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Transcriptomic Analysis of the Rice White Tip Nematode, Aphelenchoides besseyi (Nematoda: Aphelenchoididae)

  • Feng Wang ,

    Contributed equally to this work with: Feng Wang, Lihong Liu, Buyong Wang

    Affiliation College of Forestry, Northeast Forestry University, Harbin, Heilongjiang, China

  • Danlei Li ,

    Affiliation College of Forestry, Northeast Forestry University, Harbin, Heilongjiang, China

  • Zhiying Wang,

    Affiliation College of Forestry, Northeast Forestry University, Harbin, Heilongjiang, China

  • Airong Dong,

    Affiliation College of Forestry, Northeast Forestry University, Harbin, Heilongjiang, China

  • Lihong Liu ,

    Contributed equally to this work with: Feng Wang, Lihong Liu, Buyong Wang

    Affiliation College of Forestry, Northeast Forestry University, Harbin, Heilongjiang, China

  • Buyong Wang ,

    Contributed equally to this work with: Feng Wang, Lihong Liu, Buyong Wang

    Affiliation College of Forestry, Northeast Forestry University, Harbin, Heilongjiang, China

  • Qiaoli Chen,

    Affiliation College of Forestry, Northeast Forestry University, Harbin, Heilongjiang, China

  • Xiaohan Liu

    Affiliation College of Forestry, Northeast Forestry University, Harbin, Heilongjiang, China

Transcriptomic Analysis of the Rice White Tip Nematode, Aphelenchoides besseyi (Nematoda: Aphelenchoididae)

  • Feng Wang, 
  • Danlei Li, 
  • Zhiying Wang, 
  • Airong Dong, 
  • Lihong Liu, 
  • Buyong Wang, 
  • Qiaoli Chen, 
  • Xiaohan Liu



The rice white tip nematode Aphelenchoides besseyi, a devastating nematode whose genome has not been sequenced, is distributed widely throughout almost all the rice-growing regions of the world. The aims of the present study were to define the transcriptome of A. besseyi and to identify parasite-related, mortality-related or host resistance-overcoming genes in this nematode.

Methodology and Principal Findings

Using Solexa/Illumina sequencing, we profiled the transcriptome of mixed-stage populations of A. besseyi. A total of 51,270 transcripts without gaps were produced based on high-quality clean reads. Of all the A. besseyi transcripts, 9,132 KEGG Orthology assignments were annotated. Carbohydrate-active enzymes of glycoside hydrolases (GHs), glycosyltransferases (GTs), carbohydrate esterases (CEs) and carbohydrate-binding modules (CBMs) were identified. The presence of the A. besseyi GH45 cellulase gene was verified by in situ hybridization. Given that 13 unique A. besseyi potential effector genes were identified from 41 candidate effector homologs, further studies of these homologs are merited. Finally, comparative analyses were conducted between A. besseyi contigs and Caenorhabditis elegans genes to look for orthologs of RNAi phenotypes, neuropeptides and peptidases.

Conclusions and Significance

The present results provide comprehensive insight into the genetic makeup of A. besseyi. Many of this species' genes are parasite related, nematode mortality-related or necessary to overcome host resistance. The generated transcriptome dataset of A. besseyi reported here lays the foundation for further studies of the molecular mechanisms related to parasitism and facilitates the development of new control strategies for this species.


Parasitic nematodes that prey on plants cause devastating losses in agricultural production and contribute to a significant reduction in yield. It has been estimated that plant parasitic nematodes cause annual losses in crop production valued at US$125 billion [1]. The rice white tip nematode Aphelenchoides besseyi Christie, 1942, which is widely distributed throughout almost all the rice growing regions of the world, is considered to be a major contributor to the seed-borne pathogens of rice [2][4]. A. besseyi is a global burden, causing losses of up to 50% in upland rice in Brazil [5] and 10–50% in flooded rice in China [6].

As a seed-borne nematode, A. besseyi can survive on stored grain in anhydrobiosis for several years [7]. This species is a facultative migratory ecto- and endoparasite of the leaf or young tissue of rice, causing whitening of the top of the leaf, which later becomes necrotic, and a crinkling and distortion of the flag leaf enclosing the panicle, which then dies off and disintegrates [4], [8]. Moreover, A. besseyi is polyphagous and damages a wide range of host plants, including many important crop species, such as strawberry (Fragaria grandiflora), sweet corn (Zea mays), sweet potato (Dioscorea esculenta), bird's nest fern (Asplenium nidus) and many vegetables and grasses [9][11].

