Figures
Abstract
Background
Artemisia sphaerocephala, a semi-shrub belonging to the Artemisia genus of the Compositae family, is an important pioneer plant that inhabits moving and semi-stable sand dunes in the deserts and steppes of northwest and north-central China. It is very resilient in extreme environments. Additionally, its seeds have excellent nutritional value, and the abundant lipids and polysaccharides in the seeds make this plant a potential valuable source of bio-energy. However, partly due to the scarcity of genetic information, the genetic mechanisms controlling the traits and environmental adaptation capacity of A. sphaerocephala are unknown.
Results
Here, we present the first in-depth transcriptomic analysis of A. sphaerocephala. To maximize the representation of conditional transcripts, mRNA was obtained from 17 samples, including living tissues of desert-growing A. sphaerocephala, seeds germinated in the laboratory, and calli subjected to no stress (control) and high and low temperature, high and low osmotic, and salt stresses. De novo transcriptome assembly performed using an Illumina HiSeq 2500 platform resulted in the generation of 68,373 unigenes. We analyzed the key genes involved in the unsaturated fatty acid synthesis pathway and identified 26 A. sphaerocephala fad2 genes, which is the largest fad2 gene family reported to date. Furthermore, a set of genes responsible for resistance to extreme temperatures, salt, drought and a combination of stresses was identified.
Conclusion
The present work provides abundant genomic information for functional dissection of the important traits of A. sphaerocephala and contributes to the current understanding of molecular adaptive mechanisms of A. sphaerocephala in the desert environment. Identification of the key genes in the unsaturated fatty acid synthesis pathway could increase understanding of the biological regulatory mechanisms of fatty acid composition traits in plants and facilitate genetic manipulation of the fatty acid composition of oil crops.
Citation: Zhang L, Hu X, Miao X, Chen X, Nan S, Fu H (2016) Genome-Scale Transcriptome Analysis of the Desert Shrub Artemisia sphaerocephala. PLoS ONE 11(4): e0154300. https://doi.org/10.1371/journal.pone.0154300
Editor: Debasis Chakrabarty, CSIR-National Botanical Research Institute, INDIA
Received: December 15, 2015; Accepted: April 12, 2016; Published: April 26, 2016
Copyright: © 2016 Zhang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the paper and its Supporting Information files.
Funding: This research was funded by the National Basic Research Program of China (2014CB138703) and the Program for Changjiang Scholars and Innovative Research Team in University (IRT13019).
Competing interests: The authors have declared that no competing interests exist.
Introduction
China has the largest desertification area in the world, with a total desertified land area of 2,623,700 km2 comprising 27.33% of the national territory by the end of 2009 [1]. With great efforts in reforestation and revegetation, desertification in China has been reversed, as shown by the annual decrease in the desertified land area of 1,375 km2 over the last 10 years [2]. Desert plants are highly adaptable to adverse environmental conditions [3,4] and are attracting increasing research interest regarding the genetic basis of their unique adaptation and survival abilities [5–9]. These plants are also uniquely economically valuable [10].
Artemisia sphaerocephala, a dicotyledonous perennial semi-shrub belonging to the Artemisia genus of the Compositae family, is distributed widely in the provinces of Gansu, Ningxia, Shanxi, and Xinjiang, as well as in Inner Mongolia, northwestern China [11,12]. This shrub is one of the most important pioneer plants in moving and semi-stable sand dunes in the deserts and steppes, protecting rangelands from wind erosion and playing a vital role in maintaining desert ecosystem stability [13]. Artemisia sphaerocephala can be consumed as food by humans; early herders consumed the seeds during ancient times. In addition, it is rich in linoleic acid, and the oil content of its seeds is 21.5% [14], with unsaturated fatty acids accounting for 91% of the total fatty acids and linoleic acid accounting for 81% of the total unsaturated fatty acids [15]. Further, the total fatty acid concentration in A. sphaerocephala leaves is 11.42 mg/g, and linoleic acid accounts for 22.31% of the total fatty acids [16]. Linoleic acid is one of the main polyunsaturated fatty acids in cell membranes, and an increase in its accumulation is thought to aid in maintenance of membrane fluidity and cellular integrity during stress [17–19]. In addition, linoleic acid is an essential fatty acid for mammals [20], and it is the precursor of conjugated linoleic acid (CLA), which is generated in the stomachs of ruminant animals as well as those of several non-ruminant animals [21]. CLA has significant protective functions against obesity [22,23], cancer [24], inflammation [25], and diabetes [26], and it is beneficial for energy metabolism [23]. Thus, there is great interest in increasing the amount of CLA in the human food supply because of its potential benefits to human health [27]. Artemisia sphaerocephala seeds are also rich in polysaccharides (up to 35% of the seed dry mass [12]), which are a type of raw material used to produce ethanol [28]. Due to the large quantities of polysaccharides and lipids in A. sphaerocephala seeds, this desert shrub has the potential for use as a bio-fuel for diesel engines.
Transcriptome analysis aims to capture an unbiased view of the complete RNA transcript profile of a species, allowing for monitoring of the transcript level of each gene in a given tissue at a given point in the organisms’ life cycle [29]. During recent years, next-generation sequencing technology has been applied in studies of desert plants, such as Populus euphratica [6], Rhazya stricta [30], and Ammopiptanthus mongolicus [31]. Despite its important ecological and economic value, no transcriptome or genomic sequences are currently available for A. sphaerocephala in the GenBank database. In this paper, we present a de novo assembly of the A. sphaerocephala transcriptome performed using an Illumina HiSeq 2500 platform. Data were collected via sequencing of cDNA libraries of living tissues obtained from shrubs growing in the Alxa Desert. We further analyzed genes related to the unsaturated fatty acid synthesis pathway in this species and constructed a phylogenetic tree of fad2 genes. This information could improve our understanding of unsaturated fatty acid metabolic pathways in A. sphaerocephala. We specifically examined the gene expression dynamics of this plant in response to stresses and identified a set of stress-related transcripts. Our findings could shed light on the possible adaptive mechanisms of A. sphaerocephala in the desert.
Materials and Methods
Plant materials
Mature leaves, stems, roots, flowers, flower buds, early developing seeds, mid-developing seeds and mature seeds were collected from A. sphaerocephala plants growing in the Alxa Desert of Inner Mongolia, northwest China (N: 38°68’, E: 105°61’). The sampling ground is in an uninhabited desert; no specific permission was required and no endangered or protected species were involved in this study. In addition, we collected plant materials in the laboratory, including germinated seeds after 3 days, germinated seeds after 7 days, seedlings and 6 different calli. The calli were cultivated using the method described by Xu and Jia [32]. One month later, the calli were assigned to 5 treatment groups and 1 control group and exposed to the following conditions: a) addition of 100 mM NaCl to the medium to induce salt stress; b) addition of PEG-8000 to the medium to induce osmotic stress of -0.7 MPa and -1.7 MPa [33]; (c) incubation at 40°C and 4°C to induce high- and low-temperature stresses, respectively; and d) normal conditions (untreated control group). After 24 h, all samples were rapidly frozen in liquid nitrogen and stored at -80°C for later RNA extraction.
RNA extraction
Total RNA was extracted from each tissue using an RNAprep Pure Plant Kit (Tiangen, China). The quantity and quality of total RNA were determined using a NanoDrop ND1000 (Thermo Science, USA), Agilent 2100 Bioanalyzer (Agilent, USA), Qubit 2.0 and gel electrophoresis. At least 20 μg of total RNA was used for cDNA library preparation.
Library preparation and RNA sequencing
Illumina sequencing was performed following the manufacturer’s instructions. First, oligo(dT) beads were used for enrichment of eukaryotic mRNA. Subsequently, poly(A)+ RNA was purified and fragmented into smaller pieces. First-strand cDNA was synthesized with random hexanucleotide primers (random hexamers) using small RNA fragments as templates. Second-strand cDNA was then synthesized in a reaction mixture containing buffer, dNTPs, RNase H and DNA polymerase I. Then, AMPure XP beads were used to purify the cDNA. The purified double-stranded cDNA was end-repaired, and poly(A) tails were added; then, AMPure XP beads were used to select fragments of a particular size. Finally, a sequencing library was constructed by PCR enrichment. After construction of the library, Qubit 2.0 and an Agilent 2100 Bioanalyzer were used to determine the the concentrations and sizes of the inserts. To ensure the high quality of the library, qRT-PCR was performed to measure the effective concentrations of the library reads. Then, high-throughput sequencing was conducted using an Illumina HiSeq 2500 platform. In total, 46.83 million reads were generated, 86.15% of which had a quality score above Q30 (Table 1).
