Metabolome genome-wide association study provides biochemical and genetic insights into natural variation of primary metabolites in sesame.

Plants' primary metabolites are of great importance from the survival and nutritional perspectives. However, the genetic bases underlying the profiles of primary metabolites in oilseed crops remain largely unclear. As one of the main oilseed crops, sesame (Sesamum indicum L.) is a potential model plant for investigating oil metabolism in plants. Therefore, the objective of this study is to disclose the genetic variants associated with variation in the content of primary metabolites in sesame. We performed a comprehensive metabolomics analysis of primary metabolites in 412 diverse sesame accessions using gas chromatography-mass spectrometry and identified a total of 45 metabolites, including fatty acids, monoacylglycerols (MAGs), and amino acids. Genome-wide association study unveiled 433 significant single-nucleotide polymorphism loci associated with variation in primary metabolite contents in sesame. By integrating diverse genomic analyses, we identified 10 key candidate causative genes of variation in MAG, fatty acid, asparagine, and sucrose contents. Among them, SiDSEL was significantly associated with multiple traits. SiCAC3 and SiKASI were strongly associated with variation in oleic acid and linoleic acid contents. Overexpression of SiCAC3, SiKASI, SiLTPI.25, and SiLTPI.26 in transgenic Arabidopsis and Saccharomyces cerevisiae revealed that SiCAC3 is a potential target gene for improvement of unsaturated fatty acid levels in crops. Furthermore, we found that it may be possible to breed several quality traits in sesame simultaneously. Our results provide valuable genetic resources for improving sesame seed quality and our understanding of oilseed crops' primary metabolism.

Inhibition of AGEs-RAGE-PP2A Axis Alleviates Cognitive Impairment after Chronic Heart Failure.

To investigate the effect of the AGEs-RAGE-PP2A axis on cognitive impairment (CI) after chronic heart failure (CHF). Mice were divided into six groups: Sham, TAC, Sham+RAGE-/-, TAC+RAGE-/-, AG, and FTY720 group. AG mice and FTY720 mice were treated with AGEs inhibitor (aminoguanidine, AG) and PP2A activator (FTY720) respectively after TAC surgery. The cardiac function of AG and TAC+RAGE-/- mice was significantly better than that of TAC mice (P<0.05). However, the heart function of FTY720 mice were just improved a part of that. To behavioral function, the escape latency period of the TAC+RAGE-/-, AG and FTY720 mice were significantly shorter (P<0.05), and the times of platform crossings and residence time of them were significantly improved (P<0.05). HE staining and silver staining show the structure of TAC+RAGE-/-, AG and FTY720 mice were more complete. Also, in these three groups, the expression of Aß and p-tau protein in the brain can be significantly down-regulated (P<0.05) and the PP2A protein expression level was up-regulated (P<0.05). And the expression of hippocampal Bax, Cyt-C, and Caspase-3 of that were all down-regulated (P<0.05), and Bcl-2 was up-regulated (P<0.05). Deficient of AGEs, RAGE and activating PP2A can significantly attenuate the cognitive impairment in CHF mice, and protect the brain structure. This mechanism seems via reducing the expression of Aß, p-tau, and apoptotic protein.

The pattern of alternative splicing and DNA methylation alteration and their interaction in linseed (Linum usitatissimum L.) response to repeated drought stresses.

