Identification of Loci Associated with Drought Resistance Traits in Heterozygous Autotetraploid Alfalfa (Medicago sativa L.) Using Genome-Wide Association Studies with Genotyping by Sequencing

Analyzing Medicago spp. seed morphology using GWAS and machine learning

Alfalfa is widely recognized as an important forage crop. To understand the morphological characteristics and genetic basis of seed morphology in alfalfa, we screened 318 Medicago spp., including 244 Medicago sativa subsp. sativa (alfalfa) and 23 other Medicago spp., for seed area size, length, width, length-to-width ratio, perimeter, circularity, the distance between the intersection of length & width (IS) and center of gravity (CG), and seed darkness & red-green-blue (RGB) intensities. The results revealed phenotypic diversity and correlations among the tested accessions. Based on the phenotypic data of M. sativa subsp. sativa, a genome-wide association study (GWAS) was conducted using single nucleotide polymorphisms (SNPs) called against the Medicago truncatula genome. Genes in proximity to associated markers were detected, including CPR1, MON1, a PPR protein, and Wun1(threshold of 1E-04). Machine learning models were utilized to validate GWAS, and identify additional marker-trait associations for potentially complex traits. Marker S7_33375673, upstream of Wun1, was the most important predictor variable for red color intensity and highly important for brightness. Fifty-two markers were identified in coding regions. Along with strong correlations observed between seed morphology traits, these genes will facilitate the process of understanding the genetic basis of seed morphology in Medicago spp.

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.

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.

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.

Crop Landraces and Indigenous Varieties: A Valuable Source of Genes for Plant Breeding

Landraces and indigenous varieties comprise valuable sources of crop species diversity. Their utilization in plant breeding may lead to increased yield and enhanced quality traits, as well as resilience to various abiotic and biotic stresses. Recently, new approaches based on the rapid advancement of genomic technologies such as deciphering of pangenomes, multi-omics tools, marker-assisted selection (MAS), genome-wide association studies (GWAS), and CRISPR/Cas9 gene editing greatly facilitated the exploitation of landraces in modern plant breeding. In this paper, we present a comprehensive overview of the implementation of new genomic technologies and highlight their importance in pinpointing the genetic basis of desirable traits in landraces and indigenous varieties of annual, perennial herbaceous, and woody crop species cultivated in the Mediterranean region. The need for further employment of advanced -omic technologies to unravel the full potential of landraces and indigenous varieties underutilized genetic diversity is also indicated. Ultimately, the large amount of genomic data emerging from the investigation of landraces and indigenous varieties reveals their potential as a source of valuable genes and traits for breeding. The role of landraces and indigenous varieties in mitigating the ongoing risks posed by climate change in agriculture and food security is also highlighted.

Molecular mechanisms of drought resistance using genome-wide association mapping in maize (Zea mays L.)

BACKGROUND

Drought is a critical abiotic stress that influences maize yield and reduces grain yield when it occurs at the flowering or filling stage. To dissect the genetic architecture of grain yield under drought stress (DS), a genome-wide association analysis was conducted in a maize population composed of diverse inbred lines from five locations under well-watered and DS conditions at flowering in 2019 and 2020.

RESULTS

Using a fixed and random model circulating probability unification model, a total of 147 loci associated with grain yield or the drought resistance index (DRI) were identified, of which 54 loci were associated with a DRI with an average phenotypic variation explanation of 4.03%. Further, 10 of these loci explained more than 10% of the phenotypic variation. By integrating two public transcriptome datasets, 22 differentially expressed genes were considered as candidate genes, including the cloned gene ZmNAC49, which responds to drought by regulating stomatal density. Enrichment and protein interaction network showed that signaling pathways responded to drought resistance, including jasmonic acid and salicylic acid, mitogen-activated protein kinase, and abscisic acid-activated. Additionally, several transcription factors involved in DS were identified, including basic leucine zipper (GRMZM2G370026), NAC (GRMZM2G347043), and ethylene-responsive element binding protein (GRMZM2G169654).

CONCLUSIONS

In this study, we nominated several genes as candidate genes for drought resistance by intergrating association maping and transcription analysis. These results provide valuable information for understanding the genetic basis of drought tolerance at the mature stage and for designing drought-tolerant maize breeding.

Sustainable Innovation: Turning Waste into Soil Additives

In recent years, a dynamic increase in environmental pollution with textile waste has been observed. Natural textile waste has great potential for environmental applications. This work identifies potential ways of sustainably managing natural textile waste, which is problematic waste from sheep farming or the cultivation of fibrous plants. On the basis of textile waste, an innovative technology was developed to support water saving and plant vegetation- biodegradable water-absorbing geocomposites (BioWAGs). The major objective of this study was to determine BioWAG effectiveness under field conditions. The paper analyses the effect of BioWAGs on the increments in fresh and dry matter, the development of the root system, and the relative water content (RWC) of selected grass species. The conducted research confirmed the high efficiency of the developed technology. The BioWAGs increased the fresh mass of grass shoots by 230-420% and the root system by 130-200% compared with the control group. The study proved that BioWAGs are a highly effective technology that supports plant vegetation and saves water. Thanks to the reuse of waste materials, the developed technology is compatible with the assumptions of the circular economy and the goals of sustainable development.

