Identification of Candidate Genes Regulating the Seed Coat Color Trait in Sesame (Sesamum indicum L.) Using an Integrated Approach of QTL Mapping and Transcriptome Analysis

High-density genetic map and quantitative trait loci map of skin color in hawthorn (Crataegus pinnatifida bge. Var. major N.E.Br.)

Fruit skin color is an important trait of the hawthorn tree, which has an important influence on fruit quality. Crataegus pinnatifida Bge. var. Major N.E.Br. Is one of the most widely cultivated varieties in China and has a long history of medicinal use. In recent years, it has attracted the attention of the world due to its nutritional and medicinal values. Skin color is the focus of breeders and food processors. At present, skin color-related genes have still not been mapped. In this study, "Shandong Da Mianqiu" (♀, red skin color), "Da Huang Mianzha" (♂, yellow skin color) and 131 F1 hybrids were used to construct genetic map of hawthorn by RAD-seq, and QTL mapping was performed by combining these features with the hue angle and the observed color. In this study, 13,260 SNP was assigned to 17 linkage groups, with an integrated map covering 2,297.75 cM was constructed. A total of 5 QTLs related to hawthorn skin color were detected on LG1, LG3 and LG15. Whether hue angle or pericarp color acts as phenotype for QTL mapping, the candidate genes include bHLH086, WD repeat regions and Myb-like. bHLH, WD and Myb play an important role in the color regulation of Hawthorn skin color. These results lay a solid foundation for QTL mapping and molecular marker-assisted breeding of hawthorn.

Genetic Dissection of Diverse Seed Coat Patterns in Cowpea through a Comprehensive GWAS Approach

This study investigates the genetic determinants of seed coat color and pattern variations in cowpea (Vigna unguiculata), employing a genome-wide association approach. Analyzing a mapping panel of 296 cowpea varieties with 110,000 single nucleotide polymorphisms (SNPs), we focused on eight unique coat patterns: (1) Red and (2) Cream seed; (3) White and (4) Brown/Tan seed coat; (5) Pink, (6) Black, (7) Browneye and (8) Red/Brown Holstein. Across six GWAS models (GLM, SRM, MLM, MLMM, FarmCPU from GAPIT3, and TASSEL5), 13 significant SNP markers were identified and led to the discovery of 23 candidate genes. Among these, four specific genes may play a direct role in determining seed coat pigment. These findings lay a foundational basis for future breeding programs aimed at creating cowpea varieties aligned with consumer preferences and market requirements.

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 map for faba bean (Vicia faba L.) and quantitative trait loci mapping of seed-related traits

Faba bean (Vicia faba L.) is a valuable legume crop and data on its seed-related traits is required for yield and quality improvements. However, basic research on faba bean is lagging compared to that of other major crops. In this study, an F₂ faba bean population, including 121 plants derived from the cross WY7×TCX7, was genotyped using the Faba_bean_130 K targeted next-generation sequencing genotyping platform. The data were used to construct the first ultra-dense faba bean genetic map consisting of 12,023 single nucleotide polymorphisms markers covering 1,182.65 cM with an average distance of 0.098 cM. The map consisted of 6 linkage groups, which is consistent with the 6 faba bean chromosome pairs. A total of 65 quantitative trait loci (QTL) for seed-related traits were identified (3 for 100-seed weight, 28 for seed shape, 12 for seed coat color, and 22 for nutritional quality). Furthermore, 333 candidate genes that are likely to participate in the regulation of seed-related traits were also identified. Our research findings can provide a basis for future faba bean marker-assisted breeding and be helpful to further modify and improve the reference genome.

Genetic mapping of QTLs controlling brown seed coat traits by genome resequencing in sesame (Sesamum indicum L.)

INTRODUCTION

Sesame seeds have become an irreplaceable source of edible oils and food products with rich nutrients and a unique flavor, and their metabolite contents and physiological functions vary widely across different seed coat colors. Although the quantitative trait loci (QTLs) for genetic variation in seed coat color have been extensively investigated, the identification of unique genetic loci for intermediate colors such as brown has not been reported due to their complexity.

