Development and Genetic Characterization of Peanut Advanced Backcross Lines That Incorporate Root-Knot Nematode Resistance From Arachis stenosperma

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.

Introduction

Arachis hypogaea L., with a common name of peanut or groundnut, is an important oil, food, and fodder crop cultivated worldwide with an annual production of 66.3 million tons and grown on 34.1 Mha (FAOSTAT, 2021). Peanut is an allotetraploid species (AABB, 2n = 4x = 40), with a recent and unique polypoid origin, which occurred 5 to 10 thousand years ago (Bertioli et al., 2019, 2020). This narrow genetic base and limited gene flow with its genetically diverse diploid wild relatives resulted in a lack of strong resistance alleles for pests and diseases in the primary gene pool. One important pest is the peanut root-knot nematode (PRKN) (Meloidogyne arenaria) (Holbrook and Stalker, 2003). It causes yield losses greater than 50% in infested fields, and at times, 100% losses in heavily infested areas of fields have been reported (Dickson and De Waele, 2005; Timper et al., 2018). In the United States, M. arenaria is the most damaging nematode for peanut (Timper et al., 2018). Chemical control is one option, but is costly, hazardous to human health, and can damage the environment (Oka, 2020). Crop rotation is also effective, but with susceptible cultivars, the constraints on the frequency at which peanut can be grown reduce agronomic and financial sustainability. The use of high-yielding and nematode-resistant cultivars in combination with rotation is the most efficient and effective way to control nematode populations and maintain yield while reducing the use of nematicides.

Strong resistance to many pests and diseases is limited in the A. hypogaea primary gene pool (Stalker, 2017), which imposes constraints for crop improvement using cultivated germplasm (Nelson et al., 1989; Noe et al., 1992). Yet, the wild relatives comprise a diverse genetic pool that has the potential to broaden a peanut’s genetic base and to improve its performance under pest/disease pressure (Stalker, 2017). Previously, successful transfer of root-knot nematode resistance into cultivated peanut was accomplished through backcrossing schemes involving a synthetic allotetraploid (Simpson and Starr, 2001). This resistance is derived from introgression of a large segment on chromosome A09 from the wild species Arachis cardenasii (Nagy et al., 2010; Chu et al., 2016), and is present in several commercial cultivars (Georgia-14N, TifNV-High O/L, Tifguard, NemaTAM, and Webb) (Simpson et al., 2003, 2013; Holbrook et al., 2008, 2017; Branch and Brenneman, 2015). Although this resistance has been durable thus far, occasional resistance breakdown has been reported (Holbrook CC, personal communication). Therefore, it is important to incorporate new sources of resistance to reduce the risk of selection of a virulent population of M. arenaria and to guarantee continued protection of the peanut crop from losses due to PRKN.

The peanut wild relative Arachis stenosperma PI666100/V10309 has been described as highly resistant to peanut root-knot nematode (Proite et al., 2008). Previously, three quantitative trait loci (QTL) (on chromosomes A02, A04, and A09) were identified in the diploid genome of Arachis stenosperma (Leal-Bertioli et al., 2016). Later, segments of both chromosomes A02 and A09, that provide near immunity, were mapped using a segregating population derived from a cross between A. hypogaea and the synthetic allotetraploid BatSten1 (Bertioli et al., 2021a), and validated in a tetraploid background (Ballén-Taborda et al., 2019, 2021). The main objective of this study was to incorporate PRKN resistance QTL from A. stenosperma into elite peanut. To accomplish this goal, a marker-assisted backcross breeding approach was employed and BatSten1 was used as the donor parent. Four cycles of backcrossing were completed with genetic foreground and background selection and phenotypic characterization were performed in each generation. Correlations between the wild introgressions across the genome and the phenotypic data allowed us to identify candidate regions controlling traits measured in the BC₃F₁ population.

This work is key to developing new high-yielding peanut cultivars with a new and strong resistance against the peanut root-knot nematode. Additionally, single nucleotide polymorphism (SNP) markers tightly linked to the QTL are described to facilitate the introgression of A. stenosperma resistance into different elite recipient lines. In the near future, we expect to release advanced introgression lines that incorporate strong PRKN resistance with attached molecular information, that can be used directly in breeding programs in areas where PRKN is a constraint for peanut cultivation.

Materials and Methods

Plant Materials

The synthetic allotetraploid BatSten1 PI 695418 {[Arachis batizocoi PI298639/K9484 x A. stenosperma PI666100/V10309]^{(2n = 4x = 40)}} (Bertioli et al., 2021a) was used to introgress the nematode resistance QTL from A. stenosperma into tetraploid peanut. An F₂ population was created by selfing an F₁ derived from a cross between A. hypogaea cv. Runner IAC-886 (herein called Runner-886) and BatSten1, and then used for QTL mapping (Ballén-Taborda et al., 2019). From this population, four superior F₂ lines (F₂-7, F₂-13, F₂-34, and F₂-73) were selected based on (1) better vigor, as visually more leaf biomass; (2) good agronomic traits; (3) late leaf spot (LLS) and PRKN resistance; (4) harboring QTL in A02 and A09 for nematode resistance per molecular genotyping. Six F₂-derived F₃ (F_2:3) homozygous progeny from F_2:3-7 and F_2:3-34, with validated resistance to PRKN (Ballén-Taborda et al., 2021), were used as initial donor parents in a backcrossing scheme (Figure 1, red boxes). For incorporation of resistance from A. stenosperma into peanut, we used three susceptible recurrent parents, which are TifGP-2, 5-646-10, and 13-1014. For pyramiding resistances from both wild species A. stenosperma and A. cardenasii, we used two resistant lines, which are 13-2113 and 13-1125. (1) TifGP-2 is a breeding line with good yield and grade, and normal oleic content (Holbrook et al., 2012); (2) 5-646-10 is derived from the cross Florida-07 x Tifguard, with good yield and grade, and high oleic/linoleic fatty acid ratio (Holbrook, CC, unpublished data); (3) 13-1014 is derived from [C1805-617-1 (Florida-07 x Tifguard) x GA-06G], with high oleic/linoleic fatty acid ratio (Holbrook, CC, unpublished data); (4) 13-2113 is derived from [C1805-2-9-16 (Florida-07 x Tifguard) x TifGP-2], a high oleic/linoleic fatty acid ratio, that was included in the second cycle only (Holbrook, CC, unpublished data); (5) 13-1125 breeding line was included in the fourth cycle only (Holbrook, CC, unpublished data) (Figure 1, blue boxes).

FIGURE 1

Figure 1. Schematic of the marker-assisted backcrossing scheme for incorporation of peanut root-knot nematode resistance from the wild species A. stenosperma V10309 into peanut breeding lines from Tifton, GA. Superior F₂-derived F₃ lines (Ballén-Taborda et al., 2019) were selected as donor parents (DP, red boxes). Recurrent parents (RP, blue boxes) included TifGP-2, 5-646-10, 13-1014, 13-2113, and 13-1125. In each cycle, KASP genotyping was performed to identify lines carrying resistance loci in chromosomes A02 and A09 (Marker-assisted selection – MAS) (green checkmark) (Supplementary Tables 1, 2, gray-shaded markers). BC_nF_n progeny from each cycle were used as male parents for the next (orange boxes). All BC_nF_ns were genotyped for seed size (weight, length, and width) (seed symbol). BC₂F₁s were genome-wide genotyped and phenotyped for PRKN resistance for validation (green circle and nematode symbol) (Ballén-Taborda et al., 2021) and pollen viability was studied (pollen symbol). BC₃F₁s were subjected to genome-wide genotyping for characterization of introgressions (green circle) and phenotyped for leaf spot incidence, fertility, architecture, and flower color (indicated by leaf spot, brown arrow, architecture, and flower symbols, respectively). BC₃F₂s were phenotyped for leaf spot incidence, architecture, branching, and extra leaves (indicated by leaf spots, architecture, branching, and leaves symbols, respectively). BC₃F₃s were phenotyped for PRKN resistance and KASP genotyped (green checkmark and nematode symbol). Self-pollination is represented by ⊗.

