomics of TBW resistance, improving future breeding efforts to increase crop productivity.

Recent Advances in Molecular Marker-Assisted Breeding for Quality Improvement of Traditional Chinese Medicine

BACKGROUND

The quality of Traditional Chinese Medicine (TCM), reflected by its bioactive compounds and associated contents, is directly linked to its clinical efficacy. Therefore, it is of great importance to improve the quality of TCM by increasing the bioactive compound content.

METHODS

Mapping the active component content-associated QTLs in TCM and further markerassisted breeding has enabled us to rapidly and effectively cultivate new varieties with high bioactive compound contents, which has opened the door for genetic breeding studies on medicinal plants.

RESULTS

In this paper, a strategy and technical molecular breeding method for TCM are discussed. The development of four methods and progress in functional marker development, as well as the applications of such markers in TCM, are reviewed.

CONCLUSION

The progress in, challenges of, and future of marker-assisted breeding for quality improvement of TCM are discussed, which provide valuable scientific references for future molecular breeding.

Prospects for Trifolium Improvement Through Germplasm Characterisation and Pre-breeding in New Zealand and Beyond

Trifolium is the most used pastoral legume genus in temperate grassland systems, and a common feature in meadows and open space areas in cities and parks. Breeding of Trifolium spp. for pastoral production has been going on for over a century. However, the breeding targets have changed over the decades in response to different environmental and production pressures. Relatively small gains have been made in Trifolium breeding progress. Trifolium breeding programmes aim to maintain a broad genetic base to maximise variation. New Zealand is a global hub in Trifolium breeding, utilising exotic germplasm imported by the Margot Forde Germplasm Centre. This article describes the history of Trifolium breeding in New Zealand as well as the role and past successes of utilising genebanks in forage breeding. The impact of germplasm characterisation and evaluation in breeding programmes is also discussed. The history and challenges of Trifolium breeding and its effect on genetic gain can be used to inform future pre-breeding decisions in this genus, as well as being a model for other forage legumes.

Genotyping-by-Sequencing-Based Genome-Wide Association Studies of Fusarium Wilt Resistance in Radishes (Raphanus sativus L.)

Fusarium wilt (FW) is a fungal disease that causes severe yield losses in radish production. The most effective method to control the FW is the development and use of resistant varieties in cultivation. The identification of marker loci linked to FW resistance are expected to facilitate the breeding of disease-resistant radishes. In the present study, we applied an integrated framework of genome-wide association studies (GWAS) using genotyping-by-sequencing (GBS) to identify FW resistance loci among a panel of 225 radish accessions, including 58 elite breeding lines. Phenotyping was conducted by manual inoculation of seedlings with the FW pathogen, and scoring for the disease index was conducted three weeks after inoculation during two constitutive years. The GWAS analysis identified 44 single nucleotide polymorphisms (SNPs) and twenty putative candidate genes that were significantly associated with FW resistance. In addition, a total of four QTLs were identified from F2 population derived from a FW resistant line and a susceptible line, one of which was co-located with the SNPs on chromosome 7, detected in GWAS study. These markers will be valuable for molecular breeding programs and marker-assisted selection to develop FW resistant varieties of R. sativus.

Identification of Genetic Loci Associated With Crude Protein Content and Fiber Composition in Alfalfa (Medicago sativa L.) Using QTL Mapping

