Genetic Heterogeneity in Cowpea Genotypes (Vigna unguiculata L. Walp) Using DArTseq (GBS)-Derived Single Nucleotide Polymorphisms.

Cowpeas (Vigna unguiculata L. Walp) have been credible constituents of nutritious food and forage in human and animal diets since the Neolithic era. The modern technique of Diversity Array Technology (DArTseq) is both cost-effective and rapid in producing thousands of high-throughputs, genotyped, single nucleotide polymorphisms (SNPs) in wide-genomic analyses of genetic diversity. The aim of this study was to assess the heterogeneity in cowpea genotypes using DArTseq-derived SNPs. A total of 92 cowpea genotypes were selected, and their fourteen-day-old leaves were freeze-dried for five days. DNA was extracted using the CTAB protocol, genotyped using DArTseq, and analysed using DArTsoft14. A total of 33,920 DArTseq-derived SNPs were recalled for filtering analysis, with a final total of 16,960 SNPs. The analyses were computed using vcfR, poppr, and ape in R Studio v1.2.5001-3 software. The heatmap revealed that the TVU 9596 (SB26), Orelu (SB72), 90K-284-2 (SB55), RV 403 (SB17), and RV 498 (SB16) genotypes were heterogenous. The mean values for polymorphic information content, observed heterozygosity, expected heterozygosity, major allele frequency, and the inbreeding coefficient were 0.345, 0.386, 0.345, 0.729, and 0.113, respectively. Moreover, they validated the diversity of the evaluated cowpea genotypes, which could be used for potential breeding programmes and management of cowpea germplasm.

Seed morphology of 31 Euphorbia L. species (Euphorbiaceae) in Turkey and their taxonomic significance.

This paper includes a comprehensive taxonomical study based on seed morphology of 31 Euphorbia L species from Türkiye. The studied Euphorbia taxa have been examined for morphological traits such as seed color, dimensions, surface ornamentation, cell wall structures, lipid granule presence, and caruncle shape and dimensions with Scanning electron microscopy (SEM) and stereo microscopy to develop a better understanding of the basis of its species. The outcomes show that the species differ based on seed shape and color. The seed width dimensions are between 0.55 and 3.83 mm and the length dimensions are between 1.03 and 5.87 mm. Euphorbia lathyris, E. prostrata, and E. nutans are marked differently from the rest of the studied species based on their seed dimension. The seed surface ornamentation is classified into 12 different types: tuberculate, reticulate, areolate, colliculate, verrucate, alveolate, rugose, alveolate-reticulate, slightly reticulate, reticulate-areolate, pusticulate, and ruminate. The most common form is reticulate, found in eight species. The tuberculate (in E. helioscopia), areolate (in E. oblongata), slightly reticulate (in E. amygdaloides), and ruminate (in E. herniariifolia) ornamentation types are each characterized by only one species. The presence of lipid granules and anticlinal and periclinal cell walls disclose interspecific relationships within the examined taxa. Also, an identification key is offered for the studied species based on seed characters. RESEARCH HIGHLIGHTS: The seeds of Turkish Euphorbia species have been studied in depth. The morphological characters of seeds of Turkish Euphorbia species have been examined utilizing SEM and light microscopy for the first time and discussed the taxonomic practice of these characteristics. A dichotomous key containing seed morphological data has presented.

MMV method: a new approach to compare protein sequences under binary representation.

In the present work, a new form of descriptor using minimal moment vector (MMV) is introduced to compare protein sequences in the frequency domain under their component wise binary representations. From every sequence, 20 different binary component sequences are formed, each corresponding to 20 amino acids. Each such vector is now shifted from the time domain to the frequency domain by applying the Fast Fourier Transform (FFT). Next, the power spectrum calculated from the FFT values for each component sequence is so normalized that the sum of the components equals 1. The descriptor is defined as a 20-component vector composed of the 20 second-order minimal moments calculated from the normalized spectrum of the 20 component sequences. Once the descriptor is known, the distance matrix is created by applying the Euclidean Distance measure. The phylogenetic tree is generated by applying the unweighted pair group method with the arithmetic mean (UPGMA) algorithm using Molecular Evolutionary Genetics Analysis11 (MEGA11) software. In this work, the datasets used for similarity studies are 9 NADH dehydrogenase 5 (ND5), 12 Baculoviruses, 24 Transferrins (TF) proteins, and 50 Spike Protein of coronavirus. A qualitative measure using rationalized perception is used to compare the effectiveness of the proposed method. Quantitative measure based on symmetric distance (SD) is used to compare the phylogenetic trees of the present method with those obtained by other methods. It is observed that the phylogenetic trees generated by the proposed technique are at par with their known biological references, and they produce results better than those of the earlier methods.Communicated by Ramaswamy H. Sarma.

