A High-Density SNP Genetic Map Construction Using ddRAD-Seq and Mapping of Capsule Shattering Trait in Sesame

High-density genetic map construction and QTL mapping to identify genes for blight defense- and yield-related traits in sesame (Sesamum indicum L.)

Sesame (Sesamum indicum L.) is an important oilseed crop widely cultivated in subtropical and tropical areas. Low genetic yield potential and susceptibility to disease contribute to low productivity in sesame. However, the genetic basis of sesame yield- and disease-related traits remains unclear. Here, we represent the construction of a high-density bin map of sesame using whole genome sequencing of an F2 population derived from 'Yizhi' and 'Mingdeng Zhima'. A total of 2766 Bins were categorized into 13 linkage groups. Thirteen significant QTLs were identified, including ten QTLs related to yield, two QTLs related to Sesame Fusarium wilt (SFW) disease, and one QTL related to seed color. Among these QTLs, we found that SFW-QTL1.1 and SFW-QTL1.2 were major QTLs related to Fusarium wilt disease, explaining more than 20% of the phenotypic variation with LOD > 6. SCC-QTL1.1 was related to seed coat color, explaining 52% of the phenotypic variation with LOD equal to 25.3. This suggests that seed color traits were controlled by a major QTL. Candidate genes related to Fusarium wilt disease and seed color in the QTLs were annotated. We discovered a significant enrichment of genes associated with resistance to late blight. These genes could be spectral disease resistance genes and may have a role in the regulation of Fusarium wilt disease resistance. Our study will benefit the implementation of marker-assisted selection (MAS) for the genetic improvement of disease resistance and yield-related traits in sesame.

Sesame, an Underutilized Oil Seed Crop: Breeding Achievements and Future Challenges

Sesame seeds and their edible oil are highly nutritious and rich in mono- and polyunsaturated fatty acids. Bioactive compounds such as sterols, tocopherols, and sesamol provide significant medicinal benefits. The high oil content (50%) and favorable mono- and polyunsaturated fatty acid balance, as well as resilience to water stress, make sesame a promising candidate crop for global agricultural expansion. However, sesame production faces challenges such as low yields, poor response to agricultural inputs, and losses due to capsule dehiscence. To enhance yield, traits like determinate growth, dwarfism, a high harvest index, non-shattering capsules, disease resistance, and photoperiod sensitivity are needed. These traits can be achieved through variation or induced mutation breeding. Crossbreeding methods often result in unwanted genetic changes. The gene editing CRISPR/Cas9 technology has the potential to suppress detrimental alleles and improve the fatty acid profile by inhibiting polyunsaturated fatty acid biosynthesis. Even though sesame is an orphan crop, it has entered the genomic era, with available sequences assisting molecular breeding efforts. This progress aids in associating single-nucleotide polymorphisms (SNPs) and simple sequence repeats (SSR) with key economic traits, as well as identifying genes related to adaptability, oil production, fatty acid synthesis, and photosynthesis. Additionally, transcriptomic research can reveal genes involved in abiotic stress responses and adaptation to diverse climates. The mapping of quantitative trait loci (QTL) can identify loci linked to key traits such as capsule size, seed count per capsule, and capsule number per plant. This article reviews recent advances in sesame breeding, discusses ongoing challenges, and explores potential strategies for future improvement. Hence, integrating advanced genomic tools and breeding strategies provides promising ways to enhance sesame production to meet global demands.

QTL analysis of traits related to seed size and shape in sesame (Sesamum indicum L.)