Forage quality determined mainly by protein content and fiber composition has a crucial influence on digestibility and nutrition intake for animal feeding. To explore the genetic basis of quality traits, we conducted QTL mapping based on the phenotypic data of crude protein (CP), neutral detergent fiber (NDF), acid detergent fiber (ADF), and lignin of an F1 alfalfa population generated by crossing of two alfalfa parents with significant difference in quality. In total, 83 QTLs were identified with contribution to the phenotypic variation (PVE) ranging from 1.45 to 14.35%. Among them, 47 QTLs interacted significantly with environment and 12 QTLs were associated with more than one trait. Epistatic effect was also detected for 73 pairs of QTLs with PVE of 1.08-14.06%. The results suggested that the inheritance of quality-related traits was jointly affected by additive, epistasis and environment. In addition, 83.33% of the co-localized QTLs were shared by ADF and NDF with the same genetic direction, while the additive effect of crude protein-associated QTLs was opposite to that fiber composition on the same locus, suggesting that the loci may antagonistically contribute to protein content and fiber composition. Further analysis of a QTL related to all the three traits of fiber composition (qNDF1C, qADF1C-2, and qlignin1C-2) showed that five candidate genes were homologs of cellulose synthase-like protein A1 in Medicago truncatula, indicating the potential role in fiber synthesis. For the protein-associated loci we identified, qCP4C-1 was located in the shortest region (chr 4.3 39.3-39.4 Mb), and two of the seven corresponding genes in this region were predicted to be E3 ubiquitin-protein ligase in protein metabolism. Therefore, our results provide some reliable regions significantly associated with alfalfa quality, and identification of the key genes would facilitate marker-assisted selection for favorable alleles in breeding program of alfalfa quality improvement.

Genome-Wide Association Studies Identifying Multiple Loci Associated With Alfalfa Forage Quality

Autotetraploid alfalfa is a major hay crop planted all over the world due to its adaptation in different environments and high quality for animal feed. However, the genetic basis of alfalfa quality is not fully understood. In this study, a diverse panel of 200 alfalfa accessions were planted in field trials using augmented experimental design at three locations in 2018 and 2019. Thirty-four quality traits were evaluated by Near Infrared Reflectance Spectroscopy (NIRS). The plants were genotyped using a genotyping by sequencing (GBS) approach and over 46,000 single nucleotide polymorphisms (SNPs) were obtained after variant calling and filtering. Genome-wide association studies (GWAS) identified 28 SNP markers associated with 16 quality traits. Among them, most of the markers were associated with fiber digestibility and protein content. Phenotypic variations were analyzed from three locations and different sets of markers were identified by GWAS when using phenotypic data from different locations, indicating that alfalfa quality traits were also affected by environmental factors. Among different sets of markers identified by location, two markers were associated with nine traits of fiber digestibility. One marker associated with lignin content was identified consistently in multiple environments. Putative candidate genes underlying fiber-related loci were identified and they are involved in the lignin and cell wall biosynthesis. The DNA markers and associated genes identified in this study will be useful for the genetic improvement of forage quality in alfalfa after the validation of the markers.

Phenomics-Assisted Selection for Herbage Accumulation in Alfalfa (Medicago sativa L.)

The application of remote sensing in plant breeding is becoming a routine method for fast and non-destructive high-throughput phenotyping (HTP) using unmanned aerial vehicles (UAVs) equipped with sensors. Alfalfa (Medicago sativa L.) is a perennial forage legume grown in more than 30 million hectares worldwide. Breeding alfalfa for herbage accumulation (HA) requires frequent and multiple phenotyping efforts, which is laborious and costly. The objective of this study was to assess the efficiency of UAV-based imagery and spatial analysis in the selection of alfalfa for HA. The alfalfa breeding population was composed of 145 full-sib and 34 half-sib families, and the experimental design was a row-column with augmented representation of controls. The experiment was established in November 2017, and HA was harvested four times between August 2018 and January 2019. A UAV equipped with a multispectral camera was used for HTP before each harvest. Four vegetation indices (VIs) were calculated from the UAV-based images: NDVI, NDRE, GNDVI, and GRVI. All VIs showed a high correlation with HA, and VIs predicted HA with moderate accuracy. HA and NDVI were used for further analyses to calculate the genetic parameters using linear mixed models. The spatial analysis had a significant effect in both dimensions (rows and columns) for HA and NDVI, resulting in improvements in the estimation of genetic parameters. Univariate models for NDVI and HA, and bivariate models, were fit to predict family performance for scenarios with various levels of HA data (simulated in silico by assigning missing values to full dataset). The bivariate models provided higher correlation among predicted values, higher coincidence for selection, and higher genetic gain even for scenarios with only 30% of HA data. Hence, HTP is a reliable and efficient method to aid alfalfa phenotyping to improve HA. Additionally, the use of spatial analysis can also improve the accuracy of selection in breeding trials.

