Morphological and genetic diversity assessment of sesame (Sesamum indicum L.) accessions differing in origin

Transcriptome-derived SSR markers for DNA fingerprinting and inter-populations genetic diversity assessment of Atractylodes chinensis

Atractylodes chinensis (fam. Asteraceae) is an important medicinal plant due to its unique pharmacological activity. The species is widely distributed in most areas of northern China. It is difficult to identify different populations of A. chinensis due to their similarity in characteristics. This study was the first investigation to date that assessed the genetic diversity of A. chinensis from different geographical counties of northern China using simple sequence repeat (SSR) markers. Of the 106 SSR primers in the clusters classified in the sesquiterpenoid biosynthesis pathway in the transcriptomic database of A. chinensis, ten with high polymorphism were used to analyze the inter-populations genetic diversity and construct DNA fingerprinting of 19 A. chinensis populations. A total of 78 alleles were detected, with an average number of 6.5 alleles per primer. The PIC value ranged from 0.4748 to 0.8918 with a mean of 0.6265. The neighbor-joining tree was used to classify 19 populations of A. chinensis into three clusters. DNA fingerprinting was performed according to these ten SSR markers. The results revealed that geographic origin is not exactly related to genetic diversity, as populations belonging to different provinces are grouped in the same cluster. The results of this study confirm that SSR markers are effective for genetic diversity analysis. The inter-populations genetic diversity and fingerprinting of A. chinensis in this study could provide a scientific basis for species identification and selective breeding.

Current Research Trends and Prospects for Yield and Quality Improvement in Sesame, an Important Oilseed Crop

Climate change is shifting agricultural production, which could impact the economic and cultural contexts of the oilseed industry, including sesame. Environmental threats (biotic and abiotic stresses) affect sesame production and thus yield (especially oil content). However, few studies have investigated the genetic enhancement, quality improvement, or the underlying mechanisms of stress tolerance in sesame. This study reveals the challenges faced by farmers/researchers growing sesame crops and the potential genetic and genomic resources for addressing the threats, including: (1) developing sesame varieties that tolerate phyllody, root rot disease, and waterlogging; (2) investigating beneficial agro-morphological traits, such as determinate growth, prostrate habit, and delayed response to seed shattering; (3) using wild relatives of sesame for wide hybridization; and (4) advancing existing strategies to maintain sesame production under changing climatic conditions. Future research programs need to add technologies and develop the best research strategies for economic and sustainable development.

DIVIS: a semantic DIstance to improve the VISualisation of heterogeneous phenotypic datasets

Background

Thanks to the wider spread of high-throughput experimental techniques, biologists are accumulating large amounts of datasets which often mix quantitative and qualitative variables and are not always complete, in particular when they regard phenotypic traits. In order to get a first insight into these datasets and reduce the data matrices size scientists often rely on multivariate analysis techniques. However such approaches are not always easily practicable in particular when faced with mixed datasets. Moreover displaying large numbers of individuals leads to cluttered visualisations which are difficult to interpret.

Results

We introduced a new methodology to overcome these limits. Its main feature is a new semantic distance tailored for both quantitative and qualitative variables which allows for a realistic representation of the relationships between individuals (phenotypic descriptions in our case). This semantic distance is based on ontologies which are engineered to represent real-life knowledge regarding the underlying variables. For easier handling by biologists, we incorporated its use into a complete tool, from raw data file to visualisation. Following the distance calculation, the next steps performed by the tool consist in (i) grouping similar individuals, (ii) representing each group by emblematic individuals we call archetypes and (iii) building sparse visualisations based on these archetypes. Our approach was implemented as a Python pipeline and applied to a rosebush dataset including passport and phenotypic data.

Conclusions

The introduction of our new semantic distance and of the archetype concept allowed us to build a comprehensive representation of an incomplete dataset characterised by a large proportion of qualitative data. The methodology described here could have wider use beyond information characterizing organisms or species and beyond plant science. Indeed we could apply the same approach to any mixed dataset.