Based on its phylogenetic tree [12], A. besseyi belongs to clade 10B, whereas most other major plant-parasitic nematodes belong to clade 12. Only a high-quality draft genome sequence from Bursaphelenchus xylophilus is available for the investigation of the biological basis of clade 10 nematodes [13]. The investigation of B. xylophilus genes linked to key biological processes and parasitism will provide guidance for further studies of A. besseyi and the other clade 10 nematodes. Although the model free-living nematodes Caenorhabditis spp. (clade 9A), the human parasite Brugia malayi (clade 8B) and several plant-parasitic nematodes (clade 12) have been subjected to molecular analysis [14], very little is known about the genomic background of A. besseyi. However, recently, a fatty acid and retinoid-binding protein gene (Ab-far-1) was cloned from A. besseyi based on EST sequencing [15]. In addition, an exciting small-scale transcriptome project for A. besseyi was recently published [16], [17].

Next-generation sequencing technology, such as the Solexa/Illumina, 454 (Roche) and ABI-SOLiD platforms, has dramatically improved the efficiency of gene discovery [18]. Using next-generation sequencing technology, several nematode transcriptomes have been sequenced, including Trichuris suis, Necator americanus, B. malayi, Trichostrongylus colubriformis, Pratylenchus coffeae and P. thornei [14], [19][24]. Whereas genomic analyses of B. xylophilus reveal the genetic potential of clade 10 nematodes, transcriptomic studies of nematodes will enable the regulatory networks controlling the expression of parasitism-related genes in space and at different stages to be deciphered.

In the present study, Solexa/Illumina sequencing technology was used to explore and functionally annotate the transcriptome of a mixed-stage population of A. besseyi. The results provide insights into the genetic background of A. besseyi. The transcriptomic data presented here serve as a valuable resource that will help deepen our understanding of the parasitism of this nematode. Understanding the basic biology of plant-parasitic nematodes, especially the parasitic mechanisms at the molecular level, is essential for the development of effective control strategies.

Materials and Methods

Nematode Material

The nematode A. besseyi (NCBI BioSample accession No. SAMN02420038), derived from a single female isolated from an infected rice grain in eastern China, was maintained by serial subculture on a Botrytis cinerea mat grown on sterilized barley [25] and kept in the dark at 25°C. Nematodes freshly extracted from sterilized barley were used for RNA extraction. Eggs, juvenile stages (J2–J4) and adults were mixed together at a ratio of 1∶2∶3.

RNA Extraction, cDNA Library Construction and Illumina Sequencing

Total RNA was extracted from mixed-stage nematodes using TRIzol regent (Invitrogen, Carlsbad, CA, USA) [26] and then cleaned using an RNeasy Minikit column (Qiagen, Valencia, CA, USA) according to the manufacturers' instructions. The extracted RNA was assessed for quality and quantified using a BioPhotometer D30 (Eppendorf, Hamburg, Germany).

Two micrograms of total RNA was used to extract polyadenylated RNA and construct strand-specific RNAseq libraries according to the Illumina protocol (directional mRNASeq sample preparation part #15018460 Rev. A, October 2010; Illumina, San Diego, CA, USA) (detailed in Text S1 in File S1). The library quality was validated with a Bioanalyzer 2100 (Agilent, CA, USA). Each sample was sequenced for 80 cycles on one lane of the Illumina GAIIX platform (Illumina, San Diego, CA, USA) with a 2×100 bp module by LC Sciences (Houston, TX, USA). The dataset generated by deep-sequencing platforms was deposited in the NIH short-read archive (accession No. SRR1040470).

Data Filtering and De Novo Assembly

Low-quality reads with ambiguous sequences “N” were removed according to a sliding window method using a threshold of 35 bp. To examine the coverage of the sequences, 500,000 randomly selected reads were compared with the NT (non-redundant nucleotide sequences in the NCBI) database using BLAST, and a typical cutoff expectation value (E-value) was less than 1e-10. The trinity (trinityrnaseq_r2013-02-25) [27] and paired-end methods were used to generate non-redundant unigenes via the de novo assembly of the clean reads. The quality of the assembly was critically assessed by LC Sciences (Houston, TX, USA) before subsequent analysis.

