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Article

Genome-Wide Association Study Uncovers Loci and Candidate Genes Underlying Phytosterol Variation in Sesame (Sesamum indicum L.)

by
Zhijian Wang
1,
Qi Zhou
1,
Senouwa Segla Koffi Dossou
1,2,
Rong Zhou
1,
Yingzhong Zhao
1,
Wangyi Zhou
1,
Yanxin Zhang
1,
Donghua Li
1,
Jun You
1 and
Linhai Wang
1,*
1
Key Laboratory of Biology and Genetic Improvement of Oil Crops of the Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Wuhan 430062, China
2
Laboratoire de Physiologie et de Biotechnologie Végétales, Faculté des Sciences, Université de Lomé, Lomé 01BP1515, Togo
*
Author to whom correspondence should be addressed.
Agriculture 2022, 12(3), 392; https://doi.org/10.3390/agriculture12030392
Submission received: 24 February 2022 / Revised: 9 March 2022 / Accepted: 9 March 2022 / Published: 11 March 2022
(This article belongs to the Special Issue QTL Mapping for Yield and Quality Traits in Crops)
Browse Figures
Versions Notes

Abstract

:
Sesame is one of the most important oilseed crops grown worldwide. It provides diverse nutraceuticals—including lignans, unsaturated fatty acids (UFA), phytosterols, etc.—to humans. Among sesame’s nutraceuticals, phytosterols have received less attention from sesame breeders, although their biological and pharmacological functions have been recorded. Therefore, in the present study, we evaluated the variation of phytosterol contents in 402 sesame accessions grown in two environments and revealed their associated loci and candidate genes. Gas chromatography (GC) analysis unveiled that sesame mainly contains four phytosterols: campesterol, stigmasterol, β-sitosterol, and Δ5-avenasterol. β-sitosterol (1.6–4.656 mg/g) was the major phytosterol, followed by campesterol (0–2.847 mg/g), stigmasterol (0.356–1.826 mg/g), and Δ5-avenasterol (0–1.307 mg/g). The total phytosterol content varied from 2.694 to 8.388 mg/g. Genome-wide association study identified 33 significant associated single nucleotide polymorphism (SNP) loci for the four traits, of which Ch6-39270 and Ch11-142842 were environmentally stable and simultaneously linked with campesterol and stigmasterol content variation. Candidate genes screening indicated that SINPZ1100015 encoding a NAC domain-containing protein 43 is likely the major candidate effect gene of phytosterol variation in sesame. The results of this study extend knowledge of phytosterol variation in sesame and provide important resources for markers-assisted breeding of high-phytosterol content varieties.

1. Introduction

Phytosterols, or plant sterols, are a group of natural products that exist in various organs at all stages of plants’ development [1]. Phytosterols have received broad concern as a critical diet component and possess huge applications in foods, cosmetics, medicines, etc. [2]. They have shown a wide range of biological and pharmacological abilities, including promotion of lipids metabolism [3]; lowering cholesterol level [4,5]; and anticancer [6,7], anti-neurodegenerative [2], antioxidant and anti-microbial [8], and anti-cardiovascular disease activity [9]. Consequently, they have become compounds of countless research interests aiming to understand their physiological functions and improve their natural levels in seed oils through genetic engineering.
Structurally, sterols are based on 1,2-cyclopentane perhydrophenantrene and are distinguished by a hydroxyl moiety at the C-3 position and a side chain at the C-17 position [10]. Compared to animals, which contain only one main sterol type (cholesterol), plants possess diversified and complex sterol compositions [11]. Hitherto, over 250 types of phytosterols have been identified, among which β-sitosterol, stigmasterol, and campesterol are the most abundant in diverse plant species [11,12]. β-sitosterol and stigmasterol differ from campesterol in terms of the alkyl group in the side chain at the C-24 position. Campesterol has a methyl at C-24 (24-methylsterol), while the others have an ethyl group (24-ethylsterols) [12]. The diversity of phytosterols is associated with various in planta functions. They are precursors of a class of plant hormones, namely brassinosteroids (BRs), which regulate plant growth and development [12]. Besides their conversion into BRs, phytosterols are basically integral components of biological membranes. They regulate membrane fluidity and permeability to influence its functions, properties, and structure [13,14]. In addition, they are involved in transmembrane signal transduction via lipid microdomain formation and by modulating the activity of membrane-bound enzymes [12,14]. Accordingly, they play important roles during embryogenesis, cell proliferation and elongation, hormone signaling, vascular differentiation, and plant tolerance to environmental stresses [13,15,16,17]. Furthermore, they are required for the coordinated assembly of lipid droplets, which are intracellular organelles essential for energy storage and lipid metabolism in developing seeds [18].
The biosynthesis of phytosterols occurs in the endoplasmic reticulum mainly via the cycloartenol pathway and consists of three steps (Figure 1) [11,12]. The first step is the mevalonate pathway consisting of the conversion of acetyl-CoA into squalene via the formation of mevalonate and many intermediate reactions [11,12]. The second step consists of squalene cyclization up to the formation of cycloartenol [11,12]. The final step is the conversion of cycloartenol into phytosterols via a series of oxidative demethylation reactions [11,12]. The plant sterols biosynthetic pathway involves many enzymes, among which 3-hydroxy-3-methylglutaryl-CoA reductase (HMGR), C24-sterol methyltransferase (SMT), and C22-sterol desaturase (CYP710A) are the key ones [1,12]. The three major phytosterols are biosynthesized principally via SMT, sterol-Δ24-isomerase/reductase, or Dimunito/Dwarf1 (DWF1), and CYP710A [11].
Sesame (Sesamum indicum L., 2n = 26) is one of the most ancient oil crops widely cultivated in Asia, Africa, and South America [19]. Its oil contains important nutraceuticals such as UFA, lignans, vitamin E, and phytosterols. Therefore, with regard to nutraceutical functions, efforts are being made for the crop’s quality improvement. Accordingly, genetic markers and candidate genes associated with fatty acids (FAs), lignans, vitamin E have been detected [20,21,22,23]. However, despite their huge pharmacological capacities, no study has yet focused on phytosterol content variation in large sesame germplasms, and the genetic basis of its natural variation in sesame is undetermined. Therefore, it is necessary to reveal the variation and dissect the genetic basis of phytosterol content in sesame for quality-breeding purposes. This study investigated the composition and natural variation in phytosterol contents of 402 sesame accessions grown in two environments. Moreover, we performed a genome-wide association study (GWAS) for phytosterol traits in sesame for the first time and identified several significant SNP loci and candidate genes. These findings represent valuable resources for functional studies towards the genetic improvement of phytosterol contents in sesame.
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Figure 1. A diagram of the phytosterol biosynthesis pathway in plants. Adapted from [11,12,24].
Figure 1. A diagram of the phytosterol biosynthesis pathway in plants. Adapted from [11,12,24].
Agriculture 12 00392 g001

