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Peanut is a vital source of protein, particularly in the tropical regions of Asian and African countries. About three-quarters of peanut production occurs worldwide in arid and semi-arid regions, making drought an important concern in peanut production. In the US about two-thirds of peanuts are grown in non-irrigated lands, where drought accounts for 50 million USD loss each year. The looming threat of climate change exacerbates this situation by increasing erratic rainfall. Drought not only reduces yield but also degrades product quality. Peanuts under drought stress exhibit higher levels of pre-harvest aflatoxin contamination, a toxic fungal metabolite detrimental to both humans and animals. One way to sustain peanut production in drought-prone regions and address pre-harvest aflatoxin contamination is by developing drought-tolerant peanut cultivars, a process that can be accelerated by understanding the underlying physiological and genetic mechanisms for tolerance to drought stress. Different physiological attributes and genetic regions have been identified in drought-tolerant cultivars that help them cope with drought stress. The advent of precise genetic studies, artificial intelligence, high-throughput phenotyping, bioinformatics, and data science have significantly improved drought studies in peanuts. Yet, breeding peanuts for drought tolerance is often a challenge as it is a complex trait significantly affected by environmental conditions. Besides technological advancements, the success of drought-tolerant cultivar development also relies on the identification of suitable germplasm and the conservation of peanut genetic variation.

Peanut, also known as groundnut (Arachis hypogaea L.), is an important oilseed and food crop globally, contributing significantly to the economy and food security. However, its productivity is often hampered by pests and diseases. Traditional breeding methods have been used to develop resistant cultivars, but these are often time-consuming and labor-intensive. Recent technological advancements have revolutionized the identification of novel resistance sources and the development of resistant peanut cultivars. This review explores the latest techniques and approaches used in peanut breeding for pest and disease resistance, focusing on the identification of resistance loci and their incorporation into peanut using marker-assisted selection (MAS) and genomic tools. Next-generation sequencing (NGS) technologies, bioinformatics pipelines, comparative genomics, and transcriptomics have helped identify a plethora of candidate genes involved in pest resistance. However, peanut lags behind other cereal crops in terms of phenomics and precision genetic techniques for their functional validation. In conclusion, recent technological advancements have significantly improved the efficiency and precision of peanut breeding for pest and disease resistance and hold great promise for developing durable and sustainable resistance in peanut cultivars, ultimately benefiting peanut farmers and consumers globally.

Peanut stem rot (also known as white mold), caused by the fungus Athelia rolfsii, is one of the most damaging soilborne pathogens for U.S. peanut production. The disease is mainly controlled by fungicides and by adopting cultivars with moderate resistance. Field evaluation is the main approach for evaluating plant resistance, but it is costly and labor-intensive. Reliable methods for in vitro or greenhouse evaluations are desirable. Greenhouse, growth chamber, and in vitro methods have been tried to assess resistance, but they generally do not correlate well with field results. In this study, we developed a reliable method to assess resistance to stem rot on peanut under greenhouse conditions. Stem cuttings were taken from 60-day-old plants and placed into a cup filled with potting mix. Cuttings were inoculated with active A. rolfsii mycelial plugs above the soil line, with mycelium directly contacting the stem. Inoculated cuttings were put in a mist chamber to keep humidity high. Highly significant differences in disease resistance among genotypes were found at 7 days after inoculation (P < 0.05). Moreover, evaluations done at 3, 5, 7, and 9 days after inoculation and the area under the disease progress curve were significantly correlated with field evaluations of the same genotypes. This greenhouse assay is a step forward to screen peanut germplasm more efficiently for stem rot resistance. [Figure: see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.

Abstract In addition to the challenge of meeting global demand for food production, there are increasing concerns about food safety and the need to protect consumer health from the negative effects of foodborne allergies. Certain bio‐molecules (usually proteins) present in food can act as allergens that trigger unusual immunological reactions, with potentially life‐threatening consequences. The relentless working lifestyles of the modern era often incorporate poor eating habits that include readymade prepackaged and processed foods, which contain additives such as peanuts, tree nuts, wheat, and soy‐based products, rather than traditional home cooking. Of the predominant allergenic foods (soybean, wheat, fish, peanut, shellfish, tree nuts, eggs, and milk), peanuts (Arachis hypogaea) are the best characterized source of allergens, followed by tree nuts (Juglans regia, Prunus amygdalus, Corylus avellana, Carya illinoinensis, Anacardium occidentale, Pistacia vera, Bertholletia excels), wheat (Triticum aestivum), soybeans (Glycine max), and kidney beans (Phaseolus vulgaris). The prevalence of food allergies has risen significantly in recent years including chance of accidental exposure to such foods. In contrast, the standards of detection, diagnosis, and cure have not kept pace and unfortunately are often suboptimal. In this review, we mainly focus on the prevalence of allergies associated with peanut, tree nuts, wheat, soybean, and kidney bean, highlighting their physiological properties and functions as well as considering research directions for tailoring allergen gene expression. In particular, we discuss how recent advances in molecular breeding, genetic engineering, and genome editing can be used to develop potential low allergen food crops that protect consumer health.

