Genetic architecture of adult-plant resistance to stripe rust in bread wheat (Triticum aestivum L.) association panel.

Stripe rust, caused by Puccinia striiformis f. sp. tritici, is a severe disease in wheat worldwide, including Ethiopia, causing up to 100% wheat yield loss in the worst season. The use of resistant cultivars is considered to be the most effective and durable management technique for controlling the disease. Therefore, the present study targeted the genetic architecture of adult plant resistance to yellow rust in 178 wheat association panels. The panel was phenotyped for yellow rust adult-plant resistance at three locations. Phonological, yield, yield-related, and agro-morphological traits were recorded. The association panel was fingerprinted using the genotyping-by-sequencing (GBS) platform, and a total of 6,788 polymorphic single nucleotide polymorphisms (SNPs) were used for genome-wide association analysis to identify effective yellow rust resistance genes. The marker-trait association analysis was conducted using the Genome Association and Prediction Integrated Tool (GAPIT). The broad-sense heritability for the considered traits ranged from 74.52% to 88.64%, implying the presence of promising yellow rust resistance alleles in the association panel that could be deployed to improve wheat resistance to the disease. The overall linkage disequilibrium (LD) declined within an average physical distance of 31.44 Mbp at r2 = 0.2. Marker-trait association (MTA) analysis identified 148 loci significantly (p = 0.001) associated with yellow rust adult-plant resistance. Most of the detected resistance quantitative trait loci (QTLs) were located on the same chromosomes as previously reported QTLs for yellow rust resistance and mapped on chromosomes 1A, 1B, 1D, 2A, 2B, 2D, 3A, 3B, 3D, 4A, 4B, 4D, 5A, 5B, 6A, 6B, 7A, and 7D. However, 12 of the discovered MTAs were not previously documented in the wheat literature, suggesting that they could represent novel loci for stripe rust resistance. Zooming into the QTL regions in IWGSC RefSeq Annotation v1 identified crucial disease resistance-associated genes that are key in plants' defense mechanisms against pathogen infections. The detected QTLs will be helpful for marker-assisted breeding of wheat to increase resistance to stripe rust. Generally, the present study identified putative QTLs for field resistance to yellow rust and some important agronomic traits. Most of the discovered QTLs have been reported previously, indicating the potential to improve wheat resistance to yellow rust by deploying the QTLs discovered by marker-assisted selection.

Harnessing genome-wide genetic diversity, population structure and linkage disequilibrium in Ethiopian durum wheat gene pool.

Yanyang Liu, Henan Academy of Agricultural Sciences (HNAAS), China; Landraces are an important genetic source for transferring valuable novel genes and alleles required to enhance genetic variation. Therefore, information on the gene pool's genetic diversity and population structure is essential for the conservation and sustainable use of durum wheat genetic resources. Hence, the aim of this study was to assess genetic diversity, population structure, and linkage disequilibrium, as well as to identify regions with selection signature. Five hundred (500) individuals representing 46 landraces, along with 28 cultivars were evaluated using the Illumina Infinium 25K wheat SNP array, resulting in 8,178 SNPs for further analysis. Gene diversity (GD) and the polymorphic information content (PIC) ranged from 0.13-0.50 and 0.12-0.38, with mean GD and PIC values of 0.34 and 0.27, respectively. Linkage disequilibrium (LD) revealed 353,600 pairs of significant SNPs at a cut-off (r2 > 0.20, P < 0.01), with an average r2 of 0.21 for marker pairs. The nucleotide diversity (π) and Tajima's D (TD) per chromosome for the populations ranged from 0.29-0.36 and 3.46-5.06, respectively, with genome level, mean π values of 0.33 and TD values of 4.43. Genomic scan using the Fst outlier test revealed 85 loci under selection signatures, with 65 loci under balancing selection and 17 under directional selection. Putative candidate genes co-localized with regions exhibiting strong selection signatures were associated with grain yield, plant height, host plant resistance to pathogens, heading date, grain quality, and phenolic content. The Bayesian Model (STRUCTURE) and distance-based (principal coordinate analysis, PCoA, and unweighted pair group method with arithmetic mean, UPGMA) methods grouped the genotypes into five subpopulations, where landraces from geographically non-adjoining environments were clustered in the same cluster. This research provides further insights into population structure and genetic relationships in a diverse set of durum wheat germplasm, which could be further used in wheat breeding programs to address production challenges sustainably.

