Search

Peanuts play a crucial role as an oil crop, serving not only as a primary source of edible oil but also offering ample protein and vitamins for human consumption. The lateral branch angle of peanuts is the angle between the main stem and the first pair of lateral branches, which is an important agronomic trait of peanuts, significantly impacts the peg penetration into the soil, plant growth, and pod yield. It is closely intertwined with planting density, cultivation techniques, and mechanized harvesting methods. Therefore, the lateral branch angle holds substantial importance in enhancing peanut yield and facilitating mechanization. In order to conduct in-depth research on the lateral branch angle of peanuts, this research is grounded in the QTL mapping findings, specifically focusing on the QTL qGH associated with the lateral branch angle of peanuts located on chromosome B05 (142610834-146688220). By using Jihua 5 and PZ42 for backcrossing, a BC1F2 population comprising 8000 individual plants was established. Molecular markers were then developed to screen the offspring plants, recombine individual plants, conduct fine mapping. he results showed that using the phenotype and genotype of 464 recombinant individual plants selected from 8000 offspring, narrow down the localization interval to 48kb, and designate it as qLBA. The gene Arahy.C4FM6Y , responsible for the F-Box protein, was identified within qLBA through screening. Real-time quantitative detection of Arahy.C4FM6Y was carried out using M130 and Jihua 5, revealing that the expression level of Arahy.C4FM6Y at the junction of the main stem and the first lateral branch of peanuts was lower in M130 compared to Jihua 5 during the growth period of the first lateral branch from 1 to 10 centimeters. Consequently, Arahy.C4FM6Y emerges as a gene that restrains the increase in the angle of the first lateral branch in peanuts. This investigation offers novel genetic reservoirs for peanut plant type breeding and furnishes a theoretical foundation for molecular marker-assisted peanut breeding. [ABSTRACT FROM AUTHOR]

Peanuts play a crucial role as an oil crop, serving not only as a primary source of edible oil but also offering ample protein and vitamins for human consumption. The lateral branch angle of peanuts is the angle between the main stem and the first pair of lateral branches, which is an important agronomic trait of peanuts, significantly impacts the peg penetration into the soil, plant growth, and pod yield. It is closely intertwined with planting density, cultivation techniques, andmechanized harvesting methods. Therefore, the lateral branch angle holds substantial importance in enhancing peanut yield and facilitating mechanization. In order to conduct indepth research on the lateral branch angle of peanuts, this research is grounded in the QTL mapping findings, specifically focusing on the QTL qGH associated with the lateral branch angle of peanuts located on chromosome B05 (142610834-146688220). By using Jihua 5 and PZ42 for backcrossing, a BC1F2 population comprising 8000 individual plants was established. Molecular markers were then developed to screen the offspring plants, recombine individual plants, conduct fine mapping. he results showed that using the phenotype and genotype of 464 recombinant individual plants selected from 8000 offspring, narrow down the localization interval to 48kb, and designate it as qLBA. The gene Arahy.C4FM6Y, responsible for the F-Box protein, was identified within qLBA through screening. Real-time quantitative detection of Arahy.C4FM6Y was carried out using M130 and Jihua 5, revealing that the expression level of Arahy.C4FM6Y at the junction of the main stem and the first lateral branch of peanuts was lower in M130 compared to Jihua 5 during the growth period of the first lateral branch from 1 to 10 centimeters. Consequently, Arahy.C4FM6Y emerges as a gene that restrains the increase in the angle of the first lateral branch in peanuts. This investigation offers novel genetic reservoirs for peanut plant type breeding and furnishes a theoretical foundation for molecular marker-assisted peanut breeding. [ABSTRACT FROM AUTHOR]

