Meta-QTL analysis of seed iron and zinc concentration and content in common bean (Phaseolus vulgaris L.)

Meta QTL analysis for dissecting abiotic stress tolerance in chickpea

BACKGROUND

Chickpea is prone to many abiotic stresses such as heat, drought, salinity, etc. which cause severe loss in yield. Tolerance towards these stresses is quantitative in nature and many studies have been done to map the loci influencing these traits in different populations using different markers. This study is an attempt to meta-analyse those reported loci projected over a high-density consensus map to provide a more accurate information on the regions influencing heat, drought, cold and salinity tolerance in chickpea.

RESULTS

A meta-analysis of QTL reported to be responsible for tolerance to drought, heat, cold and salinity stress tolerance in chickpeas was done. A total of 1512 QTL responsible for the concerned abiotic stress tolerance were collected from literature, of which 1189 were projected on a chickpea consensus genetic map. The QTL meta-analysis predicted 59 MQTL spread over all 8 chromosomes, responsible for these 4 kinds of abiotic stress tolerance in chickpea. The physical locations of 23 MQTL were validated by various marker-trait associations and genome-wide association studies. Out of these reported MQTL, CaMQAST1.1, CaMQAST4.1, CaMQAST4.4, CaMQAST7.8, and CaMQAST8.2 were suggested to be useful for different breeding approaches as they were responsible for high per cent variance explained (PVE), had small intervals and encompassed a large number of originally reported QTL. Many putative candidate genes that might be responsible for directly or indirectly conferring abiotic stress tolerance were identified in the region covered by 4 major MQTL- CaMQAST1.1, CaMQAST4.4, CaMQAST7.7, and CaMQAST6.4, such as heat shock proteins, auxin and gibberellin response factors, etc. CONCLUSION: The results of this study should be useful for the breeders and researchers to develop new chickpea varieties which are tolerant to drought, heat, cold, and salinity stresses.

Dynamic Expressions of Yellow Stripe-Like (YSL) Genes During Pod Development Shed Light on Associations with Iron Distribution in Phaseolus vulgaris

The global prevalence of iron deficiency-induced "hidden hunger" highlights a critical health concern, underscoring the pressing need to improve iron nutrition through safe and efficient means, such as increasing iron intake from plant-based foods. Yellow Stripe-Like (YSL) genes play a crucial role in long-distance iron transport between source and sink tissues in plants. Here, we report on the analysis of YSL family genes in the common bean (Phaseolus vulgaris L.), an iron-rich legume crop. We identified 9 YSL genes in the common bean genome using BLAST and HMM methods. Gene duplication analysis revealed that PvYSL7a and PvYSL7b originated through tandem duplication events. Structural analysis noted an absence of conservative motifs in PvYSL3b and PvYSL7a, which led to distinct predicted 3D protein structures. Leveraging publicly available RNA-seq data from developing bean pods, the expression patterns of PvYSL genes alongside pod and seed development were analyzed. Notably, PvYSL7a and PvYSL7b, as well as PvYSL1a and PvYSL1b, exhibited diverged expression patterns in seeds, signifying their functional divergence in this tissue. Moreover, PvYSL3a and PvYSL3b exhibited divergent expression patterns in both pod walls and seeds during pod development, underscoring their distinct roles in facilitating iron transportation between pods and seeds. This study provides valuable insights into the gene regulatory basis of iron accumulation in bean pods and seeds.

Genome-wide association and genomic prediction for iron and zinc concentration and iron bioavailability in a collection of yellow dry beans

Dry bean is a nutrient-dense food targeted in biofortification programs to increase seed iron and zinc levels. The underlying assumption of breeding for higher mineral content is that enhanced iron and zinc levels will deliver health benefits to the consumers of these biofortified foods. This study characterized a diversity panel of 275 genotypes comprising the Yellow Bean Collection (YBC) for seed Fe and Zn concentration, Fe bioavailability (FeBio), and seed yield across 2 years in two field locations. The genetic architecture of each trait was elucidated via genome-wide association studies (GWAS) and the efficacy of genomic prediction (GP) was assessed. Moreover, 82 yellow breeding lines were evaluated for seed Fe and Zn concentrations as well as seed yield, serving as a prediction set for GP models. Large phenotypic variability was identified in all traits evaluated, and variations of up to 2.8 and 13.7-fold were observed for Fe concentration and FeBio, respectively. Prediction accuracies in the YBC ranged from a low of 0.12 for Fe concentration, to a high of 0.72 for FeBio, and an accuracy improvement of 0.03 was observed when a QTN, identified through GWAS, was used as a fixed effect for FeBio. This study provides evidence of the lack of correlation between FeBio estimated in vitro and Fe concentration and highlights the potential of GP in accurately predicting FeBio in yellow beans, offering a cost-effective alternative to the traditional assessment of using Caco2 cell methodologies.

Genome-Wide Association Study to Identify Possible Candidate Genes of Snap Bean Leaf and Pod Color

Color can be an indicator of plant health, quality, and productivity, and is useful to researchers to understand plant nutritional content in their studies. Color may be related to chlorophyll content and photosynthetic activity and provides information for those studying diseases and mineral nutrition because every nutrient deficiency and many diseases produce symptoms that affect color. In order to identify significant loci related to both leaf and pod color in a snap bean (Phaseolus vulgaris L.) diversity panel, a genome-wide association study (GWAS) was carried out. Leaf color in one and pod traits in multiple environments were characterized using a colorimeter. L*a*b* color data were recorded and used to calculate chroma (C*) and hue angle (H°). Leaves were evaluated at three positions (lower, middle, and upper) in the canopy and both pod exterior and interior colors were obtained. GWAS was conducted using two reference genomes that represent the Andean (G19833) and Middle American (5-593) domestication centers. Narrow sense heritabilities were calculated using the mixed linear model (MLM) method in genome association and prediction integrated tool (GAPIT), and significant single nucleotide polymorphisms (SNPs) for each color parameter were obtained using the Bayesian-information and linkage-disequilibrium iteratively nested keyway (BLINK) GWAS model with two principal components (PCAs). In comparison to pod color traits, narrow sense heritabilities of leaf traits were low and similar for both reference genomes. Generally, narrow sense heritability for all traits was highest in the lower, followed by middle, and then upper leaf positions. Heritability for both pod interior and exterior color traits was higher using the G19833 reference genome compared to 5-593 when evaluated by year and means across years. Forty-five significant SNPs associated with leaf traits and 872 associated with pods, totaling 917 significant SNPs were identified. Only one SNP was found in common for both leaf and pod traits on Pv03 in the 5-593 reference genome. One-hundred thirteen significant SNPs, 30 in leaves and 83 in pods had phenotypic variation explained (PVE) of 10% or greater. Fourteen SNPs (four from G19833 and ten from 5-593) with ≥10 PVE%, large SNP effect, and largest p-value for L* and H° pod exterior was identified on Pv01, Pv02, Pv03, and Pv08. More SNPs were associated with pod traits than with leaf traits. The pod interior did not exhibit colors produced by anthocyanins or flavonols which allowed the differentiation of potential candidate genes associated with chloroplast and photosynthetic activity compared to the pod exterior where candidate genes related to both flavonoids and photosynthesis affected color. Several SNPs were associated with known qualitative genes including the wax pod locus (y), persistent color (pc), purple pods (V), and two genes expressed in seeds but not previously reported to affect other plant tissues (B and J). An evaluation of significant SNPs within annotated genes found a number, within a 200 kb window, involved in both flavonoid and photosynthetic biosynthetic pathways.