Geographic population genetic structure and diversity of Sophora moorcroftiana based on genotyping-by-sequencing (GBS)

Sophora moorcroftiana is a perennial leguminous low shrub endemic to the Yarlung Zangbo River basin in Tibet with irreplaceable economic and ecological value. To determine the drivers of evolution in this species, 225 individuals belonging to 15 populations from different geographic locations were sampled, and population genetics was studied using high-throughput genotyping-by-sequencing (GBS). Based on genetic diversity analysis, phylogenetic analysis, principal component analysis, and structure analysis, 15 natural populations were clustered into the following five subgroups: subgroup I (Shigatse subgroup) was located in the upper reaches of the Yarlung Zangbo River with a relatively high level of population genetic variation (means for PIC, Shannon and PI were 0.173, 0.326 and 0.0000305, respectively), and gene flow within the subgroup was also high (mean value for Nm was 4.67). Subgroup II (including Pop 7 and Pop 8; means for PIC, Shannon and PI were 0.182, 0.345 and 0.0000321, respectively), located in the middle reaches of the Yarlung Zangbo River had relatively high levels of gene flow with the populations distributed in the upper and lower reaches. The Nm between subgroup II with subgroups I and III was 3.271 and 2.894, respectively. Considering all the genetic diversity indices Pop 8 had relatively high genetic diversity. Subgroup III (the remaining mixed subgroup of Lhasa and Shannan) was located in the middle reaches of the Yarlung Zangbo River and the means for PIC, Shannon and PI were 0.172, 0.324 and 0.0000303, respectively. Subgroup IV (Nyingchi subgroup), located in the lower reaches of the Yarlung Zangbo River basin, showed a further genetic distance from the other subgroups and the means for PIC, Shannon and PI were 0.147, 0.277 and 0.0000263, respectively. Subgroup V (Nyingchi Gongbu Jiangda subgroup), located in the upper reaches of the Niyang River, had the lowest level of genetic variation (means for PIC, Shannon and PI were 0.106, 0.198 and 0.0000187, respectively) and gene flow with other populations (mean value for Nm was 0.42). According to the comprehensive analysis, the S. moorcroftiana populations generally expanded from upstream to downstream and displayed a high level of genetic differentiation in the populations in the upper and lower reaches. There were high levels of gene exchange between the central populations with upstream and downstream populations, and wind-induced seed dispersal was an important factor in the formation of this gene exchange mode.

Identification of genetic loci associated with forage quality in response to water deficit in autotetraploid alfalfa (Medicago sativa L.)

BACKGROUND

Alfalfa has been cultivated in many regions around the world as an important forage crop due to its nutritive value to livestock and ability to adapt to various environments. However, the genetic basis by which plasticity of quality-relevant traits influence alfalfa adaption to different water conditions remain largely unknown.

RESULTS

In the present study, 198 accessions of alfalfa of the core collection for drought tolerance were evaluated for 26 forage quality traits in a field trial under an imposed deficit irrigation gradient. Regression analysis between quality traits and water stress revealed that values of fiber-related traits were negatively correlated with values of energy-related traits as water deficit increased. More than one hundred significant markers associated with forage quality under different water treatments were identified using genome-wide association studies with genotyping by sequencing. Among them, 131 markers associated with multiple traits in all the water deficit treatments. Most of the associated markers were dependent to the levels of water deficit, suggesting genetic controls for forage quality traits were dependent to the stress treatment. Twenty-four loci associated with forage quality were annotated to functional genes that may play roles in cell development or in response to water stress.

CONCLUSIONS

This study addressed the genetic base of phenotypic variation of forage quality traits under water deficit. The SNP markers identified in this study will be useful in marker-assisted selection for the genetic improvement of alfalfa with enhanced drought tolerance while maintaining forage quality.