De novo assembly and assessment
Clean reads were obtained after filtering adaptor sequences and reads with ambiguous “N” bases and those with a base quality score of less than Q30. Further, all sequences smaller than 60 bases were eliminated because such small reads might be sequencing products [34]. The high-quality reads were then assembled into unigenes using Trinity software with a sensitivity similar to methods that rely on genome alignments [35].
qRT-PCR analysis
Total RNA was extracted from 6 calli exposed to different conditions using RNAprep Pure Plant Kit (Tiangen, China). Then, the RNA was reverse transcribed (Prime-Script RT-PCR Kit, Takara, China) into cDNA to measure the expression of 5 genes that are commonly involved in the responses to PEG-induced drought stress, extreme temperatures and high salinity (the sequences of these 5 genes are provided in S1 Table). qRT-PCR was performed using an MyiQ Single-Color Real-Time PCR Detection System (Bio-Rad, USA) and a SYBR Premix Ex Taq Kit (Takara, China), which is a real-time PCR kit. PCR was performed under the following conditions: 95°C for 30 s, followed by 40 cycles at 95°C for 5 s for denaturation and 60°C for 30 s for annealing and extension. The experiments were repeated three times using independent RNA samples, and actin was used as an internal control. Relative gene expression was calculated with the 2-ΔΔCt method [36]. Synthesis of qRT-PCR primers for the 5 genes were completed by Sangon Biotech Company (Sangon, China), and SPSS software was used for data analysis (P<0.05). Primers information is presented in S2 Table.
Results and Discussion
Sequence analysis and assembly
To obtain a global and comprehensive overview of the A. sphaerocephala transcriptome, total RNA was obtained from 17 different plant tissues (the morphologies of the various tissues are shown in Fig 1). Comparable amounts of total RNA from each tissue were mixed. Then, each specimen was sequenced using an Illumina HiSeq 2500 platform. After the reads were subjected to stringent quality assessment and data filtering, 46,831,604 reads (9.46 Gb) with 86.15% Q30 bases remained. A summary of the transcriptome sequencing results is presented in Table 1. The raw high-quality sequence datasets were archived in the National Center for Biotechnology Information (NCBI) Short Read Archive database (SAMN03951130).
Note: (a) Whole plant, (b) stem, (c) leaf, (d) root, (e) flower bud, (f) flower, (g) early developing seed husk, (h) early developing seed, (i) mid-developing seed husk, (j) mid-developing seed, (k) mature seed husk, (l) mature seed, (m) germinating seed at 3 days, (n) germinating seed at 7 days, (o) seedling, and (p) callus cell.
All high-quality clean reads were assembled de novo with Trinity software [35], as shown in Table 2, which generated 137,060 transcripts with an average length of 884.39 nt and an N50 of 1,403 nt (S1 Fig). After further analyses were performed, 68,373 unigenes with a mean length of 692.76 nt and an N50 of 1,161 nt were obtained (Fig 2). A positive relationship was found between unigene length and the number of reads assembled into the corresponding unigenes, as expected for a randomly fragmented transcriptome (Fig 3). Moreover, open reading frames (ORFs) were predicted using getORF software (http://emboss.sourceforge.net/apps/cvs/emboss/apps/getorf.html), which revealed that the ORFs of 67,917 unigenes (99.33%) had an average length of 444.59 nt and an N50 of 963 nt (S3 Table and S2 Fig). These results indicated that high transcriptomic coverage was achieved for this species.
Functional annotation
All unigenes were aligned to the NCBI non-redundant (Nr) protein database and annotated using Clusters of Orthologous Groups (COG) of protein, gene ontology (GO) terms, the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database and the Swiss-Prot protein database, with a BLAST threshold of less than 1E-5 [37]. Out of the 68,373 unigenes, 40,153 (58.70%) significantly matched sequences deposited in the public protein databases (Table 3). Approximately 59.4% of the unigenes had best hits to known plant genes (E-value<1E-50, S3 Fig). Technical limitations, such as sequencing depth and read length, influenced the rate of transcriptomic annotation to some extent [30, 38, 39]. The mean length of the annotated unigenes was longer than that of the un-annotated unigenes (S4 Fig, 868.1683 nt vs. 335.1881 nt), and the expression levels of the annotated unigenes inferred from the fragments per kilobase of transcript per million mapped reads (FPKM) were much higher than those of the un-annotated unigenes (S5 Fig). A possible explanation for the low percentage of annotated unigenes (58.7%) is that the unigenes might be species-specific, which would prevent their annotation.
A summary of the final A. sphaerocephala transcriptome annotation results is shown in S4 Table. Annotation of all 68,373 unigenes was performed using the COG database, resulting in classification of 13,041 (19.10%) unigenes into COG categories (Fig 4). Among the 25 COG classifications, the cluster for general function prediction was predominant, followed by replication, recombination and repair. Further, GO annotation, with assignment of the A. sphaerocephala unigenes to molecular function, biological process and cellular component GO terms, was performed (E-value<1E-5, Fig 5). The top 50 represented GO terms are shown in S6 Fig. A total of 42.4% of the unigenes (28,997) had a significant hit in GO public databases, and 28,997 unigenes were assigned to at least one GO term. The most abundant biological process GO terms were oxidation-reduction process (2,324 unigenes) and protein phosphorylation (935 unigenes). GO terms associated with responses to other environmental factors, such as cadmium ion (717 unigenes), salt (671 unigenes), cold (447 unigenes), abscisic acid (397 unigenes), bacteria (380 unigenes), wounding (332 unigenes) and water deprivation (323 unigenes), were also enriched. The highly enriched biological process GO terms indicated that most of the annotated unigenes were associated with elementary responses to environmental factors. In addition, 22.04% of the unigenes shared over 80% similarity with sequences deposited in the Nr database (S7 Fig).
To identify and screen for the prominent metabolic pathways in A. sphaerocephala, the acquired unigenes were mapped to metabolic pathways in the KEGG database. In total, 9,148 unigenes were mapped to 117 metabolic pathways. Most unigenes were assigned to 3 pathways, namely Ribosome, Protein processing in endoplasmic reticulum and Oxidative phosphorylation (717, 359 and 338, respectively) (Table 4).
Fatty acid synthesis-related genes in Artemisia sphaerocephala
Fatty acid compositions vary among different species (Table 5). Linoleic acid (18:2) is the most abundant (80%) fatty acid in A. sphaerocephala seed oil, and linoleic and linolenic acids in the leaf comprise 22.31% and 46.33% of the total fatty acids, respectively [16]. The pathways for polyunsaturated fatty acid production in plants are generally well understood and have been largely elucidated [40]. C18:1 may be converted to C18:2 in plastids by a membrane-bound fatty acid desaturase called FAD6, or C18:1 may be exported from the plastids to the ER for conversion to C18:2 by a structurally related enzyme called FAD2. In a similar manner, C18:2 may be converted to C18:3 in plastids by the FAD7 or FAD8 enzyme, or it can be exported to the ER for conversion to C18:3 by the FAD3 enzyme [19]. Different species have different fatty acid desaturases (Table 6). In the A. sphaerocephala transcriptome, 26 putative fad2s, 3 putative fad3s, 1 putative fad6 and 9 putative fad7/fad8s were identified (Fig 6). With regard to fad2, safflower has 11 fad2s [41], soybean has 5 [42, 43], cotton [44–47] and rapeseed [48] each have 4, sunflower [49] and peanut [50, 51] each have 3, and A. thaliana has 1 [52]. Although previous studies have shown that flax has 15 fad2s [53–55], only one protein sequence was found in the NCBI database because the base substitutions of 15 fad2 genes in flax do not result in amino acid changes. We identified 20 fad2 genes from the Artemisia annua transcriptomic data [56]. In this study, we found the largest fad2 gene family to date. As shown in Table 5, the linoleic acid concentrations in the leaves and seeds of A. sphaerocephala are higher than those in other plants, and the large fad2 gene family may play a prominent role in fatty acid synthesis.
Note: The numbers in the brackets indicate gene numbers.
We employed fad genes from the transcriptomic data of A. sphaerocephala and those on oil crops, A. thaliana and two Compositae plants (Artemisia annua and Carthamus tinctorius) to further analyze the phylogenetic position of the fad2 family, Artemisia sphaerocephala and A. annua protein sequences are shown in S5 Table. An evolutionary tree with 2 main categories (shown in green) was constructed (Fig 7), and the first category was divided into 6 parts (shown in red). Then, the first part was divided into 3 branches (shown in blue). AsFAD2-15, 16 and 14 are located on the first branch, and AsFAD2-15 and AcFAD2-19 are located next to each other and adjacent to AsFAD2-16 and ctFAD2-8. AsFAD2-14, ctFAD2-4 and ctFAD2-5 are also located on the first branch. The above results indicate that these genes might have high structural homology and similar functions. The first histidine motifs are HDCGHH in ctFAD2-5 and HECGHH in ctFAD2-4 and ctFAD2-8. ctFAD2-5 and ctFAD2-8 appear to be root specific, and ctFAD2-4 is highly expressed in young seedling tissues, including cotyledons and hypocotyls [68]. The second branch includes AsFAD2-10, 17 and 9. AsFAD2-10 and ctFAD2-2 are located next to each other; thus, we deduced that they have high structural homology and similar functions. ctFAD2-2 exhibited significantly increased expression in the cotyledonary tissues of young seedlings. The second histidine motif, HRRHH, is highly conserved in ctFAD2-2, which is a Δ12-oleate desaturase that converts oleic acid to linoleic acid and presumably plays only a secondary role in linoleic acid production in seed oil [68]. AsFAD2-9 was also situated next to AcFAD2-10 on the second branch. AsFAD2-11 and ctFAD2-6 are located next to each other on the third branch, and ctFAD2-6 has been found to be highly expressed in cotyledons and hypocotyls [68]. In addition, AsFAD2-12 and ctFAD2-10 are located next to each other in the second part. In ctFAD2-10, the amino acid immediately preceding the first histidine box is Ala (A); this gene is primarily expressed in flower tissues, with relatively low expression in other tissues, including the cotyledon, hypocotyls, root, and leaf [68]. AsFAD2-13 is also located in the second part next to ctFAD2-3. In CtFAD2-3, the serine at the +3 position is substituted by proline, which is also exclusively present in other FAD2 fatty acid conjugases [68]. The fad2 genes of oil crops constitute the majority of the third part, and one sequence each from A. annua and Carthamus tinctorius are present in this part. However, no A. sphaerocephala sequence was observed in this part. AsFAD2-4 is located in the fourth part. AsFAD2-21 and AcFAD2-3 are located next to each other and form the fifth part. AsFAD2-22 and AcFAD2-8 are situated next to each other and form the sixth part. The second category contains AsFAD2-2, 1, 8, 20, 19, 18, 24, 25, 26, 3, 23, 5, 6, and 7. Genes in this category show high homology with genes in A. annua.
