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

Medicago2035: Genomes, functional genomics, and molecular breeding

Medicago, a genus in the Leguminosae or Fabaceae family, includes the most globally significant forage crops, notably alfalfa (Medicago sativa). Its close diploid relative Medicago truncatula serves as an exemplary model plant for investigating legume growth and development, as well as symbiosis with rhizobia. Over the past decade, advances in Medicago genomics have significantly deepened our understanding of the molecular regulatory mechanisms that underlie various traits. In this review, we comprehensively summarize research progress on Medicago genomics, growth and development (including compound leaf development, shoot branching, flowering time regulation, inflorescence development, floral organ development, and seed dormancy), resistance to abiotic and biotic stresses, and symbiotic nitrogen fixation with rhizobia, as well as molecular breeding. We propose avenues for molecular biology research on Medicago in the coming decade, highlighting those areas that have yet to be investigated or that remain ambiguous.

GWAS for Drought Resilience Traits in Red Clover (Trifolium pratense L.)

Red clover (Trifolium pratense L.) is a well-appreciated grassland crop in temperate climates but suffers from increasingly frequent and severe drought periods. Molecular markers for drought resilience (DR) would benefit breeding initiatives for red clover, as would a better understanding of the genes involved in DR. Two previous studies, as follows, have: (1) identified phenotypic DR traits in a diverse set of red clover accessions; and (2) produced genotypic data using a pooled genotyping-by-sequencing (GBS) approach in the same collection. In the present study, we performed genome-wide association studies (GWAS) for DR using the available phenotypic and genotypic data. Single nucleotide polymorphism (SNP) calling was performed using GBS data and the following two red clover genome assemblies: the recent HEN-17 assembly and the Milvus assembly. SNP positions with significant associations were used to delineate flanking regions in both genome assemblies, while functional annotations were retrieved from Medicago truncatula orthologs. GWAS revealed 19 significant SNPs in the HEN-17-derived SNP set, explaining between 5.3 and 23.2% of the phenotypic variation per SNP-trait combination for DR traits. Among the genes in the SNP-flanking regions, we identified candidate genes related to cell wall structuring, genes encoding sugar-modifying proteins, an ureide permease gene, and other genes linked to stress metabolism pathways. GWAS revealed 29 SNPs in the Milvus-derived SNP set that explained substantially more phenotypic variation for DR traits, between 5.3 and 42.3% per SNP-trait combination. Candidate genes included a DEAD-box ATP-dependent RNA helicase gene, a P-loop nucleoside triphosphate hydrolase gene, a Myb/SANT-like DNA-binding domain protein, and an ubiquitin-protein ligase gene. Most accessions in this study are genetically more closely related to the Milvus genotype than to HEN-17, possibly explaining how the Milvus-derived SNP set yielded more robust associations. The Milvus-derived SNP set pinpointed 10 genomic regions that explained more than 25% of the phenotypic variation for DR traits. A possible next step could be the implementation of these SNP markers in practical breeding programs, which would help to improve DR in red clover. Candidate genes could be further characterized in future research to unravel drought stress resilience in red clover in more detail.

An alfalfa MYB-like transcriptional factor MsMYBH positively regulates alfalfa seedling drought resistance and undergoes MsWAV3-mediated degradation

Drought is a major threat to alfalfa (Medicago sativa L.) production. The discovery of important alfalfa genes regulating drought response will facilitate breeding for drought-resistant alfalfa cultivars. Here, we report a genome-wide association study of drought resistance in alfalfa. We identified and functionally characterized an MYB-like transcription factor gene (MsMYBH), which increases the drought resistance in alfalfa. Compared with the wild-types, the biomass and forage quality were enhanced in MsMYBH overexpressed plants. Combined RNA-seq, proteomics and chromatin immunoprecipitation analysis showed that MsMYBH can directly bind to the promoters of MsMCP1, MsMCP2, MsPRX1A and MsCARCAB to improve their expression. The outcomes of such interactions include better water balance, high photosynthetic efficiency and scavenge excess H2O2 in response to drought. Furthermore, an E3 ubiquitin ligase (MsWAV3) was found to induce MsMYBH degradation under long-term drought, via the 26S proteasome pathway. Furthermore, variable-number tandem repeats in MsMYBH promoter were characterized among a collection of germplasms, and the variation is associated with promoter activity. Collectively, our findings shed light on the functions of MsMYBH and provide a pivotal gene that could be leveraged for breeding drought-resistant alfalfa. This discovery also offers new insights into the mechanisms of drought resistance in alfalfa.

