Aspergillus flavus pangenome (AflaPan) uncovers novel aflatoxin and secondary metabolite associated gene clusters.

BACKGROUND: Aspergillus flavus is an important agricultural and food safety threat due to its production of carcinogenic aflatoxins. It has high level of genetic diversity that is adapted to various environments. Recently, we reported two reference genomes of A. flavus isolates, AF13 (MAT1-2 and highly aflatoxigenic isolate) and NRRL3357 (MAT1-1 and moderate aflatoxin producer). Where, an insertion of 310 kb in AF13 included an aflatoxin producing gene bZIP transcription factor, named atfC. Observations of significant genomic variants between these isolates of contrasting phenotypes prompted an investigation into variation among other agricultural isolates of A. flavus with the goal of discovering novel genes potentially associated with aflatoxin production regulation. Present study was designed with three main objectives: (1) collection of large number of A. flavus isolates from diverse sources including maize plants and field soils; (2) whole genome sequencing of collected isolates and development of a pangenome; and (3) pangenome-wide association study (Pan-GWAS) to identify novel secondary metabolite cluster genes. RESULTS: Pangenome analysis of 346 A. flavus isolates identified a total of 17,855 unique orthologous gene clusters, with mere 41% (7,315) core genes and 59% (10,540) accessory genes indicating accumulation of high genomic diversity during domestication. 5,994 orthologous gene clusters in accessory genome not annotated in either the A. flavus AF13 or NRRL3357 reference genomes. Pan-genome wide association analysis of the genomic variations identified 391 significant associated pan-genes associated with aflatoxin production. Interestingly, most of the significantly associated pan-genes (94%; 369 associations) belonged to accessory genome indicating that genome expansion has resulted in the incorporation of new genes associated with aflatoxin and other secondary metabolites. CONCLUSION: In summary, this study provides complete pangenome framework for the species of Aspergillus flavus along with associated genes for pathogen survival and aflatoxin production. The large accessory genome indicated large genome diversity in the species A. flavus, however AflaPan is a closed pangenome represents optimum diversity of species A. flavus. Most importantly, the newly identified aflatoxin producing gene clusters will be a new source for seeking aflatoxin mitigation strategies and needs new attention in research.

Linkage Mapping and Genome-Wide Association Study Identified Two Peanut Late Leaf Spot Resistance Loci, PLLSR-1 and PLLSR-2, Using Nested Association Mapping.

Identification of candidate genes and molecular markers for late leaf spot (LLS) disease resistance in peanut (Arachis hypogaea) has been a focus of molecular breeding for the U.S. industry-funded peanut genome project. Efforts have been hindered by limited mapping resolution due to low levels of genetic recombination and marker density available in traditional biparental mapping populations. To address this, a multi-parental nested association mapping population has been genotyped with the peanut 58K single-nucleotide polymorphism (SNP) array and phenotyped for LLS severity in the field for 3 years. Joint linkage-based quantitative trait locus (QTL) mapping identified nine QTLs for LLS resistance with significant phenotypic variance explained up to 47.7%. A genome-wide association study identified 13 SNPs consistently associated with LLS resistance. Two genomic regions harboring the consistent QTLs and SNPs were identified from 1,336 to 1,520 kb (184 kb) on chromosome B02 and from 1,026.9 to 1,793.2 kb (767 kb) on chromosome B03, designated as peanut LLS resistance loci, PLLSR-1 and PLLSR-2, respectively. PLLSR-1 contains 10 nucleotide-binding site leucine-rich repeat disease resistance genes. A nucleotide-binding site leucine-rich repeat disease resistance gene, Arahy.VKVT6A, was also identified on homoeologous chromosome A02. PLLSR-2 contains five significant SNPs associated with five different genes encoding callose synthase, pollen defective in guidance protein, pentatricopeptide repeat, acyl-activating enzyme, and C2 GRAM domains-containing protein. This study highlights the power of multi-parent populations such as nested association mapping for genetic mapping and marker-trait association studies in peanuts. Validation of these two LLS resistance loci will be needed for marker-assisted breeding.

Nomogram for predicting the risk of nonalcoholic fatty liver disease in older adults in Qingdao, China: A cross-sectional study.