Abstract 'Runner' and 'Virginia', the two main market types of Arachis hypogaea subspecies hypogaea, differ in several agricultural and industrial characteristics. One such trait is time to maturation (TTM), contributing to the specific environmental adaptability of each subspecies. However, little is known regarding TTM's genetic and molecular control in peanut in general, and particularly in the Runner/Virginia background. Here, a recombinant inbred line population, originating from a cross between an early-maturing Virginia and a late-maturing Runner type, was used to detect quantitative trait loci (QTL) for maturity. An Arachis SNP-array was used for genotyping, and a genetic map with 1425 SNP loci spanning 24 linkage groups was constructed. Six significant QTLs were identified for the maturity index (MI) trait on chromosomes A04, A08, B02 and B04. Two sets of stable QTLs in the same loci were identified, namely qMIA04a,b and qMIA08_2a,b with 11.5%, 8.1% and 7.3%, 8.2% of phenotypic variation explained respectively in two environments. Interestingly, one consistent QTL, qMIA04a,b, overlapped with the previously reported QTL in a Virginia × Virginia population having the same early-maturing parent ('Harari') in common. The information and materials generated here can promote informed targeting of peanut idiotypes by indirect marker-assisted selection.

Root nodule symbiosis (RNS) is the pillar behind sustainable agriculture and plays a pivotal role in the environmental nitrogen cycle. Most of the genetic, molecular, and cell-biological knowledge on RNS comes from model legumes that exhibit a root-hair mode of bacterial infection, in contrast to the Dalbergoid legumes exhibiting crack-entry of rhizobia. As a step toward understanding this important group of legumes, we have combined microscopic analysis and temporal transcriptome to obtain a dynamic view of plant gene expression during Arachis hypogaea (peanut) nodule development. We generated comprehensive transcriptome data by mapping the reads to A. hypogaea, and two diploid progenitor genomes. Additionally, we performed BLAST searches to identify nodule-induced yet-to-be annotated peanut genes. Comparison between peanut, Medicago truncatula, Lotus japonicus, and Glycine max showed upregulation of 61 peanut orthologs among 111 tested known RNS-related genes, indicating conservation in mechanisms of nodule development among members of the Papilionoid family. Unlike model legumes, recruitment of class 1 phytoglobin-derived symbiotic hemoglobin (SymH) in peanut indicates diversification of oxygen-scavenging mechanisms in the Papilionoid family. Finally, the absence of cysteine-rich motif-1-containing nodule-specific cysteine-rich peptide (NCR) genes but the recruitment of defensin-like NCRs suggest a diverse molecular mechanism of terminal bacteroid differentiation. In summary, our work describes genetic conservation and diversification in legume–rhizobia symbiosis in the Papilionoid family, as well as among members of the Dalbergoid legumes.[Graphic: see text] Copyright © 2022 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Early leaf spot (ELS) and late leaf spot (LLS) diseases are the two most destructive groundnut diseases in Ghana resulting in ≤ 70% yield losses which is controlled largely by chemical method. To develop leaf spot resistant varieties, the present study was undertaken to identify single nucleotide polymorphism (SNP) markers and putative candidate genes underlying both ELS and LLS. In this study, six multi-locus models of genome-wide association study were conducted with the best linear unbiased predictor obtained from 294 African groundnut germplasm screened for ELS and LLS as well as image-based indices of leaf spot diseases severity in 2020 and 2021 and 8,772 high-quality SNPs from a 48 K SNP array Axiom platform. Ninety-seven SNPs associated with ELS, LLS and five image-based indices across the chromosomes in the 2 two sub-genomes. From these, twenty-nine unique SNPs were detected by at least two models for one or more traits across 16 chromosomes with explained phenotypic variation ranging from 0.01 - 62.76%, with exception of chromosome (Chr) 08 (Chr08), Chr10, Chr11, and Chr19. Seventeen potential candidate genes were predicted at ± 300 kbp of the stable/prominent SNP positions (12 and 5, down- and upstream, respectively). The results from this study provide a basis for understanding the genetic architecture of ELS and LLS diseases in African groundnut germplasm, and the associated SNPs and predicted candidate genes would be valuable for breeding leaf spot diseases resistant varieties upon further validation.