GPOSYSH: Genomic Prediction of Oryza Sativa Yield and Subpopulation Using Hybrid Methods.

Accurate prediction of breeding values is challenging due to the genotype-phenotype relationship is crucial and necessary for producing crops with elite genotypes. This paper is about investigating and predicting the phenotypic trait Height and Yeild in a genotype. BACKGROUND: Most of the existing studies focus on genetic methods or Machine learning models, in this, we implemented a hybrid combination of genetic methods and machine learning models that accurately predicted phenotypic trait yield, height and subpopulation. METHODOLOGY: Our proposed methodology for genomic prediction of yield in Oryza sativa (rice) involves a two-level classification approach. First, we classify biological sequences and cluster them using the UPGMA algorithm on a phylogenetic tree. Then, we use advanced machine learning techniques like Random Forest, and K-Nearest Neighbours to predict GEBVs with 85- 95% accuracy on rice subpopulations. RESULTS: we achieved an accuracy of 93% when compared with other stated literature in this paper. CONCLUSION: This approach overcomes limitations and effectively enhances crop breeding by capturing the genotype-phenotype relationship.

Agro-morphological, biochemical, and molecular markers of barley genotypes grown under salinity stress conditions.

The aim of this study was to evaluate the impact of salt stress on morphological, yield, biochemical, and molecular attributes of different barley genotypes. Ten genotypes were cultivated at Fayoum Research Station, El-Fayoum Governorate, Egypt, during two seasons (2020-2021 and 2021-2022), and they were exposed to two different salt concentrations (tap water as a control and 8000 ppm). The results showed that genotypes and salt stress had a significant impact on all morphological and physiological parameters. The morphological parameters (plant height) and yield attributes (spike length, number of grains per spike, and grain yield per plant) of all barley genotypes were significantly decreased under salt stress as compared to control plants. Under salt stress, the total soluble sugars, proline, total phenol, total flavonoid, ascorbic acid, malondialdehyde, hydrogen peroxide, and sodium contents of the shoots of all barley genotypes significantly increased while the potassium content decreased. L1, which is considered a sensitive genotype was more affected by salinity stress than the tolerance genotypes L4, L6, L9, and Giza 138. SDS-PAGE of seed proteins demonstrated high levels of genetic variety with a polymorphism rate of 42.11%. All genotypes evaluated revealed significant variations in the seed protein biochemical markers, with new protein bands appearing and other protein bands disappearing in the protein patterns of genotypes cultivated under various conditions. Two molecular marker techniques (SCoT and ISSR primers) were used in this study. Ten Start Codon Targeted (SCoT) primers exhibited a total of 94 fragments with sizes ranging from 1800 base pairs to 100 base pairs; 29 of them were monomorphic, and 65 bands, with a polymorphism of 62.18%, were polymorphic. These bands contained 21 unique bands (9 positive specific markers and 12 negative specific markers). A total of 54 amplified bands with molecular sizes ranging from 2200 to 200 bp were produced using seven Inter Simple Sequence Repeat (ISSR) primers; 31 of them were monomorphic bands and 23 polymorphic bands had a 40.9% polymorphism. The techniques identified molecular genetic markers associated with salt tolerance in barley crop and successfully marked each genotype with distinct bands. The ten genotypes were sorted into two main groups by the unweighted pair group method of arithmetic averages (UPGMA) cluster analysis based on molecular markers and data at a genetic similarity coefficient level of 0.71.

Differential Detection of Alternaria alternata Haplotypes Isolated from Carya illinoinensis Using PCR-RFLP Analysis of Alt a1 Gene Region.

