QTL analyses for tolerance to abiotic stresses in a common bean (Phaseolus vulgaris L.) population

Plant Biotechnology-An Indispensable Tool for Crop Improvement

Traditional plant breeding has helped to increase food production dramatically over the past five decades, and many countries have managed to produce enough food for the growing population, particularly in the developing world [...].

Mapping yield and yield-related traits using diverse common bean germplasm

Common bean (bean) is one of the most important legume crops, and mapping genes for yield and yield-related traits is essential for its improvement. However, yield is a complex trait that is typically controlled by many loci in crop genomes. The objective of this research was to identify regions in the bean genome associated with yield and a number of yield-related traits using a collection of 121 diverse bean genotypes with different yields. The beans were evaluated in replicated trials at two locations, over two years. Significant variation among genotypes was identified for all traits analyzed in the four environments. The collection was genotyped with the BARCBean6K_3 chip (5,398 SNPs), two yield/antiyield gene-based markers, and seven markers previously associated with resistance to common bacterial blight (CBB), including a Niemann-Pick polymorphism (NPP) gene-based marker. Over 90% of the single-nucleotide polymorphisms (SNPs) were polymorphic and separated the panel into two main groups of small-seeded and large-seeded beans, reflecting their Mesoamerican and Andean origins. Thirty-nine significant marker-trait associations (MTAs) were identified between 31 SNPs and 15 analyzed traits on all 11 bean chromosomes. Some of these MTAs confirmed genome regions previously associated with the yield and yield-related traits in bean, but a number of associations were not reported previously, especially those with derived traits. Over 600 candidate genes with different functional annotations were identified for the analyzed traits in the 200-Kb region centered on significant SNPs. Fourteen SNPs were identified within the gene model sequences, and five additional SNPs significantly associated with five different traits were located at less than 0.6 Kb from the candidate genes. The work confirmed associations between two yield/antiyield gene-based markers (AYD1m and AYD2m) on chromosome Pv09 with yield and identified their association with a number of yield-related traits, including seed weight. The results also confirmed the usefulness of the NPP marker in screening for CBB resistance. Since disease resistance and yield measurements are environmentally dependent and labor-intensive, the three gene-based markers (CBB- and two yield-related) and quantitative trait loci (QTL) that were validated in this work may be useful tools for simplifying and accelerating the selection of high-yielding and CBB-resistant bean cultivars.

Combination of meta-analysis of QTL and GWAS to uncover the genetic architecture of seed yield and seed yield components in common bean

Increasing seed yield in common bean could help to improve food security and reduce malnutrition globally due to the high nutritional quality of this crop. However, the complex genetic architecture and prevalent genotype by environment interactions for seed yield makes increasing genetic gains challenging. The aim of this study was to identify the most consistent genomic regions related with seed yield components and phenology reported in the last 20 years in common bean. A meta-analysis of quantitative trait locus (QTL) for seed yield components and phenology (MQTL-YC) was performed for 394 QTL reported in 21 independent studies under sufficient water and drought conditions. In total, 58 MQTL-YC over different genetic backgrounds and environments were identified, reducing threefold on average the confidence interval (CI) compared with the CI for the initial QTL. Furthermore, 40 MQTL-YC identified were co-located with 210 SNP peak positions reported via genome-wide association (GWAS), guiding the identification of candidate genes. Comparative genomics among these MQTL-YC with MQTL-YC reported in soybean and pea allowed the identification of 14 orthologous MQTL-YC shared across species. The integration of MQTL-YC, GWAS, and comparative genomics used in this study is useful to uncover and refine the most consistent genomic regions related with seed yield components for their use in plant breeding.

Genome-wide characterization and comparative analysis of the OSCA gene family and identification of its potential stress-responsive members in legumes

Cicer arietinum, Cajanus cajan, Vigna radiata, and Phaseolus vulgaris are economically important legume crops with high nutritional value. They are negatively impacted globally by different biotic and abiotic stresses. Hyperosmolality-gated calcium-permeable channels (OSCA) have been characterized as osmosensors in Arabidopsis thaliana but have not previously reported in legumes. This study provides a genome-wide identification, characterization, and comparative analysis of OSCA genes in legumes. Our study identified and characterized 13 OSCA genes in C. cajan, V. radiata, P. vulgaris, and 12 in C. arietinum, classified into four distinct clades. We found evidence to suggest that the OSCAs might be involved in the interaction between hormone signalling pathways and stress signalling pathways. Furthermore, they play a major role in plant growth and development. The expression levels of the OSCAs vary under different stress conditions in a tissue-specific manner. Our study can be used to develop a detailed understanding of stress regulatory mechanisms of the OSCA gene family in legumes.

