Genome-wide association study and expression of candidate genes for Fe and Zn concentration in sorghum grains.

Sorghum germplasm showed grain Fe and Zn genetic variability, but a few varieties were biofortified with these minerals. This work contributes to narrowing this gap. Fe and Zn concentrations along with 55,068 high-quality GBS SNP data from 140 sorghum accessions were used in this study. Both micronutrients exhibited good variability with respective ranges of 22.09-52.55 ppm and 17.92-43.16 ppm. Significant marker-trait associations were identified on chromosomes 1, 3, and 5. Two major effect SNPs (S01_72265728 and S05_58213541) explained 35% and 32% of Fe and Zn phenotypic variance, respectively. The SNP S01_72265728 was identified in the cytochrome P450 gene and showed a positive effect on Fe accumulation in the kernel, while S05_58213541 was intergenic near Sobic.005G134800 (zinc-binding ribosomal protein) and showed negative effect on Zn. Tissue-specific in silico expression analysis resulted in higher levels of Sobic.003G350800 gene product in several tissues such as leaf, root, flower, panicle, and stem. Sobic.005G188300 and Sobic.001G463800 were expressed moderately at grain maturity and anthesis in leaf, root, panicle, and seed tissues. The candidate genes expressed in leaves, stems, and grains will be targeted to improve grain and stover quality. The haplotypes identified will be useful in forward genetics breeding.

Recent advancements in the breeding of sorghum crop: current status and future strategies for marker-assisted breeding.

Sorghum is emerging as a model crop for functional genetics and genomics of tropical grasses with abundant uses, including food, feed, and fuel, among others. It is currently the fifth most significant primary cereal crop. Crops are subjected to various biotic and abiotic stresses, which negatively impact on agricultural production. Developing high-yielding, disease-resistant, and climate-resilient cultivars can be achieved through marker-assisted breeding. Such selection has considerably reduced the time to market new crop varieties adapted to challenging conditions. In the recent years, extensive knowledge was gained about genetic markers. We are providing an overview of current advances in sorghum breeding initiatives, with a special focus on early breeders who may not be familiar with DNA markers. Advancements in molecular plant breeding, genetics, genomics selection, and genome editing have contributed to a thorough understanding of DNA markers, provided various proofs of the genetic variety accessible in crop plants, and have substantially enhanced plant breeding technologies. Marker-assisted selection has accelerated and precised the plant breeding process, empowering plant breeders all around the world.

Exploring the sorghum race level diversity utilizing 272 sorghum accessions genomic resources.

Due to evolutionary divergence, sorghum race populations exhibit significant genetic and morphological variation. A k-mer-based sorghum race sequence comparison identified the conserved k-mers of all 272 accessions from sorghum and the race-specific genetic signatures identified the gene variability in 10,321 genes (PAVs). To understand sorghum race structure, diversity and domestication, a deep learning-based variant calling approach was employed in a set of genotypic data derived from a diverse panel of 272 sorghum accessions. The data resulted in 1.7 million high-quality genome-wide SNPs and identified selective signature (both positive and negative) regions through a genome-wide scan with different (iHS and XP-EHH) statistical methods. We discovered 2,370 genes associated with selection signatures including 179 selective sweep regions distributed over 10 chromosomes. Co-localization of these regions undergoing selective pressure with previously reported QTLs and genes revealed that the signatures of selection could be related to the domestication of important agronomic traits such as biomass and plant height. The developed k-mer signatures will be useful in the future to identify the sorghum race and for trait and SNP markers for assisting in plant breeding programs.

Genetic and genomic interventions in crop biofortification: Examples in millets.

