QTL-Seq and Transcriptome Analysis Disclose Major QTL and Candidate Genes Controlling Leaf Size in Sesame (Sesamum indicum L.)

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.

Refining flowering date enhances sesame yield independently of day-length

BACKGROUND

The transition from vegetative to reproductive growth is a key factor in yield maximization. Sesame (Sesamum indicum), an indeterminate short-day oilseed crop, is rapidly being introduced into new cultivation areas. Thus, decoding its flowering mechanism is necessary to facilitate adaptation to environmental conditions. In the current study, we uncover the effect of day-length on flowering and yield components using F2 populations segregating for previously identified quantitative trait loci (Si_DTF QTL) confirming these traits.

RESULTS

Generally, day-length affected all phenotypic traits, with short-day preceding days to flowering and reducing yield components. Interestingly, the average days to flowering required for yield maximization was 50 to 55 days, regardless of day-length. In addition, we found that Si_DTF QTL is more associated with seed-yield and yield components than with days to flowering. A bulk-segregation analysis was applied to identify additional QTL differing in allele frequencies between early and late flowering under both day-length conditions. Candidate genes mining within the identified major QTL intervals revealed two flowering-related genes with different expression levels between the parental lines, indicating their contribution to sesame flowering regulation.

CONCLUSIONS

Our findings demonstrate the essential role of flowering date on yield components and will serve as a basis for future sesame breeding.

Integrated Bulk Segregant Analysis, Fine Mapping, and Transcriptome Revealed QTLs and Candidate Genes Associated with Drought Adaptation in Wild Watermelon

Drought stress has detrimental effects on crop productivity worldwide. A strong root system is crucial for maintaining water and nutrients uptake under drought stress. Wild watermelons possess resilient roots with excellent drought adaptability. However, the genetic factors controlling this trait remain uninvestigated. In this study, we conducted a bulk segregant analysis (BSA) on an F2 population consisting of two watermelon genotypes, wild and domesticated, which differ in their lateral root development under drought conditions. We identified two quantitative trait loci (qNLR_Dr. Chr01 and qNLR_Dr. Chr02) associated with the lateral root response to drought. Furthermore, we determined that a small region (0.93 Mb in qNLR_Dr. Chr01) is closely linked to drought adaptation through quantitative trait loci (QTL) validation and fine mapping. Transcriptome analysis of the parent roots under drought stress revealed unique effects on numerous genes in the sensitive genotype but not in the tolerant genotype. By integrating BSA, fine mapping, and the transcriptome, we identified six genes, namely L-Ascorbate Oxidase (AO), Cellulose Synthase-Interactive Protein 1 (CSI1), Late Embryogenesis Abundant Protein (LEA), Zinc-Finger Homeodomain Protein 2 (ZHD2), Pericycle Factor Type-A 5 (PFA5), and bZIP transcription factor 53-like (bZIP53-like), that might be involved in the drought adaptation. Our findings provide valuable QTLs and genes for marker-assisted selection in improving water-use efficiency and drought tolerance in watermelon. They also lay the groundwork for the genetic manipulation of drought-adapting genes in watermelon and other Cucurbitacea species.

Identification of QTLs and allelic effect controlling lignan content in sesame (Sesamum indicum L.) using QTL-seq approach

Sesame (Sesamum indicum L.), an oilseed crop, is gaining worldwide recognition for its healthy functional ingredients as consumption increases. The content of lignans, known for their antioxidant and anti-inflammatory effects, is a key agronomic trait that determines the industrialization of sesame. However, the study of the genetics and physiology of lignans in sesame is challenging, as they are influenced by multiple genes and environmental factors, therefore, the understanding of gene function and synthetic pathways related to lignan in sesame is still limited. To address these knowledge gaps, we conducted genetic analyses using F7 recombinant inbred line (RIL) populations derived from Goenbaek and Gomazou as low and high lignin content variants, respectively. Using the QTL-seq approach, we identified three loci, qLignan1-1, qLignan6-1, and qLignan11-1, that control lignan content, specifically sesamin and sesamolin. The allelic effect between loci was evaluated using the RIL population. qLignan6-1 had an additive effect that increased lignan content when combined with the other two loci, suggesting that it could be an important factor in gene pyramiding for the development of high-lignan varieties. This study not only highlights the value of sesame lignan, but also provides valuable insights for the development of high-lignan varieties through the use of DNA markers in breeding strategies. Overall, this research contributes to our understanding of the importance of sesame oil and facilitates progress in sesame breeding for improved lignan content.