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.

Recent advancement in OMICS approaches to enhance abiotic stress tolerance in legumes

The world is facing rapid climate change and a fast-growing global population. It is believed that the world population will be 9.7 billion in 2050. However, recent agriculture production is not enough to feed the current population of 7.9 billion people, which is causing a huge hunger problem. Therefore, feeding the 9.7 billion population in 2050 will be a huge target. Climate change is becoming a huge threat to global agricultural production, and it is expected to become the worst threat to it in the upcoming years. Keeping this in view, it is very important to breed climate-resilient plants. Legumes are considered an important pillar of the agriculture production system and a great source of high-quality protein, minerals, and vitamins. During the last two decades, advancements in OMICs technology revolutionized plant breeding and emerged as a crop-saving tool in wake of the climate change. Various OMICs approaches like Next-Generation sequencing (NGS), Transcriptomics, Proteomics, and Metabolomics have been used in legumes under abiotic stresses. The scientific community successfully utilized these platforms and investigated the Quantitative Trait Loci (QTL), linked markers through genome-wide association studies, and developed KASP markers that can be helpful for the marker-assisted breeding of legumes. Gene-editing techniques have been successfully proven for soybean, cowpea, chickpea, and model legumes such as Medicago truncatula and Lotus japonicus. A number of efforts have been made to perform gene editing in legumes. Moreover, the scientific community did a great job of identifying various genes involved in the metabolic pathways and utilizing the resulted information in the development of climate-resilient legume cultivars at a rapid pace. Keeping in view, this review highlights the contribution of OMICs approaches to abiotic stresses in legumes. We envisage that the presented information will be helpful for the scientific community to develop climate-resilient legume cultivars.

Genetic Augmentation of Legume Crops Using Genomic Resources and Genotyping Platforms for Nutritional Food Security

Recent advances in next generation sequencing (NGS) technologies have led the surge of genomic resources for the improvement legume crops. Advances in high throughput genotyping (HTG) and high throughput phenotyping (HTP) enable legume breeders to improve legume crops more precisely and efficiently. Now, the legume breeder can reshuffle the natural gene combinations of their choice to enhance the genetic potential of crops. These genomic resources are efficiently deployed through molecular breeding approaches for genetic augmentation of important legume crops, such as chickpea, cowpea, pigeonpea, groundnut, common bean, lentil, pea, as well as other underutilized legume crops. In the future, advances in NGS, HTG, and HTP technologies will help in the identification and assembly of superior haplotypes to tailor the legume crop varieties through haplotype-based breeding. This review article focuses on the recent development of genomic resource databases and their deployment in legume molecular breeding programmes to secure global food security.

Contrasting Phaseolus Crop Water Use Patterns and Stomatal Dynamics in Response to Terminal Drought

Terminal drought stress affects more than half of the areas planted with common bean (Phaseolus vulgaris), the main food legume globally, generating severe yield losses. Phenotyping water deficit responses and water use are central strategies to develop improved terminal drought resilience. The exploration and exploitation of genetic diversity in breeding programs are gaining importance, with a particular interest in related species with great adaptation to biotic and abiotic factors. This is the case with tepary beans (Phaseolus acutifolius), a bean that evolved and was domesticated in arid conditions and is considered well adapted to drought and heat stress. Under greenhouse conditions, using one genotype of tepary beans (resistant to drought) and two of common beans (one resistant and one susceptible to terminal drought), we evaluated phenotypic differences in traits such as water use efficiency (WUE), transpiration efficiency, rate of photosynthesis, photosynthetic efficiency, stomatal density, stomatal index, stomatal size, and the threshold for transpiration decline under well-watered and terminal drought conditions. Our results indicate two different water use strategies in drought-resistant genotypes: one observed in common bean aimed at conserving soil water by closing stomata early, inhibiting stomatal development, and limiting growth; and the other observed in tepary bean, where prolonged stomatal opening and higher carbon fixation, combined with no changes in stomata distribution, lead to higher biomass accumulation. Strategies that contribute to drought adaptation combined with other traits, such as greater mobilization of photoassimilates to the formation of reproductive structures, confer bean drought resistance and are useful targets in breeding programs.