Alfalfa vein mottling virus, a novel potyvirid infecting Medicago sativa L

BACKGROUND

We have recently identified a novel virus detected in alfalfa seed material. The virus was tentatively named alfalfa-associated potyvirus 1, as its genomic fragments bore similarities with potyvirids. In this study, we continued investigating this novel species, expanding information on its genomic features and biological characteristics.

METHODS

This research used a wide range of methodology to achieve end results: high throughput sequencing, bioinformatics tools, reverse transcription-polymerase chain reactions, differential diagnostics using indicator plants, virus purification, transmission electron microscopy, and others.

RESULTS

In this study, we obtained a complete genome sequence of the virus and classified it as a tentative species in the new genus, most closely related to the members of the genus Ipomovirus in the family Potyviridae. This assumption is based on the genome sequence and structure, phylogenetic relationships, and transmission electron microscopy investigations. We also demonstrated its mechanical transmission to the indicator plant Nicotiana benthamiana and to the natural host Medicago sativa, both of which developed characteristic symptoms therefore suggesting a pathogenic nature of the disease.

CONCLUSIONS

Consistent with symptomatology, the virus was renamed to alfalfa vein mottling virus. A name Alvemovirus was proposed for the new genus in the family Potyviridae, of which alfalfa vein mottling virus is a tentative member.

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.

Transcriptome and GWAS Analyses Reveal Candidate Gene for Root Traits of Alfalfa during Germination under Salt Stress

Alfalfa growth and production in China are negatively impacted by high salt concentrations in soils, especially in regions with limited water supplies. Few reliable genetic markers are currently available for salt tolerance selection. As a result, molecular breeding strategies targeting alfalfa are hindered. Therefore, with the continuous increase in soil salinity in agricultural lands, it is indispensable that a salt-tolerant variety of alfalfa is produced. We collected 220 alfalfa varieties around the world for resequencing and performed genome-wide association studies (GWASs). Alfalfa seeds were germinated in saline water with different concentrations of NaCl, and the phenotypic differences in several key root traits were recorded. In the phenotypic analysis, the breeding status and geographical origin strongly affected the salt tolerance of alfalfa. Forty-nine markers were significantly associated with salt tolerance, and 103 candidate genes were identified based on linkage disequilibrium. A total of 2712 differentially expressed genes were upregulated and 3570 were downregulated based on transcriptomic analyses. Some candidate genes that affected root development in the seed germination stage were identified through the combination of GWASs and transcriptome analyses. These genes could be used for molecular breeding strategies to increase alfalfa’s salt tolerance and for further research on salt tolerance in general.

Forage quality and physiological performance of mowed alfalfa (Medicago sativa L.) subjected to combined light quality and drought

Alfalfa (Medicago sativa) can dwell in water-deficient habitats, where it is difficult to predict dry mass (DM) production and forage quality due to understory transmittance. Mowing is a recommended practice for alfalfa populations under drought, but its effect on forested land receives less attention. In a controlled indoor experiment, we found that drought better reduces shoot DM weight and crude fiber content (CFi) in blue light (33.7% red, 48.5% green, and 17.8% blue lights) than red light (71.7% red, 13.7% green, and 14.6% blue lights). Mowing decreases carbon (C) isotope signature (δ¹³C), CFi, and total C content in shoots but increases their accumulations in DM, nonstructural carbohydrates, and crude fat content (CFa). The results also demonstrated that mown alfalfa has higher starch content when exposed to green light (26.2% red, 56.4% green, and 17.4% blue lights) compared to the other two spectra. Multiple factorial regression indicated that higher soluble sugar content accounted for the increase of CFa and DM weight for CFi. Overall, mowing in blue-light-enriched understory stands is recommended and produces high-forage-quality alfalfa, which can be used as a lowered crude fiber component.