2. Materials and Methods

2.1. Plant Materials

The 402 sesame accessions were given by the National Medium-Term Sesame Gene Bank of China (Wuhan, China). The population was cultivated at two experimental field stations of the Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences (OCRI-CAAS) located in Wuhan (WH) and Zhumadian (ZMD). Wuhan belongs to the Yangtze River valley with a subtropical humid monsoon climate, while Zhumadian belongs to the Huang-Huai River valley with a warm temperate climate. Standard agronomic practices were applied in field management, and the experiments were conducted in a completely randomized block design, with three replications at each location. When the seeds reached maturity, they were harvested and dried. Seeds from the three replications were mixed and stored at the seed room for phytosterol content analysis.

2.2. Phytosterol Content Analysis

The sesame oil was extracted from 5.5 g of each seed sample in triplicate via a manual press. First, the primary extracts were centrifuged at 13,000 rpm for 10 min, and the clear oil supernatants were collected. Next, to 0.2 g of each seed pure oil extract, 0.5 mL of alpha-cholestanol was added as internal standard. Then, the samples were saponified by adding 10 mL of 2 M KOH–ethanol solution, followed by shaking at 60 °C for 1 h. After cooling at room temperature, 10 mL of n-hexane and 4 mL of distilled water were added to the saponification solution, vortex mixed, and the reaction was allowed to stand for 15 min. Next, the upper n-hexane extract was collected. This step was repeated twice, and the collected n-hexanes were pooled, following dehydration by anhydrous Na2SO4 and then evaporation to dryness. Finally, 100 μL of trimethylsilylation reagent (N, O-Bis(trimethylsilyl)trifluoroacetamide containing 1% trimethylchlorosilane) was added to the dried sample followed by derivatization at 105 °C for 15 min, and dissolution in 1 mL n-hexane.
The dissolved solution was analyzed using an Agilent 6890N gas chromatography (GC, Wilmington, NC, USA) equipped with a flame ionization detector (FID) and a DB-5HT (30 m × 0.22 mm × 0.1 μm) capillary column. The column temperature was initially set at 60 °C and held for 1 min and then increased to 310 °C at the rate of 40 °C/min and maintained at this temperature for 10 min. The FID temperature was set at 320 °C. The injection volume was 1 μL with a split ratio of 1:25. Helium served as the carrier gas at a 2 mL/min flow rate. The composition and concentration of the sterols were analyzed by the relative retention time and standard internal methods [25].

2.3. Statistical Analysis

The descriptive statistical analysis was performed by Microsoft Excel 2010. The frequency distributions were explored by SPSS (version 25.0, SPSS Inc, Chicago, IL, USA). The Pearson correlation coefficients for different phytosterols were calculated using the R package ‘ggplot’, and the statistical differences were determined by Student’s t-test.

2.4. Genome-Wide Association Analysis

5,385,583 single-nucleotide polymorphisms (SNPs) generated from the whole-genome resequencing of 402 worldwide sesame accessions data in our group (unpublished data) were used for the genome-wide association study (GWAS). The population structure (Q) analysis was carried out using the Admixture software, and the kinship (K) matrix was implemented using the Tassel 5.0 software [26]. It was reported that the linkage disequilibrium (LD) windows in the sesame genome were 88 kb [20,27]. The significance threshold was set as −log10 (P) ≥ 5. The GWAS for phytosterol content was conducted using the EMMAX software with the MLM (mixed linear model). The R package ‘qq-man’ was used to visualize GWAS results as Manhattan and QQ plots [28]. The PVE (R2) of each significant associated peak SNP was calculated by the regression model in Microsoft Excel 2010.

2.5. Identification of Candidate Gene and Haplotype Analysis

The candidate genes were extracted from the LD widow (±88 kb) of the significant associated SNP loci detected in the two environments [20,27]. Gene Ontology (GO) enrichment analysis was performed using an online tool at https://www.omicshare.com/tools/ (accessed on 1 December 2021). The LD (linkage disequilibrium) analysis and drawing were carried out with LDBlockShow software [29]. The haplotype analysis was performed using CandiHap software [30]. Haplotypes were classified according to all SNPs with MAF > 0.05 in the candidate gene. Haplotypes containing at least 10 accessions were used to perform comparative analysis, and the difference in the corresponding phytosterol content among the haplotypes was analyzed using Student’s t-test.

