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Screening of Salinity Tolerance and Genome-Wide Association Study in 249 Peanut Accessions (Arachis hypogaea L.)
Plant Breed. Biotech. 2020;8:434-438
Published online December 1, 2020
© 2020 Korean Society of Breeding Science.

Kunyan Zou1, Dongwoo Kang1, Ki-Seung Kim2*, Tae-Hwan Jun1,3*

1Department of Plant Bioscience, Pusan National University, Miryang 50463, Korea
2FarmHannong, Ltd., Daejeon 34115, Korea
3Life and Industry Convergence Research Institute, Pusan National University, Miryang 50463, Korea
Corresponding author: Ki-Seung Kim,, Tel: +82-41-730-9159, Fax: +82-41-742-8516
Tae-Hwan Jun,, Tel: +82-55-350-5507, Fax: +82-55-350-5509
Received September 21, 2020; Revised October 6, 2020; Accepted October 8, 2020.
This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Salinity stress is one of the important abiotic stresses in crops. In this study, ten different concentrations of NaCl solutions were tested to determine the optimal level of NaCl concentration for salinity tolerance test at the germination stage in peanut, and 0.6% NaC1 was suitable for the test. A total of 249 peanut accessions were tested with 0.6% NaC1 and radical root lengths of the accessions were measured. The results showed that there were significant genetic variations on the tolerance to salinity stress among the tested accessions. Through a Genome-Wide Association Study (GWAS) using the Axiom_Arachis array with 58K SNPs, three putative SNPs with significant relation to radicle root length were identified on chromosomes Aradu.A03, Araip.B01, and Araip.B05.
Keywords : Peanut, Germination stage, Salinity tolerance, Genome-Wide Association Study

As one of the economic oilseeds, Peanut (Arachis hypogaea L.) or groundnut is the second important cultivated legume in the world (Kavi Kishor et al. 2018). Salinity stress is one of the important abiotic stresses across the crops (El-Akhal et al. 2013) and soil salinization has been steadily increasing in the world (Ahmad et al. 2019). Excessive salinity could adversely affect seed germination, seedling growth, water and mineral uptake, photosynthetic efficiency and cause osmotic stress, yield reduction, and death of plants (Singh and Prasad 2009; Qin et al. 2011; Sui et al. 2018). Roots are in direct contact with soil solution and the length of roots is an important measure to the response of plants under salt stress (Mbarki et al. 2020). In four grasspea (Lathyrus sativus) cultivars, the effects of different salinity concentrations on radicle and hypocotyl length were evaluated, and the results showed that salinity stress had significant effect on seed germination percentage and germination index, indicating that genetic variation exists within the cultivars (Mahdavi et al. 2007).

Several studies have been conducted to assess salinity tolerance in different crop species: wild rice (Quan et al. 2017), tomato (Wang et al. 2020), and soybean (Do et al. 2019). Although peanut is considered as a moderately sensitive species to salinity stress (Cui et al. 2018), a few reports on salinity tolerance in peanut have been reported. Chen et al. (2015) reported 7 materials (JS011, JS024, JS125, JS491, JS523, JS524 and JS525) as salt tolerance germplasms by screening of a total of 128 peanut germplasms under 2.5% NaCl solution. The relative germination potential, relative germination rate and relative germination index were used to identify the salt tolerance of 41 Chinese peanut varieties during germination, and three salt tolerance cultivars and two salt sensitive cultivars were selected (Liu et al. 2012). High-density SNP arrays have been widely used in many crop species and the Axiom_Arachis array (Pandey et al. 2017) has been developed for peanut. The present study was conducted 1) to determine the optimal NaCl concentration to test salinity tolerance at the germination stage, 2) to evaluate salinity tolerance of 249 peanut accessions, and 3) to identify genomic regions related to salinity tolerance by GWAS.


Plant materials and genotyping

A total of 249 peanut accessions were used for the present study (Supplementary Table S1). Seventy-four Korean accessions and the US core collection were ob-tained from the RDA-GenBank Information Center, South Korea and the US Department of Agriculture, respectively. DNA from each accession was extracted using the Cetyl Trimethyl Ammonium Bromide (CTAB) method (Saghai-Maroof et al. 1984). The quality and quantity of the extracted DNA were determined using a NanoDrop ND-1000 (Thermos Fisher Scientific Inc., USA) and agarose-gel electrophoresis. The Axiom_Arachis array with 58K SNPs was used for genotyping.

Salinity tolerance test and phenotyping

To determine the optimal NaCl concentration for salinity-tolerance screening during the germination stage, ten gradient NaC1 solutions from 0.3% to 1.2% w/v were tested to Korean peanut cultivar K-OL. The same volume of sterilized distilled water was added for control (CK). The test was conducted in an incubator with 24 hours dark and 26℃. The solutions were replaced every two days and germination was continuously counted during six days. The following parameters were calculated; Germination rate (GR, %) = (number of germinated seeds /number of tested seeds) ×100; Relative germination index (RGI, %) = (number of germinated seeds /number of CK seeds) ×100; Salt damage rate (SDR, %) = [(number of CK seeds ‒ number of germinated seeds) /number of CK seeds] ×100. The 249 accessions were also tested with CK and the selected NaC1 concentration. Ten seeds per accession (5 seeds × 2 reps) were tested and measured for the radicle root length on the seventh days.

