Gynophore miRNA analysis at different developmental stages in Arachis duranensis
Abstract
Peanut is one of the most important oilseed crops in the world that provides a significant amount of lipids and protein for many people. The gynophore plays an important role in gynophore development after fertilization of the peanut ovule. MicroRNAs (miRNAs) play an important role in numerous developmental and physiological plant processes. Therefore, it is essential to analyze the miRNA sequences at different gynophore stages to explore and validate gene function. Multiple small RNAs were sequenced and collected from gynophore stages A1, A2, and A3 (5, 10, and 20 days of development, respectively) for further prediction. We obtained 266 known and 357 novel miRNAs from the three different stages. Stage A3 had the largest number of reads. Genes involved in the lignin catabolic process were identified only at stage A1. The copper ion-binding process also specifically emerged at stage A1, whereas negative regulation of biological processes occurred only in stages A2 and A3. The genes related to growth were found only at stage A3, suggesting that the gynophore may contribute to rapid development of the gynophore at this stage. Our identification and assessment of miRNAs from different gynophore stages may serve as a basis for further studies of gynophore miRNA regulation mechanisms. Some biological processes were specifically regulated at different gynophore stages indicating that miRNAs play an important role in the gynophore development.
INTRODUCTION
Studies have shown that gynophore has similar absorption characteristics to roots, is sensitive to light and friction, and has geotropism. A gynophore is the stalk of certain flowers that supports the gynoecium (the ovule-producing part of a flower), elevating it above the branching points of other floral parts. Gravitropism (also known as geotropism) is a turning or growth movement by a plant or fungus in response to gravity. Various hormones have shown marked differences in accumulation and distribution during different stages of gynophore development (Moctezuma, 2003). Before enlargement of the buried peanut gynophore, auxin (IAA) and abscisic acid levels rapidly increase, and ethylene is released. In addition, rapidly decreasing content of gibberellic acid (GA) results in a significantly increased expression of the enzyme gibberellin 2-oxidase, which is negatively regulated by GA (Wang et al., 2013).
MicroRNAs (miRNA) play important roles in eukaryotes by regulating target genes. After the discovery of the first miRNA (Lee et al., 1993), a large number of miRNAs have been identified and analyzed in various animals and plants that are recorded in the miRBase database (
A shortcoming of existing studies is that high-throughput sequencing experiments have only been carried out with tetraploid-cultivated peanut (Yueyou 7 and Luhua 14). This restriction to the highly homologous tetraploid chromosomes between peanut AA and BB makes it difficult to effectively detect transcripts and to explore and validate gene function. In this study, miRNA data from different stages of gynophore development were obtained from diploid wild peanut Arachis duranensis. This information could be used to further expand the research on different developmental stages of the gynophore and effectively determine the important functional genes.
MATERIAL AND METHODS
Plant materials
Peanuts (A. duranensis) were grown in the field at Jiangsu Academy of Agricultural Sciences. Three different gynophore stages (A1: 5 days, A2: 10 days, and A3: 20 days) were collected and immediately stored in liquid nitrogen before RNA extraction. This study was approved by the Institutional Plant Care and Use Committee of Jiangsu Academy of Agricultural Sciences.
