Especially, six candidate genes were detected at 41.8–41.9 Mb genomic hotspots on chromosome 5 based on ANNOtate VARiation analysis. Among the genes, only Glyma.05G243400 carried a non-synonymous mutation that encodes a “translation elongation factor EF1A or initiation factor IF2gamma family protein” was identified. The haplotype analysis confirmed that Glyma.05G243400 exhibited highly significant variations in terms of tocopherol content across multiple experimental locations, suggesting that it can be the key candidate gene regulating soybean seed tocopherols. The present findings provide novel gene resources related to seed tocopherols for further validation by genome editing, functional characterization, and genetic improvement targeting enhanced tocopherol composition in soybean molecular breeding.Soybean seeds are primary sources of natural tocopherols used by the food and pharmaceutical industries, owing to their beneficial impacts on human health. Selection for higher tocopherol contents in seeds along with other desirable traits is an important goal in soybean breeding. In order to identify the genomic loci and candidate genes controlling tocopherol content in soybean seeds, the bulked-segregant analysis technique was performed using a natural population of soybean consisting of 1525 accessions. We constructed the bulked-segregant analysis based on 98 soybean accessions that showed extreme phenotypic variation for the target trait, consisting of 49 accessions with extremely-high and 49 accessions with extremely-low tocopherol content. A total of 144 variant sites and 109 predicted genes related to tocopherol content were identified, in which a total of 83 genes were annotated by the gene ontology functions. Furthermore, 13 enriched terms ( Vitamin E (VE) is an important health-promoting element in oilseed crops and is highly esteemed in foods, medicines, cosmetics, and animal feed ,2. VE isSoybean is one of the globally most significant leguminous crop species with an ever-increasing demand for its grains and processed products . SoybeanNext-generation sequencing (NGS) is a high-throughput molecular technology and has been used to identify several informative single nucleotide polymorphism (SNP) markers in a cost-effective and rapid fashion in diverse species. NGS techniques continue to provide new ways that can accelerate the genetic analysis of traits, such as candidate gene identification. One of the major applications of NGS in recent times involves the use of bulked segregant analysis (BSA) coupled with whole-genome resequencing (WGR) aimed at candidate gene identification and fine-mapping of causal polymorphisms. Thus, the bulked segregant analysis, an NGS technique popularly known as BSA-seq, has been applied in the genetic analysis since the early 1990s to elucidate gene conditioning phenotypic variations in organisms ,19. The Currently, molecular breeding techniques have been ubiquitously applied in soybean research and have become a fundamental means of increasing the quantitative and qualitative yields of the crop . Recent −1, ranging from 276.151 to 310.167 μg·g−1)   , and gen μg·g−1)  among th μg·g−1)  were sam μg·g−1) . The accThe two DNA bulks (high and low tocopherol content) were used to perform high-throughput BSA sequencing using an Illumina HiSeq platform  to identify the genomic variation between the two pools and, consequently, detect the putative candidate genomic loci and genes associated with tocopherols in soybean. The sequencing data generated 53.07 Gb  and 57.65 Gb  of high-quality clean reads of the high (VE-High) and low (VE-Low) bulks, respectively. Single-nucleotide polymorphisms (SNPs) are nucleotide variations in the genome, such as conversions and reversal of single bases. Insertion-deletions (InDels), on the other hand, are the insertions and missing genomic sequences of small DNA fragments. Following the alignment of reads to the soybean reference genome version 2.0 (Wm82.a2.v1), variant (SNPs and Indels) calling for the two bulks was performed. Variant detection was achieved with the SAMtools program . Poorly In this study, a total of 109 candidate genes  consistiAmong the candidate genes detected in this study, Glyma.08G184700 and Glyma.15G233300 had frameshift deletion mutation effects. Glyma.08G184700 and Glyma.15G233300 carried genomic variants of Chr08_14819413 and Chr15_43894622, respectively . Glyma.0Glyma.05G243400 contained non-synonymous mutation encoding “translation elongation factor EF1A or initiation factor IF2gamma family protein”  and corresponding alternative (ALT) base are first determined for each SNP. Subsequently, the ALT read is divided by the total read  in the bulk to give an SNP/InDel index, also known as the allele frequency. A delta SNP/InDel index or Δ(SNP/InDel-index) is finally computed as the difference of the SNP/InDel indices between the two bulks, where a higher Δ(SNP/InDel index) indicates that it is more likely that the SNP is linked to a gene conditioning the target trait. By examining the Δ(SNP/InDel-index) plots, the peak regions exceeding the threshold value were defined as putative candidate regions or regions with the fitted values greater than the standard deviations above the genome-wide media. Only peak regions that were highly consistent across the SNPs and InDels plots were considered putative genes associated with tocopherols. Based on a physical map constructed for all the 109 putative genes  and the protein” . Analysiocations .http://plantregmap.gao-lab.org/go.php accessed on 22 May 2022). The candidate genes were classified into two ontological classes: biological processes and molecular functions (p < 0.05) enriched. The GO enriched terms consisted of response to lipid (GO:0033993), response to abscisic acid (GO:0009737), response to alcohol (GO:0097305), response to oxygen-containing compound (GO:1901700), response to acid chemical (GO:0001101), transition metal ion transport (GO:0000041), seed germination (GO:0009845), seedling development (GO:0090351), response to chemical (GO:0042221), cellular response to abscisic acid stimulus (GO:0071215), response to endogenous stimulus (GO:0009719), transition metal ion transmembrane transporter activity (GO:0046915), and double-stranded DNA binding (GO:0003690) (The gene ontology (GO) database has a standard biological functions annotation system to produce functional annotation terms of genes and gene products. In this study, a total of 109 candidate genes  carryingunctions . Among t0003690) .Glyma.04G199900, Glyma.05G243800, Glyma.05G244100, Glyma.06G249800, and Glyma.17G219400 (GO:0033993: Response to lipid), and the genes included Glyma.05G243800, Glyma.05G244100, Glyma.06G249800, and Glyma.17G219400 (GO:0009737: Response to abscisic acid) (Glyma.05G243800 and Glyma.05G244100) were also identified via an SNP/InDel plot and verified by MapChart analysis (Glyma.05G243800 contained a mutation occurring at the genomic position of 41836669 and encodes a “receptor for activated C kinase 1C” while Glyma.05G244100 contained mutations occurring at genomic positions of 41855575 (upstream) and 41855657 (upstream), which encodes “phosphatidylethanolamine-binding protein (PEBP) family protein” , response to abscisic acid (GO:0009737), transition metal ion transmembrane transporter activity (GO:0046915), and double-stranded DNA binding (GO:0003690) were the most highly enriched . The annic acid) . Two of analysis . The genprotein” . This reprotein” . Candida binding . The preSoybean is a major grain legume and an oilseed crop with an estimated 260 million tons produced globally . The graTo identify genomic loci and candidate genes related to tocopherols in soybean seed, the soybean germplasm panel consisting of 1525 accessions  was cultivated in Beijing (2017 and 2018), Anhui (2017), and Hainan (2017 and 2018) and profiled for seed tocopherol content. The phenotypic data of tocopherol content distribution of the soybean accessions revealed a substantial continuous variation among the accessions . A naturGlyma.05G243400, encoding translation elongation factor EF1A or initiation factor IF2gamma family protein, was detected, which carries a mutation (T > G) with a genomic variant of Chr05_41807338 that induced a non-synonymous mutation  on chromosome 5, which contains six candidate genes . Specifimutation . Haplotyocations . Resultsocations . The curGlyma.08G184700, carrying frameshift deletion mutation, which encodes uridine diphosphate (UDP)-glycosyltransferase superfamily protein in chromosome 08  associated with the GO term “response to lipid” were considered putative genes that express tocopherol in soybean.Previous studies have revealed a possible biochemical association between tocopherol and lipid oxidation of oils . Thus, gPlant-growth regulators or phytohormones are plant signal molecules produced at different stages of plant growth, development, and during plant response to biotic and abiotic stresses . Plants OsHPPD, OsγTMT, and OsMPBQMT1) [HPPD, VTE2, VTE1, and VTE4) in response to increased ABA treatment [HPPD (p-hydroxyphenylpyruvate dioxygenase), VTE2 (Homogentisic acid phytyltransferase encoding homogentisate phytyltransferase), VTE1 , and VTE4  may be influenced by ABA. The involvement of tocopherols in promoting seed longevity and preventing lipid peroxidation during seed dormancy, seed germination, and early-stage seedling development [Glyma.05G243800, Glyma.05G244100, Glyma.06G249800, and Glyma.17G219400) associated with the GO term “response to abscisic acid” can be considered as promising candidates associated with tocopherol content in soybean.A previous study in rice focused on promoter analyses of the ABA-responsive genes and discovered the presence of several abscisic acid-responsive elements . For insMPBQMT1) . EarlierMPBQMT1)  also repMPBQMT1)  showed treatment . Meaningelopment  provideselopment ,63,65 suIn this study, a natural population consisting of 1525 soybean accessions collected from various soybean growing regions across the world was used to profile the tocopherol composition of the seeds . AccessiTocopherol components were detected from matured soybean seeds using a reverse-phase HPLC  system following the method described by Dwiyanti et al. (2007)  with som® spectrophotometer  and 1% agarose gel electrophoresis, respectively. DNA concentration was measured using Qubit® DNA Assay Kit in Qubit® 2.0 Flurometer . Only genomic DNA samples with an OD260/280 value ranging from 1.8 to 2.2 were considered good quality DNA for further analyses.At the vegetative stage (V2: one fully expanded trifoliolate leaf presence), leaves were sampled from young, healthy plants of accessions that exhibited extreme contrasting differences for tocopherol composition and used for genomic DNA isolation according to the standard protocol of the Novel Plant Genomic DNA Extraction Kit . The RNase A was used to remove RNA contamination. The concentration and quality of each genomic DNA were measured by the NanoPhotometer® 2.0 for preliminary quantification, diluted the library to 1 ng/μL, and then used Agilent 2100 Bioanalyzer to detect the insert size of the library. After the insert size was as expected, we used the quantitative polymerase chain reaction (Q-PCR) method to determine the effective concentration of the library. To further confirm the quality of the library, the PCR products were purified (AMPure XP system). An effective library concentration > 2 nM ensures library quality. After the library check was qualified, different libraries were pooled according to the requirements