BACKGROUND AND OBJECTIVES: To explore the risk factors for non-alcoholic fatty liver disease (NAFLD) and to establish a non-invasive tool for the screening of NAFLD in an older adult population. METHODS AND STUDY DESIGN: A total of 131,161 participants were included in this cross-sectional study. Participants were randomly divided into training and validation sets (7:3). The least absolute shrinkage and selection operator method was used to screen risk factors. Multivariate logistic regression was employed to develop a nomogram, which was made available online. Receiver operating characteristic curve analysis, calibration plots, and decision curve analysis were used to validate the discrimination, calibration, and clinical practicability of the nomogram. Sex and age subgroup analyses were conducted to further validate the reliability of the model. RESULTS: Nine variables were identified for inclusion in the nomogram (age, sex, waist circumference, body mass index, exercise frequency, systolic blood pressure, fasting plasma glucose, alanine aminotransferase, and low-density lipoprotein cholesterol). The area under the receiver operating characteristic curve values were 0.793 and 0.790 for the training set and the validation set, respectively. The calibration plots and decision curve analyses showed good calibration and clinical utility. Subgroup analyses demonstrated consistent discriminatory ability in different sex and age subgroups. CONCLUSIONS: This study established and validated a new nomogram model for evaluating the risk of NAFLD among older adults. The nomogram had good discriminatory performance and is a non-invasive and convenient tool for the screening of NAFLD in older adults.

Value of DUSP6 in peripheral blood mononuclear cells in predicting adverse cardiovascular events after peritoneal dialysis in diabetic nephropathy. / å¤–å‘¨è¡€å•ä¸ªæ ¸ç»†èƒžä¸­DUSP6é¢„è­¦ç³–å°¿ç— è‚¾ç— è ¹è†œé€æžåŽä¸è‰¯å¿ƒè¡€ç®¡äº‹ä»¶çš„ä»·å€¼.

OBJECTIVES: Adverse cardiovascular events are the leading cause of death in peritoneal dialysis patients. Identifying indicators that can predict adverse cardiovascular events in these patients is crucial for prognosis. This study aims to assess the value of dual-specificity phosphatase 6 (DUSP6) in peripheral blood mononuclear cells as a predictor of adverse cardiovascular events after peritoneal dialysis in diabetic nephropathy patients. METHODS: A total of 124 diabetic nephropathy patients underwent peritoneal dialysis treatment at the Department of Nephrology of the First Affiliated Hospital of Hebei North University from June to September 2022 were selected as study subjects. The levels of DUSP6 in peripheral blood mononuclear cells were determined using Western blotting. Patients were categorized into high-level and low-level DUSP6 groups based on the median DUSP6 level. Differences in body mass index, serum albumin, high-sensitivity C-reactive protein, and dialysis duration were compared between the 2 groups. Pearson, Spearman, and multiple linear regression analyses were performed to examine factors related to DUSP6. Patients were followed up to monitor the occurrence of adverse cardiovascular events, and risk factors for adverse cardiovascular events after peritoneal dialysis were analyzed using Kaplan-Meier and Cox regression. RESULTS: By the end of the follow-up, 33 (26.61%) patients had experienced at least one adverse cardiovascular event. The high-level DUSP6 group had higher body mass index, longer dialysis duration, and higher high-sensitivity C-reactive protein, but lower serum albumin levels compared to the low-level DUSP6 group (all P<0.05). DUSP6 was negatively correlated with serum albumin levels (r=-0.271, P=0.002) and positively correlated with dialysis duration (rs=0.406, P<0.001) and high-sensitivity C-reactive protein (rs=0.367, P<0.001). Multiple linear regression analysis revealed that dialysis duration and high-sensitivity C-reactive protein were independently correlated with DUSP6 levels (both P<0.05). The cumulative incidence of adverse cardiovascular events was higher in the high-level DUSP6 group than in the low-level DUSP6 group (46.67% vs 7.81%, P<0.001). Cox regression analysis indicated that low serum albumin levels (HR=0.836, 95% CI 0.778 to 0.899), high high-sensitivity C-reactive protein (HR=1.409, 95% CI 1.208 to 1.644), and high DUSP6 (HR=6.631, 95% CI 2.352 to 18.693) were independent risk factors for adverse cardiovascular events in peritoneal dialysis patients. CONCLUSIONS: Dialysis duration and high-sensitivity C-reactive protein are independently associated with DUSP6 levels in peripheral blood mononuclear cells of diabetic nephropathy patients undergoing peritoneal dialysis. High DUSP6 levels indicate a higher risk of adverse cardiovascular events.