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.

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.

Alfalfa genomic selection for different stress-prone growing regions

Alfalfa (Medicago sativa L.) selection for stress-prone regions has high priority for sustainable crop-livestock systems. This study assessed the genomic selection (GS) ability to predict alfalfa breeding values for drought-prone agricultural sites of Algeria, Morocco, and Argentina; managed-stress (MS) environments of Italy featuring moderate or intense drought; and one Tunisian site irrigated with moderately saline water. Additional aims were to investigate genotype × environment interaction (GEI) patterns and the effect on GS predictions of three single-nucleotide polymorphism (SNP) calling procedures, 12 statistical models that exclude or incorporate GEI, and allele dosage information. Our study included 127 genotypes from a Mediterranean reference population originated from three geographically contrasting populations, genotyped via genotyping-by-sequencing and phenotyped based on multi-year biomass dry matter yield of their dense-planted half-sib progenies. The GEI was very large, as shown by 27-fold greater additive genetic variance × environment interaction relative to the additive genetic variance and low genetic correlation for progeny yield responses across environments. The predictive ability of GS (using at least 37,969 SNP markers) exceeded 0.20 for moderate MS (representing Italian stress-prone sites) and the sites of Algeria and Argentina while being quite low for the Tunisian site and intense MS. Predictions of GS were complicated by rapid linkage disequilibrium decay. The weighted GBLUP model, GEI incorporation into GS models, and SNP calling based on a mock reference genome exhibited a predictive ability advantage for some environments. Our results support the specific breeding for each target region and suggest a positive role for GS in most regions when considering the challenges associated with phenotypic selection.

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.

Tapping into Plant-Microbiome Interactions through the Lens of Multi-Omics Techniques

This review highlights the pivotal role of root exudates in the rhizosphere, especially the interactions between plants and microbes and between plants and plants. Root exudates determine soil nutrient mobilization, plant nutritional status, and the communication of plant roots with microbes. Root exudates contain diverse specialized signaling metabolites (primary and secondary). The spatial behavior of these metabolites around the root zone strongly influences rhizosphere microorganisms through an intimate compatible interaction, thereby regulating complex biological and ecological mechanisms. In this context, we reviewed the current understanding of the biological phenomenon of allelopathy, which is mediated by phytotoxic compounds (called allelochemicals) released by plants into the soil that affect the growth, survival, development, ecological infestation, and intensification of other plant species and microbes in natural communities or agricultural systems. Advances in next-generation sequencing (NGS), such as metagenomics and metatranscriptomics, have opened the possibility of better understanding the effects of secreted metabolites on the composition and activity of root-associated microbial communities. Nevertheless, understanding the role of secretory metabolites in microbiome manipulation can assist in designing next-generation microbial inoculants for targeted disease mitigation and improved plant growth using the synthetic microbial communities (SynComs) tool. Besides a discussion on different approaches, we highlighted the advantages of conjugation of metabolomic approaches with genetic design (metabolite-based genome-wide association studies) in dissecting metabolome diversity and understanding the genetic components of metabolite accumulation. Recent advances in the field of metabolomics have expedited comprehensive and rapid profiling and discovery of novel bioactive compounds in root exudates. In this context, we discussed the expanding array of metabolomics platforms for metabolome profiling and their integration with multivariate data analysis, which is crucial to explore the biosynthesis pathway, as well as the regulation of associated pathways at the gene, transcript, and protein levels, and finally their role in determining and shaping the rhizomicrobiome.

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.

Intraspecific Variation for Leaf Physiological and Root Morphological Adaptation to Drought Stress in Alfalfa (Medicago sativa L.)

