Identification of novel microRNAs in the Verticillium wilt-resistant upland cotton variety KV-1 by high-throughput sequencing
© He et al.; licensee Springer. 2014
Received: 6 September 2014
Accepted: 16 September 2014
Published: 27 September 2014
Plant microRNAs (miRNAs) play essential roles in the post-transcriptional regulation of gene expression during development, flowering, plant growth, metabolism, and stress responses. Verticillium wilt is one of the vascular disease in plants, which is caused by the Verticillium dahlia and leads to yellowing, wilting, lodging, damage to the vascular tissue, and death in cotton plants. Upland cotton varieties KV-1 have shown resistance to Verticillium wilt in multiple levels. However, the knowledge regarding the post-transcriptional regulation of the resistance is limited. Here two novel small RNA (sRNA) libraries were constructed from the seedlings of upland cotton variety KV-1, which is highly resistant to Verticillium wilts and inoculated with the V991 and D07038 Verticillium dahliae (V. dahliae) of different virulence strains. Thirty-seven novel miRNAs were identified after sequencing these two libraries by the Illumina Solexa system. According to sequence homology analysis, potential target genes of these miRNAs were predicted. With no more than three sequence mismatches between the novel miRNAs and the potential target mRNAs, we predicted 49 target mRNAs for 24 of the novel miRNAs.
These target mRNAs corresponded to genes were found to be involved in plant–pathogen interactions, endocytosis, the mitogen-activated protein kinase (MAPK) signaling pathway, and the biosynthesis of isoquinoline alkaloid, terpenoid backbone, primary bile acid and secondary metabolites. Our results showed that some of these miRNAs and their relative gene are involved in resistance to Verticillium wilts. The identification and characterization of miRNAs from upland cotton could help further studies on the miRNA regulatory mechanisms of resistance to Verticillium wilt.
Cotton is a fiber crop with worldwide economic importance. It is vulnerable to some diseases such as Fusarium wilt and Verticillium wilt, which caused by the phytopathogenic fungus V. dahliae Kleb and could have severe detrimental effects on the cotton in China, the Americas, and Mediterranean regions (Cai et al.2009; Gao et al.2010). The soil-borne fungal pathogen has displayed extraordinary genetic plasticity and broad-hosts rang in diverse ecological niches (Fradin & Thomma2006). They invade the vascular tissue by invading cortex of root via wounds or epidermal cells to cross the endodermis. The plant could show leaf vein browning, wilting, yellowing, vascular discoloration, defoliation and death after conidia are produced in large numbers and migrate via the xylem to the aerial part of the plants (Klosterman et al.2009; BejaranoAlcazar et al.1997). Consequently, Verticillium wilt is often referred to as the ‘cancer of cotton crops’. Therefore, the control against Verticillium wilt is necessary. However, it is also particularly difficult. The V. dahliae strains D07038 and V991 were used in this study and are moderately virulent and virulent, respectively. At the peak of infection, the defoliating type V991 strain has a disease incidence of 99.10% and a disease index of 81.98 relative to uninfected control plants (Fan & Jiang2006). The moderately toxic and defoliating wild-type D07038 strain was obtained from infected Gossypium hirsutum, plant and had a mean disease index of 46.1%.
Cotton varieties are assigned to five disease-resistance classes based on relative disease index scores. Varieties with relative disease index scores of 0.0 are designated immune (I); scores between 0.1 and 10.0 indicate high resistance (HR); varieties with scores between 10.1 and 20.0 are resistant (R); scores between 20.1 and 35.0 indicate tolerant (T) varieties; and varieties with scores greater than 35.0 are susceptible (S) (Zhang et al.2012a). The cotton variety Zhongzhimian KV-1 (KV-1) was developed at Institute of Plant Protection, Chinese Academy of Agricultural Sciences (Beijing, China) and shows stable high resistance to Verticillium wilt (Zhao et al.2009) with no significant differences between relative disease indices over three consecutive years. In this study we identify the novel miRNAs by high-throughput sequencing applying KV-1 highly resistant to Verticillium wilt.
MicroRNAs are small (~21 nt), single strain and non-coding RNAs which play key role in plant developmental and responses to stress. Precursor stem-loop secondary structures are characteristic features of miRNAs and are conserved across species (Bartel2004; Carrington & Ambros2003). miRNAs are transcribed from DNA. However, those miRNAs are not translated into protein. They regulate functions of other genes at the level of protein synthesis. To date, 4,933 miRNAs which are from 53 eudicotyledon species had been identified and submitted to miRBase (miRBase Release 20.0, http://www.mirbase.org/). A total of 78 precursors and 80 mature Gossypium hirsutum miRNAs have been deposited in miRBase. Previous studies have focused primarily on miRNA expression in ovules and during fiber development. Knowledge of miRNA regulatory mechanisms associated with G. hirsutum resistant to Verticillium wilt is very limited. The miRNAs, miR1321-1334, were predicted and identified in cotton using bioinformatics and the Solexa sequencing method (Yin et al.2012a). Identification of novel miRNAs provides us an important genomic resource to investigate of the miRNAs regulatory mechanism of the resistance to wilt disease in upland cotton.