Abstract Apomixis, a type of asexual reproduction in angiosperms, results in progenies that are genetically identical to the mother plant. It is a highly desirable trait in agriculture due to its potential to preserve heterosis of F1 hybrids through subsequent generations. However, no major crops are apomictic. Deciphering mechanisms underlying apomixis becomes one of the alternatives to engineer self-reproducing capability into major crops. Parthenogenesis, a major component of apomixis, commonly described as the ability to initiate embryo formation from the egg cell without fertilization, also can be valuable in plant breeding for doubled haploid production. A deeper understanding of transcriptional differences between parthenogenetic and sexual or non-parthenogenetic eggs can assist with pathway engineering. By conducting laser capture microdissection-based RNA-seq on sexual and parthenogenetic egg cells on the day of anthesis, a de novo transcriptome for the Cenchrus ciliaris egg cells was created, transcriptional profiles that distinguish the parthenogenetic egg from its sexual counterpart were identified, and functional roles for a few transcription factors in promoting natural parthenogenesis were suggested. These transcriptome data expand upon previous gene expression studies and will be a resource for future research on the transcriptome of egg cells in parthenogenetic and sexual genotypes.

Abstract Background Time-to-maturation (TTM) is an important trait contributing to adaptability, yield and quality in peanut (Arachis hypogaea L). Virginia market-type peanut belongs to the late-maturing A. hypogaea subspecies with considerable variation in TTM within this market type. Consequently, planting and harvesting schedule of peanut cultivars, including Virginia market-type, need to be optimized to maximize yield and grade. Little is known regarding the genetic control of TTM in peanut due to the challenge of phenotyping and limited DNA polymorphism. Here, we investigated the genetic control of TTM within the Virginia market-type peanut using a SNP-based high-density genetic map. A recombinant inbred line (RIL) population, derived from a cross between two Virginia-type cultivars ‘Hanoch’ and ‘Harari’ with contrasting TTM (12–15 days on multi-years observations), was phenotyped in the field for 2 years following a randomized complete block design. TTM was estimated by maturity index (MI). Other agronomic traits like harvest index (HI), branching habit (BH) and shelling percentage (SP) were recorded as well. Results MI was highly segregated in the population, with 13.3–70.9% and 28.4–80.2% in years 2018 and 2019. The constructed genetic map included 1833 SNP markers distributed on 24 linkage groups, covering a total map distance of 1773.5 cM corresponding to 20 chromosomes on the tetraploid peanut genome with 1.6 cM mean distance between the adjacent markers. Thirty QTL were identified for all measured traits. Among the four QTL regions for MI, two consistent QTL regions (qMIA04a,b and qMIB03a,b) were identified on chromosomes A04 (118680323–125,599,371; 6.9Mbp) and B03 (2839591–4,674,238; 1.8Mbp), with LOD values of 5.33–6.45 and 5–5.35 which explained phenotypic variation of 9.9–11.9% and 9.3–9.9%, respectively. QTL for HI were found to share the same loci as MI on chromosomes B03, B05, and B06, demonstrating the possible pleiotropic effect of HI on TTM. Significant but smaller effects on MI were detected for BH, pod yield and SP. Conclusions This study identified consistent QTL regions conditioning TTM for Virginia market-type peanut. The information and materials generated here can be used to further develop molecular markers to select peanut idiotypes suitable for diverse growth environments.

Modern plant breeding programs rely heavily on the generation of homozygous lines, with the traditional process requiring the inbreeding of a heterozygous cross for five to six generations. Doubled haploid (DH) technology, a process of generating haploid plants from an initial heterozygote, followed by chromosome doubling, reduces the process to two generations. Currently established in vitro methods of haploid induction include androgenesis and gynogenesis, while in vivo methods are based on uni-parental genome elimination. Parthenogenesis, embryogenesis from unfertilized egg cells, presents another potential method of haploid induction. PsASGR-BABY BOOM-like, an AP2 transcription factor, induces parthenogenesis in a natural apomictic species, Pennisetum squamulatum (Cenchrus squamulatus) and PsASGR-BBML transgenes promote parthenogenesis in several crop plants, including rice, maize, and pearl millet. The dominant nature of PsASGR-BBML transgenes impedes their use in DH technology. Using a glucocorticoid-based post-translational regulation system and watering with a 100 μM DEX solution before anthesis, PsASGR-BBML can be regulated at the flowering stage to promote parthenogenesis. Conditional expression presents a novel opportunity to use parthenogenetic genes in DH production technology and to elucidate the molecular mechanism underlying parthenogenetic embryogenesis.

