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Ethylene plays essential roles in plant growth, development and stress responses. The ethylene signaling pathway and molecular mechanism have been studied extensively in Arabidopsis and rice but limited in peanuts. Here, we established a sand-culture method to screen pingyangmycin mutagenized peanut lines based on their specific response to ethylene (“triple response“). An ethylene-insensitive mutant, inhibition of peanut hypocotyl elongation 1 (iph1), was identified that showed reduced sensitivity to ethylene in both hypocotyl elongation and root growth. Through bulked segregant analysis sequencing, a major gene related to iph1, named AhIPH1, was preliminarily mapped at the chromosome Arahy.01, and further narrowed to a 450-kb genomic region through substitution mapping strategy. A total of 7014 genes were differentially expressed among the ACC treatment through RNA-seq analysis, of which only the Arahy.5BLU0Q gene in the candidate mapping interval was differentially expressed between WT and mutant iph1. Integrating sequence variations, functional annotation and transcriptome analysis revealed that a predicated gene, Arahy.5BLU0Q, encoding SNF1 protein kinase, may be the candidate gene for AhIPH1. This gene contained two single-nucleotide polymorphisms at promoter region and was more highly expressed in iph1 than WT. Our findings reveal a novel ethylene-responsive gene, which provides a theoretical foundation and new genetic resources for the mechanism of ethylene signaling in peanuts.

Abstract Background The cultivated peanut (Arachis hypogaea L., AABB) is an allotetraploid hybrid between two diploid peanuts, A. duranensis (AA genome) and A. ipaensis (BB genome). Miniature inverted-repeat transposable elements (MITEs), some of which are known as active nonautonomous DNA transposons with high copy numbers, play important roles in genome evolution and diversification. AhMITE1, a member of the MITE family of transposons, but information on the peanut genomes is still limited. Here, we analyzed AhMITE1, AuMITE1 and ApMITE1 in the cultivated (A. hypogaea) and two wild peanut (A. duranensis and A. ipaensis) genomes. Results The cultivated and the two wild peanut genomes harbored 142, 14 and 21 AhMITE1, AuMITE1 and ApMITE1 family members, respectively. These three family members exhibited highly conserved TIR sequences, and insertions preferentially occurred within 2 kb upstream and downstream of gene-coding and AT-rich regions. Phylogenetic and pairwise nucleotide diversity analysis showed that AhMITE1 and ApMITE1 family members have undergone one round of amplification bursts during the evolution of the peanut genome. PCR analyses were performed in 23 peanut varieties and demonstrated that AhMITE1 is an active transposon and that hybridization or chemical mutagenesis can promote the mobilization of AhMITE1. Conclusions AhMITE1, AuMITE1 and ApMITE1 family members were identified based on local BLAST search with MAK between the cultivated and the two wild peanut genomes. The phylogenetic, nucleotide diversity and variation copy numbers of AhMITE1, AuMITE1 and ApMITE1 members provides opportunities for investigating their roles during peanut evolution. These findings will contribute to knowledge on diversity of AhMITE1, provide information about the potential impact on the gene expression and promote the development of DNA markers in peanut.

Background: Late embryogenesis abundant (LEA) proteins were reported to be related to adversity stress and drought tolerance. Lea-3 from Arachis hypogaea L. (AhLea-3) was previously found to be related to salt tolerance according to the result of transcriptome profiling and digital gene expression analysis. So, AhLea-3 was cloned and the salt tolerance was validated by transgenic peanut plants. Results: AhLea-3 was isolated from M34, a salt-resistant mutant of peanut, with its cDNA as the template. AhLea-3 contains one intron and two extrons, and the full-length cDNA sequence contains 303 bp. AhLea-3 was ligated to pCAMBIA1301 to obtain the overexpression vector pCAMBIA1301-AhLea-3, which was then transferred into peanut variety Huayu23. The expression level of AhLea-3, as determined by qRT-PCR analysis, was >10 times higher in transgenic than in non-transgenic plants. Five days after they were irrigated with 250 mM NaCl, the transgenic plants showed less severe leaf wilting, higher activities of antioxidant enzymes (superoxide dismutase, peroxidase, and catalase), and lower malonic dialdehyde content than non-transgenic plants. Relative to non-transgenic plants, the transgenic plants had a higher photosynthetic net rate, stomatal conductance, and transpiration rate, and a lower intercellular CO2 concentration after salt stress treatment (250 mM NaCl). Conclusions: These results indicate that overexpression of AhLea-3 increased the salt tolerance of transgenic peanut plants. AhLea-3 might become a useful gene resource for the variety breeding of salinity tolerance in peanut.How to cite: Qiao L, Jiang P, Tang Y, et al. Characterization of AhLea-3 and its enhancement of salt tolerance in transgenic peanut plants. Electron J Biotechnol 2020; 49. https://doi.org/10.1016/j.ejbt.2020.10.006