Hiding in plain sight: Genome-wide recombination and a dynamic accessory genome drive diversity in Fusarium oxysporum f.sp. ciceris.

Understanding the origins of variation in agricultural pathogens is of fundamental interest and practical importance, especially for diseases that threaten food security. Fusarium oxysporum is among the most important of soil-borne pathogens, with a global distribution and an extensive host range. The pathogen is considered to be asexual, with horizontal transfer of chromosomes providing an analog of assortment by meiotic recombination. Here, we challenge those assumptions based on the results of population genomic analyses, describing the pathogen's diversity and inferring its origins and functional consequences in the context of a single, long-standing agricultural system. We identify simultaneously low nucleotide distance among strains, and unexpectedly high levels of genetic and genomic variability. We determine that these features arise from a combination of genome-scale recombination, best explained by widespread sexual reproduction, and presence-absence variation consistent with chromosomal rearrangement. Pangenome analyses document an accessory genome more than twice the size of the core genome, with contrasting evolutionary dynamics. The core genome is stable, with low diversity and high genetic differentiation across geographic space, while the accessory genome is paradoxically more diverse and unstable but with lower genetic differentiation and hallmarks of contemporary gene flow at local scales. We suggest a model in which episodic sexual reproduction generates haplotypes that are selected and then maintained through clone-like dynamics, followed by contemporary genomic rearrangements that reassort the accessory genome among sympatric strains. Taken together, these processes contribute unique genome content, including reassortment of virulence determinants that may explain observed variation in pathogenic potential.

Genetic Diversity of Durum Wheat (Triticum turgidum L. ssp. durum, Desf) Germplasm as Revealed by Morphological and SSR Markers.

Ethiopia is considered a center of origin and diversity for durum wheat and is endowed with many diverse landraces. This research aimed to estimate the extent and pattern of genetic diversity in Ethiopian durum wheat germplasm. Thus, 104 durum wheat genotypes representing thirteen populations, three regions, and four altitudinal classes were investigated for their genetic diversity, using 10 grain quality- and grain yield-related phenotypic traits and 14 simple sequence repeat (SSR) makers. The analysis of the phenotypic traits revealed a high mean Shannon diversity index (H' = 0.78) among the genotypes and indicated a high level of phenotypic variation. The principal component analysis (PCA) classified the genotypes into three groups. The SSR markers showed a high mean value of polymorphic information content (PIC = 0.50) and gene diversity (h = 0.56), and a moderate number of alleles per locus (Na = 4). Analysis of molecular variance (AMOVA) revealed a high level of variation within populations, regions, and altitudinal classes, accounting for 88%, 97%, and 97% of the total variation, respectively. Pairwise genetic differentiation and Nei's genetic distance analyses identified that the cultivars are distinct from the landrace populations. The distance-based (Discriminant Analysis of Principal Component (DAPC) and Minimum Spanning Network (MSN)) and model-based population stratification (STRUCTURE) methods of clustering grouped the genotypes into two clusters. Both the phenotypic data-based PCA and the molecular data-based DAPC and MSN analyses defined distinct groupings of cultivars and landraces. The phenotypic and molecular diversity analyses highlighted the high genetic variation in the Ethiopian durum wheat gene pool. The investigated SSRs showed significant associations with one or more target phenotypic traits. The markers identify landraces with high grain yield and quality traits. This study highlights the usefulness of Ethiopian landraces for cultivar development, contributing to food security in the region and beyond.

Genome analyses reveal population structure and a purple stigma color gene candidate in finger millet.

Finger millet is a key food security crop widely grown in eastern Africa, India and Nepal. Long considered a 'poor man's crop', finger millet has regained attention over the past decade for its climate resilience and the nutritional qualities of its grain. To bring finger millet breeding into the 21st century, here we present the assembly and annotation of a chromosome-scale reference genome. We show that this ~1.3 million years old allotetraploid has a high level of homoeologous gene retention and lacks subgenome dominance. Population structure is mainly driven by the differential presence of large wild segments in the pericentromeric regions of several chromosomes. Trait mapping, followed by variant analysis of gene candidates, reveals that loss of purple coloration of anthers and stigma is associated with loss-of-function mutations in the finger millet orthologs of the maize R1/B1 and Arabidopsis GL3/EGL3 anthocyanin regulatory genes. Proanthocyanidin production in seed is not affected by these gene knockouts.

