The GW5-WRKY53-SGW5 module regulates grain size variation in rice.

Grain size is a crucial agronomic trait that affects stable yield, appearance, milling quality, and domestication in rice. However, the molecular and genetic relationships among QTL genes (QTGs) underlying natural variation for grain size remain elusive. Here, we identified a novel QTG SGW5 (suppressor of gw5) by map-based cloning using an F2 segregation population by fixing same genotype of the master QTG GW5. SGW5 positively regulates grain width by influencing cell division and cell size in spikelet hulls. Two nearly isogenic lines exhibited a significant differential expression of SGW5 and a 12.2% increase in grain yield. Introducing the higher expression allele into the genetic background containing the lower expression allele resulted in increased grain width, while its knockout resulted in shorter grain hulls and dwarf plants. Moreover, a cis-element variation in the SGW5 promoter influenced its differential binding affinity for the WRKY53 transcription factor, causing the differential SGW5 expression, which ultimately leads to grain size variation. GW5 physically and genetically interacts with WRKY53 to suppress the expression of SGW5. These findings elucidated a new pathway for grain size regulation by the GW5-WRKY53-SGW5 module and provided a novel case for generally uncovering QTG interactions underlying the genetic diversity of an important trait in crops.

High hopes for short corn.

Plants bred or engineered to be short can stand up better to windstorms. They could also boost yields and benefit the environment.

CRISPR-Cas9 Mediated Mutation in OsPUB43 Improves Grain Length and Weight in Rice by Promoting Cell Proliferation in Spikelet Hull.

Grain weight, a crucial trait that determines the grain yield in rice, is influenced by grain size. Although a series of regulators that control grain size have been identified in rice, the mechanisms underlying grain development are not yet well understood. In this study, we identified OsPUB43, a U-box E3 ubiquitin ligase, as an important negative regulator determining the gain size and grain weight in rice. Phenotypes of large grain are observed in ospub43 mutants, whereas overexpression of OsPUB43 results in short grains. Scanning electron microscopy analysis reveals that OsPUB43 modulates the grain size mainly by inhibiting cell proliferation in the spikelet hull. The OsPUB43 protein is localized in the cytoplasm and nucleus. The ospub43 mutants display high sensitivity to exogenous BR, while OsPUB43-OE lines are hyposensitive to BR. Furthermore, the transient transcriptional activity assay shows that OsBZR1 can activate the expression of OsPUB43. Collectively, our results indicate that OsPUB43 negatively controls the gain size by modulating the expression of BR-responsive genes as well as MADS-box genes that are required for lemma/palea specification, suggesting that OsPUB43 has a potential valuable application in the enlargement of grain size in rice.

Genetic dissection of quantitative trait loci for grain size and weight by high-resolution genetic mapping in bread wheat (Triticum aestivum L.).

KEY MESSAGE: Six major QTLs for wheat grain size and weight were identified on chromosomes 4A, 4B, 5A and 6A across multiple environments, and were validated in different genetic backgrounds. Grain size and weight are crucial components of wheat yield. Dissection of their genetic control is thus essential for the improvement of yield potential in wheat breeding. We used a doubled haploid (DH) population to detect quantitative trait loci (QTLs) for grain width (GW), grain length (GL), and thousand grain weight (TGW) in five environments. Six major QTLs, QGw.cib-4B.2, QGl.cib-4A, QGl.cib-5A.1, QGl.cib-6A, QTgw.cib-4B, and QTgw.cib-5A, were consistently identified in at least three individual environments and in best linear unbiased prediction (BLUP) datasets, and explained 5.65-34.06% of phenotypic variation. QGw.cib-4B.2, QTgw.cib-4B, QGl.cib-5A.1 and QGl.cib-6A had no effect on grain number per spike (GNS). In addition to QGl.cib-4A, the other major QTLs were further validated by using Kompetitive Allele Specific PCR (KASP) markers in different genetic backgrounds. Moreover, significant interactions between the three major GL QTLs and two major TGW QTLs were observed. Comparison analysis showed that QGl.cib-5A.1 and QGl.cib-6A are likely new loci. Notably, QGw.cib-4B.2 and QTgw.cib-4B were co-located on chromosome 4B and improved TGW by increasing only GW, unlike nearby or overlapped loci reported previously. Three genes associated with grain development within the QGw.cib-4B.2/QTgw.cib-4B interval were identified by searches on sequence similarity, spatial expression patterns, and orthologs. The major QTLs and KASP markers reported here will be useful for elucidating the genetic architecture of grain size and weight and for developing new wheat cultivars with high and stable yield.