Identification of QTL and candidate genes associated with biomass yield and Feed Quality in response to water deficit in alfalfa (Medicago sativa L.) using linkage mapping and RNA-Seq

Biomass yield and Feed Quality are the most important traits in alfalfa (Medicago sativa L.), which directly affect its economic value. Drought stress is one of the main limiting factors affecting alfalfa production worldwide. However, the genetic and especially the molecular mechanisms for drought tolerance in alfalfa are poorly understood. In this study, linkage mapping was performed in an F1 population by combining 12 phenotypic data (biomass yield, plant height, and 10 Feed Quality-related traits). A total of 48 significant QTLs were identified on the high-density genetic linkage maps that were constructed in our previous study. Among them, nine main QTLs, which explained more than 10% phenotypic variance, were detected for biomass yield (one), plant height (one), CP (two), ASH (one), P (two), K(one), and Mg (one). A total of 31 candidate genes were identified in the nine main QTL intervals based on the RNA-seq analysis under the drought condition. Blast-P was further performed to screen candidate genes controlling drought tolerance, and 22 functional protein candidates were finally identified. The results of the present study will be useful for improving drought tolerance of alfalfa varieties by marker-assisted selection (MAS), and provide promising candidates for further gene cloning and mechanism study.

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.

A Genome-Wide Association Study Coupled With a Transcriptomic Analysis Reveals the Genetic Loci and Candidate Genes Governing the Flowering Time in Alfalfa (Medicago sativa L.)

The transition to flowering at the right time is very important for adapting to local conditions and maximizing alfalfa yield. However, the understanding of the genetic basis of the alfalfa flowering time remains limited. There are few reliable genes or markers for selection, which hinders progress in genetic research and molecular breeding of this trait in alfalfa. We sequenced 220 alfalfa cultivars and conducted a genome-wide association study (GWAS) involving 875,023 single-nucleotide polymorphisms (SNPs). The phenotypic analysis showed that the breeding status and geographical origin strongly influenced the alfalfa flowering time. Our GWAS revealed 63 loci significantly related to the flowering time. Ninety-five candidate genes were detected at these SNP loci within 40 kb (20 kb up- and downstream). Thirty-six percent of the candidate genes are involved in development and pollen tube growth, indicating that these genes are key genetic mechanisms of alfalfa growth and development. The transcriptomic analysis showed that 1,924, 2,405, and 3,779 differentially expressed genes (DEGs) were upregulated across the three growth stages, while 1,651, 2,613, and 4,730 DEGs were downregulated across the stages. Combining the results of our GWAS and transcriptome analysis, in total, 38 candidate genes (7 differentially expressed during the bud stage, 13 differentially expressed during the initial flowering stage, and 18 differentially expressed during the full flowering stage) were identified. Two SNPs located in the upstream region of the Msa0888690 gene (which is involved in isop renoids) were significantly related to flowering. The two significant SNPs within the upstream region of Msa0888690 existed as four different haplotypes in this panel. The genes identified in this study represent a series of candidate targets for further research investigating the alfalfa flowering time and could be used for alfalfa molecular breeding.

Genome-Wide Analysis and Profile of UDP-Glycosyltransferases Family in Alfalfa (Medicago sativa L.) under Drought Stress

Drought stress is one of the major constraints that decreases global crop productivity. Alfalfa, planted mainly in arid and semi-arid areas, is of crucial importance in sustaining the agricultural system. The family 1 UDP-glycosyltransferases (UGT) is indispensable because it takes part in the regulation of plant growth and stress resistance. However, a comprehensive insight into the participation of the UGT family in adaptation of alfalfa to drought environments is lacking. In the present study, a genome-wide analysis and profiling of the UGT in alfalfa were carried out. A total of 409 UGT genes in alfalfa (MsUGT) were identified and they are clustered into 13 groups. The expression pattern of MsUGT genes were analyzed by RNA-seq data in six tissues and under different stresses. The quantitative real-time PCR verification genes suggested the distinct role of the MsUGT genes under different drought stresses and abscisic acid (ABA) treatment. Furthermore, the function of MsUGT003 and MsUGT024, which were upregulated under drought stress and ABA treatment, were characterized by heterologous expression in yeast. Taken together, this study comprehensively analyzed the UGT gene family in alfalfa for the first time and provided useful information for improving drought tolerance and in molecular breeding of alfalfa.