BACKGROUND: Drought stress has significantly hampered agricultural productivity worldwide and can also result in modifications to DNA methylation levels. However, the dynamics of DNA methylation and its association with the changes in gene transcription and alternative splicing (AS) under drought stress are unknown in linseed, which is frequently cultivated in arid and semiarid regions. RESULTS: We analysed AS events and DNA methylation patterns in drought-tolerant (Z141) and drought-sensitive (NY-17) linseed under drought stress (DS) and repeated drought stress (RD) treatments. We found that the number of intron-retention (IR) and alternative 3' splice site (Alt3'SS) events were significantly higher in Z141 and NY-17 under drought stress. We found that the linseed response to the DS treatment was mainly regulated by transcription, while the response to the RD treatment was coregulated by transcription and AS. Whole genome-wide DNA methylation analysis revealed that drought stress caused an increase in the overall methylation level of linseed. Although we did not observe any correlation between differentially methylated genes (DMGs) and differentially spliced genes (DSGs) in this study, we found that the DSGs whose gene body region was hypermethylated in Z141 and hypomethylated in NY-17 were enriched in abiotic stress response Gene Ontology (GO) terms. This finding implies that gene body methylation plays an important role in AS regulation in some specific genes. CONCLUSION: Our study is the first comprehensive genome-wide analysis of the relationship between linseed methylation changes and AS under drought and repeated drought stress. Our study revealed different interaction patterns between differentially expressed genes (DEGs) and DSGs under DS and RD treatments and differences between methylation and AS regulation in drought-tolerant and drought-sensitive linseed varieties. The findings will probably be of interest in the future. Our results provide interesting insights into the association between gene expression, AS, and DNA methylation in linseed under drought stress. Differences in these associations may account for the differences in linseed drought tolerance.

Plantamajoside attenuates cardiac fibrosis via inhibiting AGEs activated-RAGE/autophagy/EndMT pathway.

Advanced glycation end products (AGEs) have been identified to transduce fibrogenic signals via inducing the activation of their receptor (RAGE)-mediated pathway. Recently, disrupting AGE-RAGE interaction has become a promising therapeutic strategy for chronic heart failure (CHF). Endothelial-to-mesenchymal transition (EndMT) is close to the cardiac fibrosis pathological process. Our previous studies have demonstrated that knockout RAGE suppressed the autophagy-mediated EndMT, and thus alleviated cardiac fibrosis. Plantamajoside (PMS) is the major bioactive compound of Plantago Asiatica, and its activity of anti-fibrosis has been documented in many reports. However, its effect on CHF and the underlying mechanism remains elusive. Thus, we tried to elucidate the protective role of PMS in CHF from the viewpoint of the AGEs/RAGE/autophagy/EndMT axis. Herein, PMS was found to attenuate cardiac fibrosis and dysfunction, suppress EndMT, reduce autophagy levels and serum levels of AGEs, yet did not affect the expression of RAGE in CHF mice. Mechanically, PMS possibly binds to the V-domain of RAGE, which is similar to the interaction between AGEs and RAGE. Importantly, this competitive binding disturbed AGEs-induced the RAGE-autophagy-EndMT pathway in vitro. Collectively, our results indicated that PMS might exert an anti-cardiac fibrosis effect by specifically binding RAGE to suppress the AGEs-activated RAGE/autophagy/EndMT pathway.

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.

Resequencing of 410 Sesame Accessions Identifies SINST1 as the Major Underlying Gene for Lignans Variation.

Sesame is a promising oilseed crop that produces specific lignans of clinical importance. Hence, a molecular description of the regulatory mechanisms of lignan biosynthesis is essential for crop improvement. Here, we resequence 410 sesame accessions and identify 5.38 and 1.16 million SNPs (single nucleotide polymorphisms) and InDels, respectively. Population genomic analyses reveal that sesame has evolved a geographic pattern categorized into northern (NC), middle (MC), and southern (SC) groups, with potential origin in the southern region and subsequent introduction to the other regions. Selective sweeps analysis uncovers 120 and 75 significant selected genomic regions in MC and NC groups, respectively. By screening these genomic regions, we unveiled 184 common genes positively selected in these subpopulations for exploitation in sesame improvement. Genome-wide association study identifies 17 and 72 SNP loci for sesamin and sesamolin variation, respectively, and 11 candidate causative genes. The major pleiotropic SNPC/A locus for lignans variation is located in the exon of the gene SiNST1. Further analyses revealed that this locus was positively selected in higher lignan content sesame accessions, and the "C" allele is favorable for a higher accumulation of lignans. Overexpression of SiNST1C in sesame hairy roots significantly up-regulated the expression of SiMYB58, SiMYB209, SiMYB134, SiMYB276, and most of the monolignol biosynthetic genes. Consequently, the lignans content was significantly increased, and the lignin content was slightly increased. Our findings provide insights into lignans and lignin regulation in sesame and will facilitate molecular breeding of elite varieties and marker-traits association studies.