RNA extraction and high-throughput sequencing
Total RNA was obtained from the different gynophore stages (A1, A2, and A3) using Trizol agent (TaKaRa, Dalian, China), following the manufacturer instructions. Total RNA of peanut gynophores was isolated by an improved CTAB method with isopropanol instead of lithium chloride for RNA precipitation (Mi et al., 2008). Briefly, 1 g gynophore tissue was added to liquid nitrogen to obtain a fine powder. Subsequently, the powder was evenly mixed using 5 mL preheated (65°C) extraction buffer (2% CTAB, 2% PVP, 0.1 M Tris-HCl, 2.0 M NaCl, 25 mM EDTA, 2% beta-mercaptoethanol, pH 8.0). The mixture was incubated for 5 min at 65°C and shaken three times during the incubation time. After a short-time cooling, 2.5 mL isopropanol was added to the cooling mixture. After vortexing for 1 min, the mixture was centrifuged at 13,800 g for 15 min at 4°C. DNase was used to treat the extraction, and RNA was precipitated at 25°C for 10 min using 2.5 mL isopropanol. The extracted RNA was first resuspended with an equal volume of mixture (phenol:chloroform:isopropanol = 25:24:1), followed by resuspension using an equal mixture volume (chloroform:isopropanol = 24:1). Both 0.25mL 3 M NaOAC, pH 5.2, and 7.5 mL cooling ethanol were added to the mixture to precipitate the RNA overnight at -20°C. The quality of the prepared RNA from each sample was analyzed using Agilent 2100 (Agilent Technologies Co., Ltd., Palo Alto, CA, USA). The added fragmentation buffer (Ambion) was used to cut mRNA into short fragments (200-700 nt). First-strand cDNA was synthesized based on the short-fragment templates. DNA polymerase I (New England Biolabs, Beijing, China), dNTPs, RNase H (Invitrogen), and buffer were used to synthesize the second-strand cDNA. The fragments were purified using QiaQuick PCR kit and washed in EB buffer for end repair before adding polyA tails and adaptors. Fragments of suitable size were collected by agarose gel electrophoresis and amplified using polymerase chain reaction (PCR). The resulting products were sequenced by Illumina HiSeq™ 2000.
Prediction of novel miRNA
In order to predict novel gynophore miRNAs, the small RNA sequences were aligned to ESTs of peanut to collect precursor sequences. The structural features of the miRNA precursors were analyzed using the Mireap program constructed by the Beijing Genome Institute to find novel miRNA candidates. The collected structures were considered to be novel miRNA candidates when they conformed to the standard described by Allen et al. (2005). Mfold (Zuker, 2003) was used to examine the secondary structures of the collected pre-miRNA sequences. Furthermore, structures with the lowest energy were filtered for manual inspection.
Target gene prediction
The psRNATarget program (
Analysis of GO pathway
BLASTx analysis was performed using the target sequences and the NCBI database to better understand the function of the miRNA targets and the metabolic regulatory networks related to the identified peanut miRNAs. A BLASTx of the Interpro and KEGG databases was used to collect the predicted target proteins with an E value of 1e-30. The target gene function and metabolic pathway of the miRNAs were verified using the best hits. Finally, we obtained molecular function, biological process, and cellular component of the target genes from the GO and Interpro database.
Data analysis
Clean reads were filtered from the raw reads obtained after sequencing, by removing sequences containing adapters. The collected reads were used for de novo assembly, which was performed using the SOAPdenovo program. Firstly, the filtered reads with suitable overlap length were combined to form contigs. Secondly, the filtered reads were re-mapped to contigs, and then scaffolds were made. Lastly, pair-end reads were used again for gap filling to construct unigenes. To show the alternation of each DEG during the whole development stages, their fold-change data were imported into MultiExperiment Viewer (MeV v4.8,
RESULTS
Sequence analysis
In the present study, high-throughput sequencing was used to identify low-abundance candidate miRNAs in gynophores at different developmental stages. After filtering out low-quality tags, excluding adaptor/acceptor sequences, and removing contamination caused by adaptor-adaptor ligation, multiple-clean reads were obtained. All sequences were found to be small RNAs, including miRNA, noncoding RNA, tRNA, rRNA, snRNA, and snoRNA. Of the small RNAs, 70.62% were common to stages A1 and A2, whereas 16.28 and 13.10% were unique to stages A1 and A2, respectively. Furthermore, 60.45% of the small RNAs were common to stages A1 and A3, whereas 15.72 and 23.83% were unique to stages A1 and A3, respectively. Finally, 64.17% of the small RNAs were common to stages A2 and A3, 12.33% were unique to stage A2 and 23.50% were unique to stage A3 (Table 1). The numbers and kinds of small RNAs identified in the gynophore at different stages are shown in Table 1. A large number of known miRNAs were detected in all three developmental stages of the peanut gynophore. More miRNAs were found in stage A2 than in stages A1 or A3. Interestingly, stage A1 contained the most different kinds of miRNAs, whereas stage A3 had the fewest kinds of miRNAs. The length distribution of small RNAs at different stages often determines their roles in the particular stage and biogenetic machines. As shown in Figure 1, the majority of the small RNAs in the stage A1, A2, and A3 libraries were 21 nt long and accounted for 29.9, 34.0, and 32.5% of the total sequence numbers, respectively. In addition, the number of small RNAs (24 nt) from stages A1, A2, and A3 were 26.4, 22.7, and 30.4%, respectively, of the total number of RNAs. The 21 and 24 nt small RNAs were the most prevalent in the gynophore, which was consistent with the results reported for other peanut tissues (Chi et al., 2011). There were more 21 nt small RNAs than 24 nt RNAs in gynophore. Furthermore, as found in other studies (Chi et al., 2011), the high percentage of 24 nt small RNAs in the peanut gynophore could be indicative of the complexity of the peanut genome.