of effective concentration and target data volume, and then the genomic DNA of the two pools was submitted to sequencing using the Illumina HiSeq™ PE150 platform. The sequencing process generated 150 bp paired-end reads with an insert size of 350 bp.Two genomic DNA bulks were constructed for bulked segregant analysis sequencing (BSA-seq) based on observed phenotypic data (tocopherol content) of the target population. The two bulk samples for whole-genome resequencing were generated by pooling equal amounts of DNA from a total of 98 soybean germplasms (49 accessions each of high and low tocopherol content)  sampled The original image data file obtained from the high-throughput Illumina HighSeq sequencing was analyzed by the CASAVA Base Recognition  and, subsequently, converted into the sequence reads, also known as raw reads and stored in FASTQ (fq) file format. Reads obtained from the sequencing results, including raw reads that contained connectors or low-quality bases that may affect the subsequent assembly and analyses, were further processed by filtering for quality check. Thus, raw reads were processed by: (1) Removing read pairs containing connectors; (2) Reads that contained ≥ 10% of unidentified nucleotides (N); (3) Reads that contained low-quality (Q ≤ 5) bases that exceeded 50% of the length of the read; (4) Reads with > 10 nt aligned to the adapter, allowing ≤ 10% mismatches; (5) Putative PCR duplicates generated by PCR amplification in the library construction process .After removing the connectors and low-quality reads, the clean reads obtained were further submitted to quality check to obtain high-quality clean reads. The Burrows–Wheeler Alignment (BWA) algorithm (Version 0.7.10)  with theThe Unified Genotyper module of Genome Analysis Toolkit (GATK) software , versionHigh-quality SNPs and InDels in the bulks were selected for SNP/InDel-index analyses . The SNPA sliding window analysis approach was applied to the SNP- and InDel-index of the whole genome with a 2 Mb window size and 10 Kb step size as default. The average SNP/InDel-index of the SNPs/InDels located in the window was then calculated and used for the sliding window plot. The difference in the SNP/InDel-index of the two bulks was calculated to obtain Δ(SNP/InDel-index) and confidence intervals generated and plotted for all the genomic regions that showed variable read depths. The selected SNPs and InDels detected in the peak regions were annotated and screened for potential functional variants.https://sfgb.rmbreeding.cn/, accessed on 18 May 2022) was used for the genotypic data and/or genetic approaches.The SNP/InDel and Δ(SNP/InDel-index) plots were examined in order to identify causal regions. Using the sliding window analysis method, the average SNP/InDel-index and Δ(SNP/InDel-index) were calculated for each genomic interval by using a window size of 2 Mb and step product size of 10 Kb as default. The window graphs were generated and plotted against the genomic positions for the VE-High and VE-Low bulks. The Δ(SNP/InDel-index) of the polymorphic loci between the VE-High and VE-Low pools was then calculated. Only peak regions that were highly consistent across the SNPs and InDels plots were considered to contain candidate genes. Gene models earlier reported in Arabidopsis to be linked to tocopherol biosynthesis were used to predict putative soybean tocopherol candidate genes. The soybean tocopherol genes were subsequently mapped with the annotated candidate genes detected in the BSA-seq. Genes that were found within the genomic loci and matched with the sliding window plots where the peak regions exceeded the threshold value were considered candidate genes. Additionally, genes with non-synonymous mutations were examined for their haplotype structure in our germplasm panel. This consisted of 1525 soybean accessions evaluated in three different locations, including Beijing (2017 and 2018), Anhui (2017), and Hainan (2017 and 2018). Haplotypes were prepared using R statistical software version 4.0.2 . The Soybean Functional Genomics and Breeding database (SoyFGB v2.0) (p < 0.05) enriched terms using the PlantRegMap website tool .To determine the main biological functions of genes , a deep annotation of databases was performed. Based on the 109 predicted candidate genes, the GO analysis was conducted to identify significantly  was considered the most promising candidate gene related to tocopherol content in soybean. An analysis of haplotype variation also confirmed that Glyma.05G243400 exhibited highly significant variations in terms of tocopherol content across the experimental locations. Therefore, the results imply the gene Glyma.05G243400 is the most promising candidate for tocopherol content, which is a novel gene and will serve as a useful gene resource for functional characterization and validation by genome editing. Our present findings hold prospects for molecular marker identification and marker-assisted selection of soybean genetic resources endowed with improved tocopherol content.Increased tocopherol composition in soybean has immense potential to enhance the shelf life of seeds, seed vigor, and seed oil quality. Therefore, understanding the genetic mechanisms conditioning tocopherol expression will contribute immensely toward the molecular breeding of soybean with enhanced tocopherol composition in order to fully exploit its diverse benefits. This study was performed to investigate the genomic loci and candidate genes regulating tocopherol content in soybean through a BSA-seq approach. Based on GO annotation analysis, a total of five and four genes were found with their biological functions associated with response to lipid and response to abscisic acid, respectively, which were considered promising candidates associated with tocopherol content in soybean. Following the ANNOVAR analysis, genes containing mutations that occurred in the exonic region, including 10 non-synonymous, 1 stop-gain, and 2 frameshift variants, were preferentially selected as candidate genes related to tocopherol content. Following an SNP/InDel index analysis method, one associated genomic region (from 41.8 to 41.9 Mb) directly corresponding with the sliding window plots where the peak regions exceeded the threshold value was identified on chromosome 5, which contained six putative genes. Among the genes,


Fungi produce a wide range of specialized metabolites (SMs) involved in biotic interactions. Pathways for the production of SMs are often encoded in clusters of tightly arranged genes identified as biosynthetic gene clusters. Such gene clusters can undergo horizontal gene transfers between species and rapid evolutionary change within species. The acquisition, rearrangement, and deletion of gene clusters can generate significant metabolome diversity. However, the genetic basis underlying variation in SM production remains poorly understood.Zymoseptoria tritici. The pathogen causes major yield losses and shows variation in gene clusters. We performed untargeted ultra-high performance liquid chromatography-high resolution mass spectrometry to profile the metabolite diversity among 102 isolates of the same species. We found substantial variation in the abundance of the detected metabolites among isolates. Integrating whole-genome sequencing data, we performed metabolite genome-wide association mapping to identify loci underlying variation in metabolite production . We found that significantly associated SNPs reside mostly in coding and gene regulatory regions. Associated genes encode mainly transport and catalytic activities. The metabolite-GWAS identified also a polymorphism in the 3′UTR region of a virulence gene related to metabolite production and showing expression variation.Here, we analyzed the metabolite production of a large population of the fungal pathogen of wheat, Taken together, our study provides a significant resource to unravel polymorphism underlying metabolome diversity within a species. Integrating metabolome screens should be feasible for a range of different plant pathogens and help prioritize molecular studies.The online version contains supplementary material available at 10.1186/s12915-022-01422-z. Ralstonia solanacearum, is conserved in distant fungal pathogens [Fusarium graminearum, the BGC encoding the pathway for the production of the mycotoxin trichothecene is upregulated during colonization of wheat [Fungi are capable of synthesizing a wide range of compounds including amino acids, pigments, antibiotics, and toxins –3. Such athogens . Besidesathogens . In the of wheat  and esseof wheat , 10. Theof wheat , 11. BGCof wheat .Fusarium fungi [Aspergillus fungi, BGCs contribute to shared virulence profiles based on gliotoxin and fumitremorgin production and species-specific virulence, e.g., due to fumagillin [Arabidopsis thaliana [Large-scale fungal genome analyses have revolutionized the discovery of genes underlying the specialized metabolism and rapidly evolving BGCs transferred among species , 13, 14.um fungi . The evoum fungi , 17. BGCum fungi . Furtherum fungi . The facum fungi –22. Horimagillin . Geneticthaliana . Recent thaliana  and contthaliana . Metabolthaliana , 28. TheZymoseptoria tritici is a highly polymorphic fungal pathogen of wheat and shows a marked variability in BGCs among members of the species [Z. tritici remains poorly understood. A metabolome analysis of the wheat infection process showed that lipid metabolism is the initial energy source during leaf colonization prior to the induction of host cell death [Z. tritici. The locus underlying variation in melanin production was first identified using quantitative trait mapping and then confirmed to be a polyketide synthase gene cluster [The ascomycete  species –31. The  species , 33. Pop species . Comparill death . The patll death , 36. Prell death . Melanin cluster , 38. Amo cluster . PopulatZ. tritici has been used successfully to identify the genetic basis underlying virulence on different wheat cultivars, resistance to fungicides, and temperature adaptation [Here, we take advantage of genome-wide association (GWA) mapping using the production of individual metabolites under standardized conditions as trait values. GWA mapping in aptation –43. We fZ. tritici isolates collected from six continents and 13 different countries . We analyzed whole-genome sequences of 102 strains isolated from a single wheat field during a single growing season . The iso., sugars, amino acids) and hydrophobic  molecules based on retention times, we retained 2633 metabolite marker peaks . The analyzed metabolites were extracted from blastospores after culture washing. After excluding highly hydrophilic  of untargeted metabolites showed at least one significant SNP association  and accessory chromosomes (n = 8). Accessory chromosomes 14 and 18 showed high proportions of associated SNPs  [p < 0.00001). This suggests that such variants tend to be linked to regulatory variation. For the remainder, we focused only on the most significantly associated SNPs for each metabolite marker falling within 5 kb of a gene .We analyzed the closest gene to the most significantly associated SNP for each metabolite marker Fig. B. Genome1500 bp) . The abuWe performed gene ontology (GO) term enrichment analyses of the protein functions encoded by genes nearest to the most significantly associated SNP , we focused on the closest gene to the most significantly associated SNP of each trait  to prioritize the most robust metabolic pathway associations. We identified 124 genes encoding functionally predicted