Micronutrient malnutrition is a serious threat to the developing world's human population, which largely relies on a cereal-based diet that lacks diversity and micronutrients. Besides major cereals, millets represent the key sources of energy, protein, vitamins, and minerals for people residing in the dryland tropics and drought-prone areas of South Asia and sub-Saharan Africa. Millets serve as multi-purpose crops with several salient traits including tolerance to abiotic stresses, adaptation to diverse agro-ecologies, higher productivity in nutrient-poor soils, and rich nutritional characteristics. Considering the potential of millets in empowering smallholder farmers, adapting to changing climate, and transforming agrifood systems, the year 2023 has been declared by the United Nations as the International Year of Millets. In this review, we highlight recent genetic and genomic innovations that can be explored to enhance grain micronutrient density in millets. We summarize the advances made in high-throughput phenotyping to accurately measure grain micronutrient content in cereals. We shed light on genetic diversity in millet germplasm collections existing globally that can be exploited for developing nutrient-dense and high-yielding varieties to address food and nutritional security. Furthermore, we describe the progress made in the fields of genomics, proteomics, metabolomics, and phenomics with an emphasis on enhancing the grain nutritional content for designing competitive biofortified varieties for the future. Considering the close genetic-relatedness within cereals, upcoming research should focus on identifying the genetic and genomic basis of nutritional traits in millets and introgressing them into major cereals through integrated omics approaches. Recent breakthroughs in the genome editing toolbox would be crucial for mainstreaming biofortification in millets.

Innovation in the Breeding of Common Bean Through a Combined Approach of in vitro Regeneration and Machine Learning Algorithms.

Common bean is considered a recalcitrant crop for in vitro regeneration and needs a repeatable and efficient in vitro regeneration protocol for its improvement through biotechnological approaches. In this study, the establishment of efficient and reproducible in vitro regeneration followed by predicting and optimizing through machine learning (ML) models, such as artificial neural network algorithms, was performed. Mature embryos of common bean were pretreated with 5, 10, and 20 mg/L benzylaminopurine (BAP) for 20 days followed by isolation of plumular apice for in vitro regeneration and cultured on a post-treatment medium containing 0.25, 0.50, 1.0, and 1.50 mg/L BAP for 8 weeks. Plumular apice explants pretreated with 20 mg/L BAP exerted a negative impact and resulted in minimum shoot regeneration frequency and shoot count, but produced longer shoots. All output variables (shoot regeneration frequency, shoot counts, and shoot length) increased significantly with the enhancement of BAP concentration in the post-treatment medium. Interaction of the pretreatment × post-treatment medium revealed the need for a specific combination for inducing a high shoot regeneration frequency. Higher shoot count and shoot length were achieved from the interaction of 5 mg/L BAP × 1.00 mg/L BAP followed by 10 mg/L BAP × 1.50 mg/L BAP and 20 mg/L BAP × 1.50 mg/L BAP. The evaluation of data through ML models revealed that R 2 values ranged from 0.32 to 0.58 (regeneration), 0.01 to 0.22 (shoot counts), and 0.18 to 0.48 (shoot length). On the other hand, the mean squared error values ranged from 0.0596 to 0.0965 for shoot regeneration, 0.0327 to 0.0412 for shoot count, and 0.0258 to 0.0404 for shoot length from all ML models. Among the utilized models, the multilayer perceptron model provided a better prediction and optimization for all output variables, compared to other models. The achieved results can be employed for the prediction and optimization of plant tissue culture protocols used for biotechnological approaches in a breeding program of common beans.

Magnesium- a Forgotten Element: Phenotypic Variation and Genome Wide Association Study in Turkish Common Bean Germplasm.

Magnesium (Mg) is the fourth most abundant element in the human body and plays the role of cofactor for more than 300 enzymatic reactions. In plants, Mg is involved in various key physiological and biochemical processes like growth, development, photophosphorylation, chlorophyll formation, protein synthesis, and resistance to biotic and abiotic stresses. Keeping in view the importance of this element, the present investigation aimed to explore the Mg contents diversity in the seeds of Turkish common bean germplasm and to identify the genomic regions associated with this element. A total of 183 common bean accessions collected from 19 provinces of Turkey were used as plant material. Field experiments were conducted according to an augmented block design during 2018 in two provinces of Turkey, and six commercial cultivars were used as a control group. Analysis of variance depicted that Mg concentration among common bean accessions was statistically significant (p < 0.05) within each environment, however genotype × environment interaction was non-significant. A moderate level (0.60) of heritability was found in this study. Overall mean Mg contents for both environments varied from 0.33 for Nigde-Dermasyon to 1.52 mg kg-1 for Nigde-Derinkuyu landraces, while gross mean Mg contents were 0.92 mg kg-1. At the province level, landraces from Bolu were rich while the landraces from Bitlis were poor in seed Mg contents respectively. The cluster constellation plot divided the studied germplasm into two populations on the basis of their Mg contents. Marker-trait association was performed using a mixed linear model (Q + K) with a total of 7,900 DArTseq markers. A total of six markers present on various chromosomes (two at Pv01, and one marker at each chromosome i.e., Pv03, Pv07, Pv08, Pv11) showed statistically significant association for seed Mg contents. Among these identified markers, the DArT-3367607 marker present on chromosome Pv03 contributed to maximum phenotypic variation (7.5%). Additionally, this marker was found within a narrow region of previously reported markers. We are confident that the results of this study will contribute significantly to start common bean breeding activities using marker assisted selection regarding improved Mg contents.