2.6. Gene Expression Analysis of Candidate Genes

Two contrasting sesame accessions in campesterol and stigmasterol contents, G268 (campesterol, 1.547 mg/g; stigmasterol, 0.498 mg/g) and G580 (campesterol, 0.758 mg/g; stigmasterol 1.419 mg/g) were selected for gene expression analysis. They were grown at the Wuhan experimental station from May to September 2021. Seed samples were collected at 20 days post-anthesis (DPA) on ice, frozen in liquid nitrogen, and then stored at −80 °C for RNA extraction.
The total RNA of the seed samples was extracted using EASYspin Plus Plant RNA Kit (Vazyme Biotech, Nanjing, China). The quantity and quality of RNA were evaluated by the ND-1000 NanoDrop spectrometer (NanoDrop Technologies, Wilmington, DE USA). The RNA was reverse-transcribed into cDNA with HiScriptIIQRT SuperMix (Vazyme Biotech, Nanjing, China). The qRT-PCR was conducted in triplicated with ChamQ™ SYBR1 qPCR Master Mix (Vazyme Biotech, Nanjing, China) on LightCycler480 real-time (RT) PCR system (Roche, Basel, Switzerland) following the manufacturer’s instructions. The specific primers for the selected genes were designed using Primer Premier 5.0 (PREMIER Biosoft, San Francisco, CA, USA), and the sesame H3.3 gene was used as an internal control (Table S1). The relative expression levels of genes were calculated by the comparative 2−ΔΔCt method [31].

3. Results

3.1. Phenotypic Variation and Correlation Analysis of Primary Phytosterols in Sesame

To reveal the natural variation in phytosterol content in sesame seeds, 402 sesame accessions were cultivated in two different environments located in Wuhan (WH) and Zhumadian (ZMD), and mature seed samples were collected and analyzed by GC. The results indicated that sesame contains four phytosterols: campesterol, stigmasterol, β-sitosterol, and Δ5-avenasterol. The summary of the descriptive statistics of the four phytosterol variation in sesame is presented in Table 1. The total phytosterol content varied from 2.694 to 8.206 mg/g and 2.986 to 8.388 mg/g in WH and ZMD, respectively. β-sitosterol and campesterol exhibited the highest contents with an average range of 2.662–3.003 mg/g and 1.129–1.298 mg/g, respectively. The average content of Δ5-avenasterol was the lowest in the two environments, with a range of 0.467–0.544 mg/g. Among them, campesterol and Δ5-avenasterol exhibited higher variations, and the coefficient of variation (CV) at the two locations was 28.85 and 31.14 for campesterol and 28.04 and 38.72 for Δ5-avenasterol. The lowest CV at the two locations of 15.87 and 17.58 was observed for β-sitosterol, indicating it is less affected by environmental conditions. The stigmasterol content varied from 0.356 to 1.825 mg/g, with CV ranging from 22.24 to 24.38. The four phytosterol contents in the two environments were almost normally distributed (Figure S1), indicating that they might be under the control of several loci. To facilitate the overview of differences in the variation of the four phytosterol contents in the two environments, we graphed the data and performed a one-way analysis of variance (ANOVA (Figure 2a)). The results confirmed that environmental conditions significantly influence phytosterol content in sesame.
We performed correlation analysis to investigate whether it would be possible to improve the four phytosterol contents simultaneously in sesame. The correlation trends among the four phytosterols in the two environments were consistent (Figure 2b,c). β-sitosterol, Δ5-avenasterol, and stigmasterol exhibited positive correlations with the most significant positive correlation observed between β-sitosterol and stigmasterol (r = 0.71 and 0.84 in WH and ZMD, respectively). The campesterol and stigmasterol contents were negatively correlated in the two environments.

3.2. GWAS for Four Phytosterol Contents in Sesame

The GWAS revealed 33 significant SNP loci explaining a PVE ranging from 1.37 to 31.02% associated with the four phytosterols (Table 2). The Manhattan and QQ plots for all traits at the two locations are shown in Figure S2. These loci are distributed on all the 13 chromosomes of the sesame genome. Notably, we detected 9, 12, 5, and 4 significant SNP loci for campesterol, stigmasterol, β-sitosterol, and Δ5-avenasterol, respectively. It is worth noting that two loci, Ch6-39270 and Ch11-142842, were associated with campesterol and stigmasterol in the two environments.

3.3. Candidate Genes Associated with Phytosterol Contents

The common loci (Chr11:142842 and Chr06:39270) of campesterol and stigmasterol detected in the two environments were selected for candidate genes identification. We screened the ±88 kb window of each locus and disclosed a total of 37 genes (Table S2). Of the 37 candidate genes, only 14 were annotated. Gene ontology (GO) enrichment analysis revealed that these genes are mainly involved in the metabolic process (eight genes), cellular process (seven genes), binding (eight genes), and catalytic activity (five genes) (Figure 3). We selected the eight genes assigned into the metabolic process and examined their expression levels at a critical sesame seed development stage of 20 DPA [32,33], in G268 (high campesterol and low stigmasterol contents sesame accession) and G580 (low campesterol and high stigmasterol contents sesame accession) via qRT-PCR. The results indicated that six of these genes are differentially expressed during seed development in G580 and G268 (Figure S3). Among them, SINPZ1100015 exhibited the most differential expression in the two sesame accessions.
SINPZ1100015 locate at the pleiotropic locus Chr11:142842 of campesterol and stigmasterol (Figure 4a,b). Interestingly, it may also contribute significantly to oil and lignans contents variation in sesame [20,23]. SINPZ1100015 encodes a NAC domain-containing protein 43 and is known to substantially influence the elongation of cells and deposition of secondary cell walls [34,35,36]. The LD analysis results corroborated the association analysis (Figure 4c,d). SINPZ1100015 contains three exons and two introns and harbored one type of SNP mutation (Figure 4e). The SNP mutation is a nonsynonymous mutation in the exon of the gene. It consists of allele change from C to A, leading to amino acid change from threonine (Thr) to lysine (Lys). The expression level of SINPZ1100015 in the seed of G268 at 20 DPA was significantly higher than that of G580 (Figure 4f). We identified two haplotypes of this gene, Hap1 (C/C) and Hap2 (A/A). Hap1 is associated with high campesterol content and low stigmasterol content, while Hap2 is associated with low campesterol content and high stigmasterol content (Figure 4g,h).