Background: Soil salinity can significantly reduce crop production, but the molecular mechanism of salinity tolerance in peanut is poorly understood. A mutant (S1) with higher salinity resistance than its mutagenic parent HY22 (S3) was obtained. Transcriptome sequencing and digital gene expression (DGE) analysis were performed with leaves of S1 and S3 before and after plants were irrigated with 250 mM NaCl. Results: A total of 107,725 comprehensive transcripts were assembled into 67,738 unigenes using TIGR Gene Indices clustering tools (TGICL). All unigenes were searched against the euKaryotic Ortholog Groups (KOG), gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases, and these unigenes were assigned to 26 functional KOG categories, 56 GO terms, 32 KEGG groups, respectively. In total 112 differentially expressed genes (DEGs) between S1 and S3 after salinity stress were screened, among them, 86 were responsive to salinity stress in S1 and/or S3. These 86 DEGs included genes that encoded the following kinds of proteins that are known to be involved in resistance to salinity stress: late embryogenesis abundant proteins (LEAs), major intrinsic proteins (MIPs) or aquaporins, metallothioneins (MTs), lipid transfer protein (LTP), calcineurin B-like protein-interacting protein kinases (CIPKs), 9-cis-epoxycarotenoid dioxygenase (NCED) and oleosins, etc. Of these 86 DEGs, 18 could not be matched with known proteins. Conclusion: The results from this study will be useful for further research on the mechanism of salinity resistance and will provide a useful gene resource for the variety breeding of salinity resistance in peanut. Keywords: Digital gene expression, Gene, Mutant, NaCl, Peanut (Arachis hypogaea L.), RNA-seq, Salinity stress, Salinity tolerance, Soil salinity, Transcripts, Unigenes

Soil salinity seriously limits plant growth and yield. Strategies have been developed for plants to cope with various environmental stresses during evolution. To screen for the broad-spectrum genes and the molecular mechanism about a hydroxyproline-tolerant mutant of peanut with enhanced salinity resistance under salinity stress, digital gene expression (DGE) sequencing was performed in the leaves of salinity-resistant mutant (S2) and Huayu20 as control (S4) under salt stress. The results indicate that major transcription factor families linked to salinity stress responses (NAC, bHLH, WRKY, AP2/ERF) are differentially expressed in the leaves of peanut under salinity stress. In addition, genes related to cell wall loosening and stiffening (xyloglucan endotransglucosylase/hydrolases, peroxidases, lipid transfer protein, expansin, extension), late embryogenesis abundant protein family, fatty acid biosynthesis and metabolism (13-lipoxygenase omega-6 fatty acid desaturase, omega-3 fatty acid desaturase) and some previously reported stress-related genes encoding proteins such as defensin, universal stress protein, metallothionein, peroxidase etc, and some other known or unknown function stress related genes, have been identified. The information from this study will be useful for further research on the mechanism of salinity resistance and will provide a useful genomic resource for the breeding of salinity resistance variety in peanut.

Peanut is vulnerable to a range of diseases, such as Tomato spotted wilt virus (TSWV) and leaf spots which will cause significant yield loss. The most sustainable, economical and eco-friendly solution for managing peanut diseases is development of improved cultivars with high level of resistance. We developed a recombinant inbred line population from the cross between SunOleic 97R and NC94022, named as the S-population. An improved genetic linkage map was developed for the S-population with 248 marker loci and a marker density of 5.7 cM/loci. This genetic map was also compared with the physical map of diploid progenitors of tetraploid peanut, resulting in an overall co-linearity of about 60% with the average co-linearity of 68% for the A sub-genome and 47% for the B sub-genome. The analysis using the improved genetic map and multi-season (2010-2013) phenotypic data resulted in the identification of 48 quantitative trait loci (QTLs) with phenotypic variance explained (PVE) from 3.88 to 29.14%. Of the 48 QTLs, six QTLs were identified for resistance to TSWV, 22 QTLs for early leaf spot (ELS) and 20 QTLs for late leaf spot (LLS), which included four, six, and six major QTLs (PVE larger than 10%) for each disease, respectively. A total of six major genomic regions (MGR) were found to have QTLs controlling more than one disease resistance. The identified QTLs and resistance gene-rich MGRs will facilitate further discovery of resistance genes and development of molecular markers for these important diseases.