Does Plant Breeding for Antioxidant-Rich Foods Have an Impact on Human Health?

Given the general beneficial effects of antioxidants-rich foods on human health and disease prevention, there is a continuous interest in plant secondary metabolites conferring attractive colors to fruits and grains and responsible, together with others, for nutraceutical properties. Cereals and Solanaceae are important components of the human diet, thus, they are the main targets for functional food development by exploitation of genetic resources and metabolic engineering. In this review, we focus on the impact of antioxidants-rich cereal and Solanaceae derived foods on human health by analyzing natural biodiversity and biotechnological strategies aiming at increasing the antioxidant level of grains and fruits, the impact of agronomic practices and food processing on antioxidant properties combined with a focus on the current state of pre-clinical and clinical studies. Despite the strong evidence in in vitro and animal studies supporting the beneficial effects of antioxidants-rich diets in preventing diseases, clinical studies are still not sufficient to prove the impact of antioxidant rich cereal and Solanaceae derived foods on human.

Whole-genome resequencing of Sorghum bicolor and S. bicolor × S. halepense lines provides new insights for improving plant agroecological characteristics.

Sorghum (Sorghum bicolor L. (Moench)) is the world's fifth economically most important cereal and is a staple particularly in the semi-arid tropics of Africa and Asia. Genetic gains in this crop can benefit from wild relatives such as Sorghum halepense. Genome sequences including those from this wild species can boost the study of genome-wide and intraspecific variation for dissecting the genetic basis and improving important traits in sorghum. The whole-genome resequencing carried out in this work on a panel of 172 populations of S. bicolor and S. bicolor × S. halepense (SbxSh) advanced lines generated a total of 567,046,841 SNPs, 91,825,474 indels, 1,532,171 SVs, and 4,973,961 CNVs. Clearly, SbxSh accumulated more variants and mutations with powerful effects on genetic differentiation. A total of 5,548 genes private to SbxSh mapped to biological process GO enrichment terms; 34 of these genes mapped to root system development (GO: 0022622). Two of the root specific genes i.e., ROOT PRIMORDIUM DEFECTIVE 1 (RPD1; GeneID: 8054879) and RETARDED ROOT GROWTH (RRG, GeneID: 8072111), were found to exert direct effect on root growth and development. This is the first report on whole-genome resequencing of a sorghum panel that includes S. halepense genome. Mining the private variants and genes of this wild species can provide insights capable of boosting sorghum genetic improvement, particularly the perenniality trait that is compliant with agroecological practices, sustainable agriculture, and climate change resilience.

Genetic dissection of days to flowering via genome-wide association studies in Turkish common bean germplasm.