Marker-Assisted Breeding

A marker-assisted backcrossing (MABC) approach was used to incorporate PRKN resistance from A. stenosperma into cultivated peanut. Four cycles of backcrossing were performed in two different locations: Athens, GA and Tifton, GA under greenhouse conditions. In the first, second, and third cycles, 16 SNP markers linked to the QTL in A02 and A09 (Leal-Bertioli et al., 2016) were used for foreground selection (Supplementary Table 1, gray-shaded markers). For the fourth cycle, 10 new markers were used to finely target these chromosome segments based on high-throughput genotyping of backcross (BC) lines (Ballén-Taborda et al., 2021) (Supplementary Table 2, gray-shaded markers). 60 additional SNPs markers were also developed and are available here for genotypic selection in breeding programs (Supplementary Tables 1, 2, not shaded markers). Progeny from each cycle that harbored segments associated with PRKN resistance were used as male parents for the next backcross cycle (Figure 1, orange boxes). BC₄F₁s were germinated for seed increase.

Kompetitive Allele-Specific PCR assays (KASP, LGC Biosearch Technologies, Hoddesdon, United Kingdom)¹ assays were used for the selection of PRKN resistance alleles. For KASP reactions, genomic DNA was isolated from a small section of the peanut cotyledon opposite to the embryo (seed chip, ∼50-100 mg). DNA was extracted using the DNeasy Plant Mini Kit (QIAGEN, Hilden, DE) according to the manufacturer’s instructions. Each KASP marker consisted of three primers per SNP position (two allele-specific and one common flanking primer). Primers were designed using the web-based program BatchPrimer3² (USDA-ARS, Albany, CA, United States) (You et al., 2008) with the “Allele-specific primers and allele flanking primers” option. Parameters used were 60–120 bp in fragment size, GC content of 30–80%, and Tm between 58 and 60°. KASP primer assay mix per SNP position consisted of 12 ul (100 uM) of each allele-specific primer, 30 ul (100 uM) of the flanking primer, and 46 ul of H₂O. Single KASP reactions (5 ul) consisted of 2.5 ul of KASP 2x Master Mix (Low Rox 5000 V4.0), 0.07 ul of KASP primer assay mix, 1.93 ul of water, and 0.5 ul of DNA (10 ng/ul). Two replicates per primer per sample were included in each reaction, as well as no-template controls (NTCs). A C100 touch Thermal Cycler (BIO-RAD, Hercules, CA, United States) was used with the following conditions: 94°C for 15 min; 8 cycles of 94°C for 20 s and touchdown starting at 61°C for 1 min (dropping 6° per cycle); 31 cycles of 94°C for 10 s and 55°C for 1 min; 9 cycles of 94°C for 20 s, and 57°C for 1 min; 4°C hold. Fluorescence was read with a LightCycler^® 480 Instrument II (Roche Life Science, Switzerland) and analyzed using the LightCycler^® 480 Software (v.1.5.1.62) (Roche Life Science, Switzerland). Finally, data were exported into Microsoft Excel for analysis.

Genome-Wide Genotyping of BC₃F₁s

Genomic DNA of 271 BC₃F₁ lines and controls (BatSten1, Runner-886, 5-646-10, 13-1014, TifGP-2, Tifguard, and Tifrunner) were extracted from lyophilized leaves using the DNeasy 96 Plant Kit (QIAGEN, Hilden, DE, United States) according to the manufacturer’s instructions. DNAs were genotyped with the Axiom_Arachis2 SNP array (Clevenger et al., 2018; Korani et al., 2019). Genotypic data was extracted and processed using the Axiom™ Analysis Suite software (v.4.0.3.3) (ThermoFisher Scientific, Waltham, MA, United States). Output was analyzed using custom shell scripts (see below) and resulting data were visualized as a color map in Microsoft Excel. The physical positions of the A-genome markers were determined according to the position of their orthologs in the A. duranensis pseudomolecules and the K-genome markers based on the A. ipaensis pseudomolecules (Bertioli et al., 2016).

The strategy to identify polymorphic SNP markers included two main steps. First, a set of polymorphic SNP markers between parental genotypes (BatSten1 ≠ Runner-886) was extracted. Original genotyping calls were replaced by numbers (“1” for BatSten, “2” for Runner-886, and “3” for a different genotype). Second, SNPs present in the genetic map previously identified (A. stenosperma-specific and A. batizocoi-specific markers) (Ballén-Taborda et al., 2019) were retrieved (Supplementary Script 1). Genotypic data were used to perform the principal component analysis (PCA) using the “dist” function in R.

Peanut Root-Knot Nematode Resistance Validation Using BC₃F₃s

BC₃F₃ segregating lines from five BC₃F₁ families and controls were evaluated for PRKN resistance to further validate the QTL in A02 and/or A09 (Table 1). The experiment included 72 BC₃F₃ lines, which were selected based on the genotypic information of the BC₃F₁ generation, by focusing on high cultivar genome recovery (89.1–95.9%) and with superior field performance (data not shown) of the BC₃F₂ generation during summer 2020. Selected lines included two BC₃F₃ lineages with the A02-QTL, two with the A09-QTL, one with both A02-QTL and A09-QTL, and one with a large A09-QTL. The synthetic allotetraploid BatSten1 and the cultivar A. hypogea TifNV-High O/L (Holbrook et al., 2017) were used as resistant controls and A. hypogea 5-646-10 and 13-1014 as susceptible controls. To confirm the presence of the QTL, BC₃F₃s and controls were genotyped using KASP markers (as described in the “Marker-assisted breeding” section). Six KASP markers targeting the bottom of A02 (A02-83,464,195, A02-92,077,207, and A02-92,983,792) and A09 (A09-16,516,448, A09-112309,231 and A09-114,515,959) (Supplementary Table 2) were used. Additionally, Axiom_Arachis2 SNP array genotyping was performed for genome-wide characterization, and data were filtered as described above.

TABLE 1

Table 1. Average and standard deviation for GI/g and eggs/g measured in BC₃F₃ lines, resistant, and susceptible controls using a pot bioassay.

Peanut root-knot nematode (PRKN) populations were cultured and extracted from eggplant (Solanum melongena) to be used as inoculum for bioassays. Second stage juveniles (J₂s) were collected from infected roots in a mist chamber every 2–3 days over a week and stored at 10°C until inoculation. Peanut seeds were grown in nursery pots filled with steam-sterilized sandy soil in the greenhouse. Bioassay was performed under greenhouse conditions, in a randomized complete block design with 12 replicates per genotype. Furthermore, 40-day-old plants were inoculated with 6,000 J₂s by adding the inoculum in two 2-cm deep holes at the base of the plant. Two months later, plants were uprooted, rinsed to remove soil, assessed for galling, and weighed. Eggs were extracted from roots using 0.5% NaOCl and counted (Hussey and Barker, 1973; Holbrook et al., 2003). Two different traits were measured: (1) galling index (GI), where 0 = no galls, 1 = 1-2 galls, 2 = 3-10 galls, 3 = 11-30 galls, 4 = 31-100 galls and 5 = more than 100 galls (Taylor and Sasser, 1978) and (2) number of eggs. Galling index and number of eggs per root weight (GI/g and eggs/g) were used for resistance assessment. A highly resistant plant was defined as such when the reproduction of nematodes was less than 20% of the reproduction in a susceptible plant (Taylor and Sasser, 1978).