Biotechnological Perspectives of Omics and Genetic Engineering Methods in Alfalfa

For several decades, researchers are working to develop improved major crops with better adaptability and tolerance to environmental stresses. Forage legumes have been widely spread in the world due to their great ecological and economic values. Abiotic and biotic stresses are main factors limiting legume production, however, alfalfa (Medicago sativa L.) shows relatively high level of tolerance to drought and salt stress. Efforts focused on alfalfa improvements have led to the release of cultivars with new traits of agronomic importance such as high yield, better stress tolerance or forage quality. Alfalfa has very high nutritional value due to its efficient symbiotic association with nitrogen-fixing bacteria, while deep root system can help to prevent soil water loss in dry lands. The use of modern biotechnology tools is challenging in alfalfa since full genome, unlike to its close relative barrel medic (Medicago truncatula Gaertn.), was not released yet. Identification, isolation, and improvement of genes involved in abiotic or biotic stress response significantly contributed to the progress of our understanding how crop plants cope with these environmental challenges. In this review, we provide an overview of the progress that has been made in high-throughput sequencing, characterization of genes for abiotic or biotic stress tolerance, gene editing, as well as proteomic and metabolomics techniques bearing biotechnological potential for alfalfa improvement.

Genome-Wide Correlation of 36 Agronomic Traits in the 287 Pepper (Capsicum) Accessions Obtained from the SLAF-seq-Based GWAS

There are many agronomic traits of pepper (Capsicum L.) with abundant phenotypes that can benefit pepper growth. Using specific-locus amplified fragment sequencing (SLAF-seq), a genome-wide association study (GWAS) of 36 agronomic traits was carried out for 287 representative pepper accessions. To ensure the accuracy and reliability of the GWAS results, we analyzed the genetic diversity, distribution of labels (SLAF tags and single nucleotide polymorphisms (SNPs)) and population differentiation and determined the optimal statistical model. In our study, 1487 SNPs were highly significantly associated with 26 agronomic traits, and 2126 candidate genes were detected in the 100-kb region up- and down-stream near these SNPs. Furthermore, 13 major association peaks were identified for 11 key agronomic traits. Then we examined the correlations among the 36 agronomic traits and analyzed SNP distribution and found 37 SNP polymerization regions (total size: 264.69 Mbp) that could be selected areas in pepper breeding. We found that the stronger the correlation between the two traits, the greater the possibility of them being in more than one polymerization region, suggesting that they may be linked or that one pleiotropic gene controls them. These results provide a theoretical foundation for future multi-trait pyramid breeding of pepper. Finally, we found that the GWAS signals were highly consistent with those from the nuclear restorer-of-fertility (Rf) gene for cytoplasmic male sterility (CMS), verifying their reliability. We further identified Capana06g002967 and Capana06g002969 as Rf candidate genes by functional annotation and expression analysis, which provided a reference for the study of cytoplasmic male sterility in Capsicum.

Correlative evidence for co-regulation of phosphorus and carbon exchanges with symbiotic fungus in the arbuscular mycorrhizal Medicago truncatula

Research efforts directed to elucidation of mechanisms behind trading of resources between the partners in the arbuscular mycorrhizal (AM) symbiosis have seen a considerable progress in the recent years. Yet, despite of the recent developments, some key questions still remain unanswered. For example, it is well established that the strictly biotrophic AM fungus releases phosphorus to- and receives carbon molecules from the plant symbiont, but the particular genes, and their products, responsible for facilitating this exchange, are still not fully described, nor are the principles and pathways of their regulation. Here, we made a de novo quest for genes involved in carbon transfer from the plant to the fungus using genome-wide gene expression array targeting whole root and whole shoot gene expression profiles of mycorrhizal and non-mycorrhizal Medicago truncatula plants grown in a glasshouse. Using physiological intervention of heavy shading (90% incoming light removed) and the correlation of expression levels of MtPT4, the mycorrhiza-inducible phosphate transporter operating at the symbiotic interface between the root cortical cells and the AM fungus, and our candidate genes, we demonstrate that several novel genes may be involved in resource tradings in the AM symbiosis established by M. truncatula. These include glucose-6-phosphate/phosphate translocator, polyol/monosaccharide transporter, DUR3-like, nucleotide-diphospho-sugar transferase or a putative membrane transporter. Besides, we also examined the expression of other M. truncatula phosphate transporters (MtPT1-3, MtPT5-6) to gain further insights in the balance between the "direct" and the "mycorrhizal" phosphate uptake pathways upon colonization of roots by the AM fungus, as affected by short-term carbon/energy deprivation. In addition, the role of the novel candidate genes in plant cell metabolism is discussed based on available literature.