Common bean is a nutrient-dense legume crop serving as a source of food for millions of people. Characterization of unexplored common bean germplasm to unlock the phenotypic and genetic variations is still needed to explore the breeding potential of this crop. The current study aimed to dissect the genetic basis having association for days to flowering (DF). A total of 188 common bean accessions collected from 19 provinces of Turkey were used as plant material under five environments and two locations. Analysis of variance (ANOVA) revealed that genotypes and genotype by environment interaction have significant effects on DF. A total of 10 most stable accessions were evaluated from stability analysis. Overall maximum (75) and minimum (54) DF were observed for Hakkari-51 and Mus-46 accessions, respectively. The implemented constellation plot divided studied germplasm according to their DF and growth habit. A total of 7900 DArTseq markers were used for association analysis. Mixed linear model using the Q + K Model resulted a total of 18 DArTseq markers from five environments. DArT-8668385 marker identified in Bolu during 2016 was also associated with DF in Sivas during 2017. Combined data of five years resulted a total of four markers (DArT-22346534, DArT-3369768, DArT-3374613, and DArT-3370801) having significant association ( p < 0.01 ) for DF. DArT-22346534 present on Pv 08 accounted a maximum of 9.89% variation to the studied trait. A total of four putative candidate genes were predicted from sequences reflecting homology to identified four DArTseq markers. We envisage that exploitation of identified DArTseq markers will hopefully beneficial for the development of new common bean varieties having better adaptation ability to changing climatic conditions. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12298-021-01029-8.

Machine learning models based on remote and proximal sensing as potential methods for in-season biomass yields prediction in commercial sorghum fields.

Crop yield monitoring demonstrated the potential to improve agricultural productivity through improved crop breeding, farm management and commodity planning. Remote and proximal sensing offer the possibility to cut crop monitoring costs traditionally associated with surveys and censuses. Fraction of absorbed photosynthetically active radiation (fAPAR), chlorophyll concentration (CI) and normalized difference vegetation (NDVI) indices were used in crop monitoring, but their comparative performances in sorghum monitoring is lacking. This work aimed therefore at closing this gap by evaluating the performance of machine learning modelling of in-season sorghum biomass yields based on Sentinel-2-derived fAPAR and simpler high-throughput optical handheld meters-derived NDVI and CI calculated from sorghum plants reflectance. Bayesian ridge regression showed good cross-validated performance, and high reliability (R2 = 35%) and low bias (mean absolute prediction error, MAPE = 0.4%) during the validation step. Hand-held optical meter-derived CI and Sentinel-2-derived fAPAR showed comparable effects on machine learning performance, but CI outperformed NDVI and was therefore considered as a good alternative to Sentinel-2's fAPAR. The best times to sample the vegetation indices were the months of June (second half) and July. The results obtained in this work will serve several purposes including improvements in plant breeding, farming management and sorghum biomass yield forecasting at extension services and policy making levels.

Genome-Wide Association Study for Biomass Related Traits in a Panel of Sorghum bicolor and S. bicolor × S. halepense Populations.

The efficient use of sorghum as a renewable energy source requires high biomass yields and reduced agricultural inputs. Hybridization of Sorghum bicolor with wild Sorghum halepense can help meet both requirements, generating high-yielding and environment friendly perennial sorghum cultivars. Selection efficiency, however, needs to be improved to exploit the genetic potential of the derived recombinant lines and remove weedy and other wild traits. In this work, we present the results from a Genome-Wide Association Study conducted on a diversity panel made up of S. bicolor and an advanced population derived from S. bicolor × S. halepense multi-parent crosses. The objective was to identify genetic loci controlling biomass yield and biomass-relevant traits for breeding purposes. Plants were phenotyped during four consecutive years for dry biomass yield, dry mass fraction of fresh material, plant height and plant maturity. A genotyping-by-sequencing approach was implemented to obtain 92,383 high quality SNP markers used in this work. Significant marker-trait associations were uncovered across eight of the ten sorghum chromosomes, with two main hotspots near the end of chromosomes 7 and 9, in proximity of dwarfing genes Dw1 and Dw3. No significant marker was found on chromosomes 2 and 4. A large number of significant marker loci associated with biomass yield and biomass-relevant traits showed minor effects on respective plant characteristics, with the exception of seven loci on chromosomes 3, 8, and 9 that explained 5.2-7.8% of phenotypic variability in dry mass yield, dry mass fraction of fresh material, and maturity, and a major effect (R 2 = 16.2%) locus on chromosome 1 for dry mass fraction of fresh material which co-localized with a zinc-finger homeodomain protein possibly involved in the expression of the D (Dry stalk) locus. These markers and marker haplotypes identified in this work are expected to boost marker-assisted selection in sorghum breeding.