Characterizing patterns of seasonal drought stress for use in common bean breeding in East Africa under present and future climates

Common bean (Phaseolus vulgaris L.) is the second most important source of dietary protein and the third most important source of calories in Africa, especially for the poor. In East Africa, drought is an important constraint to bean production. Therefore, breeding programs in East Africa have been trying to develop drought resistant varieties of common bean. To do this, breeders need information about seasonal drought stress patterns including their onset, intensity, and duration in the target area of the breeding program, so that they can mimic this pattern during field trials. Using the Decision Support for Agrotechnology Transfer (DSSAT) v4.7 model together with historical and future (Coupled Model Inter-comparison Project 6, CMIP6) climate data, this study categorized Ethiopia, Tanzania, and Uganda into different target population of environments (TPEs) based on historical and future seasonal drought stress patterns. We find that stress-free conditions generally dominate across the three countries under historical conditions (50-80% frequency). These conditions are projected to increase in frequency in Ethiopia by 2-10% but the converse is true for Tanzania (2-8% reduction) and Uganda (17-20% reduction) by 2050 depending on the Shared Socioeconomic Pathway (SSP). Accordingly, by 2050, terminal drought stresses of various intensities (moderate, severe, extreme) are prevalent in 34% of Uganda, around a quarter of Ethiopia, and 40% of the bean growing environments in Tanzania. The TPEs identified in each country serve as a basis for prioritizing breeding activities in national programs. However, to optimize resource use in international breeding programs to develop genotypes that are resilient to future projected stress patterns, we argue that common bean breeding programs should focus primarily on identifying genotypes with tolerance to severe terminal drought, with co-benefits in relation to adaptation to moderate and extreme terminal drought. Little to no emphasis on heat stress is warranted by 2050s.

Delineation of novel genomic loci and putative candidate genes associated with seed iron and zinc content in lentil (Lens culinaris Medik.)

The use of molecular breeding approaches for development of lentil genotypes biofortified with essential micro-nutrients such as iron and zinc, could serve as a promising solution to address the problem of global malnutrition. Thus, genome-wide association study (GWAS) strategy was adopted in this study to identify the genomic regions associated with seed iron and zinc content in lentil. A panel of 95 diverse lentil genotypes, grown across three different geographical locations and evaluated for seed iron and zinc content, exhibited a wide range of variation. Genotyping-by-sequencing (GBS) analysis of the panel identified 33,745 significant single nucleotide polymorphisms (SNPs) that were distributed across all the 7 lentil chromosomes. Association mapping revealed 23 SNPs associated with seed iron content that were distributed across all the chromosomes except chromosome 3. Similarly, 14 SNPs associated with seed zinc content were also identified that were distributed across chromosomes 1, 2, 4, 5 and 6. Further, 80 genes were identified in the proximity of iron associated markers and 36 genes were identified in the proximity of zinc associated markers. Functional annotation of these genes revealed their putative involvement in iron and zinc metabolism. For seed iron content, two highly significant SNPs were found to be located within two putative candidate genes namely iron-sulfur cluster assembly (ISCA) and flavin binding monooxygenase (FMO) respectively. For zinc content, a highly significant SNP was detected in a gene encoding UPF0678 fatty acid-binding protein. Expression analysis of these genes and their putative interacting partners suggests their involvement in iron and zinc metabolism in lentil. Overall, in this study we have identified markers, putative candidate genes and predicted putative interacting protein partners significantly associated with iron and zinc metabolism that could be utilized in future breeding studies of lentil for nutrient biofortification.

Telomere-to-telomere genome assembly of melon (Cucumis melo L. var. inodorus) provides a high-quality reference for meta-QTL analysis of important traits

Melon is an important horticultural crop with extensive diversity in many horticultural groups. To explore its genomic diversity, it is necessary to assemble more high-quality complete genomes from different melon accessions. Meanwhile, a large number of QTLs have been mapped in several studies. Integration of the published QTLs onto a complete genome can provide more accurate information for candidate gene cloning. To address these problems, a telomere-to-telomere (T2T) genome of the elite melon landrace Kuizilikjiz (Cucumis melo L. var. inodorus) was de novo assembled and all the published QTLs were projected onto it in this study. The results showed that a high-quality Kuizilikjiz genome with the size of 379.2 Mb and N50 of 31.7 Mb was de novo assembled using the combination of short reads, PacBio high-fidelity long reads, Hi-C data, and a high-density genetic map. Each chromosome contained the centromere and telomeres at both ends. A large number of structural variations were observed between Kuizilikjiz and the other published genomes. A total of 1294 QTLs published in 67 studies were collected and projected onto the T2T genome. Several clustered, co-localized, and overlapped QTLs were determined. Furthermore, 20 stable meta-QTLs were identified, which significantly reduced the mapping intervals of the initial QTLs and greatly facilitated identification of the candidate genes. Collectively, the T2T genome assembly together with the numerous projected QTLs will not only broaden the high-quality genome resources but also provide valuable and abundant QTL information for cloning the genes controlling important traits in melon.

Comprehensive meta-QTL analysis for dissecting the genetic architecture of stripe rust resistance in bread wheat

BACKGROUND

Yellow or stripe rust, caused by the fungus Puccinia striiformis f. sp. tritici (Pst) is an important disease of wheat that threatens wheat production. Since developing resistant cultivars offers a viable solution for disease management, it is essential to understand the genetic basis of stripe rust resistance. In recent years, meta-QTL analysis of identified QTLs has gained popularity as a way to dissect the genetic architecture underpinning quantitative traits, including disease resistance.

RESULTS

Systematic meta-QTL analysis involving 505 QTLs from 101 linkage-based interval mapping studies was conducted for stripe rust resistance in wheat. For this purpose, publicly available high-quality genetic maps were used to create a consensus linkage map involving 138,574 markers. This map was used to project the QTLs and conduct meta-QTL analysis. A total of 67 important meta-QTLs (MQTLs) were identified which were refined to 29 high-confidence MQTLs. The confidence interval (CI) of MQTLs ranged from 0 to 11.68 cM with a mean of 1.97 cM. The mean physical CI of MQTLs was 24.01 Mb, ranging from 0.0749 to 216.23 Mb per MQTL. As many as 44 MQTLs colocalized with marker-trait associations or SNP peaks associated with stripe rust resistance in wheat. Some MQTLs also included the following major genes- Yr5, Yr7, Yr16, Yr26, Yr30, Yr43, Yr44, Yr64, YrCH52, and YrH52. Candidate gene mining in high-confidence MQTLs identified 1,562 gene models. Examining these gene models for differential expressions yielded 123 differentially expressed genes, including the 59 most promising CGs. We also studied how these genes were expressed in wheat tissues at different phases of development.