proteins including seven proteins characterized as putative effectors  were of unknown category. Next, we focused on BGC candidate gene clusters due to their well-established role in fungal metabolism [Due to the large number of metabolic traits analyzed n = 288, we fo. The gene cluster is 35kb in size and predicted to carry 15 genes including two biosynthetic core genes and a regulatory gene  and geographically distant isolates from Yemen (Yeq92) and Tunisia  compared to genome-wide expectations   showed a trend of higher pycnidia production of the isolates carrying the alternative genotype associated with higher metabolite production  with 90% confidence as a cysteine derivative. The PubChem database classified Zt248 as an N-Acetyl-S-(2-ethylbutyl)-L-cysteine. The metabolite Zt231 (C11H22N2O3) produced fragments at m/z 86.097 typical for leucine and isoleucine moieties. A natural product database search retrieved N-Valyl-Leucine as the most likely compound for Zt231. Our analysis using MS/MS showed three peaks at 2.15, 2.24, and 2.37, corresponding to the D-l, L-D, and L-L isoforms  playing a role in shaping within species metabolome diversity. We identified genetic polymorphisms close to genes encoding a broad range of functions with an enrichment of transporter and catalytic functions. Such transporters include major facilitator superfamily (MFS) transporters known to modulate fungicide and stress tolerance [Variation in metabolite abundance among individuals can be used to identify candidate genes underlying the regulation of metabolite production. We found a strong enrichment of intergenic regions contributing to metabolite production suggesting olerance –53. MFS olerance –56.. Standing variation for the production of SM elevates the evolutionary potential of Z. tritici, because populations could respond rapidly to selection for or against the production of specific metabolites. Intra-species variation in BGCs and SM production have been observed in a range of fungi including the rice blast pathogen Pyricularia oryzae, where a gain of virulence was linked to the duplication of a hybrid PKS-NRPS cluster [Aspergillus species show also significant intra- and interspecific variation in BGCs and the potential to produce specific SM with consequences for niche adaptation [The studied species harbors a high degree of polymorphism in BGCs with likely consequences for the production of specialized metabolites. The mGWAS captured 41 BGC-related associations affecting approximately half of all known BGCs of the species cluster . Aspergiaptation .Z. tritici BGCs show such an association as well [We investigated in detail two associations linking a SNP segregating in a BGC with clear metabolite variation. The first SNP was found in the candidate effector gene Zt09_00502, which is a component of the NRPS gene cluster 18 upregulated during the initial phase of infection. Pathogens secrete effectors to manipulate the host immune responses and physiology to its advantage . The pro as well . The conP. oryzae resulted in reduced lesion sizes on rice [A. confluens [The second investigated metabolite association was within the UTR region of the gene Zt09_13_00231 encoding an F-box protein, which generally binds and transports proteins to be discarded by the cell . The enc on rice . The dip on rice . Chemicaonfluens . ConvergOur study highlights the power of association mapping to identify candidate loci underlying metabolite diversity and associated with the host infection process. Previously, mGWAS was limited to plant models, but our findings illustrate how applications to plant pathogenic fungi can efficiently produce candidate lists. A key requirement is access to large, experimentally tractable isolate collections. High degrees of recombination and rapid decay of linkage disequilibrium are further requirements for the successful application of association mapping approaches . EstabliZ. tritici isolates from the Field Phenotyping Platform (FIP) site of the ETH Zürich, Switzerland  [n = 48) was established in May when wheat plants were in growth stage (GS) 41. The second (n = 7) and third collections (n = 47) were established when the plants were in GS 75 and GS 85, respectively. After sampling, spores of each isolate were stored in either 50% glycerol or anhydrous silica gel at −80 °C. Additional information regarding the sampling scheme and genetic diversity of the collection is described in [We collected .682° E) . We anal.682° E) . We analIsolates were revived from glycerol stock by adding 50 μl fungal stock solution to a 50-ml conical flask containing 35 ml liquid YSB (yeast-sucrose broth) medium. The inoculated flasks were incubated in the dark at 18°C and 160 rpm on a shaker-incubator. After 8 days of incubation, the cultures were passed through four layers of meshed cheesecloth and washed thrice with sterile milli-Q water to remove media traces. Spores were then lyophilized and metabolites extracted by resuspending the spores (~80 mg) in 1 ml of HPLC-grade methanol. The extract was centrifuged at 15,000 rpm for 5 min to pellet down debris before retrieving the supernatant. The last step was repeated until a clear supernatant was recovered.https://fungi.ensembl.org/Zymoseptoria_tritici/Info/Index) and the mitochondrial genome (European Nucleotide Archive accession EU090238.1) using Bowtie2 v. 2.4.1 [Approximately 100 mg of lyophilized spores was used to extract high-quality genomic DNA with the Qiagen DNeasy Plant Mini Kit according to the manufacturer’s protocol. We sequenced paired-end reads of 100 bp each with an insert size of ~550 bp on the Illumina HiSeq 4000 platform. Raw reads are available on the NCBI Sequence Read Archive under the BioProject PRJNA596434 , 68. Illv. 2.4.1 . Multi-sv. 2.4.1 . We retav. 2.4.1 . Additiov. 2.4.1 .p distances [We reduce the SNP dataset using vcftools –thin  with a 1istances . We perfistances . The croistances . All filistances .We analyzed gene models predicted for the reference-quality genomes assembled for the pangenome of the species with models trained using RNA-seq datasets . ProteinMetabolome analyses were carried out by UHPLC-HRMS using an Acquity UPLC coupled to a Synapt G2 QTOF mass spectrometer (Waters). An Acquity UPLC HSS T3 column  was employed at a flow rate of 500 μl/min and maintained at a temperature of 40°C. The following gradient with 0.05% formic acid in water as mobile phase A and 0.05% formic acid in acetonitrile as mobile phase B was applied: 0–100 % B in 10 min, holding at 100% B for 2.0 min, re-equilibration at 0% B for 3.0 min. The injection volume was 2.5 μl. The QTOF was operated in electrospray negative mode using data-independent acquisition (DIA) alternating between two acquisition functions, one at low and another at high fragmentation energies. Mass spectrometric parameters were as follows: mass range 50–1200 Da, scan time 0.2 s, source temperature 120°C, capillary voltage −2.5 kV, cone voltage −25V, desolvation gas flow and temperature 900 L/h and 400°C respectively, cone gas flow 20 L/h, collision energy 4 eV (low energy acquisition function) or 15–50 eV (high energy acquisition function). A 500 ng/ml solution of the synthetic peptide leucine-enkephaline in water:acetonitrile:formic acid (50:50:0.1) was infused constantly into the mass spectrometer as internal reference to ensure accurate mass measurements (<2ppm). Data was recorded by Masslynx v.4.1. Marker detection was performed using Markerlynx XS (Waters) with the following parameters: initial and final retention time 1.5 and 10.0 min, mass range 85–1200 Da, mass window 0.02 Da, retention time window 0.08 min, intensity threshold 500 counts, automatic peak width and peak-to-peak baseline noise calculation, deisotoping applied. Data was mean-centered and Pareto scaled before applying multivariate analysis.p-values based on the Bonferroni threshold at alpha = 0.05. Per metabolite, we selected the closest gene to the most significant associated SNP using the “closest” command in bedtools v. 2.29.0 [We performed GWAS based on mixed linear models accounting for degrees of kinship among genotypes (MLM+K). The kinship matrix was computed using the scaled identity-by-state (IBS) algorithm implemented in TASSEL v. 20201114 . We incl. 2.29.0 . Linkage. 2.29.0  and visu. 2.29.0 . GO term. 2.29.0  and plot. 2.29.0 . To inven = 102) in a Vogel Minimal N Medium [Z. tritici reference genome (IPO323). Mapped transcripts were quantified using HTSeq-count [To investigate loci during the fungal life cycle, we used public RNA-seq dataset (NCBI Short Read Archive accession number SRP077418) of four isolates included in the pangenome dataset . The isolates were inoculated on wheat plants to monitor transcription levels during the infection process at four time points  . For traN Medium  where amN Medium . FiltereN Medium  to the Zeq-count . Read coeq-count .Additional file 1: Table S1.Zymoseptoria tritici field collection information including collection time point (C1-3), cultivar of origin, field plot. Table S2. Relative intensities of 2633 metabolite markers. The isolate name corresponding to sample identifiers are detailed in Table S1. Table S3. List of metabolite-GWAS top significant SNPs and distance to closest gene. Table S4. Gene function enrichment based on m-GWAS closest genes to top significant SNPs.Additional file 2: Figure S1. A) The first two principal components (PC) from a PC analysis of genome-wide SNPs after removal of outliers (n=7). Isolates are color coded by the collection time point and wheat cultivar. B) SplitsTree phylogenetic network constructed from genome-wide single nucleotide polymorphism (SNP) data. Figure S2. Discriminant analysis of principal components (DAPC) results from the genome-wide SNP dataset. Cumulated variance explained by the eigenvalues of the PCs and scatter plot of the Bayesian Information Criterion (BIC) values. The lowest BIC value indicates the most parsimonious number of clusters. Figure S3. A) The first two principal components (PC) from a PC analysis of SNPs closest to biosynthetic gene clusters BGC. Isolates are color coded by the collection time point and wheat cultivar. B) Down sampling analysis to identify the proportion of 2633 metabolite markers detected in mapping population. Figure S4. Percentage leaf area covered by lesions and pycnidia during wheat infection for subset of Z. tritici strains included in the metabolome-GWAS analysis (n = 76). The isolates are grouped by their genotype at significant metabolome GWAS SNPs. Figure S5. Evolutionary history of the putative effector gene Zt09_00502. A) Alignment of the 3’UTR region of the gene. The box refers to the haplotypes found in the single Swiss field population. B) Phylogenetic tree of the 3’UTR region and (C) of the gene sequence. Names in bold black, blue and grey refer to the reference genomes of the species (IPO), isolates included in the metabolite GWAS and sister species, respectively. The phylogenetic tree was inferred by using maximum likelihood and the Tamura-Nei model. D) Pairwise linkage disequilibrium (LD) among all pairs of SNPs within the gene cluster. The red dotted line marks the r2=0.2. The blue dotted line represents distance where the LD drops to r2<0.2. Figure S6. Classification of protein family domains encoded by the gene Zt09_13_00231.Figure S7. MS scans of metabolite elution (A) Zt248 and (B) Zt231, eluting at 3.53 and 2.15 minutes, respectively. The neighboring peaks at the m/z range eluting at different retention times likely represent distinct structural isomers of the same compound.