Drought stress reduces crop biomass yield and the profitability of rainfed agricultural systems. Evaluation of populations or accessions adapted to diverse geographical and agro-climatic environments sheds light on beneficial plant responses to enhance and optimize yield in resource-limited environments. This study used the morphological and physiological characteristics of leaves and roots from two different alfalfa subspecies during progressive drought stress imposed on controlled and field conditions. Two different soils (Experiments 1 and 2) imposed water stress at different stress intensities and crop stages in the controlled environment. Algorithm-based image analysis of leaves and root systems revealed key morphological and physiological traits associated with biomass yield under stress. The Medicago sativa subspecies (ssp.) sativa population, PI478573, had smaller leaves and maintained higher chlorophyll content (CC), leaf water potential, and osmotic potential under water stress. In contrast, M. sativa ssp. varia, PI502521, had larger leaves, a robust root system, and more biomass yield. In the field study, an unmanned aerial vehicle survey revealed PI502521 to have a higher normalized difference vegetation index (vegetation cover and plant health characteristics) throughout the cropping season, whereas PI478573 values were low during the hot summer and yielded low biomass in both irrigated and rainfed treatments. RhizoVision Explorer image analysis of excavated roots revealed a smaller diameter and a narrow root angle as target traits to increase alfalfa biomass yield irrespective of water availability. Root architectural traits such as network area, solidity, volume, surface area, and maximum radius exhibited significant variation at the genotype level only under limited water availability. Different drought-adaptive strategies identified across subspecies populations will benefit the plant under varying levels of water limitation and facilitate the development of alfalfa cultivars suitable across a broad range of growing conditions. The alleles from both subspecies will enable the development of drought-tolerant alfalfa with enhanced productivity under limited water availability.

Validation of DNA marker-assisted selection for forage biomass productivity under deficit irrigation in alfalfa

Drought and limited irrigation resources threaten agricultural sustainability in many regions of the world. Application of genomic-based breeding strategies may benefit crop variety development for these environments. Here, we provide a first report on the effect of deploying DNA marker-assisted selection (MAS) for the drought resilience quantitative trait in alfalfa (Medicago sativa L.). The goals of this study were to validate the effect of several quantitative trait loci (QTL) associated with alfalfa forage and crown-root (CR) biomass during drought and to determine their potential to improve forage yield of elite germplasm under water-limited conditions. Marker assisted selection was employed to introgress favorable or unfavorable DNA marker alleles affiliated with 10 biomass QTL into three elite backgrounds. Thirty-two populations were developed and evaluated for forage productivity over 3 yr under continuous deficit irrigation management in New Mexico, USA. Significant yield differences (ranging from -13 to 26%) were detected among some MAS-derived populations in all three elite backgrounds. Application of QTL MAS generally resulted in expected phenotypic responses within an elite genetic background that was similar to that in which the QTL were originally identified. However, relative performance of the populations varied substantially across the three genetic backgrounds. These outcomes indicate that QTL MAS can significantly affect forage productivity of elite alfalfa germplasm in drought-stressed environments. However, if biomass QTL are detected in donor germplasm that is genetically dissimilar to targeted elite populations, characterization of donor alleles may be warranted within elite backgrounds of interest to confirm their phenotypic effects prior to implementing MAS-based breeding.

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.

Potential of Trichoderma harzianum and Its Metabolites to Protect Wheat Seedlings against Fusarium culmorum and 2,4-D

Wheat is a critically important crop. The application of fungi, such as Trichoderma harzianum, to protect and improve crop yields could become an alternative solution to synthetic chemicals. However, the interaction between the fungus and wheat in the presence of stress factors at the molecular level has not been fully elucidated. In the present work, we exposed germinating seeds of wheat (Triticum aestivum) to the plant pathogen Fusarium culmorum and the popular herbicide 2,4-dichlorophenoxyacetic acid (2,4-D) in the presence of T. harzianum or its extracellular metabolites. Then, the harvested roots and shoots were analyzed using spectrometry, 2D-PAGE, and MALDI-TOF/MS techniques. Although F. culmorum and 2,4-D were found to disturb seed germination and the chlorophyll content, T. harzianum partly alleviated these negative effects and reduced the synthesis of zearalenone by F. culmorum. Moreover, T. harzianum decreased the activity of oxidoreduction enzymes (CAT and SOD) and the contents of the oxylipins 9-Hode, 13-Hode, and 13-Hotre induced by stress factors. Under the influence of various growth conditions, changes were observed in over 40 proteins from the wheat roots. Higher volumes of proteins and enzymes performing oxidoreductive functions, such as catalase, ascorbate peroxidase, cytochrome C peroxidase, and Cu/Zn superoxide dismutase, were found in the Fusarium-inoculated and 2,4-D-treated wheat roots. Additionally, observation of the level of 12-oxo-phytodienoic acid reductase involved in the oxylipin signaling pathway in wheat showed an increase. Trichoderma and its metabolites present in the system leveled out the mentioned proteins to the control volumes. Among the 30 proteins examined in the shoots, the expression of the proteins involved in photosynthesis and oxidative stress response was found to be induced in the presence of the herbicide and the pathogen. In summary, these proteomic and metabolomic studies confirmed that the presence of T. harzianum results in the alleviation of oxidative stress in wheat induced by 2,4-D or F. culmorum.

Genetic Dissection of Mature Root Characteristics by Genome-Wide Association Studies in Rapeseed (Brassica napus L.)