Statistical analysis of phenotyping data

The phenotype data were analyzed using the SPSS 15.0 software to conduct a normal distribution in the accessions. Wilcoxon rank-sum (WRS) test with continuity correction was used for t-test of phenotype data, and a boxplot data visualization was performed using Qrigin software (

Genome-wide association analysis

SNPs in Axiom_Arachis array were analyzed by R software analysis tools (Zhang et al. 2010; Lipka et al. 2012). The GAPIT package of R software was used to conduct GWAS and the compressed mixed linear model (CMLM) was used for the association analysis of SNPs to the radicle length (Tang et al. 2016).


There was no significant difference in GR, RGI, and SDR between CK and 0.1-0.3% NaC1 concentrations while significant differences were detected in the others. The SDR showed positive correlation with salinity concentration while GR and RGI were opposite (Fig. 1). The 0.6% NaCl was selected for future test because the concentration could clearly differentiate tolerance or sensiti-vity to salinity during the germination stage.

Figure 1. Effects of NaCl concentrations on three parameters.

The radicle root lengths of 249 accessions were examined with CK and 0.6% NaCl at the germination stage. The result was presented in Supplementary Table S1 and presented a normal distribution (Fig. 2a). There was significant difference in the root lengths between Korean accessions and the core collections, and it is likely that the germination ability of the core collections was stronger than that of Korean (Fig. 2b) at the 0.05 probability level. Ten accessions with high tolerance or sensitivity were listed in Table 1.

Table 1 . Ten highly sensitive and tolerant accessions to salinity stress in the 249 accessions.

Accession No.Improvement statusOriginName0.6% NaCl root length (cm)/CK root length (cm)
GWP260Core collectionArgentinaFAV 630.079
GWP242Core collectionPortugalAmendoim de Andalazia, Espanha0.121
GWP035CultivarKorea, SouthSaedeul Ttangkong0.123
GWP096CultivarKorea, SouthIlpyeong0.135
GWP131Core collectionUruguay56.1340.137
GWP058CultivarKorea, SouthSuweon 1000.166
GWP130Core collectionCubaNO 156120.170
GWP317Core collectionTaiwanCC7370.175
GWP086CultivarKorea, SouthBaekan0.177
GWP023CultivarKorea, SouthSuweon 370.178
GWP064LandraceKorea, SouthJeonnam Damyang-1995-62770.889
GWP175Core collectionZambiaAB260.890
GWP225Core collectionIndiaCC2210.932
GWP261Core collectionMoroccoWHITE SPANISH 320.939
GWP346Core collectionZimbabweTGR 2650.996
GWP277Core collectionMexicoCC2851.059
GWP118Core collectionSouth AfricaNatal Common1.068
GWP303Core collectionNigeriaCC2961.098
GWP110Core collectionSenegal40-751.205
GWP227Core collectionIndiaCC2301.299

Figure 2. (a) The normal distribution of radical root lengths in 249 accessions; (b) Boxplot indicating the phenotype of the 0.6% NaCl root length (cm)/CK root length (cm) between Korean accessions and the core collection. Each box depicts the upper and lower values, with the median values being represented by a horizontal solid line. Outliers are pointed by diamond symbol.

A total of 6,003 SNPs were selected for GWAS and three SNPs significantly (P < 0.001) related to the radicle length were identified on chromosomes Aradu.A03, Araip.B01, and Araip.B05 (Table 2, Supplementary Table S2, and Fig. 3a). The QQ plot represented that the population structure and kinship relationship were well controlled in the GWAS analysis (Fig. 3b).

Table 2 . SNPs associated with the radicle root length under the salinity stress.

SNP nameChromosomePosition (bp)P-value

Figure 3. (a) Manhattan plot of a genome-wide association analysis; (b) Q-Q (quantile-quantile) plot.

Relatively few studies on salt tolerance in peanut have been reported of. Therefore, it would be important to find and establish effective methods for evaluating salinity tolerance. Because peanut at the germination stage is very sensitive to the external environment (Badigannavar et al. 2007), evaluation at the stage could test effectively and quickly large quantities of materials. The results of this study about screening method, selecting highly tolerant accessions, and SNP markers could provide a cornerstone of molecular breeding for salinity tolerance in peanut.

PBB-8-434_SuppleT1.xlsx PBB-8-434_SuppleT2.xlsx

This research was carried out with the support of the “Cooperative Research Program for Agriculture Science and Technology Development (Project No. PJ013125022020)” Rural Development Administration, Republic of Korea.

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