1. Introduction
With increasing demand for food and the decreasing availability of arable land [
1,
2], intercropping, a practice where multiple crop species are grown together, is gaining in popularity as a sustainable practice for low-input or resource-limited agricultural systems [
3]. Several intercropping systems, such as maize/soybeans [
4,
5,
6], maize/peanut [
7], cotton/peanut [
8], and sugarcane/soybean [
9], have been developed and have proven to be efficient. High and low tiers of intercropped plants may benefit from each other, especially for leguminous crops and others [
3]. However, interspecific competition for light and fertilizer is the main factor constraining plant growth and yield in the intercropping systems [
10].
Shading emerges as a result of high-density planting and intercropping, which reduces light intensity and changes the light quality to a low ratio of red light to far-red light [
11,
12]. A low-height crop is always affected by a tall crop in the intercropping practice, receiving a reduced amount of sunlight. It is known that plants will try to escape shade, after perceiving the change of light signal in shade caused by plant proximity, through shade avoidance. Shade avoidance syndrome (SAS) includes elongation growth, accelerated flowering, early seed production, and reduced yield [
13]. Photoreceptor phytochromes perceive a change in the ratio of red light to far-red light under shade, and photoreceptor cryptochromes sense the change of light intensity to control adaptive developmental strategies [
14,
15,
16,
17]. The signal then is transduced and cascaded via PHYTOCHROME INTERACTING FACTORS (PIFS), circadian clock basic helix–loop–helix protein PIL1, circadian clock protein TOC1, and other transcription factors in DELLA families to trigger changes of gene expression and induce a series of SAS responses [
11,
12,
14,
18,
19]. Many genes were involved in light, hormone, and stress responses in early responses to low ratio of red and far-red light of shade [
20,
21,
22,
23]. Comparative RNA-Seq analyses in conifers with different syndromes of shade avoidance and tolerance show that main transcriptional regulations are involved in hormone signaling and pigment biosynthesis [
24]. Crosstalk of shade avoidance has been found between transcription factors, hormones, and circadian clock etc. in plants [
14]. Growth elongation of the stem and petioles is to avoid shading at the cost of assimilated resources, which eventually reduces the crop yield [
25,
26]. Under intercropping, shading occurs for the low-tier plant where the photosynthetically active radiation (PAR) decreases [
27]. The SAS is balanced plastic responses from interactions of both PAR and the low ratio of red to far-red light [
28,
29]. Most knowledge of shade studies has been gained from model plants e.g.
Arabidopsis, instead of crops.
Peanut
Arachis hypogaea L. (Fabaceae), also known as groundnut, is an important oil and protein crop of South American origin and is nowadays cultivated worldwide [
30]. The cultivated peanut is a tetraploid that was derived from an ancient hybridization of two diploid peanut ancestors. The genome sequences of ancestral diploid peanuts with ~1.2 Gb genome A in
A. duranensis or B in
A. ipaensis [
31,
32], and genome sequences of three cultivars of
A. hypogaea with genome AABB of 2.6 Gb are made available now [
33,
34,
35], which has facilitated the exploration of molecular mechanisms of physiological processes in peanut, including SAS. The SAS effect is of high practical importance due to the decreasing intensity of sunlight in China and other countries as a result of pollution [
36].
In this study, we simulated 40% and 80% shade to treat peanut plants at the seedling stage, flowering stage, and combined both stages (CS) for two periods (15 days and 30 days, respectively) while kept the control plants under natural sunlight. To understand the shade effects on growth, biomass, and seed yield, we first examined the physiological and hormonal changes. Then, to understand the gene regulatory mechanisms of peanut plant responses to shade, we generated and compared the genome-scale transcriptome profiles for shaded and control leaves. We identified common expressional regulation under different shade schemes involved in photosynthesis pathways, starch and sucrose metabolism, and hormonal signal pathways. We found that shade stresses induced expressional reduction of genes in light-harvesting complex and were associated with altered expression of genes in photosynthesis systems, which resulted in low physiological photosynthesis. Shade stress also caused the common downregulation of key genes in starch and sucrose metabolism and hormonal signal pathways. Shading degree, duration, and developmental stages were also compared to reveal the difference of effects. Our results demonstrated the association of gene expressional regulation with strong SAS in peanut plants under shade stress. This study provided clues to physiological changes and gene regulatory mechanisms of shade avoidance syndrome in peanut plants, which advances our understanding of shade avoidance in the peanut crop. Thus, our results may guide the design of intercropping and breeding by tuning the associated gene expression.