This study aimed to identify novel miRNAs and their potential target genes, which specifically expressed in the Verticillium wilt-resistant upland cotton variety KV-1. So two independent small RNA (sRNA) libraries were constructed from whole KV-1 seedlings inoculated with the V991 and D07038 V. dahliae strains; the libraries were then sequenced using the Illumina Solexa system. Then the selected upland cotton miRNAs were confirmed by quantitative real time PCR (qRT-PCR).
The potential target genes of these novel miRNAs were predicted by transcriptome sequencing in G. hirsutum. We found some of these targets could function as new transcripts involved in plant-pathogen interactions, which will facilitate identification of candidate genes in G. hirsutum for resistance to V. dehliae.
Materials and methods
Fungal strains and inoculums preparation
The wild-type pathogenic V. dehliae V991 strain are used for inoculations, which was isolated from an infected upland cotton plant. Compared with the intermediately aggressive D07038 strain obtained from the Cotton Research Institute of the Chinese Academy of Agricultural Sciences, V991 is highly toxic, defoliant and more virulent. For conidial production, V991 and D07038 were subcultured from potato dextrose agar plates onto Czapek’s medium and incubated at 26°C for 7 days. Fungal cultures were filtered through sterile gauze to removal the mycelium. The concentrations of the conidial suspensions were counted under a microscope using a hemocytometer and adjusted to 1.0 × 107conidia/ml with sterile distilled water (Zhang et al.2012b).
Plant culture and treatment
To investigate the mechanism of disease resistance in the cotton variety Zhongzhimian KV-1, we infected seedlings with the defoliating V. dahliae strains D07038 (moderate virulence) and V991 (high virulence). Seeds were treated with 98% H2SO4 to remove the surface fuzz, and then soaked in 70% ethanol for 5 min and in 10% H2O2 for 1 h to sterilize the surface, followed by three rinses with sterile water. Surface-sterilised seeds were germinated at 26°C on plates containing sterilised water and filter paper. The seedlings were grown under supplemental light outside the laboratory for 2 days and then transferred to an autoclaved mixture of vermiculite and peat (1:1 v/v). Cotton seedlings were inoculated using a root dip method. The V. dahliae strains D07038 and V991 were cultured for 7 days and used separately to infect roots of 21-day-old seedlings, at which point the seedlings had grown one to two euphylla. Roots were infected with V. dahliae inoculums of 107 CFU/mL (10 mL) fungal suspensions and incubated for ~1–2 days at 26°C and ~80% humidity. The seedlings were treated for 24 and 48 h with D07038 as the control group or with V991 as the experimental group. Total RNAs from seedlings were harvested 24 and 48 h after inoculation and pooled in a 1:1 ratio. The whole seedling was chosen as the experimental material because the pathogenic fungus directly infects cotton roots in soil and enters the vasculature through the cortical cells, resulting in disease in the stems and leaves (Cai et al.2009).
Construction and sequencing of sRNA libraries
Two sRNA libraries were constructed using the procedure of Kwak et al. (Kwak et al.2009). Total RNA was isolated from G. hirsutum seedlings using a Plant RNA Kit (Watson Biotech, Shanghai, China) according to the manufacturer’s instructions. All the RNA samples were quantified and equalised to guarantee equal amounts of RNA from each treatment. The quality of RNA samples was evaluated using an Agilent 2100 Bioanalyzer (Agilent, Waldbronn, Germany). All the RNA samples were separated by 15% urea denaturing polyacrylamide gel electrophoresis and the 18–30 nucleotide sRNA bands were excised and extracted with 0.4 M NaCl over night at 4°C. The isolated sRNAs were converted into DNA by reverse transcription PCR (RT-PCR) after being ligated sequentially to 5′ and 3′ adapters. The DNAs were confirmed by sequencing with Solexa sequencing technology (BGI, Shenzhen, China).