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.

Heterogeneous effects of climatic conditions on Andean bean landraces and cowpeas highlight alternatives for crop management and conservation

The use and conservation of agrobiodiversity have become critical to face the actual and future challenges imposed by climate change. Collecting phytogenetic resources is a first step for their conservation; however, the genetic material must be analysed to understand their potential to improve agricultural resilience and adaptation to the new climatic conditions. We have selected nine Phaseolus vulgaris, one P. lunatus and two Vigna unguiculata landraces from two different climatic backgrounds of the Andean region of South Ecuador and one P. vulgaris commercial cultivar, and we grew them under two different conditions of temperature and humidity (open field and greenhouse). Then, we recorded data for 32 characters of plant architecture, flower and fruit characteristics and yield, and 17 events in the phenology of the plants. We analysed the impact of treatment on species, climatic background, and each of the landraces, and identified both characters and landraces that are mostly affected by changes in their environmental conditions. Overall, higher temperatures were benign for all materials except for two P. vulgaris landraces from cold background, which performed better or developed faster under cold conditions. Finally, we calculated a climate resilience landrace index, which allowed us to classify the landraces by their plasticity to new environmental conditions, and found heterogeneous landrace susceptibility to warmer conditions. Two P. vulgaris landraces were highlighted as critical targets for conservation.

Water Shortage Affects Vegetative and Reproductive Stages of Common Bean (Phaseolus vulgaris) Chilean Landraces, Differentially Impacting Grain Yield Components

Water availability for agricultural use is currently a global problem that worsens with climate change in several regions of the world. Among grain legumes, common bean (Phaseolus vulgaris) is the most cultivated in the worldwide. The Chilean germplasm of common bean is characterized by tolerance to water stress. Here, we analyzed a selection of nine ancient Chilean landraces in regard to their drought tolerance, simulating optimal (OW) and restricted watering (RW) in a Mediterranean environment. Phenological, growth, and yield traits were recorded, and correlation analysis was performed. Accordingly, leaf temperature and osmotic potential were higher under RW, while the leaf chlorophyll content decreased in all landraces. Physiological maturity days and seed-filling days were lower in RW than in OW. This similarly occurred with the grain yield. The % yield reduction was negatively correlated with the % pod reduction and the relative rate of leaf expansion (RLAE) reduction. However, the 100-seed weight value was not significantly modified by water treatment (p > 0.05). For instance, landraces that preferred to fill the grain with a lower rate of leaf expansion showed a lower loss in grain yield under drought conditions. These results suggest that the resource partitioning between growing leaves, flowers, and developing pods in Chilean landraces is variable, affecting the common bean drought tolerance.

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.

Fab Advances in Fabaceae for Abiotic Stress Resilience: From 'Omics' to Artificial Intelligence

Legumes are a better source of proteins and are richer in diverse micronutrients over the nutritional profile of widely consumed cereals. However, when exposed to a diverse range of abiotic stresses, their overall productivity and quality are hugely impacted. Our limited understanding of genetic determinants and novel variants associated with the abiotic stress response in food legume crops restricts its amelioration. Therefore, it is imperative to understand different molecular approaches in food legume crops that can be utilized in crop improvement programs to minimize the economic loss. 'Omics'-based molecular breeding provides better opportunities over conventional breeding for diversifying the natural germplasm together with improving yield and quality parameters. Due to molecular advancements, the technique is now equipped with novel 'omics' approaches such as ionomics, epigenomics, fluxomics, RNomics, glycomics, glycoproteomics, phosphoproteomics, lipidomics, regulomics, and secretomics. Pan-omics-which utilizes the molecular bases of the stress response to identify genes (genomics), mRNAs (transcriptomics), proteins (proteomics), and biomolecules (metabolomics) associated with stress regulation-has been widely used for abiotic stress amelioration in food legume crops. Integration of pan-omics with novel omics approaches will fast-track legume breeding programs. Moreover, artificial intelligence (AI)-based algorithms can be utilized for simulating crop yield under changing environments, which can help in predicting the genetic gain beforehand. Application of machine learning (ML) in quantitative trait loci (QTL) mining will further help in determining the genetic determinants of abiotic stress tolerance in pulses.