Note: The phylogenetic tree was generated using Mega 5.0. The GenBank accession numbers of the amino acid sequences represented in the phylogenetic tree are as follows: CtFAD2-1, AGC65498.1; CtFAD2-2, AGC65499.1; CtFAD2-3, AGC65500.1; CtFAD2-4, AGC65501.1; CtFAD2-5, AGC65502.1; CtFAD2-6, AGC65503.1; CtFAD2-7, AGC65504.1; CtFAD2-8, AGC65505.1; CtFAD2-9; AGC65506.1; CtFAD2-10, AGC65507.1; CtFAD2-11, AGC65508.1; ghFAD2, AAQ16654.1; ghDES-2, AAL37484.1; ghDES-3, ADP02395.1; ahDES-1, ACZ06072.1; ahDES-2, AHN60569.1; gmFAD2-1B, ABF84062.1; gmFAD2-4, NP_001237865.1; gmDES-1, AAX29989.1; gmDES-2, AAB00860.1; gmDES-3, NP_001238342.1; BnA.FAD2.a-1, AFJ19029.1; BnA.FAD2.a, AFJ19030.1; BnC.FAD2.a, AFJ19031.1; BnC.FAD2.b, AFJ19032.1; bnDES-1, AGV77099.1; bnDES-2, AAT02411.1; haFAD2-1, AAL68981.1; haFAD2-2, AAL68982.1; haFAD2-3, AAL68983.1; luFAD2, AFJ53087.1; and atDES, AEE85834.1 (ct, Carthamus tinctorius; gh, Gossypium hirsutum; ah, Arachis hypogaea; gm, Glycine max; bn, Brassica napus; ha, Helianthus annuus; lu, Linum usitatissimum; at, Arabidopsis thaliana; As, Artemisia sphaerocephala; and Ac, Artemisia annua).
The fad2 genes are members of a large and complex gene family, and they have base substitutions at multiple loci that result in amino acid differences [41]. Analysis of the evolutionary tree revealed that 26 putative FAD2s of A. sphaerocephala shared the highest homology with A. annua, and the second highest homology with sequences from safflower. There are 3 possible explanations for these results. First, A. sphaerocephala contains an abundance of linoleic acid; second, these three species belong to the Compositae family and have a close relationship; and third, the fad2 gene family of safflower is the largest gene family discovered to date and serves as a significant reference. Interestingly, we found that FAD2s of traditional oil crops were located in the first category of the phylogenetic tree, particularly in the third group. We speculated that the conventional breeding process might have led to the loss of several genes from the wild species. In the second category of the tree, the fad2 gene family of A. sphaerocephala showed obvious expansion and high homology with A. annua; FAD2s of these two species were predominant in this category and formed a very large fad2 gene family.
Fatty acid desaturases are not only the key enzymes of unsaturated fatty acid synthesis but also have vital significance in terms of resistance to adverse environmental conditions. In a previous study, plant cold resistance was demonstrated to be reduced in an A. thaliana fad2 mutant with a decrease in the unsaturated fatty acid concentration in extrachloroplast membrane lipids [79]. This A. thaliana fad2 mutant has also been shown to accumulate a large amount of Na+ in the root cell cytoplasm and to be sensitive to salt stress during seed germination and early seedling growth [17]. Exogenous expression of sunflower fad2 has been reported to increase the yeast unsaturated lipid index and membrane lipid fluidity, and resistance to salt and cold stresses was also enhanced [80]. The fad3 gene is regulated through the synergistic and antagonistic interactions of plant hormones such as auxin, cytokinin, and abscisic acid, and the tissue specificity of the expression of this gene is further modified in accordance with the growth phase during plant development [81]. The Arabidopsis fad6 mutant exhibits obvious chlorosis at low temperatures [82]. In addition, FAD6 is required for salt resistance in Arabidopsis [83]. Further, overexpression of the A. thaliana fad7 gene in tobacco seedlings during cryogenic treatment has been shown to result in etiolation [76, 84]. Studies have shown that the fad7 gene is induced by light [85]. In Arabidopsis, fad8 expression is strongly promoted by low temperatures [77]. In addition, eleven fad2 genes have been identified in a cDNA library constructed from 8 safflower tissues, including leaves, roots, cotyledons, hypocotyls, flowering heads, and developing embryos at 3 stages. The expression of fad genes is tissue specific [41, 42], and some of these genes display inducible expression [77, 85]. We constructed the A. sphaerocephala transcriptome by collecting 17 samples from plants grown under different conditions, including 4 stress-exposed samples, which could explain our finding of the largest fad2 gene family to date in this organism.
Candidate genes involved in stress responses in Artemisia sphaerocephala
Transcriptome analysis resulted in the identification of 1,212 unigenes involved in heat, cold, salt and drought responses. These 1,212 unigenes were annotated using GO terms, and 222, 447, 671 and 108 unigenes were found to have functions in heat, cold, salt and drought responses, respectively. Interestingly, 5 out of the 1,212 stress response unigenes, including 2 heat shock protein 90s (HSP90s), HyPRP2, the hypothetical protein PRUPE_ppa001487mg and an uncharacterized protein, play roles in all 4 biological response processes (Fig 8). Next, qRT-PCR was performed to verify the expression of these 5 genes in response to all four stress conditions. Four of these genes, excluding the uncharacterized protein, showed large expression differences compared with the control (Fig 9); no suitable primers could be designed for the uncharacterized protein because of its short sequence. Many studies have shown that HSPs accumulate under abiotic stresses, such as heat, cold, osmotic and salt stresses [86–90]. However, the expression levels of 2 HSPs in A. sphaerocephala were lower than those in the control under all treatments, with the exception of the expression of HSP90-A, which did not significantly differ between the 40°C treatment and the control. Recent studies have demonstrated that under normal conditions, HSP90 suppresses the functioning of heat shock factor (HSF); however, under heat stress, HSP90 is inactivated, and HSF is activated and regulates the expression of downstream genes to enable adaptation to oxidative stress [91–93]. Thus, low HSP90 expression may contribute to HSF activation in A. sphaerocephala. The expression levels of plant HyPRP genes vary in different species, in different organs within the same species, and in diverse environments [94–96]. Under cold, salt and drought stresses, cotton HyPRP expression is up-regulated [95]. Further, HyPRP overexpression decreases the tolerance of tobacco to cold and drought [96]. In this study, HyPRP2 expression was up-regulated under osmotic stress (-0.7 Mpa) and at 4°C, and it was down-regulated under salt stress and at 40°C. Expression of the hypothetical protein PRUPE_ppa001487mg was down-regulated under all treatments. The above results confirmed the expression changes of the stress response genes detected in transcriptome analysis. Expression profiling of the stress response genes must be carried out in a future study to elucidate the adaptive mechanisms of A. sphaerocephala to changing environmental conditions.
Heat tolerance.
Daily and seasonal temperatures fluctuate greatly in the desert. A total of 222 unigenes classified as heat responsive were annotated using the Nr and Swiss-Prot databases (S6 Table). Of these unigenes, 64 potential chaperones, 55 putative enzymes, 15 transcription factors and 8 kinases were identified. Under the high temperature treatment, the plants exhibited a heat shock response (HSR), thereby triggering production of HSPs, which can act as molecular chaperones to enable the normal functioning of other proteins in high-temperature environments [97]. Therefore, the HSP family could improve the heat resistance of plants [98]. Four HSP110s, 7 HSP100s, 7 HSP90s, 14 HSP70s and 32 small HSPs have been discovered in A. thaliana, most of which are localized to the cytosol [99]. In the A. sphaerocephala transcriptome, 3 HSP110s, 5 HSP100s, 4 HSP90s, 4 HSP70s and 3 small HSPs were identified (S7 Table). Interestingly, 3 unigenes encoding putative HSPs, in addition to HSP90s, HSP70s and small HSPs were among the 1,000 most highly expressed unigenes (S8 Table), indicating that HSPs might contribute substantially to the high temperature resistance of A. sphaerocephala. One previous study has shown that a complex cascade mediates the up-regulation of HSPs and activation of heat shock transcription factors (HSFs), which show extremely essential function to regulate HSP gene expression [100]. Arabidopsis thaliana possesses diverse HSF families that include 21 genes [101, 102]. Fifteen HSFs were found in A. sphaerocephala, 5 of which had orthologs in A. thaliana (S9 Table). Fifteen unigenes out of the 1,000 most highly expressed unigenes were classified as heat responsive (S8 Table), including HyPRP2, a 17.7-kD class I small heat shock protein, inositol-3-phosphate synthase and others. Previous reports have shown that these genes are involved in processes used by plants for adaptation to external environments, especially hot environments [103–105]. These genes were highly expressed in A. sphaerocephala and might greatly contribute to the survival of this species in the hot desert environment.