Dissociation is a psychopathological condition with a range of alterations or changes in the normally integrated mental functions such as identity, consciousness, or memory and can manifest in various types such as depersonalization, trance states, derealisation, dissociative amnesia, and dissociative identity disorder . From an etiological perspective, past experience of trauma plays a major role as a precipitating factor in dissociation, wherein dissociation is conceptualized as a reaction to trauma as a way to distance oneself from the traumatic situation and events related to it . Initially understood as a coping mechanism, the persistent manifestation of dissociation hinders the overall psychological functioning and interferes with the daily activities of the individual. Therefore, the focus of the various treatment modalities of dissociative disorders is mostly focused on enhancing the coping skills of the patient. The current case study demonstrates the manifestation of dissociation in a 16 years old adolescent with a history of trauma. Furthermore, it documents the efficacy of Trauma-Focused Cognitive Statistical Manual of Mental . Dissociation is a psychopathological condition with a range of alterations or changes in the normally integrated mental functions such as identity, consciousness, or memory and can manifest in various types such as depersonalization, trance states, derealisation, dissociative amnesia, and dissociative identity disorder . The latDissociative disorders are rare in children, but conversion disorders account for the majority of them, especially in developing countries . StudiesFrom an etiological perspective, past experience of trauma plays a major role as a precipitating factor in dissociation, wherein dissociation is conceptualized as a reaction to trauma as a way to distance oneself from the traumatic situation and events related to it . InitialThe treatment addresses distorted or upsetting beliefs and attributions related to the traumas and provide a supportive environment in which children are encouraged to talk about their traumatic experiences and learn skills to help them cope with ordinary life stressors. The current case study demonstrates the manifestation of dissociation in a 16 years adolescent with a history of trauma. Furthermore, it documents the efficacy of Trauma-Focused Cognitive Behaviour Therapy (TF-CBT) in dissociation .Index patient, a 16 years old adolescent boy, belonging to Hindu nuclear family from a lower socioeconomic strata, hailing from rural Bihar was admitted in the inpatient Department of Central Institute of Psychiatry, Ranchi. The adolescent was maintaining well and would go to school regularly until about four months ago when, one day his cousin brother who was around one year older than him passed away by drowning in a river nearby his village, where he had gone to take bath. The adolescent was extremely shocked and traumatized when he came to know about this incident. He shared a close emotional bond with his cousin and would spend most of his time at school as well as home with his cousin brother. According to the adolescent, his deceased brother was like a father figure for him, who would always standby him in his good and bad times and would always save him from bullies in school.The dead body of deceased brother was found two days later and the patient had a glimpse of the body, which left him completely shattered. The family members further observed a change in his behaviour; he would remain upset, stay alone, and would not talk to anybody in the following days.The adolescent reportedly would have difficulty falling sleep and would stay awake and keep thinking about his deceased brother. When he would fall asleep, he would have nightmares causing him to wake up in a fearful state.The adolescent resumed his schooling after a week and took the bus to his school. However, the family members received complaints about his behaviour as he would stay alone, not talk to anybody, and would not respond to his teachers either. Within few days, the adolescent experienced the first episode of dissociative amnesia, when one day he left his class without informing anyone and reached his aunt's place nearby his school. He would not speak to his aunt for hours. His parents were called and the patient was taken home. Later, upon inquiry, he could not recall anything about this journey to his aunt's place.The adolescent experienced the second episode of dissociation, two days after this incident, the adolescent was studying inside his room, when his mother called him for some work, he was not present in the room and was not present around the home either. Hours after this, the family members received a call from a person who informed them about the adolescent. When the family members found him, he again reported being unable to recall the incident and further complained of dizziness and headache. He would also refuse to go to school and state that he cannot concentrate on his studies and that the image of deceased brother comes into his mind.The adolescent had similar episodes 2-3 times in the week, whereby he would walk alone for distance of 1-2 kms and then suddenly ask people nearby about his own whereabouts. In one such incident, it was reported that the adolescent was walking with the mother to a market nearby. The mother noticed that after sometime, the adolescent walked by himself and did not respond to the mother and would not speak to anybody. His mother kept following him for 2-3 kms and suddenly the adolescent stopped and started asking the mother how he reached here or what are they doing here.The family members were concerned about the deteriorating state of the patient. Eventually, they took him to a faith healer, who saw him and told them that he is being targeted by some evil spirit and asked them to perform rituals and did some religious spells. This further triggered a sense of fear in the adolescent, as he would say he is scared that something might happen to him.In the following days, condition worsened as he would run away from home almost 3-4 times in a day without any recall. He also started having episodes where he would fall and lie down on the ground without any response and have jerky movements characterized by head shaking without any symptom of up rolling of eyes or tongue biting with his eyes tightly closed, that would last for a minute and occur every day. According to the mother, in one such incident, the adolescent had gone to take a bath by himself in the bathroom. After 3-4 minutes, the mother suddenly heard the adolescent screamed “mummy.” The mother tried to open the door but it was latched from inside. When, the adolescent's younger brother tried to peep in through the window, it was seen that the adolescent was lying still on the floor of the bathroom. They got inside and tried to wake him up, by calling him out loudly and by sprinkling water, but the adolescent did not respond in any manner and remained still. After 4-5 minutes, he got up and could recall anything about the incident. He again started asking the mother about the incident.Eventually, family members brought him to outpatient department (OPD) of Central Institute of Psychiatry (CIP), and he was admitted eventually in the inpatient ward. His persistent and pervasive mood was irritable. His role functioning was impaired and personal care was intact.Index child was kempt, tidy, and in touch with surroundings. He was maintaining eye contact, rapport was established; speech was soft, relevant, coherent, and goal directed with normal reaction time and decreased productivity. He had adequate level of attention and concentration. Cognitive functions were intact. His affect was dysphoric, communicable, and appropriate.Hopelessness, pessimistic view towards future was present in thought content, and no abnormality was detected in perception. His social judgment was impaired with grade II insight. The case was diagnosed as mixed-dissociative disorder as per the guidelines provided in the International Classification of Disease 10 (ICD 10).The child had normal findings on Computed Tomography Scan (CT-Scan) and Electroencephalogram (EEG). Therefore, the possibility of seizures was ruled out.The Full-Scale IQ derived from the combination of all 10 subtest scores is considered to be the most representative estimate of global intellectual functioning. His Full-Scale IQ score is 89 which suggests a dull normal level of global intellectual functioning.It also known as Brief Dissociative Experiences Scale (DES-B)—Modified is an 8-item measure that assesses the severity of dissociative experiences in children ages 11–17. Each item asks the child receiving care to rate the severity of his or her dissociative experiences during the past 7 days. Each item on the measure is rated on a 5-point scale . The raw total score can range from 0 to 32, which is then converted into average total score by using the formulaIt allows the clinician to think of the severity of the child's brief dissociative experiences in terms of none (0), mild (1), moderate (2), severe (3), or extreme (4). The score and impression of the index child are as follows: The baseline raw score was 16 and the average score was 2, which indicates moderate level of dissociation symptoms.(1)To reduce anxiety and distress related to traumaIncreasing child's awareness of distorted appraisal of unwanted thoughtsTo modify specific cognitive processes and behaviours that is maintaining the dissociative symptomsTo ward off negative emotionsTo change dysfunctional parentingTarget of therapy(2)Treatment module: Trauma-Focused Cognitive Behaviour Therapy for Adolescents(3)Psychoeducation (to build insight about the illness)Relaxation (to reduce anxiety and distress related to trauma)Thought-emotion-action matter (to modify his cognitive process and maintaining the dissociative symptoms)Chill Out Kit (to ward off negative emotions)Parent counseling Techniques of Cognitive Behaviour TherapyDissociation has been found to be linked with the experience of trauma . Some auThe informed consent was sought from the child as well as the parents regarding the adolescent's participation in the therapy as well as its documentation after the successful completion of nine sessions. Ethical guidelines of psychotherapy and research were followed during intervention as well as documentation of this case.The adolescent was prescribed with standardized dosage of antidepressant and antipsychotic, i.e., fluoxetine and olanzapine in the course of treatment.The intervention was given by the author, who is an RCI Licensed Clinical Psychologist. The Trauma-Focused Cognitive Behaviour Therapy was delivered to the indexed patient in 9 sessions with duration of 1 hour each for a period of nine weeks in the inpatient ward. The initial session was mainly focused on building of therapeutic alliance with the adolescent and his mother who was the main caregiver during the adolescent's stay at the inpatient ward. In the first week, the clarification of history of presenting complaints was done with the adolescent's mother. The baseline