The combination of apomixis and hybrid production is hailed as the holy grail of agriculture for the ability of apomixis to fix heterosis of F1 hybrids in succeeding generations, thereby eliminating the need for repeated crosses to produce F1 hybrids. Apomixis, asexual reproduction through seed, achieves this feat by circumventing two processes that are fundamental to sexual reproduction (meiosis and fertilization) and replacing them with apomeiosis and parthenogenesis, resulting in seeds that are clonal to the maternal parent. Parthenogenesis, embryo development without fertilization, has been genetically engineered in rice, maize, and pearl millet using PsASGR-BABY BOOM-like (PsASGR-BBML) transgenes and in rice using the OsBABY BOOM1 (OsBBM1) cDNA sequence when expressed under the control of egg cell-specific promoters. A phylogenetic analysis revealed that BABY BOOM (BBM)/BBML genes from monocots cluster within three different clades. The BBM/BBML genes shown to induce parthenogenesis cluster within clade 1 (the ASGR-BBML clade) along with orthologs from other monocot species, such as Setaria italica. For this study, we tested the parthenogenetic potential of three BBM transgenes from S. italica, each a member of a different phylogenetic BBM clade. All transgenes were genomic constructs under the control of the AtDD45 egg cell-specific promoter. All SiBBM transgenes induced various levels of parthenogenetic embryo development, resulting in viable haploid T1 seedlings. Poor seed set and lower haploid seed production were characteristics of multiple transgenic lines. The results presented in this study illustrate that further functional characterization of BBMs in zygote/embryo development is warranted.

Cultivated peanut (Arachis hypogaea) is an important oil, food, and feed crop worldwide. The USDA peanut germplasm collection currently contains 8,982 accessions. In the 1990s, 812 accessions were selected as a core collection on the basis of phenotype and country of origin. The present study reports genotyping results for the entire available core collection. Each accession was genotyped with the Arachis_Axiom2 SNP array, yielding 14,430 high-quality, informative SNPs across the collection. Additionally, a subset of 253 accessions was replicated, using between two and five seeds per accession, to assess heterogeneity within these accessions. The genotypic diversity of the core is mostly captured in five genotypic clusters, which have some correspondence with botanical variety and market type. There is little genetic clustering by country of origin, reflecting peanut’s rapid global dispersion in the 18th and 19th centuries. A genetic cluster associated with the hypogaea/aequatoriana/peruviana varieties, with accessions coming primarily from Bolivia, Peru, and Ecuador, is consistent with these having been the earliest landraces. The genetics, phenotypic characteristics, and biogeography are all consistent with previous reports of tetraploid peanut originating in Southeast Bolivia. Analysis of the genotype data indicates an early genetic radiation, followed by regional distribution of major genetic classes through South America, and then a global dissemination that retains much of the early genetic diversity in peanut. Comparison of the genotypic data relative to alleles from the diploid progenitors also indicates that subgenome exchanges, both large and small, have been major contributors to the genetic diversity in peanut.

Efforts in genome sequencing in the Aspergillus genus have led to the development of quality reference genomes for several important species including A. nidulans, A. fumigatus, and A. oryzae. However, less progress has been made for A. flavus. As part of the effort of the USDA-ARS Annual Aflatoxin Workshop Fungal Genome Project, the isolate NRRL3357 was sequenced and resulted in a scaffold-level genome released in 2005. Our goal has been biologically driven, focusing on two areas: isolate variation in aflatoxin production and drought stress exacerbating aflatoxin production by A. flavus. Therefore, we developed two reference pseudomolecule genome assemblies derived from chromosome arms for two isolates: AF13, a MAT1-2, highly stress tolerant, and highly aflatoxigenic isolate; and NRRL3357, a MAT1-1, less stress tolerant, and moderate aflatoxin producer in comparison to AF13. Here, we report these two reference-grade assemblies for these isolates through a combination of PacBio long-read sequencing and optical mapping, and coupled them with comparative, functional, and phylogenetic analyses. This analysis resulted in the identification of 153 and 45 unique genes in AF13 and NRRL3357, respectively. We also confirmed the presence of a unique 310 Kb insertion in AF13 containing 60 genes. Analysis of this insertion revealed the presence of a bZIP transcription factor, named atfC, which may contribute to isolate pathogenicity and stress tolerance. Phylogenomic analyses comparing these and other available assemblies also suggest that the species complex of A. flavus is polyphyletic.