Alternaria black spot disease on pecan is caused by the opportunistic pathogen Alternaria alternata and poses a serious threat to the local South African and global pecan industry. Several diagnostic molecular marker applications have been established and used in the screening of various fungal diseases worldwide. The present study investigated the potential for polymorphism within samples of A. alternata isolates obtained from eight different geographical locations in South Africa. Pecan (Carya illinoinensis) leaves, shoots, and nuts-in-shuck with Alternaria black spot disease were sampled, and 222 A. alternata isolates were retrieved. For rapid screening to identify Alternaria black spot pathogens, polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) analysis of the Alternaria major allergen (Alt a1) gene region was used, followed by the digestion of the amplicons with HaeIII and HinfI endonucleases. The assay resulted in five (HaeIII) and two (HinfI) band patterns. Unique banding patterns from the two endonucleases showed the best profile and isolates were grouped into six clusters using a UPGMA (unweighted pair group method with arithmetic averages) distance matrix (Euclidean) dendrogram method on R-Studio. The analysis confirmed that the genetic diversity of A. alternata does not depend on host tissues or the pecan cultivation region. The grouping of selected isolates was confirmed by DNA sequence analysis. The Alt a1 phylogeny corroborated no speciation within the dendrogram groups and showed 98-100% bootstrap similarity. This study reports the first documented rapid and reliable technique for routine screening identification of pathogens causing Alternaria black spot in South Africa.

PTGAC Model: A machine learning approach for constructing phylogenetic tree to compare protein sequences.

This work proposes a machine learning-based phylogenetic tree generation model based on agglomerative clustering (PTGAC) that compares protein sequences considering all known chemical properties of amino acids. The proposed model can serve as a suitable alternative to the Unweighted Pair Group Method with Arithmetic Mean (UPGMA), which is inherently time-consuming in nature. Initially, principal component analysis (PCA) is used in the proposed scheme to reduce the dimensions of 20 amino acids using seven known chemical characteristics, yielding 20 TP (Total Points) values for each amino acid. The approach of cumulative summing is then used to give a non-degenerate numeric representation of the sequences based on these 20 TP values. A special kind of three-component vector is proposed as a descriptor, which consists of a new type of non-central moment of orders one, two, and three. Subsequently, the proposed model uses Euclidean Distance measures among the descriptors to create a distance matrix. Finally, a phylogenetic tree is constructed using hierarchical agglomerative clustering based on the distance matrix. The results are compared with the UPGMA and other existing methods in terms of the quality and time of constructing the phylogenetic tree. Both qualitative and quantitative analysis are performed as key assessment criteria for analyzing the performance of the proposed model. The qualitative analysis of the phylogenetic tree is performed by considering rationalized perception, while the quantitative analysis is performed based on symmetric distance (SD). On both criteria, the results obtained by the proposed model are more satisfactory than those produced earlier on the same species by other methods. Notably, this method is found to be efficient in terms of both time and space requirements and is capable of dealing with protein sequences of varying lengths.

Association Mapping of Amylose Content in Maize RIL Population Using SSR and SNP Markers.

The ratio of amylose to amylopectin in maize kernel starch is important for the appearance, structure, and quality of food products and processing. This study aimed to identify quantitative trait loci (QTLs) controlling amylose content in maize through association mapping with simple sequence repeat (SSR) and single-nucleotide polymorphism (SNP) markers. The average value of amylose content for an 80-recombinant-inbred-line (RIL) population was 8.8 ± 0.7%, ranging from 2.1 to 15.9%. We used two different analyses-Q + K and PCA + K mixed linear models (MLMs)-and found 38 (35 SNP and 3 SSR) and 32 (29 SNP and 3 SSR) marker-trait associations (MTAs) associated with amylose content. A total of 34 (31 SNP and 3 SSR) and 28 (25 SNP and 3 SSR) MTAs were confirmed in the Q + K and PCA + K MLMs, respectively. This study detected some candidate genes for amylose content, such as GRMZM2G118690-encoding BBR/BPC transcription factor, which is used for the control of seed development and is associated with the amylose content of rice. GRMZM5G830776-encoding SNARE-interacting protein (KEULE) and the uncharacterized marker PUT-163a-18172151-1376 were significant with higher R2 value in two difference methods. GRMZM2G092296 were also significantly associated with amylose content in this study. This study focused on amylose content using a RIL population derived from dent and waxy inbred lines using molecular markers. Future studies would be of benefit for investigating the physical linkage between starch synthesis genes using SNP and SSR markers, which would help to build a more detailed genetic map and provide new insights into gene regulation of agriculturally important traits.

Genetic Diversity and Population Structure of Normal Maize Germplasm Collected in South Sudan Revealed by SSR Markers.