3. Discussion
Shade avoidance in plants is an adaptive response to avoid shade stress. To date, many studies show that shade avoidance is induced by light regimes with a reduced light intensity or PAR, and/or low ratio of red to far-red light [
14,
15,
48]. In intercropping systems such as maize/peanut [
7] and cotton/peanut [
8], the peanut plant is shade stressed which reduced the yield of peanut. For intercropping with peanut, the existing knowledge is focused on biomass and physiological changes [
8]. Here, our results revealed the systematic effects of simulated shades on phenotypic, physiological, and expressional regulation in peanut, which advances our understanding of shade regulation in intercropping. To our best knowledge, this is the first report on shade avoidance responses at the whole transcriptome scale to reveal the common core regulation of expression across shade stresses in peanut plants. Our results reveal that tuning the expressional regulation under shade could be the fundamental solution to avoid shade syndrome and to avoid yield decrease of peanut. Of course, it is of priority to further examine the expressional regulation in field shading in the real intercropping farming.
Shade stress changes the growth, photosynthesis, assimilation, and allocation of resources. As was observed in our study, decreased biomass and increased elongation growth are common characteristics of shade avoidance in plants [
14,
15,
48]. Elongation growth is a typical shade response to low ratio of red to far-red light [
17]; the latter changes auxin synthesis, transportation, perception and signaling via free auxin levels, and expression of IAA associated transcription factors [
15,
44]. A study of elongation of the hypocotyl in
Arabidopsis under shade shows that cotyledon-derived auxin is necessary to initiate hypocotyl growth [
23]. In our study, elongation was associated with an increase in auxin levels in leaves, which suggests that shade induces a crosstalk within hormones [
44] and the auxin promotes elongation under shade [
49]. Our analysis of gene regulation in multiple plant hormone signal pathways revealed that the growth promoting hormones auxin, gibberellin, brassinosteroid, cytokinine and senescing hormones of abscisic acid and ethylene were all stimulated under shade treatment. This could be a crosstalk from a manner of hormone cascaded signaling network [
44,
47,
50]. The regulation on the hormone DEGs activates downstream regulation to promote growth elongation under shade [
45]. The gene expressional crosstalk and associated hormone levels in both leaves and stem should be investigated further under shade treatment, especially for the seedling stage, where elongation is the most significant. It was observed that under shade, reduced photosynthetic activity was the result of the reduced availability of PAR. This can be explained by low expression of light-harvesting complex genes, and low expression of photosynthesis genes in our core DEG sets in photosynthesis pathways. The association between low PAR and low photosynthetic activity could be an economic and adaptive response where low concentration light-harvesting protein is enough to capture the available light energy for photosynthesis under shade, which is to optimize the use of resources under shade [
15]. Several DEGs, which may have multiple homologous genes, were upregulated in the long duration shading treatment CS80 but downregulated in other short duration shade treatments, which could be a plant response to extreme stress induced by a deep and prolonged shade (i.e., too little light to maintain necessary photosynthesis). Previous research showed the phytochrome effects on plant biomass, resource allocation, and metabolic state under shade [
51]. Therefore, the observed low plant biomass under stress is the resulting effect of low photosynthesis and reallocation of metabolites among investigated three tissues. The observed elongation may change the allocation of carbohydrates, which are transferred from leaves to the main stem for elongation. This matches the observed changes in biomass of root, leaf, and stem, which could be a way to balance storing into a biomass and investing in growth under shade stress [
52]. Therefore, to achieve high peanut yield in an intercropping system, a variety must have high tolerance to shade and high adaptivity to low light intensity. The observation of very low expression levels of several DEGs, e.g., 0 FPKM, in photosynthesis pathways, and metabolism of sucrose and starch suggests expressional switching off or on, which may play important roles in the shade responsive regulation, but attention should be drawn because those genes’ levels were very low, less than 1 FPKM.