Supplementary Information

The online version contains supplementary material available at (10.1186/s13040-022-00293-y).

Identifying Traits Associated With Terminal Drought Tolerance in Sesame (Sesamum indicum L.) Genotypes

Sesame is predominantly cultivated in rainfed and low fertile lands and is frequently exposed to terminal drought. Sesamum species inhabiting dryland ecosystems adaptively diverge from those inhabiting rainfed habitats, and drought-specific traits have a genetic basis. In sesame, traits associated with drought conditions have not been explored to date, yet studies of these traits are needed given that drought is predicted to become more frequent and severe in many parts of the world because of climate change. Here, 76 accessions from the available Indian core set were used to quantify variation in several traits under irrigated (WW) and terminal drought stress (WS) conditions as well as their association with seed yield over two consecutive years. The range of trait variation among the studied genotypes under WW and WS was significant. Furthermore, the traits associated with seed yield under WW and WS differed. The per se performance of the accessions indicated that the expression of most traits was reduced under WS. The correlation analysis revealed that the number of branches, leaf area (LA), leaves dry weight (LDW), number of capsules plant^-1, and harvest index (HI) were positively correlated with seed yield under WW and WS, and total dry matter (TDM), plant stem weight, and canopy temperature (CT) were negatively correlated with seed yield under WW and WS, indicating that smaller and cooler canopy genotypes had higher yields. The genotypes IC-131936, IC-204045, IC-204861, IC-205363, IC-205311, and IC-73576 with the highest seed yields were characterized by low canopy temperature, high relative water content, and high harvest index under WS. Phenotypic and molecular diversity analysis was conducted on genotypes along with checks. Phenotypic diversity was assessed using multivariate analysis, whereas molecular diversity was estimated using simple sequence repeat (SSR) loci to facilitate the use of sesame in breeding and genetic mapping. SSRs showed low allelic variation, as indicated by a low average number of alleles (2.31) per locus, gene diversity (0.25), and polymorphism information content (0.22). Cluster analysis (CA) [neighbor-joining (NJ) tree] revealed three major genotypic groups and structure analysis showed 4 populations. The diverse genotypes identified with promising morpho-physiological traits can be used in breeding programs to develop new varieties.

Comparative metabolomics analysis of different sesame (Sesamum indicum L.) tissues reveals a tissue-specific accumulation of metabolites

BACKGROUND

Sesame (Sesamum indicum L.) leaves, flowers, especially seeds are used in traditional medicine to prevent or cure various diseases. Its seed's market is expanding. However, the other tissues are still underexploited due to the lack of information related to metabolites distribution and variability in the plant. Herein, the metabolite profiles of five sesame tissues (leaves, fresh seeds, white and purple flowers, and fresh carpels) have been investigated using ultra-high-performance liquid chromatography-mass spectrometry (UPLC-MS/MS)-based widely targeted metabolomics analysis platform.

RESULTS

In total, 776 metabolites belonging to diverse classes were qualitatively and quantitatively identified. The different tissues exhibited obvious differences in metabolites composition. The majority of flavonoids predominantly accumulated in flowers. Amino acids and derivatives, and lipids were identified predominantly in fresh seeds followed by flowers. Many metabolites, including quinones, coumarins, tannins, vitamins, terpenoids and some bioactive phenolic acids (acteoside, isoacteoside, verbascoside, plantamajoside, etc.) accumulated mostly in leaves. Lignans were principally detected in seeds. 238 key significantly differential metabolites were filtered out. KEGG annotation and enrichment analyses of the differential metabolites revealed that flavonoid biosynthesis, amino acids biosynthesis, and phenylpropanoid biosynthesis were the main differently regulated pathways. In addition to the tissue-specific accumulation of metabolites, we noticed a cooperative relationship between leaves, fresh carpels, and developing seeds in terms of metabolites transfer. Delphinidin-3-O-(6"-O-p-coumaroyl)glucoside and most of the flavonols were up-regulated in the purple flowers indicating they might be responsible for the purple coloration.