Roots are complicated quantitative characteristics that play an essential role in absorbing water and nutrients. To uncover the genetic variations for root-related traits in rapeseed, twelve mature root traits of a Brassica napus association panel were investigated in the field within three environments. All traits showed significant phenotypic variation among genotypes, with heritabilities ranging from 55.18% to 79.68%. Genome-wide association studies (GWAS) using 20,131 SNPs discovered 172 marker-trait associations, including 103 significant SNPs (-log10 (p) > 4.30) that explained 5.24-20.31% of the phenotypic variance. With the linkage disequilibrium r² > 0.2, these significant associations were binned into 40 quantitative trait loci (QTL) clusters. Among them, 14 important QTL clusters were discovered in two environments and/or with phenotypic contributions greater than 10%. By analyzing the genomic regions within 100 kb upstream and downstream of the peak SNPs within the 14 loci, 334 annotated genes were found. Among these, 32 genes were potentially associated with root development according to their expression analysis. Furthermore, the protein interaction network using the 334 annotated genes gave nine genes involved in a substantial number of interactions, including a key gene associated with root development, BnaC09g36350D. This research provides the groundwork for deciphering B. napus' genetic variations and improving its root system architecture.

Annual and perennial Medicago show signatures of parallel adaptation to climate and soil in highly conserved genes

Human induced environmental change may require rapid adaptation of plant populations and crops, but the genomic basis of environmental adaptation remain poorly understood. We analysed polymorphic loci from the perennial crop Medicago sativa (alfalfa or lucerne) and the annual legume model species M. truncatula to search for a common set of candidate genes that might contribute to adaptation to abiotic stress in both annual and perennial Medicago species. We identified a set of candidate genes of adaptation associated with environmental gradients along the distribution of the two Medicago species. Candidate genes for each species were detected in homologous genomic linkage blocks using genome-environment (GEA) and genome-phenotype association analyses. Hundreds of GEA candidate genes were species-specific, of these, 13.4% (M. sativa) and 24% (M. truncatula) were also significantly associated with phenotypic traits. A set of 168 GEA candidates were shared by both species, which was 25.4% more than expected by chance. When combined, they explained a high proportion of variance for certain phenotypic traits associated with adaptation. Genes with highly conserved functions dominated among the shared candidates and were enriched in gene ontology terms that have shown to play a central role in drought avoidance and tolerance mechanisms by means of cellular shape modifications and other functions associated with cell homeostasis. Our results point to the existence of a molecular basis of adaptation to abiotic stress in Medicago determined by highly conserved genes and gene functions. We discuss these results in light of the recently proposed omnigenic model of complex traits.

Identification of Candidate Genes for Drought Tolerance at Maize Seedlings Using Genome-Wide Association

BACKGROUND

Drought stress is a serious threat that limit maize growth and production.

OBJECTIVES

The assessment tolerance level of maize by measuring changes in the main biochemical and physiological indicators under drought stress.

MATERIAL AND METHODS

We performed a genome-wide association analysis of biochemical and physiological indicators using an elite association panel.

RESULTS

The results revealed that eight significant SNPs (p<0.05/N) located in eight genes that are distributed on different chromosomes were associated with drought resistance indices under drought stress. Among these genes, four genes were linked via the associated SNPs with drought-resistance indices of the malondialdehyde activity (MDA), three genes were linked with drought resistance indexes of the superoxide dismutase activity (SOD), and one gene was linked with drought resistance indexes of relative conductivity (REC). The candidate genes functioned as transcription factors, enzymes, and transporters, which included trehalase, the AP2/EREB160 transcription factor, and glutathione S-transferase and also encoded a gene of unknown function. These genes may be directly or indirectly involved in drought resistance. The expression levels of ZmEREB160 responded to ABA and drought stress.

CONCLUSIONS

These results provided good information to understand the genetic basis of variation in drought resistance indices of biochemical and physiological indicators during drought stress.

Medicago sativa and Medicago truncatula Show Contrasting Root Metabolic Responses to Drought

Drought is an environmental stressor that affects crop yield worldwide. Understanding plant physiological responses to stress conditions is needed to secure food in future climate conditions. In this study, we applied a combination of plant physiology and metabolomic techniques to understand plant responses to progressive water deficit focusing on the root system. We chose two legume plants with contrasting tolerance to drought, the widely cultivated alfalfa Medicago sativa (Ms) and the model legume Medicago truncatula (Mt) for comparative analysis. Ms taproot (tapR) and Mt fibrous root (fibR) biomass increased during drought, while a progressive decline in water content was observed in both species. Metabolomic analysis allowed the identification of key metabolites in the different tissues tested. Under drought, carbohydrates, abscisic acid, and proline predominantly accumulated in leaves and tapRs, whereas flavonoids increased in fibRs in both species. Raffinose-family related metabolites accumulated during drought. Along with an accumulation of root sucrose in plants subjected to drought, both species showed a decrease in sucrose synthase (SUS) activity related to a reduction in the transcript level of SUS1, the main SUS gene. This study highlights the relevance of root carbon metabolism during drought conditions and provides evidence on the specific accumulation of metabolites throughout the root system.