Seed size and shape are important traits that determine seed yield in sesame. Understanding the genetic basis of seed size and shape is essential for improving the yield of sesame. In this study, F2 and BC1 populations were developed by crossing the Yuzhi 4 and Bengal small-seed (BS) lines for detecting the quantitative trait loci (QTLs) of traits related to seed size and shape. A total of 52 QTLs, including 13 in F2 and 39 in BC1 populations, for seed length (SL), seed width (SW), and length to width ratio (L/W) were identified, explaining phenotypic variations from 3.68 to 21.64%. Of these QTLs, nine stable major QTLs were identified in the two populations. Notably, three major QTLs qSL-LG3-2, qSW-LG3-2, and qSW-LG3-F2 that accounted for 4.94-16.34% of the phenotypic variations were co-localized in a 2.08 Mb interval on chromosome 1 (chr1) with 279 candidate genes. Three stable major QTLs qSL-LG6-2, qLW-LG6, and qLW-LG6-F2 that explained 8.14-33.74% of the phenotypic variations were co-localized in a 3.27 Mb region on chr9 with 398 candidate genes. In addition, the stable major QTL qSL-LG5 was co-localized with minor QTLs qLW-LG5-3 and qSW-LG5 to a 1.82 Mb region on chr3 with 195 candidate genes. Gene annotation, orthologous gene analysis, and sequence analysis indicated that three genes are likely involved in sesame seed development. These results obtained herein provide valuable in-formation for functional gene cloning and improving the seed yield of sesame.

Omics technologies towards sesame improvement: a review

Genetic improvement of sesame (Sesamum indicum L.), one of the most important oilseed crops providing edible oil, proteins, minerals, and vitamins, is important to ensure a balanced diet for the growing world population. Increasing yield, seed protein, oil, minerals, and vitamins is urgently needed to meet the global demand. The production and productivity of sesame is very low due to various biotic and abiotic stresses. Therefore, various efforts have been made to combat these constraints and increase the production and productivity of sesame through conventional breeding. However, less attention has been paid to the genetic improvement of the crop through modern biotechnological methods, leaving it lagging behind other oilseed crops. Recently, however, the scenario has changed as sesame research has entered the era of "omics" and has made significant progress. Therefore, the purpose of this paper is to provide an overview of the progress made by omics research in improving sesame. This review presents a number of efforts that have been made over past decade using omics technologies to improve various traits of sesame, including seed composition, yield, and biotic and abiotic resistant varieties. It summarizes the advances in genetic improvement of sesame using omics technologies, such as germplasm development (web-based functional databases and germplasm resources), gene discovery (molecular markers and genetic linkage map construction), proteomics, transcriptomics, and metabolomics that have been carried out in the last decade. In conclusion, this review highlights future directions that may be important for omics-assisted breeding in sesame genetic improvement.

Construction of a high-density genetic linkage map and QTL mapping for bioenergy-related traits in sweet sorghum [Sorghum bicolor (L.) Moench]

Sorghum is an important but arguably undervalued cereal crop, grown in large areas in Asia and Africa due to its natural resilience to drought and heat. There is growing demand for sweet sorghum as a source of bioethanol as well as food and feed. The improvement of bioenergy-related traits directly affects bioethanol production from sweet sorghum; therefore, understanding the genetic basis of these traits would enable new cultivars to be developed for bioenergy production. In order to reveal the genetic architecture behind bioenergy-related traits, we generated an F₂ population from a cross between sweet sorghum cv. 'Erdurmus' and grain sorghum cv. 'Ogretmenoglu'. This was used to construct a genetic map from SNPs discovered by double-digest restriction-site associated DNA sequencing (ddRAD-seq). F₃ lines derived from each F₂ individual were phenotyped for bioenergy-related traits in two different locations and their genotypes were analyzed with the SNPs to identify QTL regions. On chromosomes 1, 7, and 9, three major plant height (PH) QTLs (qPH1.1, qPH7.1, and qPH9.1) were identified, with phenotypic variation explained (PVE) ranging from 10.8 to 34.8%. One major QTL (qPJ6.1) on chromosome 6 was associated with the plant juice trait (PJ) and explained 35.2% of its phenotypic variation. For fresh biomass weight (FBW), four major QTLs (qFBW1.1, qFBW6.1, qFBW7.1, and qFBW9.1) were determined on chromosomes 1, 6, 7, and 9, which explained 12.3, 14.5, 10.6, and 11.9% of the phenotypic variation, respectively. Moreover, two minor QTLs (qBX3.1 and qBX7.1) of Brix (BX) were mapped on chromosomes 3 and 7, explaining 8.6 and 9.7% of the phenotypic variation, respectively. The QTLs in two clusters (qPH7.1/qBX7.1 and qPH7.1/qFBW7.1) overlapped for PH, FBW and BX. The QTL, qFBW6.1, has not been previously reported. In addition, eight SNPs were converted into cleaved amplified polymorphic sequences (CAPS) markers, which can be easily detected by agarose gel electrophoresis. These QTLs and molecular markers can be used for pyramiding and marker-assisted selection studies in sorghum, to develop advanced lines that include desirable bioenergy-related traits.