Analysis of gut microbiota in chinese donkey in different regions using metagenomic sequencing.

BACKGROUND: Gut microbiota plays a significant role in host survival, health, and diseases; however, compared to other livestock, research on the gut microbiome of donkeys is limited. RESULTS: In this study, a total of 30 donkey samples of rectal contents from six regions, including Shigatse, Changdu, Yunnan, Xinjiang, Qinghai, and Dezhou, were collected for metagenomic sequencing. The results of the species annotation revealed that the dominant phyla were Firmicutes and Bacteroidetes, and the dominant genera were Bacteroides, unclassified_o_Clostridiales (short for Clostridiales) and unclassified_f_Lachnospiraceae (short for Lachnospiraceae). The dominant phyla, genera and key discriminators were Bacteroidetes, Clostridiales and Bacteroidetes in Tibet donkeys (Shigatse); Firmicutes, Clostridiales and Clostridiales in Tibet donkeys (Changdu); Firmicutes, Fibrobacter and Tenericutes in Qinghai donkeys; Firmicutes, Clostridiales and Negativicutes in Yunnan donkeys; Firmicutes, Fibrobacter and Fibrobacteres in Xinjiang donkeys; Firmicutes, Clostridiales and Firmicutes in Dezhou donkeys. In the functional annotation, it was mainly enriched in the glycolysis and gluconeogenesis of carbohydrate metabolism, and the abundance was the highest in Dezhou donkeys. These results combined with altitude correlation analysis demonstrated that donkeys in the Dezhou region exhibited strong glucose-conversion ability, those in the Shigatse region exhibited strong glucose metabolism and utilization ability, those in the Changdu region exhibited a strong microbial metabolic function, and those in the Xinjiang region exhibited the strongest ability to decompose cellulose and hemicellulose. CONCLUSION: According to published literature, this is the first study to construct a dataset with multi-regional donkey breeds. Our study revealed the differences in the composition and function of gut microbes in donkeys from different geographic regions and environmental settings and is valuable for donkey gut microbiome research.

Transcriptional networks orchestrating red and pink testa color in peanut.

BACKGROUND: Testa color is an important trait of peanut (Arachis hypogaea L.) which is closely related with the nutritional and commercial value. Pink and red are main color of peanut testa. However, the genetic mechanism of testa color regulation in peanut is not fully understood. To elucidate a clear picture of peanut testa regulatory model, samples of pink cultivar (Y9102), red cultivar (ZH12), and two RNA pools (bulk red and bulk pink) constructed from F4 lines of Y9102 x ZH12 were compared through a bulk RNA-seq approach. RESULTS: A total of 2992 differential expressed genes (DEGs) were identified among which 317 and 1334 were up-regulated and 225 and 1116 were down-regulated in the bulk red-vs-bulk pink RNA pools and Y9102-vs-ZH12, respectively. KEGG analysis indicates that these genes were divided into significantly enriched metabolic pathways including phenylpropanoid, flavonoid/anthocyanin, isoflavonoid and lignin biosynthetic pathways. Notably, the expression of the anthocyanin upstream regulatory genes PAL, CHS, and CHI was upregulated in pink and red testa peanuts, indicating that their regulation may occur before to the advent of testa pigmentation. However, the differential expression of down-stream regulatory genes including F3H, DFR, and ANS revealed that deepening of testa color not only depends on their gene expression bias, but also linked with FLS inhibition. In addition, the down-regulation of HCT, IFS, HID, 7-IOMT, and I2'H genes provided an alternative mechanism for promoting anthocyanin accumulation via perturbation of lignin and isoflavone pathways. Furthermore, the co-expression module of MYB, bHLH, and WRKY transcription factors also suggested a fascinating transcriptional activation complex, where MYB-bHLH could utilize WRKY as a co-option during the testa color regulation by augmenting anthocyanin biosynthesis in peanut. CONCLUSIONS: These findings reveal candidate functional genes and potential strategies for the manipulation of anthocyanin biosynthesis to improve peanut varieties with desirable testa color.

Comparative Transcriptome Analysis Identified Candidate Genes for Late Leaf Spot Resistance and Cause of Defoliation in Groundnut.