Genetic diversity and population structure of endangered rosewood from the Peruvian Amazon using ISSR markers

Rosewood, Aniba rosaeodora is an endangered species in Amazon forests and its natural stands have been heavily depleted due to over-exploitation for the cosmetic industry. This study aimed to investigate the genetic diversity and population structure of 90 rosewood accessions from eight localities in the Peruvian Amazon through 11 Inter Simple Sequence Repeats (ISSR) primers. The ISSR primers produced a sum of 378 bands, of which 375 (99.2%) were polymorphic, with an average polymorphism information content (PIC) value of 0.774. The mean effective number of alleles (Ne), Shannon informative index (I), gene diversity (He) and total gene diversity (Ht) were 1.485, 0.294, 0.453 and 0.252, respectively. Analysis of molecular variance (AMOVA) showed the presence of maximum variability within populations (88%). The Structure algorithm, neighbor joining and principal coordinate analysis (PCoA) grouped the 90 rosewood accessions into three main populations (A, B and C). Diversity indices at the inter-population level revealed a greater genetic diversity in population A, due to higher gene flow. The neighbor-joining analysis grouped populations A and B, while population C was found to be divergent at the inter population level. We concluded that population A reflects higher genetic diversity and should be prioritized for future management and conservation plans. (AU)

Genetic Diversity, Population Structure and Marker-Trait Association for 100-Seed Weight in International Safflower Panel Using SilicoDArT Marker Information.

Safflower is an important oilseed crop mainly grown in the arid and semi-arid regions of the world. The aim of this study was to explore phenotypic and genetic diversity, population structure, and marker-trait association for 100-seed weight in 94 safflower accessions originating from 26 countries using silicoDArT markers. Analysis of variance revealed statistically significant genotypic effects (p < 0.01), while Turkey samples resulted in higher 100-seed weight compared to Pakistan samples. A Constellation plot divided the studied germplasm into two populations on the basis of their 100-seed weight. Various mean genetic diversity parameters including observed number of alleles (1.99), effective number of alleles (1.54), Shannon's information index (0.48), expected heterozygosity (0.32), and unbiased expected heterozygosity (0.32) for the entire population exhibited sufficient genetic diversity using 12232 silicoDArT markers. Analysis of molecular variance (AMOVA) revealed that most of the variations (91%) in world safflower panel are due to differences within country groups. A model-based structure grouped the 94 safflower accessions into populations A, B, C and an admixture population upon membership coefficient. Neighbor joining analysis grouped the safflower accessions into two populations (A and B). Principal coordinate analysis (PCoA) also clustered the safflower accessions on the basis of geographical origin. Three accessions; Egypt-5, Egypt-2, and India-2 revealed the highest genetic distance and hence might be recommended as candidate parental lines for safflower breeding programs. The mixed linear model i.e., the Q + K model, demonstrated that two DArTseq markers (DArT-45483051 and DArT-15672391) had significant association (p < 0.01) for 100-seed weight. We envisage that identified DArTseq markers associated with 100-seed weight will be helpful to develop high-yielding cultivars of safflower through marker-assisted breeding in the near future.

Genomic Selection for Optimum Index with Dry Biomass Yield, Dry Mass Fraction of Fresh Material, and Plant Height in Biomass Sorghum.

Sorghum is one of the world's major crops, expresses traits for resilience to climate change, and can be used for several purposes including food and clean fuels. Multiple-trait genomic prediction and selection models were implemented using genotyping-by-sequencing single nucleotide polymorphism markers and phenotypic data information. We demonstrated for the first time the efficiency genomic selection modelling of index selection including biofuel traits such as aboveground biomass yield, plant height, and dry mass fraction of the fresh material. This work also sheds light, for the first time, on the promising potential of using the information from the populations grown from seed to predict the performance of the populations regrown from the rhizomes-even two winter seasons after the original trial was sown. Genomic selection modelling of the optimum index selection including the three traits of interest (plant height, aboveground dry biomass yield, and dry mass fraction of fresh mass material) was the most promising. Since the plant characteristics evaluated herein are routinely measured in cereal and other plant species of agricultural interest, it can be inferred that the findings can be transferred in other major crops.