Comparison of immunohistochemistry and RT-qPCR for assessing ER, PR, HER2, and Ki67 and evaluating subtypes in patients with breast cancer.

PURPOSE: Currently, the most commonly applied method for the determination of breast cancer subtypes is to test estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), and Ki67 by immunohistochemistry (IHC). However, the IHC method has substantial intraobserver and interobserver variability. ESR1, PGR, ERBB2, and MKi67 mRNA tests by reverse transcription-quantitative polymerase chain reaction (RT-qPCR) assay may improve the diagnostic objectivity and efficiency. Here, we compared the concordance between RT-qPCR and IHC for assessment of the same biomarkers and evaluated the subtypes. METHODS: A total of 265 eligible cases were divided into a training cohort and a validation cohort, and the expressions of ER/ESR1, PR/PGR, HER2/ERBB2, and Ki67/MKI67 were tested by IHC and RT-qPCR. Then, the appropriate cutoff of RT-qPCR was calculated in the training cohort. The concordance between RT-qPCR and IHC was calculated for individual marker. In addition, we investigated the subtypes based on the RT-qPCR results. RESULTS: The Spearman correlation coefficients between ER/ESR1, PR/PGR, HER2/ERBB2, and Ki67/MKI67 by IHC and RT-qPCR were 0.768, 0.699, 0.762, and 0.387, respectively. The cutoff values for the RT-qPCR assay of ESR1 (1%), PGR (1%), ERBB2, and MKi67 (14%) were 35.539, 32.139, 36.398, and 29.176, respectively. The overall percent agreement (OPA) between ER/ESR1, PR/PGR, HER2/ERBB2, and Ki67/MKI67 by IHC and RT-qPCR was 92.48%, 73.68%, 92.80%, and 74.44%, respectively. A total of 224 (84.53%) specimens were concordant for the breast cancer subtypes (IHC-based type) by RT-qPCR. CONCLUSION: Evaluation of breast cancer biomarker status by RT-qPCR was highly concordant with IHC. RT-qPCR can be used as a supplementary method to detect molecular markers of breast cancer.

The fluorescent aptasensor based on CRISPR-Cas12a combined with TdT for highly sensitive detection of cocaine.

Ultrasensitive and specific detection of cocaine is of great significance for monitoring cocaine abuse. Herein, a fluorescent aptasensor via coupling CRISPR-Cas12a, with magnetic nanoparticles (MNPs), split-aptamer, and terminal deoxynucleotidyl transferase (TdT), was developed for the detection of cocaine. In short, the complete cocaine aptamer is split into two parts, one is modified on magnetic nanoparticles (MNPs) and the other is free. The presence of cocaine will mediate the binding of these two segments. Then TdT will mediate the extension to form an ultra-long sequence that can bind with multiple CRISPR-Cas12a resulting in the trans-cleavage activity of CRISPR-Cas12a being triggered. Thence, the DNA reporter which is bi-labeled with fluorophore and quencher is cleaved resulting in the generation of a fluorescence signal. The developed fluorescent aptasensor realizes the detection of cocaine with excellent sensitivity and specificity. The detection limit is low down to 33 pM, and the linear range is from 330 to 1.65 × 105 pM. Most importantly, this fluorescent aptasensor can be successfully applied to the determination of cocaine in human plasma samples.

High-resolution temporal transcriptome sequencing unravels ERF and WRKY as the master players in the regulatory networks underlying sesame responses to waterlogging and recovery.