CONCLUSION

The most promising MQTLs identified in this study may facilitate marker-assisted breeding for stripe rust resistance in wheat. Information on markers flanking the MQTLs can be utilized in genomic selection models to increase the prediction accuracy for stripe rust resistance. The candidate genes identified can also be utilized for enhancing the wheat resistance against stripe rust after in vivo confirmation/validation using one or more of the following methods: gene cloning, reverse genetic methods, and omics approaches.

Cooking properties and nutrient retention of biofortified common bean (Phaseolus vulgaris) varieties: The case of Burundi

Introduction

Current research on micronutrient deficiency indicates positive outcomes associated with utilizing biofortified beans in mitigating nutrition-related iron and zinc deficiencies, primarily in Sub-Saharan Africa. The common bean is however not palatable in its raw state and requires cooking before consumption. Existing research on the cooking qualities and nutrient retention of these novel biofortified common bean varieties is nonetheless scant, notably in Burundi.

Materials and methods

This study determined water absorption capacity, cooking yield, cooking time, and iron and zinc retention of 9 biofortified common bean varieties with Kinure, a traditional non-biofortified variety, as the control. The study employed a 10 × 2 completely randomized design in a factorial arrangement. The first factor was bean varieties with ten levels, and the second was pre-treatment with two levels, soaking and not soaking. Standard methods were used to analyze cooking properties and mineral retention, and experiments replicated thrice. Data analysis was conducted at a 95% confidence level and included Analysis of Variance and t-test comparison studies. Post-hoc analysis was performed using Tukey's Honestly Significant Difference.

Results and discussion

Cooking properties and mineral retention varied significantly between soaked and unsoaked bean varieties (P < 0.05) and in comparison, to Kinure (P < 0.05 and P < 0.001). Water absorption capacity varied from 64.51% to 116.3%. Soaked beans recorded half the total cooking time needed to cook unsoaked beans (77.62 versus 156.86 minutes), had higher cooking yields (289.77% versus 259.82%), and reduced Fe (121.58 versus 167.8%) and Zn (127.74% versus 145.15%) retention. Compared to Kinure, soaking resulted in longer cooking times, lower cooking yields in the biofortified common beans, and an insignificant effect on their zinc retention. A significant correlation between iron and zinc retention (r = 0.445), water absorption capacity and iron retention (r = −0.0425) and water absorption capacity and zinc retention (r = −0.477) were recorded. Three clusters were also observed; iron and zinc retention, cooking yields, and water absorption capacity, and cooking time. It was observed that, soaking common beans before cooking reduces cooking time and increases cooking yield in both biofortified and traditional common bean varieties. Moreover, biofortified common beans are a good source of iron and zinc and could considerably alleviate micronutrient deficiencies, particularly in developing countries.

Meta-QTL Analysis for Yield Components in Common Bean (Phaseolus vulgaris L.)

Common bean is one of the most important legumes produced and consumed worldwide because it is a highly valuable food for the human diet. However, its production is mainly carried out by small farmers, who obtain average grain yields below the potential yield of the species. In this sense, numerous mapping studies have been conducted to identify quantitative trait loci (QTL) associated with yield components in common bean. Meta-QTL (MQTL) analysis is a useful approach to combine data sets and for creating consensus positions for the QTL detected in independent studies. Consequently, the objective of this study was to perform a MQTL analysis to identify the most reliable and stable genomic regions associated with yield-related traits of common bean. A total of 667 QTL associated with yield-related traits reported in 21 different studies were collected. A total of 42 MQTL associated with yield-related traits were identified, in which the average confidence interval (CI) of the MQTL was 3.41 times lower than the CIs of the original QTL. Most of the MQTL (28) identified in this study contain QTL associated with yield and phenological traits; therefore, these MQTL can be useful in common bean breeding programs. Finally, a total of 18 candidate genes were identified and associated with grain yield within these MQTL, with functions related to ubiquitin ligase complex, response to auxin, and translation elongation factor activity.

Genome-wide meta-QTL analyses provide novel insight into disease resistance repertoires in common bean

BACKGROUND

Common bean (Phaseolus vulgaris) is considered a staple food in a number of developing countries. Several diseases attack the crop leading to substantial economic losses around the globe. However, the crop has rarely been investigated for multiple disease resistance traits using Meta-analysis approach.

RESULTS AND CONCLUSIONS

In this study, in order to identify the most reliable and stable quantitative trait loci (QTL) conveying disease resistance in common bean, we carried out a meta-QTL (MQTL) analysis using 152 QTLs belonging to 44 populations reported in 33 publications within the past 20 years. These QTLs were decreased into nine MQTLs and the average of confidence interval (CI) was reduced by 2.64 folds with an average of 5.12 cM in MQTLs. Uneven distribution of MQTLs across common bean genome was noted where sub-telomeric regions carry most of the corresponding genes and MQTLs. One MQTL was identified to be specifically associated with resistance to halo blight disease caused by the bacterial pathogen Pseudomonas savastanoi pv. phaseolicola, while three and one MQTLs were specifically associated with resistance to white mold and anthracnose caused by the fungal pathogens Sclerotinia sclerotiorum and Colletotrichum lindemuthianum, respectively. Furthermore, two MQTLs were detected governing resistance to halo blight and anthracnose, while two MQTLs were detected for resistance against anthracnose and white mold, suggesting putative genes governing resistance against these diseases at a shared locus. Comparative genomics and synteny analyses provide a valuable strategy to identify a number of well‑known functionally described genes as well as numerous putative novels candidate genes in common bean, Arabidopsis and soybean genomes.

Integrated breeding approaches to enhance the nutritional quality of food legumes

Global food security, both in terms of quantity and quality remains as a challenge with the increasing population. In parallel, micronutrient deficiency in the human diet leads to malnutrition and several health-related problems collectively known as "hidden hunger" more prominent in developing countries around the globe. Biofortification is a potential tool to fortify grain legumes with micronutrients to mitigate the food and nutritional security of the ever-increasing population. Anti-nutritional factors like phytates, raffinose (RFO's), oxalates, tannin, etc. have adverse effects on human health upon consumption. Reduction of the anti-nutritional factors or preventing their accumulation offers opportunity for enhancing the intake of legumes in diet besides increasing the bioavailability of micronutrients. Integrated breeding methods are routinely being used to exploit the available genetic variability for micronutrients through modern "omic" technologies such as genomics, transcriptomics, ionomics, and metabolomics for developing biofortified grain legumes. Molecular mechanism of Fe/Zn uptake, phytate, and raffinose family oligosaccharides (RFOs) biosynthesis pathways have been elucidated. Transgenic, microRNAs and genome editing tools hold great promise for designing nutrient-dense and anti-nutrient-free grain legumes. In this review, we present the recent efforts toward manipulation of genes/QTLs regulating biofortification and Anti-nutrient accumulation in legumes using genetics-, genomics-, microRNA-, and genome editing-based approaches. We also discuss the success stories in legumes enrichment and recent advances in development of low Anti-nutrient lines. We hope that these emerging tools and techniques will expedite the efforts to develop micronutrient dense legume crop varieties devoid of Anti-nutritional factors that will serve to address the challenges like malnutrition and hidden hunger.