Genome-wide association mapping of total antioxidant capacity, phenols, tannins, and flavonoids in a panel of Sorghum bicolor and S. bicolor × S. halepense populations using multi-locus models.

Sorghum is widely used for producing food, feed, and biofuel, and it is increasingly grown to produce grains rich in health-promoting antioxidants. The conventional use of grain color as a proxy to indirectly select against or for antioxidants polyphenols in sorghum grain was hampered by the lack of consistency between grain color and the expected antioxidants concentration. Marker-assisted selection built upon significant loci identified through linkage disequilibrium studies showed interesting potential in several plant breeding and animal husbandry programs, and can be used in sorghum breeding for consumer-tailored antioxidant production. The purpose of this work was therefore to conduct genome-wide association study of sorghum grain antioxidants using single nucleotide polymorphisms in a novel diversity panel of Sorghum bicolor landraces and S. bicolor × S. halepense recombinant inbred lines. The recombinant inbred lines outperformed landraces for antioxidant production and contributed novel polymorphism. Antioxidant traits were highly correlated and showed very high broad-sense heritability. The genome-wide association analysis uncovered 96 associations 55 of which were major quantitative trait loci (QTLs) explaining 15 to 31% of the observed antioxidants variability. Eight major QTLs localized in novel chromosomal regions. Twenty-four pleiotropic major effect markers and two novel functional markers (Chr9_1550093, Chr10_50169631) were discovered. A novel pleiotropic major effect marker (Chr1_61095994) explained the highest proportion (R2 = 27-31%) of the variance observed in most traits evaluated in this work, and was in linkage disequilibrium with a hotspot of 19 putative glutathione S-transferase genes conjugating anthocyanins into vacuoles. On chromosome four, a hotspot region was observed involving major effect markers linked with putative MYB-bHLH-WD40 complex genes involved in the biosynthesis of the polyphenol class of flavonoids. The findings in this work are expected to help the scientific community particularly involved in marker assisted breeding for the development of sorghum cultivars with consumer-tailored antioxidants concentration.

Genomic Selection for Antioxidant Production in a Panel of Sorghum bicolor and S. bicolor × S. halepense Lines.

The purpose of this work was to assess the performance of four genomic selection (GS) models (GBLUP, BRR, Bayesian LASSO and BayesB) in 4 sorghum grain antioxidant traits (phenols, flavonoids, total antioxidant capacity and condensed tannins) using whole-genome SNP markers in a novel diversity panel of Sorghum bicolor lines and landraces and S. bicolor × S. halepense recombinant inbred lines. One key breeding problem modelled was predicting the performance in the antioxidant production of new and unphenotyped sorghum genotypes (validation set). The population was weakly structured (analysis of molecular variance, AMOVA R2 = 9%), showed a significant genetic diversity and expressed antioxidant traits with a good level of variability and high correlation. The S. bicolor × S. halepense lines outperformed Sorghum bicolor populations for all the antioxidants. The four GS models implemented in this work performed comparably across traits, with accuracy ranging from 0.49 to 0.58, and are considered high enough to sustain sorghum breeding for antioxidants production and allow important genetic gains per unit of time and cost. The results presented in this work are expected to contribute to GS implementation and the genetic improvement of sorghum grain antioxidants for different purposes, including the manufacture of health-promoting and specialty foods.

Mobile genomic element diversity in world collection of safflower (Carthamus tinctorius L.) panel using iPBS-retrotransposon markers.

