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Electronic Journal of Biotechnology

On-line version ISSN 0717-3458

Electron. J. Biotechnol. vol.17 no.6 Valparaíso Nov. 2014

http://dx.doi.org/10.1016/j.ejbt.2014.09.004 

RESEARCH ARTICLE

Isolation and characterization of drought-responsive genes from peanut roots by suppression subtractive hybridization

 

Hong Ding, Zhi Meng Zhang*, Fei Fei Qin, Liang Xiang Dai, Chun Juan Li, Dun Wei Ci, Wen Wu Song

Shandong Peanut Research Institute, 126 Wannianquan Rd., Qingdao 266100, China


ABSTRACT

Background

Peanut (Arachis hypogaea L.) is an important economic and oilseed crop. Long-term rainless conditions and seasonal droughts can limit peanut yields and were conducive to preharvest aflatoxin contamination. To elucidate the molecular mechanisms by which peanut responds and adapts to water limited conditions, we isolated and characterized several drought-induced genes from peanut roots using a suppression subtractive hybridization (SSH) technique.

Results

RNA was extracted from peanut roots subjected to a water stress treatment (45% field capacity) and from control plants (75% field capacity), and used to generate an SSH cDNA library. A total of 111 non-redundant sequences were obtained, with 80 unique transcripts showing homology to known genes and 31 clones with no similarity to either hypothetical or known proteins. GO and KEGG analyses of these differentially expressed ESTs indicated that drought-related responses in peanut could mainly be attributed to genes involved in cellular structure and metabolism. In addition, we examined the expression patterns of seven differentially expressed candidate genes using real-time reverse transcription-PCR (qRT-PCR) and confirmed that all were up-regulated in roots in response to drought stress, but to differing extents.

Conclusions

We successfully constructed an SSH cDNA library in peanut roots and identified several drought-related genes. Our results serve as a foundation for future studies into the elucidation of the drought stress response mechanisms of peanut.

Keywords: Drought-related genes; Drought stress; GO and KEGG analyses; Real-time reverse transcription-PCR


 

1. Introduction

Peanut (Arachis hypogaea L.) is an important economic and oilseed crop, which is mainly grown under rain-fed conditions in arid and semi-arid regions. Consequently, drought is a major production constraint since rainfall is generally both erratic and inadequate [ 1, 2]. Hence, improving the drought tolerance of peanut is a key objective. Genetic engineering is one approach that could be used, but requires prior information about drought stress-related genes in peanut. However, the molecular mechanisms by which peanut adapts to water stress are not well described. The peanut genome is very large in comparison to other plant species, making it difficult to study. Thus, a detailed understanding of peanut water stress tolerance would be highly informative and, moreover, the altered expression of key genes may enhance peanut drought tolerance.

Studies into the mechanisms of peanut drought resistance have previously focused on aboveground plant tissues. For instance, nearly 700 genes were identified as being enriched in a subtractive cDNA library generated from peanut leaves exposed to a gradual drought stress treatment [3]; and a proteomic analysis of the water-deficit stress response in three contrasting peanut genotypes implicated a variety of stress response mechanisms as being active in peanut [4]. Dang et al. [5] analyzed the gene expression of twelve transcription factors from two drought tolerant peanut genotypes under drought conditions and identified the expression patterns of drought-inducible transcripts.

As the major interface between the plant and the various biotic and abiotic factors in the soil environment, root tissues may produce root-to-shoot chemical signals that regulate stomatal closure and thus reduce transpiration [6,7]. However, there is currently limited information on the root responses of peanut under water deficit conditions, particularly at the molecular level. Suppression subtractive hybridization (SSH) is a powerful technique for the identification of differentially expressed genes and for the enrichment of genes with low expression levels [8]. There are several examples in the literature where the SSH approach has been successfully employed to screen for candidate genes, including the identification of chilling-responsive transcripts in peanut [9], and the isolation of a submergence-induced gene, OsGGT (glycogenin glucosyltransferase) in rice [10]. Hence, we utilized an SSH strategy to isolate and characterize drought-induced transcripts from peanut roots. A better understanding of the key genes involved in peanut stress response is vital for the development of plants that can maintain high yields under drought conditions, and the cultivation of drought-resistant peanut varieties.