Major crops are generally sensitive to waterlogging, but our limited understanding of the waterlogging gene regulatory network hinders the efforts to develop waterlogging-tolerant cultivars. We generated high-resolution temporal transcriptome data from root of two contrasting sesame genotypes over a 48 h period waterlogging and drainage treatments. Three distinct chronological transcriptional phases were identified, including the early-waterlogging, late-waterlogging and drainage responses. We identified 47 genes representing the core waterlogging-responsive genes. Waterlogging/drainage-induced transcriptional changes were mainly driven by ERF and WRKY transcription factors (TF). The major difference between the two genotypes resides in the early transcriptional phase. A chronological transcriptional network model predicting putative causal regulations between TFs and downstream waterlogging-responsive genes was constructed and some interactions were validated through yeast one-hybrid assay. Overall, this study unveils the architecture and dynamic regulation of the waterlogging/drainage response in a non-model crop and helps formulate new hypotheses on stress sensing, signaling and sophisticated adaptive responses.

Signal Source Positioning Based on Angle-Only Measurements in Passive Sensor Networks.

Some passive sensors can measure only directions of arrival of signals, but the real positions of signal sources are often desirable, which can be estimated by combining distributed passive sensors as a network. However, passive observations should be correctly associated first. This paper studies the multi-target data association and signal localization problem in distributed passive sensor networks. With angle-only measurements from distributed passive sensors, multiple lines in a 3-dimensional (3D) scenario can be built and then those that will intersect in a small volume in 3D are classified into the same source. The center of the small volume is taken as an estimate of the signal source position, whose statistical distributions are formulated. If the minimum distance is less than an association threshold, then two lines are considered to be from the same signal source. In numerical results, the impacts of angle measurement accuracy and platform self-positioning accuracy are analyzed, indicating that this method can achieve a prescribed data association rate and a high positioning performance with a low computation cost.

Signal Source Localization with Long-Term Observations in Distributed Angle-Only Sensors.

Angle-only sensors cannot provide range information of targets and in order to determine accurate position of a signal source, one can connect distributed passive sensors with communication links and implement a fusion algorithm to estimate target position. To measure moving targets with sensors on moving platforms, most of existing algorithms resort to the filtering method. In this paper, we present two fusion algorithms to estimate both the position and velocity of moving target with distributed angle-only sensors in motion. The first algorithm is termed as the gross least square (LS) algorithm, which takes all observations from distributed sensors together to form an estimate of the position and velocity and thus needs a huge communication cost and a huge computation cost. The second algorithm is termed as the linear LS algorithm, which approximates locations of sensors, locations of targets, and angle-only measures for each sensor by linear models and thus does not need each local sensors to transmit raw data of angle-only observations, resulting in a lower communication cost between sensors and then a lower computation cost at the fusion center. Based on the second algorithm, a truncated LS algorithm, which estimates the target velocity through an average operation, is also presented. Numerical results indicate that the gross LS algorithm, without linear approximation operation, often benefits from more observations, whereas the linear LS algorithm and the truncated LS algorithm, both bear lower communication and computation costs, may endure performance loss if the observations are collected in a long period such that the linear approximation model becomes mismatch.

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

BACKGROUND: Sesame is a rare example of non-model and minor crop for which numerous genetic loci and candidate genes underlying features of interest have been disclosed at relatively high resolution. These progresses have been achieved thanks to the applications of the genome-wide association study (GWAS) approach. GWAS has benefited from the availability of high-quality genomes, re-sequencing data from thousands of genotypes, extensive transcriptome sequencing, development of haplotype map and web-based functional databases in sesame. RESULTS: In this paper, we reviewed the GWAS methods, the underlying statistical models and the applications for genetic discovery of important traits in sesame. A novel online database SiGeDiD ( http://sigedid.ucad.sn/ ) has been developed to provide access to all genetic and genomic discoveries through GWAS in sesame. We also tested for the first time, applications of various new GWAS multi-locus models in sesame. CONCLUSIONS: Collectively, this work portrays steps and provides guidelines for efficient GWAS implementation in sesame, a non-model crop.