Maize is one of the leading global cereals, and in South Sudan maize cultivation occurs in nearly all of the country's agro-ecological zones. Despite its widespread cultivation, farmers in South Sudan depend on undeveloped varieties, which results in very low yields in the field. In the current study, 27 simple sequence repeat (SSR) markers were used to investigate genetic diversity and population structures among 37 landrace maize accessions collected from farmers' fields in South Sudan. In total, 200 alleles were revealed with an average of 7.4 alleles per locus and a range from 3.0 to 13.0 alleles per locus. The observed heterozygosity values ranged from 0.06 to 0.91 with an average of 0.35. High polymorphic information content (PIC) values were identified with a mean of 0.69, which indicates the informativeness of the chosen SSR loci. Genetic structure analysis revealed a moderate genetic differentiation among the maize populations with a fixation index of 0.16, while there was very high genetic differentiation within the groups of populations of three regions with a mean fixation index (F) of 0.37. An unweighted pair group method with an arithmetic mean (UPGMA) dendrogram clustered the 37 maize accessions into three groups with 43% genetic similarity. The clustering pattern of the maize accessions was moderately consistent with their collection area. The findings of this study will provide maize breeders with a better understanding of maize diversification as well as a reserve of genetic resources for use in the selection of advantageous and useful resources for the development of maize varieties in South Sudan.

Simple Sequence Repeat Markers Reveal Genetic Diversity and Population Structure of Bolivian Wild and Cultivated Tomatoes (Solanum lycopersicum L.).

The western part of South America is a centre of diversity for tomatoes, but genetic diversity studies are lacking for parts of that region, including Bolivia. We used 11 simple sequence repeat (SSR) markers (including seven novel markers) to evaluate genetic diversity and population structure of 28 accessions (four modern cultivars, four advanced lines, nine landraces, 11 wild populations), and to compare their genetic variation against phenotypic traits, geographical origin and altitude. In total, 33 alleles were detected across all loci, with 2-5 alleles per locus. The top three informative SSRs were SLM6-11, LE20592 and TomSatX11-1, with polymorphism information content (PIC) of 0.65, 0.55 and 0.49, respectively. The genetic diversity of Bolivian tomatoes was low, as shown by mean expected heterozygosity (He) of 0.07. Analysis of molecular variance (AMOVA) revealed that 77.3% of the total variation was due to variation between accessions. Significant genetic differentiation was found for geographical origin, cultivation status, fruit shape, fruit size and growth type, each explaining 16-23% of the total variation. Unweighted Pair Group Method with Arithmetic Mean (UPGMA) tree and principal coordinate analysis (PCoA) scatter plot both revealed differentiation between accessions with determinate flowers and accessions with indeterminate flowers, regardless of cultivation status. The genetic profiles of the accessions suggest that the Bolivian tomato gene pool comprises both strictly self-pollinating and open-pollinating genotypes.

Comparative study of the morphological characteristics of Phoenix dactylifera L. cultivars in Al-Madinah Al-Munawarah-Saudi Arabia.

BACKGROUND: Phoenix dactylifera L. belongs to the subfamily Coryphoideae. Saudi Arabia is the third producing country of dates in the world with over a million tons of dates every year. P. dactylifera is one of the most important species that grows in Al-Madinah and has cultivars that are distinguished by their appearance and taste. RESULTS: This study aimed to investigate the importance of morphology among P. dactylifera cultivars by using statistical analysis and the ability to identify the cultivars just by looking at them in the obvious characters of palms. Plant specimens were collected from different areas in the Al-Madinah region. All the data obtained from morphology were transferred to numerical characters and used in the multivariate statistical package (MVSP) to study the similarity between the cultivars and give phenetic clusters. One-way ANOVA test and the least significant difference test (LSD) were used to find the significant differences among cultivars in p = 0.05. The numerical data that was recorded indicated significant differences among cultivars. Principal coordinates analysis and cluster analysis (UPGMA) were utilized to study the distance of similarities and differences between cultivars. CONCLUSION: The most distinguishing characteristics were fruit and seed, and the least characteristic was the trunk. However, the features of spine, frond and leaflet were also important in distinguishing between cultivars.

Microbiome profiling of nasal extracellular vesicles in patients with allergic rhinitis.