Late leaf spot (LLS) caused by fungus Nothopassalora personata in groundnut is responsible for up to 50% yield loss. To dissect the complex nature of LLS resistance, comparative transcriptome analysis was performed using resistant (GPBD 4), susceptible (TAG 24) and a resistant introgression line (ICGV 13208) and identified a total of 12,164 and 9954 DEGs (differentially expressed genes) respectively in A- and B-subgenomes of tetraploid groundnut. There were 135 and 136 unique pathways triggered in A- and B-subgenomes, respectively, upon N. personata infection. Highly upregulated putative disease resistance genes, an RPP-13 like (Aradu.P20JR) and a NBS-LRR (Aradu.Z87JB) were identified on chromosome A02 and A03, respectively, for LLS resistance. Mildew resistance Locus (MLOs)-like proteins, heavy metal transport proteins, and ubiquitin protein ligase showed trend of upregulation in susceptible genotypes, while tetratricopeptide repeats (TPR), pentatricopeptide repeat (PPR), chitinases, glutathione S-transferases, purple acid phosphatases showed upregulation in resistant genotypes. However, the highly expressed ethylene responsive factor (ERF) and ethylene responsive nuclear protein (ERF2), and early responsive dehydration gene (ERD) might be related to the possible causes of defoliation in susceptible genotypes. The identified disease resistance genes can be deployed in genomics-assisted breeding for development of LLS resistant cultivars to reduce the yield loss in groundnut.

Epigenetics and epigenomics: underlying mechanisms, relevance, and implications in crop improvement.

Epigenetics is defined as changes in gene expression that are not associated with changes in DNA sequence but due to the result of methylation of DNA and post-translational modifications to the histones. These epigenetic modifications are known to regulate gene expression by bringing changes in the chromatin state, which underlies plant development and shapes phenotypic plasticity in responses to the environment and internal cues. This review articulates the role of histone modifications and DNA methylation in modulating biotic and abiotic stresses, as well as crop improvement. It also highlights the possibility of engineering epigenomes and epigenome-based predictive models for improving agronomic traits.

Integrated small RNA and mRNA expression profiles reveal miRNAs and their target genes in response to Aspergillus flavus growth in peanut seeds.

BACKGROUND: MicroRNAs are important gene expression regulators in plants immune system. Aspergillus flavus is the most common causal agents of aflatoxin contamination in peanuts, but information on the function of miRNA in peanut-A. flavus interaction is lacking. In this study, the resistant cultivar (GT-C20) and susceptible cultivar (Tifrunner) were used to investigate regulatory roles of miRNAs in response to A. flavus growth. RESULTS: A total of 30 miRNAs, 447 genes and 21 potential miRNA/mRNA pairs were differentially expressed significantly when treated with A. flavus. A total of 62 miRNAs, 451 genes and 44 potential miRNA/mRNA pairs exhibited differential expression profiles between two peanut varieties. Gene Ontology (GO) analysis showed that metabolic-process related GO terms were enriched. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses further supported the GO results, in which many enriched pathways were related with biosynthesis and metabolism, such as biosynthesis of secondary metabolites and metabolic pathways. Correlation analysis of small RNA, transcriptome and degradome indicated that miR156/SPL pairs might regulate the accumulation of flavonoids in resistant and susceptible genotypes. The miR482/2118 family might regulate NBS-LRR gene which had the higher expression level in resistant genotype. These results provided useful information for further understanding the roles of miR156/157/SPL and miR482/2118/NBS-LRR pairs. CONCLUSIONS: Integration analysis of the transcriptome, miRNAome and degradome of resistant and susceptible peanut varieties were performed in this study. The knowledge gained will help to understand the roles of miRNAs of peanut in response to A. flavus.

Arachis hypogaea gene expression atlas for fastigiata subspecies of cultivated groundnut to accelerate functional and translational genomics applications.