Gene expressional regulation in shade avoidance, especially induced by the low ratio of red and far-red light, has been well studied in model plants. Microarray analysis showed that light signal genes, hormone related genes, and stress induced genes were induced by low ratio of red and far-red light [
20]. Another microarray analysis revealed the expressional regulation of genes involved in the metabolism of cell wall carbohydrates, auxin responses, and flavonoids in the stem of tomato [
21]. RNA-Seq based transcriptome analyses in other plants like conifers revealed regulations on hormone signaling and pigment biosynthesis under shade [
24]. Here, analyses of DEGs also identified enrichments of those reported pathways and more additional pathways, 18 pathways in total in our study, which suggests that shade stress induced systematic changes in pathways and complicated expressional regulation in plants. Of these, under prolonged shade in peanut plants, the two most important pathways, namely photosynthesis and sucrose metabolism, are commonly regulated. An existence of core regulation in light sensitivity and chloroplast metabolism was proposed in an RNA-Seq analysis of dynamic changes of gene expression under shade in
Arabidopsis [
24]. Our finding agrees with that and evidenced a core set of regulated genes in photosynthesis. Besides, we observed core set of expressional regulation in starch and sucrose metabolism under different shade treatments. The enrichment of starch and sucrose metabolism has been reported previously, but has not been investigated in depth [
24]. Observed in our study, DEGs regulation indicates that under shade a reduced hydrolysis of sucrose and starch in leaf may be caused by reduced output from the reduced photosynthesis. Together, we conclude that the core set of expressional regulation in photosynthesis and starch and sucrose metabolism could be a common mechanism of shade responses in plants. We also identified DEGs enriched in flavonoid metabolism, which plays role in defense and immunity to diseases. So, it indicates that the shade avoidance may share some common regulation mechanisms with defense and immunity to other stresses. Genes involved in anthocyanin biosynthesis and accumulation were reported to be inhibited under shade [
24]. A previous report found that dihydroflavonol 4-reductase involved in anthocyanin biosynthesis pathway was up-regulated in pine, whereas it was downregulated in spruce [
24]. Flavanone 3-hydroxylase and leucoanthocyanidin dioxygenase in anthocyanin biosynthesis were down-regulated under shade stress in conifer [
24]. Here, in peanut plants experiencing shade stress, we did not observe similar changes in these encoding genes in the flavonoid pathway. We found that two DEGs (gene id
0AN8KE and
0UU5IV) encoding isoflavone/4’-methoxyisoflavone 2’-hydroxylase were upregulated while another four DEGs (9WXZ62, IFA20P, QJ0MNA, XS7PLW) encoding the same enzyme were downregulated. Another DEG encoding 2-hydroxyisoflavanone synthase in the flavonoid biosynthesis pathway was upregulated under shade. Therefore, the regulation of flavonoid pathway under shade may be species specific. The detailed role of the expressional regulation of these DEGs under shade is still not clear although it was reported to associated with the anthocyanin biosynthesis [
53].
Currently, peanut is used in several intercropping systems with evidence of a positive effect on yield of tall crops [
7]. However, the intercropping combination is not good for peanut since we can see a high sensitivity to shade in this investigated peanut cultivar and a reduced yield of peanut seed. This suggests that breeders should pay attention to choosing an appropriate peanut variety with a higher shade tolerance than peanut cultivar Huayu 39 to avoid negative effects of shading on peanut plants.
4. Materials and Methods
4.1. Plant and Growth Condition
The experiment was conducted at South China Agricultural University (113°15′ E, 23°06′ N) Guangzhou, China during spring in 2019. The peanut cultivar Huayu 39, bred by Shandong Peanut Research Institute, was selected for its lodging resistance and its generally wide use in the actual production in China. One seed was sowed into a pot with a height of 35 cm and a diameter of 40 cm full of 35 kg soil from the 0–20 cm depth of the land surface of Guangzhou (23°09′30″ N, 113°21′52″ E).
4.2. Shade Stress Treatments
Two shadings, 40% and 80% shade, were applied for 15 and 30 days at the seedling stage, flowering stage, and both stages, respectively. The control treatment was done parallelly under natural sunlight. The other peanut plants were put into a shelter covered with different layers of black polyethylene nets, which arrowed 60% and 20% of sunlight to go through, to provide shading termed here as 40% shade and 80% shade. Other field management activities were proceeded according to local agronomic practices.
4.3. Length and Biomass Measurements
At the end of each shade treatment, three plants were collected for each treatment. The length and the number of leaves on the main stem were measured. The diameter and length of the third internode counted from the bottom in the main stem were measured. Roots, stems, and leaves were separated and dried at 105 °C for 30 min followed by 80 °C until a constant dry weight was reached. Then dry weight of roots, stems, and leaf leaves were measured.