Ascorbic acid regulates nitrogen, energy, and gas exchange metabolisms of alfalfa in response to high-nitrate stress

The effects of exogenous ascorbic acid (AsA) on the growth parameters, nitrogen metabolism, energy status, and photosynthetic gas exchange in alfalfa under high-nitrate stress were studied. The seedlings treated with the control, 200 mmol L-1 nitrates (HN) or 200 mmol L-1 nitrate + 0.1 mmol L-1 AsA (HN + AsA), were sampled on days 0 and 10 after treatments. AsA was sprayed on the leaves, while HN was conducted by watering. Both of them were performed once every other day for three times in total. The results revealed that in the HN treatment, the growth parameters were the lowest; total phosphorus (TP), nitrogen-related enzyme activities, soluble protein (SP), adenosine triphosphate (ATP), and energy charge (EC) were reduced; and photosynthetic rate (Photo), conductance to H2O (Cond), transpiration rate (Trmmol), instantaneous water use efficiency (WUE), and apparent CO2 use efficiency (CUE) were also inhibited; and total nitrogen (TN), nitrate-nitrogen (NO3¯-N), ammonium-nitrogen (NH4+-N), adenosine diphosphate (ADP), adenosine monophosphate (AMP), and intercellular CO2 concentration (Ci) were increased compared with the control. However, these parameters changed conversely in the HN + AsA treatment. In addition, there was a good curve regression equation relationship between TN and NO3¯-N, TN and NH4+-N, NO3¯-N and NH4+-N, respectively. It indicates that AsA improves the growth parameters, nitrogen-related enzyme activities, energy metabolism, and photosynthesis, whereas it inhibits the toxicity of excess NO3¯-N and NH4+-N accumulations, thereby promoting the growth of alfalfa under high-nitrate stress. These metabolisms are closely related to each other during the regulatory process in alfalfa. Hence, AsA has potential to be applied to improve the growth of alfalfa under high-nitrate stress.

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.

Pan-transcriptome identifying master genes and regulation network in response to drought and salt stresses in Alfalfa (Medicago sativa L.)

Alfalfa is an important legume forage grown worldwide and its productivity is affected by environmental stresses such as drought and high salinity. In this work, three alfalfa germplasms with contrasting tolerances to drought and high salinity were used for unraveling the transcriptomic responses to drought and salt stresses. Twenty-one different RNA samples from different germplasm, stress conditions or tissue sources (leaf, stem and root) were extracted and sequenced using the PacBio (Iso-Seq) and the Illumina platforms to obtain full-length transcriptomic profiles. A total of 1,124,275 and 91,378 unique isoforms and genes were obtained, respectively. Comparative analysis of transcriptomes identified differentially expressed genes and isoforms as well as transcriptional and post-transcriptional modifications such as alternative splicing events, fusion genes and nonsense-mediated mRNA decay events and non-coding RNA such as circRNA and lncRNA. This is the first time to identify the diversity of circRNA and lncRNA in response to drought and high salinity in alfalfa. The analysis of weighted gene co-expression network allowed to identify master genes and isoforms that may play important roles on drought and salt stress tolerance in alfalfa. This work provides insight for understanding the mechanisms by which drought and salt stresses affect alfalfa growth at the whole genome level.

Effects of Melatonin on Morphological Characteristics, Mineral Nutrition, Nitrogen Metabolism, and Energy Status in Alfalfa Under High-Nitrate Stress

Melatonin is an indoleamine small molecular substance that has been shown to play an important role in the growth, development, and stress response of plants. The effects of melatonin on the morphological characteristics, mineral nutrition, nitrogen metabolism, and energy status in alfalfa (Medicago sativa L.) under high-nitrate stress were studied. The alfalfa plants were treated with water (CK), 200 mmol L^-1 nitrates (HN), or 200 mmol L^-1 nitrates + 0.1 mmol L^-1 melatonin (HN+MT), and then were sampled for measurements on days 0 and 10, respectively. The results showed that the HN treatment resulted in a decrease in the morphological characteristics (such as shoot height, leaf length, leaf width, leaf area, and biomass), phosphorus, soluble protein (SP), nitrogen-related enzymes activities and gene relative expression, adenosine triphosphate (ATP), and energy charge (EC). It also caused an increase in nitrogen, sodium, potassium, calcium, nitrate-nitrogen ( NO 3 - -N), ammonium-nitrogen ( NH 4 + -N), adenosine diphosphate (ADP), and adenosine monophosphate (AMP). However, these parameters were conversely changed in the HN+MT treatment. Besides, these parameters were closely related to each other, and were divided into two principal components. It reveals that melatonin plays an important role in modulating the morphology, mineral nutrition, nitrogen metabolism and energy status, thereby alleviating the adverse effects of high-nitrate stress and improving the growth of alfalfa.

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.