Identification of Genomic Regions Controlling Chalkiness and Grain Characteristics in a Recombinant Inbred Line Rice Population Based on High-Throughput SNP Markers.

Rice (Oryza sativa L.) is the primary food for half of the global population. Recently, there has been increasing concern in the rice industry regarding the eating and milling quality of rice. This study was conducted to identify genetic information for grain characteristics using a recombinant inbred line (RIL) population from a japonica/indica cross based on high-throughput SNP markers and to provide a strategy for improving rice quality. The RIL population used was derived from a cross of "Kaybonnet (KBNT lpa)" and "ZHE733" named the K/Z RIL population, consisting of 198 lines. A total of 4133 SNP markers were used to identify quantitative trait loci (QTLs) with higher resolution and to identify more accurate candidate genes. The characteristics measured included grain length (GL), grain width (GW), grain length to width ratio (RGLW), hundred grain weight (HGW), and percent chalkiness (PC). QTL analysis was performed using QTL IciMapping software. Continuous distributions and transgressive segregations of all the traits were observed, suggesting that the traits were quantitatively inherited. A total of twenty-eight QTLs and ninety-two candidate genes related to rice grain characteristics were identified. This genetic information is important to develop rice varieties of high quality.

Association mapping of drought tolerance and agronomic traits in rice (Oryza sativa L.) landraces.

BACKGROUND: Asian cultivars were predominantly represented in global rice panel selected for sequencing and to identify novel alleles for drought tolerance. Diverse genetic resources adapted to Indian subcontinent were not represented much in spite harboring useful alleles that could improve agronomic traits, stress resilience and productivity. These rice accessions are valuable genetic resource in developing rice varieties suited to different rice ecosystem that experiences varying drought stress level, and at different crop stages. A core collection of rice germplasm adapted to Southwestern Indian peninsular genotyped using SSR markers and characterized by contrasting water regimes to associate genomic regions for physiological, root traits and yield related traits. Genotyping-By-Sequencing of selected accessions within the diverse panel revealed haplotype variation in genic content within genomic regions mapped for physiological, morphological and root traits. RESULTS: Diverse rice panel (99 accessions) were evaluated in field and measurements on plant physiological, root traits and yield related traits were made over five different seasons experiencing varying drought stress intensity at different crop stages. Traits like chlorophyll stability index, leaf rolling, days to 50% flowering, chlorophyll content, root volume and root biomass were identified as best predictors of grain yield under stress. Association mapping revealed genetic variation among accessions and revealed 14 genomic targets associated with different physiological, root and plant production traits. Certain accessions were found to have beneficial allele to improve traits, plant height, root length and spikelet fertility, that contribute to the grain yield under stress. Genomic characterization of eleven accessions revealed haplotype variation within key genomic targets on chromosomes 1, 4, 6 and 11 for potential use as molecular markers to combine drought avoidance and tolerance traits. Genes mined within the genomic QTL intervals identified were prioritized based on tissue specific expression level in publicly available rice transcriptome data. CONCLUSION: The genetic and genomic resources identified will enable combining traits with agronomic value to optimize yield under stress and hasten trait introgression into elite cultivars. Alleles associated with plant height, specific leaf area, root length from PTB8 and spikelet fertility and grain weight from PTB26 can be harnessed in future rice breeding program.

GridFree: a python package of imageanalysis for interactive grain counting and measuring.

Grain characteristics, including kernel length, kernel width, and thousand kernel weight, are critical component traits for grain yield. Manual measurements and counting are expensive, forming the bottleneck for dissecting these traits' genetic architectures toward ultimate yield improvement. High-throughput phenotyping methods have been developed by analyzing images of kernels. However, segmenting kernels from the image background and noise artifacts or from other kernels positioned in close proximity remain as challenges. In this study, we developed a software package, named GridFree, to overcome these challenges. GridFree uses an unsupervised machine learning approach, K-Means, to segment kernels from the background by using principal component analysis on both raw image channels and their color indices. GridFree incorporates users' experiences as a dynamic criterion to set thresholds for a divide-and-combine strategy that effectively segments adjacent kernels. When adjacent multiple kernels are incorrectly segmented as a single object, they form an outlier on the distribution plot of kernel area, length, and width. GridFree uses the dynamic threshold settings for splitting and merging. In addition to counting, GridFree measures kernel length, width, and area with the option of scaling with a reference object. Evaluations against existing software programs demonstrated that GridFree had the smallest error on counting seeds for multiple crop species. GridFree was implemented in Python with a friendly graphical user interface to allow users to easily visualize the outcomes and make decisions, which ultimately eliminates time-consuming and repetitive manual labor. GridFree is freely available at the GridFree website (https://zzlab.net/GridFree).