QTL mapping in sesame (Sesamum indicum L.): A review

Sesame (Sesamum indicum L.) is an important oilseed crop used for food, feed, medicinal, and industrial applications. Inherently low genetic yield potential and susceptibility to biotic and abiotic stresses contribute to low productivity in sesame. Development of stress resistant varieties coupled with high yield is a viable option to raise the genetic potential of sesame. Conventional phenotype-based breeding methods have made an important role in the last couple of decades by developing several sesame varieties with improved quality, yield, and tolerance to biotic and abiotic stresses. However, due to adverse environmental effects, time consuming to develop new variety, and low genetic gain, conventional phenotype-based approach is not adequate to satisfy the rising population growth. In this context, advanced method of genotype selection via modern techniques of biotechnology plays essential roles in reducing the constraints and boosting sesame production to satisfy the huge demand. In line to this, quantitative trait loci (QTL) mapping is considered as a promising method to address the problems of sesame breeding. Previously, huge data have been generated in the practical use of QTL for sesame improvement. Therefore, this paper aims to review recent advances in the area of QTL mapping for yield and yield related traits in sesame for enhancing and sustaining sesame production. In this section, we present an intensive review on the identification and mapping of the most desirable potential candidate genes/QTLs associated with desirable traits. Moreover, this review focuses on the major QTL regions and/or potential candidate genes and associated molecular markers that could provide potential genetic resources for molecular marker-assisted selection and further cloning of functional genes for yield and yield-related traits as well as various biotic and abiotic stress tolerances. Finally, the summarized QTL mapping data shed light on future directions for enhanced sesame breeding programs.

A derived weedy rice × ancestral cultivar cross identifies evolutionarily relevant weediness QTLs

Weedy rice (Oryza spp.) is a weedy relative of the cultivated rice that competes with the crop and causes significant production loss. The BHA (blackhull awned) US weedy rice group has evolved from aus cultivated rice and differs from its ancestors in several important weediness traits, including flowering time, plant height and seed shattering. Prior attempts to determine the genetic basis of weediness traits in plants using linkage mapping approaches have not often considered weed origins. However, the timing of divergence between crossed parents can affect the detection of quantitative trait loci (QTL) relevant to the evolution of weediness. Here, we used a QTL-seq approach that combines bulked segregant analysis and high-throughput whole genome resequencing to map the three important weediness traits in an F2 population derived from a cross between BHA weedy rice with an ancestral aus cultivar. We compared these QTLs with those previously detected in a cross of BHA with a more distantly related crop, indica. We identified multiple QTLs that overlapped with regions under selection during the evolution of weedy BHA rice and some candidate genes possibly underlying the evolution weediness traits in BHA. We showed that QTLs detected with ancestor-descendant crosses are more likely to be involved in the evolution of weediness traits than those detected from crosses of more diverged taxa.

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.

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.

Mapping of a QTL associated with sucrose content in peanut kernels using BSA-seq

As an important factor affecting the edible quality of peanut kernels, sucrose content is a complex quantitative trait regulated by multiple factors. In this study, an F₂ segregating population and a recombinant inbred line (RIL) population, derived from a cross between the high sucrose content variety Jihuatian 1 and the low sucrose content line PI478819, were used as materials to map a quantitative trait locus (QTL) associated with sucrose content in peanut kernels. Four QTLs were initially located on chromosomes A03 and A06 based on BSA-seq technology, and multiple kompetitive allele-specific PCR markers were developed based on single-nucleotide polymorphisms (SNPs) in the intervals. The markers were genotyped in the RIL population and finely mapped to a stable QTL, qSUCA06, located on chromosome A06 within a 0.29-Mb physical genomic interval (112367085-112662675 bp), which accounted for 31.95%-41.05% of the phenotypic variance explained. SNP and insertion/deletion annotations were performed on genes in the candidate interval, and having screened out those genes with mutations in exons, candidate genes were verified by qRT-PCR. The results revealed that Arahy.Y2LWD9 may be the main gene regulating sucrose content. The QTL identified in this study will not only contribute to marker-assisted breeding for improvement of peanut sucrose content but also paves the way for identifying gene function.

Identification of QTLs and joint QTL segments of leaflet traits at different canopy layers in an interspecific RIL population of soybean

A leaflet trait on different canopy layers may have different QTLs; leaflet trait QTLs may cluster to form joint QTL segments; all canopy layer QTLs form a complete QTL system for a leaflet trait. As the main part of the plant canopy structure, leaf/leaflet size and shape affect the plant architecture and yield. To explore the leaflet trait QTL system, a population composed of 199 recombinant inbred lines derived from Changling (annual wild, narrow leaflet) and Yiqianli (landrace, broad leaflet) with their parents was tested for leaflet length (LL), width (LW) and length to width (LLW). The population was genotyped with specific-locus amplified fragment sequencing (SLAF-seq) and applied for linkage mapping of the leaflet traits. The results showed that the leaflet traits varied greatly even within a plant, which supported a stratified leaflet sampling strategy to evaluate these traits at top, middle and bottom canopy layers. Altogether, 13 LL, 10 LW and 9 LLW in a total of 32 plus 3 duplicated QTLs were identified, in which, 17 QTLs were new ones, and 48.6%, 28.6% and 22.8% of QTLs were from the top, middle and bottom layers, respectively, indicating the genetic importance of the top layer leaves. Since a leaflet trait may have layer-specific QTLs, all layer QTLs form a complete QTL system. Five QTL clusters each with their QTL supporting intervals overlapped were designated as joint QTL segments (JQSs). In JQS-16, with its linkage map further validated using PCR markers, two QTLs, qLW-16-1 and qLLW-16-1 of the top layer leaflet, were identified six QTL·times. Six candidate genes were predicted, with Glyma.16G127900 as the most potential one for LW and LLW. Three PCR markers, Gm16PAV0653, BARCSOYSSR_16_0796 and YC-16-3, were suggested for marker-assisted selection for LW and LLW in JQS-16.

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.