Peanuts play a crucial role as an oil crop, serving not only as a primary source of edible oil but also offering ample protein and vitamins for human consumption. The lateral branch angle of peanuts is the angle between the main stem and the first pair of lateral branches, which is an important agronomic trait of peanuts, significantly impacts the peg penetration into the soil, plant growth, and pod yield. It is closely intertwined with planting density, cultivation techniques, andmechanized harvesting methods. Therefore, the lateral branch angle holds substantial importance in enhancing peanut yield and facilitating mechanization. In order to conduct indepth research on the lateral branch angle of peanuts, this research is grounded in the QTL mapping findings, specifically focusing on the QTL qGH associated with the lateral branch angle of peanuts located on chromosome B05 (142610834-146688220). By using Jihua 5 and PZ42 for backcrossing, a BC1F2 population comprising 8000 individual plants was established. Molecular markers were then developed to screen the offspring plants, recombine individual plants, conduct fine mapping. he results showed that using the phenotype and genotype of 464 recombinant individual plants selected from 8000 offspring, narrow down the localization interval to 48kb, and designate it as qLBA. The gene Arahy.C4FM6Y, responsible for the F-Box protein, was identified within qLBA through screening. Real-time quantitative detection of Arahy.C4FM6Y was carried out using M130 and Jihua 5, revealing that the expression level of Arahy.C4FM6Y at the junction of the main stem and the first lateral branch of peanuts was lower in M130 compared to Jihua 5 during the growth period of the first lateral branch from 1 to 10 centimeters. Consequently, Arahy.C4FM6Y emerges as a gene that restrains the increase in the angle of the first lateral branch in peanuts. This investigation offers novel genetic reservoirs for peanut plant type breeding and furnishes a theoretical foundation for molecular marker-assisted peanut breeding. [ABSTRACT FROM AUTHOR]

High sugar content in peanut seeds is one of the major breeding objectives for peanut flavor improvement. In order to explore the genetic control of sugar accumulation in peanut kernels, we constructed a recombinant inbred line population of 256 F2:6-7 lines derived from the Luhua11 × 06B16 cross. A highresolution genetic map was constructed with 3692 bin markers through whole genome re-sequencing. The total map distance was 981.65 cM and the average bin marker distance was 0.27cM. A major stable QTL region (qSCB09/qSSCB09) was identified on linkage group (LG) B09 associated with both sucrose content (SC) and soluble sugar content (SSC) explaining 21.51-33.58% phenotypic variations. This major QTL region was consistently detected in three environments and mapped within a physical interval of 1.56 Mb on chromosome B09, and six candidate genes were identified. These results provide valuable information for further map-based cloning of favorable allele for sugar content in peanut. [ABSTRACT FROM AUTHOR]

Peanut pod rot is one of the major plant diseases affecting peanut production and quality over China, which causes large productivity losses and is challenging to control. To improve the disease resistance of peanuts, breeding is one significant strategy. Crucial preventative and management measures include grading peanut pod rot and screening high-contributed genes that are highly resistant to pod rot should be carried out. A machine vision-based grading approach for individual cases of peanut pod rot was proposed in this study, which avoids timeconsuming, labor-intensive, and inaccurate manual categorization and provides dependable technical assistance for breeding studies and peanut pod rot resistance. The Shuffle Attention module has been added to the YOLOv5s (You Only Look Once version 5 small) feature extraction backbone network to overcome occlusion, overlap, and adhesions in complex backgrounds. Additionally, to reduce missing and false identification of peanut pods, the loss function CIoU (Complete Intersection over Union) was replaced with EIoU (Enhanced Intersection over Union). The recognition results can be further improved by introducing grade classification module, which can read the information from the identified RGB images and output data like numbers of non-rotted and rotten peanut pods, the rotten pod rate, and the pod rot grade. The Precision value of the improved YOLOv5s reached 93.8%, which was 7.8%, 8.4%, and 7.3% higher than YOLOv5s, YOLOv8n, and YOLOv8s, respectively; the mAP (mean Average Precision) value was 92.4%, which increased by 6.7%, 7.7%, and 6.5%, respectively. Improved YOLOv5s has an average improvement of 6.26% over YOLOv5s in terms of recognition accuracy: that was 95.7% for non-rotted peanut pods and 90.8% for rotten peanut pods. This article presented a machine vision-based grade classification method for peanut pod rot, which offered technological guidance for selecting high-quality cultivars with high resistance to pod rot in peanut. [ABSTRACT FROM AUTHOR]

Peanut is a critical food crop worldwide, and the development of high-throughput phenotyping techniques is essential for enhancing the crop's genetic gain rate. Given the obvious challenges of directly estimating peanut yields through remote sensing, an approach that utilizes above-ground phenotypes to estimate underground yield is necessary. To that end, this study leveraged unmanned aerial vehicles (UAVs) for high-throughput phenotyping of surface traits in peanut. Using a diverse set of peanut germplasm planted in 2021 and 2022, UAV flight missions were repeatedly conducted to capture image data thatwere used to construct high-resolution multitemporal sigmoidal growth curves based on apparent characteristics, such as canopy cover and canopy height. Latent phenotypes extracted from these growth curves and their first derivatives informed the development of advanced machine learning models, specifically random forest and eXtreme Gradient Boosting (XGBoost), to estimate yield in the peanut plots. The random forest model exhibited exceptional predictive accuracy (R2 = 0.93), while XGBoost was also reasonably effective (R2 = 0.88). When using confusion matrices to evaluate the classification abilities of each model, the two models proved valuable in a breeding pipeline, particularly for filtering out underperforming genotypes. In addition, the random forest model excelled in identifying top-performing material while minimizing Type I and Type II errors. Overall, these findings underscore the potential of machine learning models, especially random forests and XGBoost, in predicting peanut yield and improving the efficiency of peanut breeding programs. [ABSTRACT FROM AUTHOR]