Genetic dissection of grain architecture-related traits in a winter wheat population.

BACKGROUND: The future productivity of wheat (T. aestivum L.) as the most grown crop worldwide is of utmost importance for global food security. Thousand kernel weight (TKW) in wheat is closely associated with grain architecture-related traits, e.g. kernel length (KL), kernel width (KW), kernel area (KA), kernel diameter ratio (KDR), and factor form density (FFD). Discovering the genetic architecture of natural variation in these traits, identifying QTL and candidate genes are the main aims of this study. Therefore, grain architecture-related traits in 261 worldwide winter accessions over three field-year experiments were evaluated. RESULTS: Genome-wide association analysis using 90K SNP array in FarmCPU model revealed several interesting genomic regions including 17 significant SNPs passing false discovery rate threshold and strongly associated with the studied traits. Four of associated SNPs were physically located inside candidate genes within LD interval e.g. BobWhite_c5872_589 (602,710,399 bp) found to be inside TraesCS6A01G383800 (602,699,767-602,711,726 bp). Further analysis reveals the four novel candidate genes potentially involved in more than one grain architecture-related traits with a pleiotropic effects e.g. TraesCS6A01G383800 gene on 6A encoding oxidoreductase activity was associated with TKW and KA. The allelic variation at the associated SNPs showed significant differences betweeen the accessions carying the wild and mutated alleles e.g. accessions carying C allele of BobWhite_c5872_589, TraesCS6A01G383800 had significantly higher TKW than the accessions carying T allele. Interestingly, these genes were highly expressed in the grain-tissues, demonstrating their pivotal role in controlling the grain architecture. CONCLUSIONS: These results are valuable for identifying regions associated with kernel weight and dimensions and potentially help breeders in improving kernel weight and architecture-related traits in order to increase wheat yield potential and end-use quality.

Verification and dissection of one quantitative trait locus for grain size and weight on chromosome 1 in rice.

Grain size and weight are the key traits determining rice quality and yield and are mainly controlled by quantitative trait loci (QTL). In this study, one minor QTL that was previously mapped in the marker interval of JD1009-JD1019 using the Huanghuazhan/Jizi1560 (HHZ/JZ1560) recombinant inbred line (RIL) population, qTGW1-2, was validated to regulate grain size and weight across four rice-growing seasons using twenty-one near isogenic line (NIL)-F2 populations. The twenty-one populations were in two types of genetic background that were derived from the same parents HHZ and JZ1560. Twelve F9, F10 or F11 NIL-F2 populations with the sequential residual heterozygous regions covering JD1009-RM6840 were developed from one residual heterozygote (RH) in the HHZ/JZ1560 RIL population, and the remaining nine BC3F3, BC3F4 or BC3F5 NIL-F2 populations with the sequential residual heterozygous regions covering JD1009-RM6840 were constructed through consecutive backcrosses to the recurrent parent HHZ followed with marker assistant selection in each generation. Based on the QTL analysis of these genetic populations, qTGW1-2 was successfully confirmed to control grain length, width and weight and further dissected into two QTLs, qTGW1-2a and qTGW1-2b, which were respectively narrowed down to the marker intervals of JD1139-JD1127 (~ 978.2-kb) and JD1121-JD1102 (~ 54.8-kb). Furthermore, the two types of NIL-F2 populations were proved to be able to decrease the genetic background noise and increase the detection power of minor QTL. These results provided an important basis for further map-based cloning and molecular design breeding with the two QTLs in rice.

Identification of genetic loci associated with major agronomic traits of wheat (Triticum aestivum L.) based on genome-wide association analysis.