4. Discussion

It is essential for breeders to understand quantitative agronomic trait variation in crop germplasms under various environments as it helps select genotypes. In sesame, the variability of phytosterol contents was still not well understood. Ryan et al. [37] have tested one sesame variety and found that the content of β-sitosterol, campesterol, and stigmasterol was 1.39, 0.223, and 0.415 mg/g, respectively. Liu et al. [38] have evaluated five sesame oil samples and found that they contained brassicasterol, β-sitosterol, campesterol, and stigmasterol in the range of 0.0031–0.0044, 0.746–1.131, 0.112–0.182, and 0.113–0.129 mg/g, respectively. In this study, we analyzed 402 sesame accessions grown in two environments and found that sesame mainly contains four phytosterols, including β-sitosterol, stigmasterol, campesterol, and Δ5-avenasterol. This results suggest that the brassicasterol detected by Liu et al. might be due to contamination during experimental processes [38]. In agreement with previous studies, we found that β-sitosterol (1.909–4.287 mg/g) is the most predominant phytosterol in sesame. Campesterol, stigmasterol, and Δ5-avenasterol content varied from 0 to 2.847, 0.356 to 1.826, and 0 to 1.307 mg/g, respectively. Compared with other crops, the composition and content of phytosterols in sesame are different. In rice, only three phytosterols, namely campesterol, stigmasterol, and β-sitosterol, have been detected [13]. In pecan nut, Δ5-avenasterol (1.139–2.144 mg/g) has been reported as the second most abundant sterol [39], while in sesame, we found that Δ5-avenasterol is the least abundant sterol. In rapeseed oil, it is reported that the main phytosterols include β-sitosterol (0.976–2.148 mg/g), followed by campesterol (0.636–1.364 mg/g), and brassicasterol (0.375–0.678 mg/g) [40]. Consistent with studies in wheat and sunflower, we found that the variability of phytosterol content in sesame is attributable to genotypes and environmental conditions [41,42]. The content of phytosterols gradually increased in response to changes in the external environment [43]. β-sitosterol content exhibited the lowest CV of 15.87 and 17.58 at the two locations, indicating it might be easier to improve its content through genetic engineering. Taken together, these findings confirm that β-sitosterol is the most prevalent and abundant phytosterol in plants and imply that it might play critical roles in the growth and development of plants. It is reported that the ratio of campesterol to sitosterol influences Arabidopsis plant growth [44]. β-sitosterol may also affect the physical and chemical properties of ordered microdomains to modulate signal pathways of biological membranes [45].
Phytosterols are naturally occurring compounds essential for plant species survival and human health [2,3,8,9,11,12]. In sesame, GWAS has become the method of choice for identifying genetic variants associated with complex agronomic traits [46,47]. Herein, we performed GWAS for the four phytosterols in sesame and detected 33 significant SNP loci, among which Ch6-39270 and Ch11-142842 were associated with campesterol and stigmasterol in the two environments. We searched for candidate genes for phytosterol variation at these two loci and selected 37 genes for future functional studies. Campesterol and stigmasterol contents were negatively correlated at the two locations, indicating that it might not be possible to breed for high content of campesterol and stigmasterol in sesame. The biosynthetic pathways of the two phytosterols represent support of this finding. In plants, the ratio between 24-methylcholesterol (campesterol) and 24-ethylcholesterol (β-sitosterol) is of great importance for maintaining membranes’ properties and cell survival, which in turn influence normal growth and development of the whole plant [12]. A decrease in the content of campesterol may negatively affect BRs biosynthesis leading to a dwarfism phenotype [44]. Meanwhile, the stigmasterol/β-sitosterol ratio in membranes may influence plants’ response to various abiotic and biotic stresses [12]. β-sitosterol is the precursor of stigmasterol. At the locus Ch11-142842, associated with campesterol and stigmasterol, locate the gene SINPZ1100015 (SIN_1005755/ SiNST1). It encoded a NAC domain-containing protein 43 and was previously associated with oil and lignans contents variation in sesame [20,23]. Its homologous AT2G46770 in Arabidopsis is a master regulator of secondary wall synthesis [34,35,36,48]. As integral components of biological membranes, variation in phytosterol contents may significantly influence secondary cell walls formation. In cotton, it was shown that changes in the composition and content of phytosterols affect fiber cell elongation and secondary cell wall deposition [49]. The qRT-PCR analysis showed that SINPZ1100015 is significantly expressed in high campesterol content sesame varieties compared to high stigmasterol varieties. Haplotype analysis showed that the Hap1 (C/C) of SINPZ1100015 are favorable for higher campesterol accumulation in seeds. In contrast, the Hap2 (A/A) is favorable for high stigmasterol accumulation in seeds. These results indicate that SINPZ1100015 is the major candidate effect gene of phytosterol contents variation in sesame. Targeting this gene may help improve sesame seed quality. Therefore, functional studies are required to decipher the molecular mechanisms underlined by this gene for exploitation in sesame breeding.

5. Conclusions

In summary, this study characterized the composition and variation of phytosterols in sesame. Sesame seeds contain four phytosterols—β-sitosterol, campesterol, stigmasterol, and Δ5-avenasterol according to their order of abundance. Although these traits are significantly influenced by environmental conditions, they could be improved through genetic engineering. Thirty-three (33) significant SNP loci associated with the four phytosterols were detected, and 37 candidate genes were selected for future studies. Among them, SINPZ1100015 was associated with stigmasterol and campesterol contents variation and may represent the major candidate effect gene for phytosterol variation in sesame. Our findings represent key resources for future studies regarding the dissection of molecular mechanisms involved in phytosterol biosynthesis and regulation in sesame and for crop improvement.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/agriculture12030392/s1, Figure S1: Histograms for the frequency distribution of phytosterols in WH and ZMD; Figure S2: Manhattan plots and QQ plots of the four phytosterol traits content in WH and ZMD; Figure S3: Expression levels of eight selected candidate genes in two contrasting campesterol and stigmasterol contents sesame accessions; Table S1: List of the primers used for the qRT-PCR analysis; Table S2: List of the 37 candidate genes detected at the environmentally stable loci associated with campesterol and stigmasterol variation.