Understanding complex genetic architecture of rice grain weight through QTL-meta analysis and candidate gene identification

Quantitative trait loci (QTL) for rice grain weight identified using bi-parental populations in various environments were found inconsistent and have a modest role in marker assisted breeding and map-based cloning programs. Thus, the identification of a consistent consensus QTL region across populations is critical to deploy in marker aided breeding programs. Using the QTL meta-analysis technique, we collated rice grain weight QTL information from numerous studies done across populations and in diverse environments to find constitutive QTL for grain weight. Using information from 114 original QTL in meta-analysis, we discovered three significant Meta-QTL (MQTL) for grain weight on chromosome 3. According to gene ontology, these three MQTL have 179 genes, 25 of which have roles in developmental functions. Amino acid sequence BLAST of these genes indicated their orthologue conservation among core cereals with similar functions. MQTL3.1 includes the OsAPX1, PDIL, SAUR, and OsASN1 genes, which are involved in grain development and have been discovered to play a key role in asparagine biosynthesis and metabolism, which is crucial for source-sink regulation. Five potential candidate genes were identified and their expression analysis indicated a significant role in early grain development. The gene sequence information retrieved from the 3 K rice genome project revealed the deletion of six bases coding for serine and alanine in the last exon of OsASN1 led to an interruption in the synthesis of α-helix of the protein, which negatively affected the asparagine biosynthesis pathway in the low grain weight genotypes. Further, the MQTL3.1 was validated using linked marker RM7197 on a set of genotypes with extreme phenotypes. MQTL that have been identified and validated in our study have significant scope in MAS breeding and map-based cloning programs for improving rice grain weight.

Meta-QTL analysis explores the key genes, especially hormone related genes, involved in the regulation of grain water content and grain dehydration rate in maize

BACKGROUND

Low grain water content (GWC) at harvest of maize (Zea mays L.) is essential for mechanical harvesting, transportation and storage. Grain drying rate (GDR) is a key determinant of GWC. Many quantitative trait locus (QTLs) related to GDR and GWC have been reported, however, the confidence interval (CI) of these QTLs are too large and few QTLs has been fine-mapped or even been cloned. Meta-QTL (MQTL) analysis is an effective method to integrate QTLs information in independent populations, which helps to understand the genetic structure of quantitative traits.

RESULTS

In this study, MQTL analysis was performed using 282 QTLs from 25 experiments related GDR and GWC. Totally, 11 and 34 MQTLs were found to be associated with GDR and GWC, respectively. The average CI of GDR and GWC MQTLs was 24.44 and 22.13 cM which reduced the 57 and 65% compared to the average QTL interval for initial GDR and GWC QTL, respectively. Finally, 1494 and 5011 candidate genes related to GDR and GWC were identified in MQTL intervals, respectively. Among these genes, there are 48 genes related to hormone metabolism.

CONCLUSIONS

Our studies combined traditional QTL analyses, genome-wide association study and RNA-seq to analysis major locus for regulating GWC in maize.

Improving Association Studies and Genomic Predictions for Climbing Beans With Data From Bush Bean Populations

Common bean (Phaseolus vulgaris L.) has two major origins of domestication, Andean and Mesoamerican, which contribute to the high diversity of growth type, pod and seed characteristics. The climbing growth habit is associated with increased days to flowering (DF), seed iron concentration (SdFe), nitrogen fixation, and yield. However, breeding efforts in climbing beans have been limited and independent from bush type beans. To advance climbing bean breeding, we carried out genome-wide association studies and genomic predictions using 1,869 common bean lines belonging to five breeding panels representing both gene pools and all growth types. The phenotypic data were collected from 17 field trials and were complemented with 16 previously published trials. Overall, 38 significant marker-trait associations were identified for growth habit, 14 for DF, 13 for 100 seed weight, three for SdFe, and one for yield. Except for DF, the results suggest a common genetic basis for traits across all panels and growth types. Seven QTL associated with growth habits were confirmed from earlier studies and four plausible candidate genes for SdFe and 100 seed weight were newly identified. Furthermore, the genomic prediction accuracy for SdFe and yield in climbing beans improved up to 8.8% when bush-type bean lines were included in the training population. In conclusion, a large population from different gene pools and growth types across multiple breeding panels increased the power of genomic analyses and provides a solid and diverse germplasm base for genetic improvement of common bean.

Zinc deficiency responses: bridging the gap between Arabidopsis and dicotyledonous crops

Zinc (Zn) deficiency is a widespread phenomenon in agricultural soils worldwide and has a major impact on crop yield and quality, and hence on human nutrition and health. Although dicotyledonous crops represent >30% of human plant-based nutrition, relatively few efforts have been dedicated to the investigation of Zn deficiency response mechanisms in dicotyledonous, in contrast to monocotyledonous crops, such as rice or barley. Here, we describe the Zn requirement and impact of Zn deficiency in several economically important dicotyledonous crops, Phaseolus vulgaris, Glycine max, Brassica oleracea, and Solanum lycopersicum. We briefly review our current knowledge of the Zn deficiency response in Arabidopsis and outline how this knowledge is translated in dicotyledonous crops. We highlight commonalities and differences between dicotyledonous species (and with monocotyledonous species) regarding the function and regulation of Zn transporters and chelators, as well as the Zn-sensing mechanisms and the role of hormones in the Zn deficiency response. Moreover, we show how the Zn homeostatic network intimately interacts with other nutrients, such as iron or phosphate. Finally, we outline how variation in Zn deficiency tolerance and Zn use efficiency among cultivars of dicotyledonous species can be leveraged for the design of Zn biofortification strategies.

Applications of Genomic Tools in Plant Breeding: Crop Biofortification

Crop breeding has mainly been focused on increasing productivity, either directly or by decreasing the losses caused by biotic and abiotic stresses (that is, incorporating resistance to diseases and enhancing tolerance to adverse conditions, respectively). Quite the opposite, little attention has been paid to improve the nutritional value of crops. It has not been until recently that crop biofortification has become an objective within breeding programs, through either conventional methods or genetic engineering. There are many steps along this long path, from the initial evaluation of germplasm for the content of nutrients and health-promoting compounds to the development of biofortified varieties, with the available and future genomic tools assisting scientists and breeders in reaching their objectives as well as speeding up the process. This review offers a compendium of the genomic technologies used to explore and create biodiversity, to associate the traits of interest to the genome, and to transfer the genomic regions responsible for the desirable characteristics into potential new varieties. Finally, a glimpse of future perspectives and challenges in this emerging area is offered by taking the present scenario and the slow progress of the regulatory framework as the starting point.