METHODS

Here, we crossed the white sesame 'Yuzhi No. 8' (YZ8) and the brown sesame 'Yanzhou Erhongpi' (YZEHP) to construct a recombinant inbred line (RIL) population with consecutive self-fertilization for ten generations.

RESULTS

The selfed F1 seeds were brown which was controlled by a dominant gene. Based on the genotyping by whole-genome resequencing of the RILs, a major-effect QTL for brown coat color was identified through both bulk segregant analysis (BSA) and genetic linkage mapping in sesame, which was located within a 1.19 Mb interval on chromosome 6 (qBSCchr6). Moreover, we found that the YZEHP seed coat initially became pigmented at 20 days post-anthesis (DPA) and was substantially colored at 30 DPA. We screened 13 possible candidate genes based on the effects of genetic variants on protein coding and predicted gene functions. Furthermore, qRT‒PCR was used to verify the expression patterns of these genes in different post-anthesis developmental periods. We noted that in comparison to YZ8 seeds, YZEHP seeds had expression of SIN_1023239 that was significantly up-regulated 2.5-, 9.41-, 6.0-, and 5.9-fold at 15, 20, 25, and 30 DPA, respectively, which was consistent with the pattern of brown seed coat pigment accumulation.

DISCUSSION

This study identified the first major-effect QTL for the control of the brown seed coat trait in sesame. This finding lays the foundation for further fine mapping and cloning as well as investigating the regulatory mechanism of seed coat color in 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.

Analysis of transcriptome data and quantitative trait loci enables the identification of candidate genes responsible for fiber strength in Gossypium barbadense

Gossypium barbadense possesses a superior fiber quality because of its fiber length and strength. An in-depth analysis of the underlying genetic mechanism could aid in filling the gap in research regarding fiber strength and could provide helpful information for Gossypium barbadense breeding. Three quantitative trait loci related to fiber strength were identified from a Gossypium barbadense recombinant inbred line (PimaS-7 × 5917) for further analysis. RNA sequencing was performed in the fiber tissues of PimaS-7 × 5917 0–35 days postanthesis. Four specific modules closely related to the secondary wall-thickening stage were obtained using the weighted gene coexpression network analysis. In total, 55 genes were identified as differentially expressed from 4 specific modules. Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes were used for enrichment analysis, and Gbar_D11G032910, Gbar_D08G020540, Gbar_D08G013370, Gbar_D11G033670, and Gbar_D11G029020 were found to regulate fiber strength by playing a role in the composition of structural constituents of cytoskeleton and microtubules during fiber development. Quantitative real-time PCR results confirmed the accuracy of the transcriptome data. This study provides a quick strategy for exploring candidate genes and provides new insights for improving fiber strength in cotton.

Identification of genetic loci conferring seed coat color based on a high-density map in soybean

Seed coat color is a typical evolutionary trait. Identification of the genetic loci that control seed coat color during the domestication of wild soybean could clarify the genetic variations between cultivated and wild soybean. We used 276 F₁₀ recombinant inbred lines (RILs) from the cross between a cultivated soybean (JY47) and a wild soybean (ZYD00321) as the materials to identify the quantitative trait loci (QTLs) for seed coat color. We constructed a high-density genetic map using re-sequencing technology. The average distance between adjacent markers was 0.31 cM on this map, comprising 9,083 bin markers. We identified two stable QTLs (qSC08 and qSC11) for seed coat color using this map, which, respectively, explained 21.933 and 26.934% of the phenotypic variation. Two candidate genes (CHS3C and CHS4A) in qSC08 were identified according to the parental re-sequencing data and gene function annotations. Five genes (LOC100786658, LOC100801691, LOC100806824, LOC100795475, and LOC100787559) were predicted in the novel QTL qSC11, which, according to gene function annotations, might control seed coat color. This result could facilitate the identification of beneficial genes from wild soybean and provide useful information to clarify the genetic variations for seed coat color in cultivated and wild soybean.