The expression level of each transcript was measured as the number of clean reads mapped to its sequence. The mapped clean read number was normalized to RPKM (reads per kilobase of exon model per million mapped reads) with Bowtie 0.12.8 (single-end mapping) and adjusted with a normalized factor [28].

To determine how many unigenes in total were available in our transcriptome and another recently published A. besseyi transcriptome [16], we compared the unigenes with the 5,804 MIRA assembly sequences downloaded from [29] using BLASTN with an E-value cutoff of 1e-6.

Annotation and KEGG Pathway Determination

Unigene sequence directions were determined by searches against the NR (non-redundant protein sequences in the NCBI), Swiss-Prot, TrEMBL, Cdd, Pfam and KOG databases (E-value<1e-5).

KEGG mapping was used to determine the metabolic pathways of metabolism, genetic information processing, environmental information processing, cellular processes, organismal systems and etc. [30]. Sequences were submitted to the KEGG Automatic Annotation Server (KAAS) [31] to enrich the pathway annotation.

Annotation of Carbohydrate-Active Enzymes

The CAZymes Analysis Toolkit [32] was used to detect A. besseyi carbohydrate-active enzymes (CAZymes) according to a previous report [13]. Expansin-like proteins, pectinases and arabinanases were detected with a BLAST search using core modules of known protein sequences as queries. BLASTP was used to predict protein functions by searching against known protein modules and catalytic sites downloaded from NCBI's Conserved Domain Database service. Multiple sequence alignments were performed using Clustal W, and phylogenetic trees were constructed based on those sequences using the MEGA 5.05 program.

Effector Candidate Identification

Known putative effectors and selected annotated secreted protein sequences from different plant-parasitic nematodes (Aphelenchus avenae, B. mucronatus, B. xylophilus, Ditylenchus africanus, Globodera mexicana, G. pallida, G. rostochiensis, G. tabacum, Heterodera glycines, H. schachtii, M. arenaria, M. chitwoodi, M. hapla, M. incognita, M. javanica, P. coffeae, P. penetrans, Rotylenchulus reniformis, Radopholus similis and Xiphinema index) [33] were downloaded from GenBank. These sequences were searched against the A. besseyi contigs with TBLASTN to identify potential homologs [34]. An E-value cutoff of 1e-5 was used to identify significant matches. SignalP 4.1 [35] and TMHMM 2.0 [36] were used to identify secreted proteins as previously described [13].

RNAi Phenotype Matches to C. elegans Genes

Seventy-five C. elegans in vitro RNA interference (RNAi)-related genes were identified and retrieved from WormBase (version WS236). The A. besseyi contigs were compared with C. elegans genes to identify orthologs of RNAi phenotypes [37].

Neuropeptides and Peptidase Detection

One hundred thirteen C. elegans neuropeptide genes were identified and retrieved from WormBase (version WS236). The A. besseyi contigs were compared with C. elegans genes to identify orthologs with high identity to neuropeptides by BLAST.

The MEROPS database 9.8 was used to identify putative A. besseyi peptidases [38]. The candidates were derived and examined for similarity (E-value<1e-10) to MEROPS proteins.

In Situ Hybridization of GH45 Cellulases

In situ hybridization was performed on A. besseyi essentially as described by De Boer et al. [39]. A digoxigenin-labeled A. besseyi GH45 cellulase DNA probe was synthesized using the cDNA sequence following the general protocol of the Roche DIG DNA Labeling Kit (Roche, Mannheim, Germany, cat. no. 11175033910). The specificity of the probe was verified by Southern blotting. The hybridization signals were detected by incubation with the DIG High Prime DNA Labeling and Detection Starter Kit I (Roche, Mannheim, Germany, cat. no. 11745832910) and photographed under a Bx51 microscope (Olympus, Tokyo, Japan).


Illumina Sequencing and De Novo Assembly

A total of 46,826,350 raw reads were obtained by Solexa (Illumina GAIIX) RNA paired-end sequencing, and 36,905,372 high-quality clean reads were obtained after a strict filtering process. The average length of the clean reads was 89.89 bp. The ratio of clean reads was 78.81%. No RNA contamination from B. cinerea or other organisms was found based on 500,000 randomly selected reads from the NT database. Using the clean reads, Trinity produced 51,270 transcripts with length >200 bp. The average length and N50 of these transcripts were 1,241 bp and 1,857 bp, respectively. A total of 35,180 unigenes with an average length of 1,050 bp and N50 of 1,626 bp was generated after further clustering and assembly. Of these unigenes, 21,882 unigenes (62.2%) were >500 bp and 13,259 unigenes (37.7%) were >1,000 bp (Figure S1 in File S1). The frequency distribution of the GC content is shown in Figure S2 in File S1.