Raw sequences were processed using the SOAP 2.0 software (BGI, Shenzhen, China) as reported previously (Li et al.2008). Without the vector sequences, the sequences longer than 17 nt were considered for further analyses. Excluding rRNA, scRNA, snoRNA, snRNA, tRNA and the sequences containing a polyA tail, the other sequences were compared with G. hirsutum non-coding RNA sequences in the NCBI GenBank and Rfam 10.1 databases. To identify conserved miRNAs in upland cotton, the unique small RNA sequences were selected to carry out BLASTN search in the miRBase. Conserved miRNAs require perfect match. The novel miRNAs are predicted according to the characteristic hairpin structure of microRNA precursors by the RNA-folding software Mireap (http://sourceforge.net/projects/mireap/), which could provide the information about the secondary structures, the minimum free energies and the Dicer cleavage sites of the unidentified sRNA tags. We used the G. raimondii genome sequences (ftp://ftp.ncbi.nih.gov/pub/TraceDB/gossypium_raimondii/) as an miRNA positioning reference sequence. Only mature miRNA sequences were considered, which locatein the stem region of the stem-loop structure and range between 20–22 nt as well as a minimal folding free energy index (MFEI) greater than 0.85. After the selected sequences by the Mireap were folded into the secondary structure, a novel miRNA was selected when it was at 5′end arm of the stem of a perfect stem-loop structure, and another sequence was at 3′end arm and then the small RNA was consisted as a novel miRNA from cotton.
The targets of these novel microRNAs were predicted through BLAST analysis of transcriptome sequencing data from KV-1 plants infected with V. dahliae Kleb. Target gene predictions followed the methods reported by Allen et al. (Allen et al.2005). Sequences less than 4 nt mismatches relative to the query miRNA sequences were chosen manually. We allowed one mismatch in the region complementary to nucleotide positions 2–12 of the miRNA except the mismatch at a predicted cleavage site at positions 10 or 11. We also allowed three additional mismatches between positions 12 and 22 except more than two continuous mismatches. The G:U base pair was treated as a mismatch with a value of 0.5.
Confirmation of predicted miRNAs by qRT-PCR
Primers Used in this Study
Sequence(5′ → 3′)
*V = A, G, C;
Analysis of sequences from libraries of small RNAs
Statistics of small RNA sequences from two upland cotton libraries generated from KV-1 seedlings infected with the D07038 or V991 strain
Expression levels of upland cotton miRNA families showed by Solexa sequencing
Identification of conserved miRNAs from upland cotton
We raked through sequence homology analysis for known microRNAs in the two sRNA libraries with a requirement of at least 18 nt in length with a maximum of three mismatches compared to miRNAs in miRBase17. The abundance of specific miRNAs varied greatly between different miRNA families and between members within families. The depth of sequencing in our study was successfully identified 284 significant genes out of 443 differences expressed miRNA families of conservative miRNAs (Additional file1). Among the miRNAs identified by comparing resistance to V991 and D07038 in KV-1 seedlings, 119 miRNAs were differentially up-regulated and 165 miRNAs were differentially down-regulated in cotton seedlings. As shown in Additional file1, miR156, miR2911, miR2916, and miR172 were high expression in two sRNA libraries but a few conserved miRNAs (for example, miR161, miR163, and miR416) and most of the non-conserved miRNAs were found to have either very low expression. We also found some miRNAs such as miR5266, miR2867, miR3437, miR2086, and miR5652 were expressed preferentially corresponding to resistance to Verticillium wilt in KV-1 cotton. The results indicate that the expression of miRNAs was significantly affected by infection with V. dahliae, which suggested that miRNAs could be participate in the regulation of gene expression as part of the resistance to Verticillium wilt infection in the KV-1 variety.
Identification of novel miRNAs in upland cotton
Many researchers have identified novel miRNAs in numerous plant species by high-throughput sequencing means based on small RNA. They have find sRNA to a genomic location based on genomic DNA sequences of the species to predict secondary structure characteristic of an miRNA precursor. As described by Reinhart et al. (Reinhart et al.2002), the lowest-energy structures sRNA is identified as new miRNAs. A total of 78 miRNA precursors and 80 mature miRNAs from G. hirsutum are listed in miRbase release 20 and they belong to 51 miRNA families respectively. We screened the sRNA sequences generated in this study against the Rfam database to remove all known non-coding RNAs, which including scRNA, rRNAs, snoRNAs, tRNAs, piRNA, et al. For the identification of novel cotton miRNAs using the Mireap software, we used the G. raimondii genome sequence as an miRNA positioning reference sequence. We predicted 1141 miRNA candidate genes from the two sRNA libraries.
Identified of novel miRNAs from upland cotton
Mature miRNA sequence(5′→3′)
Identification of miRNA targets in G. hirsutum
Identification of putative miRNA targets is an effective approach for identifying the functions of miRNAs. Plant miRNAs typically have higher sequence complementarity with their target mRNAs than do animal miRNAs (Wang et al.2004). We search for potential silenced target genes by the novel miRNAs isolated from cotton base on transcriptome sequencing data generated for KV-1 cotton infected with the D07038 and V991 V. dahliae strains as described in the Materials and Methods section. We were predicting 49 putative targets (Additional file4) for 24 novel microRNA candidates. No potential targets were identified for 13 of the novel miRNAs.