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

BACKGROUND: Sesame (Sesamum indicum L.) leaves, flowers, especially seeds are used in traditional medicine to prevent or cure various diseases. Its seed's market is expanding. However, the other tissues are still underexploited due to the lack of information related to metabolites distribution and variability in the plant. Herein, the metabolite profiles of five sesame tissues (leaves, fresh seeds, white and purple flowers, and fresh carpels) have been investigated using ultra-high-performance liquid chromatography-mass spectrometry (UPLC-MS/MS)-based widely targeted metabolomics analysis platform. RESULTS: In total, 776 metabolites belonging to diverse classes were qualitatively and quantitatively identified. The different tissues exhibited obvious differences in metabolites composition. The majority of flavonoids predominantly accumulated in flowers. Amino acids and derivatives, and lipids were identified predominantly in fresh seeds followed by flowers. Many metabolites, including quinones, coumarins, tannins, vitamins, terpenoids and some bioactive phenolic acids (acteoside, isoacteoside, verbascoside, plantamajoside, etc.) accumulated mostly in leaves. Lignans were principally detected in seeds. 238 key significantly differential metabolites were filtered out. KEGG annotation and enrichment analyses of the differential metabolites revealed that flavonoid biosynthesis, amino acids biosynthesis, and phenylpropanoid biosynthesis were the main differently regulated pathways. In addition to the tissue-specific accumulation of metabolites, we noticed a cooperative relationship between leaves, fresh carpels, and developing seeds in terms of metabolites transfer. Delphinidin-3-O-(6"-O-p-coumaroyl)glucoside and most of the flavonols were up-regulated in the purple flowers indicating they might be responsible for the purple coloration. CONCLUSION: This study revealed that the metabolic processes in the sesame tissues are differently regulated. It offers valuable resources for investigating gene-metabolites interactions in sesame tissues and examining metabolic transports during seed development in sesame. Furthermore, our findings provide crucial knowledge that will facilitate sesame biomass valorization.

Genome-Wide Analysis of nsLTP Gene Family and Identification of SiLTPs Contributing to High Oil Accumulation in Sesame (Sesamum indicum L.).

The biosynthesis and storage of lipids in oil crop seeds involve many gene families, such as nonspecific lipid-transfer proteins (nsLTPs). nsLTPs are cysteine-rich small basic proteins essential for plant development and survival. However, in sesame, information related to nsLTPs was limited. Thus, the objectives of this study were to identify the Sesamum indicum nsLTPs (SiLTPs) and reveal their potential role in oil accumulation in sesame seeds. Genome-wide analysis revealed 52 SiLTPs, nonrandomly distributed on 10 chromosomes in the sesame variety Zhongzhi 13. Following recent classification methods, the SiLTPs were divided into nine types, among which types I and XI were the dominants. We found that the SiLTPs could interact with several transcription factors, including APETALA2 (AP2), DNA binding with one finger (Dof), etc. Transcriptome analysis showed a tissue-specific expression of some SiLTP genes. By integrating the SiLTPs expression profiles and the weighted gene co-expression network analysis (WGCNA) results of two contrasting oil content sesame varieties, we identified SiLTPI.23 and SiLTPI.28 as the candidate genes for high oil content in sesame seeds. The presumed functions of the candidate gene were validated through overexpression of SiLTPI.23 in Arabidopsis thaliana. These findings expand our knowledge on nsLTPs in sesame and provide resources for functional studies and genetic improvement of oil content in sesame seeds.

Comprehensive Analysis of SRO Gene Family in Sesamum indicum (L.) Reveals Its Association with Abiotic Stress Responses.

SIMILAR TO RCD-ONEs (SROs) comprise a small plant-specific gene family which play important roles in regulating numerous growth and developmental processes and responses to environmental stresses. However, knowledge of SROs in sesame (Sesamum indicum L.) is limited. In this study, four SRO genes were identified in the sesame genome. Phylogenetic analysis showed that 64 SROs from 10 plant species were divided into two groups (Group I and II). Transcriptome data revealed different expression patterns of SiSROs over various tissues. Expression analysis showed that Group II SROs, especially SiSRO2b, exhibited a stronger response to various abiotic stresses and phytohormones than those in Group I, implying their crucial roles in response to environmental stimulus and hormone signals. In addition, the co-expression network and protein-protein interaction network indicated that SiSROs are associated with a wide range of stress responses. Moreover, transgenic yeast harboring SiSRO2b showed improved tolerance to salt, osmotic and oxidative stress, indicating SiSRO2b could confer multiple tolerances to transgenic yeast. Taken together, this study not only lays a foundation for further functional dissection of the SiSRO gene family, but also provides valuable gene candidates for genetic improvement of abiotic stress tolerance in sesame.