Phenotypic Characterization

Seed Size

In each cycle of backcrossing, 11 BC₁F₁, 30 BC₂F₁, 253 BC₃F₁, 101 BC₃F₂ and 25 BC₄F₁ seeds were phenotyped for weight (g), length (mm, longest point) and width (mm, widest point) prior to planting. For controls (A. stenosperma V10309; A. batizocoi K9484; BatSten1; A. hypogaea genotypes, 5-646-10, 13-1014, TifGP-2 and Runner-886), 10 individual seeds were measured (Table 2).

TABLE 2

Table 2. Average and standard deviation for seed weight, length, and width measured in BC_nF_n lines, diploid wild species, induced allotetraploid BatSten1, and cultivated controls.

Pollen Viability (BC₂F₁s)

Pollen viability (PV) was evaluated for the BC₂F₁s and controls (Table 3). Flowers were collected early morning (between 8:00 and 10:00 am) and stained with acetocarmine (Heslop-Harrison, 1992). Stained pollen grains were observed and counted under a microscope (40X). Pollen viability from 10 individual flowers (reps) per genotype was assessed as the percentage of stained pollen grains (Gaaliche et al., 2013).

TABLE 3

Table 3. Average and standard deviation for pollen viability (%) and the number of pods quantified in BC₂F₁s lines and controls.

Leaf Spot Incidence, Fertility, Architecture, and Flower Color (BC₃F₁s)

While the BC₃F₁s were growing in the greenhouse, segregation for different traits was noticed, including foliar disease incidence, fertility (number of pegs), plant architecture, and flower color (Figures 2A–C). Single plant measurements were recorded. Leaf spot incidence was scored as a categorical variable as: “yes” (1) for A. hypogaea phenotype (susceptible) or “no” (0) for the resistant phenotype (Figure 2A). A total number of pegs was counted for assessment of fertility. Plant architecture or growth habit was scored from 1 to 4, with 1 being erect and 4 for prostrate growth habit (Figure 2B) (Pittman, 1995). Lastly, flower color was scored visually as orange (1) for A. hypogaea phenotype versus yellow (0) for the wild phenotype (Figure 2C).

FIGURE 2

Figure 2. Phenotypic characterization of advanced backcross population. Leaf spot incidence for BC₃F₁s and BC₃F₂s [“yes” (1) or “no” (0)] (A); architecture for BC₃F₁s and BC₃F₂s (scores: 1 – erect, 2 and 3 – intermediate, 4 – prostrate, and 5 – dwarf phenotype observed only for BC₃F₂ generation) (Pittman, 1995) (B); flower color for BC₃F₁s (scores: Orange – 1 or yellow – 0) (C); variation in branching for BC₃F₂s (scores: 1 – high, 2 – intermediate and 3 – normal) (D); 1–3 extra leaves in leaflets for BC₃F₂s (score 0) (E). “*” indicates A. hypogaea phenotype in all the cases.

Leaf Spot Incidence, Architecture, Branching, and Extra Leaves (BC₃F₂s)

A group of 101 BC₃F₂ plants from 12 BC₃F₁ families with a high recurrent parent (A. hypogaea) genome recovery (88.3–97.3%) were selected to create a group of lines carrying different sizes of introgressions in A02 and A09 for future gene cloning experiments. KASP assays targeting ten SNPs at A02-QTL and A09-QTL (Supplementary Table 2, gray-shaded markers) were used to confirm the presence of the QTL. While the plants were growing, several traits were recorded: leaf spot incidence and plant architecture were scored as above, in addition, a score of 5 for dwarf phenotype was included (Figures 2A,B). Branching was scored from an abnormal number of branches (high) (1) to intermediate (2) to normal A. hypogea phenotype (3) (see Figure 2D). Finally, extra leaves in leaflets were observed and scored as 1 for A. hypogaea and 0 for the presence of at least one extra leaf (Figure 2E).

Association Analysis Using the BC₃F₁ Population

Association between genome-wide genotypic data of BC₃F₁ lines and phenotypic data of seed weight, length and width, leaf spot incidence, fertility, architecture, and flower color were used to identify candidate wild introgressions that could be controlling these traits. For seed size, leaf spot incidence, fertility, and architecture a Pearson correlation was performed. Flower color was analyzed using a mixed linear model (MLM) in Tassel (v.5) (Ithaca, NY, United States) (Bradbury et al., 2007). A Manhattan plot was created in R using the “qqman” package (Turner, 2014) and thresholds calculated using the “CalcThreshold” package with the Bonferroni method (Hamazaki and Iwata, 2020).

Statistical Analysis

Phenotypic data for seed weight, length and width, pollen viability, and nematode resistance bioassay were analyzed using the package R. A Shapiro-Wilk test was used to test for normal distribution. Non-parametric Kruskal-Wallis one-way analysis of variance (Kruskal and Wallis, 1952) was used to evaluate differences at a 5% level of significance (P < 0.05). For the seed weight, length, and width (transformed to Log10 when needed) the Welch t-test was used to perform pair-wise comparisons between wild accessions, cultivated genotypes, and backcross generations. Additionally, the non-parametric Skillings-Mack test (Chatfield and Mander, 2009) was used to evaluate significant differences for the RCBD nematode bioassay (P < 0.05). Further analysis included the Wilcoxon signed-rank test for pairwise comparisons using false discovery rate (FDR) correction to group samples by significant similarity (P < 0.05).

Results

Marker-Assisted Breeding

Four generations of MABC for introgression of PRKN resistance from A. stenosperma were completed in two locations, Athens, GA, and Tifton, GA under greenhouse conditions (Figure 1). KASP genotyping was performed using 16 (for first, second and third cycles) and 10 SNP markers (fourth cycle) (Supplementary Tables 1, 2, gray-shaded markers). For the first cycle of backcrosses, 38 cross combinations were used, with 19 F_2:3 plants as donor male parents and two cultivated peanut female parents, namely, TifGP-2 and 5-646-10. In this cycle, 1,008 potential BC₁F₁ seeds were harvested, and based on KASP genotyping, 17 were selected for harboring the nematode resistance segments in A02 and A09 (Supplementary Table 3).

For the second cycle, 14 cross combinations were made with four cultivated peanut female parents, TifGP-2, 5-646-10, 13-1014 and 13-2113, and 11 BC₁F₁ male parents. Here, 61 potential BC₂F₁ seeds were obtained and genotyped with KASP markers. A total of 21 were selected as they harbored resistance segments in A02 and A09 PRKN resistance QTL (Supplementary Table 4).

For the third cycle of backcrossing, a total of 21 cross combinations were made using 5-646-10 and 13-1014 as female parents and 21 BC₂F₁ male parents selected the previous year, six of which were shown to be resistant to PRKN (Ballén-Taborda et al., 2021). This resulted in 397 potential BC₃F₁ seeds (Supplementary Table 5), that were genotypically characterized in two different ways. First, 81 BC₃F₁ seeds were randomly selected and evaluated for the presence of resistance segments using the KASP assays. From this group, 52 BC₃F₁s harbored the segments in A02 and A09 from A. stenosperma (Supplementary Table 5). Second, 271 BC₃F₁s were genome-wide genotyped (see next section).

For the fourth cycle, six cross combinations were used with 5-646-10, 13-1014, and 13-1125 as females and two BC₃F₂ male parents harboring A02 and A09 loci. Here, 27 potential BC₄F₁ seeds were obtained and genotyped with KASP markers. A total of 25 were confirmed to harbor PRKN resistance chromosome segments at the bottom of both A02 and A09 (Supplementary Table 6). Three of them could have combined both sources of resistance in A02 from A. stenosperma and A09 from A. cardenasii present in parent 13-1125.