BACKGROUND: Bread wheat (Triticum aestivum L.) is one of the most widely consumed cereal crops, but its complex genome makes it difficult to investigate the genetic effect on important agronomic traits. Genome-wide association (GWA) analysis is a useful method to identify genetic loci controlling complex phenotypic traits. With the RNA-sequencing based gene expression analysis, putative candidate genes governing important agronomic trait can be suggested and also molecular markers can be developed. RESULTS: We observed major quantitative agronomic traits of wheat; the winter survival rate (WSR), days to heading (DTH), days to maturity (DTM), stem length (SL), spike length (SPL), awn length (AL), liter weight (LW), thousand kernel weight (TKW), and the number of seeds per spike (SPS), of 287 wheat accessions from diverse country origins. A significant correlation was observed between the observed traits, and the wheat genotypes were divided into three subpopulations according to the population structure analysis. The best linear unbiased prediction (BLUP) values of the genotypic effect for each trait under different environments were predicted, and these were used for GWA analysis based on a mixed linear model (MLM). A total of 254 highly significant marker-trait associations (MTAs) were identified, and 28 candidate genes closely located to the significant markers were predicted by searching the wheat reference genome and RNAseq data. Further, it was shown that the phenotypic traits were significantly affected by the accumulation of favorable or unfavorable alleles. CONCLUSIONS: From this study, newly identified MTA and putative agronomically useful genes will help to study molecular mechanism of each phenotypic trait. Further, the agronomically favorable alleles found in this study can be used to develop wheats with superior agronomic traits.

A homologous gene of OsREL2/ASP1, ASP-LSL regulates pleiotropic phenotype including long sterile lemma in rice.

BACKGROUND: Panicle is a harvesting organ of rice, and its morphology and development are closely associated with grain yield. The current study was carried on a mutant screened through an EMS (ethyl-methane sulphonate) mutagenized population of a Japonica cultivar Kitaake (WT). RESULTS: A mutant, named as asp-lsl (aberrant spikelet-long sterile lemma), showed a significant decrease in plant height, number of tillers, thousand-grains weight, seed setting rate, spikelet length, kernel length and effective number of grains per panicle as compared to WT. Asp-lsl showed a pleiotropic phenotype coupled with the obvious presence of a long sterile lemma. Cross-sections of lemma showed an increase in the cell volume rather than the number of cells. Genetic segregation analysis revealed its phenotypic trait is controlled by a single recessive nuclear gene. Primary and fine mapping indicated that candidate gene controlling the phenotype of asp-lsl was located in an interval of 212 kb on the short arm of chromosome 8 between RM22445 and RM22453. Further sequencing and indels markers analysis revealed LOC_Os08g06480 harbors a single base substitution (G→A), resulting in a change of 521st amino acid(Gly→Glu. The homology comparison and phylogenetic tree analysis revealed mutation was occurred in a highly conserved domain and had a high degree of similarity in Arabidopsis, corn, and sorghum. The CRISPR/Cas9 mutant line of ASP-LSL produced a similar phenotype as that of asp-lsl. Subcellular localization of ASP-LSL revealed that its protein is localized in the nucleus. Relative expression analysis revealed ASP-LSL was preferentially expressed in panicle, stem, and leaves. The endogenous contents of GA, CTK, and IAA were found significantly decreased in asp-lsl as compared to WT. CONCLUSIONS: Current study presents the novel phenotype of asp-lsl and also validate the previously reported function of OsREL2 (ROMOSA ENHANCER LOCI2), / ASP1(ABERRANT SPIKELET AND PANICLE 1).

Gene duplication drove the loss of awn in sorghum.

Loss of the awn in some cereals, including sorghum, is a key transition during cereal domestication or improvement that has facilitated grain harvest and storage. The genetic basis of awn loss in sorghum during domestication or improvement remains unknown. Here, we identified the awn1 gene encoding a transcription factor with the ALOG domain that is responsible for awn loss during sorghum domestication or improvement. awn1 arose from a gene duplication on chromosome 10 that translocated to chromosome 3, recruiting a new promoter from the neighboring intergenic region filled with "noncoding DNA" and recreating the first exon and intron. awn1 acquired high expression after duplication and represses the elongation of awns in domesticated sorghum. Comparative mapping revealed high collinearity at the awn1 paralog locus on chromosome 10 across cereals, and awn growth and development were successfully reactivated on the rice spikelet by inactivating the rice awn1 ortholog. RNA-seq and DAP-seq revealed that as a transcriptional repressor, AWN1 bound directly to a motif in the regulatory regions of three MADS genes related to flower development and two genes, DL and LKS2, involved in awn development. AWN1 downregulates the expression of these genes, thereby repressing awn elongation. The preexistence of regulatory elements in the neighboring intergenic region of awn1 before domestication implicates that noncoding DNA may serve as a treasure trove for evolution during sorghum adaptation to a changing world. Taken together, our results suggest that gene duplication can rapidly drive the evolution of gene regulatory networks in plants.

Genetic mapping for grain quality and yield-attributed traits in Basmati rice using SSR-based genetic map.