Host Specificity Controlled by PWL1 and PWL2 Effector Genes in the Finger Millet Blast Pathogen Magnaporthe oryzae in Eastern Africa.

Magnaporthe oryzae, a devastating pathogen of finger millet (Eleusine coracana), secretes effector molecules during infection to manipulate host immunity. This study determined the presence of avirulence effector genes PWL1 and PWL2 in 221 Eleusine blast isolates from eastern Africa. Most Ethiopian isolates carried both PWL1 and PWL2. Kenyan and Ugandan isolates largely lacked both genes, and Tanzanian isolates carried either PWL1 or lacked both. The roles of PWL1 and PWL2 towards pathogenicity on alternative chloridoid hosts, including weeping lovegrass (Eragrostis curvula), were also investigated. PWL1 and PWL2 were cloned from Ethiopian isolate E22 and were transformed separately into Ugandan isolate U34, which lacked both genes. Resulting transformants harboring either gene gained varying degrees of avirulence on Eragrostis curvula but remained virulent on finger millet. Strains carrying one or both PWL1 and PWL2 infected the chloridoid species Sporobolus phyllotrichus and Eleusine tristachya, indicating the absence of cognate resistance (R) genes for PWL1 and PWL2 in these species. Other chloridoid grasses, however, were fully resistant, regardless of the presence of one or both PWL1 and PWL2, suggesting the presence of effective R genes against PWL and other effectors. Partial resistance in some Eragrostis curvula accessions to some blast isolates lacking PWL1 and PWL2 also indicated the presence of other interactions between fungal avirulence (AVR) genes and host resistance (R) genes. Related chloridoid species thus harbor resistance genes that could be useful to improve finger millet for blast resistance. Conversely, loss of AVR genes in the fungus could expand its host range, as demonstrated by the susceptibility of Eragrostis curvula to finger millet blast isolates that had lost PWL1 and PWL2. [Formula: see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.

Corrigendum to "Genetic diversity and population structure of sorghum [Sorghum bicolor (L.) Moench] genotypes in Ethiopia as revealed by microsatellite markers" [Heliyon Volume 9, Issue 1, January 2023, Article e12830].

[This corrects the article DOI: 10.1016/j.heliyon.2023.e12830.].

Evaluation of finger millet (Eleusine coracana (L.) Gaertn.) in multi-environment trials using enhanced statistical models.

Spatial variation and genotype by environment (GxE) interaction are common in varietal selection field trials and pose a significant challenge for plant breeders when comparing the genetic potential of different varieties. Efficient statistical methods must be employed for the evaluation of finger millet breeding trials to accurately select superior varieties that contribute to agricultural productivity. The objective of this study was to improve selection strategies in finger millet breeding in Ethiopia through modeling of spatial field trends and the GxE interaction. A dataset of seven multi-environment trials (MET) conducted in randomized complete block design (RCBD) with two replications laid out in rectangle (row x column) arrays of plots was used in this study. The results revealed that, under the linear mixed model, the spatial and factor analytic (FA) models were efficient methods of data analysis for this study, and this was demonstrated with evidence of heritability measure. We found two clusters of correlated environments that helped to select superior and stable varieties through ranking average Best Linear Unbiased Predictors (BLUPs) within clusters. The first cluster was chosen because it contained a greater number of environments with high heritability. Based on this cluster, Bako-09, 203439, 203325, and 203347 were the top four varieties with relatively high yield performance and stability across correlated environments. Hence, scaling up the use of this efficient analysis method will improve the selection of superior finger millet varieties.

Genetic diversity and population structure of sorghum [Sorghum bicolor (L.) Moench] genotypes in Ethiopia as revealed by microsatellite markers.