Genome-Wide Genotyping of BC₃F₁s

To characterize the wild introgressions in the BC₃F₁ population, 271 lines and controls were genotyped with the Axiom_Arachis2 SNP array. A total of 930 informative polymorphic SNP markers, previously identified and assigned to A and B subgenomes (Ballén-Taborda et al., 2019), were recovered. Among these, 527 markers were located in A-subgenome (A. stenosperma-specific markers) and 403 to B/K-subgenome (A. batizocoi-specific markers). Of the 271 genotyped lines, 253 (93.4%) were true progeny from hybridization and 18 (6.6%) were products of self-pollination (Supplementary Table 7).

Examples of Axiom clustering plots of SNPs linked to QTL in A02 (Supplementary Figures 1A,B) and A09 (Supplementary Figures 1C–E) show the distribution of BC₃F₁ lines and controls. Red clusters (A02 SNPs) and blue clusters (A09 SNPs) comprise genotypes without the A. stenosperma-derived allele. A. stenosperma was genotyped with the alternate allele. Yellow clusters indicate the backcross lines with incorporated PRKN resistance from A. stenosperma.

The principal component analysis (PCA) performed on the genotyping data, allowed us to observe that the BC₃F₁s have recovered a high percentage of the A. hypogaea genome. Backcross lines showed a recurrent parent genome recovery between 80.2 and 98.8%, while still carrying between 1.1 and 19.1% of the wild donor genome (Supplementary Figure 2). Additionally, to visualize the distribution of the backcross population according to the proportion of wild introgression (%) in each chromosome, the data was displayed in violin plots. These plots allowed us to observe that the lines were harboring more wild alleles in the A-subgenome than in B-subgenome, especially in chromosomes A02 and A09 where foreground selection was applied during the backcrossing process (Figure 3 and Supplementary Table 7).

FIGURE 3

Figure 3. Violin plots for the proportion of wild genome (%) (y-axis) in each of the 10 A- and 10 B-subgenome chromosomes (x-axis) for the 271 BC₃F₁ lines. Black dots indicate each individual BC₃F_1, and red dots indicate the mean.

Peanut Root-Knot Nematode Resistance Validation Using BC₃F₃s

To validate the PRKN resistance controlled by QTL in A02 and/or A09, 72 BC₃F₃ segregating lines, and resistant and susceptible controls were evaluated using a greenhouse pot nematode bioassay and genotyped with both KASP and Affymetrix to confirm the presence of the QTL. Specifically, Affymetrix was completed for genome-wide characterization. Galling index (GI) and number of eggs in relation to root weight (GI/g and eggs/g) allowed us to assess the resistance to M. arenaria within the backcross lines (Table 1).

Resistant controls (BatSten1 and TifNV-High O/L) and susceptible genotypes (5-646-10 and 13-1014) exhibited the expected phenotype. BatSten1 and TifNV-High O/L showed strong resistance, with no or low gall/egg production. In contrast, for 5-646-10 and 13-1014, GI/g fluctuated between 0.31 ± 0.26 and 0.42 ± 0.11 and eggs/g varied between 579.18 ± 855.26 and 1268.64 ± 1046.49 (Figure 4, Table 1 and Supplementary Table 8). BC₃F₃ lines showed significant differences for GI/g and eggs/g (Kruskal-Wallis, Skillings-Mack and Wilcoxon tests, P < 0.05). Since the BC₃F₃s were still recombining and segregating for PRKN QTL, to better summarize the results, the lines were grouped according to the segments they were carrying as follows: • Group 1: bottom A02 (A02) (A. stenosperma allele at A02-83,464,195, A02-92,077,207 and A02-92,983,792 → 81.0 – 93.8 Mb); • Group 2: bottom A09 (A09) (A. stenosperma allele at A09-112,309,231 and A09-114,515,959 → 104.6 – 119.8 Mb); • Group 3: large A09 (A09+) (A. stenosperma allele at A09-16,516,448, A09-112,309,231 and A09-114,515,959 → 3.4 – 118.7 Mb); and • Group 4: Both bottom small A02 (A. stenosperma allele at A02-92,077,207 and A02-92,983,792 → 91.6 – 93.8 Mb) and bottom A09 (A02- and A09). According to this grouping, all the backcross materials belonging to groups 1, 3, and 4 exhibited high levels of resistance to PRKN. No or few galls (0.01 ± 0.03–0.17 ± 0.20) and low egg production (0.00 ± 0.00–36.30 ± 83.17) was observed in the infected roots. For groups 3 and 4 galls were observed in the roots, but the production of eggs was inhibited. In contrast, lines in group 2 were susceptible to PRKN by having GI/g and eggs/g values of 0.26 ± 0.19 and 1050.62 ± 1005.38, respectively (Figure 4). For more details of GI/g and eggs/g values for the BC₃F₃ lines, see Table 1 and Supplementary Table 8.

FIGURE 4

Figure 4. Boxplot diagrams for Galling index per gram of root (GI/g) (A) and Number of eggs per gram of root (eggs/g) (B) of BC₃F₃ lines, resistant controls Batsten1 and A. hypogea TifNV-High O/L, and susceptible controls 5-646-10 and 13-1014. BC₃F₃ lines were grouped according to the A. stenosperma alleles that they are carrying as: • Group 1: bottom A02 (A02) (A. stenosperma allele at A02-83,464,195, A02-92,077,207, and A02-92,983,792); • Group 2: bottom A09 (A09) (A. stenosperma allele at A09-112,309,231 and A09-114,515,959); • Group 3: large A09 (A09+) (A. stenosperma allele at A09-16,516,448, A09-112,309,231 and A09-114,515,959); and • Group 4: Both bottom small A02 (A. stenosperma allele at A02-92,077,207 and A02-92,983,792) and bottom A09 (A02- and A09). The top of the figure indicates the introgression in A02 and A09 from A. stenosperma in blue and SNP markers as black horizontal lines. For TifNV-High O/L, resistance from A. cardenasii is colored in gray. The numbers at the top of the bars indicate the mean ± SD. The numbers above the groups indicate the number of lines included in each group. Complete pedigree in Supplementary Table 8. Black bars across boxes indicate the median and red dot the mean. BC₃F₃s in salmon color and controls in teal color.

Phenotypic Characterization

A wide variation of morphological and agronomic traits was observed in the backcross populations (BC₃F₁s and BC₃F₂s), including seed size, pollen viability, leaf spot incidence, fertility (number of pegs), plant architecture, flower color, branching, and extra leaves (Figure 2). Association analysis between phenotypic information and wild introgressions in the BC₃F₁ population was performed to identify candidate regions associated with these traits.

Seed Size

Seed weight (g), length (mm) and width (mm) measurements were recorded for 11 BC₁F₁, 30 BC₂F₁, 253 BC₃F₁, 101 BC₃F₂ and 25 BC₄F₁ seeds prior to planting, along with wild and cultivated controls. Significant differences were observed between the control genotypes according to the Kruskal-Wallis test and the Wilcoxon Test (P < 0.05), where wild genotypes have significantly smaller and lighter seeds as compared with seed dimensions of cultivated genotypes (Figure 5A, Table 2, and Supplementary Table 9). There was a clear recovery in seed size as early as BC₁. According to the Welch t-test, the wild accessions (A. stenosperma V10309, A. batizocoi K9484, and BatSten1) differed significantly from the cultivated genotypes (A. hypogaea 5-646-10, 13-1014, TifGP-2 and Runner-886) and the backcross generations (BC₁F₁, BC₂F₁, BC₃F₁, BC₃F₂, and BC₄F₁) for weight, length, and width (P < 0.05). When comparing seed measurements of cultivated genotypes with each of the BC generations and between BC generations, in most of the cases there were no significant differences in seed size (P < 0.05 and P < 0.01) (Welch t-test matrix in Supplementary Table 9). Between the BC lines seed size exhibited variation, and on average the seed weight fluctuated from 0.66 g (BC₃F₁s) and 0.72 g (BC₂F₁s and BC₃F₂s), but having weight as high as 1.47 g when compared to the cultivated controls that exhibited similar seed weight of 0.74 g (Runner-886) and 0.84 g (13-1014), with the highest being 1.03 g. In this study, we presented data for the weight (Figure 5A), a similar tendency was observed for length and width (Table 2 and Supplementary Table 9). Based on the Pearson correlations performed between the seed weight, length, and width and the genotypic data for the BC₃F₁s potential A. hypogaea loci associated with large seed size were identified in chromosomes A03, B01, and B08 (Supplementary Figures 3A–C and Supplementary Table 10).