Although seed and pod traits are important for peanut breeding, little is known about the inheritance of these traits. A recombinant inbred line (RIL) population of 156 lines from a cross of Tifrunner x NC 3033 was genotyped with the Axiom_Arachis1 SNP array and SSRs to generate a genetic map composed of 1524 markers in 29 linkage groups (LG). The genetic positions of markers were compared with their physical positions on the peanut genome to confirm the validity of the linkage map and explore the distribution of recombination and potential chromosomal rearrangements. This linkage map was then used to identify Quantitative Trait Loci (QTL) for seed and pod traits that were phenotyped over three consecutive years for the purpose of developing trait-associated markers for breeding. Forty-nine QTL were identified in 14 LG for seed size index, kernel percentage, seed weight, pod weight, single-kernel, double-kernel, pod area and pod density. Twenty QTL demonstrated phenotypic variance explained (PVE) greater than 10% and eight more than 20%. Of note, seven of the eight major QTL for pod area, pod weight and seed weight (PVE >20% variance) were attributed to NC 3033 and located in a single linkage group, LG B06_1. In contrast, the most consistent QTL for kernel percentage were located on A07/B07 and derived from Tifrunner.

We deployed field-based high-throughput phenotyping (HTP) techniques to acquire trait data for a subset of a peanut chromosome segment substitution line (CSSL) population. Sensors mounted on an unmanned aerial vehicle (UAV) were used to derive various vegetative indices as well as canopy temperatures. A combination of aerial imaging and manual scoring showed that CSSL 100, CSSL 84, CSSL 111, and CSSL 15 had remarkably low tomato spotted wilt virus (TSWV) incidence, a devastating disease in South Georgia, USA. The four lines also performed well under leaf spot pressure. The vegetative indices showed strong correlations of up to 0.94 with visual disease scores, indicating that aerial phenotyping is a reliable way of selecting under disease pressure. Since the yield components of peanut are below the soil surface, we deployed ground penetrating radar (GPR) technology to detect pods non-destructively. Moderate correlations of up to 0.5 between pod weight and data acquired from GPR signals were observed. Both the manually acquired pod data and GPR variables highlighted the three lines, CSSL 84, CSSL 100, and CSSL 111, as the best-performing lines, with pod weights comparable to the cultivated check Tifguard. Through the combined application of manual and HTP techniques, this study reinforces the premise that chromosome segments from peanut wild relatives may be a potential source of valuable agronomic traits.

Crop wild species are increasingly important for crop improvement. Peanut (Arachis hypogaea L.) wild relatives comprise a diverse genetic pool that is being used to broaden its narrow genetic base. Peanut is an allotetraploid species extremely susceptible to peanut root-knot nematode (PRKN) Meloidogyne arenaria. Current resistant cultivars rely on a single introgression for PRKN resistance incorporated from the wild relative Arachis cardenasii, which could be overcome as a result of the emergence of virulent nematode populations. Therefore, new sources of resistance may be needed. Near-immunity has been found in the peanut wild relative Arachis stenosperma. The two loci controlling the resistance, present on chromosomes A02 and A09, have been validated in tetraploid lines and have been shown to reduce nematode reproduction by up to 98%. To incorporate these new resistance QTL into cultivated peanut, we used a marker-assisted backcrossing approach, using PRKN A. stenosperma-derived resistant lines as donor parents. Four cycles of backcrossing were completed, and SNP assays linked to the QTL were used for foreground selection. In each backcross generation seed weight, length, and width were measured, and based on a statistical analysis we observed that only one generation of backcrossing was required to recover the elite peanut’s seed size. A populating of 271 BC3F1 lines was genome-wide genotyped to characterize the introgressions across the genome. Phenotypic information for leaf spot incidence and domestication traits (seed size, fertility, plant architecture, and flower color) were recorded. Correlations between the wild introgressions in different chromosomes and the phenotypic data allowed us to identify candidate regions controlling these domestication traits. Finally, PRKN resistance was validated in BC3F3 lines. We observed that the QTL in A02 and/or large introgression in A09 are needed for resistance. This present work represents an important step toward the development of new high-yielding and nematode-resistant peanut cultivars.

AbstractThe fatty acid composition of seed oil is a major determinant of the flavor, shelf-life, and nutritional quality of peanuts. Major QTLs controlling high oil content, high oleic content, and low linoleic content have been characterized in several seed oil crop species. Here, we employ genome-wide association approaches on a recently genotyped collection of 787 plant introduction accessions in the USDA peanut core collection, plus selected improved cultivars, to discover markers associated with the natural variation in fatty acid composition, and to explain the genetic control of fatty acid composition in seed oils. Overall, 251 single nucleotide polymorphisms (SNPs) had significant trait associations with the measured fatty acid components. Twelve SNPs were associated with two or three different traits. Of these loci with apparent pleiotropic effects, 10 were associated with both oleic (C18:1) and linoleic acid (C18:2) content at different positions in the genome. In all 10 cases, the favorable allele had an opposite effect—increasing and lowering the concentration, respectively, of oleic and linoleic acid. The other traits with pleiotropic variant control were palmitic (C16:0), behenic (C22:0), lignoceric (C24:0), gadoleic (C20:1), total saturated, and total unsaturated fatty acid content. One hundred (100) of the significantly associated SNPs were located within 1000 kbp of 55 genes with fatty acid biosynthesis functional annotations. These genes encoded, among others: ACCase carboxyl transferase subunits, and several fatty acid synthase II enzymes. With the exception of gadoleic (C20:1) and lignoceric (C24:0) acid content, which occur at relatively low abundance in cultivated peanuts, all traits had significant SNP interactions exceeding a stringent Bonferroni threshold (αP