Safflower (Carthamus tinctorius L.) is a multipurpose crop of dry land yielding very high quality of edible oil. Present study was aimed to investigate the genetic diversity and population structure of 131 safflower accessions originating from 28 different countries using 13 iPBS-retrotransposon markers. A total of 295 iPBS bands were observed among which 275 (93.22%) were found polymorphic. Mean Polymorphism information content (0.48) and diversity parameters including mean effective number of alleles (1.33), mean Shannon's information index (0.33), overall gene diversity (0.19), Fstatistic (0.21), and inbreeding coefficient (1.00) reflected the presence of sufficient amount of genetic diversity in the studied plant materials. Analysis of molecular variance (AMOVA) showed that more than 40% of genetic variation was derived from populations. Model-based structure, principal coordinate analysis (PCoA) and unweighted pair-group method with arithmetic means (UPGMA) algorithms clustered the 131 safflower accessions into four main populations A, B, C, D and an unclassified population, with no meaningful geographical origin. Most diverse accessions originated from Asian countries including Afghanistan, Pakistan, China, Turkey, and India. Four accessions, Turkey3, Afghanistan4, Afghanistan2, and Pakistan24 were found most genetically distant and might be recommended as a candidate parents for breeding purposes. The findings of this study are most probably supported by the seven similarity centers hypothesis of safflower. This is a first study to explore the genetic diversity and population structure in safflower accessions using the iPBS-retrotransposon markers. The information provided in this work will therefore be helpful for scientists interested in safflower breeding.

Uncovering Phenotypic Diversity and DArTseq Marker Loci Associated with Antioxidant Activity in Common Bean.

Antioxidants play an important role in animal and plant life owing to their involvement in complex metabolic and signaling mechanisms, hence uncovering the genetic basis associated with antioxidant activity is very important for the development of improved varieties. Here, a total of 182 common bean (Phaseolus vulgaris) landraces and six commercial cultivars collected from 19 provinces of Turkey were evaluated for seed antioxidant activity under four environments and two locations. Antioxidant activity was measured using ABTS radical scavenging capacity and mean antioxidant activity in common bean landraces was 20.03 µmol TE/g. Analysis of variance reflected that genotype by environment interaction was statistically non-significant and heritability analysis showed higher heritability of antioxidant activity. Variations in seed color were observed, and a higher antioxidant activity was present in seeds having colored seed as compared to those having white seeds. A negative correlation was found between white-colored seeds and antioxidant activity. A total of 7900 DArTseq markers were used to explore the population structure that grouped the studied germplasm into two sub-populations on the basis of their geographical origins and trolox equivalent antioxidant capacity contents. Mean linkage disequilibrium (LD) was 54%, and mean LD decay was 1.15 Mb. Mixed linear model i.e., the Q + K model demonstrated that four DArTseq markers had significant association (p < 0.01) for antioxidant activity. Three of these markers were present on chromosome Pv07, while the fourth marker was located on chromosome Pv03. Among the identified markers, DArT-3369938 marker showed maximum (14.61%) variation. A total of four putative candidate genes were predicted from sequences reflecting homology to identified DArTseq markers. This is a pioneering study involving the identification of association for antioxidant activity in common bean seeds. We envisage that this study will be very helpful for global common bean breeding community in order to develop cultivars with higher antioxidant activity.

Characterization of genetic diversity in Turkish common bean gene pool using phenotypic and whole-genome DArTseq-generated silicoDArT marker information.

Turkey presents a great diversity of common bean landraces in farmers' fields. We collected 183 common bean accessions from 19 different Turkish geographic regions and 5 scarlet runner bean accessions to investigate their genetic diversity and population structure using phenotypic information (growth habit, and seed weight, flower color, bracteole shape and size, pod shape and leaf shape and color), geographic provenance and 12,557 silicoDArT markers. A total of 24.14% markers were found novel. For the entire population (188 accessions), the expected heterozygosity was 0.078 and overall gene diversity, Fst and Fis were 0.14, 0.55 and 1, respectively. Using marker information, model-based structure, principal coordinate analysis (PCoA) and unweighted pair-group method with arithmetic means (UPGMA) algorithms clustered the 188 accessions into two main populations A (predominant) and B, and 5 unclassified genotypes, representing 3 meaningful heterotic groups for breeding purposes. Phenotypic information clearly distinguished these populations; population A and B, respectively, were bigger (>40g/100 seeds) and smaller (<40g/100 seeds) seed-sized. The unclassified population was pure and only contained climbing genotypes with 100 seed weight 2-3 times greater than populations A and B. Clustering was mainly based on A: seed weight, B: growth habit, C: geographical provinces and D: flower color. Mean kinship was generally low, but population B was more diverse than population A. Overall, a useful level of gene and genotypic diversity was observed in this work and can be used by the scientific community in breeding efforts to develop superior common bean strains.