Peanut yield in southern China is usually limited by calcium deficiency in soil. Most previous studies have found that small-seed varieties showed higher tolerance than large-seed varieties (e.g. Virginia type) under calcium deficiency, however, our preliminary research found that sensitive varieties also existed in small-seed counterparts. Few studies have been conducted to characterize low-calcium tolerance among small-seed germplasms with genetic diversity, and the differences in physiological characteristics between sensitive and tolerant varieties has not been reported yet. Thus, in order to better understand such differences, the current study firstly collected and characterized a diversity germplasm panel consisting of 50 small-seed peanut genotypes via a 2-year field trial, followed by the physiological characterization in sensitive (HN032) and tolerant (HN035) peanut genotypes under calcium deficiency. As a result, the adverse effects brought by calcium deficiency on calcium uptake and distribution in HN032 was much larger than HN035. In details, calcium uptake in the aboveground part (leaves and stems) was reduced by 16.17% and 33.66%, while in the underground part (roots and pods), it was reduced by 13.69% and 68.09% under calcium deficiency for HN035 and HN032, respectively; The calcium distribution rate in the pods of HN035 was 2.74 times higher than HN032. The utilization efficiency of calcium in the pods of HN035 was 1.68 and 1.37 times than that of HN032 under calcium deficiency and sufficiency, respectively. In addition, under calcium deficiency conditions, the activities of antioxidant enzymes SOD, POD, and CAT, as well as the MDA content, were significantly increased in the leaves of HN032, peanut yield was significantly reduced by 22.75%. However, there were no significant changes in the activities of antioxidant enzymes, MDA content, and peanut yield in HN035. Therefore, higher calcium absorption and utilization efficiency may be the key factors maintaining peanut yield in calcium-deficient conditions for tolerant genotypes. This study lays a solid foundation for selecting low-calcium tolerant varieties in future peanut breeding. [ABSTRACT FROM AUTHOR]

Peanut growth, development, and eventual production are constrained by biotic and abiotic stresses resulting in serious economic losses. To understand the response and tolerance mechanism of peanut to biotic and abiotic stresses, high-throughput Omics approaches have been applied in peanut research. Integrated Omics approaches are essential for elucidating the temporal and spatial changes that occur in peanut facing different stresses. The integration of functional genomics with other Omics highlights the relationships between peanut genomes and phenotypes under specific stress conditions. In this review, we focus on research on peanut biotic stresses. Here we review the primary types of biotic stresses that threaten sustainable peanut production, the multi-Omics technologies for peanut research and breeding, and the recent advances in various peanut Omics under biotic stresses, including genomics, transcriptomics, proteomics, metabolomics, miRNAomics, epigenomics and phenomics, for identification of biotic stress-related genes, proteins, metabolites and their networks as well as the development of potential traits. We also discuss the challenges, opportunities, and future directions for peanut Omics under biotic stresses, aiming sustainable food production. The Omics knowledge is instrumental for improving peanut tolerance to cope with various biotic stresses and for meeting the food demands of the exponentially growing global population. [ABSTRACT FROM AUTHOR]

Introduction: Fungal foliar diseases can severely affect the productivity of the peanut crop worldwide. Late leaf spot is the most frequent disease and a major problem of the crop in Brazil and many other tropical countries. Only partial resistance to fungal diseases has been found in cultivated peanut, but high resistances have been described on the secondary gene pool. Methods: To overcome the known compatibility barriers for the use of wild species in peanut breeding programs, we used an induced allotetraploid (Arachis stenosperma x A. magna)4x, as a donor parent, in a successive backcrossing scheme with the high-yielding Brazilian cultivar IAC OL 4. We used microsatellite markers associated with late leaf spot and rust resistance for foreground selection and high-throughput SNP genotyping for background selection. Results: With these tools, we developed agronomically adapted lines with high cultivated genome recovery, high-yield potential, and wild chromosome segments from both A. stenosperma and A. magna conferring high resistance to late leaf spot and rust. These segments include the four previously identified as having QTLs (quantitative trait loci) for resistance to both diseases, which could be confirmed here, and at least four additional QTLs identified by using mapping populations on four generations. Discussion: The introgression germplasm developed here will extend the useful genetic diversity of the primary gene pool by providing novel wild resistance genes against these two destructive peanut diseases. [ABSTRACT FROM AUTHOR]

