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Drought is a destructive abiotic stress that affects all critical stages of peanut growth such as emergence, flowering, pegging, and pod filling. The development of a drought-tolerant variety is a sustainable strategy for long-term peanut production. The U.S. mini-core peanut germplasm collection was evaluated for drought tolerance to the middle-season drought treatment phenotyping for pod weight, pod count, relative water content (RWC), specific leaf area (SLA), leaf dry matter content (LDMC), and drought rating. A genome-wide association study (GWAS) was performed to identify minor and major QTLs. A total of 144 QTLs were identified, including 18 significant QTLs in proximity to 317 candidate genes. Ten significant QTLs on linkage groups (LGs) A03, A05, A06, A07, A08, B04, B05, B06, B09, and B10 were associated with pod weight and pod count. RWC stages 1 and 2 were correlated with pod weight, pod count, and drought rating. Six significant QTLs on LGs A04, A07, B03, and B04 were associated with RWC stages 1 and 2. Drought rating was negatively correlated with pod yield and pod count and was associated with a significant QTL on LG A06. Many QTLs identified in this research are novel for the evaluated traits, with verification that the pod weight shared a significant QTL on chromosome B06 identified in other research. Identified SNP markers and the associated candidate genes provide a resource for molecular marker development. Verification of candidate genes surrounding significant QTLs will facilitate the application of marker-assisted peanut breeding for drought tolerance.

Peanut flavor is a complex and important trait affected by raw material and processing technology owing to its significant impact on consumer preference. In this research, principal component analysis (PCA) on 33 representative traits associated with flavor revealed that total sugars, sucrose, and total tocopherols provided more information related to peanut flavor. Genome-wide association studies (GWAS) using 102 U.S. peanut mini-core accessions were performed to study associations between 12,526 single nucleotide polymorphic (SNP) markers and the three traits. A total of 7 and 22 significant quantitative trait loci (QTLs) were identified to be significantly associated with total sugars and sucrose, respectively. Among these QTLs, four and eight candidate genes for the two traits were mined. In addition, two and five stable QTLs were identified for total sugars and sucrose in both years separately. No significant QTLs were detected for total tocopherols. The results from this research provide useful knowledge about the genetic control of peanut flavor, which will aid in clarifying the molecular mechanisms of flavor research in peanuts.

Twenty-seven genotypes of varieties and advanced breeding lines were grown in two locations in three years with three replications to estimate the effects of the genotype-by-environment interaction (G × E) on the oil and oleic fatty acid contents of cultivated peanuts. Oil and oleic fatty acid contents were quantified using NMR and GC, respectively. The tested lines were genotyped with functional SNP markers from the FAD2A and FAD2B genes using real-time PCR and classified into four genotypes. The results indicated that Alabama was the environment that better discriminated the test genotypes during the year 2012. Eight promising selected genotypes #12, #15, ARSOKR, Brantley, GaHO, M04-149, M04-48, and SunO97R showed wide adaptation and high-oleic acids of 83.02%, 81.32%, 82.03%, 81.15%, 79.21%, 80.94%, 82.46%, and 82.18%, respectively. The Additive Main Effects and Multiplicative Interaction (AMMI) model that combines the conventional analyses of variance for additive main effects with the principal component analysis (PCA) for the non-additive residuals was applied to estimate the additive effects from FAD2A and FAD2B genes and the G × E interaction. The results indicated significant G × E interactions for oleic fatty acid contents. No correlation between oil content and FAD2A and FAD2B genes was found. The FAD2B gene had a larger additive effect than the FAD2A gene. The results from this study may be useful not only for peanut breeders, but also for food processors and product consumers to select suitable cultivars.