In order to enlarge the potential resources of drought-tolerant peanuts, we conducted in vitro mutagenesis with Pingyangmycin (PYM) as the mutagen as well as directed screening on a medium supplemented with Hydroxyproline (HYP). After being extracted from mature seeds (cv. Huayu 20), the embryonic leaflets were cultured on somatic embryogenesis-induction medium with 4 mg/L PYM and the generated embryos were successively transferred to a germination medium with 4 and then 8 mmol/L HYP to screen HYP-tolerant plantlets. After that, these plantlets were grafted and transplanted to the experimental field. In the next generation, all seeds were sown in the field, and phenotype variation and trait segregation can be observed in most of the offspring (M2 generation). The M3 generation individuals were subjected to drought stress at the seedling stages. The activities of SOD and POD were substantially increased in eight offspring of 11 HYP-tolerant, regenerated plants than in their mutagenic parents. To determine the correlation between mutant phenotypes and genomic modification, we carried out a comparison of the DNA polymorphisms between the mutagenic parents and 13 M3 generation individuals from different HYP-tolerant, regenerated plants with SSR primers. Results showed that most mutants and parent plants had signs of polymorphisms. Under drought stress, some M3 generation individuals of 10 original HYP-tolerant, regenerated plants produced more pods than the mutagenic parent; twenty individuals among them produced >60 g pods/plant. M4-generation seeds were tested for quality characteristics by Near Infrared Spectroscopy (NIS) and nine individuals with higher protein content (>30%) and 21 individuals with higher oil content (>58%) were screened. We concluded that the use of PYM-based in vitro mutagenesis in combination with directed screening with HYP is effective for the creation of potential drought-tolerant mutants of peanut.

Peanut, a high-oil crop with about 50% oil content, is either crushed for oil or used as edible products. Fatty acid composition determines the oil quality which has high relevance to consumer health, flavor, and shelf life of commercial products. In addition to the major fatty acids, oleic acid (C18:1) and linoleic acid (C18:2) accounting for about 80% of peanut oil, the six other fatty acids namely palmitic acid (C16:0), stearic acid (C18:0), arachidic acid (C20:0), gadoleic acid (C20:1), behenic acid (C22:0), and lignoceric acid (C24:0) are accounted for the rest 20%. To determine the genetic basis and to improve further understanding on effect of FAD2 genes on these fatty acids, two recombinant inbred line (RIL) populations namely S-population (high oleic line 'SunOleic 97R' × low oleic line 'NC94022') and T-population (normal oleic line 'Tifrunner' × low oleic line 'GT-C20') were developed. Genetic maps with 206 and 378 marker loci for the S- and the T-population, respectively were used for quantitative trait locus (QTL) analysis. As a result, a total of 164 main-effect (M-QTLs) and 27 epistatic (E-QTLs) QTLs associated with the minor fatty acids were identified with 0.16% to 40.56% phenotypic variation explained (PVE). Thirty four major QTLs (>10% of PVE) mapped on five linkage groups and 28 clusters containing more than three QTLs were also identified. These results suggest that the major QTLs with large additive effects would play an important role in controlling composition of these minor fatty acids in addition to the oleic and linoleic acids in peanut oil. The interrelationship among these fatty acids should be considered while breeding for improved peanut genotypes with good oil quality and desired fatty acid composition.

One mapping population derived from Tifrunner × GT-C20 has shown great potential in developing a high density genetic map and identifying quantitative trait loci (QTL) for important disease resistance, tomato spotted wilt virus (TSWV) and leaf spot (LS). Both F and F generation-based genetic maps were previously constructed with 318 and 239 marker loci, respectively. Higher map density could be achieved with the F map (5.3 cM per locus) as compared to the F (5.7 cM per locus). Quantitative trait loci analysis using multi-environment phenotyping data from F and higher generations for disease resistance identified 54 QTL in the F map including two QTL for thrips (12.14–19.43% phenotypic variation explained [PVE]), 15 for TSWV (4.40–34.92% PVE), and 37 for LS (6.61–27.35% PVE). Twenty-three QTL could be identified in the F map including one QTL for thrips (5.86% PVE), nine for TSWV (5.20–14.14% PVE), and 13 for LS (5.95–21.45% PVE). Consistent QTL identified in each map have shown higher phenotypic variance than nonconsistent QTL. As expected, the number of QTL and their estimates of phenotypic variance were lower in the F map. This is the first QTL study reporting novel QTL for thrips, TSWV, and LS in peanut ( L.), and therefore, future studies will be conducted to refine these QTL.