2. Materials and methods

2.1. Plant growth and drought stress treatment

A. hypogaea cv Huayu 25 were used in this study. Plants were grown in a growth chamber at 28°C/18°C (day/night), and 300 µmoL m- 2 s- 1 light intensity provided by reflector sunlight dysprosium lamps (DDF 400, Nanjing, China). The water stress treatment was as described by Govind et al. [3]. The amount of water held by the soil is expressed as a mass percentage, and it is considered as 100% field capacity (FC) of soil. Three different water treatments were considered in this study: 75%, 45% and 20% FC with 75% FC serving as the control treatment. Plants were held at one of the three different water treatments (75%, 45% and 20% FC) for the plants planted at 75% FC for 25 d after sowing. The water stress treatment was maintained for a total of 5 d and was monitored gravimetrically by weighing the pots twice daily. The fresh roots, first nodal leaves and the first main stem were harvested at the end of the stress period from three treated plants for RNA isolation. The second fully expanded leaves were harvested for the measurement of leaf relative water content (RWC). The RWC was calculated as described by Barrs and Weatherly [11]:

RWC(%) = [(Fresh wt - dry wt)/(Turgid wt - dry wt)] × 100.

2.2. Isolation of total RNA and cDNA synthesis

Total RNA was isolated from the frozen roots using RNAprep pure Plant Kit (Tiangen, Beijing, China) according to the manufacturer's instructions. RNA was treated with recombinant RNase-free DNaseI (Takara, Toyoto, Japan) to avoid genomic DNA contamination before cDNA synthesis. RNA integrity was verified by 1% agarose gel electrophoresis, with only RNA preparations having an A260/A280 ratio of 1.8-2.0 and an A260/A230 ratio > 2.0 used for subsequent analysis. cDNA was synthesized using SMARTer™ PCR cDNA Synthesis Kit (Clontech, Mountain View, CA, USA) as described by the manufacturer. The cDNA was purified by column chromatography and digested with RsaI for SSH library construction.

2.3. Construction of an SSH cDNA library

A subtractive cDNA library was constructed using the PCR Select™ cDNA subtraction kit (Clontech, Mountain View, CA, USA) according to the manufacturer's instructions. The 45% FC root cDNA was used as the tester and the 75% FC root cDNA as the driver for SSH. The digested cDNA were ligated to adapters 1 and 2R supplied with the PCR-Select cDNA Subtraction Kit. After two rounds of hybridization and PCR amplification, the differentially expressed cDNAs were normalized and enriched. The subtracted and enriched DNA fragments were purified by QIAquick PCR Purification Kit (Qiagen, Hilden, Germany). The PCR products were ligated to pGEM-T Easy vector (Promega Co., USA) and transformed into DH5α cells using heat shock. Transformants were isolated from white colonies on X-gal/isopropyl-beta-d-thio-galatopyranoside agar plates. Positive colonies were identified by colony PCR. PCR products were separated on a 2% agarose gel to detect the amplification quality and quantity.

2.4. Sequencing and sequence analysis

The clones were sequenced by Sangon (Shanghai, China). The vector and adaptor sequences were removed using the DNAman software, and masked repeats, rRNA and low complicity sequences were eliminated using RepeatMasker. The sequences were searched against the NCBI database using BLASTN and BLASTX. Transcript annotation and functional assignment were performed using Blast2GO (http://blast2go.org).