In the tropical and semi-arid regions of Africa, sorghum [Sorghum bicolor (L.) Moench] is mainly grown as a major food security crop. Understanding the extent and pattern of genetic variability is a prerequisite criterion for sorghum improvement and conservation. The genetic diversity and population structure of 100 genotypes of sorghum were profiled using 15 microsatellite loci. A total of 108 alleles, with an overall mean of 7.2 alleles per locus, were produced by all of the microsatellite loci used due to their high polymorphism. Polymorphic information content values ranging from 0.68 to 0.89 indicated that all of the loci are effective genetic tools for analysing the genetic structure of sorghum. Different diversity metrics were used to evaluate genetic diversity among populations, and Nei's gene diversity index ranged from 0.74 to 0.81 with an overall mean of 0.78. Poor genetic differentiation (FST: 0.02; p < 0.0001) was found, where 98% of entire variability was accounted by the within populations genetic variability, leaving only 2.32% among populations. The highest genetic differentiation and Nis's genetic distance were observed between the sorghum populations of the Southern Nation and Nationalities Peoples and Dire Dawa regions. Due to increased gene flow (Nm = 10.53), the clustering, principal coordinate analysis and STRUCTURE analysis failed to categorize the populations into genetically different groups corresponding to their geographic sampling areas. In general, it was found that the microsatellite loci were highly informative and therefore valuable genetic tools to unfold the genetic diversity and population structure of Ethiopian sorghum genotypes. Among the five populations studied, sorghum populations from Amhara and Oromia had the highest genetic variation, indicating that the regions could be perhaps hotspots for useful alleles for the development of better-performing genotypes, and also for designing appropriate germplasm management strategies.

Analysis of genetic diversity and population structure of oilseed crop noug (Guizotia abyssinica) accessions collected from Ethiopia.

BACKGROUND: Noug is an Ethiopian indigenous oilseed crop cultivated primarily for its oil and various economic importance. Evaluating the extent of genetic diversity within and among populations is one of the most important steps in breeding and conservation measures. Thus, this study aimed to uncover the extent of genetic diversity and population structure of noug accessions collected from different regions of Ethiopia using microsatellite markers. METHODS AND RESULTS: A total of 161 accessions from fourteen regions of Ethiopia, including some from Eritrea using 13 microsatellite markers were analyzed. All the 13 microsatellite markers were polymorphic and highly informative with a mean PIC value of 0.82. The analysis generated a total of 158 alleles with a mean of 12.15 per locus. The overall mean of Shannon information index and heterozygosity/gene diversity were 1.57 and 0.74, respectively suggesting the presence of higher genetic diversity across the collection regions. AMOVA revealed that 96.06% of the total genetic variation was attributed to within populations while only 3.94% was attributed to among populations. Likewise, the dendrogram clustering, PCoA, and the model-based population structure analysis didn't exactly corresponded the grouping of the genotypes according to their regions of origin. CONCLUSION: The microsatellites used in the present study are highly informative and could be targeted for developing markers for future marker-assisted breeding. Genotypes collected from Shewa, Wollo, Gojjam, Tigray, and B/G showed a higher genetic diversity and private alleles as compared to other populations. Hence, these areas can be considered as hotspots which could help for the identification of genotypes that can be used in breeding programs as well as for the implementation of further conservation programs.

Genetic composition and diversity of Arabica coffee in the crop's centre of origin and its impact on four major fungal diseases.

Conventional wisdom states that genetic variation reduces disease levels in plant populations. Nevertheless, crop species have been subject to a gradual loss of genetic variation through selection for specific traits during breeding, thereby increasing their vulnerability to biotic stresses such as pathogens. We explored how genetic variation in Arabica coffee sites in southwestern Ethiopia was related to the incidence of four major fungal diseases. Sixty sites were selected along a gradient of management intensity, ranging from nearly wild to intensively managed coffee stands. We used genotyping-by-sequencing of pooled leaf samples (pool-GBS) derived from 16 individual coffee shrubs in each of the 60 sites to assess the variation in genetic composition (multivariate: reference allele frequency) and genetic diversity (univariate: mean expected heterozygosity) between sites. We found that genetic composition had a clear spatial pattern and that genetic diversity was higher in less managed sites. The incidence of the four fungal diseases was related to the genetic composition of the coffee stands, but in a specific way for each disease. In contrast, genetic diversity was only related to the within-site variation of coffee berry disease, but not to the mean incidence of any of the four diseases across sites. Given that fungal diseases are major challenges of Arabica coffee in its native range, our findings that genetic composition of coffee sites impacted the major fungal diseases may serve as baseline information to study the molecular basis of disease resistance in coffee. Overall, our study illustrates the need to consider both host genetic composition and genetic diversity when investigating the genetic basis for variation in disease levels.