Genetic Correlation Between Fe and Zn Biofortification and Yield Components in a Common Bean (Phaseolus vulgaris L.)

Common bean (Phaseolus vulgaris L.) is the most important legume for direct human consumption worldwide. It is a rich and relatively inexpensive source of proteins and micronutrients, especially iron and zinc. Bean is a target for biofortification to develop new cultivars with high Fe/Zn levels that help to ameliorate malnutrition mainly in developing countries. A strong negative phenotypic correlation between Fe/Zn concentration and yield is usually reported, posing a significant challenge for breeders. The objective of this study was to investigate the genetic relationship between Fe/Zn. We used Quantitative Trait Loci (QTLs) mapping and Genome-Wide Association Studies (GWAS) analysis in three bi-parental populations that included biofortified parents, identifying genomic regions associated with yield and micromineral accumulation. Significant negative correlations were observed between agronomic traits (pod harvest index, PHI; pod number, PdN; seed number, SdN; 100 seed weight, 100SdW; and seed per pod, Sd/Pd) and micronutrient concentration traits (SdFe and SdZn), especially between pod harvest index (PHI) and SdFe and SdZn. PHI presented a higher correlation with SdN than PdN. Seventy-nine QTLs were identified for the three populations: 14 for SdFe, 12 for SdZn, 13 for PHI, 11 for SdN, 14 for PdN, 6 for 100SdW, and 9 for Sd/Pd. Twenty-three hotspot regions were identified in which several QTLs were co-located, of which 13 hotpots displayed QTL of opposite effect for yield components and Fe/Zn accumulation. In contrast, eight QTLs for SdFe and six QTLs for SdZn were observed that segregated independently of QTL of yield components. The selection of these QTLs will enable enhanced levels of Fe/Zn and will not affect the yield performance of new cultivars focused on biofortification.

Identification of Quantitative Trait Loci Associated With Iron Deficiency Tolerance in Maize

Iron (Fe) is a limiting factor in crop growth and nutritional quality because of its low solubility. However, the current understanding of how major crops respond to Fe deficiency and the genetic basis remains limited. In the present study, Fe-efficient inbred line Ye478 and Fe-inefficient inbred line Wu312 and their recombinant inbred line (RIL) population were utilized to reveal the physiological and genetic responses of maize to low Fe stress. Compared with the Fe-sufficient conditions (+Fe: 200 μM), Fe-deficient supply (-Fe: 30 μM) significantly reduced shoot and root dry weights, leaf SPAD of Fe-efficient inbred line Ye478 by 31.4, 31.8, and 46.0%, respectively; decreased Fe-inefficient inbred line Wu312 by 72.0, 45.1, and 84.1%, respectively. Under Fe deficiency, compared with the supply of calcium nitrate (N1), supplying ammonium nitrate (N2) significantly increased the shoot and root dry weights of Wu312 by 37.5 and 51.6%, respectively; and enhanced Ye478 by 23.9 and 45.1%, respectively. Compared with N1, N2 resulted in a 70.0% decrease of the root Fe concentration for Wu312 in the -Fe treatment, N2 treatment reduced the root Fe concentration of Ye478 by 55.8% in the -Fe treatment. These findings indicated that, compared with only supplying nitrate nitrogen, combined supply of ammonium nitrogen and nitrate nitrogen not only contributed to better growth in maize but also significantly reduced Fe concentration in roots. In linkage analysis, ten quantitative trait loci (QTLs) associated with Fe deficiency tolerance were detected, explaining 6.2-12.0% of phenotypic variation. Candidate genes considered to be associated with the mechanisms underlying Fe deficiency tolerance were identified within a single locus or QTL co-localization, including ZmYS3, ZmPYE, ZmEIL3, ZmMYB153, ZmILR3 and ZmNAS4, which may form a sophisticated network to regulate the uptake, transport and redistribution of Fe. Furthermore, ZmYS3 was highly induced by Fe deficiency in the roots; ZmPYE and ZmEIL3, which may be involved in Fe homeostasis in strategy I plants, were significantly upregulated in the shoots and roots under low Fe stress; ZmMYB153 was Fe-deficiency inducible in the shoots. Our findings will provide a comprehensive insight into the physiological and genetic basis of Fe deficiency tolerance.

Delineating meta-quantitative trait loci for anthracnose resistance in common bean (Phaseolus vulgaris L.)

Anthracnose, caused by the fungus Colletotrichum lindemuthianum, is one of the devastating disease affecting common bean production and productivity worldwide. Several quantitative trait loci (QTLs) for anthracnose resistance have been identified. In order to make use of these QTLs in common bean breeding programs, a detailed meta-QTL (MQTL) analysis has been conducted. For the MQTL analysis, 92 QTLs related to anthracnose disease reported in 18 different earlier studies involving 16 mapping populations were compiled and projected on to the consensus map. This meta-analysis led to the identification of 11 MQTLs (each involving QTLs from at least two different studies) on 06 bean chromosomes and 10 QTL hotspots each involving multiple QTLs from an individual study on 07 chromosomes. The confidence interval (CI) of the identified MQTLs was found 3.51 times lower than the CI of initial QTLs. Marker-trait associations (MTAs) reported in published genome-wide association studies (GWAS) were used to validate nine of the 11 identified MQTLs, with MQTL4.1 overlapping with as many as 40 MTAs. Functional annotation of the 11 MQTL regions revealed 1,251 genes including several R genes (such as those encoding for NBS-LRR domain-containing proteins, protein kinases, etc.) and other defense related genes. The MQTLs, QTL hotspots and the potential candidate genes identified during the present study will prove useful in common bean marker-assisted breeding programs and in basic studies involving fine mapping and cloning of genomic regions associated with anthracnose resistance in common beans.

Characterization of pea seed nutritional value within a diverse population of Pisum sativum

Micronutrient malnutrition is a global concern that affects more than two billion people worldwide. Pea (Pisum sativum) is a nutritious pulse crop with potential to assist in tackling hidden hunger. Here we report seed ionomic data of 96 diverse pea accessions collected via inductively coupled plasma mass spectrometry (ICP-MS). We found a 100 g serving of peas provides the following average percent daily value for U.S. recommendations: 8% Ca, 39% Mg, 73% Cu, 37% Fe, 63% Mn, 45% Zn, 28% K, and 43% P. Correlations were observed between the majority of minerals tested suggesting strong interrelationships between mineral concentration levels. Hierarchical clustering identified fifteen accessions with high-ranking mineral concentrations. Thirty accessions could be compared to earlier inductively coupled optical emission spectrometry (ICP-OES) data, which revealed significant differences particularly for elements at extreme low or high levels of accumulation. These results improve our understanding of the range of variation in mineral content found in peas and provide additional mineral data resources for germplasm selection.