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).

Genome-wide association study of berry-related traits in grape [Vitis vinifera L.] based on genotyping-by-sequencing markers

Deciphering the genetic control of grape berry traits is crucial for optimizing yield, fruit quality, and consumer acceptability. In this study, an association panel of 179 grape genotypes comprising a mixture of ancient cultivars, landraces, and modern varieties collected worldwide were genotyped with genotyping-by-sequencing using a genome-wide association approach based on 32,311 single-nucleotide polymorphism (SNP) markers. Genome-wide efficient mixed-model association was selected as the optimal statistical model based on the results of known control loci of grape berry color traits. Many of the associated SNPs identified in this study were in accordance with the previous QTL analyses using biparental mapping. The grape skin color locus was found to be associated with a mybA transcription factor on chromosome 2. Two strong and distinct association signals associated with berry development periods were found on chromosome 16. Most candidate genes of the interval were highlighted as receptor-like protein kinase. For berry weight, significant association loci were identified on chromosome 18, as previously known, and on chromosome 19 and chromosome 17, as newly mapped. Berry flesh texture was newly located on chromosome 16; candidate genes in the interval were related to calcium. Berry flavor was determined on chromosome 5. Genomic regions were further investigated to reveal candidate genes. In this work, we identified interesting genetic determinants of grape berry-related traits. The identification of the markers closely associated with these berry traits may be useful for grape molecular breeding.

Understanding the Complexity of Cold Tolerance in White Clover using Temperature Gradient Locations and a GWAS Approach

White clover ( L.) is the most important grazing perennial forage legume in temperate climates. However, its limited capacity to survive and restore growth after low temperatures during winter constrains the productivity and wide adoption of the crop. Despite the importance of cold tolerance for white clover cultivar development, the genetic basis of this trait remains largely unknown. Hence, in this study, we performed the first genome-wide association study (GWAS) analyses in white clover to identify quantitative trait loci (QTL) for cold-tolerance-related traits. Seeds from 192 divergent genotypes from six populations in the Patagonia region of South America were collected and seed-derived plants were further clonally propagated. Clonal trials were established in three locations representing temperature gradient associated with elevation. Given the allotetraploid nature of the white clover genome, distinct genetic models (diploid and tetraploid) were tested. Only the tetraploid parameterization was able to detect the 53 loci associated with cold-tolerance traits. Out of the 53 single nucleotide polymorphism (SNP) trait associations, 17 controlled more than one trait or were stable across multiple sites. This work represents the first report of QTL for cold-tolerance-related traits, providing insights into its genetic basis and candidate genomic regions for further functional validation studies.

Harnessing the Potential of Forage Legumes, Alfalfa, Soybean, and Cowpea for Sustainable Agriculture and Global Food Security

Substantial improvements in access to food and increased purchasing power are driving many people toward consuming nutrition-rich foods causing an unprecedented demand for protein food worldwide, which is expected to rise further. Forage legumes form an important source of feed for livestock and have potential to provide a sustainable solution for food and protein security. Currently, alfalfa is a commercially grown source of forage and feed in many countries. However, soybean and cowpea also have the potential to provide quality forage and fodder for animal use. The cultivation of forage legumes is under threat from changing climatic conditions, indicating the need for breeding cultivars that can sustain and acclimatize to the negative effects of climate change. Recent progress in genetic and genomic tools have facilitated the identification of quantitative trait loci and genes/alleles that can aid in developing forage cultivars through genomics-assisted breeding. Furthermore, transgenic technology can be utilized to manipulate the genetic makeup of plants to improve forage digestibility for better animal performance. In this article, we assess the genetic potential of three important legume crops, alfalfa, soybean, and cowpea in supplying quality fodder and feed for livestock. In addition, we examine the impact of climate change on forage quality and discuss efforts made in enhancing the adaptation of the plant to the abiotic stress conditions. Subsequently, we suggest the application of integrative approaches to achieve adequate forage production amid the unpredictable climatic conditions.