assessment indicated that he has moderate level of distress and dissociative symptoms. The psychological causes of dissociation and role of TF-CBT in treatment was explained in details.The second session was focused on teaching and practicing of Jacobson's progressive muscle relaxation training, which is one of the key techniques of TF-CBT commonly introduced in the initial sessions. The adolescent was also given homework to practice relaxation whenever he feels anxious and tensed in and around the inpatient ward. In the following week, the adolescent's attempts at relaxation practice were reviewed and he had practiced and reported a temporary relief in his body and mind with each round of JPMRT. The adolescent's attempts at relaxation were admired and he was further encouraged to practice it on a daily basis.Once the rapport was adequately established and relaxation was properly taught to the adolescent, in the next session, his hobbies and likes were assessed. The adolescent was passionate about science projects and had received prize for his science project assignments at school, he liked socializing with other children, and drawing was also listed as one of his hobbies. An activity schedule was prepared for the adolescent collaboratively, which listed science project assignments, drawing, and interaction with other children in the inpatient ward along with the academic tasks. The adolescent was provide with the necessary materials for his drawing and science projects, including, sketch pens, drawing books, and science books from the ward stock. He was explained in details about the activity schedule and encouraged to follow it on a routine basis. In the fourth session, the concept of emotion, emotional identification, and emotional regulation was explained to the child with the help of emoticon stickers. He was taught to identify various emotions and rate his own emotions on the “emotional thermometer.” It was discovered that the major emotions experienced by the adolescent were anxiety and sadness, which were mostly related to his recent loss of his brother and uncertainty of his present condition.In the next session, the concept of “Chill Out Kit” was explained to the adolescent. The therapist and the adolescent collaboratively included various activities including, drawing, talking to other children, practicing relaxation, and engaging in science projects into the child survival kit. He was taught about ways in which he can use these activities from the survival kit to ward off his anxiety or sadness. He was encouraged to use his survival kit as frequently as he can in the treatment ward. His attempts at using this kit were routinely monitored by the therapist in the ward. The sixth session focused on the thought aspect of TF-CBT, i.e., the Thought-Action-Matter. The meaning of thoughts and its relation with emotions and action were explained to the child with simple examples. He was explained if our thoughts are positive then our feelings and actions are also positive. But if our thoughts are negative, then our feelings and actions are also negative. The therapist and the adolescent worked on some activities based on Thought-Action-Matter aimed at helping the adolescent understand the thought-emotion link more clearly. The testing of thought for validity and utility was done in the next session collaboratively. The dominant negative thoughts including those related to “loss of his cousin” were put to test to assess the validity and utility of these thoughts. The adolescent was taught to restructure the thoughts by drawing from evidences “for and against” the thoughts. He was given homework based on the Thought-Action-Matter to deepen his understanding, to restructure his negative thoughts, and to develop a balanced, realistic, and adaptive thought.In the following session, the mother was psychoeducated to develop a right attitude towards the adolescent by imparting correct information regarding nature, causes and management of dissociation with examples. An authoritarian parenting style was found from the mother's side. She was explained about the harmful effects of authoritarian parenting including shouting, critical comments, or hitting on the mental health of the adolescent. The mother was explained about the need to adopt an authoritative parenting style focused on placing reasonable demands on the adolescent by providing him with love and care without setting unrealistic expectations or punishment especially in academics.In the ninth session, the activity on “survival kit” and “Thought-Action-Matter” was reviewed by the therapist and its importance was summarized to the adolescent. He was informed about the termination of the therapy and was given the homework to write about his own story of success, narrating about the various skills that he has learned in therapy. The adolescent maintained a record of his activities in survival kit and Thought-Action-Matter. It was observed that the adolescent was actively socializing and participating in the ward activities along with other children. The feedback was taken from the adolescent and the mother. Significant improvements in dissociative episodes were reported. The adolescent reported that he felt in control of his thoughts and that he was now aware of the activities and techniques that can be used to cope up and ward off distressing thoughts and emotions. The rating scale was readministered. The post intervention raw score was 2 and the average score was 0, which indicates no dissociative symptoms.In the present case, the dissociative symptoms were precipitated after the loss of adolescent's cousin brother, who was perceived as a father figure by him and was his primary support at home as well as school. The psychoanalytic theory postulates that the early loss of a parental figure can lead to psychopathological symptoms in children and also predispose them in adulthood to various psychiatric disorders . Early lThere are a number of treatment modalities available for trauma in adult population. However, these treatment options may not be as helpful for and adolescents as they have a lower awareness of emotions and struggle to express certain emotions. Given this, the Trauma-Focused Cognitive Behaviour Therapy for adolescents based on Cohen's model is simplified and applicable in adolescent population with a history of trauma. The intervention module includes parents or caregivers as well that plays a key role in management of psychopathology . The exiOn the other hand, the existing studies on interventions in dissociative disorders in younger children includes play therapy, hypnosis, storytelling, and other forms of art therapy that does not require an advanced level of capacity to process and evaluate and restructure thoughts –21.The existing literature on the efficacy of Trauma-Focused Cognitive Behaviour Therapy on dissociation is limited in both child as well as adolescent population. According to the author's knowledge, this is the first case study report that has demonstrated the clinical manifestation of mixed-dissociative disorder , and successful treatment adolescent. The short-term goals of the current intervention were to help to process painful memories of the loss, help him restructure his thoughts, and regulate his emotions. The long-term goal was to enhance the coping skills of the adolescent and prevent future episodes. The findings from the case study show that Trauma-Focused Cognitive Behaviour Therapy for adolescents as set out in the manual , 22 is eSince it was a single case intervention report, the findings of the study may not be generalizable to a larger population with dissociative disorders. However, it facilitates the reader's conclusion about its transferability in cases with similar manifestations of dissociation. Secondly, as a part of the treatment as usual procedure (TAU), the child was already prescribed and adhered to psychotropic medications. Therefore, the clinical improvements cannot be fully attributed to the nonpharmacological intervention, i.e., (TF-CBT) delivered in the present case. Finally, the case report is based on a prepost intervention with no follow-up observation of the case. Therefore, the long-term efficacy of the TF-CBT in the present case could not be stated.The future studies may focus on the efficacy of TF-CBT in adolescents in dissociative disorders with a larger sample size along with follow-up studies.


Mapping of quantitative trait loci (QTL) associated with molecular phenotypes is a powerful approach for identifying the genes and molecular mechanisms underlying human traits and diseases, though most studies have focused on individuals of European descent. While important progress has been made to study a greater diversity of human populations, many groups remain unstudied, particularly among indigenous populations within Africa. To better understand the genetics of gene regulation in East Africans, we perform expression and splicing QTL mapping in whole blood from a cohort of 162 diverse Africans from Ethiopia and Tanzania. We assess replication of these QTLs in cohorts of predominantly European ancestry and identify candidate genes under selection in human populations.We find the gene regulatory architecture of African and non-African populations is broadly shared, though there is a considerable amount of variation at individual loci across populations. Comparing our analyses to an equivalently sized cohort of European Americans, we find that QTL mapping in Africans improves the detection of expression QTLs and fine-mapping of causal variation. Integrating our QTL scans with signatures of natural selection, we find several genes related to immunity and metabolism that are highly differentiated between Africans and non-Africans, as well as a gene associated with pigmentation.Extending QTL mapping studies beyond European ancestry, particularly to diverse indigenous populations, is vital for a complete understanding of the genetic architecture of human traits and can reveal novel functional variation underlying human traits and disease.The online version contains supplementary material available at 10.1186/s13059-023-02874-4. Gene regulation is a principal mechanism by which genetic variation contributes to phenotypic variation, making its study essential for understanding human evolution and disease. The genomics era has underscored the importance of noncoding variation in human evolution and disease: ~ 90% of the genotype–phenotype associations identified by genome-wide association studies (GWAS) cannot be explained by coding variation , 2, and While GWAS and scans of selection can identify genomic regions of interest, they often lack the resolution to identify the specific genes underlying traits or targeted by selection. To bridge this gap, studies have aimed to identify genetic variation associated with fine-scale, molecular phenotypes, through quantitative trait locus (QTL) mapping . CombiniWhile there is an established and active field of study identifying novel GWAS associations and genetic variation contributing to gene expression differences across populations , 