Spatio-temporal and developmental stage-specific transcriptome analysis plays a crucial role in systems biology-based improvement of any species. In this context, we report here the Arachis hypogaea gene expression atlas (AhGEA) for the world's widest cultivated subsp. fastigiata based on RNA-seq data using 20 diverse tissues across five key developmental stages. Approximately 480 million paired-end filtered reads were generated followed by identification of 81 901 transcripts from an early-maturing, high-yielding, drought-tolerant groundnut variety, ICGV 91114. Further, 57 344 genome-wide transcripts were identified with ≥1 FPKM across different tissues and stages. Our in-depth analysis of the global transcriptome sheds light into complex regulatory networks namely gravitropism and photomorphogenesis, seed development, allergens and oil biosynthesis in groundnut. Importantly, interesting insights into molecular basis of seed development and nodulation have immense potential for translational genomics research. We have also identified a set of stable expressing transcripts across the selected tissues, which could be utilized as internal controls in groundnut functional genomics studies. The AhGEA revealed potential transcripts associated with allergens, which upon appropriate validation could be deployed in the coming years to develop consumer-friendly groundnut varieties. Taken together, the AhGEA touches upon various important and key features of cultivated groundnut and provides a reference for further functional, comparative and translational genomics research for various economically important traits.

Whole-genome resequencing-based QTL-seq identified AhTc1 gene encoding a R2R3-MYB transcription factor controlling peanut purple testa colour.

Peanut (Arachis hypogaea. L) is an important oil crop worldwide. The common testa colours of peanut varieties are pink or red. But the peanut varieties with dark purple testa have been focused in recent years due to the potential high levels of anthocyanin, an added nutritional value of antioxidant. However, the genetic mechanism regulating testa colour of peanut is unknown. In this study, we found that the purple testa was decided by the female parent and controlled by a single major gene named AhTc1. To identify the candidate gene controlling peanut purple testa, whole-genome resequencing-based approach (QTL-seq) was applied, and a total of 260.9 Gb of data were generated from the parental and bulked lines. SNP index analysis indicated that AhTc1 located in a 4.7 Mb region in chromosome A10, which was confirmed by bulked segregant RNA sequencing (BSR) analysis in three segregation populations derived from the crosses between pink and purple testa varieties. Allele-specific markers were developed and demonstrated that the marker pTesta1089 was closely linked with purple testa. Further, AhTc1 encoding a R2R3-MYB gene was positional cloned. The expression of AhTc1 was significantly up-regulated in the purple testa parent YH29. Overexpression of AhTc1 in transgenic tobacco plants led to purple colour of leaves, flowers, pods and seeds. In conclusion, AhTc1, encoding a R2R3-MYB transcription factor and conferring peanut purple testa, was identified, which will be useful for peanut molecular breeding selection for cultivars with purple testa colour for potential increased nutritional value to consumers.

Nested-association mapping (NAM)-based genetic dissection uncovers candidate genes for seed and pod weights in peanut (Arachis hypogaea).

Multiparental genetic mapping populations such as nested-association mapping (NAM) have great potential for investigating quantitative traits and associated genomic regions leading to rapid discovery of candidate genes and markers. To demonstrate the utility and power of this approach, two NAM populations, NAM_Tifrunner and NAM_Florida-07, were used for dissecting genetic control of 100-pod weight (PW) and 100-seed weight (SW) in peanut. Two high-density SNP-based genetic maps were constructed with 3341 loci and 2668 loci for NAM_Tifrunner and NAM_Florida-07, respectively. The quantitative trait locus (QTL) analysis identified 12 and 8 major effect QTLs for PW and SW, respectively, in NAM_Tifrunner, and 13 and 11 major effect QTLs for PW and SW, respectively, in NAM_Florida-07. Most of the QTLs associated with PW and SW were mapped on the chromosomes A05, A06, B05 and B06. A genomewide association study (GWAS) analysis identified 19 and 28 highly significant SNP-trait associations (STAs) in NAM_Tifrunner and 11 and 17 STAs in NAM_Florida-07 for PW and SW, respectively. These significant STAs were co-localized, suggesting that PW and SW are co-regulated by several candidate genes identified on chromosomes A05, A06, B05, and B06. This study demonstrates the utility of NAM population for genetic dissection of complex traits and performing high-resolution trait mapping in peanut.

High-density SNP map facilitates fine mapping of QTLs and candidate genes discovery for Aspergillus flavus resistance in peanut (Arachis hypogaea).