Cold tolerance.
Coldness has been proven to be one of the most significant factors limiting plant development. Temperatures of below zero during the winter can injure plant cells and tissues. Many plants are able to survive cold temperatures [106]. A total of 447 potentially cold-responsive unigenes were annotated using the Nr and Swiss-Prot databases (S6 Table). Among these unigenes, 13 potential chaperones, 6 late embryogenesis-abundant proteins (LEAs), 2 aquaporins, 222 enzymes, 8 transcription factors and 41 kinases were identified. The eight transcription factors, including the homeobox-leucine zipper protein (HD-zip), which is unique to the plant kingdom, are mainly involved in responses to abiotic stress and auxin, de-etiolation, and blue light signaling, as well as the regulation of organ growth and developmental processes [107–109]. Zinc finger proteins have been found to participate in extraordinarily diverse signal transduction pathways and developmental processes, including flower, seed and seedling development; trichome and root hair formation [110–113]; pathogen defenses [114]; and stress responses [115]. Zinc finger protein expression is increased in plants under both salt and cold stresses [116]. Excessive expression of zinc finger protein, which is induced by cold, enhances cold resistance in plants [117]. Dehydration-responsive element-binding protein/C-repeat binding factor (DREB/CBF) and a cis-acting element specifically bind to the dehydration-responsive element/C-repeat (DRE/CRT). The inducible production of DREB/CBF activates stress-resistant functions depending on the presence of DRE/CRT [106]. Two putative CBF/DEREs were discovered in A. sphaerocephala. WRKY transcription factors make up one of the largest families of transcriptional regulators in plants, and they form integral parts of signaling networks that mediate many plant processes [118]; some of these transcription factors were also classified as cold responsive in A. sphaerocephala. Among 447 cold-responsive unigenes, 52 were among the 1,000 most highly expressed unigenes, including HyPRP2, glycine-rich RNA-binding protein 7, 29-kD ribonucleoprotein and other highly expressed unigenes (S10 Table). These genes play important roles in resistance to cold stress [104, 117, 119].
Salt tolerance.
High salt concentrations induce both osmotic and metal ion stresses. Plants have developed physiological and morphological strategies to adapt to these stresses [120]. To analyze the salt stress response and to screen for possible functional genes in A. sphaerocephala, 671 unigenes potentially responsive to salt stress were annotated using the Nr and Swiss-Prot databases (S6 Table). Of the 671 unigenes, 36 potential chaperones, 4 LEAs, 4 aquaporins and 286 enzymes, including reactive oxygen species (ROS) scavenging enzymes, MDAR, GST, superoxide dismutase (SOD) and catalase (CAT), were identified. In addition, 25 transcription factors and 58 kinases were found in the A. sphaerocephala transcriptome. The 25 transcription factors included bZIP (basic domain/leucine zipper), AP2/EREBP, HD ZIP, WRKY and MYB. Many studies have shown that these transcription factors play essential roles in the regulation of gene expression to cope with salt stress [121–125]. These transcription factors regulate and control the expression of downstream genes related to salt resistance by interacting with cis-acting elements. Extensive studies have shown that under high-salinity conditions, with the aid of Na+/H+ reverse transporters in the tonoplast, the expression of genes or the activities of H+-PPase and the vacuole-type H+-ATPase are increased, and Na+ enters into vacuoles [126–128]. Genes encoding Na+/H+ reverse transporters and vacuole-type H+-ATPase and H+-PPase were found in A. sphaerocephala. Salt overly sensitive (SOS) signal transduction pathwayis closely related to plant salt tolerance and has the most important role in ion homeostasis [129], A gene encoding ptotein involved in SOS pathway was also detected in A. sphaerocephala. Transcriptome analysis revealed that 103 out of 671 unigenes were among the top 1,000 highly expressed unigenes (S11 Table). Recent research has shown that HyPRP2, glycine-rich RNA-binding protein 7, glyceraldehyde-3-phosphate dehydrogenase, cysteine protease, HD-zip, isocitrate dehydrogenase, alcohol dehydrogenase 1 and other highly expressed unigenes participate in the process of salt tolerance and that expression of these genes improves the salt tolerance of plants [104, 130–133].
Drought tolerance.
In desert regions, water deficit is an important factor affecting plant growth. To identify hyperosmotic response mechanisms and to screen for possible functional genes, 108 unigenes related to the hyperosmotic response were annotated using the Nr and Swiss-Prot databases (S6 Table). Among these unigenes, 17 kinases, 2 potential chaperones, 52 enzymes (including SOD), 6 transporters and channels and 3 aquaporins were identified. Although we did not identify transcription factors that were involved in the drought response, 25 out of the 108 unigenes were among the 1,000 most highly expressed genes (S12 Table), including HyPRP2, glycine-rich RNA-binding protein 7, glyceraldehyde-3-phosphate dehydrogenase, cysteine protease and others; thus, they might participate in the process of drought resistance and ensure normal plant growth in arid environments [104, 130–132].
Multiple stresses.
Recurrent or multiple environmental stresses, such as high solar radiation and extreme temperatures, occur in the desert, and high evaporation rates lead to vapor pressure deficits and thus water stress. Salt also accumulates in surface soil. Combinations of various abiotic stresses affect plants simultaneously. Recent plant transcriptome studies have shown that the molecular mechanisms related to multiple stresses might differ from those associated with a single stress [134–137]. A total of 190 specific candidate genes are necessary for plant responses to various combinations of stresses, including salinity, osmotic stress and high temperature [136]. We found that 58 out of these 190 genes had orthologs in A. sphaerocephala (S13 Table) and that 8 of these unigenes were included among the 1,000 most highly expressed unigenes. These genes help A. sphaerocephala to minimize stress-related damage and to protect itself in harsh environments.
To reduce the chance of mistaking a paralog for an ortholog, we identified pairs of putative orthologs consisting of reciprocal best hits (RBHs) [138]. This approach resulted in detection of 17,904 pairs of putative orthologs that each corresponded to a single A. sphaerocephala unigene and A. thaliana peptide sequence (S14 Table). We compared 1,212 unigenes with 17,904 pairs of putative orthologs and identified 548 unigenes in A. thaliana, including 23 transcription factors, 6 LEAs, 2 aquaporins, 29 chaperones, 229 enzymes and 35 kinases. Among the 23 transcription factors, HD-zips and zinc finger proteins were classified as cold responsive, and 16 transcription factors, including MYB, WRKY, and bZIP transcription factors, were classified as salt responsive. Further, 5 HSFs were found to function in response to heat stress, and 2 aquaporins were determined to function in response to cold and salt stresses. Among the 6 LEAs, 4 were classified as cold responsive, and 4 were classified as salt responsive. The other 664 unigenes were also found to play important roles in stress responses in A. sphaerocephala, and they included 25 transcription factors, 3 LEAs, 2 aquaporins, 62 chaperones, 359 enzymes and 60 kinases. Among the 25 transcription factors, 9 HSFs were found to function in response to heat, and 4 transcription factors were determined to function in response to cold, including HD-zips and WRKY transcription factors. Further, 12 transcription factors were classified as salt responsive, including bZIP and MYB transcription factors, 3 LEAs were classified as cold and salt responsive, and 2 aquaporins were classified as cold, drought and salt responsive.
Conclusions and Perspectives
Artemisia sphaerocephala is a desert plant species with high ecological and economic value. In this study, 68,373 A. sphaerocephala unigenes were identified by high-throughput sequencing using an Illumina HiSeq 2500 platform, 58.7% of which were annotated. A set of heat, cold, salt and drought stress-responsive genes were identified, as well as 26 fad2, 3 fad3, 1 fad6, and 9 fad7/8 genes. To our knowledge, this study is the first to use high-throughput sequencing to investigate the global transcriptome of A. sphaerocephala. This study has provided valuable genetic resources that may be useful for modification of plant unsaturated fatty acids. These genetic findings are also potentially very valuable for increasing our understanding of the unsaturated fatty acid synthesis pathway, the biological effects of fad genes on stress and the molecular adaptive mechanisms of desert plants.