FIGURE 5

Figure 5. Violin plots for the distribution of seed weight (g) (y-axis) for wild controls, several backcross generations (BC₁F₁s, BC₂F₁s, BC₃F₁s, BC₃F₂s, and BC₄F₁s) and cultivated genotypes (x-axis); Black dots indicate each individual line and red dot the mean (A). Photo of seeds of diploid species (A. stenosperma and A. batizocoi), synthetic allotetraploid BatSten1, cultivated genotypes (Runner-886, 5-646-10, 13-1014, TifGP-2), and seeds from BC₃F₁ lines (B). Groups of 15 seeds are presented. Recurrent parent (RP) indicated in parenthesis for each BC₃F₁ line. Complete pedigree in Supplementary Table 7. The same trend for length (mm) and width (mm) was observed (Supplementary Table 9). Refer to Table 2 for average, SD, and statistical analysis for controls.

Pollen Viability (BC₂F₁s)

Pollen viability (PV) of wild accessions A. stenosperma, A. batizocoi, the induced allotetraploid BatSten1, recurrent parents 5-646-10 and 13-1014 and 9 BC₂F₁ lines was evaluated to estimate differences in viability within BC lines. Individuals showed varying degrees of pollen viability, ranging from 65.6 to 94.9% (Table 3). In control genotypes, PV varied from 71.7 to 94.9% and in the BC₂F₁s, it fluctuated from 65.6 to 89.8%. Although significant differences were observed between the genotypes according to the Kruskal-Wallis test and the Wilcoxon Test (P < 0.05), no grouping trend was observed. In summary, high pollen viability in the cultivated genotypes (5-646-10 and 13-1014), A. stenosperma, and some BC₂F₁s were observed, and lower pollen viability was observed for BatSten1, A. batizocoi, and other BC₂F₁s (Supplementary Figure 4). A low correlation between pollen viability and the number of produced pods per plant was observed (–0.007, p < 0.05).

Leaf Spot Incidence, Fertility, Architecture, and Flower Color (BC₃F₁s)

For the BC₃F₁ population that included 253 lines, segregation for leaf spot incidence, fertility, architecture, and flower color was noticed while growing in the greenhouse in a randomized position (Figures 2A–C). 150 lines exhibited signs of leaf spot, while 103 did not (Supplementary Figure 5A). Pearson correlation performed between phenotypic and genotypic data allowed us to identify two candidate loci in chromosomes A06 and B02 that could be associated with resistance to leaf spot (Supplementary Figure 3D) and are now being tested using BC₃F₂ progeny (data not shown). The number of pegs was counted as an indication of fertility. The distribution of the data showed that the majority of the lines had a similar number of pegs as the recurrent parents 5-646-10 and 13-1014, with an average of 13.15 ± 7.83 total number of pegs (Supplementary Figure 5B). For this trait, A. hypogaea loci in chromosomes A02 and A09 could be associated with fewer pegs (Supplementary Figure 3E). For architecture, around two-thirds of the lines had the cultivated growth habit phenotype (163) and one-third of the lines were exhibiting an erect growth habit (84) (six were too small to be scored) (Figure 2B and Supplementary Figure 5C). According to the association analysis, SNPs in chromosomes A01 and B08 could be associated with changes in plant architecture (Supplementary Figure 3F). Most lines exhibited orange flowers (245) while eight had the yellow color, a common trait within Arachis wild species (Supplementary Figure 5D). After running the mixed linear model in Tassel, introgression on the top of chromosome A05 (7.92–8.62 Mb) was found to be associated with the change in flower color from orange to yellow. In this study, four markers were found to be linked with this trait (A05-7,919,003, A05-7,958,564, A05-8,040,921, A05-8,621,849) (Supplementary Figure 6).

Leaf Spot Incidence, Architecture, Branching, and Extra Leaves (BC₃F₂s)

Segregation for leaf spot incidence, architecture, branching, and extra leaves was also noticed among the 101 BC₃F₂ lines (two of them were too small to be scored) (Supplementary Table 11). 38 lines had leaf spots and 61 did not (Supplementary Figure 5E). Around half of the lines had the cultivated growth habit phenotype (51), some exhibiting an erect phenotype (41) and a few with a dwarf phenotype (7) (Supplementary Figure 5F). Most lines showed the peanut phenotype of normal branching (79 with score 3) and some presented a high number of stems (20 with score 1 or 2) (Supplementary Figure 5G). Finally, at least one extra leaflet was observed in 70 plants (score 0) and 31 did not display this unexpected phenotype (score 1) (Supplementary Figure 5H).

Discussion

Crop wild relatives (CWR) have become an important source to reintroduce genetic diversity for crop improvement (Dempewolf et al., 2017). For peanut breeding, diploid wild relatives comprise a diverse genetic pool that is being used to broaden peanut’s genetic base (Stalker, 2017). Transferring wild beneficial alleles requires an additional step of developing peanut compatible wild-derived synthetic allotetraploids (Suassuna et al., 2020). To incorporate root-knot nematode resistance from A. cardenasii, synthetic allotetraploids were successfully developed and used (Simpson et al., 1993; Simpson and Starr, 2001). The introgression in A09 controlling PRKN resistance (Nagy et al., 2010; Chu et al., 2016) is present in several commercial cultivars (Simpson et al., 2003, 2013; Holbrook et al., 2008, 2017; Branch and Brenneman, 2015) and has provided a strong resistance over the years. Since the resistance to PRKN is controlled by a single source, there is a risk of virulent nematode populations developing. Therefore, the incorporation of new alleles is essential to provide stronger and more durable resistance against PRKN.

One of the peanut wild relatives A. stenosperma PI666100/V10309 has been confirmed to be resistant to peanut root-knot nematode, M. arenaria (Proite et al., 2008), and genes involved in plant defense against this pathogen have been described (Proite et al., 2007; Guimarães et al., 2010; Mota et al., 2018; Araujo et al., 2021). The present work reports the successful incorporation of two new and strong PRKN resistance loci from A. stenosperma previously mapped and validated (Leal-Bertioli et al., 2016; Ballén-Taborda et al., 2019, 2021). Here, marker-assisted backcross breeding was employed to complete four cycles, and genetic and phenotypic characterization was performed (Figure 1). As pyramiding of major R-genes has been proven to be valuable to extend durability and effectiveness of major genes (Pilet-Nayel et al., 2017), in the fourth cycle the elite breeding line 13-1125 harboring nematode resistance from A. cardenasii was included as a female parent (Holbrook, CC, unpublished data). Based on KASP genotyping, three BC lines could have pyramided both sources of resistance in A02 from A. stenosperma and A09 from A. cardenasii (Supplementary Tables 6, 12, highlighted in green).