Genetic Mapping for Agronomic Traits in IAPAR 81/LP97-28 Population of Common Bean (Phaseolus vulgaris L.) under Drought Conditions

One of the significant challenges of common bean breeding is developing cultivars with high yields under drought conditions. The present study attempted to map quantitative trait loci (QTLs) and identify molecular markers that are linked to drought tolerance in the common bean. We evaluated 160 recombinant inbred lines (RILs), derived from the cross between the carioca cultivars IAPAR 81 (drought tolerant) and LP97-28 (susceptible to drought). In 2014 and 2015, two experiments were conducted (DS-drought stress, and NS-no drought stress). In the DS experiment, water suppression was performed at the flowering stages R5 to R6. The results of our experiments showed that drought conditions play an essential role in reducing most of the traits that were evaluated. RILs under drought conditions reduced the grain yield by 62.03% and 24% in 2014 and 2015, respectively. We identified 15 quantitative trait loci distributed on the chromosomes Pv01, Pv02, Pv03, Pv07, Pv08, Pv09, Pv10, and Pv11, related to grain yield, seed yield per day, 100-seed weight, number of pods per plant, plant height, number of days for flowering, and number of days to maturity. The characteristics of seed yield per day, 100-seed weight, and number of days to maturity showed that QTLs colocalized on Pv07. Identifying QTLs that are linked to drought tolerance in the RIL population IAPAR 81 × LP97-28 is of particular importance for common bean breeding programs seeking to improve carioca beans that are cultivated in regions with drought conditions, such as Brazil.

Physiological and genetic characterization of heat stress effects in a common bean RIL population

Heat stress is a major abiotic stress factor reducing crop productivity and climate change models predict increasing temperatures in many production regions. Common bean (Phaseolus vulgaris L.) is an important crop for food security in the tropics and heat stress is expected to cause increasing yield losses. To study physiological responses and to characterize the genetics of heat stress tolerance, we evaluated the recombinant inbred line (RIL) population IJR (Indeterminate Jamaica Red) x AFR298 of the Andean gene pool. Heat stress (HS) conditions in the field affected many traits across the reproductive phase. High nighttime temperatures appeared to have larger effects than maximum daytime temperatures. Yield was reduced compared to non-stress conditions by 37% and 26% in 2016 and 2017 seasons, respectively. The image analysis tool HYRBEAN was developed to evaluate pollen viability (PolVia). A significant reduction of PolVia was observed in HS and higher viability was correlated with yield only under stress conditions. In susceptible lines the reproductive phase was extended and defects in the initiation of seed, seed fill and seed formation were identified reducing grain quality. Higher yields under HS were correlated with early flowering, high pollen viability and effective seed filling. Quantitative trait loci (QTL) analysis revealed a QTL for both pod harvest index and PolVia on chromosome Pv05, for which the more heat tolerant parent IJR contributed the positive allele. Also, on chromosome Pv08 a QTL from IJR improved PolVia and the yield component pods per plant. HS affected several traits during the whole reproductive development, from floral induction to grain quality traits, indicating a general heat perception affecting many reproductive processes. Identification of tolerant germplasm, indicator traits for heat tolerance and molecular tools will help to breed heat tolerant varieties to face future climate change effects.

Ancient relaxation of an obligate short-day requirement in common bean through loss of CONSTANS-like gene function

Common bean (Phaseolus vulgaris L.) is a major global food staple and source of dietary protein that was domesticated independently in Mexico and Andean South America. Its subsequent development as a crop of importance worldwide has been enabled by genetic relaxation of the strict short-day requirement typical of wild forms, but the genetic basis for this change is not well understood. Recently, a loss of photoperiod sensitivity was shown to result from mutations in the phytochrome photoreceptor gene Ppd/PHYA3 that arose independently within the two major domesticated lineages. Here, we define a second major photoperiod sensitivity locus, at which recessive alleles associate with deleterious mutations affecting the CONSTANS-like gene COL2. A wider survey of sequence variation in over 800 diverse lines, including wild, landrace, and domesticated accessions, show that distinct col2 haplotypes are associated with early flowering in Andean and Mesoamerican germplasm. The relative frequencies and distributions of COL2 and PHYA3 haplotypes imply that photoperiod adaptation developed in two phases within each gene pool: an initial reduction in sensitivity through impairment of COL2 function and subsequent complete loss through PHYA3. Gene expression analyses indicate that COL2 functions downstream of PHYA3 to repress expression of FT genes and may function in parallel with PvE1, the bean ortholog of a key legume-specific flowering repressor. Collectively, these results define the molecular basis for a key phenological adaptation, reveal a striking convergence in the naturally replicated evolution of this major crop, and further emphasize the wider evolutionary lability of CONSTANS effects on flowering time control.