2.5. Quantitative real time PCR analysis (qRT-PCR)

Total RNA for qRT-PCR analysis was treated with recombinant RNase-free DNaseI (Takara, Toyoto, Japan) to remove any contaminating genomic DNA. First-strand cDNA was synthesized using SuperScript III reverse transcriptase (Invitrogen, USA). Primer pairs were designed using the Primer 5.0 software (Table 1). ACT11 was used as a reference gene for the normalization of all data [12]. qRT-PCR was carried out in a Lightcycler 2.0 PCR machine (Roche, USA) based on SYBR Premix Ex Taq polymerase (Takara, Toyoto, Japan). The thermal protocol consisted of 95°C for 30 s, then 40 cycles of amplification at 95°C for 5 s, 60°C for 20 s, and 72°C for 15 s. Melting curves were obtained by slow heating from 65°C to 95°C at 0.1°C/s and continuous monitoring of the fluorescence signal. The reactions were performed in 20 µL volumes containing 2 µL of cDNA solution, 10 µL 2 × SYBR Premix and 0.4 µL (10 µM) of each primer. Each experiment was replicated three times. The comparative Ct method was applied.

 

Table 1. Sequences of qRT-PCR primers used in this study.

Gene Forward primer (5'-3') Reverse primer (5'-3')
STPK TCCAAATGGGCAAATGAAACC ATTCCATCGTTCGTCTGTTTCG
ANN TTTGTGGCAGCGGTTATTATGTC ATCCCAACCCAAACCACCTACAT
P5CS GTCCTGTAGGAGTTGAGGGTTTG TTTAGTGGCAGTTCTTTATGAGTGT
GolS GGTTCACTATTGTGCTGCTGGGT CCTCATATATCTCCCACCATTTCTTA
ADH CGAATGATGCACCTGATGG CCCGAACCGATCTTCCTAAT
MnSOD TATGCCAGCGAAGTGTATGAAAAAG GTCTTATATGCCACATTACATCCTTTT
Gsi-83 GACGGTGCCGAGGGTGAGA AGCAAGCAGTAATGGCGGAGA
ACT11 TTGGAATGGGTCAGAAGGATGC AGTGGTGCCTCAGTAAGAAGC

 

3. Results

3.1. Performance of peanut under drought stress

Huayu 25 has been identified as a peanut variety with strong drought tolerance. An obvious difference in phenotype was observed between plants subjected to drought stress and well-watered plants (Fig. 1a). Visible symptoms such as leaf rolling and leaf thinning were seen in the plants subjected to drought stress, and the leaves of the control plants were greener than those of the stressed plants. The RWC of the leaves decreased in line with the increasing degree of drought stress with the 20% FC treated plants exhibiting a 70.58% decline in comparison to the control plants (Fig. 1b).

Fig. 1. (a) Phenotype of peanut plants exposed to different levels of water deficit. Leaf rolling and leaf thinning were observed in drought stressed plants but not in control plants; (b) changes in RWC of peanut leaves subjected to different water deficit treatments for 5 d. RWC was measured in the upper fully expanded leaves. Bars represent mean ± SD of three samples.

3.2. Construction of an SSH cDNA library

A differential expression cDNA library of peanut roots was constructed utilizing Clontech PCR Select Subtraction Kit. After subtraction and transformation, the blue-white spot screening showed that approximately 95% of transformants contained an insert. A total of 576 clones were randomly selected prior to sequencing and were shown to have an insert size of approximately 200-1000 bp. Sequencing of positive clones yielded a total of 360 EST sequences. Thus, we successfully constructed a putative drought-stress specific subtracted cDNA library from peanut roots.

3.3. Analysis of differentially expressed ESTs

After the removal of vector and adaptor sequences and elimination of masked repeats, rRNA and low complicity sequences, 111 non-redundant sequences were obtained. Based on homology searches to the NCBI database, 80 clones (72.07%) were homologous to known genes and 31 clones were homologous to genes with unknown function or had no matches in the NCBI database (Table 2). For functional annotation, Blast2GO was used to classify the ESTs into three principal GO categories: cellular location, molecular function and biological process. Some ESTs were simultaneously annotated into the three categories. Amongst the 80 ESTs with known homologs, 30 (37.5%) were attributed to a cellular component, 45 (56.25%) to a biological process and 36 to a molecular function (45%).