Peanut is an important food and feed crop, providing oil and protein nutrients. Germins and germin-like proteins (GLPs) are ubiquitously present in plants playing numerous roles in defense, growth and development, and different signaling pathways. However, the GLP members have not been comprehensively studied in peanut at the genome-wide scale. We carried out a genome-wide identification of the GLP genes in peanut genome. GLP members were identified comprehensively, and gene structure, genomic positions, motifs/domains distribution patterns, and phylogenetic history were studied in detail. Promoter Cis-elements, gene duplication, collinearity, miRNAs, protein-protein interactions, and expression were determined. A total of 84 GLPs (AhGLPs) were found in the genome of cultivated peanut. These GLP genes were clustered into six groups. Segmental duplication events played a key role in the evolution of AhGLPs, and purifying selection pressure was underlying the duplication process. Most AhGLPs possessed a well-maintained gene structure and motif organization within the same group. The promoter regions of AhGLPs contained several key cis-elements responsive to 'phytohormones', 'growth and development', defense, and 'light induction'. Seven microRNAs (miRNAs) from six families were found targeting 25 AhGLPs. Gene Ontology (GO) enrichment analysis showed that AhGLPs are highly enriched in nutrient reservoir activity, aleurone grain, external encapsulating structure, multicellular organismal reproductive process, and response to acid chemicals, indicating their important biological roles. AhGLP14, AhGLP38, AhGLP54, and AhGLP76 were expressed in most tissues, while AhGLP26, AhGLP29, and AhGLP62 showed abundant expression in the pericarp. AhGLP7, AhGLP20, and AhGLP21, etc., showed specifically high expression in embryo, while AhGLP12, AhGLP18, AhGLP40, AhGLP78, and AhGLP82 were highly expressed under different hormones, water, and temperature stress. The qRT-PCR results were in accordance with the transcriptome expression data. In short, these findings provided a foundation for future functional investigations on the AhGLPs for peanut breeding programs. [ABSTRACT FROM AUTHOR]

Introduction: The wild allotetraploid peanut Arachis monticola contains a higher oil content than the cultivated allotetraploid Arachis hypogaea. Besides the fact that increasing oil content is the most important peanut breeding objective, a proper understanding of its molecular mechanism controlling oil accumulation is still lacking. Methods: We investigated this aspect by performing comparative transcriptomics from developing seeds between three wild and five cultivated peanut varieties. Results: The analyses not only showed species-specific grouping transcriptional profiles but also detected two gene clusters with divergent expression patterns between two species enriched in lipid metabolism. Further analysis revealed that expression alteration of lipid metabolic genes with coexpressed transcription factors in wild peanut led to enhanced activity of oil biogenesis and retarded the rate of lipid degradation. In addition, bisulfite sequencing was conducted to characterize the variation of DNA methylation between wild allotetraploid (245, WH 10025) and cultivated allotetraploid (Z16, Zhh 7720) genotypes. CG and CHG context methylation was found to antagonistically correlate with gene expression during seed development. Differentially methylated region analysis and transgenic assay further illustrated that variations of DNA methylation between wild and cultivated peanuts could affect the oil content via altering the expression of peroxisomal acyl transporter protein (Araip.H6S1B).Discussion: From the results, we deduced that DNA methylation may negatively regulate lipid metabolic genes and transcription factors to subtly affect oil accumulation divergence between wild and cultivated peanuts. Our work provided the first glimpse on the regulatory mechanism of gene expression altering for oil accumulation in wild peanut and gene resources for future breeding applications. [ABSTRACT FROM AUTHOR]