Total and unique gynophore stages (A1, A2, and A3).
Category | Total | Unique | ||||
---|---|---|---|---|---|---|
A1 | A2 | A3 | A1 | A2 | A3 | |
Intro sense | 524566 | 397067 | 529940 | 265675 | 205660 | 280197 |
Intro antisense | 257063 | 182697 | 295128 | 138474 | 104909 | 148491 |
Exon sense | 303767 | 303429 | 367802 | 117457 | 113322 | 118786 |
Exon antisense | 162741 | 163788 | 263940 | 73265 | 61219 | 89830 |
snoRNA | 4447 | 6665 | 5956 | 1510 | 1770 | 1836 |
snRNA | 7294 | 12175 | 10548 | 1755 | 2145 | 2381 |
Known miRNA | 1265723 | 1284734 | 1175955 | 3275 | 3159 | 2838 |
miRNA | 209469 | 269289 | 212947 | 16439 | 15729 | 15147 |
tRNA | 635578 | 480252 | 624491 | 38593 | 53824 | 57599 |
rRNA | 2275873 | 3132040 | 1874242 | 223665 | 268616 | 230163 |
rRNAetc | 92534 | 105705 | 84033 | 15719 | 14795 | 15829 |
unann | 8205594 | 7634949 | 8972250 | 3986769 | 3193330 | 4449319 |
Tag length distribution of the three different gynophore stages.

Known and novel miRNAs
There were 266 known miRNAs detected in the three different stages of the gynophore ( Cluster analysis of miRNAs from three different gynophore stages (A1, A2, and A3) of known ( Number of reads to one gene from different gynophore stages (A1, A2, and A3). The contrast between stages A1 and A2 of known (
Prediction of function
In order to fully investigate the biological functions of the known and novel miRNAs, GO analysis was used to investigate the gene ontology of all targets regulated by the miRNAs (Du et al., 2010). The terms from different stages are listed in Function of known miRNAs from different gynophore stages (A1, A2, and A3). Function of novel miRNAs from different gynophore stages (A1, A2, and A3).
DISCUSSION
Studies of miRNAs in tetraploid peanut have been reported in the past several years (Chi et al., 2011). However, no study has been carried out on diploid wild peanut, which could provide a deeper understanding of transcripts and gene functions. To date, many miRNAs in the peanut gynophore have been identified and studied using computational and direct cloning approaches (Sunkar and Jagadeeswaran, 2008; Zhao et al., 2010), but the identity and functions of most miRNAs in the gynophore are still largely unknown. After removing low-quality tags, excluding adaptor/acceptor sequences, and removing contamination formed by the adaptor-adaptor ligation, many small RNAs were obtained in the present study. In accordance with previous studies (Griffiths-Jones, 2006; Griffiths-Jones et al., 2006; Chi et al., 2011), the filtered small RNAs included miRNA, noncoding RNA, tRNA, rRNA, snRNA, and snoRNA. There were fewer miRNAs in the gynophore than in the whole plant (Zhao et al., 2010), suggesting that the gynophore only had some of the functions found in the entire peanut plant. We found that the length distributions of small RNAs in different stages of the gynophore were similar to each other. However, differences in small RNA composition often reflect specific roles in particular tissues or species. The 21 nt small RNAs detected in this study were different compared with those observed in the whole peanut plant (Chi et al., 2011), which indicates that the small RNAs might play a specific role in the gynophore tissue. In addition, the high percentage of 24 nt small RNAs could reflect the complexity of the peanut gynophore genome, because 24 nt siRNAs are known to be susceptible to heterochromatin modification, especially for a genome with a high number of repetitive sequences (Herr, 2005; Vazquez, 2006).