A population of 253 true third backcross lines were subjected to genome-wide genotyping and phenotypically characterized for association analysis. These lines originally selected for PRKN resistance had wild introgressions between 1.1 and 19.1% across the genome. Having a high percentage of the wild genome would indicate that additional cycles of backcrossing are needed to assure maximum elite genome representation; therefore, we completed the fourth cycle. However, segregation for several phenotypic attributes (seed size, pollen viability, leaf spot incidence, fertility, architecture, flower color, branching, and extra leaves) was observed, which indicated that wild introgressions in different chromosomes could be controlling these traits and are worth further study. The whole BC₃ population has been carried forward not only to develop nematode-resistant cultivars but additionally to study resistances to other pests and diseases and to develop a CSSL-like population that would be useful for precise mapping of QTL.

Based on the data of agronomic and morphological traits measured in several generations, most lines exhibited elite peanut traits and were similar to recurrent parental breeding lines. First, seed size in each generation of introgression was examined. This was done to observe the seed size recovery as we progressed through our MABC scheme, as seed size is an important trait associated with germination, vigor, and yield, and is important for the peanut industry and market (Singh et al., 1998). For the backcross lines, our measurements showed that seed size was not progressively increased as the wild genome representation was reduced in each generation. On the contrary, we observed that only one backcross generation was required to recover the elite peanut’s large seeds and that in later generations the average seed size did not change significantly (Figure 5B). We also observed that larger and heavier seeds were produced by some BC lines, by having seed weight as high as 1.47 g compared to the cultivated controls that exhibited 1.03 g as the heaviest seed. Similar behavior was observed for length and width. An explanation for the transgressive segregation in seed size could be due to the presence of wild alleles that are contributing to larger seed size, as reported before in interspecific peanut progenies (Fonceka et al., 2012a; Suassuna et al., 2015). Although the correlation analysis showed candidate regions in chromosomes A03, B01, and B08, this requires further validation as these have not been reported previously.

Results for pollen viability measured in the BC₂ generation agreed with that of Leal-Bertioli et al. (2015) as cultivated peanut genotypes and A. stenosperma showed a high pollen viability (average of 91.9%) and most of the BC₂F₁ lines had lower numbers (average of 79.2%) reflecting the genetic distance of the parental genotypes. Our results showed little variation regardless of the genotype, which suggests that pollen viability is not a key contributor to the production of seeds within the backcross lines (Leal-Bertioli et al., 2015). This was also corroborated by the low correlation between pollen staining and pod production (–0.007, P < 0.05). The correlation analysis on the BC₃ generation, also allowed us to identify candidate introgressions for leaf spot reduction in chromosomes A06 and B02. For flower color, the region at the top of chromosome A05 (7.92 – 8.62 Mbp) associated with the yellow color trait is consistent with previous reports, and a result of homologous recombination (Fonceka et al., 2012b; Bertioli et al., 2019).

Although most of the BC lines had domesticated features, we also observed some variation in fertility (number of pegs), plant architecture, branching, and extra leaves. Further analyses will be required to fully understand the candidate wild introgressions that are controlling these traits. Finally, in the case of extra leaflets, this is a phenotype that has been described as a novel heterozygous trait that continues to segregate even after several generations of selfing (Branch et al., 2020).

Validation of Nematode Resistance

In this study, resistance to PRKN was successfully validated in a set of BC₃F₃ lines. The bottom of A02 (81.0 – 93.8 Mb) (Figure 4, group 1) provided strong resistance as previously described and validated (Leal-Bertioli et al., 2016; Ballén-Taborda et al., 2019, 2021). In the case of the QTL in chromosome A09, we observed that the small introgression at the bottom (104.6 – 119.8 Mb) was insufficient to stop nematode development (group 2) and that a larger segment at the top-bottom of A09 (3.4 – 118.7 Mb) was required to provide resistance, especially for preventing eggs production (group 3). It is possible that the presence of wild alleles in A04 associated with susceptibility in group 2 could be acting against resistance as previously described (Ballén-Taborda et al., 2019). When the plants were harboring both bottom small A02 (91.6 – 93.8 Mb) and bottom A09 (104.6 – 119.8 Mb) (group 4) we would expect to observe inhibition of both galls and egg production since A02 was present; however, galls were present in the roots. Field testing is in progress to test the stability of the resistance and for allele fixation through selfing.

Implications for Breeding for Disease Resistance

Genetic maps, quantitative trait loci (QTL), and marker-phenotype associations have been reported for numerous crops and traits (Collard and Mackill, 2008). Despite this, examples of QTL incorporation in plant breeding programs are lower than expected (Bernardo, 2016). This work represents a successful example of QTL introgression from a wild relative into an elite peanut despite the genetic incompatibilities. This provides an alternative to the only source of root-knot resistance currently deployed in the peanut crop, derived from A. cardenasii (Simpson and Starr, 2001).

The population of advanced peanut backcross lines that we have developed during this work has wild chromosome segments through much of the genome, distributed in different ways in different lines. They are being tested and advanced in several locations, and the best performing lines are being selected for germplasm release. The PRKN resistance alleles have been successfully validated and DNA markers are now available to facilitate the marker-assisted selection. Furthermore, because of the diverse wild chromosome segments in this population, we also anticipate that it has other disease resistances and traits of value to the peanut crop. We anticipate that, over time, these backcrossed lines will impact peanut production by delivering several new traits to the peanut crop, similar to the case of North Carolina peanut lines with A. cardenasii segments that have provided resistance to late leaf spot, rust, and web blotch in numerous countries around the world (Bertioli et al., 2021b).

Data Availability Statement

The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.

Author Contributions

SCML-B, DJB, SAJ, and PO-A conceptualized this project. PO-A, YC, CCH, and CB-T performed crosses. CB-T and PT performed phenotyping for nematode resistance. CB-T performed phenotypic characterization of traits and wrote the original draft. CB-T, DJB, and SCML-B conducted genotyping and data analysis. All authors revised and approved the manuscript.

Funding

This work was supported by the Agriculture and Food Research Initiative Competitive Grant (#2018-67013-28139) co-funded by the USDA National Institute of Food and Agriculture and the National Peanut Board and grants from the National Science Foundation (#MCB-1543922), Georgia Peanut Commission, Peanut Research Foundation, and Mars Wrigley Inc.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Acknowledgments

We appreciate Jenny Leverett, Victoria Morris, Mark Hopkins, Stephanie Botton, and Emily Jackson for their technical assistance.

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpls.2021.785358/full#supplementary-material

Footnotes

1. ^ https://biosearch-cdn.azureedge.net/assetsv6/KASP-genotyping-chemistry-User-guide.pdf
2. ^ https://wheat.pw.usda.gov/demos/BatchPrimer3/

References

Araujo, A. C. G., Guimarães, P. M., Mota, A. P. Z., Guimarães, L. A., Pereira, B. M., Vinson, C. C., et al. (2021). Overexpression of DUF538 from wild arachis enhances plant resistance to Meloidogyne spp. Agronomy 11:559. doi: 10.3390/agronomy11030559

CrossRef Full Text | Google Scholar

Ballén-Taborda, C., Chu, Y., Ozias-Akins, P., Timper, P., Holbrook, C. C., Jackson, S. A., et al. (2019). A new source of root-knot nematode resistance from Arachis stenosperma incorporated into allotetraploid peanut (Arachis hypogaea). Sci. Rep. 9:17702. doi: 10.1038/s41598-019-54183-1

PubMed Abstract | CrossRef Full Text | Google Scholar

Ballén-Taborda, C., Chu, Y., Ozias-Akins, P., Timper, P., Jackson, S. A., Bertioli, D. J., et al. (2021). Validation of resistance to root-knot nematode incorporated in peanut from the wild relative Arachis stenosperma. Agron. J. 113, 2293–2302. doi: 10.1002/agj2.20654

CrossRef Full Text | Google Scholar

Bernardo, R. (2016). Bandwagons I, too, have known. Theor. Appl. Genet. 129, 2323–2332. doi: 10.1007/s00122-016-2772-5

PubMed Abstract | CrossRef Full Text | Google Scholar

Bertioli, D. J., Abernathy, B., Seijo, G., Clevenger, J., and Cannon, S. B. (2020). Evaluating two different models of peanut’s origin. Nat. Genet. 52, 557–559.