Supporting Information
S1 Fig. Histogram of the length distribution of transcripts.
https://doi.org/10.1371/journal.pone.0154300.s001
(DOCX)
S2 Fig. Histogram of the length distribution of ORFs.
https://doi.org/10.1371/journal.pone.0154300.s002
(DOCX)
S3 Fig. Nr annotation results distributed by E-values.
https://doi.org/10.1371/journal.pone.0154300.s003
(DOCX)
S4 Fig. Length distributions of annotated and un-annotated unigenes according to log(length).
https://doi.org/10.1371/journal.pone.0154300.s004
(DOCX)
S5 Fig. Expression levels of annotated and un-annotated unigenes according to log(FPKM).
https://doi.org/10.1371/journal.pone.0154300.s005
(DOCX)
S7 Fig. Nr annotation results based on sequence identities.
https://doi.org/10.1371/journal.pone.0154300.s007
(DOCX)
S1 Table. Information for 5 stress-response genes.
https://doi.org/10.1371/journal.pone.0154300.s008
(XLSX)
S2 Table. Primer information for 5 stress-response genes.
https://doi.org/10.1371/journal.pone.0154300.s009
(DOCX)
S3 Table. Length distribution of open reading frames (ORFs).
https://doi.org/10.1371/journal.pone.0154300.s010
(DOCX)
S4 Table. Summary of the final Artemisia sphaerocephala transcriptome annotation.
https://doi.org/10.1371/journal.pone.0154300.s011
(XLSX)
S5 Table. Artemisia sphaerocephala and Artemisia annua FAD2 protein sequences.
https://doi.org/10.1371/journal.pone.0154300.s012
(XLSX)
S6 Table. Annotation of stress response unigenes using the Nr and Swiss-Prot databases.
https://doi.org/10.1371/journal.pone.0154300.s013
(XLSX)
S7 Table. HSPs in the Artemisia sphaerocephala transcriptome.
https://doi.org/10.1371/journal.pone.0154300.s014
(XLSX)
S8 Table. Highly expressed heat-responsive unigenes.
https://doi.org/10.1371/journal.pone.0154300.s015
(XLSX)
S9 Table. Fifteen HSFs in Artemisia sphaerocephala.
https://doi.org/10.1371/journal.pone.0154300.s016
(XLSX)
S10 Table. Highly expressed cold-responsive unigenes.
https://doi.org/10.1371/journal.pone.0154300.s017
(XLSX)
S11 Table. Highly expressed salt-responsive unigenes.
https://doi.org/10.1371/journal.pone.0154300.s018
(XLSX)
S12 Table. Highly expressed hyperosmotic—responsive unigenes.
https://doi.org/10.1371/journal.pone.0154300.s019
(XLSX)
S13 Table. Possible genes involved in multiple stress responses.
https://doi.org/10.1371/journal.pone.0154300.s020
(XLSX)
S14 Table. Pairs of putative orthologs between Artemisia sphaerocephala and Arabidopsis thaliana.
https://doi.org/10.1371/journal.pone.0154300.s021
(XLSX)
Acknowledgments
We thank Dr. Changgui Wan and Dr. Pamela F. for English revision. We also thank the anonymous referees and editors for their comments and suggestions that helped to improve the manuscript.
Author Contributions
Conceived and designed the experiments: LZ. Performed the experiments: XH. Analyzed the data: LZ XH HF. Contributed reagents/materials/analysis tools: XM XC SHN. Wrote the paper: LZ XH.
References
- 1.
State Forestry Administration. A bulletin of status quo of desertification and sandification in China. Beijing: State Forestry Administration; 2011.
- 2. Tao W. Aeolian desertification and its control in Northern China. Int Soil Water Conserv Res. 2014;2: 34–41.
- 3. McNeely JA. Biodiversity in arid regions: values and perceptions. J Arid Environ. 2003;54: 61–70.
- 4. Yates SA, Chernukhin I, Alvarez-Fernandez R, Bechtold U, Baeshen M, Baeshen N, et al. The temporal foliar transcriptome of the perennial C3 desert plant Rhazya stricta in its natural environment. BMC Plant Biol. 2014;14: 2. pmid:24387666
- 5. Gutterman Y. Minireview: survival adaptations and strategies of annuals occurring in the Judean and Negev Deserts of Israel. Isr J Plant Sci. 2002;50: 165–175.
- 6. Qiu Q, Ma T, Hu Q, Liu B, Wu Y, Zhou H, et al. Genome-scale transcriptome analysis of the desert poplar, populus euphratica. Tree Physiol. 2011;31: 452–461. pmid:21427158
- 7. Dang ZH, Zheng LL, Wang J, Gao Z, Wu SB, Qi Z, et al. Transcriptomic profiling of the salt-stress response in the wild recretohalophyte Reaumuria trigyna. BMC Genomics. 2013;14: 29. pmid:23324106
- 8. Liu M, Shi J, Lu C. Identification of stress-responsive genes in Ammopiptanthus mongolicus using ESTs generated from cold- and drought-stressed seedlings. BMC Plant Biol. 2013;13: 88. pmid:23734749
- 9. Zhou R, Hou Y, Zuo J, Wang Y. The physiological adaptation mechanisms of four common desert species in response to desert environments. Acta Ecol Sin. 2015;2: 015.
- 10.
Lu Q, Wang JH, Chu JM. Desert plants in China. Beijing: China: Forestry Publishing House; 2012.
- 11. Xing XH, Zhang ZM, Hu XZ, Wu RQ, Xu C. Antidiabetic effects of Artemisia sphaerocephala Krasch. Gum, a novel food additive in China, on streptozotocin-induced type 2 diabetic rats. J Ethnopharmacol. 2009;125: 410–416. pmid:19635546
- 12. Yang X, Dong M, Huang Z. Role of mucilage in the germination of Artemisia sphaerocephala (Asteraceae) achenes exposed to osmotic stress and salinity. Plant Physiol Biochem. 2010;48: 131–135. pmid:20093038
- 13. Yang X, Baskin CC, Baskin JM, Liu G, Huang Z. Seed mucilage improves seedling emergence of a sand desert shrub. PLOS ONE. 2012;7: e34597. pmid:22511952
- 14. Yang TX, Li XX. Exploitation and application strategies of drought-resistant energy plants. Chin Bull. Life Sci. 2014;26: 440–446.
- 15. Song HX, Yang DQ, Zhao DY, Lu MX. Studies on the Artemisia sphaerocephala krasch seed oil refining. J Shaanxi Univ Sci Technol. 1996;14: 92–96.
- 16. Miao XM, Zhang LJ, Chen XL, Wu SJ, Niu DC, Fu H. The relationship of fatty acid composition and resistance of Artemisia shaerocephala seedlings under water stress. Acta Pratacultrae Sin. 2015;24: 55–61.
- 17. Roman O, Heyd B, Broyart B, Castillo R, Maillard M. Oxidative reactivity of unsaturated fatty acids from sunflower, high oleic sunflower and rapeseed oils subjected to heat treatment, under controlled conditions. LWT Food Sci Technol. 2013;52: 49–59.
- 18. Yurchenko OP, Park S, Ilut DC, Inmon JJ, Millhollon JC, Liechty Z, et al. Genome-wide analysis of the omega-3 fatty acid desaturase gene family in Gossypium. BMC Plant Biol. 2014;14: 312. pmid:25403726
- 19. Zhang J, Liu H, Sun J, Li B, Zhu Q, Chen S, et al. Arabidopsis fatty acid desaturase FAD2 is required for salt tolerance during seed germination and early seedling growth. PLOS ONE. 2012;7: e30355. pmid:22279586
- 20. Emken EA, Adlof RO, Gulley RM. Dietary linoleic acid influences desaturation and acylation of deuterium-labeled linoleic and linolenic acids in young adult males. Biochim Biophys Acta. 1994;1213: 277–288. pmid:7914092
- 21. Vattem DA, Crumb DJ. Conjugated linoleic acid (CLA)-an overview. IJARNP. 2011;4: 12–15.
- 22. Dilzer A, Park Y. Implication of conjugated linoleic acid (CLA) in human health. Crit Rev Food Sci Nutr. 2012;52: 488–513. pmid:22452730
- 23. Lehnen TE, da Silva MR, Camacho A, Marcadenti A, Lehnen AM. A review on effects of conjugated linoleic fatty acid (CLA) upon body composition and energetic metabolism. J Int Soc Sports Nutr. 2015;12: 36. pmid:26388708
- 24. Shahzad MM, Al-Niaimi A, Felder MA, Kapur A, Claussen N, Jallow F, et al. Abstract 683: biological significance of conjugated linoleic acid in ovarian carcinoma. Cancer Res. 2011;71: 683–683.
- 25. Kanauchi O, Mitsuyama K, Andoh A. The new prophylactic strategy for colon cancer in inflammatory bowel disease by modulating microbiota. Scand J Gastroenterol. 2013;48: 387–400. pmid:23249220
- 26. Risérus U, Berglund L, Vessby B. Conjugated linoleic acid (CLA) reduced abdominal adipose tissue in obese middle-aged men with signs of the metabolic syndrome: a randomised controlled trial. Int J Obes Relat Metab Disord. 2001;25: 1129–1135. pmid:11477497
- 27. Palmquist DL, Lock AL, Shingfield KJ, Bauman DE. Biosynthesis of conjugated linoleic acid in ruminants and humans. Adv Food Nutr Res. 2005;50: 179–217. pmid:16263431
- 28. Scheffer M, Carpenter SR. Catastrophic regime shifts in ecosystems: linking theory to observation. Trends Ecol Evol. 2003;18: 648–656.