CONCLUSION

This study revealed that the metabolic processes in the sesame tissues are differently regulated. It offers valuable resources for investigating gene-metabolites interactions in sesame tissues and examining metabolic transports during seed development in sesame. Furthermore, our findings provide crucial knowledge that will facilitate sesame biomass valorization.

Genome-wide association study and its applications in the non-model crop Sesamum indicum

BACKGROUND

Sesame is a rare example of non-model and minor crop for which numerous genetic loci and candidate genes underlying features of interest have been disclosed at relatively high resolution. These progresses have been achieved thanks to the applications of the genome-wide association study (GWAS) approach. GWAS has benefited from the availability of high-quality genomes, re-sequencing data from thousands of genotypes, extensive transcriptome sequencing, development of haplotype map and web-based functional databases in sesame.

RESULTS

In this paper, we reviewed the GWAS methods, the underlying statistical models and the applications for genetic discovery of important traits in sesame. A novel online database SiGeDiD ( http://sigedid.ucad.sn/ ) has been developed to provide access to all genetic and genomic discoveries through GWAS in sesame. We also tested for the first time, applications of various new GWAS multi-locus models in sesame.

CONCLUSIONS

Collectively, this work portrays steps and provides guidelines for efficient GWAS implementation in sesame, a non-model crop.

Characterization of the Genetic Diversity Present in a Diverse Sesame Landrace Collection Based on Phenotypic Traits and EST-SSR Markers Coupled With an HRM Analysis

A selection of sesame (Sesamum indicum L.) landraces of different eco-geographical origin and breeding history have been characterized using 28 qualitative morpho-physiological descriptors and seven expressed sequence tag-simple sequence repeat (EST-SSR) markers coupled with a high-resolution melting (HRM) analysis. The most variable qualitative traits that could efficiently discriminate landraces, as revealed by the correlation analyses, were the plant growth type and position of the branches, leaf blade width, stem pubescence, flowering initiation, capsule traits and seed coat texture. The agglomerative hierarchical clustering analysis based on a dissimilarity matrix highlighted three main groups among the sesame landraces. An EST-SSR marker analysis revealed an average polymorphism information content (PIC) value of 0.82, which indicated that the selected markers were highly polymorphic. A principal coordinate analysis and dendrogram reconstruction based on the molecular data classified the sesame genotypes into four major clades. Both the morpho-physiological and molecular analyses showed that landraces from the same geographical origin were not always grouped in the same cluster, forming heterotic groups; however, clustering patterns were observed for the Greek landraces. The selective breeding of such traits could be employed to unlock the bottleneck of local phenotypic diversity and create new cultivars with desirable traits.

Transcriptome Dynamics during Black and White Sesame (Sesamum indicum L.) Seed Development and Identification of Candidate Genes Associated with Black Pigmentation

Seed coat color is a crucial agronomic trait in sesame (Sesamum indicum L.) since it is strongly linked to seed oil, proteins, and lignans contents, and also influences consumer preferences. In East Asia, black sesame seed is used in the treatment and the prevention of various diseases. However, in sesame, little is known about the establishment of the seed coat color, and only one gene has been reported to control black pigmentation. This study provides an overview of developing seeds transcriptome of two varieties of sesame "Zhongfengzhi No.1" (white seed) and "Zhongzhi No.33" (black seed) and shed light on genes involving in black seed formation. Until eight days post-anthesis (DPA), both the seeds of the two varieties were white. The black sesame seed turned to yellow between 9 and 11 DPA and then black between 12 and 14 DPA. The black and white sesame showed similar trend-expressed genes with the numbers increased at the early stages of seed development. The differentially expressed genes (DEGs) number increased with seed development in the two sesame varieties. We examined the DEGs and uncovered that more were up-regulated at the early stages. The DEGs between the black and white sesame were mainly enriched in 37 metabolic pathways, among which the flavonoid biosynthesis and biosynthesis of secondary metabolites were dominants. Furthermore, we identified 20 candidate genes associated with pigment biosynthesis in black sesame seed, among which 10 were flavonoid biosynthesis and regulatory genes. These genes also include isochorismate and polyphenol oxidase genes. By comparing the phenotypes and genes expressions of the black and white sesame seed at different development stages, this work revealed the important role of 8-14 DPA in black pigment biosynthesis and accumulation. Moreover, it unfolded candidate genes associated with black pigmentation in sesame. These findings provide a vast transcriptome dataset and list of genes that will be targeted for functional studies related to the molecular mechanism involved in biosynthesis and regulation of seed coat color in sesame.