Discovery of beneficial haplotypes for complex traits in maize landraces

Genetic variation is of crucial importance for crop improvement. Landraces are valuable sources of diversity, but for quantitative traits efficient strategies for their targeted utilization are lacking. Here, we map haplotype-trait associations at high resolution in ~1000 doubled-haploid lines derived from three maize landraces to make their native diversity for early development traits accessible for elite germplasm improvement. A comparative genomic analysis of the discovered haplotypes in the landrace-derived lines and a panel of 65 breeding lines, both genotyped with 600k SNPs, points to untapped beneficial variation for target traits in the landraces. The superior phenotypic performance of lines carrying favorable landrace haplotypes as compared to breeding lines with alternative haplotypes confirms these findings. Stability of haplotype effects across populations and environments as well as their limited effects on undesired traits indicate that our strategy has high potential for harnessing beneficial haplotype variation for quantitative traits from genetic resources.

Genetic variations present in landraces are critical for crop genetic improvement. Here, the authors map haplotype-trait associations in ~1000 doubled haploid lines derived from three European maize landraces and identify beneficial haplotypes for quantitative traits that are not present in breeding lines.

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.

Morphological, Physiological, and Genetic Responses to Salt Stress in Alfalfa: A Review

Alfalfa (Medicago sativa L.) is an important legume forage crop. However, its genetic improvement for salt tolerance is challenging, as alfalfa’s response to salt stress is genetically and physiologically complex. A review was made to update the knowledge of morphological, physiological, biochemical, and genetic responses of alfalfa plants to salt stress, and to discuss the potential of applying modern plant technologies to enhance alfalfa salt-resistant breeding, including genomic selection, RNA-Seq analysis, and cutting-edge Synchrotron beamlines. It is clear that alfalfa salt tolerance can be better characterized, genes conditioning salt tolerance be identified, and new marker-based tools be developed to accelerate alfalfa breeding for salt tolerance.

Targeted genotyping by sequencing: a new way to genome profile the cat

Targeted GBS is a recent approach for obtaining an effective characterization for hundreds to thousands of markers. The high throughput of next-generation sequencing technologies, moreover, allows sample multiplexing. The aims of this study were to (i) define a panel of single nucleotide polymorphisms (SNPs) in the cat, (ii) use GBS for profiling 16 cats, and (iii) evaluate the performance with respect to the inference using standard approaches at different coverage thresholds, thereby providing useful information for designing similar experiments. Probes for sequencing 230 variants were designed based on the Felis_catus_8.0. 8.0 genome. The regions comprised anonymous and non-anonymous SNPs. Sixteen cat samples were analysed, some of which had already been genotyped in a large group of loci and one having been whole-genome sequenced in the 99_Lives Cat Genome Sequencing Project. The accuracy of the method was assessed by comparing the GBS results with the genotypes already available. Overall, GBS achieved good performance, with 92-96% correct assignments, depending on the coverage threshold used to define the set of trustable genotypes. Analyses confirmed that (i) the reliability of the inference of each genotype depends on the coverage at that locus and (ii) the fraction of target loci whose genotype can be inferred correctly is a function of the total coverage. GBS proves to be a valid alternative to other methods. Data suggested a depth of less than 11× is required for greater than 95% accuracy. However, sequencing depth must be adapted to the total size of the targets to ensure proper genotype inference.

Role of genomics in promoting the utilization of plant genetic resources in genebanks

Global efforts have seen the world's plant genetic resources (PGRs) conserved in about 1625 germ plasm repositories. Utility of these resources is important in increasing the resilience and productivity of agricultural production systems. However, despite their importance, utility of these resources has been poor. This article reviews the real and potential application of the current advances in genomic technologies in improving the utilization of these resources. The actual and potential application of these genomic approaches in plant identification, phylogenetic analysis, analysing the genetic value of germ plasm, facilitating germ plasm selection in genebanks as well as instilling confidence in international germ plasm exchange system is discussed. We note that if genebanks are to benefit from this genomic revolution, there is need for fundamental changes in the way genebanks are managed, perceived, organized and funded. Increased collaboration between genebank managers and the user community is also recommended.

High-density linkage map construction and mapping QTL for yield and yield components in autotetraploid alfalfa using RAD-seq

BACKGROUND

Alfalfa (Medicago sativa L.) is an important forage crop grown worldwide. Alfalfa is called the "queen of forage crops" due to its high forage yield and nutritional characteristics. The aim of this study was to undertake quantitative trait loci (QTL) mapping of yield and yield-related traits in an F₁ population of two alfalfa varieties that differ in their yield and yield-related traits.