9–14, mIn this study, we probe the genetic architecture of gene regulation in whole blood from indigenous East Africans by performing expression QTL (eQTL) and splicing QTL (sQTL) mapping in a cohort of 162 individuals, representing nine ethnic groups, from Ethiopia and Tanzania. We measure the degree to which African architecture is shared with that of non-Africans, test whether Africans harbor functional variation absent from existing cohorts, and investigate the demographic and genetic forces that may contribute to variation in gene regulatory architecture. We test whether fine-mapping of QTL signals is improved in Africans relative to an equivalently sized cohort of European Americans, and highlight individual genes with improved fine-mapping in Africans. Finally, we measure the effect of selective forces on shaping gene regulatory architecture and identify candidate genes under selection.The cohort for this study consists of 162 Ethiopian and Tanzanian individuals belonging to nine ethnically and culturally diverse sub-Saharan groups previously unsampled in gene expression studies, including the Cushitic speaking Agaw and Weyto, the Semitic speaking Argoba and Amhara, the Omotic speaking Dizi, the Nilo-Saharan speaking Mursi, the Chabu who speak an unclassified language similar to Nilo-Saharan, and the Khoesan speaking Hadza and Sandawe  dataset  and a daDMIXTURE  also indDMIXTURE , represecis for expressed protein-coding and long-noncoding RNA genes; collectively, we refer to eQTLs and sQTLs as transcriptomic QTLs (tQTLs). We first correct our phenotypes (expression and splicing) for a number of covariates, including age, sex, delivery date, hidden covariates inferred by PEER [CIBERSORT [GEMMA [To assess the contribution of genetic variation to transcriptomic trait variation, we performed genome-wide QTL mapping for expression (eQTL) and splicing (sQTL) transcriptomic traits in  by PEER , and celIBERSORT . Cell-tyIBERSORT . To accoT [GEMMA . Testingp = 8.2 × 10−37 Fisher’s exact test) and slightly less likely to be associated with increased junction inclusion , suggesting that regulatory mechanisms altering chromatin accessibility play a greater role in regulation of gene expression than splicing. When we restrict to variants with a greater than 10% probability of being causal (Methods), we find a further enrichment in functional categories, particularly for caQTLs among eQTLs and splice regions among sQTLs, indicating we are capturing true causal variation  and splicing (sSNPs) show a characteristic enrichment near the transcription start site or intron boundary of their target gene, respectively   v8, which is comprised of 85% European Americans . An advadatasets . In addientclass1pt{minima1, we also investigate the degree to which individual loci show evidence of shared causal variation. Estimating credible sets for all eGenes and sIntrons in GTEx v8 as described above, we find that 715/1262 (57%) of eGene credible sets and 619/852 (73%) of sIntron credible sets in Africans overlap with credible sets in GTEx v8. While the majority of tQTL credible sets overlap, the many non-overlapping sets suggest many tQTL signals identified in Africans may be driven by independent causal variants. To further evaluate this independence, we remapped tQTLs in Africans, conditioning on sets of independent tQTLs identified in GTEx by forward regression [While tQTLs as a whole show strong replication using πgression . In casep > 0.01), we find that non-replicating tSNPs have consistently lower MAF in GTEx when compared with replicating tSNPs , suggesting we are not detecting an excess of false positives. Further restricting to those independent tQTLs identified above, we investigate whether MAF and LD differences can account for our findings. For eight genes, INPP5K, TMEM140, ACSM3, CNTNAP3, PPP1R14C, PDZK1TP1, GPR56, and TRAM2, the top eSNP in Africans is untested in GTEx and has a MAF < 0.01 (the threshold used by GTEx) in 1kGP EUR populations. The top eSNP for these eight genes are also non-significant or absent from the FIVEx browser [ADAM8, ICAM2, LINC00694, and MAPK1, are absent in GTEx, absent or non-significant in the FIVEx browser, and have a EUR MAF ≤ 0.01. Overall, however, we find that frequency differences between Africans and EUR do not differ significantly between shared and independent eQTLs  test, Methods), while we do find a significant, though slight, enrichment for larger frequency differences among independent sQTLs . To investigate the impact of LD variation on tQTL replication, we estimate r2 between tQTL lead SNPs and SNPs within 100 kb of lead SNPs in 1kGP CEU and YRI populations. We find that correlations between CEU and YRI r2 values do not differ significantly between shared and independent tQTLs . Finally, comparing effect size estimates between the African cohort and GTEx at top tSNPs, we find a significantly lower correlation of independent tQTLs when compared with shared signals , which may reflect true effect size variation, GxE effects [The source of replication differences between our cohort and GTEx may be due to several factors, including MAF differences, false positives, differences in LD between cohorts, differences in expression, and/or differences in effect size. Investigating those African tSNPs that fail to replicate in GTEx , sound (FDR = 1.60 × 10−5), mechanical stimulus (FDR = 5.60 × 10−5), and chemical stimulus (FDR = 5.22 × 10−4). Similarly, 6728 out of 18,168 tested for eQTLs in GTEx were not tested in Africans and are enriched for several biological processes related to immunity, including “complement activation, classical pathway” (FDR = 1.78 × 10−22), “humoral immune response mediated by circulating immunoglobulin” (FDR = 7.32 × 10−18), and “B cell mediated immunity” (FDR = 2.02 × 10−2). This observation suggests that disease status, sample collection, and response to environmental factors, in addition to genetics, may account in part for incongruent findings between eQTL cohorts.Finally, we investigate whether expression differences may affect replication between cohorts. Of the 1330 eGenes identified in Africans, the expression of 98 in GTEx v8 whole blood is too low to be tested for eQTLs. These 98 genes are significantly enriched in two KEGG pathways, “Hypertrophic cardiomyopathy” (FDR = 0.032) and “Dilated cardiomyopathy” (FDR = 0.038). Investigating what may be driving broader expression differences for testable genes, we identify those genes measured in Africans that fail to reach expression thresholds for testing in GTEx whole blood and vice versa. Altogether, 951 out of 12,377 genes measured in both cohorts and tested for eQTLs in Africans were not tested in GTEx. These genes are enriched for a number of biological processes related to sensory perception, including perception of smell  individuals from GTEx v8 using FastQTL , with seanalyses . Testinganalyses ; eQTLs tp = 2.06 × 10−11 binomial test), with a median credible set size of 25 in Africans vs 58 in EAs, and 23 genes fine-mapped to a single variant in Africans vs. 13 in EAs, demonstrating that using ethnically diverse populations facilitates fine-mapping, as has been shown previously [We next investigate the relative ability to fine-map eQTLs between our African cohort and the 162 EA individuals from GTEx v8. Considering eGenes that are FDR-significant in either cohort (Methods), we perform fine-mapping in both our African cohort and the 162 EAs using the approach described above. Overall, most genes do not fine-map well at this modest sample size, with 57% of genes having a credible set larger than 50 in both cohorts Fig. A. Excludeviously . One posTHRA and NR1B1, which is FDR-significant in GTEx whole blood but is not the lead eSNP. SNP rs883871 is a strong chromatin QTL in lymphoblastoid cell lines (LCLs) [ETS1 itself have been previously associated with multiple sclerosis [We further compare our credible sets in African eQTLs to credible sets estimated in the full GTEx dataset. As expected, the majority of eGenes have smaller credible sets in GTEx due to the considerably larger sample size (670 vs 162), though we do identify several examples of greatly reduced credible sets in the African cohort. For 18 eGenes and 32 sGenes, we are able to fine-map the QTL signals to a single variant in Africans and find that these variants overlap a lead GWAS association for 10 eGenes and 3 sGenes (supplement). We highlight rs883871  , overlaps (LCLs) , is preds (LCLs) ; variantclerosis .FST between our broader African dataset and the 1kGP European (EUR) individuals, with the expectation that selection for expression-altering alleles will lead to increased differentiation at these loci. To assess whether tQTLs are enriched for evidence of positive selection, we identify the highest FST value for all SNPs in high LD (r2 > 0.8) with the top eQTL or sQTL and compare these values with null SNPs matched on MAF and the number of SNPs in LD (Methods). Overall, we do not find an enrichment of high FST among eQTLs or sQTLs, either when combining all populations or testing populations individually, suggesting that selection has not driven significant frequency differentiation at the majority of tQTLs . Considering as candidates loci with a score within the 99th percentile threshold of all SNP FST values, and greater than 99% of background values, we identify 23 eGenes and 20 sGenes with evidence of selection (supplement). The most differentiated eGene is TTC26 (weighted FST = 0.59); a mutation in this gene has been associated with abnormal cilia in model organisms and biliary ciliopathy in human liver [ARPC1B (weighted FST = 0.59), deficiency of which can result in severe immunodeficiency [PF4V1, FST = 0.50), IL8 (FST = 0.49), a major inductor of immune cell chemotaxis and activation [CCR1 (FST = 0.43), a chemokine receptor. Among the most differentiated sGenes, we find several related to immunity and metabolism, including NADSYN1 (weighted FST = 0.50), a gene associated with vitamin D concentration [BTN3A3 (weighted FST = 0.50), a butyrophilin gene implicated in activation of T cells [GANC (weighted FST = 0.43), a member of the glycosyl hydrolase family 31, which play a key role in glycogen metabolism [We next investigate evidence of selection at individual loci. To account for the fact that the top eSNP may not be the true causal SNP, we score an individual gene’s evidence of selection by taking a weighted sum of each SNP’s an liver . We alsoficiency . Other htivation , and CCRntration , BTN3A3  T cells , and GANtabolism .d-statistic [FST, which tests for variants that are highly differentiated in a focal population versus other populations (Methods). As above, we weight these d-statistics by the probability of a SNP being causal to derive a “d-score” for each gene or intron. Genes with high d-scores in populations with evidence of non-African admixture  are more genetically similar to EUR samples from the 1kGP, based on FST. Conversely, populations with evidence of West African admixture  are more genetically similar to YRI samples at high d-score genes, suggesting that in many cases the genetic differentiation