KEY MESSAGE: Two novel resistant QTLs mapped and candidate genes identified for Aspergillus flavus resistance in cultivated peanut using SLAF-seq. Aflatoxin contamination in peanuts caused by Aspergillus flavus is a serious food safety issue for human health around the world. Host plant resistance to fungal infection and reduction in aflatoxin are crucial for mitigating this problem. Identification of the resistance-linked markers can be used in marker-assisted breeding for varietal development. Here we report construction of two high-density genetic linkage maps with 1975 SNP loci and 5022 SNP loci, respectively. Two consistent quantitative trait loci (QTL) were identified as qRAF-3-1 and qRAF-14-1, which located on chromosomes A03 and B04, respectively. QTL qRAF-3-1 was mapped within 1.67 cM and had more than 19% phenotypic variance explained (PVE), while qRAF-14-1 was located within 1.34 cM with 5.15% PVE. While comparing with the reference genome, the mapped QTLs, qRAF-3-1 and qRAF-14-1, were located within a physical distance of 1.44 Megabase pair (Mbp) and 2.22 Mbp, harboring 67 and 137 genes, respectively. Among the identified candidate genes, six genes with the same function were found within both QTLs regions. In addition, putative disease resistance RPP13-like protein 1 (RPP13), lipoxygenase (Lox), WRKY transcription factor (WRKY) and cytochrome P450 71B34 genes were also identified. Using microarray analysis, genes responded to A. flavus infection included coding for RPP13, pentatricopeptide repeat-containing-like protein, and Lox which may be possible candidate genes for resistance to A. flavus. The QTLs and candidate genes will further facilitate marker development and validation of genes for deployment in the molecular breeding programs against A. flavus in peanuts.

Translational genomics for achieving higher genetic gains in groundnut.

KEY MESSAGE: Groundnut has entered now in post-genome era enriched with optimum genomic and genetic resources to facilitate faster trait dissection, gene discovery and accelerated genetic improvement for developing climate-smart varieties. Cultivated groundnut or peanut (Arachis hypogaea), an allopolyploid oilseed crop with a large and complex genome, is one of the most nutritious food. This crop is grown in more than 100 countries, and the low productivity has remained the biggest challenge in the semiarid tropics. Recently, the groundnut research community has witnessed fast progress and achieved several key milestones in genomics research including genome sequence assemblies of wild diploid progenitors, wild tetraploid and both the subspecies of cultivated tetraploids, resequencing of diverse germplasm lines, genome-wide transcriptome atlas and cost-effective high and low-density genotyping assays. These genomic resources have enabled high-resolution trait mapping by using germplasm diversity panels and multi-parent genetic populations leading to precise gene discovery and diagnostic marker development. Furthermore, development and deployment of diagnostic markers have facilitated screening early generation populations as well as marker-assisted backcrossing breeding leading to development and commercialization of some molecular breeding products in groundnut. Several new genomics applications/technologies such as genomic selection, speed breeding, mid-density genotyping assay and genome editing are in pipeline. The integration of these new technologies hold great promise for developing climate-smart, high yielding and more nutritious groundnut varieties in the post-genome era.

Chaotic Ensemble of Online Recurrent Extreme Learning Machine for Temperature Prediction of Control Moment Gyroscopes.

Control moment gyroscopes (CMG) are crucial components in spacecrafts. Since the anomaly of bearing temperature of the CMG shows apparent correlation with nearly all critical fault modes, temperature prediction is of great importance for health management of CMGs. However, due to the complicity of thermal environment on orbit, the temperature signal of the CMG has strong intrinsic nonlinearity and chaotic characteristics. Therefore, it is crucial to study temperature prediction under the framework of chaos time series theory. There are also several other challenges including poor data quality, large individual differences and difficulty in processing streaming data. To overcome these issues, we propose a new method named Chaotic Ensemble of Online Recurrent Extreme Learning Machine (CE-ORELM) for temperature prediction of control moment gyroscopes. By means of the CE-ORELM model, this proposed method is capable of dynamic prediction of temperature. The performance of the method was tested by real temperature data acquired from actual CMGs. Experimental results show that this method has high prediction accuracy and strong adaptability to the on-orbital temperature data with sudden variations. These superiorities indicate that the proposed method can be used for temperature prediction of control moment gyroscopes.

Genetic imprints of domestication for disease resistance, oil quality, and yield component traits in groundnut (Arachis hypogaea L.).