Recently, another A. besseyi transcriptome including 5,804 MIRA assembly sequences was published [16]. Compared with this transcriptome (detailed in the supplementary dataset in File S2), 77.8% (27,380 out of 35,180) of the unigenes in our transcriptome were unique. Only 2.2% (125 out of 5,804) of the MIRA assembly-yielded sequences were not found in our dataset (detailed in Text S2 in File S1). Because the E-value cutoff of 1e-6 was used, 7,800 (22.2% of the total 35,180) of the unigenes in our transcriptome matched 5,679 (97.8% of the total 5,804) MIRA assembly sequences. Therefore, at least 33,184 unigenes are now available in the two datasets combined.

The distribution of transcript values indicated that all transcripts were expressed, and 95.69% of the reads were mapped (Table S1 in File S1). Of the 51,270 transcripts, the RPKM values of the majority of the transcripts varied from 1 to 12 (Table S2 and Figure S3 in File S1). The distribution of RPKM values indicated that most genes were expressed at low levels.


Unigenes were determined by performing BLASTX searches against the NR protein database. A total of 17,338 orthologs were identified. Of the 35,180 unigenes, 88.03% were annotated as the most common ten organisms (Figure 1). The majority of the annotated A. besseyi (clade 10B) sequences corresponded to known nucleotide sequences of nematodes belonging to clades 2A (Trichinella spiralis), 8B (Ascaris suum, Loa loa and B. malayi), 9A (Caenorhabditis spp.) and 10B (B. xylophilus). Other protein databases, such as Swiss-Prot, TrEMBL, Cdd, Pfam and KOG, were used to annotate these unigenes (detailed in Table S3 in File S1). A search for Gene Ontology (GO) identifiers for these unique sequences was performed, and 14,064 GO terms were retrieved. The most abundant GO terms in the dataset are shown in Figure 2.

Figure 1. The ten most common NR hierarchies identified in the A. besseyi sequences.

Figure 2. The most abundant Gene Ontology terms present in the dataset for the cellular component, molecular function and biological process categories.

Pathway Determination

KAAS was used to annotate the EST sequences of the animal nematodes (B. malayi and A. suum), the free-living nematode (C. elegans), A. besseyi and other plant-parasitic nematode (B. xylophilus and M. incognita) transcripts. Of all the A. besseyi transcripts, 9,132 KEGG Orthology (KO) assignments were annotated. Two Venn diagrams were drawn to show the intersections of the nematode KO assignments (Figure 3). The diagram of C. elegans, A. besseyi and the other plant parasitic nematodes indicated 8,705 A. besseyi KO assignment hits in one or more of the nematodes, of which 427 KO assignments were unique (Figure 3A). Another diagram of C. elegans, A. besseyi and the animal-parasitic nematode A. suum also illustrates 429 unique A. besseyi KO assignments (Figure 3B).

Figure 3. The intersections of lists of nematode KEGG Orthology (KO) assignments.

A: Assignment of C. elegans, A. besseyi and other plant-parasitic nematodes. B: Assignment of C. elegans, A. besseyi and the animal-parasitic nematode A. suum. Ab: A. besseyi, Bx: B. xylophilus, Mi: M. incognita, Ce: C. elegans, Bm: B. malayi, As: A. suum.

To identify the pathways in which the unigenes participated, we mapped the A. besseyi unigenes to the canonical reference pathways in the KEGG database. A total of 9,133 unigenes were annotated based on a BLASTX search of the KEGG database; 753 enzymes and 306 KEGG pathways were predicted (Table 1, Tables S4–S8 in File S1). Of these KEGG pathways, 121 pathways were consistent with the corresponding pathways in C. elegans. In addition to the most common 5 pathways (Table 2), other important pathways, including ubiquitin-mediated proteolysis (72 members), glutathione metabolism (39 members), glycolysis/gluconeogenesis (38 members), glycerophospholipid metabolism (38 members), drug metabolism (35 members) and metabolism of xenobiotics by cytochrome (32 members), were found.

Table 2. The most common 5 A. besseyi pathways consistent with C. elegans.