Abstract Background Due to the recent domestication of peanut from a single tetraploidization event, relatively little genetic diversity underlies the extensive morphological and agronomic diversity in peanut cultivars today. To broaden the genetic variation in future breeding programs, it is necessary to characterize germplasm accessions for new sources of variation and to leverage the power of genome-wide association studies (GWAS) to discover markers associated with traits of interest. We report an analysis of linkage disequilibrium (LD), population structure, and genetic diversity, and examine the ability of GWA to infer marker-trait associations in the U.S. peanut mini core collection genotyped with a 58 K SNP array. Results LD persists over long distances in the collection, decaying to r 2 = half decay distance at 3.78 Mb. Structure within the collection is best explained when separated into four or five groups (K = 4 and K = 5). At K = 4 and 5, accessions loosely clustered according to market type and subspecies, though with numerous exceptions. Out of 107 accessions, 43 clustered in correspondence to the main market type subgroup whereas 34 did not. The remaining 30 accessions had either missing taxonomic classification or were classified as mixed. Phylogenetic network analysis also clustered accessions into approximately five groups based on their genotypes, with loose correspondence to subspecies and market type. Genome wide association analysis was performed on these lines for 12 seed composition and quality traits. Significant marker associations were identified for arachidic and behenic fatty acid compositions, which despite having low bioavailability in peanut, have been reported to raise cholesterol levels in humans. Other traits such as blanchability showed consistent associations in multiple tests, with plausible candidate genes. Conclusions Based on GWA, population structure as well as additional simulation results, we find that the primary limitations of this collection for GWAS are a small collection size, significant remaining structure/genetic similarity and long LD blocks that limit the resolution of association mapping. These results can be used to improve GWAS in peanut in future studies – for example, by increasing the size and reducing structure in the collections used for GWAS.

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.

AbstractGenome instability in newly synthesized allotetraploids of peanut has breeding implications that have not been fully appreciated. Synthesis of wild species-derived neo-tetraploids offers the opportunity to broaden the gene pool of peanut; however, the dynamics among the newly merged genomes creates predictable and unpredictable variation. Selfed progenies from the neo-tetraploid Arachis ipaënsisArachis correntinaA. ipaënsisA. correntina4x12A. hypogaeaA. ipaënsisA. correntina4xArachisA. ipaënsisA. correntina012A. hypogaeaA. ipaënsisA. correntina4x2

Cultivated peanut (Arachis hypogaea L.) forms root nodules to enable a symbiotic relationship with rhizobia for biological nitrogen fixation. To understand the genetic factors of peanut nodulation, it is fundamental to genetically map and clone the genes involved in nodulation. For genetic mapping, high throughput genotyping with a large number of polymorphic markers is critical. In this study, two sets of sister recombinant inbred lines (RILs), each containing a nodulating (Nod+) and non-nodulating (Nod-) line, and their Nod+ parental lines were extensively genotyped. Several next generation sequencing (NGS) methods including target enrichment sequencing (TES), RNA-sequencing (RNA-seq), genotyping by sequencing (GBS), and the 48K Axiom Arachis2 SNP array, and various analysis pipelines were applied to identify single nucleotide polymorphisms (SNP) among the two sets of RILs and their parents. TES revealed the largest number of homozygous SNPs (15,947) between the original parental lines, followed by the Axiom Arachis2 SNP array (1,887), RNA-seq (1,633), and GBS (312). Among the five SNP analysis pipelines applied, the alignment to A/B genome followed by HAPLOSWEEP revealed the largest number of homozygous SNPs and highest concordance rate (79%) with the array. A total of 222 and 1,200 homozygous SNPs were polymorphic between the Nod+ and Nod− sister RILs and between their parents, respectively. A graphical genotype map of the sister RILs was constructed with these SNPs, which demonstrated the candidate genomic regions harboring genes controlling nodulation across the whole genome. Results of this study mainly provide the pros and cons of NGS and SNP genotyping platforms for genetic mapping in peanut, and also provide potential genetic resources to narrow down the genomic regions controlling peanut nodulation, which would lay the foundation for gene cloning and improvement of nitrogen fixation in peanut.