Google Scholar

Bertioli, D. J., Cannon, S. B., Froenicke, L., Huang, G., Farmer, A. D., Cannon, E. K., et al. (2016). The genome sequences of Arachis duranensis and Arachis ipaensis, the diploid ancestors of cultivated peanut. Nat. Genet. 48, 438–446. doi: 10.1038/ng.3517

PubMed Abstract | CrossRef Full Text | Google Scholar

Bertioli, D. J., Jenkins, J., Clevenger, J., Dudchenko, O., Gao, D., Seijo, G., et al. (2019). The genome sequence of peanut (Arachis hypogaea), a segmental allotetraploid. Nat. Genet. 51, 877–884. doi: 10.1038/s41588-019-0405-z

PubMed Abstract | CrossRef Full Text | Google Scholar

Bertioli, D. J., Gao, D., Ballen-Taborda, C., Chu, Y., Ozias-Akins, P., Jackson, S., et al. (2021a). Registration of GA-BatSten1 and GA-MagSten1, two induced allotetraploids derived from peanut wild relatives with superior resistance to leaf spots, rust and root-knot nematode. J. Plant Regist. 15, 372–378. doi: 10.1002/plr2.20133

CrossRef Full Text | Google Scholar

Bertioli, D. J., Clevenger, J., Godoy, I. J., Stalker, H. T., Wood, S., Santos, J. F., et al. (2021b). Legacy genetics of Arachis cardenasii in the peanut crop shows the profound benefits of international seed exchange. Proc. Natl. Acad. Sci. U.S.A. 118:e2104899118. doi: 10.1073/pnas.2104899118

PubMed Abstract | CrossRef Full Text | Google Scholar

Bradbury, P. J., Zhang, Z., Kroon, D. E., Casstevens, T. M., Ramdoss, Y., and Buckler, E. S. (2007). TASSEL: software for association mapping of complex traits in diverse samples. Bioinformatics 23, 2633–2635. doi: 10.1093/bioinformatics/btm308

PubMed Abstract | CrossRef Full Text | Google Scholar

Branch, W. D., and Brenneman, T. B. (2015). Registration of ‘Georgia-14N’ peanut. J. Plant Regist. 9, 159–161.

Google Scholar

Branch, W. D., Tallury, S. P., Clevenger, J. P., Schwartz, B. M., and Hanna, W. W. (2020). Inheritance of a novel heterozygous peanut mutant, 5-small leaflet. Peanut Sci. 47, 33–37.

Google Scholar

Chatfield, M., and Mander, A. (2009). The skillings-mack test (Friedman test when there are missing data). Stata J. 9, 299–305.

Google Scholar

Chu, Y., Gill, R., Clevenger, J., Timper, P., Corley Holbrook, C., and Ozias-Akins, P. (2016). Identification of rare recombinants leads to tightly linked markers for nematode resistance in peanut. Peanut Sci. 43, 88–93.

Google Scholar

Clevenger, J. P., Korani, W., Ozias-Akins, P., and Jackson, S. (2018). Haplotype-based genotyping in polyploids. Front. Plant Sci. 9:564. doi: 10.3389/fpls.2018.00564

PubMed Abstract | CrossRef Full Text | Google Scholar

Collard, B. C., and Mackill, D. J. (2008). Marker-assisted selection: an approach for precision plant breeding in the twenty-first century. Philos. Trans. R. Soc. Lond. B Biol. Sci. 363, 557–572. doi: 10.1098/rstb.2007.2170

PubMed Abstract | CrossRef Full Text | Google Scholar

Dempewolf, H., Baute, G., Anderson, J., Kilian, B., Smith, C., and Guarino, L. (2017). Past and future use of wild relatives in crop breeding. Crop Sci. 57, 1070–1082.

Google Scholar

Dickson, D. W., and De Waele, D. (2005). “Nematode parasites of peanut,” in Plant Parasitic Nematodes in Subtropical and Tropical Agriculture, eds R. A. Sikora and J. Bridge (Wallingford: CABI Publishing), 393–436. doi: 10.1079/9780851997278.0393

CrossRef Full Text | Google Scholar

FAOSTAT (2021). FAOSTAT Statistical Database. Rome: Food and Agriculture Organization of the United Nations.

Google Scholar

Fonceka, D., Tossim, H. A., Rivallan, R., Vignes, H., Faye, I., Ndoye, O., et al. (2012a). Fostered and left behind alleles in peanut: interspecific QTL mapping reveals footprints of domestication and useful natural variation for breeding. BMC Plant Biol. 12:26. doi: 10.1186/1471-2229-12-26

PubMed Abstract | CrossRef Full Text | Google Scholar

Fonceka, D., Tossim, H.-A., Rivallan, R., Vignes, H., Lacut, E., De Bellis, F., et al. (2012b). Construction of chromosome segment substitution lines in peanut (Arachis hypogaea L.) using a wild synthetic and QTL mapping for plant morphology. PLoS One 7:e48642. doi: 10.1371/journal.pone.0048642

PubMed Abstract | CrossRef Full Text | Google Scholar

Gaaliche, B., Majdoub, A., Trad, M., and Mars, M. (2013). Assessment of pollen viability, germination, and tube growth in eight tunisian Caprifig (Ficus carica L.) Cultivars. ISRN Agron. 2013, 1–4.

Google Scholar

Guimarães, P., Brasileiro, A. C. M., Proite, K., Araujo, A., Leal-Bertioli, S., Pic-Taylor, A., et al. (2010). A study of gene expression in the nematode resistant wild peanut relative, Arachis stenosperma, in response to challenge with Meloidogyne arenaria. Trop. Plant Biol. 3, 183–192.

Google Scholar

Hamazaki, K., and Iwata, H. (2020). RAINBOW: haplotype-based genome-wide association study using a novel SNP-set method. PLoS Comput. Biol. 16:e1007663. doi: 10.1371/journal.pcbi.1007663

PubMed Abstract | CrossRef Full Text | Google Scholar

Heslop-Harrison, J. S. (1992). “Cytological techniques to assess pollen quality,” in Sexual Plant Reproduction, eds M. Cresti and A. Tiezzi (Berlin: Springer-Verlag), 41–48. doi: 10.1007/978-3-642-77677-9_4

CrossRef Full Text | Google Scholar

Holbrook, C., and Stalker, H. (2003). Peanut breeding and genetic resources. Plant Breed. Rev. 22, 297–356. doi: 10.1002/9780470650202.ch6

CrossRef Full Text | Google Scholar

Holbrook, C., Dong, W., Timper, P., Culbreath, A., and Kvien, C. (2012). Registration of peanut germplasm line TifGP-2, a nematode-susceptible sister line of ‘Tifguard’. J. Plant Regist. 6, 208–211. doi: 10.3198/jpr2011.09.0507crg

CrossRef Full Text | Google Scholar

Holbrook, C., Ozias-Akins, P., Chu, Y., Culbreath, A. K., Kvien, C., and Brenneman, T. (2017). Registration of ‘TifNV-High O/L’ peanut. J. Plant Regist. 11, 228–230.

Google Scholar

Holbrook, C., Timper, P., and Culbreath, A. (2003). Resistance to and root-knot nematode in peanut interspecific breeding lines. Crop. Sci. 43, 1109–1113.

Google Scholar

Holbrook, C., Timper, P., Culbreath, A., and Kvien, C. (2008). Registration of ‘Tifguard’ peanut. J. Plant Regist. 2, 391–410.