Genetic Architecture Underpinning Yield Components and Seed Mineral-Nutrients in Sesame

Genetic dissection of yield components and seed mineral-nutrient is crucial for understanding plant physiological and biochemical processes and alleviate nutrient malnutrition. Sesame (Sesamum indicum L.) is an orphan crop that harbors rich allelic repertoire for seed mineral-nutrients. Here, we harness this wide diversity to study the genetic architecture of yield components and seed mineral-nutrients using a core-collection of worldwide genotypes and segregating mapping population. We also tested the association between these traits and the effect of seed nutrients concentration on their bio-accessibility. Wide genetic diversity for yield components and seed mineral-nutrients was found among the core-collection. A high-density linkage map consisting of 19,309 markers was constructed and used for genetic mapping of 84 QTL associated with yield components and 50 QTL for seed minerals. To the best of our knowledge, this is the first report on mineral-nutrients QTL in sesame. Genomic regions with a cluster of overlapping QTL for several morphological and nutritional traits were identified and considered as genomic hotspots. Candidate gene analysis revealed potential functional associations between QTL and corresponding genes, which offers unique opportunities for synchronous improvement of mineral-nutrients. Our findings shed-light on the genetic architecture of yield components, seed mineral-nutrients and their inter- and intra- relationships, which may facilitate future breeding efforts to develop bio-fortified sesame cultivars.

Genetic variation among Saudi tomato (Solanum lycopersicum L.) landraces studied using SDS-PAGE and SRAP markers

Genetic diversity among seven Saudi tomato landraces collected from different regions of the country was assessed using SDS-PAGE and molecular (sequence-related amplified polymorphism- SRAP) markers. A total of 19 alternative protein bands with different mobility rates were identified within a molecular weight range of 9.584–225 KDa, with 53% polymorphism. Specific protein bands were observed in the “Hail 548” and “Qatif 565” landraces. Genetic similarity based on Jaccard’s coefficient ranged from 0.53 to 1.00, with an average of 0.72. For molecular evaluation, 143 amplicons (fragments) were generated using 27 SRAP primer pair combinations, of which 88 were polymorphic across all the landraces. The PIC values ranged from 0.46 to 0.90, with an average of 0.76. All landraces showed an average of 0.66 similarity coefficient value. The UPGMA dendrogram supported by principal coordinate analysis (PCoA) revealed clusters of the landraces that almost corresponded to their geographical origin. Thus, seed storage protein profiling based on SDS-PAGE and SRAP markers can efficiently be used to assess genetic variability among tomato germplasms. The information obtained in the analysis will be of great interest in the management of ex situ collections for utilization in breeding programs or for direct use in quality markets.