Ploidy difference between wild Arachis species and cultivated genotypes hinder transfer of useful alleles for agronomically important traits. To overcome this genetic barrier, two synthetic tetraploids, viz., ISATGR 1212 (A. duranensis ICG 8123 × A. ipaensis ICG 8206) and ISATGR 265-5A (A. kempff-mercadoi ICG 8164 × A. hoehnei ICG 8190), were used to generate two advanced backcross (AB) populations. The AB-populations, namely, AB-pop1 (ICGV 91114 × ISATGR 1212) and AB-pop2, (ICGV 87846 × ISATGR 265-5A) were genotyped with DArT and SSR markers. Genetic maps were constructed for AB-pop1 and AB-pop2 populations with 258 loci (1415.7 cM map length and map density of 5.5 cM/loci) and 1043 loci (1500.8 cM map length with map density of 1.4 cM/loci), respectively. Genetic analysis identified large number of wild segments in the population and provided a good source of diversity in these populations. Phenotyping of these two populations identified several introgression lines with good agronomic, oil quality, and disease resistance traits. Quantitative trait locus (QTL) analysis showed that the wild genomic segments contributed favourable alleles for foliar disease resistance while cultivated genomic segments mostly contributed favourable alleles for oil quality and yield component traits. These populations, after achieving higher stability, will be useful resource for genetic mapping and QTL discovery for wild species segments in addition to using population progenies in breeding program for diversifying the gene pool of cultivated groundnut.

Carbohydrate, glutathione, and polyamine metabolism are central to Aspergillus flavus oxidative stress responses over time.

BACKGROUND: The primary and secondary metabolites of fungi are critical for adaptation to environmental stresses, host pathogenicity, competition with other microbes, and reproductive fitness. Drought-derived reactive oxygen species (ROS) have been shown to stimulate aflatoxin production and regulate in Aspergillus flavus, and may function in signaling with host plants. Here, we have performed global, untargeted metabolomics to better understand the role of aflatoxin production in oxidative stress responses, and also explore isolate-specific oxidative stress responses over time. RESULTS: Two field isolates of A. flavus, AF13 and NRRL3357, possessing high and moderate aflatoxin production, respectively, were cultured in medium with and without supplementation with 15 mM H2O2, and mycelia were collected following 4 and 7 days in culture for global metabolomics. Overall, 389 compounds were described in the analysis which encompassed 9 biological super-pathways and 47 sub-pathways. These metabolites were examined for differential accumulation. Significant differences were observed in both isolates in response to oxidative stress and when comparing sampling time points. CONCLUSIONS: The moderately high aflatoxin-producing isolate, NRRL3357, showed extensive stimulation of antioxidant mechanisms and pathways including polyamines metabolism, glutathione metabolism, TCA cycle, and lipid metabolism while the highly aflatoxigenic isolate, AF13, showed a less vigorous response to stress. Carbohydrate pathway levels also imply that carbohydrate repression and starvation may influence metabolite accumulation at the later timepoint. Higher conidial oxidative stress tolerance and antioxidant capacity in AF13 compared to NRRL3357, inferred from their metabolomic profiles and growth curves over time, may be connected to aflatoxin production capability and aflatoxin-related antioxidant accumulation. The coincidence of several of the detected metabolites in H2O2-stressed A. flavus and drought-stressed hosts also suggests their potential role in the interaction between these organisms and their use as markers/targets to enhance host resistance through biomarker selection or genetic engineering.

Deciphering drought-induced metabolic responses and regulation in developing maize kernels.

Drought stress conditions decrease maize growth and yield, and aggravate preharvest aflatoxin contamination. While several studies have been performed on mature kernels responding to drought stress, the metabolic profiles of developing kernels are not as well characterized, particularly in germplasm with contrasting resistance to both drought and mycotoxin contamination. Here, following screening for drought tolerance, a drought-sensitive line, B73, and a drought-tolerant line, Lo964, were selected and stressed beginning at 14 days after pollination. Developing kernels were sampled 7 and 14 days after drought induction (DAI) from both stressed and irrigated plants. Comparative biochemical and metabolomic analyses profiled 409 differentially accumulated metabolites. Multivariate statistics and pathway analyses showed that drought stress induced an accumulation of simple sugars and polyunsaturated fatty acids and a decrease in amines, polyamines and dipeptides in B73. Conversely, sphingolipid, sterol, phenylpropanoid and dipeptide metabolites accumulated in Lo964 under drought stress. Drought stress also resulted in the greater accumulation of reactive oxygen species (ROS) and aflatoxin in kernels of B73 in comparison with Lo964 implying a correlation in their production. Overall, field drought treatments disordered a cascade of normal metabolic programming during development of maize kernels and subsequently caused oxidative stress. The glutathione and urea cycles along with the metabolism of carbohydrates and lipids for osmoprotection, membrane maintenance and antioxidant protection were central among the drought stress responses observed in developing kernels. These results also provide novel targets to enhance host drought tolerance and disease resistance through the use of biotechnologies such as transgenics and genome editing.