Allelic Diversity at Abiotic Stress Responsive Genes in Relationship to Ecological Drought Indices for Cultivated Tepary Bean, Phaseolus acutifolius A. Gray, and Its Wild Relatives

Some of the major impacts of climate change are expected in regions where drought stress is already an issue. Grain legumes are generally drought susceptible. However, tepary bean and its wild relatives within Phaseolus acutifolius or P. parvifolius are from arid areas between Mexico and the United States. Therefore, we hypothesize that these bean accessions have diversity signals indicative of adaptation to drought at key candidate genes such as: Asr2, Dreb2B, and ERECTA. By sequencing alleles of these genes and comparing to estimates of drought tolerance indices from climate data for the collection site of geo-referenced, tepary bean accessions, we determined the genotype x environmental association (GEA) of each gene. Diversity analysis found that cultivated and wild P. acutifolius were intermingled with var. tenuifolius and P. parvifolius, signifying that allele diversity was ample in the wild and cultivated clade over a broad sense (sensu lato) evaluation. Genes Dreb2B and ERECTA harbored signatures of directional selection, represented by six SNPs correlated with the environmental drought indices. This suggests that wild tepary bean is a reservoir of novel alleles at genes for drought tolerance, as expected for a species that originated in arid environments. Our study corroborated that candidate gene approach was effective for marker validation across a broad genetic base of wild tepary accessions.

Environmentally stable common bean genotypes for production in different agro-ecological zones of Tanzania

Genotype by environment interaction (GxE) complicates the process of selecting genotypes suitable for quantitative traits like seed yield in beans, hence slows down the development and release of varieties by breeding programs. GxE study on seed yield in beans enables identification of stable genotypes across sites and best site(s) for discriminating the tested genotypes in terms of seed yield. The purpose of this study was to evaluate the influence of the environment, genotype, and genotype by environment interaction on seed yield stability and adaptability of common bean landraces, lines, and improved varieties across three different agro-ecologies in Tanzania. The 99 common bean genotypes (Landraces, lines, and improved varieties) were planted following alpha lattice design in three replications each contained five blocks with 20 plots. Soil properties from the experimental sites, days to 75% flowering, Seed yield, 100 seed weight, number of seeds/pod, and number of pods/plant were recorded. Data on seed yield and its components were analyzed using Additive main effect and multiplicative interaction (AMMI), genotype main effects plus genotype × environment interaction (GGE), and yield stability index (YSI). The AMMI revealed very highly significant (P ≤ 0.001) effects of genotypes, environmental, and genotype × environment interaction on all the traits. AMMI analysis revealed that genotype main effects accounted for 39.3% of the total sum square of seed yield, whereas the environment and genotype × environmental interaction accounted for 31.4% and 26.8 % respectively. Genotype main effects largely influenced the variation in days to 75% flowering (55.5%), number of pods/plant (49.2%), number of seeds/pod (73.3%), and 100 seed weight (71.2%). Among soil properties recorded, available soil phosphorus, soil pH, soil exchangeable K, Ca, and Na had a strong positive association with common bean seed yield, while soil organic carbon and total nitrogen exhibited a strong negative association with seed yield. GGE revealed that E1 (TARI-Selian) was the most discriminative and representative site for common bean genotypes seed yield. Based on the yield stability index, the most stable and high seed yielding genotypes were ACC 714, Selian 14, Selian 9, Katuku, and Msolini. The identified high seed yielding and stable genotypes can be further tested in participatory variety selection involving farmers and later on released as varieties and can also be used for different breeding purposes in different agro-ecologies of Tanzania.