Peanut is among the main oil crops in India with huge economic importance. The unpredictable rainy season during the growing time of peanuts causes waterlogging in peanut fields. Waterlogging triggers major environmental limitations that negatively affect the growth, physiology, and development of peanuts. Thus, the export and production of peanuts are severely affected by waterlogging. Therefore, the understanding of metabolic mechanisms under waterlogging is important to future water-stress tolerance breeding in peanuts. This study aimed to evaluate how peanuts responded to various waterlogging conditions in terms of their development, metabolic processes, and chlorophyll fluorescence characteristics. The evaluations were carried out at different stages of peanut variety DH-86 treated with waterlogging. The peanut plants were subjected to different waterlogging periods of 20, 40, 60, 80, and 100 days. The growth parameters including total dry mass, total leaf area, and total leaves number were calculated in all treatments. The phenomenological and specific energy fluxes andmaximumphotosystem II effciency (FV/Fm) were also determined. The measurements were done statistically using PCA, G-Means clustering, and correlation analysis to explore the interaction between different physiological parameters. The waterlogging for 100 days caused a significant reduction in the total number of leaves, dry mass, and total leaf area. The most sensitive parameters are specific and phenomenological energy fluxes and Fv/Fm, which notably decreased as waterlogging duration increased. The results indicated the growth and physiological performance of the peanut cv. DH-86 was affected significantly due to waterlogging and the interaction between all these parameters in waterlogging. This research focused on how peanuts respond to waterlogging stress and provides the basis for future plant breeding efforts to improve peanut waterlogging tolerance, especially in rainy regions. This will improve the sustainability of the entire peanut industry. [ABSTRACT FROM AUTHOR]

Ascorbate peroxidase (APX), an important antioxidant enzyme, plays a significant role in ROS scavenging by catalyzing the decrease of hydrogen peroxide under various environmental stresses. Nevertheless, information about the APX gene family and their evolutionary and functional attributes in peanut (Arachis hypogea L.) was not reported. Therefore, a comprehensive genome-wide study was performed to discover the APX genes in cultivated peanut genome. This study identified 166 AhAPX genes in the peanut genome, classified into 11 main groups. The gene duplication analysis showed that AhAPX genes had experienced segmental duplications and purifying selection pressure. Gene structure and motif investigation indicated that most of the AhAPX genes exhibited a comparatively well-preserved exon-intron pattern and motif configuration contained by the identical group. We discovered five phytohormones-, six abiotic stress-, and five growth and development-related cis-elements in the promoter regions of AhAPX. Fourteen putative ah-miRNAs from 12 families were identified, targeting 33 AhAPX genes. Furthermore, we identified 3,257 transcription factors from 38 families (including AP2, ARF, B3, bHLH, bZIP, ERF, MYB, NAC, WRKY, etc.) in 162 AhAPX genes. Gene ontology and KEGG enrichment analysis confirm the role of AhAPX genes in oxidoreductase activity, catalytic activity, cell junction, cellular response to stimulus and detoxification, biosynthesis of metabolites, and phenylpropanoid metabolism. Based on transcriptome datasets, some genes such as AhAPX4/7/17/77/82/86/130/133 and AhAPX160 showed significantly higher expression in diverse tissues/organs, i.e., flower, leaf, stem, roots, peg, testa, and cotyledon. Likewise, only a few genes, including AhAPX4/17/19/55/59/82/101/102/137 and AhAPX140, were significantly upregulated under abiotic (drought and cold), and phytohormones (ethylene, abscisic acid, paclobutrazol, brassinolide, and salicylic acid) treatments. qRT-PCR-based expression profiling presented the parallel expression trends as generated from transcriptome datasets. Our discoveries gave new visions into the evolution of APX genes and provided a base for further functional examinations of the AhAPX genes in peanut breeding programs. [ABSTRACT FROM AUTHOR]

Identification of peanut cultivars for distinct phenotypic or genotypic traits whether using visual characterization or laboratory analysis requires substantial expertise, time, and resources. A less subjective and more precise method is needed for identification of peanut germplasm throughout the value chain. In this proof-of-principle study, the accuracy of Raman spectroscopy (RS), a non-invasive, non-destructive technique, in peanut phenotyping and identification is explored. We show that RS can be used for highly accurate peanut phenotyping via surface scans of peanut leaves and the resulting chemometric analysis: On average 94% accuracy in identification of peanut cultivars and breeding lines was achieved. Our results also suggest that RS can be used for highly accurate determination of nematode resistance and susceptibility of those breeding lines and cultivars. Specifically, nematode-resistant peanut cultivars can be identified with 92% accuracy, whereas susceptible breeding lines were identified with 81% accuracy. Finally, RS revealed substantial differences in biochemical composition between resistant and susceptible peanut cultivars. We found that resistant cultivars exhibit substantially higher carotenoid content compared to the susceptible breeding lines. The results of this study show that RS can be used for quick, accurate, and non-invasive identification of genotype, nematode resistance, and nutrient content. Armed with this knowledge, the peanut industry can utilize Raman spectroscopy for expedited breeding to increase yields, nutrition, and maintaining purity levels of cultivars following release. [ABSTRACT FROM AUTHOR]