RESULTS

We constructed a high-density linkage map using single nucleotide polymorphism (SNP) markers generated by restriction-site associated DNA sequencing (RAD-seq). The linkage map contains 4346 SNP and 119 simple sequence repeat (SSR) markers, with 32 linkage groups for each parent. The average marker distances were 3.00 and 1.32 cM, with coverages of 3455 cM and 4381 cM for paternal and maternal linkage maps, respectively. Using these maps and phenotypic data, we identified a total of 21 QTL for yield and yield components, including five for yield, five for plant height, five for branch number, and six for shoot diameter. Among them, six QTL were co-located for more than one trait. Five QTL explained more than 10% of the phenotypic variation.

CONCLUSIONS

We used RAD-seq to construct a linkage map for alfalfa that greatly enhanced marker density compared to previous studies. This high-density linkage map of alfalfa is a useful reference for mapping yield-related traits. Identified yield-related loci could be used to validate their usefulness in developing markers for maker-assisted selection in breeding populations to improve yield potential in alfalfa.

Genetic Loci Associated with Salt Tolerance in Advanced Breeding Populations of Tetraploid Alfalfa Using Genome-Wide Association Studies

Many agricultural lands in the western United States consist of soil with high concentrations of salt, which is detrimental to alfalfa ( L.) growth and production, especially in the region where water resource is limited. Developing alfalfa varieties with salt tolerance is imperative for sustainable production under increasing soil salinity. In the present study, we used advanced alfalfa breeding populations and evaluated five traits related to salt tolerance including biomass dry weight (DW) and fresh weight (FW), plant height (PH), leaf relative water content (RWC), and stomatal conductance (SC) under control and salt stress. Stress susceptibility index (SSI) of each trait and single-nucleotide polymorphism (SNP) markers generated by genotyping-by-sequencing (GBS) were used for genome-wide association studies (GWAS) to identify loci associated with salt tolerance. A total of 53 significant SNPs associated with salt tolerance were identified and they were located at 49 loci through eight chromosomes. A Basic Local Alignment Search Tool (BLAST) search of the regions surrounding the SNPs revealed 21 putative candidate genes associated with salt tolerance. The genetic architecture for traits related to salt tolerance characterized in this report could help in understanding the genetic mechanism by which salt stress affects plant growth and production in alfalfa. The markers and candidate genes identified in the present study would be useful for marker-assisted selection (MAS) in breeding salt-tolerant alfalfa after validation of the markers.

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.

A fully automated pipeline for quantitative genotype calling from next generation sequencing data in autopolyploids

BACKGROUND

Genotyping-by-sequencing (GBS) has been used broadly in genetic studies for several species, especially those with agricultural importance. However, its use is still limited in autopolyploid species because genotype calling software generally fails to properly distinguish heterozygous classes based on allele dosage.

RESULTS

VCF2SM is a Python script that integrates sequencing depth information of polymorphisms in variant call format (VCF) files and SUPERMASSA software for quantitative genotype calling. VCFs can be obtained from any variant discovery software that outputs exact allele sequencing depth, such as a modified version of the TASSEL-GBS pipeline provided here. VCF2SM was successfully applied in analyzing GBS data from diverse panels (alfalfa and potato) and full-sib mapping populations (alfalfa and switchgrass) of polyploid species.

CONCLUSIONS

We demonstrate that our approach can help plant geneticists working with autopolyploid species to advance their studies by distinguishing allele dosage from GBS data.

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.

Tools for Genetic Studies in Experimental Populations of Polyploids

Polyploid organisms carry more than two copies of each chromosome, a condition rarely tolerated in animals but which occurs relatively frequently in the plant kingdom. One of the principal challenges faced by polyploid organisms is to evolve stable meiotic mechanisms to faithfully transmit genetic information to the next generation upon which the study of inheritance is based. In this review we look at the tools available to the research community to better understand polyploid inheritance, many of which have only recently been developed. Most of these tools are intended for experimental populations (rather than natural populations), facilitating genomics-assisted crop improvement and plant breeding. This is hardly surprising given that a large proportion of domesticated plant species are polyploid. We focus on three main areas: (1) polyploid genotyping; (2) genetic and physical mapping; and (3) quantitative trait analysis and genomic selection. We also briefly review some miscellaneous topics such as the mode of inheritance and the availability of polyploid simulation software. The current polyploid analytic toolbox includes software for assigning marker genotypes (and in particular, estimating the dosage of marker alleles in the heterozygous condition), establishing chromosome-scale linkage phase among marker alleles, constructing (short-range) haplotypes, generating linkage maps, performing genome-wide association studies (GWAS) and quantitative trait locus (QTL) analyses, and simulating polyploid populations. These tools can also help elucidate the mode of inheritance (disomic, polysomic or a mixture of both as in segmental allopolyploids) or reveal whether double reduction and multivalent chromosomal pairing occur. An increasing number of polyploids (or associated diploids) are being sequenced, leading to publicly available reference genome assemblies. Much work remains in order to keep pace with developments in genomic technologies. However, such technologies also offer the promise of understanding polyploid genomes at a level which hitherto has remained elusive.