Comparative Genomic Analysis of Quantitative Trait Loci Associated With Micronutrient Contents, Grain Quality, and Agronomic Traits in Wheat (Triticum aestivum L.)

Comparative genomics and meta-quantitative trait loci (MQTLs) analysis are important tools for the identification of reliable and stable QTLs and functional genes controlling quantitative traits. We conducted a meta-analysis to identify the most stable QTLs for grain yield (GY), grain quality traits, and micronutrient contents in wheat. A total of 735 QTLs retrieved from 27 independent mapping populations reported in the last 13 years were used for the meta-analysis. The results showed that 449 QTLs were successfully projected onto the genetic consensus map which condensed to 100 MQTLs distributed on wheat chromosomes. This consolidation of MQTLs resulted in a three-fold reduction in the confidence interval (CI) compared with the CI for the initial QTLs. Projection of QTLs revealed that the majority of QTLs and MQTLs were in the non-telomeric regions of chromosomes. The majority of micronutrient MQTLs were located on the A and D genomes. The QTLs of thousand kernel weight (TKW) were frequently associated with QTLs for GY and grain protein content (GPC) with co-localization occurring at 55 and 63%, respectively. The co- localization of QTLs for GY and grain Fe was found to be 52% and for QTLs of grain Fe and Zn, it was found to be 66%. The genomic collinearity within Poaceae allowed us to identify 16 orthologous MQTLs (OrMQTLs) in wheat, rice, and maize. Annotation of promising candidate genes (CGs) located in the genomic intervals of the stable MQTLs indicated that several CGs (e.g., TraesCS2A02G141400, TraesCS3B02G040900, TraesCS4D02G323700, TraesCS3B02G077100, and TraesCS4D02G290900) had effects on micronutrients contents, yield, and yield-related traits. The mapping refinements leading to the identification of these CGs provide an opportunity to understand the genetic mechanisms driving quantitative variation for these traits and apply this information for crop improvement programs.

Genomic analysis of ionome-related QTLs in Arabidopsis thaliana

Ionome contributes to maintain cell integrity and acts as cofactors for catalyzing regulatory pathways. Identifying ionome contributing genomic regions provides a practical framework to dissect the genetic architecture of ionomic traits for use in biofortification. Meta-QTL (MQTL) analysis is a robust method to discover stable genomic regions for traits regardless of the genetic background. This study used information of 483 QTLs for ionomic traits identified from 12 populations for MQTL analysis in Arabidopsis thaliana. The selected QTLs were projected onto the newly constructed genetic consensus map and 33 MQTLs distributed on A. thaliana chromosomes were identified. The average confidence interval (CI) of the drafted MQTLs was 1.30 cM, reduced eight folds from a mean CI of 10.88 cM for the original QTLs. Four MQTLs were considered as stable MQTLs over different genetic backgrounds and environments. In parallel to the gene density over the A. thaliana genome, the genomic distribution of MQTLs over the genetic and physical maps indicated the highest density at non- and sub-telomeric chromosomal regions, respectively. Several candidate genes identified in the MQTLs intervals were associated with ion transportation, tolerance, and homeostasis. The genomic context of the identified MQTLs suggested nine chromosomal regions for Zn, Mn, and Fe control. The QTLs for potassium (K) and phosphorus (P) were the most frequently co-located with Zn (78.3%), Mn (76.2%), and Fe (88.2% and 70.6%) QTLs. The current MQTL analysis demonstrates that meta-QTL analysis is cheaper than, and as informative as genome-wide association study (GWAS) in refining the known QTLs.

Transition From Targeted Breeding to Mainstreaming of Biofortification Traits in Crop Improvement Programs

Biofortification breeding for three important micronutrients for human health, namely, iron (Fe), zinc (Zn), and provitamin A (PVA), has gained momentum in recent years. HarvestPlus, along with its global consortium partners, enhances Fe, Zn, and PVA in staple crops. The strategic and applied research by HarvestPlus is driven by product-based impact pathway that integrates crop breeding, nutrition research, impact assessment, advocacy, and communication to implement country-specific crop delivery plans. Targeted breeding has resulted in 393 biofortified crop varieties by the end of 2020, which have been released or are in testing in 63 countries, potentially benefitting more than 48 million people. Nevertheless, to reach more than a billion people by 2030, future breeding lines that are being distributed by Consultative Group on International Agricultural Research (CGIAR) centers and submitted by National Agricultural Research System (NARS) to varietal release committees should be biofortified. It is envisaged that the mainstreaming of biofortification traits will be driven by high-throughput micronutrient phenotyping, genomic selection coupled with speed breeding for accelerating genetic gains. It is noteworthy that targeted breeding gradually leads to mainstreaming, as the latter capitalizes on the progress made in the former. Efficacy studies have revealed the nutritional significance of Fe, Zn, and PVA biofortified varieties over non-biofortified ones. Mainstreaming will ensure the integration of biofortified traits into competitive varieties and hybrids developed by private and public sectors. The mainstreaming strategy has just been initiated in select CGIAR centers, namely, International Maize and Wheat Improvement Center (CIMMYT), International Rice Research Institute (IRRI), International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), International Institute of Tropical Agriculture (IITA), and International Center for Tropical Agriculture (CIAT). This review will present the key successes of targeted breeding and its relevance to the mainstreaming approaches to achieve scaling of biofortification to billions sustainably.

Meta-QTL and ortho-MQTL analyses identified genomic regions controlling rice yield, yield-related traits and root architecture under water deficit conditions

Meta-QTL (MQTL) analysis is a robust approach for genetic dissection of complex quantitative traits. Rice varieties adapted to non-flooded cultivation are highly desirable in breeding programs due to the water deficit global problem. In order to identify stable QTLs for major agronomic traits under water deficit conditions, we performed a comprehensive MQTL analysis on 563 QTLs from 67 rice populations published from 2001 to 2019. Yield and yield-related traits including grain weight, heading date, plant height, tiller number as well as root architecture-related traits including root dry weight, root length, root number, root thickness, the ratio of deep rooting and plant water content under water deficit condition were investigated. A total of 61 stable MQTLs over different genetic backgrounds and environments were identified. The average confidence interval of MQTLs was considerably refined compared to the initial QTLs, resulted in the identification of some well-known functionally characterized genes and several putative novel CGs for investigated traits. Ortho-MQTL mining based on genomic collinearity between rice and maize allowed identification of five ortho-MQTLs between these two cereals. The results can help breeders to improve yield under water deficit conditions.