Peanuts (Arachis hypogaea L.) offer numerous healthy benefits, and the production of peanuts has a prominent role in global food security. As a result, it is in the interest of society to improve the productivity and quality of peanuts with transgenic means. However, the lack of a robust phylogeny of cultivated and wild peanut species has limited the utilization of genetic resources in peanut molecular breeding. In this study, a total of 33 complete peanut plastomes were sequenced, analyzed and used for phylogenetic analyses. Our results suggest that sect. Arachis can be subdivided into two lineages. All the cultivated species are contained in Lineage I with AABB and AA are the two predominant genome types present, while species in Lineage II possess diverse genome types, including BB, KK, GG, etc. Phylogenetic studies also indicate that all allotetraploid cultivated peanut species have been derived from a possible maternal hybridization event with one of the diploid Arachis duranensis accessions being a potential AA sub-genome ancestor. In addition, Arachis monticola , a tetraploid wild species, is placed in the same group with all the cultivated peanuts, and it may represent a transitional species, which has been through the recent hybridization event. This research could facilitate a better understanding of the taxonomic status of various Arachis species/accessions and the evolutionary relationship among them, and assists in the correct and efficient use of germplasm resources in breeding efforts to improve peanuts for the benefit of human beings. [ABSTRACT FROM AUTHOR]

The cultivated peanut (Arachis hypogaea L.), which is rich in edible oil and protein, is widely planted around the world as an oil and cash crop. However, aflatoxin contamination seriously affects the quality safety of peanuts, hindering the development of the peanut industry and threatening the health of consumers. Breeding peanut varieties with resistance to Aspergillus flavus infection is important for the control of aflatoxin contamination, and understanding the genetic basis of resistance is vital to its genetic enhancement. In this study, we reported the quantitative trait locus (QTL) mapping of resistance to A. flavus infection of a well-known resistant variety, J11. A mapping population consisting of 200 recombinant inbred lines (RILs) was constructed by crossing a susceptible variety, Zhonghua 16, with J11. Through whole-genome resequencing, a genetic linkage map was constructed with 2,802 recombination bins and an average inter-bin distance of 0.58 cM. Combined with phenotypic data of an infection index in 4 consecutive years, six novel resistant QTLs with 5.03–10.87% phenotypic variances explained (PVE) were identified on chromosomes A05, A08, B01, B03, and B10. The favorable alleles of five QTLs were from J11, while that of one QTL was from Zhonghua 16. The combination of these favorable alleles significantly improved resistance to A. flavus infection. These results could contribute greatly to the understanding of the genetic basis of A. flavus resistance and could be meaningful in the improvement of further resistance in peanuts. [ABSTRACT FROM AUTHOR]

Peanut is an important oil and economic crop in China. The rainy season (April–June) in the downstream Yangtze River in China always leads to waterlogging, which seriously affects plant growth and development. Therefore, understanding the metabolic mechanisms under waterlogging stress is important for future waterlogging tolerance breeding in peanut. In this study, waterlogging treatment was carried out in two different peanut cultivars [Zhonghua 4 (ZH4) and Xianghua08 (XH08)] with different waterlogging tolerance. The data-independent acquisition (DIA) technique was used to quantitatively identify the differentially accumulated proteins (DAPs) between two different cultivars. Meanwhile, the functions of DAPs were predicted, and the interactions between the hub DAPs were analyzed. As a result, a total of 6,441 DAPs were identified in ZH4 and its control, of which 49 and 88 DAPs were upregulated and downregulated under waterlogging stress, respectively, while in XH08, a total of 6,285 DAPs were identified, including 123 upregulated and 114 downregulated proteins, respectively. The hub DAPs unique to the waterlogging-tolerant cultivar XH08 were related to malate metabolism and synthesis, and the utilization of the glyoxylic acid cycle, such as L-lactate dehydrogenase, NAD+-dependent malic enzyme, aspartate aminotransferase, and glutamate dehydrogenase. In agreement with the DIA results, the alcohol dehydrogenase and malate dehydrogenase activities in XH08 were more active than ZH4 under waterlogging stress, and lactate dehydrogenase activity in XH08 was prolonged, suggesting that XH08 could better tolerate waterlogging stress by using various carbon sources to obtain energy, such as enhancing the activity of anaerobic respiration enzymes, catalyzing malate metabolism and the glyoxylic acid cycle, and thus alleviating the accumulation of toxic substances. This study provides insight into the mechanisms in response to waterlogging stress in peanuts and lays a foundation for future molecular breeding targeting in the improvement of peanut waterlogging tolerance, especially in rainy area, and will enhance the sustainable development in the entire peanut industry. [ABSTRACT FROM AUTHOR]