Abstract Background Peanut (Arachis hypogaea L.) is a grain legume crop that originated from South America and is now grown around the world. Peanut growth habit affects the variety’s adaptability, planting patterns, mechanized harvesting, disease resistance, and yield. The objective of this study was to map the quantitative trait locus (QTL) associated with peanut growth habit-related traits by combining the genome-wide association analysis (GWAS) and bulked segregant analysis sequencing (BSA-seq) methods. Results GWAS was performed with 17,223 single nucleotide polymorphisms (SNPs) in 103 accessions of the U.S. mini core collection genotyped using an Affymetrix version 2.0 SNP array. With a total of 12,342 high-quality polymorphic SNPs, the 90 suggestive and significant SNPs associated with lateral branch angle (LBA), main stem height (MSH), lateral branch height (LBL), extent radius (ER), and the index of plant type (IOPT) were identified. These SNPs were distributed among 15 chromosomes. A total of 597 associated candidate genes may have important roles in biological processes, hormone signaling, growth, and development. BSA-seq coupled with specific length amplified fragment sequencing (SLAF-seq) method was used to find the association with LBA, an important trait of the peanut growth habit. A 4.08 Mb genomic region on B05 was associated with LBA. Based on the linkage disequilibrium (LD) decay distance, we narrowed down and confirmed the region within the 160 kb region (144,193,467–144,513,467) on B05. Four candidate genes in this region were involved in plant growth. The expression levels of Araip.E64SW detected by qRT-PCR showed significant difference between ‘Jihua 5’ and ‘M130’. Conclusions In this study, the SNP (AX-147,251,085 and AX-144,353,467) associated with LBA by GWAS was overlapped with the results in BSA-seq through combined analysis of GWAS and BSA-seq. Based on LD decay distance, the genome range related to LBA on B05 was shortened to 144,193,467–144,513,467. Three candidate genes related to F-box family proteins (Araip.E64SW, Araip.YG1LK, and Araip.JJ6RA) and one candidate gene related to PPP family proteins (Araip.YU281) may be involved in plant growth and development in this genome region. The expression analysis revealed that Araip.E64SW was involved in peanut growth habits. These candidate genes will provide molecular targets in marker-assisted selection for peanut growth habits.

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.

Traits such as seed weight, shelling percent, percent sound mature kernels, and seed dormancy determines the quality of peanut seed. Few QTL (quantitative trait loci) studies using biparental mapping populations have identified QTL for seed dormancy and seed grade traits. Here, we report a genome-wide association study (GWAS) to detect marker–trait associations for seed germination, dormancy, and seed grading traits in peanut. A total of 120 accessions from the U.S. peanut mini-core collection were evaluated for seed quality traits and genotyped using Axiom SNP (single nucleotide polymorphism) array for peanut. We observed significant variation in seed quality traits in different accessions and different botanical varieties. Through GWAS, we were able to identify multiple regions associated with sound mature kernels, seed weight, shelling percent, seed germination, and dormancy. Some of the genomic regions that were SNP associated with these traits aligned with previously known QTLs. For instance, QTL for seed dormancy has been reported on chromosome A05, and we also found SNP on the same chromosome associated with seed dormancy, explaining around 20% of phenotypic variation. In addition, we found novel genomic regions associated with seed grading, seed germination, and dormancy traits. SNP markers associated with seed quality and dormancy identified here can accelerate the selection process. Further, exploring the function of candidate genes identified in the vicinity of the associated marker will assist in understanding the complex genetic network that governs seed quality.

Abstract Background Spotted wilt, caused by tomato spotted wilt virus (TSWV), has been one of major diseases in cultivated peanut grown in the southeastern United States (US) since 1990. Previously a major quantitative trait locus (QTL) controlling spotted wilt disease resistance was mapped to an interval of 2.55 cM genetic distance corresponding to a physical distance of 14.4 Mb on chromosome A01 of peanut by using a segregating F2 population. The current study focuses on refining this major QTL region and evaluating its contributions in the US peanut mini-core germplasm. Results Two simple sequence repeat (SSR) markers associated with the major QTL were used to genotype F5 individuals, and 25 heterozygous individuals were selected and developed into an F6 segregating population. Based on visual evaluation in the field, a total of 194 susceptible F6 individuals were selected and planted into F7 generation for phenotyping. Nine SSR markers were used to genotype the 194 F6 individuals, and QTL analysis revealed that a confidence interval of 15.2 Mb region had the QTL with 22.8% phenotypic variation explained (PVE). This QTL interval was further genotyped using the Amplicon-seq method. A total of 81 non-redundant single nucleotide polymorphism (SNP) and eight InDel markers were detected. No recombinant was detected among the F6 individuals. Two InDel markers were integrated into the linkage group and helped to refine the confidence interval of this QTL into a 0.8 Mb region. To test the QTL contributes to the resistance variance in US peanut mini-core germplasm, two flanking SSR markers were used to genotype 107 mini-core germplasm accessions. No statistically significant association was observed between the genotype at the QTL region and spotted wilt resistance in the mini-core germplasm, which indicated that the resistance allelic region at this QTL didn’t contribute to the resistance variance in the US peanut mini-core germplasm, thus was a unique resistance source. Conclusion A major QTL related to spotted wilt disease resistance in peanut was refined to a 0.8 Mb region on A01 chromosome, which didn’t relate to spotted wilt disease resistance in the US peanut mini-core germplasm and might be a unique genetic source.