Author Contributions

Conceptualization, J.Y. and L.W.; Formal analysis, Z.W. and S.S.K.D.; Funding acquisition, Y.Z. (Yingzhong Zhao), J.Y. and L.W.; Methodology, Z.W. and Q.Z.; Project administration, L.W.; Resources, R.Z. and Y.Z. (Yanxin Zhang); Supervision, J.Y. and L.W.; Validation, Z.W., R.Z. and D.L.; Visualization, W.Z.; Writing—original draft, Z.W.; Writing—review and editing, S.S.K.D., J.Y. and L.W. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Agricultural Science and Technology Innovation Project of the Chinese Academy of Agricultural Sciences (CAAS-ASTIP-2016-OCRI), the Key Research Projects of Hubei Province (2020BBA045, 2020BHB028), the Science and Technology Innovation Project of Hubei Province (201620000001048), China Agriculture Research System (CARS-14), and the Fundamental Research Funds for Central Non-Profit Scientific Institution (Y2019XK15-02).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

All data generated or analyzed during this study are included in this published article and its Supplementary Materials. The datasets are available from the corresponding author on reasonable request.

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

References

  1. Neelakandan, A.K.; Chamala, S.; Valliyodan, B.; Nes, W.D.; Nguyen, H.T. Metabolic engineering of soybean affords improved phytosterol seed traits. Plant Biotechnol. J. 2012, 10, 12–19. [Google Scholar] [CrossRef] [PubMed]
  2. Sharma, N.; Tan, M.A.; An, S.S.A. Phytosterols: Potential metabolic modulators in neurodegenerative diseases. Int. J. Mol. Sci. 2021, 22, 12255. [Google Scholar] [CrossRef] [PubMed]
  3. Feng, S.; Belwal, T.; Li, L.; Limwachiranon, J.; Liu, X.; Luo, Z. Phytosterols and their derivatives: Potential health-promoting uses against lipid metabolism and associated diseases, mechanism, and safety issues. Compr. Rev. Food Sci. Food Saf. 2020, 19, 1243–1267. [Google Scholar] [CrossRef] [PubMed]
  4. Racette, S.B.; Lin, X.; Ma, L.; Ostlund, R.E. Natural dietary phytosterols. J. AOAC Int. 2015, 98, 679–684. [Google Scholar] [CrossRef] [PubMed]
  5. De Smet, E.; Mensink, R.P.; Plat, J. Effects of plant sterols and stanols on intestinal cholesterol metabolism: Suggested mechanisms from past to present. Mol. Nutr. Food Res. 2012, 56, 1058–1072. [Google Scholar] [CrossRef]
  6. Ramprasath, V.R.; Awad, A.B. Role of phytosterols in cancer prevention and treatment. J. AOAC Int. 2015, 98, 735–738. [Google Scholar] [CrossRef]
  7. Shahzad, N.; Khan, W.; Shadab; Ali, A.; Saluja, S.S.; Sharma, S.; Al-Allaf, F.A.; Abduljaleel, Z.; Ibrahim, I.A.A.; Abdel-Wahab, A.F.; et al. Phytosterols as a natural anticancer agent: Current status and future perspective. Biomed. Pharmacother. 2017, 88, 786–794. [Google Scholar] [CrossRef]
  8. Sohn, S.I.; Rathinapriya, P.; Balaji, S.; Balan, D.J.; Swetha, T.K.; Durgadevi, R.; Alagulakshmi, S.; Singaraj, P.; Pandian, S. Phytosterols in seaweeds: An overview on biosynthesis to biomedical applications. Int. J. Mol. Sci. 2021, 22, 12691. [Google Scholar] [CrossRef]
  9. Kaur, R.; Myrie, S.B. Association of dietary phytosterols with cardiovascular disease biomarkers in humans. Lipids 2020, 55, 569–584. [Google Scholar] [CrossRef]
  10. Kopylov, A.T.; Malsagova, K.A.; Stepanov, A.A.; Kaysheva, A.L. Diversity of plant sterols metabolism: The impact on human health, sport, and accumulation of contaminating sterols. Nutrients 2021, 13, 1623. [Google Scholar] [CrossRef]
  11. Zhang, X.; Lin, K.; Li, Y. Highlights to phytosterols accumulation and equilibrium in plants: Biosynthetic pathway and feedback regulation. Plant Physiol. Biochem. 2020, 155, 637–649. [Google Scholar] [CrossRef] [PubMed]
  12. Valitova, J.N.; Sulkarnayeva, A.G.; Minibayeva, F.V. Plant sterols: Diversity, biosynthesis, and physiological functions. Biochem. 2016, 81, 819–834. [Google Scholar] [CrossRef] [PubMed]
  13. Kumar, M.S.S.; Ali, K.; Dahuja, A.; Tyagi, A. Role of phytosterols in drought stress tolerance in rice. Plant Physiol. Biochem. 2015, 96, 83–89. [Google Scholar] [CrossRef] [PubMed]
  14. Hartmann, M.A. Plant sterols and the membrane environment. Trends Plant Sci. 1998, 3, 170–175. [Google Scholar] [CrossRef]
  15. Wedow, J.M.; Burroughs, C.H.; Rios Acosta, L.; Leakey, A.D.B.; Ainsworth, E.A. Age-dependent increase in α-tocopherol and phytosterols in maize leaves exposed to elevated ozone pollution. Plant Direct 2021, 5, e00307. [Google Scholar] [CrossRef] [PubMed]
  16. Clouse, S.D. Arabidopsis mutants reveal multiple roles for sterols in plant development. Plant Cell 2002, 14, 1995–2000. [Google Scholar] [CrossRef] [Green Version]
  17. Schrick, K.; Mayer, U.; Martin, G.; Bellini, C.; Kuhnt, C.; Schmidt, J.; Jürgens, G. Interactions between sterol biosynthesis genes in embryonic development of Arabidopsis. Plant J. 2002, 31, 61–73. [Google Scholar] [CrossRef]
  18. Yu, L.; Fan, J.; Zhou, C.; Xu, C. Sterols are required for the coordinated assembly of lipid droplets in developing seeds. Nat. Commun. 2021, 12, 5598. [Google Scholar] [CrossRef]
  19. Mondal, N.; Bhat, K.V.; Srivastava, P.S.; Sen, S.K. Effects of domestication bottleneck and selection on fatty acid desaturases in Indian sesame germplasm. Plant Genet. Resour. Characterisation Util. 2016, 14, 81–90. [Google Scholar] [CrossRef]
  20. Wei, X.; Liu, K.; Zhang, Y.; Feng, Q.; Wang, L.; Zhao, Y.; Li, D.; Zhao, Q.; Zhu, X.; Zhu, X.; et al. Genetic discovery for oil production and quality in sesame. Nat. Commun. 2015, 6, 8609. [Google Scholar] [CrossRef] [Green Version]
  21. Ke, T.; Dong, C.; Mao, H.; Zhao, Y.; Chen, H.; Liu, H.; Dong, X.; Tong, C.; Liu, S. Analysis of expression sequence tags from a full-length-enriched cDNA library of developing sesame seeds (Sesamum indicum). BMC Plant Biol. 2011, 11, 62. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  22. He, Q.; Xu, F.; Min, M.H.; Chu, S.H.; Kim, K.W.; Park, Y.J. Genome-wide association study of vitamin E using genotyping by sequencing in sesame (Sesamum indicum). Genes Genom. 2019, 41, 1085–1093. [Google Scholar] [CrossRef] [PubMed]
  23. Xu, F.; Zhou, R.; Dossou, S.S.K.; Song, S.; Wang, L. Fine mapping of a major pleiotropic QTL associated with sesamin and sesamolin variation in sesame (Sesamum indicum L.). Plants 2021, 10, 1343. [Google Scholar] [CrossRef] [PubMed]