 

Table 2. Homology analysis of the 111 unique transcripts.

Sequence no Length Homology Species Accession no E-value
DR2 436 Alcohol dehydrogenase 1 Phaseolus vulgaris AGV54356.1 9e-27
DR3 869 Cellulose synthase-like protein G1-like Cicer arietinum XP_004499569.1 1e-140
DR 5 288 Chitinase (class II) Arachis hypogaea CAA57774.1 3e-04
DR 6 445 NA      
DR 7 501 Hypothetical protein PHAVU_007G280500g Phaseolus vulgaris ESW17931.1 2e-37
DR 8 1087 Uncharacterized protein LOC100806287 Glycine max XP_003554538.1 8e-09
DR 10 625 Annexin 1 Theobroma cacao EOY16019.1 3e-129
DR 11 840 Tobamovirus multiplication protein 2A isoform X1 Glycine max XP_003524459.1 2e-80
DR 13 572 Annexin D1-like isoform X1 Cicer arietinum XP_004516176.1 5e-33
DR 14 323 Hypothetical protein M569_00407 Genlisea aurea EPS74345.1 1e-50
DR 15 343 Vacuolar amino acid transporter 1-like Glycine max XP_006591247.1 9e-27
DR 16 440 NA      
DR 17 1123 3-Hydroxyisobutyryl-CoA hydrolase-like protein 3, mitochondrial-like isoform X2 Cicer arietinum XP_004503424.1 1E-146
DR 18 592 Uncharacterized protein LOC100306273 isoform X1 Glycine max XP_006576151.1 5e-56
DR 19 416 Predicted: protein ROS1-like Cicer arietinum XP_004497617.1 3e-07
DR 22 145 Protein phosphatase 2C 16-like Fragaria vesca subsp. vesca XP_004303490.1 6e-10
DR 25 494 NAD-dependent protein deacetylase SRT2-like Glycine max XP_003528059.2 2e-97
DR 26 612 Histidine kinase 3-like isoform X1 Glycine max XP_003531201.1 2e-09
DR 34 364 NA      
DR 36 1047 Probable ubiquitin-conjugating enzyme E2 26-like isoform X1 Glycine max XP_006580093.1 2e-61
DR 37 217 Secretory protein Arachis hypogaea AAO33586.1 3e-21
DR 45 809 Uncharacterized protein LOC101500555 Cicer arietinum XP_004503811.1 1e-66
DR 47 265 Hypothetical protein EUTSA_v10002144mg Eutrema salsugineum XP_006408892.1 4e-05
DR 49 227 Type 4 metallothionein Arachis hypogaea ABG57066.1 6e-27
DR 51 514 Hypothetical protein PHAVU_008G286500g Phaseolus vulgaris ESW14501.1 2e-61
DR 68 916 Hypothetical protein, partial Bacteroides dorei WP_007851439.1 6e-04
DR 69 899 Mitochondrial-processing peptidase subunit alpha Medicago truncatula XP_003630686.1 1e-48
DR 73 540 Uncharacterized protein LOC100778245 Glycine max NP_001239643.1 3e-37
DR 76 585 NA      
DR 77 285 WAT1-related protein At5g40240-like isoform X2 Glycine max XP_006586197.1 2e-26
DR 82 497 Unknown Lotus japonicus AFK49522.1 1e-53
DR 83 1048 NA      
DR 86 1035 Serine/threonine-protein kinase HT1-like Cicer arietinum XP_004485788.1 2e-17
DR 87 126 NA      
DR 90 1036 Protein GIGANTEA Medicago truncatula XP_003592047.1 2e-124
DR 92 412 Uncharacterized protein LOC101506019 isoform X1 Cicer arietinum XP_004485727.1 2e-08
DR 93 909 Epidermal growth factor receptor substrate 15-like Glycine max XP_003527306.1 6e-43
DR 98 556 Starch branching enzyme I Pisum sativum CAA56319.1 4e-34
DR 102 971 Epidermal growth factor receptor substrate 15-like Glycine max XM_004500802.1 1e-43
DR 105 247 DNA/RNA-binding protein KIN17-like Cicer arietinum XP_004491366.1 1e-44
DR 111 109 NA      
DR 117 645 Plasma membrane H+-ATPase Sesbania rostrata BAC77533.1 2e-130
DR 118 937 DEMETER Citrus sinensis AGU16984.1 1e-13
DR 121 475 Lipoxygenase Phaseolus vulgaris AAB18970.2 1e-70
DR 122 932 Carotenoid cleavage dioxygenase Eustoma exaltatum BAK22396.1 1e-44
DR 123 429 Universal stress protein A-like protein Medicago truncatula XP_003603940.1 7e-74
DR 125 1064 Protein ROS1-like isoform X1 Glycine max XP_006588820.1 6e-29
DR 126 454 Putative cold stress responsive protein Arachis hypogaea AAO33592.1 5e-07