- 29. Wilhelm BT, Marguerat S, Watt S, Schubert F, Wood V, Goodhead I, et al. Dynamic repertoire of a eukaryotic transcriptome surveyed at single-nucleotide resolution. Nature. 2008;453: 1239–1243. pmid:18488015
- 30. Shi Y, Yan X, Zhao P, Yin H, Zhao X, Xiao H, et al. Transcriptomic analysis of a tertiary relict plant, extreme xerophyte Reaumuria soongorica to identify genes related to drought adaptation. PLOS ONE. 2013;8: e63993. pmid:23717523
- 31. Zhou Y, Gao F, Liu R, Feng J, Li H. De novo sequencing and analysis of root transcriptome using 454 pyrosequencing to discover putative genes associated with drought tolerance in Ammopiptanthus mongolicus. BMC Genomics. 2012;13: 266. pmid:22721448
- 32. Xu ZQ, Jia JF. Tissue culture and plant regeneration in Artemisia shaerocephala Krsach. Acta Bol Boreal Occident Sin. 1995;15: 100–103.
- 33. Verslues PE, Agarwal M, Katiyar-Agarwal S, Zhu J, Zhu JK. Methods and concepts in quantifying resistance to drought, salt and freezing, abiotic stresses that affect plant water status. Plant J. 2006;45: 523–539. pmid:16441347
- 34. Meyer E, Aglyamova GV, Wang S, Buchanan-Carter J, Abrego D, Colbourne JK, et al. Sequencing and de novo analysis of a coral larval transcriptome using 454 GSFlx. BMC Genomics. 2009;10: 219. pmid:19435504
- 35. Grabherr MG, Haas BJ, Yassour M, Levin JZ, Thompson DA, Amit I, et al. Full-length transcriptome assembly from RNA-Seq data without a reference genome. Nat Biotechnol. 2011;29: 644–652. pmid:21572440
- 36. Pfaffl MW. A new mathematical model for relative quantification in real-time RT-PCR. Nucleic Acids Res. 2001;29: e45. pmid:11328886
- 37. Altschul SF, Madden TL, Schäffer AA, Zhang J, Zhang Z, Miller W, et al. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res. 1997;25: 3389–3402. pmid:9254694
- 38. Liu M, Qiao G, Jiang J, Yang H, Xie L, Xie J, et al. Transcriptome sequencing and de novo analysis for ma bamboo (Dendrocalamus latiflorus Munro) using the Illumina platform. PLOS ONE. 2012;7: e46766. pmid:23056442
- 39. Zhang XM, Zhao L, Larson-Rabin Z, Li DZ, Guo ZH. De novo sequencing and characterization of the floral transcriptome of Dendrocalamus latiflorus (Poaceae: Bambusoideae). PLOS ONE. 2012;7: e42082. pmid:22916120
- 40. Ohlrogge J, Browse J. Lipid biosynthesis. Plant Cell. 1995;7: 957–970. pmid:7640528
- 41. Cao S, Zhou XR, Wood CC, Green AG, Singh SP, Liu L, et al. A large and functionally diverse family of Fad2 genes in safflower (carthamus tinctorius L.). BMC Plant Biol. 2013;13: 5. pmid:23289946
- 42. Schlueter JA, Vasylenko-Sanders IF, Deshpande S, Yi J, Siegfried M, Roe BA, et al. The FAD2 gene family of soybean: insights into the structural and functional divergence of a paleopolyploid genome. Crop Sci. 2007;47: 14–26.
- 43. Pham AT, Lee JD, Shannon JG, Bilyeu KD. Mutant alleles of FAD2-1A and FAD2-1B combine to produce soybeans with the high oleic acid seed oil trait. BMC Plant Biol. 2010;10: 195. pmid:20828382
- 44.
Williams JP, Khan MU, Lem NW. Physiology, biochemistry and molecular biology of plant lipids. Dordrecht, The Netherlands: Kluwer Academic Publishers; 1997.
- 45. Zhang D, Pirtle IL, Park SJ, Nampaisansuk M, Neogi P, Wanjie SW, et al. Identification and expression of a new delta-12 fatty acid desaturase (FAD2-4) gene in upland cotton and its functional expression in yeast and Arabidopsis thaliana plants. Plant Physiol Biochem. 2009;47: 462–471. pmid:19217793
- 46. Liu Q, Brubaker CL, Green AG, Marshall DR, Sharp PJ, Singh SP. Evolution of the FAD2–1 fatty acid desaturase 5’ UTR intron and the molecular systematics of Gossypium (Malvaceae). Am J Bot. 2001;88: 92–102. pmid:11159130
- 47. Pirtle IL, Kongcharoensuntorn W, Nampaisansuk M, Knesek JE, Chapman KD, Pirtle RM. Molecular cloning and functional expression of the gene for a cotton Delta-12 fatty acid desaturase (FAD2). Biochim Biophys Acta. 2001;1522: 122–129. pmid:11750064
- 48. Yang Q, Fan C, Guo Z, Qin J, Wu J, Li Q, et al. Identification of FAD2 and FAD3 genes in Brassica napus genome and development of allele-specific markers for high oleic and low linolenic acid contents. Theor Appl Genet. 2012;125: 715–729. pmid:22534790
- 49. Sánchez-García A, Mancha M, Heinz E, Martínez-Rivas JM. Differential temperature regulation of three sunflower microsomal oleate desaturase (FAD2) isoforms overexpressed in Saccharomyces cerevisiae. Eur J Lipid Sci Technol. 2004;106: 583–590.
- 50. Jung S, Swift D, Sengoku E, Patel M, Teulé F, Powell G, et al. The high oleate trait in the cultivated peanut [Arachis hypogaea L.]. I. Isolation and characterization of two genes encoding microsomal oleoyl-PC desaturases. Mol Gen Genet. 2000;263: 796–805. pmid:10905347
- 51. Chi X, Yang Q, Pan L, Chen M, He Y, Yang Z, et al. Isolation and characterization of fatty acid desaturase genes from peanut (Arachis hypogaea L.). Plant Cell Rep. 2011;30: 1393–1404. pmid:21409552
- 52. Okuley J, Lightner J, Feldmann K, Yadav N, Lark E, Browse J. Arabidopsis FAD2 gene encodes the enzyme that is essential for polyunsaturated lipid synthesis. Plant Cell. 1994;6: 147–158. pmid:7907506
- 53. Krasowska A, Dziadkowiec D, Polinceusz A, Plonka A, Łukaszewicz M. Cloning of flax oleic fatty acid desaturase and its expression in yeast. J Am Oil Chem Soc. 2007;84: 809–816.
- 54. Khadake RM, Ranjekar PK, Harsulkar AM. Cloning of a novel omega-6 desaturase from flax (linum usitatissimum L.) and its functional analysis in Saccharomyces cerevisiae. Mol Biotechnol. 2009;42: 168–174. pmid:19214810
- 55. You FM, Li P, Kumar S, Ragupathy R, Li Z, Fu YB, et al. Genome-wide identification and characterization of the gene families controlling fatty acid biosynthesis in flax (linum usitatissimum L). J Proteomics Bioinform. 2014;7: 310–326.
- 56. Soetaert SS, Van Neste CM, Vandewoestyne ML, Head SR, Goossens A, Van Nieuwerburgh FC, et al. Differential transcriptome analysis of glandular and filamentous trichomes in Artemisia annua. BMC Plant Biol. 2013;13: 220. pmid:24359620
- 57. Sabzalian MR, Saeidi G, Mirlohi A. Oil content and fatty acid composition in seeds of three safflower species. J Am Oil Chem Soc. 2008;85: 717–721.
- 58. Baux A, Hebeisen T, Pellet D. Effects of minimal temperatures on low-linolenic rapeseed oil fatty-acid composition. Eur J Agron. 2008;29: 102–107.
- 59. Sabudak T. Fatty acid composition of seed and leaf oils of pumpkin, walnut, almond, maize, sunflower and melon. Chem Nat Compd. 2007;43: 465–467.
- 60.
Boerma HR, Specht JE. Soybeans: improvement, production and uses. Madison, WI: American Society of Agronomy, Crop Science Society of America, Soil Science Society of America; 2004.
- 61. Gaude N, Tippmann H, Flemetakis E, Katinakis P, Udvardi M, Dörmann P. The galactolipid digalactosyldiacylglycerol accumulates in the peribacteroid membrane of nitrogen-fixing nodules of soybean and lotus. J Biol Chem. 2004;279: 34624–34630. pmid:15159398
- 62. Lukonge E, Labuschagne MT, Hugo A. The evaluation of oil and fatty acid composition in seed of cotton accessions from various countries. J Sci Food Agric. 2007;87: 340–347.
- 63. Puttick D, Dauk M, Lozinsky S, Smith MA. Overexpression of a FAD3 desaturase increases synthesis of a polymethylene-interrupted dienoic fatty acid in seeds of Arabidopsis thaliana L. Lipids. 2009;44: 753–757. pmid:19548018
- 64. Li-Beisson Y, Shorrosh B, Beisson F, Andersson MX, Arondel V, Bates PD, et al. Acyl-lipid metabolism. Arabidopsis Book. 2010;11: e0133.