  24. Harker, M.; Hellyer, A.; Clayton, J.C.; Duvoix, A.; Lanot, A.; Safford, R. Co-ordinate regulation of sterol biosynthesis enzyme activity during accumulation of sterols in developing rape and tobacco seed. Planta 2003, 216, 707–715. [Google Scholar] [CrossRef]
  25. Zhao, X.; Shen, J.; Chang, K.J.; Kim, S.H. Analysis of fatty acids and phytosterols in ethanol extracts of Nelumbo nucifera seeds and rhizomes by GC-MS. J. Agric. Food Chem. 2013, 61, 6841–6847. [Google Scholar] [CrossRef]
  26. Liu, H.; Li, X.; Zhang, Q.; Yuan, P.; Liu, L.; King, G.J.; Ding, G.; Wang, S.; Cai, H.; Wang, C.; et al. Integrating a genome-wide association study with transcriptomic data to predict candidate genes and favourable haplotypes influencing Brassica napus seed phytate. DNA Res. 2021, 28, dsab011. [Google Scholar] [CrossRef]
  27. Dossa, K.; Li, D.; Zhou, R.; Yu, J.; Wang, L.; Zhang, Y.; You, J.; Liu, A.; Mmadi, M.A.; Fonceka, D.; et al. The genetic basis of drought tolerance in the high oil crop Sesamum indicum. Plant Biotechnol. J. 2019, 17, 1788–1803. [Google Scholar] [CrossRef] [Green Version]
  28. Turner, S. qqman: An R package for visualizing GWAS results using Q-Q and manhattan plots. J. Open Source Softw. 2018, 3, 731. [Google Scholar] [CrossRef] [Green Version]
  29. Dong, S.S.; He, W.M.; Ji, J.J.; Zhang, C.; Guo, Y.; Yang, T.L. LDBlockShow: A fast and convenient tool for visualizing linkage disequilibrium and haplotype blocks based on variant call format files. Brief. Bioinform. 2021, 22, bbaa227. [Google Scholar] [CrossRef]
  30. Li, X.; Shi, Z.; Qie, Q.; Gao, J.; Wang, X.; Han, Y. CandiHap: A toolkit for haplotype analysis for sequence of samples and fast identification of candidate causal gene(s) in genome-wide association study. bioRxiv 2020. [Google Scholar] [CrossRef]
  31. Livak, K.J.; Schmittgen, T.D. Analysis of relative gene expression data using real-time quantitative PCR and the 2-ΔΔCT method. Methods 2001, 25, 402–408. [Google Scholar] [CrossRef] [PubMed]
  32. Wang, L.; Zhang, Y.; Li, D.; Dossa, K.; Wang, M.L.; Zhou, R.; Yu, J.; Zhang, X. Gene expression profiles that shape high and low oil content sesames. BMC Genet. 2019, 20, 45. [Google Scholar] [CrossRef] [PubMed]
  33. Wang, L.; Dossou, S.S.K.; Wei, X.; Zhang, Y.; Li, D.; Yu, J.; Zhang, X. Transcriptome dynamics during black and white sesame (Sesamum indicum L.) seed development and identification of candidate genes associated with black pigmentation. Genes 2020, 11, 1399. [Google Scholar] [CrossRef] [PubMed]
  34. Mitsuda, N.; Iwase, A.; Yamamoto, H.; Yoshida, M.; Seki, M.; Shinozaki, K.; Ohme-Takagi, M. NAC transcription factors, NST1 and NST3, are key regulators of the formation of secondary walls in woody tissues of Arabidopsis. Plant Cell 2007, 19, 270–280. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  35. Zhong, R.; Ye, Z.H. The arabidopsis NAC transcription factor NST2 functions together with SND1 and NST1 to regulate secondary wall biosynthesis in fibers of inflorescence stems. Plant Signal. Behav. 2015, 10, 37–41. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  36. Zhong, R.; Richardson, E.A.; Ye, Z.H. Two NAC domain transcription factors, SND1 and NST1, function redundantly in regulation of secondary wall synthesis in fibers of Arabidopsis. Planta 2007, 225, 1603–1611. [Google Scholar] [CrossRef] [PubMed]
  37. Ryan, E.; Galvin, K.; O’Connor, T.P.; Maguire, A.R.; O’Brien, N.M. Phytosterol, squalene, tocopherol content and fatty acid profile of selected seeds, grains, and legumes. Plant Foods Hum. Nutr. 2007, 62, 85–91. [Google Scholar] [CrossRef] [PubMed]
  38. Liu, S.; Hu, H.; Yu, Y.; Zhao, J.; Liu, L.; Zhao, S.; Xie, J.; Li, C.; Shen, M. Simultaneous determination of tocopherols, phytosterols, and squalene in vegetable oils by high performance liquid chromatography-tandem mass spectrometry. Food Anal. Methods 2021, 14, 1567–1576. [Google Scholar] [CrossRef]
  39. Bouali, I.; Trabelsi, H.; Herchi, W.; Martine, L.; Albouchi, A.; Bouzaien, G.; Sifi, S.; Boukhchina, S.; Berdeaux, O. Analysis of pecan nut (Carya illinoinensis) unsaponifiable fraction. Effect of ripening stage on phytosterols and phytostanols composition. Food Chem. 2014, 164, 309–316. [Google Scholar] [CrossRef]
  40. Cegielska-Taras, T.; Nogala-Kałucka, M.; Szala, L.; Siger, A. Study of variation of tocochromanol and phytosterol contents in black and yellow seeds of Brassica napus L. doubled haploid populations. Acta Sci. Pol. Technol. Aliment. 2016, 15, 321–332. [Google Scholar] [CrossRef] [Green Version]
  41. Haddadi, P.; Ebrahimi, A.; Langlade, N.B.; Yazdi-samadi, B.; Berger, M.; Calmon, A.; Naghavi, M.R.; Vincourt, P.; Sarrafi, A. Genetic dissection of tocopherol and phytosterol in recombinant inbred lines of sunflower through quantitative trait locus analysis and the candidate gene approach. Mol. Breed. 2012, 29, 717–729. [Google Scholar] [CrossRef]
  42. Nurmi, T.; Nyström, L.; Edelmann, M.; Lampi, A.M.; Piironen, V. Phytosterols in wheat genotypes in the health grain diversity screen. J. Agric. Food Chem. 2008, 56, 9710–9715. [Google Scholar] [CrossRef] [PubMed]
  43. Kumar, M.S.S.; Mawlong, I.; Ali, K.; Tyagi, A. Regulation of phytosterol biosynthetic pathway during drought stress in rice. Plant Physiol. Biochem. 2018, 129, 11–20. [Google Scholar] [CrossRef]
  44. Schaeffer, A.; Bronner, R.; Benveniste, P.; Schaller, H. The ratio of campesterol to sitosterol that modulates growth in Arabidopsis is controlled by STEROL METHYLTRANSFERASE 2;1. Plant J. 2001, 25, 605–615. [Google Scholar] [CrossRef] [PubMed]
  45. Zauber, H.; Burgos, A.; Garapati, P.; Schulze, W.X. Plasma membrane lipid-protein interactions affect signaling processes in sterol-biosynthesis mutants in Arabidopsis thaliana. Front. Plant Sci. 2014, 5, 78. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  46. Berhe, M.; Dossa, K.; You, J.; Mboup, P.A.; Diallo, I.N.; Diouf, D.; Zhang, X.; Wang, L. Genome-wide association study and its applications in the non-model crop Sesamum indicum. BMC Plant Biol. 2021, 21, 283. [Google Scholar] [CrossRef] [PubMed]