DR 128 849 Methyl-CpG-binding domain-containing protein 10-like Glycine max XP_003543681.1 8e-60
DR 136 592 Glutamic acid-rich protein-like Glycine max XP_003548693.1 2e-05
DR 137 541 Galactinol synthase 2 Glycine max XP_003555792.1 1e-41
DR 138 338 NA
DR 139 1121 Protein ROS1-like isoform X1 Glycine max XP_006594195.1 9e-20
DR 141 558 Lea4 Glycine tomentella AAU94909.1 7e-42
DR 145 190 NA      
DR 154 1119 Serine/threonine-protein kinase HT1 Glycine max XP_003543042.1 1e-50
DR 157 1121 3-Hydroxyisobutyryl-CoA hydrolase-like protein 3, mitochondrial-like isoform 1 Glycine max XP_003525261.1 5e-144
DR 159 247 Nitrate transporter 1.1 isoform 1 Theobroma cacao EOY24389.1 1e-36
DR 167 313 NA      
DR 170 579 Hypothetical protein PHAVU_001G146200g Phaseolus vulgaris ESW34362.1 8e-27
DR 172 457 NA      
DR 176 553 Late embryogenesis abundant protein group 4 protein Arachis hypogaea ADQ91841.1 6e-35
DR 181 362 Expansin-like B1-like Glycine max XP_003517398.1 2e-67
DR 182 342 NA      
DR 188 559 Gigantean Arachis hypogaea ACF74296.1 2e-23
DR 194 1072 Protein ROS1-like isoform X4 Glycine max XP_006588823.1 1e-30
DR 195 510 Thylakoidal ascorbate peroxidase Jatropha curcas AGW52121.1 6e-16
DR 197 435 Carotenoid cleavage dioxygenase 1 Medicago truncatula CAR57918.1 1e-70
DR 203 367 NA      
DR 208 143 NA      
DR 215 423 Hypothetical protein EUTSA_v10004562mg Eutrema salsugineum XP_006395044 9e-04
DR 220 509 Manganese superoxide dismutase, partial Trifolium repens AFV96160.1 5e-45
DR 227 363 NA      
DR 230 181 NA      
DR 233 152 NA      
DR 241 322 NA      
DR 242 965 Aldose reductase-like Glycine max XP_003551585.1 6e-168
DR 262 523 Metallothionein-like protein Arachis hypogaea AAZ20291.1 8e-20
DR 278 486 Uncharacterized protein LOC101508994 Cicer arietinum XP_004500002.1 2e-60
DR 284 166 NA      
DR 285 1011 Transcriptional activator DEMETER-like Cucumis sativus XP_004150492.1 5e-13
DR 289 219 NA      
DR 291 886 Delta-1-pyrroline-5-carboxylate synthase Medicago sativa CAA67070.1 1e-84
DR 316 337 NA      
DR 318 1075 Ferrochelatase-2, chloroplastic-like isoform X2 Glycine max XP_006580371.1 3e-76
DR 324 489 NA      
DR 338 569 Mannose glucose binding lectin precursor Arachis hypogaea AAV33364.1 3e-29
DR 339 342 NA      
DR 341 529 Annexin AnxGb3 Gossypium barbadense AGG75999.1 3e-101
DR 379 441 NA      
DR 382 259 NA      
DR 383 378 Small acidic protein 1-like Glycine max XP_003555729.1 1e-06
DR 395 261 Alcohol dehydrogenase 1-like Cicer arietinum XP_004502579.1 1e-33
DR 400 444 NA      
DR 403 258 Chaperone protein dnaJ 49-like Cicer arietinum XP_004488532.1 5e-13
DR 404 734 Cyclin-dependent kinase G-2-like Glycine max XP_006601445.1 4e-40
DR 405 298 MOB kinase activator-like 1-like isoform X1 Cicer arietinum XP_004512415.1 8e-45
DR 408 379 Annexin D1-like isoform X2 Cicer arietinum XP_004516177.1 7e-35
DR 412 326 Manganese superoxide dismutase 2 Prunus persica CAC19487.1 3e-23
DR 423 187 Enolase Medicago truncatula NP_003617922.1 1E-03
DR 425 594 Lea protein 3 Arachis hypogaea AAZ20280.1 6e-60
DR 430 248 NA      
DR 432 459 NA      
DR 435 295 Lipoxygenase LoxN2 Pisum sativum AAD08700.1 4e-30
DR 449 337 Hypothetical protein ZEAMMB73_103592 Zea mays AFW74002.1 6e-20
DR 451 1076 Protein ROS1-like isoform X2 Glycine max XP_006588821.1 2e-20
DR 464 363 NA      
DR 465 257 NA      
DR 470 344 NA      
DR 471 522 Alternative oxidase 2b Glycine max AAP68983.1 9e-58
DR 472 268 Class II chitinase Arachis hypogaea AEO14153.1 4E-05