Seed size/weight, a key domestication trait, is also an important selection target during peanut breeding. However, the mechanisms that regulate peanut seed development are unknown. We re-sequenced 12 RNA samples from developing seeds of two cultivated peanut accessions (Lines 8106 and 8107) and wild Arachis monticola at 15, 30, 45, and 60 days past flowering (DPF). Transcriptome analyses showed that ∼36,000 gene loci were expressed in each of the 12 RNA samples, with nearly half exhibiting moderate (2 ≤ FPKM < 10) expression levels. Of these genes, 12.2% (4,523) were specifically expressed during seed development, mainly at 15 DPF. Also, ∼12,000 genes showed significant differential expression at 30, 45, and/or 60 DPF within each of the three peanut accessions, accounting for 31.8–34.1% of the total expressed genes. Using a method that combined comprehensive transcriptome analysis and previously mapped QTLs, we identified several candidate genes that encode transcription factor TGA7, topless-related protein 2, IAA-amino acid hydrolase ILR1-like 5, and putative pentatricopeptide repeat-containing (PPR) protein. Based on sequence variations identified in these genes, SNP markers were developed and used to genotype both 30 peanut landraces and a genetic segregated population, implying that EVM0025654 encoding a PPR protein may be associated with the increased seed size/weight of the cultivated accessions in comparison with the allotetraploid wild peanut. Our results provide additional knowledge for the identification and functional research into candidate genes responsible for the seed size/weight phenotype in peanut. [ABSTRACT FROM AUTHOR]

Drought is one of the major abiotic stress factors limiting peanut production. It causes the loss of pod yield during the pod formation stage. Here, one previously identified drought-tolerant cultivar, "L422" of peanut, was stressed by drought (35 ± 5%) at pod formation stage for 5, 7, and 9 days. To analyze the drought effects on peanut, we conducted physiological and transcriptome analysis in leaves under well-watered (CK1, CK2, and CK3) and drought-stress conditions (T1, T2, and T3). By transcriptome analysis, 3,586, 6,730, and 8,054 differentially expressed genes (DEGs) were identified in "L422" at 5 days (CK1 vs T1), 7 days (CK2 vs T2), and 9 days (CK3 vs T3) of drought stress, respectively, and 2,846 genes were common DEGs among the three-time points. Furthermore, the result of weighted gene co-expression network analysis (WGCNA) revealed one significant module that was closely correlated between drought stress and physiological data. A total of 1,313 significantly up-/down-regulated genes, including 61 transcription factors, were identified in the module at three-time points throughout the drought stress stage. Additionally, six vital metabolic pathways, namely, "MAPK signaling pathway-plant," "flavonoid biosynthesis," "starch and sucrose metabolism," "phenylpropanoid biosynthesis," "glutathione metabolism," and "plant hormone signal transduction" were enriched in "L422" under severe drought stress. Nine genes responding to drought tolerance were selected for quantitative real-time PCR (qRT-PCR) verification and the results agreed with transcriptional profile data, which reveals the reliability and accuracy of transcriptome data. Taken together, these findings could lead to a better understanding of drought tolerance and facilitate the breeding of drought-resistant peanut cultivars. [ABSTRACT FROM AUTHOR]