GWAS Uncovers Differential Genetic Bases for Drought and Salt Tolerances in Sesame at the Germination Stage

Sesame has great potential as an industrial crop but its production is challenged by drought and salt stresses. To unravel the genetic variants leading to salinity and drought tolerances at the germination stage, genome-wide association studies of stress tolerance indexes related to NaCl-salt and polyethylene glycol-drought induced stresses were performed with a diversity panel of 490 sesame accessions. An extensive variation was observed for drought and salt responses in the population and most of the accessions were moderately tolerant to both stresses. A total of 132 and 120 significant Single Nucleotide Polymorphisms (SNPs) resolved to nine and 15 Quantitative trait loci (QTLs) were detected for drought and salt stresses, respectively. Only two common QTLs for drought and salt responses were found located on linkage groups 5 and 7, respectively. This indicates that the genetic bases for drought and salt responses in sesame are different. A total of 13 and 27 potential candidate genes were uncovered for drought and salt tolerance indexes, respectively, encoding transcription factors, antioxidative enzymes, osmoprotectants and involved in hormonal biosynthesis, signal transduction or ion sequestration. The identified SNPs and potential candidate genes represent valuable resources for future functional characterization towards the enhancement of sesame cultivars for drought and salt tolerances.

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

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

Genome-Wide Association Mapping of Loci Associated with Plant Growth and Forage Production under Salt Stress in Alfalfa (Medicago sativa L.)

Salinity tolerance is highly desirable to sustain alfalfa production in marginal lands that have been rendered saline. In this study, we used a diverse panel of 198 alfalfa accessions for mapping loci associated with plant growth and forage production under salt stress using genome-wide association studies (GWAS). The plants were genotyped using genotyping-by-sequencing (GBS). A greenhouse procedure was used for phenotyping four agronomic and physiological traits affected by salt stress, including dry weight (DW), plant height (PH), leaf chlorophyll content (LCC), and stomatal conductance (SC). For each trait, a stress susceptibility index (SSI) was used to evaluate plant performance under stressed and non-stressed conditions. Marker-trait association identified a total of 42 markers significantly associated with salt tolerance. They were located on all chromosomes except chromosome 2 based on the alignment of their flanking sequences to the reference genome (Medicago truncatula). Of those identified, 13 were associated with multiple traits. Several loci identified in the present study were also identified in previous reports. BLAST search revealed that 19 putative candidate genes linked to 24 significant markers. Among them, B3 DNA-binding protein, Thiaminepyrophosphokinase and IQ calmodulin-binding motif protein were identified among multiple traits in the present and previous studies. With further investigation, these markers and candidates would be useful for developing markers for marker-assisted selection in breeding programs to improve alfalfa cultivars with enhanced tolerance to salt stress.

Systems biology and genome-wide approaches to unveil the molecular players involved in the pre-germinative metabolism: implications on seed technology traits

The pre-germinative metabolism is among the most fascinating aspects of seed biology. The early seed germination phase, or pre-germination, is characterized by rapid water uptake (imbibition), which directs a series of dynamic biochemical events. Among those are enzyme activation, DNA damage and repair, and use of reserve storage compounds, such as lipids, carbohydrates and proteins. Industrial seedling production and intensive agricultural production systems require seed stocks with high rate of synchronized germination and low dormancy. Consequently, seed dormancy, a quantitative trait related to the activation of the pre-germinative metabolism, is probably the most studied seed trait in model species and crops. Single omics, systems biology, QTLs and GWAS mapping approaches have unveiled a list of molecules and regulatory mechanisms acting at transcriptional, post-transcriptional and post-translational levels. Most of the identified candidate genes encode for regulatory proteins targeting ROS, phytohormone and primary metabolisms, corroborating the data obtained from simple molecular biology approaches. Emerging evidences show that epigenetic regulation plays a crucial role in the regulation of these mentioned processes, constituting a still unexploited strategy to modulate seed traits. The present review will provide an up-date of the current knowledge on seed pre-germinative metabolism, gathering the most relevant results from physiological, genetics, and omics studies conducted in model and crop plants. The effects exerted by the biotic and abiotic stresses and priming are also addressed. The possible implications derived from the modulation of pre-germinative metabolism will be discussed from the point of view of seed quality and technology.

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.