Background: Nasal microbiota is crucial for the pathogenesis of allergic rhinitis (AR), which has been reported to be different from that of healthy individuals. However, no study has investigated the microbiota in nasal extracellular vesicles (EVs). We aimed to compare the microbiome composition and diversity in EVs between AR patients and healthy controls (HCs) and reveal the potential metabolic mechanisms in AR. Methods: Eosinophil counts and serum immunoglobulin E (IgE) levels were measured in patients with AR (n = 20) and HCs (n = 19). Nasal EVs were identified using transmission electron microscopy and flow cytometry. 16S rRNA sequencing was used to profile the microbial communities. Alpha and beta diversities were analyzed to determine microbial diversity. Taxonomic abundance was analyzed based on the linear discriminant analysis effect size (LEfSe). Microbial metabolic pathways were characterized using Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUst2) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Results: Eosinophils, total serum IgE, and IgE specific to Dermatophagoides were increased in patients with AR. Alpha diversity in nasal EVs from patients with AR was lower than that in HCs. Beta diversity showed microbiome differences between the AR and HCs groups. The microbial abundance was distinct between AR and HCs at different taxonomic levels. Significantly higher levels of the genera Acetobacter, Mycoplasma, Escherichia, and Halomonas were observed in AR patients than in HCs. Conversely, Zoogloea, Streptococcus, Burkholderia, and Pseudomonas were more abundant in the HCs group than in the AR group. Moreover, 35 microbial metabolic pathways recognized in AR patients and HCs, and 25 pathways were more abundant in the AR group. Conclusion: Patients with AR had distinct microbiota characteristics in nasal EVs compared to that in HCs. The metabolic mechanisms of the microbiota that regulate AR development were also different. These findings show that nasal fluid may reflect the specific pattern of microbiome EVs in patients with AR.

Identification of changes in the microflora composition of Japanese horse mackerel (Trachurus japonicus) during storage to identify specific spoilageorganisms.

Japanese horse mackerel (Trachurus japonicus) is an important marine resource, and its loss and waste should be reduced. This study aimed to identify the changes in the microflora composition during storage and specific spoilage organisms (SSOs) in Japanese horse mackerel, for spoilage prevention. They were stored at either 20 °C or 4 °C aerobically, and the bacterial viable counts, concentration of total volatile basic nitrogen (TVB-N), and microflora composition for each group were analyzed. Samples stored at 20 °C for 48 h showed similar viable counts to those stored at 4 °C for 168 h; however, the TVB-N concentrations increased at 20 °C, but not at 4 °C. 16S rRNA metagenome analysis showed that Shewanella became dominant genus in the microflora regardless of the storage temperature. However, dominant amplicon sequence variants (ASVs), which are a more detailed classification level than the genus, differed depending on the storage temperatures; therefore, dominant ASVs at 20 °C were assumed to be potential SSOs. Shewanella sp. Strain NFH-SH190041, which was genetically closely related to the dominant ASVs at 20 °C, was isolated, and its spoilage ability was verified. The strain NFH-SH190041 may be considered a novel SSO of Japanese horse mackerel because its 16S rRNA sequence is clearly different from those of known species.

Nonunique UPGMA clusterings of microsatellite markers.

Agglomerative hierarchical clustering has become a common tool for the analysis and visualization of data, thus being present in a large amount of scientific research and predating all areas of bioinformatics and computational biology. In this work, we focus on a critical problem, the nonuniqueness of the clustering when there are tied distances, for which several solutions exist but are not implemented in most hierarchical clustering packages. We analyze the magnitude of this problem in one particular setting: the clustering of microsatellite markers using the Unweighted Pair-Group Method with Arithmetic Mean. To do so, we have calculated the fraction of publications at the Scopus database in which more than one hierarchical clustering is possible, showing that about 46% of the articles are affected. Additionally, to show the problem from a practical point of view, we selected two opposite examples of articles that have multiple solutions: one with two possible dendrograms, and the other with more than 2.5 million different possible hierarchical clusterings.

SSR-Based Molecular Identification and Population Structure Analysis for Forage Pea (Pisum sativum var. arvense L.) Landraces.