Relationship of Parental Genetic Distance with Heterosis and Specific Combining Ability in Sesame (Sesamum indicum L.) Based on Phenotypic and Molecular Marker Analysis

The genetic distance analysis for selection of suitable parents has been established and effectively used in many crops; however, there is dearth of conclusive report of relationship of genetic distance analysis with heterosis in sesame. In the present study, an attempt was made to estimate the associations of genetic distances using SSR (GDSSR), seed-storage protein profiling (GDSDS) and agro-morphological traits (GDMOR) with hybrid performance. Seven parents were selected from 60 exotic and Indian genotypes based on genetic distance from clustering pattern based on SSR, seed-storage protein, morphological traits and per se performance. For combining ability analysis, 7 parents and 21 crosses generated from 7 × 7 half diallel evaluated at two environments in a replicated field trial during pre-kharif season of 2013. Compared with the average parents yield (12.57 g plant^-1), eight hybrids had a significant (P < 0.01) yield advantage across environments, with averages of 26.94 and 29.99% for better-parent heterosis (BPH) and mid-parent heterosis (MPH), respectively, across environments. Highly significant positive correlation was observed between specific combining ability (SCA) and per se performance (0.97), while positive non-significant correlation of BPH with GDSSR (0.048), and non-significant negative correlations with GDMOR (- 0.01) and GDSDS (- 0.256) were observed. The linear regressions of SCA on MPH, BPH and per se performance of F₁s were significant with R² value of 0.88, 0.84 and 0.95 respectively. The present findings revealed a weak association of GDSSR with F₁'s performance; however, SCA has appeared as an important factor in the determination of heterosis and per se performance of the hybrids. The present findings also indicated that parental divergence in the intermediate group would likely produce high heterotic crosses in sesame.

The Emerging Oilseed Crop Sesamum indicum Enters the "Omics" Era

Sesame (Sesamum indicum L.) is one of the oldest oilseed crops widely grown in Africa and Asia for its high-quality nutritional seeds. It is well adapted to harsh environments and constitutes an alternative cash crop for smallholders in developing countries. Despite its economic and nutritional importance, sesame is considered as an orphan crop because it has received very little attention from science. As a consequence, it lags behind the other major oil crops as far as genetic improvement is concerned. In recent years, the scenario has considerably changed with the decoding of the sesame nuclear genome leading to the development of various genomic resources including molecular markers, comprehensive genetic maps, high-quality transcriptome assemblies, web-based functional databases and diverse daft genome sequences. The availability of these tools in association with the discovery of candidate genes and quantitative trait locis for key agronomic traits including high oil content and quality, waterlogging and drought tolerance, disease resistance, cytoplasmic male sterility, high yield, pave the way to the development of some new strategies for sesame genetic improvement. As a result, sesame has graduated from an "orphan crop" to a "genomic resource-rich crop." With the limited research teams working on sesame worldwide, more synergic efforts are needed to integrate these resources in sesame breeding for productivity upsurge, ensuring food security and improved livelihood in developing countries. This review retraces the evolution of sesame research by highlighting the recent advances in the "Omics" area and also critically discusses the future prospects for a further genetic improvement and a better expansion of this crop.

Assessment of genetic diversity of sesame accessions collected from different ecological regions using sequence-related amplified polymorphism markers

Sequence-related amplified polymorphism (SRAP) markers were used to assess the genetic diversity among a collection of 52 sesame accessions representing different geographical environments, including eight Saudi landraces. A combination of seventeen primers generated a high number of alleles (365) with 100% polymorphism. The polymorphic information content (PIC) and primer discrimination power (DP) recorded overall means of 0.88 and 5.88, respectively. Genetic similarity values based on Jaccard coefficients ranged from 0.12 to 0.49, with an average similarity value of 0.30, indicating both high genetic distance and a wide genetic basis of the investigated accessions. The unweighted pair group method with arithmetic mean (UPGMA) dendrogram grouped 48 of 52 accessions into seven main clusters, and five accessions failed to form clusters and were separated individually. However, subclusters separated the accessions and, considering the relatedness of accessions and their geographical origin, formed distinct diversity among groups. Saudi landraces showed the widest genetic basis compared with other introduced accessions that were distributed throughout the dendrogram, indicating that agro-ecological zones were indistinguishable by cluster analysis. SRAP analysis revealed a high degree of genetic polymorphism in sesame accessions investigated and showed weak association between geographical origin and SRAP patterns. This wide genetic variability should be considered for sesame breeding programs.