 

Within the category of cellular component, the highest number of ESTs (24) was obtained for ‘cell', followed by ‘membrane' (20) (Fig. 2a). Within the category of biological process, 36 ESTs (80%) were assigned to ‘metabolic process' and 34 (75.6%) to ‘cellular process', which accounted for the majority of the annotated sequences (Fig. 2b). Within the molecular function category, the GO terms with the highest number of ESTs were ‘catalytic activity' and ‘binding', with 31 and 24 ESTs, respectively (Fig. 2c). Hence, the GO analysis suggested that drought responses in peanut were mainly related to genes involved in cellular structure and metabolism.

Fig. 2.  Functional classification of drought-induced clones in peanut roots identified from subtractive cDNA library. Classification of 80 ESTs based on (a) cellular components, (b) biological process and (c) molecular function using Blast2GO software (http://blast2go.org).

3.4. Validation of differential expression using selected SSH clones and qRT-PCR

We selected seven representative ESTs encoding known cold stress-responsive proteins: (Gsi-83, colony DR126), annexin (ANN, colony DR10), alcohol dehydrogenase (ADH, colony DR395), manganese superoxide dismutase (MnSOD, colony DR220), serine/threonine-protein kinase HT1 (STPK, colony DR154), galactinol synthase 2 (GolS, colony DR137) and ?1-pyrroline-5-carboxylate synthase (P5CS, colony DR291), to further evaluate the differential expression of these genes in response to drought stress in peanut.