Current Progress, Applications and Challenges of Multi-Omics Approaches in Sesame Genetic Improvement

Sesame is one of the important traditional oil crops in the world, and has high economic and nutritional value. Recently, due to the novel high throughput sequencing techniques and bioinformatical methods, the study of the genomics, methylomics, transcriptomics, proteomics and metabonomics of sesame has developed rapidly. Thus far, the genomes of five sesame accessions have been released, including white and black seed sesame. The genome studies reveal the function and structure of the sesame genome, and facilitate the exploitation of molecular markers, the construction of genetic maps and the study of pan-genomes. Methylomics focus on the study of the molecular level changes under different environmental conditions. Transcriptomics provide a powerful tool to study abiotic/biotic stress, organ development, and noncoding RNAs, and proteomics and metabonomics also provide some support in studying abiotic stress and important traits. In addition, the opportunities and challenges of multi-omics in sesame genetics breeding were also described. This review summarizes the current research status of sesame from the perspectives of multi-omics and hopes to provide help for further in-depth research on sesame.

Discovering favorable genes, QTLs, and genotypes as a genetic resource for sesame (Sesamum indicum L.) improvement

Sesame (Sesamum indicum L.) is an ancient diploid oilseed crop with high oil content, quality protein, and antioxidant characteristics that is produced in many countries worldwide. The genes, QTLs, and genetic resources of sesame are utilized by sesame researchers and growers. Researchers have identified the many useful traits of this crop, which are available on different platforms. The genes, genotypes, QTLs, and other genetic diversity data of sesame have been collected and stored in more than nine genomic resources, and five sesame crop marker databases are available online. However, data on phenotypic and genotypic variability, which would contribute to sesame improvements, are limited and not yet accessible. The present study comprehensively reviewed more than 110 original published research papers and scientifically incorporated the results. The candidate genes, genotypes, and QTLs of significantly important traits of sesame were identified. Genetic resources related to grain yield and yield component traits, oil content and quality, drought tolerance, salt tolerance, waterlogging resistance, disease resistance, mineral nutrient, capsule shattering resistance, and other agronomic important traits of sesame were studied. Numerous candidate genotypes, genes, QTLs, and alleles associated with those traits were summarized and discovered. The chromosome regions and linkage groups, maps associated with the best traits, and candidate genes were also included. The variability presented in this paper combined with sesame genetic information will help inform further sesame improvement.

The wild allotetraploid sesame genome provides novel insights into evolution and lignan biosynthesis

INTRODUCTION

The wild tetraploid sesame (Sesamum schinzianum), an ancestral relative of diploid cultivated sesame, grows in the tropical desert of the African Plateau. As a valuable seed resource, wild sesame has several advantageous traits, such as strong environmental adaptability and an extremely high content of sesamolin in its seeds. High-quality genome assembly is essential for a detailed understanding of genome structure, genome evolution and crop improvement.

OBJECTIVES

Here, we generated two high-quality chromosome-scale genomes from S. schinzianum and a cultivated diploid elite sesame (Sesamum indicum L.) to investigate the potential genetic basis underlying these traits of wild sesame.