- 65. Cherian G, Sim JS. Effect of feeding full fat flax and canola seeds to laying hens on the fatty acid composition of eggs, embryos, and newly hatched chicks. Poult Sci. 1991;70: 917–922.
- 66. Banik M, Duguid S, Cloutier S, Belzile F. Transcript profiling and gene characterization of three fatty acid desaturase genes in high, moderate, and low linolenic acid genotypes of flax (linum usitatissimum L.) and their role in linolenic acid accumulation. Genome. 2011;54: 471–483. pmid:21627464
- 67. Vrinten P, Hu Z, Munchinsky MA, Rowland G, Qiu X. Two FAD3 desaturase genes control the level of linolenic acid in flax seed. Plant Physiol. 2005;139: 79–87. pmid:16113219
- 68. Guan LL, Wu W, Hu B, Li D, Chen JW, Hou K, et al. Devolopmental and growth temperature regulation of omega-3 fatty acid desaturase genes in safflower (carthamus tinctorius L.). Genet Mol Res. 2014;13: 6623–6637. pmid:25177943
- 69. Bilyeu K, Palavalli L, Sleper D, Beuselinck P. Mutations in soybean microsomal omega-3 fatty acid desaturase genes reduce linolenic acid concentration in soybean seeds. Crop Sci. 2005;45: 1830–1836.
- 70. Bilyeu K, Palavalli L, Sleper DA, Beuselinck P. Molecular genetic resources for development of 1% linolenic acid soybeans. Crop Sci. 2006;46: 1913–1918.
- 71. Chi X, Yang Q, Lu Y, Wang J, Zhang Q, Pan L, et al. Genome-wide analysis of fatty acid desaturases in soybean (Glycine max). Plant Mol Biol Rep. 2011;29: 769–783.
- 72. Velasco L, Becker HC. Estimating the fatty acid composition of the oil in intact-seed rapeseed (Brassica napus L.) by near-infrared reflectance spectroscopy. Euphytica. 1998;101: 221–230.
- 73. Chapman MA, Burke JM. Evidence of selection on fatty acid biosynthetic genes during the evolution of cultivated sunflower. Theor Appl Genet. 2012;125: 897–907. pmid:22580969
- 74. Venegas-Calerón M, Muro-Pastor AM, Garcés R, Martínez-Force E. Functional characterization of a plastidial omega-3 desaturase from sunflower (Helianthus annuus) in cyanobacteria. Plant Physiol Biochem. 2006;44: 517–525. pmid:17064923
- 75. Yadav NS, Wierzbicki A, Aegerter M, Caster CS, Pérez-Grau L, Kinney AJ, et al. Cloning of higher plant omega-3 fatty acid desaturases. Plant Physiol. 1993;103: 467–476. pmid:8029334
- 76. Falcone DL, Gibson S, Lemieux B, Somerville C. Identification of a gene that complements an Arabidopsis mutant deficient in chloroplast Omega 6 desaturase activity. Plant Physiol. 1994;106: 1453–1459. pmid:7846158
- 77. Kodama H, Hamada T, Horiguchi G, Nishimura M, Iba K. Genetic enhancement of cold tolerance by expression of a gene for chloroplast [Omega]-3 fatty acid desaturase in transgenic tobacco. Plant Physiol. 1994;105: 601–605. pmid:12232227
- 78. Gibson S, Arondel V, Iba K, Somerville C. Cloning of a temperature-regulated gene encoding a chloroplast omega-3 desaturase from Arabidopsis thaliana. Plant Physiol. 1994;106: 1615–1621. pmid:7846164
- 79. Miquel M, James D, Dooner H, Browse J. Arabidopsis requires polyunsaturated lipids for low-temperature survival. Proc Natl Acad Sci USA. 1993;90: 6208–6212. pmid:11607410
- 80. Rodríguez-Vargas S, Sánchez-García A, Martínez-Rivas JM, Prieto JA, Randez-Gil F. Fluidization of membrane lipids enhances the tolerance of Saccharomyces cerevisiae to freezing and salt stress. Appl Environ Microbiol. 2007;73: 110–116. pmid:17071783
- 81. Matsuda O, Watanabe C, Iba K. Hormonal regulation of tissue-specific ectopic expression of an Arabidopsis endoplasmic reticulum-type omega-3 fatty acid desaturase (FAD3) gene. Planta. 2001;213: 833–840. pmid:11722119
- 82. Hugly S, Somerville C. A role for membrane lipid polyunsaturation in chloroplast biogenesis at low temperature. Plant Physiol. 1992;99: 197–202. pmid:16668849
- 83. Zhang JT, Zhu JQ, Zhu Q, Liu H, Gao XS, Zhang HX. Fatty acid desaturase-6 (Fad6) is required for salt tolerance in Arabidopsis thaliana. Biochem Biophys Res Commun. 2009;390: 469–474. pmid:19799856
- 84. Kodama H, Horiguchi G, Nishiuchi T, Nishimura M, Iba K. Fatty acid desaturation during chilling acclimation is one of the factors involved in conferring low-temperature tolerance to young tobacco leaves. Plant Physiol. 1995;107: 1177–1185. pmid:12228424
- 85. Horiguchi G, Iwakawa H, Kodama H, Kawakami N, Nishimura M, Iba K. Expression of a gene for plastid ω-3 fatty acid desaturase and changes in lipid and fatty acid compositions in light-and dark-grown wheat leaves. Physiol Plant. 1996;96: 275–283.
- 86. Rizhsky L, Liang H, Mittler R. The combined effect of drought stress and heat shock on gene expression in tobacco. Plant Physiol. 2002;130: 1143–1151. pmid:12427981
- 87. Yabe N, Takahashi T, Komeda Y. Analysis of tissue-specific expression of Arabidopsis thaliana HSP90-family gene HSP81. Plant Cell Physiol. 1994;35: 1207–1219. pmid:7697294
- 88. Milioni D, Hatzopoulos P. Genomic organization of hsp90 gene family in Arabidopsis. Plant Mol Biol. 1997;35: 955–961. pmid:9426614
- 89. Pareek A, Singla SL, Grover A. Immunological evidence for accumulation of two high-molecular-weight (104 and 90 kDa) HSPs in response to different stresses in rice and in response to high temperature stress in diverse plant genera. Plant Mol Biol. 1995;29: 293–301. pmid:7579180
- 90. Liu D, Zhang X, Cheng Y, Takano T, Liu S. rHsp90 gene expression in response to several environmental stresses in rice (Oryza sativa L.). Plant Physiol Biochem. 2006;44: 380–386. pmid:16889974
- 91. Yamada K, Fukao Y, Hayashi M, Fukazawa M, Suzuki I, Nishimura M. Cytosolic HSP90 regulates the heat shock response that is responsible for heat acclimation in Arabidopsis thaliana. J Biol Chem. 2007;282: 37794–37804. pmid:17965410
- 92. Kadota Y, Shirasu K. The HSP90 complex of plants. Biochim Biophys Acta. 2012;1823: 689–697. pmid:22001401
- 93. Nishizawa-Yokoi A, Tainaka H, Yoshida E, Tamoi M, Yabuta Y, Shigeoka S. The 26S proteasome function and Hsp90 activity involved in the regulation of HsfA2 expression in response to oxidative stress. Plant Cell Physiol. 2010;51: 486–496. pmid:20147301
- 94. Priyanka B, Sekhar K, Reddy VD, Rao KV. Expression of pigeonpea hybrid-proline-rich protein encoding gene (CcHyPRP) in yeast and Arabidopsis affords multiple abiotic stress tolerance. Plant Biotechnol J. 2010;8: 76–87. pmid:20055960
- 95. Qin L, Zhang D, Huang G, Li L, Li J, Gong S, et al. Cotton GhHyPRP3 encoding a hybrid proline-rich protein is stress inducible and its overexpression in Arabidopsis enhances germination under cold temperature and high salinity stress conditions. Acta Physiol Plant. 2013;35: 1531–1542.
- 96. Tan J, Zhuo C, Guo Z. Nitric oxide mediates cold- and dehydration-induced expression of a novel MfHyPRP that confers tolerance to abiotic stress. Physiol Plant. 2013;149: 310–320. pmid:23387330
- 97. Miller G, Mittler R. Could heat shock transcription factors function as hydrogen peroxide sensors in plants? Ann Bot. 2006;98: 279–288. pmid:16740587
- 98. Howarth CJ, Ougham HJ. Gene expression under temperature stress. New Phytol. 1993;125: 1–26.