The expression patterns of the selected SSH clones in peanut roots, leaves and stems under water stress conditions (45% and 20% FC) were analyzed by qRT-PCR. Amongst the seven ESTs, GolS showed the greatest degree of up-regulation, with the largest increase in expression levels relative to the control observed in the stems under 20% FC conditions (1290 fold-change). The expression pattern of STPK differed in the roots, leaves and stems. In roots subjected to drought stress, the STPK transcript level increased approximately five-fold under 45% FC conditions and 11-fold under 20% FC conditions (Table 3). However, in leaves, STPK levels decreased significantly in the 45% FC treatment but showed no obvious change in the 20% FC conditions. In stems, STPK levels increased approximately two-fold following drought stress. The MnSOD gene showed no obvious expression changes in peanut roots and leaves under 45% FC water treatment, but increased between four- and nine-fold in the 20% FC water treatment (Table 3). The expression of P5CS in peanut roots and leaves increased with the degree of drought stress, with the highest expression level observed in stems at 45% FC treatment. The remaining three clones (Gsi-83, ANN and ADH) showed a similar pattern of expression in all tissues, with a small increase in the 45% FC treatment and the greatest expression level at 20% FC treatment (Table 3).

Table 3. qRT-PCR analysis of representative EST expression in peanut during drought stress treatment.

Gene Root Leaf Stem
Control 45% FC 20% FC Control 45% FC 20% FC Control 45% FC 20% FC
STPK 1.02 ± 0.13 5.24 ± 0.17 11.62 ± 1.00 1.00 ± 0.04 0.41 ± 0.03 1.30 ± 0.08 1.01 ± 0.08 1.73 ± 0.13 2.08 ± 0.44
P5CS 1.00 ± 0.00 4.08 ± 0.60 5.54 ± 0.31 1.00 ± 0.02 7.52 ± 0.34 40.28 ± 0.52 1.00 ± 0.02 33.67 ± 0.28 2471 ± 0.45
GolS 1.00 ± 0.03 19.69 ± 1.61 45.02 ± 5.17 1.01 ± 0.09 8.90 ± 0.46 179.89 ± 4.57 1.00 ± 0.02 42.20 ± 2.72 1290.17 ± 2.98
Gsi-83 1.00 ± 0.04 9.43 ± 0.04 44.70 ± 2.80 1.00 ± 0.05 5.80 ± 0.47 40.80 ± 0.74 1.00 ± 0.04 16.58 ± 1.00 54.41 ± 2.30
ANN 1.00 ± 0.06 10.14 ± 0.99 25.31 ± 2.33 1.00 ± 0.04 5.25 ± 0.37 14.16 ± 0.32 1.00 ± 0.07 12.22 ± 0.29 10.40 ± 0.32
ADH 1.00 ± 0.06 7.01 ± 0.99 20.60 ± 3.37 1.00 ± 0.05 1.46 ± 0.08 29.87 ± 0.52 1.00 ± 0.04 7.65 ± 0.02 21.02 ± 0.17
MnSOD 1.00 ± 0.00 1.04 ± 0.22 3.99 ± 0.14 1.00 ± 0.04 1.40 ± 0.04 4.91 ± 0.12 1.00 ± 0.05 5.68 ± 0.29 9.69 ± 0.12

 

4. Discussion

Drought stress cDNA libraries have previously been constructed for peanut, but these correspond to genes expressed in drought stressed leaves [3] or in immature pods [13,14]. Hence, there is limited molecular information on the root responses of peanut subjected to drought stress conditions. In this study, a total of 111 differentially expressed, non-redundant ESTs were identified in the subtractive cDNA library. Of these 111 ESTs, 80 had significant homology to known genes, many of which are associated with drought stress responses previously reported in soybean and chickpea. Some genes, such as those encoding lea3, lea4 and metallothionein-like protein had confirmed involvement in drought stress in peanut [ 15, 16]. This suggests that we have successfully constructed an SSH cDNA library and have identified drought-stress responsive genes in peanut roots.