  47. Cui, C.; Liu, Y.; Liu, Y.; Cui, X.; Sun, Z.; Du, Z.; Wu, K.; Jiang, X.; Mei, H.; Zheng, Y. Genome-wide association study of seed coat color in sesame (Sesamum indicum L.). PLoS ONE 2021, 16, e0251526. [Google Scholar] [CrossRef] [PubMed]
  48. Zhong, R.; Yuan, Y.; Spiekerman, J.J.; Guley, J.T.; Egbosiuba, J.C.; Ye, Z.H. Functional characterization of NAC and MYB transcription factors involved in regulation of biomass production in switchgrass (Panicum virgatum). PLoS ONE 2015, 10, e0251526. [Google Scholar] [CrossRef]
  49. Niu, Q.; Tan, K.; Zang, Z.; Xiao, Z.; Chen, K.; Hu, M.; Luo, M. Modification of phytosterol composition influences cotton fiber cell elongation and secondary cell wall deposition. BMC Plant Biol. 2019, 19, 208. [Google Scholar] [CrossRef]
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Figure 2. Variation and correlation of four phytosterol contents in sesame. Variation of four phytosterol contents in two different environments (a). *** indicates significant difference at p < 0.001. The correlation between the four phytosterols in Wuhan, WH (b) and Zhumadian, ZMD (c).
Figure 2. Variation and correlation of four phytosterol contents in sesame. Variation of four phytosterol contents in two different environments (a). *** indicates significant difference at p < 0.001. The correlation between the four phytosterols in Wuhan, WH (b) and Zhumadian, ZMD (c).
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Figure 3. Gene ontology (GO) enrichment analysis of the 37 candidate genes. The red, green, and blue bars represent the biological process, cellular component, and molecular function, respectively.
Figure 3. Gene ontology (GO) enrichment analysis of the 37 candidate genes. The red, green, and blue bars represent the biological process, cellular component, and molecular function, respectively.
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Figure 4. Colocalization, expression, and haplotype analysis of the candidate gene SINPZ1100015 associated with campesterol and stigmasterol content variation in sesame. Manhattan plots of stigmasterol (a) and campesterol (b) in WH and ZMD. Locus Chr11:142842 LD heatmap for stigmasterol (c) and campesterol (d). The gene’s structure (e). The red and grey rectangles line indicate upstream, exons, and introns, respectively. The bottom left is the synonymous SNP, and the right is the non-synonymous SNP. Expression levels of SINPZ1100015 in G268 and G580 (two contrasting campesterol and stigmasterol content sesame accessions) seed at 20 DPA (f). ** indicates significant difference at p < 0.01. Campesterol (g) and stigmasterol (h) contents in the two haplotypes of SINPZ1100015. The different letter indicates significant differences at p < 0.05.
Figure 4. Colocalization, expression, and haplotype analysis of the candidate gene SINPZ1100015 associated with campesterol and stigmasterol content variation in sesame. Manhattan plots of stigmasterol (a) and campesterol (b) in WH and ZMD. Locus Chr11:142842 LD heatmap for stigmasterol (c) and campesterol (d). The gene’s structure (e). The red and grey rectangles line indicate upstream, exons, and introns, respectively. The bottom left is the synonymous SNP, and the right is the non-synonymous SNP. Expression levels of SINPZ1100015 in G268 and G580 (two contrasting campesterol and stigmasterol content sesame accessions) seed at 20 DPA (f). ** indicates significant difference at p < 0.01. Campesterol (g) and stigmasterol (h) contents in the two haplotypes of SINPZ1100015. The different letter indicates significant differences at p < 0.05.
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Table
Table 1. Variation of primary phytosterol contents in sesame
Table 1. Variation of primary phytosterol contents in sesame
TraitEnvironmentMin (mg/g)Max (mg/g)Mean (mg/g)SDCV (%)
Campesterol2018_WH02.8471.1290.35231.14
2019_ZMD02.7511.2980.37528.85
Stigmasterol2018_WH0.4151.8260.8670.19322.24
2019_ZMD0.3561.6820.7930.19324.38
β-Sitosterol2018_WH1.7944.6563.0030.47715.87
2019_ZMD1.64.1142.6620.46817.58
Δ5-Avenasterol2018_WH01.3070.4670.18138.72
2019_ZMD0.1551.0120.5440.15328.04
Total phytosterol2018_WH2.6948.2065.4960.79814.6
2019_ZMD2.9868.3885.2970.85316.11
Min, minimum; Max, maximum; SD, standard deviation; CV, coefficient of variation.
Table
Table 2. List of the significant SNP loci associated with four phytosterol contents variation in two environments in sesame
Table 2. List of the significant SNP loci associated with four phytosterol contents variation in two environments in sesame
EnvironmentTraitLocusChrPositionRefAltp-ValuePVE (%)
WHCampesterolChr2-3701582370158CT5.6038.94
Chr3-18989758318989758CG5.7446.47
Chr4-10138424410138424CT6.0959.60
Chr5-970651659706516CT5.3127.76
Chr6-39270639270AC5.4241.63
Chr8-548678385486783CA6.0052.86
Chr11-14284211142842CA9.0797.95
Chr13-125543811312554381GA6.2579.03
StigmasterolChr-1-13179445113179445GA5.2074.53
Chr3-15930743315930743GA6.0985.22
Chr4-18569755418569755GA6.66811.40
Chr8-25004528825004528CA5.9543.03
Chr10-154658431015465843TC5.2826.67
Chr11-14284211142842CA19.67528.24
Chr12-102921951210292195CT7.1829.44
β-SitosterolChr4-401624144016241TC5.0335.98
Chr8-362315283623152GA5.0763.33
Chr11-1227222111227222TC5.3218.35
Chr13-148012781314801278AG5.1244.80
Δ5-AvenasterolChr2-718824127188241CA5.6072.61
Chr11-5738482115738482GA10.2116.42
Chr12-102902791210290279GA5.1157.19
ZMDCampesterolChr4-13279017413279017CT5.1821.37
Chr6-39270639270AC7.0708.20
Chr11-14284211142842CA14.88717.87
StigmasterolChr3-23741323741GT12.83022.01
Chr6-39270639270AC12.15419.11
Chr11-14284211142842CA18.35122.11
Chr7-17668358717668358GA10.52319.41
Chr11-11189511111895GA21.50731.02
Chr13-198994391319899439AG10.63519.54
β-SitosterolChr3-14800933314800933GA5.3014.41
Δ5-AvenasterolChr9-653066296530662CT5.2386.75
PVE, phenotypic variance explained.
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Wang, Z.; Zhou, Q.; Dossou, S.S.K.; Zhou, R.; Zhao, Y.; Zhou, W.; Zhang, Y.; Li, D.; You, J.; Wang, L. Genome-Wide Association Study Uncovers Loci and Candidate Genes Underlying Phytosterol Variation in Sesame (Sesamum indicum L.). Agriculture 2022, 12, 392. https://doi.org/10.3390/agriculture12030392