Gravity Observations and Apparent Density Changes before the 2017 Jiuzhaigou Ms7.0 Earthquake and Their Precursory Significance.

An Ms7.0 earthquake struck Jiuzhaigou (China) on 8 August 2017. The epicenter was in the eastern margin of the Tibetan Plateau, an area covered by a dense time-varying gravity observation network. Data from seven repeated high-precision hybrid gravity surveys (2014-2017) allowed the microGal-level time-varying gravity signal to be obtained at a resolution better than 75 km using the modified Bayesian gravity adjustment method. The "equivalent source" model inversion method in spherical coordinates was adopted to obtain the near-crust apparent density variations before the earthquake. A major gravity change occurred from the southwest to the northeast of the eastern Tibetan Plateau approximately 2 years before the earthquake, and a substantial gravity gradient zone was consistent with the tectonic trend that gradually appeared within the focal area of the Jiuzhaigou earthquake during 2015-2016. Factors that might cause such regional gravitational changes (e.g., vertical crustal deformation and variations in near-surface water distributions) were studied. The results suggest that gravity effects contributed by these known factors were insufficient to produce gravity changes as big as those observed, which might be related to the process of fluid material redistribution in the crust. Regional change of the gravity field has precursory significance for high-risk earthquake areas and it could be used as a candidate precursor for annual medium-term earthquake prediction.

Transcriptome and metabolome analyses of two contrasting sesame genotypes reveal the crucial biological pathways involved in rapid adaptive response to salt stress.

BACKGROUND: Soil salinity is one of the major serious factors that affect agricultural productivity of almost all crops worldwide, including the important oilseed crop sesame. In order to improve salinity resistance in sesame, it is crucial to understand the molecular mechanisms underlying the adaptive response to salinity stress. RESULTS: In the present study, two contrasting sesame genotypes differing in salt tolerance were used to decipher the adaptive responses to salt stress based on morphological, transcriptome and metabolome characterizations. Morphological results indicated that under salt stress, the salt-tolerant (ST) genotype has enhanced capacity to withstand salinity stress, higher seed germination rate and plant survival rate, as well as better growth rate than the salt-sensitive genotype. Transcriptome analysis revealed strongly induced salt-responsive genes in sesame mainly related to amino acid metabolism, carbohydrate metabolism, biosynthesis of secondary metabolites, plant hormone signal transduction, and oxidation-reduction process. Especially, several pathways were preferably enriched with differentially expressed genes in ST genotype, including alanine, aspartate and glutamate metabolism, carotenoid biosynthesis, galactose metabolism, glycolysis/gluconeogenesis, glyoxylate and dicarboxylate metabolism, porphyrin and chlorophyll metabolism. Metabolome profiling under salt stress showed a higher accumulation degree of metabolites involved in stress tolerance in ST, and further highlighted that the amino acid metabolism, and sucrose and raffinose family oligosaccharides metabolism were enhanced in ST. CONCLUSIONS: These findings suggest that the candidate genes and metabolites involved in crucial biological pathways may regulate salt tolerance of sesame, and increase our understanding of the molecular mechanisms underlying the adaptation of sesame to salt stress.

Transcriptomic and metabolomic profiling of drought-tolerant and susceptible sesame genotypes in response to drought stress.