Cultivated peanut (Arachis hypogaea) is one of the most widely grown food legumes in the world, being valued for its high protein and unsaturated oil contents. Drought stress is one of the major constraints that limit peanut production. This study's objective was to identify the drought-responsive genes preferentially expressed under drought stress in different peanut genotypes. To accomplish this, four genotypes (drought tolerant: C76-16 and 587; drought susceptible: Tifrunner and 506) subjected to drought stress in a rainout shelter experiment were examined. Transcriptome sequencing analysis identified that all four genotypes shared a total of 2,457 differentially expressed genes (DEGs). A total of 139 enriched gene ontology terms consisting of 86 biological processes and 53 molecular functions, with defense response, reproductive process, and signaling pathways, were significantly enriched in the common DEGs. In addition, 3,576 DEGs were identified only in drought-tolerant lines in which a total of 74 gene ontology terms were identified, including 55 biological processes and 19 molecular functions, mainly related to protein modification process, pollination, and metabolic process. These terms were also found in shared genes in four genotypes, indicating that tolerant lines adjusted more related genes to respond to drought. Forty-three significantly enriched Kyoto Encyclopedia of Genes and Genomes pathways were also identified, and the most enriched pathways were those processes involved in metabolic pathways, biosynthesis of secondary metabolites, plant circadian rhythm, phenylpropanoid biosynthesis, and starch and sucrose metabolism. This research expands our current understanding of the mechanisms that facilitate peanut drought tolerance and shed light on breeding advanced peanut lines to combat drought stress. [ABSTRACT FROM AUTHOR]

Early and late leaf spots (LLSs) are the major foliar diseases of peanut responsible for severely decreased yield in the absence of intensive fungicide spray programs. Pyramiding host resistance to leaf spots in elite cultivars is a sustainable solution to mitigate the diseases. In order to determine the genetic control of leaf spot disease resistance in peanut, a recombinant inbred line population (Florida-07 × GP-NC WS16) segregating for resistance to both diseases was used to construct a SNP-based linkage map consisting of 855 loci. QTL mapping revealed three resistance QTLs for LLS qLLSA05 (phenotypic variation explained, PVE = 7–10%), qLLSB03 (PVE = 5–7%), and qLLSB05 (PVE = 15–41%) that were consistently expressed over multi-year analysis. Two QTL, qLLSA05 and qLLSB05 , confirmed our previously published QTL-seq results. For early leaf spot, three resistance QTLs were identified in multiple years, two on chromosome A03 (PVE = 8–12%) and one on chromosome B03 (PVE = 13–20%), with the locus qELSA03_1.1 coinciding with the previously published genomic region for LLS resistance in GPBD4. Comparative analysis of the genomic regions spanning the QTLs suggests that resistance to early and LLSs are largely genetically independent. In addition, QTL analysis on yield showed that the presence of resistance allele in qLLSB03 and qLLSB05 loci might result in protection from yield loss caused by LLS disease damage. Finally, post hoc analysis of the RIL subpopulation that was not utilized in the QTL mapping revealed that the flanking markers for these QTLs can successfully select for resistant and susceptible lines, confirming the effectiveness of pyramiding these resistance loci to improve host-plant resistance in peanut breeding programs using marker-assisted selection. [ABSTRACT FROM AUTHOR]

The cultivated peanut (Arachis hypogaea L.) is an allotetraploid (AABB) species derived from the A-genome (Arachis duranensis) and B-genome (Arachis ipaensis) progenitors. Presence of two versions of a DNA sequence based on the two progenitor genomes poses a serious technical and analytical problem during single nucleotide polymorphism (SNP) marker identification and analysis. In this context, we have analyzed 200 amplicons derived from expressed sequence tags (ESTs) and genome survey sequences (GSS) to identify SNPs in a panel of genotypes consisting of 12 cultivated peanut varieties and two diploid progenitors representing the ancestral genomes. A total of 18 EST-SNPs and 44 genomic-SNPs were identified in 12 peanut varieties by aligning the sequence of A. hypogaea with diploid progenitors. The average frequency of sequence polymorphism was higher for genomic-SNPs than the EST-SNPs with one genomic-SNP every 1011 bp as compared to one EST-SNP every 2557 bp. In order to estimate the potential and further applicability of these identified SNPs, 96 peanut varieties were genotyped using high resolution melting (HRM) method. Polymorphism information content (PIC) values for EST-SNPs ranged between 0.021 and 0.413 with a mean of 0.172 in the set of peanut varieties, while genomic-SNPs ranged between 0.080 and 0.478 with a mean of 0.249. Total 33 SNPs were used for polymorphism detection among the parents and 10 selected lines from mapping population Y13Zh (Zhenzhuhei × Yueyou13). Of the total 33 SNPs, nine SNPs showed polymorphism in the mapping population Y13Zh, and seven SNPs were successfully mapped into five linkage groups. Our results showed that SNPs can be identified in allotetraploid peanut with high accuracy through amplicon sequencing and HRM assay. The identified SNPs were very informative and can be used for different genetic and breeding applications in peanut. [ABSTRACT FROM AUTHOR]