Rice grain shape and nutritional quality traits have high economic value for commercial production of rice and largely determine the market price, besides influencing the global food demand for high-quality rice. Detection, mapping and exploitation of quantitative trait loci (QTL) associated with kernel elongation and grain quality in Basmati rice is considered as an efficient strategy for improving the kernel elongation and grain quality trait in rice varieties. Genetic information in rice for most of these traits is scanty and needed interventions through the use of molecular markers. A recombinant inbred lines (RIL) population consisting of 130 lines generated from the cross involving Basmati 370, a superior quality Basmati variety and Pusa Basmati 1121, a Basmati derived variety were used to map the QTLs for 9 important grain quality and yield related traits. Correlation studies showed that various components of yield show a significant positive relationship with grain yield. A genetic map was constructed using 70 polymorphic simple sequence repeat (SSR) markers spanning a genetic distance of 689.3 cM distributed over 12 rice chromosomes. Significant variation was observed and showed transgressive segregation for grain quality traits in RIL population. A total of 20 QTLs were identified associated with nine yield and quality traits. Epistatic interactions were also identified for grain quality related traits indicating complex genetic nature inheritance. Therefore, the identified QTLs and flanking marker information could be utilized in the marker-assisted selection to improve kernel elongation and nutritional grain quality traits in rice varieties.

A novel miR167a-OsARF6-OsAUX3 module regulates grain length and weight in rice.

Grain size is one of the most important factors that control rice yield, as it is associated with grain weight (GW). To date, dozens of rice genes that regulate grain size have been isolated; however, the regulatory mechanism underlying GW control is not fully understood. Here, the quantitative trait locus qGL5 for grain length (GL) and GW was identified in recombinant inbred lines of 9311 and Nipponbare (NPB) and fine mapped to a candidate gene, OsAUX3. Sequence variations between 9311 and NPB in the OsAUX3 promoter and loss of function of OsAUX3 led to higher GL and GW. RNA sequencing, gene expression quantification, dual-luciferase reporter assays, chromatin immunoprecipitation-quantitative PCR, and yeast one-hybrid assays demonstrated that OsARF6 is an upstream transcription factor regulating the expression of OsAUX3. OsARF6 binds directly to the auxin response elements of the OsAUX3 promoter, covering a single-nucleotide polymorphism site between 9311 and NPB/Dongjin/Hwayoung, and thereby controls GL by altering longitudinal expansion and auxin distribution/content in glume cells. Furthermore, we showed that miR167a positively regulate GL and GW by directing OsARF6 mRNA silencing. Taken together, our study reveals that a novel miR167a-OsARF6-OsAUX3 module regulates GL and GW in rice, providing a potential target for the improvement of rice yield.

RNAi-mediated down-regulation of ITPK-2 enhanced inorganic phosphorus and minerals in the transgenic rice.

Phytic acid or Myo-inositol hexakisphosphate is an essential compound for the rice plants. It remains in the form of phytate, a mixed salt of different mineral cations, in the seeds. The phytate breaks down during germination and provides the inorganic phosphorus and mineral ions to the seedlings. However, humans do not get the benefit of those essential ions from rice consumption due to the absence of phytase in the gut. We envisaged down-regulating ITPK, the gene behind the phytic acid biosynthesis so that its low amount would facilitate a greater amount of free mineral ions in the endosperm. Since there are six homologues of rice ITPK, we studied their expression in seeds. Additionally, we undertook an in-silico analysis of the homologous proteins. Considering the results, we selected ITPK-2 for its RNAi-mediated embryo-specific down-regulation to obtain the low phytate rice. We obtained a 37% reduction of phytic acid content accompanied by a nearly three-fold enhancement of inorganic phosphorus in the transgenic seeds. Additionally, the iron and zinc content increased in polished rice grains compared to the wild type. The results also showed that reduced phytic acid content did not affect the germination potential and seedling growth of the transgenic rice.

Modification of cereal plant architecture by genome editing to improve yields.