BACKGROUND: Sesame is an important oil crop due to its high oil, antioxidant, and protein content. Drought stress is a major abiotic stress that affects sesame production as well as the quality of sesame seed. To reveal the adaptive mechanism of sesame in response to water deficient conditions, transcriptomic and metabolomics were applied in drought-tolerant (DT) and drought-susceptible (DS) sesame genotypes. RESULTS: Transcriptomic analysis reveals a set of core drought-responsive genes (684 up-regulated and 1346 down-regulated) in sesame that was robustly differently expressed in both genotypes. Most enriched drought-responsive genes are mainly involved in protein processing in endoplasmic reticulum, plant hormone signal transduction photosynthesis, lipid metabolism, and amino acid metabolism. Drought-susceptible genotype was more disturbed by drought stress at both transcriptional and metabolic levels, since more drought-responsive genes/metabolites were identified in DS. Drought-responsive genes associated with stress response, amino acid metabolism, and reactive oxygen species scavenging were more enriched or activated in DT. According to the partial least-squares discriminate analysis, the most important metabolites which were accumulated under drought stress in both genotypes includes ABA, amino acids, and organic acids. Especially, higher levels of ABA, proline, arginine, lysine, aromatic and branched chain amino acids, GABA, saccharopine, 2-aminoadipate, and allantoin were found in DT under stress condition. Combination of transcriptomic and metabolomic analysis highlights the important role of amino acid metabolism (especially saccharopine pathway) and ABA metabolism and signaling pathway for drought tolerance in sesame. CONCLUSION: The results of the present study provide valuable information for better understanding the molecular mechanism underlying drought tolerance of sesame, and also provide useful clues for the genetic improvement of drought tolerance in sesame.

The genetic basis of drought tolerance in the high oil crop Sesamum indicum.

Unlike most of the important food crops, sesame can survive drought but severe and repeated drought episodes, especially occurring during the reproductive stage, significantly curtail the productivity of this high oil crop. Genome-wide association study was conducted for traits related to drought tolerance using 400 diverse sesame accessions, including landraces and modern cultivars. Ten stable QTLs explaining more than 40% of the phenotypic variation and located on four linkage groups were significantly associated with drought tolerance related traits. Accessions from the tropical area harboured higher numbers of drought tolerance alleles at the peak loci and were found to be more tolerant than those from the northern area, indicating a long-term genetic adaptation to drought-prone environments. We found that sesame has already fixed important alleles conferring survival to drought which may explain its relative high drought tolerance. However, most of the alleles crucial for productivity and yield maintenance under drought conditions are far from been fixed. This study also revealed that pyramiding the favourable alleles observed at the peak loci is of high potential for enhancing drought tolerance in sesame. In addition, our results highlighted two important pleiotropic QTLs harbouring known and unreported drought tolerance genes such as SiABI4, SiTTM3, SiGOLS1, SiNIMIN1 and SiSAM. By integrating candidate gene association study, gene expression and transgenic experiments, we demonstrated that SiSAM confers drought tolerance by modulating polyamine levels and ROS homeostasis, and a missense mutation in the coding region partly contributes to the natural variation of drought tolerance in sesame.

Insight into the evolution and functional characteristics of the pan-genome assembly from sesame landraces and modern cultivars.

Sesame (Sesamum indicum L.) is an important oil crop renowned for its high oil content and quality. Recently, genome assemblies for five sesame varieties including two landraces (S. indicum cv. Baizhima and Mishuozhima) and three modern cultivars (S. indicum var. Zhongzhi13, Yuzhi11 and Swetha), have become available providing a rich resource for comparative genomic analyses and gene discovery. Here, we employed a reference-assisted assembly approach to improve the draft assemblies of four of the sesame varieties. We then constructed a sesame pan-genome of 554.05 Mb. The pan-genome contained 26 472 orthologous gene clusters; 15 409 (58.21%) of them were core (present across all five sesame genomes), whereas the remaining 41.79% (11 063) clusters and the 15 890 variety-specific genes were dispensable. Comparisons between varieties suggest that modern cultivars from China and India display significant genomic variation. The gene families unique to the sesame modern cultivars contain genes mainly related to yield and quality, while those unique to the landraces contain genes involved in environmental adaptation. Comparative evolutionary analysis indicates that several genes involved in plant-pathogen interaction and lipid metabolism are under positive selection, which may be associated with sesame environmental adaption and selection for high seed oil content. This study of the sesame pan-genome provides insights into the evolution and genomic characteristics of this important oilseed and constitutes a resource for further sesame crop improvement.