Abstract Background Pod constriction is an important descriptive and agronomic trait of peanut. For the in-shell Virginia marketing-type, this trait has commercial importance as well, since deeply constricted pods have a tendency to break, which makes them unmarketable. Classical genetic studies have indicated that pod constriction in peanut is controlled by one to four genes, depending on the genetic background. In all of those studies, pod constriction was evaluated visually as opposed to quantitatively. Here, we examined the genetic nature of this trait in the Virginia-type background. Our study involved 195 recombinant inbred lines (F7RILs) derived from two closely related cultivars that differ in their degree of pod constriction. Pod constriction was evaluated visually and quantitatively in terms of the pod constriction index (PCI), calculated as the average ratio between the pod’s waist and shoulders. Results ANOVA and genetic parameters for PCI among the F7RILs in three blocks showed very significant genotypic effect (p(F)

Blanchability is an often overlooked, but important trait for peanut breeding. The process of blanching, removing the skin, is an important step in the processing of raw nuts for manufacturing. Under strong genetic control and requiring considerable effort to phenotype, blanchability is conducive for marker-assisted selection. We used QTL sequencing (QTL-seq) to identify two QTLs related to blanchability using previously phenotyped breeding populations. To validate the QTLs, we show that two markers can select for significantly increased blanchability in an independent recombinant inbred line (RIL) population. Two wild introgressions from Arachis cardenasii conferring strong disease resistance were segregated in the population and were found to negatively impact blanchability. Finally, we show that by utilizing highly accurate sequence analysis pipelines, low coverage sequencing can be used to genotype whole populations with increased power and precision. This study highlights the potential to mine breeding data to identify and develop useful markers for genetic improvement programs, and provide powerful tools for breeding for processing and quality traits.

Abstract Resistance to root-knot nematode was introgressed into cultivated peanut Arachis hypogaea from a wild peanut relative, A. cardenasii and previously mapped to chromosome A09. The highly resistant recombinant inbred RIL 46 and moderately resistant RIL 48 were selected from a population with cv. Gregory (susceptible) and Tifguard (resistant) as female and male parents, respectively. RNA-seq analysis was performed on these four genotypes using root tissue harvested from root-knot nematode infected plants at 0, 3, 7 days after inoculation. Differential gene expression analysis provides evidence that root-knot nematodes modulate biological pathways involved in plant hormone, defense, cell signaling, cytoskeleton and cell wall metabolism in a susceptible reaction. Corresponding to resistance reaction, an effector-induced-immune response mediated by an R-gene was identified in Tifguard. Mapping of the introgressed region indicated that 92% of linkage group A09 was of A. cardenasii origin in Tifguard. RIL46 and RIL 48 possessed 3.6% and 83.5% of the introgression on A09, respectively. Within the small introgressed region carried by RIL 46, a constitutively expressed TIR-NBS-LRR gene was identified as the candidate for nematode resistance. Potential defense responsive pathways include effector endocytosis through clathrin-coated vesicle trafficking, defense signaling through membrane lipid metabolism and mucilage production.

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.

Single nucleotide polymorphisms (SNPs) have many advantages as molecular markers since they are ubiquitous and codominant. However, the discovery of true SNPs in polyploid species is difficult. Peanut ( L.) is an allopolyploid, which has a very low rate of true SNP calling. A large set of true and false SNPs identified from the Axiom_ 58k array was leveraged to train machine-learning models to enable identification of true SNPs directly from sequence data to reduce ascertainment bias. These models achieved accuracy rates above 80% using real peanut RNA sequencing (RNA-seq) and whole-genome shotgun (WGS) resequencing data, which is higher than previously reported for polyploids and at least a twofold improvement for peanut. A 48K SNP array, Axiom_2, was designed using this approach resulting in 75% accuracy of calling SNPs from different tetraploid peanut genotypes. Using the method to simulate SNP variation in several polyploids, models achieved >98% accuracy in selecting true SNPs. Additionally, models built with simulated genotypes were able to select true SNPs at >80% accuracy using real peanut data. This work accomplished the objective to create an effective approach for calling highly reliable SNPs from polyploids using machine learning. A novel tool was developed for predicting true SNPs from sequence data, designated as SNP machine learning (SNP-ML), using the described models. The SNP-ML additionally provides functionality to train new models not included in this study for customized use, designated SNP machine learner (SNP-MLer). The SNP-ML is publicly available.