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.

QTL mapping and GWAS reveal candidate genes controlling capsaicinoid content in Capsicum

Capsaicinoids are unique compounds produced only in peppers (Capsicum spp.). Several studies using classical quantitative trait loci (QTLs) mapping and genomewide association studies (GWAS) have identified QTLs controlling capsaicinoid content in peppers; however, neither the QTLs common to each population nor the candidate genes underlying them have been identified due to the limitations of each approach used. Here, we performed QTL mapping and GWAS for capsaicinoid content in peppers using two recombinant inbred line (RIL) populations and one GWAS population. Whole-genome resequencing and genotyping by sequencing (GBS) were used to construct high-density single nucleotide polymorphism (SNP) maps. Five QTL regions on chromosomes 1, 2, 3, 4 and 10 were commonly identified in both RIL populations over multiple locations and years. Furthermore, a total of 109 610 SNPs derived from two GBS libraries were used to analyse the GWAS population consisting of 208 C. annuum-clade accessions. A total of 69 QTL regions were identified from the GWAS, 10 of which were co-located with the QTLs identified from the two biparental populations. Within these regions, we were able to identify five candidate genes known to be involved in capsaicinoid biosynthesis. Our results demonstrate that QTL mapping and GBS-GWAS represent a powerful combined approach for the identification of loci controlling complex traits.

Novel and major QTL for branch angle detected by using DH population from an exotic introgression in rapeseed (Brassica napus L.)

A high-density SNP map was constructed and several novel QTL for branch angle across six environments in Brassica napus were identified. Branch angle is a major determinant for the ideotype of a plant, while the mechanisms underlying this trait in Brassica napus remain elusive. Herein, we developed one doubled haploid population from a cross involving one Capsella bursa-pastoris derived B. napus intertribal introgression line with the compressed branches and wooden stems, and constructed a high-density SNP map covering the genetic distance of 2242.14 cM, with an average marker interval of 0.73 cM. After phenotypic measurements across six environments, the inclusive composite interval mapping algorithm was conducted to analyze the QTL associated with branch angle. In single-environment analysis, a total of 17 QTL were detected and mainly distributed on chromosomes A01, A03, A09 and C03. Of these, three major QTL, qBA.A03-2, qBA.C03-3 and qBA.C03-4 were steadily expressed, each explaining more than 10% of the phenotypic variation in at least two environments. Compared with other results on rapeseed branch angle, these major QTL were newly detected. In QTL by environment interactions (QEI) mapping, 10 QTL were identified, and the QTL average effect and QEI effect were estimated. Of these, 7 QTL were detected in both single-environment analysis and QEI mapping. Based on the physical positions of SNPs and the functional annotation of the Arabidopsis thaliana genome, 27 genes within the QTL regions were selected as candidate genes, including early auxin-responsive genes, small auxin-up RNA, auxin/indoleacetic acid and gretchenhagen-3. These results may pave the way for deciphering the genetic control of branch angle in B. napus.

Identification of genetic loci associated with crude protein and mineral concentrations in alfalfa (Medicago sativa) using association mapping

BACKGROUND

Alfalfa (Medicago sativa) is one of the most important legume forage species in China and many other countries of the world. It provides a quality source of proteins and minerals to animals. Genetic underpinnings for these important traits, however, are elusive. An alfalfa (M. sativa) association mapping study for six traits, namely crude protein (CP), rumen undegraded protein (RUP), and four mineral elements (Ca, K, Mg and P), was conducted in three consecutive years using a large collection encompassing 336 genotypes genotyped with 85 simple sequence repeat (SSR) markers.