Plant genetic diversity has a significant role in providing traits that can help meet future challenges, such as the need to adapt crops to changing climatic conditions or outbreaks of disease. Our aim in this study was to evaluate the diversity of 61 forage pea specimens (P. sativum ssp. arvense L.) collected from the northeastern Anatolia region of Turkey using 28 simple sequence repeat (SSR) markers. These primers generated a total of 82 polymorphic bands. The number of observed alleles (Na) per primer varied from 2 to 4 with a mean of 2.89 alleles/locus. The mean value of expected heterozygosity (Exp-Het = 0.50) was higher than the mean value of observed heterozygosity (Obs-Het = 0.22). The mean of polymorphic information content (PIC) was 0.41 with a range of 0.03-0.70. The mean number of effective alleles (Ne) was found to be 2.15, Nei's expected heterozygosity (H) 0.49, and Shannon's information index (I) 0.81. Cluster analysis through the unweighted pair-group mean average (UPGMA) method revealed that 61 forage pea landraces were divided into three main clusters. Genetic dissimilarity between the genotypes, calculated with the use of NTSYS-pc software, varied between 0.10 (G30 and G34) and 0.66 (G1 and G32). Principal coordinate analysis (PCoA) revealed that three principal coordinates explained 51.54% of the total variation. Moreover, population structure analysis showed that all genotypes formed three sub-populations. Expected heterozygosity values varied between 0.2669 (the first sub-population) and 0.3223 (third sub-population), with an average value of 0.2924. Average population differentiation measurement (Fst) was identified as 0.2351 for the first sub-population, 0.3838 for the second sub-population, and 0.2506 for the third sub-population. In general, current results suggest that SSR markers could be constantly used to illuminate the genetic diversity of forage pea landraces and can potentially be incorporated into future studies that examine the diversity within a larger collection of forage pea genotypes from diverse regions.

Analysis of genetic diversity among Onobrychis accessions with high agronomic performance by simple sequence repeat (SSR) markers.

BACKGROUND: Onobrychis viciifolia Scop. is a short-lived perennial cool-season legume used for forage production. It is a common native species in Asia Minor, especially in Turkey, the districts of the Caucasus, and the Caspian fringes. It can grow well in a broad range of climatic and soil types found in Asia, Europe, and North America. It is a non-bloating crop, making it suitable for use in both hay and pasture. METHODS AND RESULTS: The aim was to assess the diversity of the 83 sainfoin genotypes selected based on their high agronomic performance from a germplasm collection evaluated in the experimental field of Tekirdag Namik Kemal University, Turkey. Ten nuclear simple sequence repeat (nSSR) primers (OVK036, OVK046, OVK094, OVK101, OVK125, OVK161, OVK174, OVM033, OVM061, and OVM125) were used in the study. All nSSR loci were found to be polymorphic and totally 92 alleles were detected. The mean observed number of alleles per locus was calculated as 9.2. Among the genetic diversity parameters, Shannon Index (I = 0.375), unbiased genetic diversity value (uh = 0.243), and mean polymorphic information content (PIC = 0.240) were calculated. The genetic distance value varied between 0.43 and 0.95. Based on the dendrogram built by the UPGMA clustering method using genetic distance values, it was observed that the studied sainfoin genotypes were divided into two main clusters, whereas the STRUCTURE analysis results had high support for three clusters. CONCLUSIONS: The results obtained from this study provide important information on the genetic structures of the studied sainfoin genotypes and their genetic relationship. Therefore acquired genetic data will be useful in designing more efficient polycross nurseries, allowing open pollination of best performing and genetically diverse genotypes in the isolated conditions, which will increase genetic gain in sainfoin breeding programs.

Early selective strategies for higher yielding bio-economic Indian ginseng based on genotypic study through metabolic and molecular markers.

Applying biotechnological tools to the selection of higher-yielding bioeconomic crops is a promising and remarkable means of reducing the burden on production on a global scale. In the present study, 25 germplasms of Indian ginseng (Withania somnifera (L.) Dunal) were examined for their genetic diversity by using morphological, biochemical, and molecular markers for twenty plant growth traits. The properties of plant growth differed significantly in the maximum genotypes of Indian ginseng, the markers of randomly amplified polymorphic DNA (RAPD), and inter simple sequence repeat (ISSR) showed considerable diversity between the genotypes. The combined unweighted pair group technique with arithmetic mean (UPGMA) dendrogram of morphological, biochemical, and molecular markers grouped all 25 genotypes into two main clusters at 0.61 coefficient value. In addition to this, secondary metabolite profiling by high-performance liquid chromatography (HPLC), there were high variations for withanolide B (WL-B), withanoside-V (WS-V), wedelolactone (WDL), withanoside-IV (WS-IV), and withaferin A (WF-A) content between different genotypes. For the total alkaloid and withanolide concentration in the roots and leaves, high heritability with an increased genetic gain was observed, indicating that selection based on these traits could be an effective method in breeding programs. Furthermore, the path coefficient analysis showed a direct positive impact of the total root fiber, WL-B (leaves), WF-A (leaves), WS-IV (roots), WDL (roots), and the total alkaloid content on the dry root yield. High content of WDL, a high-quality bioactive withanolide, was also described for the first time in the genotype UWS23. These properties can further be exploited to improve the dry root yield in W. somnifera genotypes. The outcomes of the present study also provide an essential foundation for the selection of high-yielding bioeconomic varieties that could be utilized to improve Ashwagandha breeding programs.