Finger millet RNA-seq reveals differential gene expression associated with tolerance to aluminum toxicity and provides novel genomic resources.

Eleusine coracana, finger millet, is a multipurpose crop cultivated in arid and semi-arid regions of Africa and Asia. RNA sequencing (RNA-seq) was used in this study to obtain valuable genomic resources and identify genes differentially expressed between Al-tolerant and Al-susceptible genotypes. Two groups of finger millet genotypes were used: Al-tolerant (215836, 215845, and 229722) and Al-susceptible (212462, 215804 and 238323). The analysis of the RNA-seq data resulted in 198,546 unigenes, 56.5% of which were annotated with significant hits in one or more of the following six databases: NR (48.8%), GO (29.7%), KEGG (45%), PlantTFDB (19.0%), Uniprot (49.2%), and NT (46.2%). It is noteworthy that only 220 unigenes in the NR database had significant hits against finger millet sequences suggesting that finger millet's genomic resources are scarce. The gene expression analysis revealed that 322 genes were significantly differentially expressed between the Al-tolerant and Al-susceptible genotypes, of which 40.7% were upregulated while 59.3% were downregulated in Al-tolerant genotypes. Among the significant DEGs, 54.7% were annotated in the GO database with the top hits being ATP binding (GO:0005524) and DNA binding (GO:0003677) in the molecular function, DNA integration (GO:0015074) and cell redox homeostasis in the biological process, as well as cellular anatomical entity and intracellular component in the cellular component GO classes. Several of the annotated DEGs were significantly enriched for their corresponding GO terms. The KEGG pathway analysis resulted in 60 DEGs that were annotated with different pathway classes, of which carbohydrate metabolism and signal transduction were the most prominent. The homologs of a number of significant DEGs have been previously reported as being associated with Al or other abiotic stress responses in various crops, including carboxypeptidase SOL1, HMA3, AP2, bZIP, C3H, and WRKY TF genes. A more detailed investigation of these and other DEGs will enable genomic-led breeding for Al tolerance in finger millet. RNA-seq data analysis also yielded 119,073 SNP markers, the majority of which had PIC values above 0.3, indicating that they are highly informative. Additionally, 3,553 single-copy SSR markers were identified, of which trinucleotide SSRs were the most prevalent. These genomic resources contribute substantially to the enrichment of genomic databases for finger millet, and facilitate future research on this crop.

Novel sources of drought tolerance in sorghum landraces revealed via the analyses of genotype-by-environment interactions.

Globally, sorghum is the fifth most important crop, which is used for food, feed and fuel. However, its production and productivity are severely limited by various stresses, including drought. Hence, this study aimed to determine the responses of different drought-tolerance related traits in the Ethiopian sorghum germplasm through multi-environment field trials, thereby identifying novel sources of germplasm that can be used for breeding the crop for drought-tolerance. Three hundred twenty sorghum landraces and four improved varieties were grown at three sites within drought-prone areas (Melkassa, Mieso and Mehoni) in Ethiopia. The targeted traits were chlorophyll content at flowering (CHLF), chlorophyll content at maturity (CHLM), green leaf number at flowering (GLNF), stay-green (SG), flag leaf area (FLA), peduncle length (PDL), and panicle exertion (PAE). Multi-variate analyses of the collected data revealed the presence of high phenotypic variation in all traits. The combined and AMMI Analysis of variance showed that phenotypic variation due to the genotypes was higher for SG, CHLM, CHLF and GLNF and lower for FLA, PE and PDL in comparison with variation due to the environments or genotype by environment interactions. High broad sense heritability was observed for CHLF, CHLM, SG, GLNF, FLA, and PDL, whereas PAE showed moderate heritability. Due to the high heritability of chlorophyll content and the relatively small effect of environmental factors on it, it could serve as a criterion for selecting desirable genotypes for drought-tolerant breeding in sorghum. It has been found that chlorophyll content has a significant positive correlation with stay-green and grain yield, indicating that high chlorophyll content contributes to increasing grain yield by delaying the process of leaf senescence. The analyses of AMMI, GGE biplot, and genotype selection index revealed that several sorghum landraces outperformed the improved varieties with respect to CHLF, CHLM, and SG. Such landraces could serve as novel sources of germplasm for improving drought tolerance through breeding.

Genome-wide analyses using multi-locus models revealed marker-trait associations for major agronomic traits in Sorghum bicolor.