Objective: Lymph node yield in therapeutic neck dissection is clinically significant and incompletely studied. We quantified node yield based on extent of neck dissection and presence of preoperative radiation. We also evaluated factors affecting incidence of extracapsular spread (ECS). Methods: Retrospective review of 499 patients undergoing therapeutic neck dissection; 414 patients met inclusion criteria and were divided into 2 groups: neck dissection alone or before radiation (surgery first: 280 patients; 385 dissections) and primary radiation before surgery (radiation first: 134 patients; 157 dissections). Node yield relative to levels dissected and incidence of ECS were examined. Results: Dissection-specific node yield was greater in the surgery first group for dissection of levels I-V (31.1 ± 16.7 vs 24.0 ± 14.7, P < .001) and levels II-V (26.7 ± 14.4 vs 21.1 ± 10.7). Extracapsular spread incidence was 32.1% (98/305) in the surgery first group and 15.4% (23/149) in the radiation first group (P < .001). Conclusion: This study clarifies anticipated node yield based on number of levels dissected and presence of preoperative radiation. Node yield and incidence of ECS are lower in patients undergoing preoperative radiation. [ABSTRACT FROM AUTHOR]

Background: Peanut (Arachis hypogaea L.) is an important crop economically and nutritionally, and is one of the most susceptible host crops to colonization of Aspergillus parasiticus and subsequent aflatoxin contamination. Knowledge from molecular genetic studies could help to devise strategies in alleviating this problem; however, few peanut DNA sequences are available in the public database. In order to understand the molecular basis of host resistance to aflatoxin contamination, a large-scale project was conducted to generate expressed sequence tags (ESTs) from developing seeds to identify resistance-related genes involved in defense response against Aspergillus infection and subsequent aflatoxin contamination. Results: We constructed six different cDNA libraries derived from developing peanut seeds at three reproduction stages (R5, R6 and R7) from a resistant and a susceptible cultivated peanut genotypes, 'Tifrunner' (susceptible to Aspergillus infection with higher aflatoxin contamination and resistant to TSWV) and 'GT-C20' (resistant to Aspergillus with reduced aflatoxin contamination and susceptible to TSWV). The developing peanut seed tissues were challenged by A. parasiticus and drought stress in the field. A total of 24,192 randomly selected cDNA clones from six libraries were sequenced. After removing vector sequences and quality trimming, 21,777 high-quality EST sequences were generated. Sequence clustering and assembling resulted in 8,689 unique EST sequences with 1,741 tentative consensus EST sequences (TCs) and 6,948 singleton ESTs. Functional classification was performed according to MIPS functional catalogue criteria. The unique EST sequences were divided into twenty-two categories. A similarity search against the nonredundant protein database available from NCBI indicated that 84.78% of total ESTs showed significant similarity to known proteins, of which 165 genes had been previously reported in peanuts. There were differences in overall expression patterns in different libraries and genotypes. A number of sequences were expressed throughout all of the libraries, representing constitutive expressed sequences. In order to identify resistance-related genes with significantly differential expression, a statistical analysis to estimate the relative abundance (R) was used to compare the relative abundance of each gene transcripts in each cDNA library. Thirty six and forty seven unique EST sequences with threshold of R > 4 from libraries of 'GT-C20' and 'Tifrunner', respectively, were selected for examination of temporal gene expression patterns according to EST frequencies. Nine and eight resistance-related genes with significant up-regulation were obtained in 'GT-C20' and 'Tifrunner' libraries, respectively. Among them, three genes were common in both genotypes. Furthermore, a comparison of our EST sequences with other plant sequences in the TIGR Gene Indices libraries showed that the percentage of peanut EST matched to Arabidopsis thaliana, maize (Zea mays), Medicago truncatula, rapeseed (Brassica napus), rice (Oryza sativa), soybean (Glycine max) and wheat (Triticum aestivum) ESTs ranged from 33.84% to 79.46% with the sequence identity ≥ 80%. These results revealed that peanut ESTs are more closely related to legume species than to cereal crops, and more homologous to dicot than to monocot plant species. Conclusion: The developed ESTs can be used to discover novel sequences or genes, to identify resistance-related genes and to detect the differences among alleles or markers between these resistant and susceptible peanut genotypes. Additionally, this large collection of cultivated peanut EST sequences will make it possible to construct microarrays for gene expression studies and for further characterization of host resistance mechanisms. It will be a valuable genomic resource for the peanut community.… [ABSTRACT FROM AUTHOR]