RESULTS

All the traits were significantly influenced by genotype, environment, and genotype × environment interaction. Eight-five significant associations (P < 0.005) were identified. Among these, five associations with Ca were repeatedly observed and six co-localized associations were identified.

CONCLUSIONS

The identified marker alleles significantly associated with the traits provided important information for understanding genetic controls of alfalfa quality. The markers could be used in assisting selection for the individual traits in breeding populations for developing new alfalfa cultivars.

Genotyping-by-Sequencing and Its Exploitation for Forage and Cool-Season Grain Legume Breeding

Genotyping-by-Sequencing (GBS) may drastically reduce genotyping costs compared with single nucleotide polymorphism (SNP) array platforms. However, it may require optimization for specific crops to maximize the number of available markers. Exploiting GBS-generated markers may require optimization, too (e.g., to cope with missing data). This study aimed (i) to compare elements of GBS protocols on legume species that differ for genome size, ploidy, and breeding system, and (ii) to show successful applications and challenges of GBS data on legume species. Preliminary work on alfalfa and Medicago truncatula suggested the greater interest of ApeKI over PstI:MspI DNA digestion. We compared KAPA and NEB Taq polymerases in combination with primer extensions that were progressively more selective on restriction sites, and found greater number of polymorphic SNP loci in pea, white lupin and diploid alfalfa when adopting KAPA with a non-selective primer. This protocol displayed a slight advantage also for tetraploid alfalfa (where SNP calling requires higher read depth). KAPA offered the further advantage of more uniform amplification than NEB over fragment sizes and GC contents. The number of GBS-generated polymorphic markers exceeded 6,500 in two tetraploid alfalfa reference populations and a world collection of lupin genotypes, and 2,000 in different sets of pea or lupin recombinant inbred lines. The predictive ability of GBS-based genomic selection was influenced by the genotype missing data threshold and imputation, as well as by the genomic selection model, with the best model depending on traits and data sets. We devised a simple method for comparing phenotypic vs. genomic selection in terms of predicted yield gain per year for same evaluation costs, whose application to preliminary data for alfalfa and pea in a hypothetical selection scenario for each crop indicated a distinct advantage of genomic selection.

Genome-Wide Association Mapping and Genomic Selection for Alfalfa (Medicago sativa) Forage Quality Traits

Genetic progress for forage quality has been poor in alfalfa (Medicago sativa L.), the most-grown forage legume worldwide. This study aimed at exploring opportunities for marker-assisted selection (MAS) and genomic selection of forage quality traits based on breeding values of parent plants. Some 154 genotypes from a broadly-based reference population were genotyped by genotyping-by-sequencing (GBS), and phenotyped for leaf-to-stem ratio, leaf and stem contents of protein, neutral detergent fiber (NDF) and acid detergent lignin (ADL), and leaf and stem NDF digestibility after 24 hours (NDFD), of their dense-planted half-sib progenies in three growing conditions (summer harvest, full irrigation; summer harvest, suspended irrigation; autumn harvest). Trait-marker analyses were performed on progeny values averaged over conditions, owing to modest germplasm × condition interaction. Genomic selection exploited 11,450 polymorphic SNP markers, whereas a subset of 8,494 M. truncatula-aligned markers were used for a genome-wide association study (GWAS). GWAS confirmed the polygenic control of quality traits and, in agreement with phenotypic correlations, indicated substantially different genetic control of a given trait in stems and leaves. It detected several SNPs in different annotated genes that were highly linked to stem protein content. Also, it identified a small genomic region on chromosome 8 with high concentration of annotated genes associated with leaf ADL, including one gene probably involved in the lignin pathway. Three genomic selection models, i.e., Ridge-regression BLUP, Bayes B and Bayesian Lasso, displayed similar prediction accuracy, whereas SVR-lin was less accurate. Accuracy values were moderate (0.3-0.4) for stem NDFD and leaf protein content, modest for leaf ADL and NDFD, and low to very low for the other traits. Along with previous results for the same germplasm set, this study indicates that GBS data can be exploited to improve both quality traits (by genomic selection or MAS) and forage yield.