High-density genetic map using whole-genome resequencing for fine mapping and candidate gene discovery for disease resistance in peanut.

Whole-genome resequencing (WGRS) of mapping populations has facilitated development of high-density genetic maps essential for fine mapping and candidate gene discovery for traits of interest in crop species. Leaf spots, including early leaf spot (ELS) and late leaf spot (LLS), and Tomato spotted wilt virus (TSWV) are devastating diseases in peanut causing significant yield loss. We generated WGRS data on a recombinant inbred line population, developed a SNP-based high-density genetic map, and conducted fine mapping, candidate gene discovery and marker validation for ELS, LLS and TSWV. The first sequence-based high-density map was constructed with 8869 SNPs assigned to 20 linkage groups, representing 20 chromosomes, for the 'T' population (Tifrunner × GT-C20) with a map length of 3120 cM and an average distance of 1.45 cM. The quantitative trait locus (QTL) analysis using high-density genetic map and multiple season phenotyping data identified 35 main-effect QTLs with phenotypic variation explained (PVE) from 6.32% to 47.63%. Among major-effect QTLs mapped, there were two QTLs for ELS on B05 with 47.42% PVE and B03 with 47.38% PVE, two QTLs for LLS on A05 with 47.63% and B03 with 34.03% PVE and one QTL for TSWV on B09 with 40.71% PVE. The epistasis and environment interaction analyses identified significant environmental effects on these traits. The identified QTL regions had disease resistance genes including R-genes and transcription factors. KASP markers were developed for major QTLs and validated in the population and are ready for further deployment in genomics-assisted breeding in peanut.

Co-localization of major quantitative trait loci for pod size and weight to a 3.7 cM interval on chromosome A05 in cultivated peanut (Arachis hypogaea L.).

BACKGROUND: Cultivated peanut (Arachis hypogaea L.), an important source of edible oil and protein, is widely grown in tropical and subtropical areas of the world. Genetic improvement of yield-related traits is essential for improving yield potential of new peanut varieties. Genomics-assisted breeding (GAB) can accelerate the process of genetic improvement but requires linked markers for the traits of interest. In this context, we developed a recombinant inbred line (RIL) mapping population (Yuanza 9102 × Xuzhou 68-4) with 195 individuals and used to map quantitative trait loci (QTLs) associated with three important pod features, namely pod length, pod width and hundred-pod weight. RESULTS: QTL analysis using the phenotyping data generated across four environments in two locations and genotyping data on 743 mapped loci identified 15 QTLs for pod length, 11 QTLs for pod width and 16 QTLs for hundred-pod weight. The phenotypic variation explained (PVE) ranged from 3.68 to 27.84%. Thirteen QTLs were consistently detected in at least two environments and three QTLs (qPLA05.7, qPLA09.3 and qHPWA05.6) were detected in all four environments indicating their consistent and stable expression. Three major QTLs, detected in at least three environments, were found to be co-localized to a 3.7 cM interval on chromosome A05, and they were qPLA05.7 for pod length (16.89-27.84% PVE), qPWA05.5 for pod width (13.73-14.12% PVE), and qHPWA05.6 for hundred-pod weight (13.75-26.82% PVE). This 3.7 cM linkage interval corresponds to ~2.47 Mb genomic region of the pseudomolecule A05 of A. duranensis, including 114 annotated genes related to catalytic activity and metabolic process. CONCLUSIONS: This study identified three major consistent and stable QTLs for pod size and weight which were co-localized in a 3.7 cM interval on chromosome A05. These QTL regions not only offer further investigation for gene discovery and development of functional markers but also provide opportunity for deployment of these QTLs in GAB for improving yield in peanut.