at these loci is driven by population-specific patterns of admixture. We therefore calculate the population branch statistic (PBS) [d and PBS score in the top 99.5th percentile as significant, we identify 22 eGenes and 22 sGenes with significant evidence of population-specific selection   between ion Fig. A, B.Fig.TMEM216 among the Nilo-Saharan speaking Mursi pastoralists , is in high LD with the top TMEM16 eQTL in Africans, rs7934229 (r2 = 0.99). Both of these SNPs are moderately associated with skin pigmentation in Africans (p < 5 × 10−6) but do not reach genome-wide significance , suggesting possible tumor suppressor function for this gene [TMEM216 eQTL and pigmentation GWAS signals suggests TMEM216 as a possible pigmentation gene, there are several haplotypes segregating in this region, some of which carry tQTLs for other genes in GTEx , which enables the detection of novel regulatory variation, these populations live in diverse climates and have distinct cultural and subsistence practices, which may have driven unique local adaptations. Using an outlier approach based on the atistics , 57, we Africans . TMEM216yndromes , 72. TMEin model . Consistin model . In addihis gene . While tThere are several limitations to our study, foremost being our modest sample size of 162 individuals, with current eQTL datasets reaching sample sizes an order of magnitude larger . Many ofTMEM216 expression in the Mursi and strong colocalization between TMEM216 eQTLs and a pigmentation GWAS locus.We have presented a comprehensive analysis of transcriptomic variation in a cohort of previously unstudied indigenous sub-Saharan Africans. We identify extensive novel regulatory variation in Africans and show that the study of African populations improves the detection of transcriptomic QTLs and fine-mapping of causal variation. Studying diverse populations within Africa also allows for the detection of genes targeted by population-specific selection, including evidence of selection on Phenotypic, genealogical, and biological data were collected from individuals belonging to nine populations in Ethiopia and Tanzania. Prior to sample collection, IRB approval for this project was obtained from the University of Pennsylvania. Written informed consent was obtained from all participants and research/ethics approval and permits were obtained from the following institutions prior to sample collection: the University of Addis Ababa and the Federal Democratic Republic of Ethiopia Ministry of Science and Technology National Health Research Ethics Review Committee; COSTECH, NIMR, and Muhimbili University of Health and Allied Sciences in Dar es Salaam, Tanzania. To obtain DNA and RNA data, whole blood was collected using vacutainers and RNA was stabilized in the field using LeukoLOCK Total RNA Isolation System (Ambion life Technologies). The Poly(A)Purist Kit  was used for mRNA selection, and Ampure XP magnetic beads  were used for size selection after amplification.A subset 162 individuals were genotyped as part of the 5 M dataset using the whole genome Illumina Omni5 Beadchip array, which includes approximately 4.5 million SNPs. The full 5 M dataset was phased using Beagle 4.0  and the r2) greater than 0.99 reported from minimac3. SNPs were LD-pruned using plink v1.90 [To identify related individuals, relatedness was inferred in the imputed 5 M dataset using the KING extension of plink 2.0 . To placnk v1.90  and parank v1.90 , with “nnk v1.90  was run Samples were sequenced on an Illumina HiSeq to a median depth of 56,122,076 reads . Prior to mapping, all reads aligned to rRNA genes with BLAST  were remCell-type fractions for each individual were inferred using CIBERSORT . The LM2PEER [Prior to hidden factor inference and QTL mapping, molecular phenotype matrices were first filtered and quantile-normalized. For eQTL mapping, only lncRNA and protein-coding genes with more than 5 reads in at least 20 individuals and with mean TPM > 0.1 across all populations were considered. For sQTL mapping, introns from lncRNA and protein-coding genes with no more than 5 individuals with 0 reads were included. Furthermore, clusters were required to have at least 20 reads in at least 100 individuals and have 0 reads in fewer than 10 individuals. These filtered phenotype matrices (TPM for eQTL mapping and JPC for sQTL) were then quantile-normalized using the two-stage procedure implemented by GTEx . BrieflyPEER  for thesPEER factors, and genetic relatedness. Mapping was performed for SNPs with MAF > 0.05, imputation r2 > 0.3, and within 100 kb of the target phenotype (gene TSS for eQTLs and intron for sQTLs) using GEMMA [PEER factors: 0–5, 10, 15, 20, 25, and 30 factors for eQTL mapping, and 0–10 factors for sQTL mapping, and the number of factors maximizing the number of eQTLs or sQTLs discovered were chosen for downstream analysis.Expression and splicing quantitative trait loci were mapped using a linear mixed modelling approach, using the quantile-normalized gene or intron fractions as phenotypes, while correcting for sex, age, cell-type composition, delivery date, latent ng GEMMA  and a gep-values (P’) for each tested SNP-phenotype pair. The minimum P’ per phenotype were again FDR-corrected using BH, yielding double-corrected p-values (P’’) per phenotype, and phenotypes with P’’ < 0.05 were considered significant. To identify significant SNPs, a threshold was set equal to the lowest P’ for the phenotype with highest significant P’’, and all SNPs with P’ lower than this threshold were deemed significant.To identify significant QTLs, tested SNPs for each phenotype were first FDR-corrected using Benjamini-Hochberg (BH), yielding single-corrected n being causal (PPn) was then taken as:For each gene or intron of interest, Approximate Bayes Factors were calculated for each tested SNP using the function “approx.bf.estimates” from the coloc package , or the Similar to The Wellcome Trust Case Control Consortium et al. , where \All SNPs in the imputed genotype dataset of 162 individuals were annotated for functional consequences using the Variant Effect Predictor (VEP)  with par1, was estimated using the R package qvalue [All SNPs and intron boundaries were converted to hg38 coordinates using liftOver . For eQTe qvalue .To identify tQTLs in the African cohort that are independent of GTEx v8 tQTLs, we performed eQTL and sQTL scans conditioning on independent GTEx eQTLs and sQTLs identified via step-wise regression . In caser2) between lead SNPs for eQTLs and sQTLs and all tested SNPs in the YRI and CEU 1kGP samples, restricting to those variants polymorphic in both, resulting in an r2 vector per group (YRI and CEU) per locus (eGenes and sIntrons). For each tQTL locus, we estimated the Pearson correlation r2 vectors, and the distribution of these To compare LD structure between Africans and Europeans at tQTL loci, LD was estimated  test, with the alternative hypothesis being that the absolute frequency difference for independent tQTLs is right skewed (i.e. has an enrichment of large frequency differences) compared with the distribution of shared tQTLs. Similarly, to test whether independent tQTLs show weaker LD-structure correlation between African and Europeans compared with shared tQTLs, we perform a one-sided KS test using the PEER factors, top 5 genotype PCs, sex, platform, and PCR batch. Significance was evaluated using the hierarchical Benjamini–Hochberg procedure used for African samples.eQTL mapping was performed on 162 individuals of European ancestry from GTEx v8 using FastQTL  with 10,FST was estimated using the Hudson estimator [FST > 0.36) were considered outliers. To test for overall enrichment of FST outliers among tQTLs, we use an approach similar to that of Quach et al. [. The maximum FST value of SNPs in LD with lead tQTL SNPs (r2 > 0.8) was found, and the fraction of outliers among these maximum FST values was calculated. To generate a null expectation, each lead tSNP was matched with a random SNP, matching on MAF (bins of 0.05) and number of SNPs in LD  and allele frequencies were combined with frequency information for EUR populations from the 1KGP, restricting to SNPs polymorphic in both datasets. stimator , and SNPh et al. . The maxTL SNPs r > 0.8 waFST scores were generated for each eGene and sIntron. For each feature of interest (gene or intron), the posterior probability of each tested SNP was calculated using the approach used to define credible sets, and for each feature, a weighted FST score was calculated as:FST of SNP FST values were considered as candidate genes under selection. To further account for background selection, or other factors that may alter the FST of the surrounding region, we permuted FST across variants for each candidate and re-calculated the FST score. This was repeated 10,000 times to generate a null expectation of weighted FST scores for each candidate gene, which we compared observed scores against to generate empirical p-values. Those candidate genes with an empirical p-value less than 0.01 were considered significant.To identify individual eGenes and sGenes with evidence of selection, weighted d-statistic for each SNP:FST between focal population FST between populations FST. To identify individual eGenes and sGenes with evidence of population-specific selection, we generate weighted FST.To detect population-specific selection, we use an adapted, polarized version of the i) [Due to differential levels of admixture across populations, some c (PBSi)  between Additional file 1: Fig S1. Principal Component Analysis of East African and 1000 Genome Project. Fig S2. ADMIXTURE analysis across K values 2-12. Fig S3. Genomic context of tQTLs. Fig S4. π1 of eQTL p-values of SNP-gene pairs ascertained as sQTLs. Fig S5. π1 between sQTLs and eQTLs across gene length deciles. Fig S6. π1 value of ascertained eQTLs and sQTLs in GTEx. Fig S7. Mapping statistics from STAR. Fig S8. Frequency and LD differences between African samples and 1000 Genomes EURpopulations. Fig S9. tQTL effect size vs MAF. Fig S10. Fraction of FST outliers among eQTLs and sQTLs compared with matched background. Fig S11. Population-specific FST outliers. Fig. S12. Global frequencies of SNPs associated with pigmentation variation and TMEM216 expression and splicing. Fig S13. Colocalization of Mursi PBS and d-statistics with TMEM216 eQTLs. Fig S14. Colocalization of Mursi PBS and d-statistics with pigmentation GWAS. Fig S15. eQTL associations for TMEM216 across populations. Fig S16. ‘LocusCompare’ plots of African pigmentation GWAS and GTEx v8 eQTLs. Fig S17. ‘LocusCompare’ plots of African pigmentation GWAS and GTEx v8 sQTLs.Additional file 2: Table S1. Genes with weighted East African-EUR eQTL FST scores greater than 99% of genome-wide SNPs. Table S2. Spliced introns and related genes with weighted East African-EUR sQTL FST scores greater than 99% of genome-wide SNPs. Table S3. Genes with weighted East African d-statistic and PBS scores greater than 99.5% of genome-wide SNPs. Table S4. Introns and related genes with weighted East African d-statistic and PBS scores greater than 99.5% of genome-wide SNPs.Additional file 3. Reviewhistory.