Common bean SNP alleles and candidate genes affecting photosynthesis under contrasting water regimes

Water deficit is a major worldwide constraint to common bean (Phaseolus vulgaris L.) production, being photosynthesis one of the most affected physiological processes. To gain insights into the genetic basis of the photosynthetic response of common bean under water-limited conditions, a collection of 158 Portuguese accessions was grown under both well-watered and water-deficit regimes. Leaf gas-exchange parameters were measured and photosynthetic pigments quantified. The same collection was genotyped using SNP arrays, and SNP-trait associations tested considering a linear mixed model accounting for the genetic relatedness among accessions. A total of 133 SNP-trait associations were identified for net CO2 assimilation rate, transpiration rate, stomatal conductance, and chlorophylls a and b, carotenes, and xanthophyll contents. Ninety of these associations were detected under water-deficit and 43 under well-watered conditions, with only two associations common to both treatments. Identified candidate genes revealed that stomatal regulation, protein translocation across membranes, redox mechanisms, hormone, and osmotic stress signaling were the most relevant processes involved in common bean response to water-limited conditions. These candidates are now preferential targets for common bean water-deficit-tolerance breeding. Additionally, new sources of water-deficit tolerance of Andean, Mesoamerican, and admixed origin were detected as accessions valuable for breeding, and not yet explored.

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.

Genome-Wide Association Studies Detect Multiple QTLs for Productivity in Mesoamerican Diversity Panel of Common Bean Under Drought Stress

Drought stress is an important abiotic factor limiting common bean yield, with great impact on the production worldwide. Understanding the genetic basis regulating beans' yield and seed weight (SW) is a fundamental prerequisite for the development of superior cultivars. The main objectives of this work were to conduct genome-wide marker discovery by genotyping a Mesoamerican panel of common bean germplasm, containing cultivated and landrace accessions of broad origin, followed by the identification of genomic regions associated with productivity under two water regimes using different genome-wide association study (GWAS) approaches. A total of 11,870 markers were genotyped for the 339 genotypes, of which 3,213 were SilicoDArT and 8,657 SNPs derived from DArT and CaptureSeq. The estimated linkage disequilibrium extension, corrected for structure and relatedness (r ² _sv ), was 98.63 and 124.18 kb for landraces and breeding lines, respectively. Germplasm was structured into landraces and lines/cultivars. We carried out GWASs for 100-SW and yield in field environments with and without water stress for 3 consecutive years, using single-, segment-, and gene-based models. Higher number of associations at high stringency was identified for the SW trait under irrigation, totaling ∼185 QTLs for both single- and segment-based, whereas gene-based GWASs showed ∼220 genomic regions containing ∼650 genes. For SW under drought, 18 QTLs were identified for single- and segment-based and 35 genes by gene-based GWASs. For yield, under irrigation, 25 associations were identified, whereas under drought the total was 10 using both approaches. In addition to the consistent associations detected across experiments, these GWAS approaches provided important complementary QTL information (∼221 QTLs; 650 genes; r ² from 0.01% to 32%). Several QTLs were mined within or near candidate genes playing significant role in productivity, providing better understanding of the genetic mechanisms underlying these traits and making available molecular tools to be used in marker-assisted breeding. The findings also allowed the identification of genetic material (germplasm) with better yield performance under drought, promising to a common bean breeding program. Finally, the availability of this highly diverse Mesoamerican panel is of great scientific value for the analysis of any relevant traits in common bean.

Genomic Prediction of Agronomic Traits in Common Bean (Phaseolus vulgaris L.) Under Environmental Stress

In plant and animal breeding, genomic prediction models are established to select new lines based on genomic data, without the need for laborious phenotyping. Prediction models can be trained on recent or historic phenotypic data and increasingly available genotypic data. This enables the adoption of genomic selection also in under-used legume crops such as common bean. Beans are an important staple food in the tropics and mainly grown by smallholders under limiting environmental conditions such as drought or low soil fertility. Therefore, genotype-by-environment interactions (G × E) are an important consideration when developing new bean varieties. However, G × E are often not considered in genomic prediction models nor are these models implemented in current bean breeding programs. Here we show the prediction abilities of four agronomic traits in common bean under various environmental stresses based on twelve field trials. The dataset includes 481 elite breeding lines characterized by 5,820 SNP markers. Prediction abilities over all twelve trials ranged between 0.6 and 0.8 for yield and days to maturity, respectively, predicting new lines into new seasons. In all four evaluated traits, the prediction abilities reached about 50-80% of the maximum accuracies given by phenotypic correlations and heritability. Predictions under drought and low phosphorus stress were up to 10 and 20% improved when G × E were included in the model, respectively. Our results demonstrate the potential of genomic selection to increase the genetic gain in common bean breeding. Prediction abilities improved when more phenotypic data was available and G × E could be accounted for. Furthermore, the developed models allowed us to predict genotypic performance under different environmental stresses. This will be a key factor in the development of common bean varieties adapted to future challenging conditions.