Genome-wide association study and Mendelian randomization analysis provide insights for improving rice yield potential

Rice yield per plant has a complex genetic architecture, which is mainly determined by its three component traits: the number of grains per panicle (GPP), kilo-grain weight (KGW), and tillers per plant (TP). Exploring ideotype breeding based on selection for genetically less complex component traits is an alternative route for further improving rice production. To understand the genetic basis of the relationship between rice yield and component traits, we investigated the four traits of two rice hybrid populations (575 + 1495 F₁) in different environments and conducted meta-analyses of genome-wide association study (meta-GWAS). In total, 3589 significant loci for three components traits were detected, while only 3 loci for yield were detected. It indicated that rice yield is mainly controlled by minor-effect loci and hardly to be identified. Selecting quantitative trait locus/gene affected component traits to further enhance yield is recommended. Mendelian randomization design is adopted to investigate the genetic effects of loci on yield through component traits and estimate the genetic relationship between rice yield and its component traits by these loci. The loci for GPP or TP mainly had a positive genetic effect on yield, but the loci for KGW with different direction effects (positive effect or negative effect). Additionally, TP (Beta = 1.865) has a greater effect on yield than KGW (Beta = 1.016) and GPP (Beta = 0.086). Five significant loci for component traits that had an indirect effect on yield were identified. Pyramiding superior alleles of the five loci revealed improved yield. A combination of direct and indirect effects may better contribute to the yield potential of rice. Our findings provided a rationale for using component traits as indirect indices to enhanced rice yield, which will be helpful for further understanding the genetic basis of yield and provide valuable information for improving rice yield potential.

Genome-Wide Association Studies of Mineral Content in Common Bean

Micronutrient malnutrition is one of the main public health problems in many parts of the world. This problem raises the attention of all valuable sources of micronutrients for the human diet, such as common bean (Phaseolus vulgaris L.). In this research, a panel of 174 accessions representing Croatian common bean landraces was phenotyped for seed content of eight nutrients (N, P, K, Ca, Mg, Fe, Zn, and Mn), and genotyped using 6,311 high-quality DArTseq-derived SNP markers. A genome-wide association study (GWAS) was then performed to identify new genetic sources for improving seed mineral content. Twenty-two quantitative trait nucleotides (QTN) associated with seed nitrogen content were discovered on chromosomes Pv01, Pv02, Pv03, Pv05, Pv07, Pv08, and Pv10. Five QTNs were associated with seed phosphorus content, four on chromosome Pv07, and one on Pv08. A single significant QTN was found for seed calcium content on chromosome Pv09 and for seed magnesium content on Pv08. Finally, two QTNs associated with seed zinc content were identified on Pv06 while no QTNs were found to be associated with seed potassium, iron, or manganese content. Our results demonstrate the utility of GWAS for understanding the genetic architecture of seed nutritional traits in common bean and have utility for future enrichment of seed with macro- and micronutrients through genomics-assisted breeding.

Enhancing the Nutritional Quality of Major Food Crops Through Conventional and Genomics-Assisted Breeding

Nutritional stress is making over two billion world population malnourished. Either our commercially cultivated varieties of cereals, pulses, and oilseed crops are deficient in essential nutrients or the soils in which these crops grow are becoming devoid of minerals. Unfortunately, our major food crops are poor sources of micronutrients required for normal human growth. To overcome the problem of nutritional deficiency, greater emphasis should be laid on the identification of genes/quantitative trait loci (QTLs) pertaining to essential nutrients and their successful deployment in elite breeding lines through marker-assisted breeding. The manuscript deals with information on identified QTLs for protein content, vitamins, macronutrients, micro-nutrients, minerals, oil content, and essential amino acids in major food crops. These QTLs can be utilized in the development of nutrient-rich crop varieties. Genome editing technologies that can rapidly modify genomes in a precise way and will directly enrich the nutritional status of elite varieties could hold a bright future to address the challenge of malnutrition.

Biofortification of Common Bean for Higher Iron Concentration

Common bean (Phaseolus vulgaris L.) is a staple food of smallholder farmers and poor urban consumers in Latin America and eastern-southern Africa among whom iron deficiency is frequent. Bean was domesticated in Mexico and the southern Andes, creating two distinct gene pools. Evaluation of a core collection of 1,441 entries revealed average concentrations of 55 mg kg−1 iron. A breeding target was set at 44 mg kg−1 iron above the level in a local check variety, while 50% of goal or a 22 mg kg−1 advantage was accepted as “biofortified.” In a bioefficacy trial among college-age women in Rwanda, high iron beans improved iron status and enhanced cognitive ability, brain function, and work efficiency. However, breeding progress has been slow, likely due in part to homeostatic mechanisms whereby organisms moderate iron and zinc uptake. This phenomenon may represent resistance to increasing concentration of these elements. Crosses between gene pools may “jumble” genes for homeostasis and permit high levels. A second breeding strategy is the use of sister species that evolved in iron-poor environments and that could be more receptive to iron uptake. Future breeding may also increase attention on improving bioavailability through mechanisms such as non-or-slow darkening grain or low phytate mutants. Changing dietary patterns in developed countries could increase iron deficiency and create demand for iron biofortified beans.

Genetic mapping for agronomic traits in a MAGIC population of common bean (Phaseolus vulgaris L.) under drought conditions

BACKGROUND

Common bean is an important staple crop in the tropics of Africa, Asia and the Americas. Particularly smallholder farmers rely on bean as a source for calories, protein and micronutrients. Drought is a major production constraint for common bean, a situation that will be aggravated with current climate change scenarios. In this context, new tools designed to understand the genetic basis governing the phenotypic responses to abiotic stress are required to improve transfer of desirable traits into cultivated beans.

RESULTS

A multiparent advanced generation intercross (MAGIC) population of common bean was generated from eight Mesoamerican breeding lines representing the phenotypic and genotypic diversity of the CIAT Mesoamerican breeding program. This population was assessed under drought conditions in two field trials for yield, 100 seed weight, iron and zinc accumulation, phenology and pod harvest index. Transgressive segregation was observed for most of these traits. Yield was positively correlated with yield components and pod harvest index (PHI), and negative correlations were found with phenology traits and micromineral contents. Founder haplotypes in the population were identified using Genotyping by Sequencing (GBS). No major population structure was observed in the population. Whole Genome Sequencing (WGS) data from the founder lines was used to impute genotyping data for GWAS. Genetic mapping was carried out with two methods, using association mapping with GWAS, and linkage mapping with haplotype-based interval screening. Thirteen high confidence QTL were identified using both methods and several QTL hotspots were found controlling multiple traits. A major QTL hotspot located on chromosome Pv01 for phenology traits and yield was identified. Further hotspots affecting several traits were observed on chromosomes Pv03 and Pv08. A major QTL for seed Fe content was contributed by MIB778, the founder line with highest micromineral accumulation. Based on imputed WGS data, candidate genes are reported for the identified major QTL, and sequence changes were identified that could cause the phenotypic variation.

CONCLUSIONS

This work demonstrates the importance of this common bean MAGIC population for genetic mapping of agronomic traits, to identify trait associations for molecular breeding tool design and as a new genetic resource for the bean research community.