Globally, sorghum is the fifth most important cereal crop, and it is a major crop in Ethiopia, where it has a high genetic diversity. The country's sorghum gene pool contributes significantly to sorghum improvement worldwide. This study aimed to identify genomic regions and candidate genes associated with major agronomic traits in sorghum by using its genetic resources in Ethiopia for a genome-wide association study (GWAS). Phenotypic data of days to flowering (DTF), plant height (PH), panicle length (PALH), panicle width (PAWD), panicle weight (PAWT), and grain yield (GY) were collected from a GWAS panel comprising 324 sorghum accessions grown in three environments. SeqSNP, a targeted genotyping method, was used to genotype the panel using 5,000 gene-based single nucleotide polymorphism (SNP) markers. For marker-trait association (MTA) analyses, fixed and random model circulating probability unification (FarmCPU), and Bayesian-information and linkage-disequilibrium iteratively nested keyway (BLINK) models were used. In all traits, high phenotypic variation was observed, with broad-sense heritability ranging from 0.32 (for GY) to 0.90 (for PALH). A population structure, principal component analysis, and kinship analysis revealed that the accessions could be divided into two groups. In total, 54 MTAs were identified, 11 of which were detected by both BLINK and farmCPU. MTAs identified for each trait ranged from five (PAWT and GY) to fourteen (PH) representing both novel and previously identified quantitative trait loci (QTLs). Three SNPs were associated with more than one trait, including a SNP within the Sobic.004G189200 gene that was associated with PH and PAWT. Major effect SNP loci, Sbi2393610 (PVE = 23.3%), Sbi10438246 (PVE = 35.2%), Sbi17789352 (PVE = 11.9%) and Sbi30169733 (PVE = 18.9%) on chromosomes 1, 3, 5 and 9 that showed strong association signals for PAWD, DTF, GY and PALH, respectively, were major findings of this study. The SNP markers and candidate genes identified in this study provide insights into the genetic control of grain yield and related agronomic traits, and once validated, the markers could be used in genomics-led breeding.

Multivariate analyses of Ethiopian durum wheat revealed stable and high yielding genotypes.

Improving crop adaptation and stability across diverse and changing environmental conditions is essential to increasing grain yield per unit area. In turn, this contributes to meeting the increasing global food demand. Nevertheless, a number of factors challenge the efficiency of crop improvement programs, of which genotype-by-environment interaction (GEI) is one of the major factors. This study aimed to evaluate the performance and phenotypic stability of 385 Ethiopian durum wheat landraces and 35 cultivars; assess the pattern of genotype by environment interaction (GEI) effect, and identify stable and high-yielding landraces or cultivars using the additive main effect and multiplicative interaction (AMMI) and genotype main effect plus genotype by environment interaction biplot (GGE-biplot). The experiment was laid out in an alpha lattice design with two replications at five test sites (Akaki, Chefe Donsa, Holeta, Kulumsa, and Sinana). The combined analysis of variance revealed highly significant effects (P ≤ 0.01) of environments (E), genotype (G), and GEI on a phenotypic variation of traits evaluated, including grain yield. For all traits, the amount of phenotypic variance and GEI explained by the GGE biplot was higher than in AMMI2, but both exhibited significant effects of E and GEI on the genotypes. The AMMI model identified G169, G420, G413, G139, G415, G416, G417, and G418 as stable genotypes across testing sites. Whereas, the GGE biplot identified G169, G420, G415, G139, G106, G412, G413, and G417 as both high-yielding and stable across test sites. Hence, genotypes identified as stable and high yielding in the present study could be used in a durum wheat breeding program aimed at identifying genes and molecular markers associated with the crop's productivity traits as well as developing stable and high-yielding cultivars for use in East Africa and beyond.

RNA-Seq Provides Novel Genomic Resources for Noug (Guizotia abyssinica) and Reveals Microsatellite Frequency and Distribution in Its Transcriptome.