Effect of Water Deficit on Morphoagronomic and Physiological Traits of Common Bean Genotypes with Contrasting Drought Tolerance

Water deficit is considered one of the most limiting factors of the common bean. Understanding the adaptation mechanisms of the crop to this stress is fundamental for the development of drought-tolerant cultivars. In this sense, the objective of this study was to analyze the influence of water deficit on physiological and morphoagronomic traits of common bean genotypes with contrasting drought tolerance, aiming to identify mechanisms associated with tolerance to water deficit. The experiment was carried out in a greenhouse, arranged in a randomized complete block 4 × 2 factorial design, consisting of four common bean genotypes under two water regimes (with and without water stress), with six replications. The morphoagronomic and physiological traits of four cultivars, two drought-tolerant (IAPAR 81 and BAT 477) and two drought-sensitive (IAC Tybatã and BRS Pontal), were measured for 0, 4, 8, and 12 days, under water deficit, initiated in the phenological stage R5. Water-deficit induced physiological changes in the plants, altering the evaluated morphoagronomic traits. The drought tolerance of cultivar BAT 477 is not only a direct result of the low influence of water deficit on its yield components, but also a consequence of the participation of multiple adaptive physiological mechanisms, such as higher intrinsic water use efficiency, net photosynthesis rate, transpiration, carboxylation efficiency, stomatal conductance, and intracellular concentration of CO2 under water deficit conditions. On the other hand, cultivar IAPAR 81 can be considered drought-tolerant for short water-deficit periods only, since after the eighth day of water deficit, the physiological activities decline drastically.

Towards Exploitation of Adaptive Traits for Climate-Resilient Smart Pulses

Pulses are the main source of protein and minerals in the vegetarian diet. These are primarily cultivated on marginal lands with few inputs in several resource-poor countries of the world, including several in South Asia. Their cultivation in resource-scarce conditions exposes them to various abiotic and biotic stresses, leading to significant yield losses. Furthermore, climate change due to global warming has increased their vulnerability to emerging new insect pests and abiotic stresses that can become even more serious in the coming years. The changing climate scenario has made it more challenging to breed and develop climate-resilient smart pulses. Although pulses are climate smart, as they simultaneously adapt to and mitigate the effects of climate change, their narrow genetic diversity has always been a major constraint to their improvement for adaptability. However, existing genetic diversity still provides opportunities to exploit novel attributes for developing climate-resilient cultivars. The mining and exploitation of adaptive traits imparting tolerance/resistance to climate-smart pulses can be accelerated further by using cutting-edge approaches of biotechnology such as transgenics, genome editing, and epigenetics. This review discusses various classical and molecular approaches and strategies to exploit adaptive traits for breeding climate-smart pulses.

Analyses of African common bean (Phaseolus vulgaris L.) germplasm using a SNP fingerprinting platform: diversity, quality control and molecular breeding

Common bean (Phaseolus vulgaris L.) is an important staple crop for smallholder farmers, particularly in Eastern and Southern Africa. To support common bean breeding and seed dissemination, a high throughput SNP genotyping platform with 1500 established SNP assays has been developed at a genotyping service provider which allows breeders without their own genotyping infrastructure to outsource such service. A set of 708 genotypes mainly composed of germplasm from African breeders and CIAT breeding program were assembled and genotyped with over 800 SNPs. Diversity analysis revealed that both Mesoamerican and Andean gene pools are in use, with an emphasis on large seeded Andean genotypes, which represents the known regional preferences. The analysis of genetic similarities among germplasm entries revealed duplicated lines with different names as well as distinct SNP patterns in identically named samples. Overall, a worrying number of inconsistencies was identified in this data set of very diverse origins. This exemplifies the necessity to develop and use a cost-effective fingerprinting platform to ensure germplasm purity for research, sharing and seed dissemination. The genetic data also allows to visualize introgressions, to identify heterozygous regions to evaluate hybridization success and to employ marker-assisted selection. This study presents a new resource for the common bean community, a SNP genotyping platform, a large SNP data set and a number of applications on how to utilize this information to improve the efficiency and quality of seed handling activities, breeding, and seed dissemination through molecular tools.