KEY MESSAGE: We summarize recent genome editing studies that have focused on the examination (or reexamination) of plant architectural phenotypes in cereals and the modification of these traits for crop improvement. Plant architecture is defined as the three-dimensional organization of the entire plant. Shoot architecture refers to the structure and organization of the aboveground components of a plant, reflecting the developmental patterning of stems, branches, leaves and inflorescences/flowers. Root system architecture is essentially determined by four major shape parameters-growth, branching, surface area and angle. Interest in plant architecture has arisen from the profound impact of many architectural traits on agronomic performance, and the genetic and hormonal regulation of these traits which makes them sensitive to both selective breeding and agronomic practices. This is particularly important in staple crops, and a large body of literature has, therefore, accumulated on the control of architectural phenotypes in cereals, particularly rice due to its twin role as one of the world's most important food crops as well as a model organism in plant biology and biotechnology. These studies have revealed many of the molecular mechanisms involved in the regulation of tiller/axillary branching, stem height, leaf and flower development, root architecture and the grain characteristics that ultimately help to determine yield. The advent of genome editing has made it possible, for the first time, to introduce precise mutations into cereal crops to optimize their architecture and close in on the concept of the ideotype. In this review, we consider recent genome editing studies that have focused on the examination (or reexamination) of plant architectural phenotypes in cereals and the modification of these traits for crop improvement.

APETALA2 functions as a temporal factor together with BLADE-ON-PETIOLE2 and MADS29 to control flower and grain development in barley.

Cereal grain develops from fertilised florets. Alterations in floret and grain development greatly influence grain yield and quality. Despite this, little is known about the underlying genetic control of these processes, especially in key temperate cereals such as barley and wheat. Using a combination of near-isogenic mutant comparisons, gene editing and genetic analyses, we reveal that HvAPETALA2 (HvAP2) controls floret organ identity, floret boundaries, and maternal tissue differentiation and elimination during grain development. These new roles of HvAP2 correlate with changes in grain size and HvAP2-dependent expression of specific HvMADS-box genes, including the B-sister gene, HvMADS29 Consistent with this, gene editing demonstrates that HvMADS29 shares roles with HvAP2 in maternal tissue differentiation. We also discovered that a gain-of-function HvAP2 allele masks changes in floret organ identity and grain size due to loss of barley LAXATUM.A/BLADE-ON-PETIOLE2 (HvBOP2) gene function. Taken together, we reveal novel pleiotropic roles and regulatory interactions for an AP2-like gene controlling floret and grain development in a temperate cereal.

Leaf angle distribution in Johnsongrass, leaf thickness in sorghum and Johnsongrass, and association with response to Colletotrichum sublineola.

Basal leaf angle distribution was surveyed in twenty-one Johnsongrass cultivars near the end of the vegetative stage. The angles increased from the top to the bottom leaves, and compared to cultivated grain sorghums, the average angle was larger in Johnsongrass. When basal leaf angle distribution data were correlated with pathogenicity test data from excised-leaf assays for three isolates of Colletotrichum sublineola, the results showed a weak positive correlation between basal leaf angle and pathogenicity level in Johnsongrass. In order to investigate a protective role of leaf thickness to C. sublineola, leaf thickness was measured in three sorghum cultivars and one Johnsongrass cultivar at the 8-leaf-stage. Leaf thickness near the apex, near the base, and half-way between the two points were measured in the top four leaves of each plant. Thickness of leaf blade and midrib were recorded separately. Using an excised-leaf-assay, the three points were inoculated with C. sublineola, and pathogenicity level was recorded 4-days-post-inoculation. Results showed strong negative correlations between leaf midrib thickness and pathogenicity level in sorghum and Johnsongrass but not in leaf blades.

Population structure and genetic diversity analyses of common bean germplasm collections of East and Southern Africa using morphological traits and high-density SNP markers.

Knowledge of genetic diversity in plant germplasm and the relationship between genetic factors and phenotypic expression is vital for crop improvement. This study's objectives were to understand the extent of genetic diversity and population structure in 60 common bean genotypes from East and Southern Africa. The common bean genotypes exhibited significant (p<0.05) levels of variability for traits such as days to flowering (DTF), days to maturity (DTM), number of pods per plant (NPP), number of seeds per pod (NSP), and grain yield per hectare in kilograms (GYD). About 47.82 per cent of the variation among the genotypes was explained by seven principal components (PC) associated with the following agronomic traits: NPP, NFF (nodes to first flower), DTF, GH (growth habit) and GYD. The SNP markers revealed mean gene diversity and polymorphic information content values of 0.38 and 0.25, respectively, which suggested the presence of considerable genetic variation among the assessed genotypes. Analysis of molecular variance showed that 51% of the genetic variation were between the gene pools, while 49% of the variation were within the gene pools. The genotypes were delineated into two distinct groups through the population structure, cluster and phylogenetic analyses. Genetically divergent genotypes such as DRK57, MW3915, NUA59, and VTTT924/4-4 with high yield and agronomic potential were identified, which may be useful for common bean improvement.