We selected seven ESTs for qRT-PCR analysis in drought-stressed and control peanut roots, leaves and stems. The expressions of ANN, ADH and MnSOD were increased in response to drought stress, especially under the 20% FC condition. These three genes are reported to be involved in water stress responses in other plant species [ 17, 18, 19, 20]. Our study confirms that these genes are also involved in the drought tolerance mechanism of peanut. Protein kinases are widely detected in living organisms and play important roles in signal perception and transduction in cells. Under environment stress conditions, protein kinases perceive and transmit various signals, and activate transcription factors to regulate the expression of downstream genes [ 21, 22]. The expression patterns of STPK differed in the roots, leaves and stems, exhibiting rapid induction in roots under drought stress, but down-regulation in leaves at 45% FC conditions. The expression pattern of this particular protein kinase indicates that its role in the regulation of drought stress response is complex and requires further study.

Some studies have shown that under drought stress conditions, plants can improve their drought tolerance by adjusting the levels of osmoprotectants such as proline [23], galactinol [24] and glycinebetaine [25]. Proline acts as an osmolyte that accumulates when plants are subjected to abiotic stress. P5CS is a key regulatory enzyme that plays a crucial role in proline biosynthesis [26]. Raffinose and galactinol are involved in tolerance to drought, high salinity and cold stress. Stress-inducible GolS plays a key role in the accumulation of galactinol and raffinose under abiotic stress conditions [24]. In this study, the mRNA levels of P5CS and GolS in the control leaves and stems were significantly reduced in comparison to roots (data not shown). Furthermore, the expression of P5CS was significantly increased in all three tissues under drought stress, suggesting that proline accumulation in peanut may form a key defense mechanism against drought stress. The up-regulation of GolS under 20% FC conditions was 9-fold, 4.5-fold and 53.8-fold greater than that of P5CS in roots, leaves and stems, respectively. This indicates that, in peanut, the osmotic adjustment ability of soluble sucrose is greater than that of proline under drought stress conditions, which is consistent with our previous report [27].

In addition, some of the genes induced under drought stress were found to be associated with other environmental stresses, such as salt, cold and high temperature stress [28,29]. We identified an EST homologous to nitrate transporter 1.1, and a cold stress responsive protein whose expression was marginally increased in peanut under drought stress conditions. This suggests that some genes respond to both drought stress and other abiotic stresses, and thus implies that similar stress tolerance mechanisms and pathways may exist. The gene expression levels analyzed in this study indicate that the response to drought is a very complex physiological and biochemical process involving multiple metabolism pathways.

5. Conclusions

We successfully constructed an SSH cDNA library from peanut roots and identified several transcripts encoding proteins with drought-related functions. These proteins were located in different cellular compartments and were involved in various molecular functions and biological processes during normal and water stress conditions in peanut. Our study contributes to a better understanding of the molecular mechanisms of water-stress tolerance in peanut and would facilitate the genetic manipulation of drought-stress resistance in this species.

Financial support

This research was supported by the earmarked fund for Promotive Research Fund for Excellent Young and Middle-aged Scientists of Shandong Province (grant No. BS2012NY010), National Natural Science Foundation of China (grant No. 31201171), Shandong Science and Technology Development Program (grant No. 2013GNC11107) and Basic Research Projects of Science and Technology Program of Qingdao (13-1-4-173-jch).

Acknowledgements

We are most grateful to Dr. Qi Wu and Dr. Yue Yi Tang for their valuable comments and suggestions.

Author contribution

Proposed the theoretical frame: HD, ZMZ; Conceived and designed the experiments: FFQ, LXD; Wrote the paper: HD; Performed the experiments: CJL, DWC; Analyzed the data: WWS.

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*Corresponding author: E-mail address: qinhdao@126.com (Z.M. Zhang).

Received 1 July 2014, Accepted 29 August 2014, Available online 26 September 2014

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