- 99. Finka A, Mattoo RU, Goloubinoff P. Meta-analysis of heat- and chemically upregulated chaperone genes in plant and human cells. Cell Stress Chaperones. 2011;16: 15–31. pmid:20694844
- 100. Saidi Y, Finka A, Goloubinoff P. Heat perception and signalling in plants: a tortuous path to thermotolerance. New Phytol. 2011;190: 556–565. pmid:21138439
- 101. von Koskull-Döring P, Scharf KD, Nover L. The diversity of plant heat stress transcription factors. Trends Plant Sci. 2007;12: 452–457. pmid:17826296
- 102. Scharf KD, Berberich T, Ebersberger I, Nover L. The plant heat stress transcription factor (Hsf) family: structure, function and evolution. Biochim Biophys Acta. 2012;1819: 104–119. pmid:22033015
- 103. Smart CC, Fleming AJ. A plant gene with homology to D-myo-inositol-3-phosphate synthase is rapidly and spatially up-regulated during an abscisic-acid-induced morphogenic response in Spirodela polyrrhiza. Plant J. 1993;4: 279–293. pmid:8220483
- 104. Xu D, Huang X, Xu ZQ, Schläppi M. The HyPRP gene EARLI1 has an auxiliary role for germinability and early seedling development under low temperature and salt stress conditions in Arabidopsis thaliana. Planta. 2011;234: 565–577. pmid:21556912
- 105. Reddy PS, Kavi Kishor PB, Seiler C, Kuhlmann M, Eschen-Lippold L, Lee J, et al. Unraveling regulation of the small heat shock proteins by the heat shock factor HvHsfB2c in barley: its implications in drought stress response and seed development. PLOS ONE. 2014;9: e89125. pmid:24594978
- 106. La PN, Sablok G, Emilliani G, Hietala AM, Giovannelli A, Fontana P, et al. Identification of low temperature stress regulated transcript sequences and gene families in Italian cypress. Mol Biotechnol. 2014;57: 407–418.
- 107. Ariel FD, Manavella PA, Dezar CA, Chan RL. The true story of the HD-Zip family. Trends Plant Sci. 2007;12: 419–426. pmid:17698401
- 108. Ariel F, Diet A, Verdenaud M, Gruber V, Frugier F, Chan R, et al. Environmental regulation of lateral root emergence in Medicago truncatula requires the HD-Zip I transcription factor HB1. Plant Cell. 2010;22: 2171–2183. pmid:20675575
- 109. Valdés AE, Overnäs E, Johansson H, Rada-Iglesias A, Engström P. The homeodomain-leucine zipper (HD-Zip) class I transcription factors ATHB7 and ATHB12 modulate abscisic acid signalling by regulating protein phosphatase 2C and abscisic acid receptor gene activities. Plant Mol Biol. 2012;80: 405–418. pmid:22968620
- 110. Luo M, Bilodeau P, Koltunow A, Dennis ES, Peacock WJ, Chaudhury AM. Genes controlling fertilization-independent seed development in Arabidopsis thaliana. Proc Natl Acad Sci USA. 1999;96: 296–301. pmid:9874812
- 111. Prigge MJ, Wagner DR. The arabidopsis serrate gene encodes a zinc-finger protein required for normal shoot development. Plant Cell. 2001;13: 1263–1279. pmid:11402159
- 112. Xiao H, Tang J, Li Y, Wang W, Li X, Jin L, et al. Stamenless 1, encoding a single C2H2 zinc finger protein, regulates floral organ identity in rice. Plant J. 2009;59: 789–801. pmid:19453444
- 113. Zhou Z, Sun L, Zhao Y, An L, Yan A, Meng X, et al. Zinc finger Protein 6 (ZFP6) regulates trichome initiation by integrating gibberellin and cytokinin signaling in Arabidopsis thaliana. New Phytol. 2013;198: 699–708. pmid:23506479
- 114. Wang Y, Dou D, Wang X, Li A, Sheng Y, Hua C, et al. The PsCZF1 gene encoding a C2H2 zinc finger protein is required for growth, development and pathogenesis in Phytophthora sojae. Microb Pathog. 2009;47: 78–86. pmid:19447167
- 115. Zhang H, Ni L, Liu Y, Wang Y, Zhang A, Tan M, et al. The C2H2-type zinc finger protein ZFP182 is involved in abscisic acid-induced antioxidant defense in rice. J Integr Plant Biol. 2012;54: 500–510. pmid:22693960
- 116. Sakamoto H, Araki T, Meshi T, Iwabuchi M. Expression of a subset of the Arabidopsis Cys(2)/His(2)-type zinc-finger protein gene family under water stress. Gene. 2000;248: 23–32. pmid:10806347
- 117. Kim JC, Lee SH, Cheong YH, Yoo CM, Lee SI, Chun HJ, et al. A novel cold-inducible zinc finger protein from soybean, SCOF-1, enhances cold tolerance in transgenic plants. Plant J. 2001;25: 247–259. pmid:11208017
- 118. Rushton PJ, Somssich IE, Ringler P, Shen QJ. WRKY transcription factors. Trends Plant Sci. 2010;15: 247–258. pmid:20304701
- 119. Rocco M, Arena S, Renzone G, Scippa GS, Lomaglio T, Verrillo F, et al. Proteomic analysis of temperature stress-responsive proteins in Arabidopsis thaliana rosette leaves. Mol Biosyst. 2013;9: 1257–1267. pmid:23624559
- 120. Thouvenot L, Deleu C, Berardocco S, Haury J, Thiébaut G. Characterization of the salt stress vulnerability of three invasive freshwater plant species using a metabolic profiling approach. J Plant Physiol. 2015;175: 113–121. pmid:25544588
- 121. Jiang Y, Deyholos MK. Functional characterization of Arabidopsis NaCl-inducible WRKY25 and WRKY33 transcription factors in abiotic stresses. Plant Mol Biol. 2009;69: 91–105. pmid:18839316
- 122. Ahuja I, de Vos RC, Bones AM, Hall RD. Plant molecular stress responses face climate change. Trends Plant Sci. 2010;15: 664–674. pmid:20846898
- 123. Dubos C, Stracke R, Grotewold E, Weisshaar B, Martin C, Lepiniec L. MYB transcription factors in Arabidopsis. Trends Plant Sci. 2010;15: 573–581. pmid:20674465
- 124. Hirayama T, Shinozaki K. Research on plant abiotic stress responses in the post-genome Era: past, present and future. Plant J. 2010;61: 1041–1052. pmid:20409277
- 125. Mizoi J, Shinozaki K, Yamaguchi-Shinozaki K. AP2/ERF family transcription factors in plant abiotic stress responses. Biochim Biophys Acta. 2012;1819: 86–96. pmid:21867785
- 126. Gaxiola RA, Li J, Undurraga S, Dang LM, Allen GJ, Alper SL, et al. Drought- and salt-tolerant plants result from overexpression of the AVP1 H+-pump. Proc Natl Acad Sci USA. 2001;98: 11444–11449. pmid:11572991
- 127. Golldack D, Dietz KJ. Salt-induced expression of the vacuolar H+-Atpase in the common ice plant is developmentally controlled and tissue specific. Plant Physiol. 2001;125: 1643–1654. pmid:11299346
- 128. Shi H, Zhu JK. Regulation of expression of the vacuolar Na+/H+ antiporter gene AtNHX1 by salt stress and abscisic acid. Plant Mol Biol. 2002;50: 543–550. pmid:12369629
- 129. Zhu JK. Salt and drought stress signal transduction in plants. Annu Rev Plant Biol. 2002;53: 247–273. pmid:12221975
- 130. Kim JY, Kim WY, Kwak KJ, Oh SH, Han YS, Kang H. Glycine-rich RNA-binding proteins are functionally conserved in Arabidopsis thaliana and Oryza sativa during cold adaptation process. J Exp Bot. 2010;61: 2317–2325. pmid:20231330
- 131. Zhang X, Rao X, Shi H, Li R, Lu Y. Overexpression of a cytosolic glyceraldehyde-3-phosphate dehydrogenase gene OsGAPC3 confers salt tolerance in rice. Plant Cell Tissue Organ Cult. 2011;107: 1–11.
- 132. Evers D, Legay S, Lamoureux D, Hausman JF, Hoffmann L, Renaut J. Towards a synthetic view of potato cold and salt stress response by transcriptomic and proteomic analyses. Plant Mol Biol. 2012;78: 503–514. pmid:22258187
- 133. Timpson LM, Liliensiek AK, Alsafadi D, Cassidy J, Sharkey MA, Liddell S, et al. A comparison of two novel alcohol dehydrogenase enzymes (ADH1 and ADH2) from the extreme halophile Haloferax volcanii. Appl Microbiol Biotechnol. 2013;97: 195–203. pmid:22526808
- 134. Mittler R. Abiotic stress, the field environment and stress combination. Trends Plant Sci. 2006;11: 15–19. pmid:16359910
- 135. Rasmussen S, Barah P, Suarez-Rodriguez MC, Bressendorff S, Friis P, Costantino P. Transcriptome responses to combinations of stresses in Arabidopsis. Plant Physiol. 2013;161: 1783–1794. pmid:23447525
- 136. Sewelam N, Oshima Y, Mitsuda N, Ohme-Takagi M. A step towards understanding plant responses to multiple environmental stresses: a genome-wide study. Plant Cell Environ. 2014;37: 2024–2035. pmid:24417440
- 137. Suzuki N, Rivero RM, Shulaev V, Blumwald E, Mittler R. Abiotic and biotic stress combinations. New Phytol. 2014;203: 32–43. pmid:24720847
- 138. Zhao P, Capella-Gutíerrez S, Shi Y, Zhao X, Chen G, Gabaldón T, et al. Transcriptomic analysis of a psammophyte food crop, sand rice (Agriophyllum squarrosum) and identification of candidate genes essential for sand dune adaptation. BMC Genomics. 2014;15: 872. pmid:25287394