Genomic resources and tools are essential for improving crops and conserving their genetic resources. Guizotia abyssinica (noug), an outcrossing edible oilseed crop, has highly limited genomic resources. Hence, RNA-Seq based transcriptome sequencing of 30 noug genotypes was performed to generate novel genomic resources and assess their usefulness. The genotypes include self-compatible and self-incompatible types, which differ in maturity time, photoperiod sensitivity, or oil content and quality. RNA-Seq was performed on Illumina HiSeq 2500 platform, and the transcript was reconstructed de novo, resulting in 409,309 unigenes. The unigenes were characterized for simple sequence repeats (SSRs), and served as a reference for single nucleotide polymorphism (SNP) calling. In total, 40,776 SSRs were identified in 35,639 of the 409,309 unigenes. Of these, mono, di, tri, tetra, penta and hexanucleotide repeats accounted for 55.4, 20.8, 21.1, 2.3, 0.2, and 0.2%, respectively. The average G+C content of the unigenes and their SSRs were 40 and 22.1%, respectively. The vast majority of mononucleotide repeat SSRs (97%) were of the A/T type. AG/CT and CCA/TGG were the most frequent di and trinucleotide repeat SSRs. A different number of single nucleotide polymorphism (SNP) loci were discovered in each genotype, of which 1,687 were common to all 30 genotypes and 5,531 to 28 of them. The mean observed heterozygosity of the 5,531 SNPs was 0.22; 19.4% of them had polymorphism information content above 0.30 while 17.2% deviated significantly from Hardy-Weinberg equilibrium (P < 0.05). In both cluster and principal coordinate analyses, the genotypes were grouped into four major clusters. In terms of population structure, the genotypes are best represented by three genetic populations, with significant admixture within each. Genetic similarity between self-compatible genotypes was higher, due to the narrow genetic basis, than that between self-incompatible genotypes. The genotypes that shared desirable characteristics, such as early maturity, and high oil content were found to be genetically diverse, and hence superior cultivars with multiple desirable traits can be developed through crossbreeding. The genomic resources developed in this study are vital for advancing research in noug, such as genetic linkage mapping and genome-wide association studies, which could lead to genomic-led breeding.

Novel GBS-Based SNP Markers for Finger Millet and Their Use in Genetic Diversity Analyses.

Eleusine coracana (L.) Gaertn., commonly known as finger millet, is a multipurpose crop used for food and feed. Genomic tools are required for the characterization of crop gene pools and their genomics-led breeding. High-throughput sequencing-based characterization of finger millet germplasm representing diverse agro-ecologies was considered an effective method for determining its genetic diversity, thereby suggesting potential candidates for breeding. In this study, the genotyping-by-sequencing (GBS) method was used to simultaneously identify novel single nucleotide polymorphism (SNP) markers and genotype 288 finger millet accessions collected from Ethiopia and Zimbabwe. The accessions were characterized at individual and group levels using 5,226 bi-allelic SNPs, with a minimum allele frequency (MAF) of above 0.05, distributed across 2,500 scaffolds of the finger millet reference genome. The polymorphism information content (PIC) of the SNPs was 0.23 on average, and a quarter of them have PIC values over 0.32, making them highly informative. The grouping of the 288 accessions into seven populations based on geographic proximity and the potential for germplasm exchange revealed a narrow range of observed heterozygosity (Ho; 0.09-0.11) and expected heterozygosity (He) that ranged over twofold, from 0.11 to 0.26. Alleles unique to the different groups were also identified, which merit further investigation for their potential association with desirable traits. The analysis of molecular variance (AMOVA) revealed a highly significant genetic differentiation among groups of accessions classified based on the geographic region, country of origin, days to flowering, panicle type, and Al tolerance (p < 0.01). The high genetic differentiation between Ethiopian and Zimbabwean accessions was evident in the AMOVA, cluster, principal coordinate, and population structure analyses. The level of genetic diversity of finger millet accessions varies moderately among locations within Ethiopia, with accessions from the northern region having the lowest level. In the neighbor-joining cluster analysis, most of the improved cultivars included in this study were closely clustered, probably because they were developed using genetically less diverse germplasm and/or selected for similar traits, such as grain yield. The recombination of alleles via crossbreeding genetically distinct accessions from different regions of the two countries can potentially lead to the development of superior cultivars.

SARS-CoV-2 Genome Sequence Obtained from Ethiopia.

The coding-complete severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genome sequences from 15 nasopharyngeal swabs collected in Addis Ababa, Ethiopia, during the period from December 2020 to March 2021 were determined using Illumina MiSeq technology. A sequence analysis identified that the B.1 SARS-CoV-2 lineage was most prevalent with the worrying emergence of B.1.1.7 in June 2021.