METHODS

The long-read data from PacBio Sequel II platform and high-throughput chromosome conformation capture (Hi-C) data were used to construct high-quality sesame genome. Then dissecting the molecular mechanisms of sesame evolution and lignan biosynthesis through comparative genomics and transcriptomics.

RESULTS

We found evidence of divergent evolution that involved differences in the number, sequence and expression level of homologous genes between the two sets of subgenomes from allotetraploids in S. schinzianum, all of which might be driven by subfunctionalization after polyploidization. Furthermore, it was found that a great number of genes involved in the stress response have undergone positive selection and resulted from gene family expansion in the wild sesame genome compared with the cultivated sesame genome, which, overall, is associated with adaptative evolution to the environment. We hypothesized that the sole functional member CYP92B14 (SscC22g35272) could be associated with high content of sesamolin in wild sesame seeds.

CONCLUSION

This study provides high-quality wild allotetraploid sesame and cultivated sesame genomes, reveals evolutionary features of the allotetraploid genome and provides novel insights into lignan synthesis pathways. Meanwhile, the wild sesame genome will be an important resource to conduct comparative genomic and evolutionary studies and plant improvement programmes.

Breeding history for shattering trait in sesame: classic to genomic approach

Sesame is an important oilseed crop that has high oil and protein content and unique antioxidant lignans. Capsule shattering at harvest is one of the most important problems affecting sesame production, with seed losses of up to 50%, making the crop unsuitable for mechanized harvesting. This paper provides an overview of breeding approaches addressing the capsule shattering trait in sesame and gives an outlook about the future perspectives of improvement for this trait. Sesame research has proceeded along the following parallel tracks: breeding for additional shatter resistance for manual harvest, breeding for mechanized harvest, and using molecular biology to improve the shatter resistance trait. In the future, genes controlling the shattering trait should be studied with techniques like RNA interference (RNAi), site-oriented mutagenesis, and gene editing with zinc finger nucleases (ZFNs) or CRISPR/Cas9, to develop new sesame varieties with capsules suitable for fully mechanized harvest.

High-Density Linkage Mapping and Identification of Quantitative Trait Loci Associated with Powdery Mildew Resistance in Flowering Dogwood (Cornus florida)

Flowering dogwood (Cornus florida L.) is a popular, spring-blooming ornamental tree native to the eastern United States. The species is in general very susceptible to powdery mildew caused by Erysiphe pulchra, which disfigures leaves, decreases growth, and negatively affects flowering. Breeding for resistance has been recognized as an ideal strategy for controlling the disease in C. florida, but efforts have been hindered by the rarity of PM resistance in available germplasm and knowledge of its genetic control. In this study, we mapped quantitative trait loci (QTL) associated with PM resistance/tolerance in two full sibling populations segregating for PM response: Rutgers H4AR15P25 (P25) × Rutgers H4AR15R28 (P28) (n = 195) and Rutgers H4AR15R25 × Rutgers H4AR15P35 (P35) (n = 83). High-density genetic linkage maps were constructed for the mapping populations using double digest restriction-site associated DNA sequencing-derived single nucleotide polymorphisms (SNPs) and simple sequence repeats (SSRs). The P25 × P28 map consisted of 2265 markers, spanning 1520 cM and 11 linkage groups (LGs) with an average marker spacing of 0.69 cM. The P25 × P35 map was constructed with 1788 markers, spanning 1256 cM and 11 LGs, with an average marker spacing of 0.72 cM. The maps had 604 markers in common and exhibited excellent collinearity. Through multiple QTL model mapping, one major QTL (LOD = 11.36 and R2 = 58.9%) was identified in P25 × P35. Furthermore, a minor QTL (LOD = 3.30 and R2 = 7.8%) was detected in P25 × P28. Due to their proximity onLG3, these QTL may be designating the same locus or tightly linked loci. The negative additive effects of both QTL signify that the PM susceptible male parents were contributing susceptibility alleles to the progeny. This is the first report of QTL associated with PM response on LG3 in C. florida and lays the groundwork for the development of marker-assisted selection for PM resistance in C. florida breeding programs.