AMA Style

Wang Z, Zhou Q, Dossou SSK, Zhou R, Zhao Y, Zhou W, Zhang Y, Li D, You J, Wang L. Genome-Wide Association Study Uncovers Loci and Candidate Genes Underlying Phytosterol Variation in Sesame (Sesamum indicum L.). Agriculture. 2022; 12(3):392. https://doi.org/10.3390/agriculture12030392

Chicago/Turabian Style

Wang, Zhijian, Qi Zhou, Senouwa Segla Koffi Dossou, Rong Zhou, Yingzhong Zhao, Wangyi Zhou, Yanxin Zhang, Donghua Li, Jun You, and Linhai Wang. 2022. "Genome-Wide Association Study Uncovers Loci and Candidate Genes Underlying Phytosterol Variation in Sesame (Sesamum indicum L.)" Agriculture 12, no. 3: 392. https://doi.org/10.3390/agriculture12030392

APA Style

Wang, Z., Zhou, Q., Dossou, S. S. K., Zhou, R., Zhao, Y., Zhou, W., Zhang, Y., Li, D., You, J., & Wang, L. (2022). Genome-Wide Association Study Uncovers Loci and Candidate Genes Underlying Phytosterol Variation in Sesame (Sesamum indicum L.). Agriculture, 12(3), 392. https://doi.org/10.3390/agriculture12030392

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