European landrace diversity for common bean biofortification: a genome-wide association study

Mineral deficiencies represent a global challenge that needs to be urgently addressed. An adequate intake of iron and zinc results in a balanced diet that reduces chances of impairment of many metabolic processes that can lead to clinical consequences. In plants, bioavailability of such nutrients is reduced by presence of compounds such as phytic acid, that can chelate minerals and reduce their absorption. Biofortification of common bean (Phaseolus vulgaris L.) represents an important strategy to reduce mineral deficiencies, especially in areas of the world where this crop plays a key role in the diet. In this study, a panel of diversity encompassing 192 homozygous genotypes, was screened for iron, zinc and phytate seed content. Results indicate a broad variation of these traits and allowed the identification of accessions reasonably carrying favourable trait combinations. A significant association between zinc seed content and some molecular SNP markers co-located on the common bean Pv01 chromosome was detected by means of genome-wide association analysis. The gene Phvul001G233500, encoding for an E3 ubiquitin-protein ligase, is proposed to explain detected associations. This result represents a preliminary evidence that can foster future research aiming at understanding the genetic mechanisms behind zinc accumulation in beans.

Genome-Wide SNP Identification and Association Mapping for Seed Mineral Concentration in Mung Bean (Vigna radiata L.)

Mung bean (Vigna radiata L.) quality is dependent on seed chemical composition, which in turn determines the benefits of its consumption for human health and nutrition. While mung bean is rich in a range of nutritional components, such as protein, carbohydrates and vitamins, it remains less well studied than other legume crops in terms of micronutrients. In addition, mung bean genomics and genetic resources are relatively sparse. The objectives of this research were three-fold, namely: to develop a genome-wide marker system for mung bean based on genotyping by sequencing (GBS), to evaluate diversity of mung beans available to breeders in the United States and finally, to perform a genome-wide association study (GWAS) for nutrient concentrations based on a seven mineral analysis using inductively coupled plasma (ICP) spectroscopy. All parts of our research were performed with 95 cultivated mung bean genotypes chosen from the USDA core collection representing accessions from 13 countries. Overall, we identified a total of 6,486 high quality single nucleotide polymorphisms (SNPs) from the GBS dataset and found 43 marker × trait associations (MTAs) with calcium, iron, potassium, manganese, phosphorous, sulfur or zinc concentrations in mung bean grain produced in either of two consecutive years' field experiments. The MTAs were scattered across 35 genomic regions explaining on average 22% of the variation for each seed nutrient in each year. Most of the gene regions provided valuable candidate loci to use in future breeding of new varieties of mung bean and further the understanding of genetic control of nutritional properties in the crop. Other SNPs identified in this study will serve as important resources to enable marker-assisted selection (MAS) for nutritional improvement in mung bean and to analyze cultivars of mung bean.

Selection of candidate genes controlling veraison time in grapevine through integration of meta-QTL and transcriptomic data

BACKGROUND

High temperature during grape berry ripening impairs the quality of fruits and wines. Veraison time, which marks ripening onset, is a key factor for determining climatic conditions during berry ripening. Understanding its genetic control is crucial to successfully breed varieties more adapted to a changing climate. Quantitative trait loci (QTL) studies attempting to elucidate the genetic determinism of developmental stages in grapevine have identified wide genomic regions. Broad scale transcriptomic studies, by identifying sets of genes modulated during berry development and ripening, also highlighted a huge number of putative candidates.

RESULTS

With the final aim of providing an overview about available information on the genetic control of grapevine veraison time, and prioritizing candidates, we applied a meta-QTL analysis for grapevine phenology-related traits and checked for co-localization of transcriptomic candidates. A consensus genetic map including 3130 markers anchored to the grapevine genome assembly was compiled starting from 39 genetic maps. Two thousand ninety-three QTLs from 47 QTL studies were projected onto the consensus map, providing a comprehensive overview about distribution of available QTLs and revealing extensive co-localization especially across phenology related traits. From 141 phenology related QTLs we generated 4 veraison meta-QTLs located on linkage group (LG) 1 and 2, and 13 additional meta-QTLs connected to the veraison time genetic control, among which the most relevant were located on LG 14, 16 and 18. Functional candidates in these intervals were inspected. Lastly, taking advantage of available transcriptomic datasets, expression data along berry development were integrated, in order to pinpoint among positional candidates, those differentially expressed across the veraison transition.

CONCLUSION

Integration of meta-QTLs analysis on available phenology related QTLs and data from transcriptomic dataset allowed to strongly reduce the number of candidate genes for the genetic control of the veraison transition, prioritizing a list of 272 genes, among which 78 involved in regulation of gene expression, signal transduction or development.

Iron Biofortification of Staple Crops: Lessons and Challenges in Plant Genetics

Plants are the ultimate source of iron in our diet, either directly as staple crops and vegetables or indirectly via animal fodder. Increasing the iron concentration of edible parts of plants, known as biofortification, is seen as a sustainable approach to alleviate iron deficiency which is a major global health issue. Advances in sequencing and gene technology are accelerating both forward and reverse genetic approaches. In this review, we summarize recent progress in iron biofortification using conventional plant breeding or transgenics. Interestingly, some of the gene targets already used for transgenic approaches are also identified as genetic factors for high iron in genome-wide association studies. Several quantitative trait loci and transgenes increase both iron and zinc, due to overlap in transporters and chelators for these two mineral micronutrients. Research efforts are predominantly aimed at increasing the total concentration of iron but enhancing its bioavailability is also addressed. In particular, increased biosynthesis of the metal chelator nicotianamine increases iron and zinc levels and improves bioavailability. The achievements to date are very promising in being able to provide sufficient iron in diets with less reliance on meat to feed a growing world population.

The Germ Fraction Inhibits Iron Bioavailability of Maize: Identification of an Approach to Enhance Maize Nutritional Quality via Processing and Breeding

Improving the nutritional quality of Fe in maize (Zea mays) represents a biofortification strategy to alleviate iron deficiency anemia. Therefore, the present study measured iron content and bioavailability via an established bioassay to characterize Fe quality in parts of the maize kernel. Comparisons of six different varieties of maize demonstrated that the germ fraction is a strong inhibitory component of Fe bioavailability. The germ fraction can contain 27-54% of the total kernel Fe, which is poorly available. In the absence of the germ, Fe in the non-germ components can be highly bioavailable. More specifically, increasing Fe concentration in the non-germ fraction resulted in more bioavailable Fe. Comparison of wet-milled fractions of a commercial maize variety and degerminated corn meal products also demonstrated the inhibitory effect of the germ fraction on Fe bioavailability. When compared to beans (Phaseolus vulgaris) containing approximately five times the concentration of Fe, degerminated maize provided more absorbable Fe, indicating substantially higher fractional bioavailability. Overall, the results indicate that degerminated maize may be a better source of Fe than whole maize and some other crops. Increased non-germ Fe density with a weaker inhibitory effect of the germ fraction are desirable qualities to identify and breed for in maize.