To have a deeper understand functions of microRNA, we subjected the identified target genes to gene ontology (GO) analysis (http://www.geneontology.org), a method for identifying relevant miRNA–gene regulatory networks based on biological processes and molecular functions (Ashburner & Bergman2005). KEGG is the major public pathway-related database (Elliott et al.2008) and it was also used to estimate the potential functions of predicted target gene candidates of the novel miRNAs. Analysis of regulatory networks and biochemical pathways help understand the biological functions of the miRNA targets. Some miRNA families had multiple target genes, which were usually different function with homologous sequences. For these target genes, binding sites of the putative miRNA were often located in the highly conserved regions. It is notable that two miRNAs, ghr-miR8156-3p and ghr-miR8170-3p, potentially target disease resistance genes such as mitogen-activated protein kinase kinase kinase 17, Nbs-lrr resistance protein, and plant viral-response family proteins. These targets include genes involved in plant–pathogen interactions, endocytosis, terpenoid backbone biosynthesis, isoquinoline alkaloid biosynthesis, primary bile acid biosynthesis, the MAPK signalling pathway, and biosynthesis of secondary metabolites. Our results may help advance understanding of the mechanism of resistance to Verticillium wilts in the upland cotton variety KV-1.
Quantitative real time-PCR and data analyses
The development of high-throughput sequencing methods have greatly accelerated the identification of miRNAs in species without or with fully sequenced genomes (Peláez et al.2012). The newly identified cotton miRNAs belonging to known miRNA families exhibited a wide range of characteristics. Previous studies have focused primarily on miRNA expression in ovules, during fiber development, and with respect to stress responses (Khan Barozai et al.2008; Pang et al.2009; Yin et al.2012b). For example, miR172, miR2948, miR2949, miR2950, miR3476, miR399, miR479, and miR827 were identified during the development of ovule and fiber in upland cotton (Pang et al.2009). In addition to miRNAs related to cotton fiber development, some miRNAs have been showed to play most vital role in response to growth stages and growth conditions. For example, ghr-miR482 regulates NBS-LRR defence genes by suppressing the miRNA-mediated gene-silencing pathway in cotton during fungal pathogen infection in cotton (Zhu et al.2013). Liu Yang also reported that bra-miR1885 the targets protein-coding disease-resistance genes of the TIR-NBS-LRR class (Yang et al.2013). 14 novel cotton miRNAs (miR1321 to miR1334) were identified from the G. barbadense L. variety ‘Hai-7124’, a Verticillium-tolerant cultivar, and the G. hirsutum L. variety ‘Yimian-11’, a Verticillium-sensitive cultivar, after roots were mock-infected and infected with Verticillium (Yin et al.2012a). There have been no reports on the potential involvement of miRNAs in mechanisms of resistance to different Verticillium wilts in upland cotton varieties. Plenty of plant miRNAs have been submitted to miRBase and their biological functions have been investigated using the Illumina Genome Analyzer. Our deep sequencing data includes conserved and novel miRNAs from upland cotton based on the G. raimondii genome sequence. We identified 443 conserved and 37 non-conserved miRNAs from our cotton sRNA data, and also analysed the miRNAs which differentially expressed against the two V. dahliae strains used. Moreover, we predicted 49 potential targets of novel miRNAs to take part in plant–pathogen interactions. Our results show that miR8163, miR8165, miR8170, miR8175, and miR8178 are involved in defence responses through relevant regulatory networks, but the underlying mechanisms remain to be elucidated. Consistent with the control group, miR8163, miR8165, miR8170 and miR8175 showed significantly low level expression in our study. Similarly, because the expression level of NBS-LRR defence genes and plant viral-response family proteins were up-regulated, we can conclude that the new miRNA may involve in the regulation of the cotton in response to Verticillium wilt. The identification of these novel microRNAs and their potential target genes improves our understanding of the mechanisms regulating defense responses. We used qRT-PCR analysis to confirm the predicted known miRNAs and found that most of the expressed miRNA shave Verticillium wilt resistance characteristics. Their specific expression could provide important information about how they function. Our future work will focus on their roles in upland KV-1 cotton resistance to Verticillium wilts. This study also provides a glimpse of the abundance and diversity of sRNAs in upland cotton.
This work was supported by grants from the National Natural Science Foundation of China (No. 31071461), Chongqing Municipal Commission of Education (No. KJ130520, KJ130502, KJ130510, and KJ050511), Natural Sciences Foundation of Chongqing (cstc2012jjA80037).
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