Google Scholar

Hussey, R. S., and Barker, K. R. (1973). A comparison of methods of collecting inocula of Meloidogyne species, including a new technique. Plant Dis. Report. 57, 1025–1028.

Google Scholar

Korani, W., Clevenger, J. P., Chu, Y., and Ozias-Akins, P. (2019). Machine learning as an effective method for identifying true single nucleotide polymorphisms in polyploid plants. Plant Genome 12:180023. doi: 10.3835/plantgenome2018.05.0023

PubMed Abstract | CrossRef Full Text | Google Scholar

Kruskal, W., and Wallis, W. (1952). Use of ranks in one-criterion variance analysis. J. Am. Stat. Assoc 47, 583–621. doi: 10.1080/01621459.1952.10483441

CrossRef Full Text | Google Scholar

Leal-Bertioli, S. C. M., Moretzsohn, M. C., Roberts, P. A., Ballén-Taborda, C., Borba, T. C. O., Valdisser, P. A., et al. (2016). Genetic mapping of resistance to Meloidogyne arenaria in Arachis stenosperma: a new source of nematode resistance for peanut. G3 6, 377–390. doi: 10.1534/g3.115.023044

PubMed Abstract | CrossRef Full Text | Google Scholar

Leal-Bertioli, S. C., Santos, S. P., Dantas, K. M., Inglis, P. W., Nielen, S., Araujo, A. C., et al. (2015). Arachis batizocoi: a study of its relationship to cultivated peanut (A. hypogaea) and its potential for introgression of wild genes into the peanut crop using induced allotetraploids. Ann. Bot. 115, 237–249. doi: 10.1093/aob/mcu237

PubMed Abstract | CrossRef Full Text | Google Scholar

Mota, A. P. Z., Vidigal, B., Danchin, E. G. J., Togawa, R. C., Leal-Bertioli, S. C. M., Bertioli, D. J., et al. (2018). Comparative root transcriptome of wild Arachis reveals NBS-LRR genes related to nematode resistance. BMC Plant Biol. 18:159. doi: 10.1186/s12870-018-1373-7

PubMed Abstract | CrossRef Full Text | Google Scholar

Nagy, E. D., Chu, Y., Guo, Y., Khanal, S., Tang, S., Li, Y., et al. (2010). Recombination is suppressed in an alien introgression in peanut harboring Rma, a dominant root-knot nematode resistance gene. Mol. Breed. 26, 357–370. doi: 10.1007/s11032-010-9430-4

CrossRef Full Text | Google Scholar

Nelson, S. C., Simpson, C. E., and Starr, J. L. (1989). Resistance to Meloidogyne arenaria in Arachis spp. germplasm. J. Nematol. 21, 654–660.

Google Scholar

Noe, J. P., Holbrook, C. C., and Minton, N. A. (1992). Field evaluation of susceptibility to Meloidogyne arenaria in Arachis hypogaea plant introductions. J. Nematol. 24, 712–716.

Google Scholar

Oka, Y. (2020). From old-generation to next-generation nematicides. Agronomy 10:1387. doi: 10.3390/agronomy10091387

CrossRef Full Text | Google Scholar

Pilet-Nayel, M.-L., Moury, B., Caffier, V., Montarry, J., Kerlan, M.-C., Fournet, S., et al. (2017). Quantitative resistance to plant pathogens in pyramiding strategies for durable crop protection. Front. Plant Sci. 8:1838. doi: 10.3389/fpls.2017.01838

PubMed Abstract | CrossRef Full Text | Google Scholar

Pittman, R. N. (1995). United States Peanut Descriptors. U.S. Department of Agriculture, Agricultural Research Service, ARS-132. Tifton, GA: U.S. Department of Agriculture, Agricultural Research Service, 18.

Google Scholar

Proite, K., Carneiro, R., Falcão, R., Gomes, A., Leal-Bertioli, S., Guimarães, P., et al. (2008). Post-infection development and histopathology of Meloidogyne arenaria race 1 on Arachis spp. Plant Pathol. 57, 974–980.

Google Scholar

Proite, K., Leal-Bertioli, S. C., Bertioli, D. J., Moretzsohn, M. C., Da Silva, F. R., Martins, N. F., et al. (2007). ESTs from a wild Arachis species for gene discovery and marker development. BMC Plant Biol. 7:7. doi: 10.1186/1471-2229-7-7

PubMed Abstract | CrossRef Full Text | Google Scholar

Simpson, C., and Starr, J. (2001). Registration of ‘COAN’ peanut. Crop Sci. 41:918. doi: 10.2135/cropsci2001.413918x

PubMed Abstract | CrossRef Full Text | Google Scholar

Simpson, C., Nelson, S. C., Starr, J. L., Woodard, K. E., and Smith, O. D. (1993). Registration of TxAG-6 and TxAG-7 peanut germplasm. Crop Sci. 33:1418.

Google Scholar

Simpson, C., Starr, J. L., Baring, M. R., Burow, M. D., Cason, J. M., and Wilson, J. N. (2013). Registration of ‘Webb’ peanut. J. Plant Regist. 7:265. doi: 10.1111/cea.13816

PubMed Abstract | CrossRef Full Text | Google Scholar

Simpson, C., Starr, J. L., Church, G., Burow, M. D., and Paterson, A. H. (2003). Registration of NemaTAM peanut. Crop Sci. 43:1561. doi: 10.2135/cropsci2003.1561

PubMed Abstract | CrossRef Full Text | Google Scholar

Singh, A., Nautiyal, P., and Zala, P. V. (1998). Growth and yield of groundnut varieties as influenced by seed size. Trop Sci. 38, 48–56. doi: 10.1186/s13002-018-0275-y

PubMed Abstract | CrossRef Full Text | Google Scholar

Stalker, T. H. (2017). Utilizing wild species for peanut improvement. Crop Sci. 57:1102. doi: 10.2135/cropsci2016.09.0824

PubMed Abstract | CrossRef Full Text | Google Scholar

Suassuna, T. M. F., Suassuna, N. D., Moretzsohn, M. C., Leal-Bertioli, S. C. M., Bertioli, D. J., and Medeiros, E. P. (2015). Yield, market quality, and leaf spots partial resistance of interspecific peanut progenies. Crop Breed. Appl. Biotechnol. 15, 175–180. doi: 10.1590/1984-70332015v15n3n30

CrossRef Full Text | Google Scholar

Suassuna, T., Suassuna, N., Martins, K., Matos, R., Heuert, J., Bertioli, D., et al. (2020). Broadening the variability for peanut breeding with a wild species-derived induced allotetraploid. Agronomy 10:1917. doi: 10.3390/agronomy10121917

CrossRef Full Text | Google Scholar

Taylor, A. L., and Sasser, J. N. (1978). Biology, Identification and Control of Root-Knot Nematodes (Meloidogyne spp.). Raleigh: North Carolina State University, 111–112.

Google Scholar

Timper, P., Dickson, D. W., and Steenkamp, S. (2018). “Nematode parasites of groundnut,” in Plant Parasitic Nematodes in Subtropical and Tropical Agriculture, eds R. A. Sikora and D. L. Coyne (Wallingford: CAB International), 411–445.

Google Scholar

Turner, S. D. (2014). qqman: an R package for visualizing GWAS results using Q-Q and manhattan plots. bioRxiv [Preprint] doi: 10.1101/005165

CrossRef Full Text | Google Scholar

You, F. M., Huo, N., Gu, Y. Q., Luo, M. C., Ma, Y., Hane, D., et al. (2008). BatchPrimer3: a high throughput web application for PCR and sequencing primer design. BMC Bioinform. 9:253. doi: 10.1186/1471-2105-9-253

PubMed Abstract | CrossRef Full Text | Google Scholar