Genetic Diversity, Population Structure, and Linkage Disequilibrium of an Association-Mapping Panel Revealed by Genome-Wide SNP Markers in Sesame

The characterization of genetic diversity and population structure can be used in tandem to detect reliable phenotype-genotype associations. In the present study, we genotyped a set of 366 sesame germplasm accessions by using 89,924 single-nucleotide polymorphisms (SNPs). The number of SNPs on each chromosome was consistent with the physical length of the respective chromosome, and the average marker density was approximately 2.67 kb/SNP. The genetic diversity analysis showed that the average nucleotide diversity of the panel was 1.1 × 10^-3, with averages of 1.0 × 10^-4, 2.7 × 10^-4, and 3.6 × 10^-4 obtained, respectively for three identified subgroups of the panel: Pop 1, Pop 2, and the Mixed. The genetic structure analysis revealed that these sesame germplasm accessions were structured primarily along the basis of their geographic collection, and that an extensive admixture occurred in the panel. The genome-wide linkage disequilibrium (LD) analysis showed that an average LD extended up to ∼99 kb. The genetic diversity and population structure revealed in this study should provide guidance to the future design of association studies and the systematic utilization of the genetic variation characterizing the sesame panel.

The Impact of Genotyping-by-Sequencing Pipelines on SNP Discovery and Identification of Markers Associated with Verticillium Wilt Resistance in Autotetraploid Alfalfa (Medicago sativa L.)

Verticillium wilt (VW) of alfalfa is a soilborne disease causing severe yield loss in alfalfa. To identify molecular markers associated with VW resistance, we used an integrated framework of genome-wide association study (GWAS) with high-throughput genotyping by sequencing (GBS) to identify loci associated with VW resistance in an F1 full-sib alfalfa population. Phenotyping was performed using manual inoculation of the pathogen to cloned plants of each individual and disease severity was scored using a standard scale. Genotyping was done by GBS, followed by genotype calling using three bioinformatics pipelines including the TASSEL-GBS pipeline (TASSEL), the Universal Network Enabled Analysis Kit (UNEAK), and the haplotype-based FreeBayes pipeline (FreeBayes). The resulting numbers of SNPs, marker density, minor allele frequency (MAF) and heterozygosity were compared among the pipelines. The TASSEL pipeline generated more markers with the highest density and MAF, whereas the highest heterozygosity was obtained by the UNEAK pipeline. The FreeBayes pipeline generated tetraploid genotypes, with the least number of markers. SNP markers generated from each pipeline were used independently for marker-trait association. Markers significantly associated with VW resistance identified by each pipeline were compared. Similar marker loci were found on chromosomes 5, 6, and 7, whereas different loci on chromosome 1, 2, 3, and 4 were identified by different pipelines. Most significant markers were located on chromosome 6 and they were identified by all three pipelines. Of those identified, several loci were linked to known genes whose functions are involved in the plants' resistance to pathogens. Further investigation on these loci and their linked genes would provide insight into understanding molecular mechanisms of VW resistance in alfalfa. Functional markers closely linked to the resistance loci would be useful for MAS to improve alfalfa cultivars with enhanced resistance to the disease.

Genome-Wide Association Study Identifies Loci for Salt Tolerance during Germination in Autotetraploid Alfalfa (Medicago sativa L.) Using Genotyping-by-Sequencing

Salinity is one of major abiotic stresses limiting alfalfa (Medicago sativa L.) production in the arid and semi-arid regions in US and other counties. In this study, we used a diverse panel of alfalfa accessions previously described by Zhang et al. (2015) to identify molecular markers associated with salt tolerance during germination using genome-wide association study (GWAS) and genotyping-by-sequencing (GBS). Phenotyping was done by germinating alfalfa seeds under different levels of salt stress. Phenotypic data of adjusted germination rates and SNP markers generated by GBS were used for marker-trait association. Thirty six markers were significantly associated with salt tolerance in at least one level of salt treatments. Alignment of sequence tags to the Medicago truncatula genome revealed genetic locations of the markers on all chromosomes except chromosome 3. Most significant markers were found on chromosomes 1, 2, and 4. BLAST search using the flanking sequences of significant markers identified 14 putative candidate genes linked to 23 significant markers. Most of them were repeatedly identified in two or three salt treatments. Several loci identified in the present study had similar genetic locations to the reported QTL associated with salt tolerance in M. truncatula. A locus identified on chromosome 6 by this study overlapped with that by drought in our previous study. To our knowledge, this is the first report on mapping loci associated with salt tolerance during germination in autotetraploid alfalfa. Further investigation on these loci and their linked genes would provide insight into understanding molecular mechanisms by which salt and drought stresses affect alfalfa growth. Functional markers closely linked to the resistance loci would be useful for MAS to improve alfalfa cultivars with enhanced resistance to drought and salt stresses.