Evidence for the existence of 266 known miRNAs and 357 novel miRNAs in the three different gynophore development stages was identified using high-throughput Solexa technology. As shown in previous studies (Sunkar and Jagadeeswaran, 2008), most miRNAs from the gynophore are highly conserved in different plant species, indicating that ancient regulatory pathways of conserved miRNAs are present in the peanut gynophore (Li et al., 2016). miRNA members of different gynophore stages were compared with each other and great differences were found between any two stages. This suggests that the miRNAs may play different roles that are specific to the different stages. The results of the miRNA analysis indicated that different members also showed differences in expression. This was probably due to expression that was specific to different developmental stages. As with the known miRNAs, many novel miRNAs showed great differences in reads between any of two stages, which also support the notion that some miRNAs play roles that are specific to the different stages of the gynophore development. The number of reads mapped to a gene was highest at stage A3 suggesting that the functions of novel miRNAs at stage A3 may be more complex compared to those in the other two stages. The differences of novel miRNAs at the different stages may suggest specific roles related to different growth conditions, specific tissues, or different developmental stages of the gynophore.
A more accurate process of target identification is important to find and define potential functions for miRNAs in plants. The results found here indicated that some of the analyzed targets of conserved miRNAs of peanut had a conserved function with miRNA targets in Arabidopsis thaliana (Griffiths-Jones et al., 2006). The miRNA target sequences were highly conserved among a variety of wild plants, as shown by Floyd and Bowman (2004). As described in earlier reports, many of the targets in the peanut gynophore are plant-specific transcription factors. However, some targets of the novel miRNAs were found to differ from A. thaliana and Oryza sativa genes, which suggests that these targets could be regarded as peanut-specific processes (Yao et al., 2007). It will be valuable to assess the functions of these predicted target genes in the peanut gynophore.
In the present study, we used GO analysis to predict the functions of miRNAs collected by high-throughput sequencing technology. The genes involved in the lignin catabolic process were found in stage A1 but not in stages A2 and A3, which suggests that this is a stage-specific process. This process is important because lignin makes the gynophore hard enough to pierce the soil surface. In addition, copper ion binding was specifically found in stage A1, providing the precondition for the subsequent A2 and A3 gynophore stages because ions play an important role in resisting ground pathogens. At stage A3, several processes involved in energy consumption were detected, whereas no such processes were found in stages A1 or A2. This difference suggests that the biological metabolism of stage A3 is vigorous because of the increased growth rate of the gynophore. Interestingly, the genes that negatively regulate biological processes were found only in stages A2 and A3, suggesting that some biological processes may be suppressed during these stages. The genes involved in growth were found only in stage A3, indicating that the gynophore may grow rapidly in stage A3 to develop into a gynophore. Moreover, the genes of fatty acids, lipoxygenase, and FAD-binding domain-containing protein were found only in stage A3, which indicates that fatty acid accumulation and seed development are initiated at this stage (Zhao et al., 2010; Zhu et al., 2013
Cultivated peanuts that are rich in lipid and protein are globally important oilseed crops (Chen et al., 2010). In our study, we investigated miRNAs that may play an important role in regulating biological processes involved in the lipid biosynthesis. Our results suggested that the genes involved in the lignin catabolic process may be specifically regulated in stage A1 of gynophore development. The copper ion-binding process was predicted to occur at stage A1 but not at stages A2 and A3. Many genes involved in apoplast development were found only in stage A1. Ether lipid metabolism was regulated by novel miRNAs at stage A3. These results demonstrate that miRNAs at different stages may play specific roles during the gynophore development of the peanut. In addition, our quantitative analyses of key miRNAs are important for furthering our understanding of differences in the three developmental stages. Quantitative analyses and related clone detection will be the focus of further studies.
To conclude, we identified large numbers of miRNAs from three different stages of gynophore development, analyzed their expressions, and predicted the potential targets. It will be important for future studies to predict the collected miRNAs and analyze their targets, because these could provide a better understanding of the functional relationship and mechanisms of miRNAs in the regulation network.