Parthenogenesis is the spontaneous development of an embryo from an unfertilized egg cell. It naturally occurs in a variety of plant and animal species. In plants, parthenogenesis usually is found in combination with apomeiosis (the omission of meiosis) and pseudogamous or autonomous (with or without central cell fertilization) endosperm formation, together known as apomixis (clonal seed production). The initiation of embryogenesis in vivo and in vitro has high potential in plant breeding methods, particularly for the instant production of homozygous lines from haploid gametes [doubled haploids (DHs)], the maintenance of vigorous F1-hybrids through clonal seed production after combining it with apomeiosis, reverse breeding approaches, and for linking diploid and polyploid gene pools. Because of this large interest, efforts to identify gene(s) for parthenogenesis from natural apomicts have been undertaken by using map-based cloning strategies and comparative gene expression studies. In addition, engineering parthenogenesis in sexual model species has been investigated via mutagenesis and gain-of-function strategies. These efforts have started to pay off, particularly by the isolation of the PsASGR-BabyBoom-Like from apomictic Pennisetum, a gene proven to be transferable to and functional in sexual pearl millet, rice, and maize. This review aims to summarize the current knowledge on parthenogenesis, the possible gene candidates also outside the grasses, and the use of these genes in plant breeding protocols. It shows that parthenogenesis is able to inherit and function independently from apomeiosis and endosperm formation, is expressed and active in the egg cell, and can induce embryogenesis in polyploid, diploid as well as haploid egg cells in plants. It also shows the importance of genes involved in the suppression of transcription and modifications thereof at one hand, and in embryogenesis for which transcription is allowed or artificially overexpressed on the other, in parthenogenetic reproduction. Finally, it emphasizes the importance of functional endosperm to allow for successful embryo growth and viable seed production.

Accurate identification of polymorphisms from sequence data is crucial to unlocking the potential of high throughput sequencing for genomics. Single nucleotide polymorphisms (SNPs) are difficult to accurately identify in polyploid crops due to the duplicative nature of polyploid genomes leading to low confidence in the true alignment of short reads. Implementing a haplotype-based method in contrasting subgenome-specific sequences leads to higher accuracy of SNP identification in polyploids. To test this method, a large-scale 48K SNP array (Axiom Arachis2) was developed for Arachis hypogaea (peanut), an allotetraploid, in which 1,674 haplotype-based SNPs were included. Results of the array show that 74% of the haplotype-based SNP markers could be validated, which is considerably higher than previous methods used for peanut. The haplotype method has been implemented in a standalone program, HAPLOSWEEP, which takes as input bam files and a vcf file and identifies haplotype-based markers. Haplotype discovery can be made within single reads or span paired reads, and can leverage long read technology by targeting any length of haplotype. Haplotype-based genotyping is applicable in all allopolyploid genomes and provides confidence in marker identification and in silico-based genotyping for polyploid genomics.

Late leaf spot (LLS; Cercosporidium personatum) is a major fungal disease of cultivated peanut (Arachis hypogaea). A recombinant inbred line population segregating for quantitative field resistance was used to identify quantitative trait loci (QTL) using QTL-seq. High rates of false positive SNP calls using established methods in this allotetraploid crop obscured significant QTLs. To resolve this problem, robust parental SNPs were first identified using polyploid-specific SNP identification pipelines, leading to discovery of significant QTLs for LLS resistance. These QTLs were confirmed over 4 years of field data. Selection with markers linked to these QTLs resulted in a significant increase in resistance, showing that these markers can be immediately applied in breeding programs. This study demonstrates that QTL-seq can be used to rapidly identify QTLs controlling highly quantitative traits in polyploid crops with complex genomes. Markers identified can then be deployed in breeding programs, increasing the efficiency of selection using molecular tools.Key Message: Field resistance to late leaf spot is a quantitative trait controlled by many QTLs. Using polyploid-specific methods, QTL-seq is faster and more cost effective than QTL mapping.

The advent of the genome sequences of Arachis duranensis and Arachis ipaensis has ushered in a new era for peanut genomics. With the goal of producing a gene atlas for cultivated peanut (Arachis hypogaea), 22 different tissue types and ontogenies that represent the full development of peanut were sequenced, including a complete reproductive series from flower to peg elongation and peg tip immersion in the soil to fully mature seed. Using a genome-guided assembly pipeline, a homeolog-specific transcriptome assembly for Arachis hypogaea was assembled and its accuracy was validated. The assembly was used to annotate 21 developmental co-expression networks as tools for gene discovery. Using a set of 8,816 putative homeologous gene pairs, homeolog expression bias was documented, and although bias was mostly balanced, there were striking differences in expression bias in a tissue-specific context. Over 9,000 alterative splicing events and over 6,000 non coding RNAs were further identified and profiled in a developmental context. Together, this work represents a major new resource for cultivated peanut and will be integrated into peanutbase.org as an available resource for all peanut researchers.