Elucidating genetic diversity and population structure of Pyricularia oryzae isolates causing wheat blast in Bangladesh.

Wheat blast, caused by Pyricularia oryzae pathotype Triticum, is one of the most notorious diseases of wheat. In this study, a total of twenty-four monoconidial isolates representing four major wheat blast affected districts, namely Chuadanga, Meherpur, Kustia and Jhenaidah of Bangladesh were analyzed. Eight RAPD and four ISSR primers being used for genetic diversity assay produced a total of 94 bands of which 85% were polymorphic. UPGMA dendrogram based on combined dataset (RAPD and ISSR) separated all the isolates into two main clusters having similarity ranged from 64 to 93%. Principal coordinate analysis showed congruent result with cluster analysis. However, clustering of the isolates according to their origin and plant part sampled was not apparent in the dendrogram. The genetic diversity indices unveiled that genetic diversity in P. oryzae populations is low. Average Nei's gene diversity (h) and Shannon's Information Index (I) calculated for isolates from each district were found 0.16 and 0.24, respectively. The population structure analysis of the isolates revealed the presence of two sub-populations with admixture of alleles. Analysis of molecular variance indicated that significantly higher level of variation (96%) in the population was present within districts while a relatively low proportion (4%) of the variation was detected among districts. Knowledge generated in this study will give a pace in the development of appropriate wheat blast management strategies to control this disease in Bangladesh.

Assessment of population structure, genetic diversity and relationship of Mediterranean olive accessions using SSR markers and computational tools.

Olive tree is an emblematic crop of the Mediterranean region, mainly renowned for its fruit oil, although the species provides several industrial purposes. The Mediterranean basin constitutes the origin of olive species diversification and represents a valuable source of genetic variability of olive germplasm. Therefore, the evaluation of the diversity and the population structure of this Mediterranean germplasm is a challenge for olive species preservation, crop breeding and genetic improvement. In this context, our study aims to analyze the genetic diversity and the population structure of 79 Mediterranean olive accessions using 15 genomic SSRs and by applying computational model-based approaches. The used SSRs revealed a total number of 225 alleles with a mean of 15 alleles per locus. Observed and expected heterozygosity (Ho = 0.79, He = 0.805) with a Polymorphism Information Content value of 0.775 indicate high level of genetic diversity. All results of the Unweighted Pair Group Method with Arithmetic (UPGMA), Jaccard similarity index, Principal Coordinate Analysis (PCoA) and the Bayesian analyses supported the separation of the Mediterranean varieties in two sub-populations, one of which mainly composed by Spanish accessions.

Genetic Similarity of Avena sativa L. Varieties as an Example of a Narrow Genetic Pool of Contemporary Cereal Species.

The assessment of the genetic diversity of cultivated varieties is a very important element of breeding programs. This allows the determination of the level of genetic differentiation of cultivated varieties, their genetic distinctiveness, and is also of great importance in the selection of parental components for crossbreeding. The aim of the present study was to determine the level of genetic diversity of oat varieties currently grown in Central Europe based on two marker systems: ISSR and SCoT. The research conducted showed that both these types of markers were suitable for conducting analyses relating to the assessment of genetic diversity. The calculated coefficients showed that the analyzed cultivars were characterized by a high genetic similarity. However, the UPGMA and PCoA analyses clearly indicated the distinctiveness of the breeding programs conducted in Central European countries. The high genetic similarity of the analyzed forms allow us to conclude that it is necessary to expand the genetic pool of oat varieties. Numerous studies show that landraces may be the donor of genetic variation.