4.4. Analyses of Photosynthesis Parameters
A portable Li-6400 (Li-COR, Lincoln, NE, USA) photosynthesis system, equipped with a red/blue LED light source, was used to measure the net photosynthetic rate, intercellular CO2 concentration, stomatal conductance, and transpiration rate of the third leaf (usually called the functional leaf in peanut plant, positioned from the top downwards) between 9:00 and 11:00 a.m. and was operated using a large volume of air with a stable CO2 pressure. All measurements were carried out at a photo flux density of 1400 μmol m−2 s−1 and an ambient CO2 concentration of 400 μmol mol−1 at 28 °C. The records were made after a stable reading was achieved. The measurement was repeated three times for each plant.
4.5. Measurement of Peanut Yield
All peanuts of each plant were harvested at 120 days for yield measurement. We randomly sampled three peanut plants to determine the number of pods per plant. All pods were removed from plants and air-dried until a constant weight was achieved. Then, the 100-pod weight was measured by measuring the weight of a random sample of 100 pods, and the 100-kernel weight in grams was calculated by for each plant.
4.6. Analysis of Plant Hormone
Peanut leaves were ground with liquid nitrogen and the homogenized material (200 mg) was added into 2 mL of extraction reagent (−4 °C), which consisted of methanol, ultrapure water, and formic acid in the proportion of 15:4:1 (
v:v:v), according to the previous method [
54]. The mixture was vigorously vortexed to obtain a homogenous solution and centrifuged for 5 min with 14000 r min
−1 at 4 °C. The collected supernatant was dried under vacuum at 35 °C and re-dissolved in 1 ml of complex solution, which consisted of methanol, water, and acetic acid in a proportion of 90:10:0.05 (
v/v/v), including 10 mmol L
−1 ammonium acetate. For selection of diagnostic precursor-to-product ion transitions, mixtures of 200 ng/mL of standard compounds dissolved in 50% MeOH with 0.1% HCO
2H were directly infused into a hybrid triple quadrupole/linear ion reap mass spectrometer (ABI 4000 Q-Traq, Applied Biosystems, Foster City, CA, USA) outfitted with an electrospray ion source using a 1 mL Hamilton syringe pump at a flow rate of 1.2 mL/h. The mixtures of standard compounds were separated by reversed-phase HPLC and analyzed by tandem mass spectrometry in the MRM mode with 20 ms dwell time, 5 ms of pause time between mass range, and 700 bms of settle time for switching polarities. In the “Enhanced Product Ion” scan mode, precursor ions were fragmented with collision energy +25 kV or −25 kV and products in the
m/
z range of 50–500 were detected.
4.7. RNA Extraction, mRNA Sequencing and Data Deposition
To measure gene regulation in response to shade treatments, RNA-Seq sequencing was used to obtain transcripts and their expression levels. Leaf samples from CK, FS40, FS80, CS40, CS80 treatments were used, and each sample from triplicate experiments was sequenced independently. Briefly, total RNAs were extracted and mRNA was enriched to construct a library for sequencing on an Illumina platform HiSeq X Ten in the paired-end 150 bp followed previous procedures [
55]. 8 G bp RNA-Seq reads were generated for each sample. For each treatment or control, three sets of RNA-Seq data were generated, one for each sample. The RNA-Seq reads were deposited and available at the database Short Read Archive at NCBI (
https://www.ncbi.nlm.nih.gov) under the master accession number of Bioproject PRJNA629665, and the accession number for each RNA-Seq data is provided in the
Supplementary File (Table S4).
4.8. Analyses of Transcript Assembly, Abundance, Gene Ontology and Pathway
All RNA-Seq reads were cleaned and mapped into tetraploid peanut
Arachis hypogaea cv. Tifrunner genome (version 2.0) [
34] and transcripts were constructed by using HiSat2 and Stringtie as described previously [
39]. The transcript level was calculated as read count and fragment per kilobase per million reads (FPKM). Differentially expressed genes were identified by using DESeq2 with cutoff great than two-fold changes and
p < 0.05. The DEG-associated gene ontologies (GOs) were enriched by using all GOs of expressed genes as background (hypergeometric,
p < 0.05). The DEG-associated pathways were analyzed with KAAS against the database KEGG (
https://www.genome.jp/kegg/) and then enriched by using the hypergeometric test (
p < 0.05) [
39,
40].
4.9. Statistical Analysis
One-way analysis of variance followed by Fisher’s least significant difference test was used to compare different treatment levels with a control for the studied physiological and phenotypic measurements. The analyses were performed with SPSS software (version 24).