Donor lines rich in multiple antioxidant properties were identified from the mapping population. The population was classified into three genetic groups and each group showed reasonable correspondence with the antioxidant traits. The presence of linkage disequilibrium in the population was confirmed from the estimated Fst values. A strong positive correlation of DPPH was established with TPC, FRAP and CUPRAC. A moderate to high mean gene diversity was observed in the panel population. Eleven significant marker-trait associations for antioxidant traits were mapped, namely, qACD2.1, qACD11.1 and qACD12.2 for DPPH; qCAT8.1 and qCAT11.1 for catalase; qFRAP11.1, qFRAP12.1 and qFRAP12.2 for FRAP; and qCUPRAC3.1, qCUPRAC11.1 and qCUPRA12.1 regulating CUPRAC. Co-localization of the QTLs for qACD11.1, qFRAP11.1 and qCUPRAC11.1 were detected, which may act as antioxidant hotspots regulating DPPH, FRAP and CUPRAC activities, respectively, while qACD12.2 and qFRAP12.1 remained close on the chromosome 12. These detected QTLs will be useful in antioxidant improvement programs in rice.Because it is rich in antioxidant compounds, the staple food of rice provides many health benefits. Four antioxidant traits in rice grain,  Antioxidants protect the plant cell from damage and act as a defense system for maintaining the structural and functional integrity of cell ,2. AntioOsAPx1 and OsAPx2, two peroxisome/glyoxysome isoforms encoded by OsAPx3 and OsAPx4, and chloroplastidic isoforms encoded by OsAPx5, OsAPx6, OsAPx7 and OsAPx8 [In rice, ascorbate peroxidase (APx) was reported to be encoded by eight APx genes: two cytosolic isoforms encoded by d OsAPx8 ,16. The d OsAPx8 ,17. Repod OsAPx8 ,18,19,20Association mapping has emerged as a powerful alternative strategy for identifying genes or QTLs for various complex traits in plants in a natural variable population by examining the marker–trait associations. Mapping of complex antioxidant compounds and antioxidant activity by exploiting the naturally occurring variations through association mapping will provide QTLs that regulate the phytochemicals in rice. The genetic diversity and structure of the population in association mapping will be helpful for detecting marker–trait associations that may be useful for trait enhancement in molecular breeding programs. In order to avoid spurious marker–phenotype association, population structure (Q) with relative kinship (K) analyses are used to check and correct the panel population composition for linkage disequilibrium (LD) mapping analyses ,22,23,24In the present investigation, association mapping was performed in a panel population containing 117 genotypes (64 white and 53 red grain) shortlisted through phenotyping of six phytochemical traits  from 270 shortlisted diverse genotypes of India. The population was studied for the population genetic structure, diversity and association of molecular markers with these phytochemical traits.A total of five antioxidant traits of rice grain, namely, catalase, peroxidase, DPPH, FRAP and CUPRAC, along with antioxidant compounds and phenolic content, were estimated from 270 genotypes during the wet season of 2018 . Wide vaThe genotype-by-trait biplot diagram was generated using the first two principal components of the six antioxidant properties estimated from the mapping population of the panel containing 117 germplasm lines . A totalThe association among six antioxidant traits revealed a strong positive correlation (r ≥ 0.7) of DPPH with TPC, FRAP and CUPRAC. Moreover, a strong correlation was noticed in FRAP with CUPRAC . HoweverThe representative mapping population containing 117 germplasm lines that exhibited wide variation for the six antioxidant traits was genotyped using 131 SSR markers. The genetic diversity parameters assessed from the panel population are shown in the STRUCTURE 2.3.6 software was used for analysis of genetic structure by applying probable subpopulations (K) at a higher delta K-value in the used diverse population for the six antioxidant traits. The rate of change in the log probability of data between successive K values was the delta K value used in the analysis. The panel population was classified into two subpopulations by assuming K = 2 and using a ∆K peak value of 309.09 . The twoThe majority of the germplasm lines with high to very high antioxidant traits were present in the subpopulation 2. The moderate value antioxidant properties containing germplasm lines were present in the subpopulation 3. The majority of the germplasm lines showing poor to moderate values for antioxidants were in subpopulation 1 . A low aIT for individuals within the total population for differentiation and FIS for the uniformity of individuals within the subpopulation in a population were computed. The FIS and FIT values within the population and the total population estimated on the basis of 131 marker loci were 0.045 and 0.051, respectively, whereas the total population had an FST value of 0.006 between the three subpopulations. Fst is used to indicate the subpopulations or population differentiation within the total population. A clear differentiation between the three subpopulations was observed from their distribution pattern based on the Fst values  . The gent values .r2 value was used to plot the linkage disequilibrium decay of the population versus the physical distance in million base pairs  was constructed based on the genotyping results of 131 SSR markers, and was used to classify the 117 germplasm lines as per the genetic relatedness among the lines . The ineThe germplasm lines containing high to very high mean values for the antioxidant traits are grouped together, forming the subpopulation 3. This subpopulation is present on quadrants 3 (top left) and 4 (bottom left), and are encircled in blue. The germplasm lines rich in the antioxidant properties are placed on both sides of the axis on quadrants 3 and 4 . The PCoWard’s clustering approach broadly grouped all the genotypes into two major groups. The largest cluster, cluster II accommodated 65 germplasm lines that all carried very low, low or medium levels of antioxidant properties. Cluster I only had 52 germplasm lines. The dendrogram placed in this cluster all the germplasm lines that were rich in antioxidant traits for at least one compound. This cluster was again subdivided into two subgroups, which were further divided into sub-subclusters. Cluster II was divided into two main subclusters, which were finally divided into small groups. All of the sub-subclusters accommodated in Ward’s clustering approach were based on the antioxidant traits present in the germplasm lines A.2 by the presence of germplasm lines containing high antioxidant properties, whereas moderate to high containing genotypes were placed in subpopulation 2. The green-colored portion of the tree is designated SP2 whereas SP3 is shown in blue. The very poor antioxidant properties carrying germplasm lines were in subpopulation 3. The majority of the germplasm lines present in subpopulation 1 were poor to medium in antioxidant traits and are shown in pink. The germplasm lines with an admix type of population are depicted in red in the neighbor joining tree . Five traits showed significant association with 43 SSR markers by GLM, and four traits with 14 SSR markers by MLM analysis at p < 0.01. The marker R2 values varied from 0.05438 to 0.12875 by GLM, and from 0.06324 to 0.12586 by the mixed linear model  and mixed linear model (MLM/ K+Q model)) in the TASSEL 5 software. The marker–trait association values were compared at less than 1% error, i.e., 99% confidence  and colored (149) rice grain landraces and cultivars, were obtained from Gene Bank, ICAR-NRRI, Cuttack, and grown in the experimental plot of the Institute during the wet season, 2018 . The ini−1 g−1) and guaicol peroxidase (PEROX: unit min−1 g−1) were estimated as per the procedures of Aebi [−1). DPPH  radical scavenging assay was estimated according to the method of Zhou et al. [−1. Cupric ion reducing antioxidant capacity (CUPRAC) was determined according to the method of Apak et al. [−1.The seed samples were dehulled by a Satake rice huller, Japan, ground into flour by a grinding machine (Glenmini grinder), sieved through 100-size mesh and stored at 4 °C for the experiment. Seed enzymatic antioxidants such as catalase  for each trait, including the estimation of mean, range and coefficient of variation (CV %). Pearson’s correlation coefficients were analyzed to determine the relationship among the various antioxidant traits based on the mean values of the 117 genotypes, and presented in a correlation matrix heatmap using PAST3 software. The germplasm lines were classified into five groups, i.e., very high, high, medium, low and very low categories, based on the mean values of the antioxidant traits.http://gramene.org/) available in the public domain (−1 ethidium bromide. A 50 bp DNA ladder was used to determine the size of amplicons. The gel was run up to 4 h at 2.5 V cm−1 and photographed using a Gel Documentation System (SynGene). Earlier publications of Barik et al. [Fifteen-day-old plants were used for extraction of genomic DNA from the germplasm lines by adopting the CTAB method . A totalc domain . The DNAc domain . The conk et al. ,46 and Pk et al.  were folIT, FIS, FST), calculated by the deviation from the Hardy–Weinberg expectation. The procedures followed in earlier publications were adopted for molecular data analysis [The presence or absence of amplified products obtained on the basis genotype-primer combination was used to score the data. A binary data matrix was used as discrete variables for the entry of the resulting data. The parameters, namely, polymorphic information content (PIC), observed heterozygosity (H), number of alleles (N), major allele frequency (A) and gene diversity (GD), for each SSR locus were analyzed using ‘Power Marker Ver 3.25’ software . The Bayanalysis ,30,54,55p-value and r2 value detected by both the models, the associated markers were identified. The associations of markers were further confirmed by the Q–Q plot generated by the software. The linkage disequilibrium plot was obtained using the LD-measured r2 between pairs of markers, and plotted against the distance between the pairs. In addition, the accuracy of the marker–trait association was checked by estimating the FDR-adjusted p-values  using R software, as described in the earlier publications [To analyze the marker–trait association for mapping study of the seed antioxidant traits in rice, the software “TASSEL 5.0” was used. The generalized linear model and mixed linear model in TASSEL 5.0 were used to determine the genetic association between the phenotypic traits and molecular markers obtained in the study . By consications ,30. viz., catalase, peroxidase, CUPRAC, DPPH, FRAP and TPC, using the population of 117 lines and 131 SSR markers. Donor lines rich in multiple antioxidant traits were identified from the population for antioxidant improvement programs. The population was classified into three genetic groups and showed reasonable correspondence with the antioxidant traits. The presence of a linkage disequilibrium in the population was confirmed from the estimated Fst values. A total of 11 significant marker–trait associations for antioxidant enzymes and activities was detected for three QTLs, namely, qACD2.1, qACD11.1 and qACD12.2 for DPPH; qCAT8.1 and qCAT11.1 for catalase; qFRAP11.1, qFRAP12.1 and qFRAP12.2 for FRAP, and qCUPRAC3.1, qCUPRAC11.1 and qCUPRA12.1 for CUPRAC. Co-localization of the QTLs was detected for qACD11.1, qFRAC11.1 and qCUPRAC11.1 regulating DPPH, FRAP and CUPRAC activities, respectively, and qACD12.2 and qFRAP12.1 remained close on chromosome 12. These QTLs will be useful in antioxidant improvement programs in rice.The representative panel population developed by shortlisting 117 germplasm lines based on six antioxidant trait phenotypic groups showed wide genetic variation among the germplasm lines. Moreover, the population showed higher diversity parameters based on 131 SSR marker allele data. Therefore, the choice of mapping population was effective for the association mapping study of the six antioxidant traits,