CAZymes and Cell Wall Degradation

Some CAZymes are known to be secreted by sedentary as well as migratory plant parasitic nematodes and have been predicted to be involved in nematode migration in the plant and feeding from host cells [40]. According to the Carbohydrate-Active enZYmes Database, CAZymes are grouped into the following classes: glycoside hydrolases (GHs), glycosyltransferases (GTs), polysaccharide lyases (PLs), carbohydrate esterases (CEs) and carbohydrate-binding modules (CBMs) [24]. A summary of the CAZymes detected in A. besseyi is provided in Table 3. In all, 524 contigs were assigned to the following four classes of CAZymes: 136 contigs with GH domains to 10 families of GHs (Table S9 in File S1), 328 contigs to 28 families of GTs (Table S10 in File S1), 42 contigs to 2 families of CEs (Table S11 in File S1) and 18 contigs to 3 families of CBMs (Table S12 in File S1). Apparently, PLs are not present in any of the contigs in this transcriptome.

With regard to plant cell wall degradation-related CAZymes, we first noted that 4 contigs were identified as homologs of GH45 cellulases previously identified in B. xylophilus and another A. besseyi transcriptome [41]. Multiple sequence alignments of A. besseyi GH45 cellulase with B. xylophilus homologs and those of Ascomycota and Basidiomycota fungi revealed that the motifs were almost identical in all proteins (Figure 4A). The GH45 cellulase maximum likelihood tree (Figure 4B) showed four major clusters. Because no other nematode GH45 cellulases could be found, B. xylophilus and B. mucronatus were the only two plant parasitic nematodes used in the phylogenetic tree study in addition to A. besseyi.

Figure 4. Alignment and polygenetic tree of the A. besseyi GH45 cellulase amino acid sequence with its homologs identified from the NCBI database.

A: The alignment shows the comparison between A. besseyi GH45 cellulase and its homologs. Active site residues are marked with red asterisks. The GH45 cellulase consensus sequences are boxed with a red line and highlighted with a magnifying lens. Asterisks, double dots and single dots denote fully conserved, strongly conserved and weakly conserved amino acid residues, respectively. B: The maximum likelihood tree shows the relationship between A. besseyi GH45 cellulase and homologs. One thousand bootstrap replicates were performed, and the node labels represent the percentage of bootstrap support.

In situ hybridization was used to determine the tissue specificity of A. besseyi GH45 cellulase gene transcription. The anti-sense probe stained the esophageal gland cell area (Figure 5). The gland region was strongly stained by probes against the A. besseyi GH45 cellulase gene, whereas the sense probes gave no signal (Figure 5E). The A. besseyi GH45 cellulase gene was expressed at a lower level in males (Figure 5A and B) than in females (Figure 5C and D).

Figure 5. Localization of A. besseyi GH45 cellulase mRNA by in situ hybridization using digoxigenin-labeled antisense or sense probes.

A and B: Antisense probe in a male nematode. C and D: Antisense probe in a female nematode. E: Control sense probe in a female nematode. The scale bars represent 20 µm. G: esophageal glands; S: stylet; M: metacarpus.

Another plant cell wall degradation-related CAZyme family secreted by plant parasitic nematodes is GH5 cellulase, which has been well studied in the plant-parasitic nematodes of the order Tylenchida (clade 12, including most of the major plant-sedentary endoparasitic nematodes such as Meloidogyne spp., Heterodera spp. and Globodera spp. and the migratory parasitic species P. thornei and P. coffeae) [14], [24]. However, GH5 cellulases were apparently absent from the A. besseyi transcriptome. Furthermore, GH28 polygalacturonase, GH30 xylanase, GH43 arabinase, GH53 arabinogalactan galactosidase, PL3 pectate lyase and expansin-like protein were absent.

In addition to plant cell wall degradation-related CAZymes, we also noted that A. besseyi possessed GH16 and GH20 CAZymes, which may be involved in fungal cell wall degradation (Table S9 in File S1). GH16, which degrades beta-1,3-glucan, a core component of the fungal cell wall, was present in this A. besseyi transcriptome in remarkable abundance (a total of 90 contigs). In contrast, GH20, which is involved in chitin degradation, was detected in low abundance (2 contigs).

Candidate Effector Identification

Numerous effectors with various functions in the plant cell are secreted into the plant by nematodes [33]. Unlike sedentary or migratory endoparasites, A. besseyi is a migratory ecto- and endoparasite nematode that does not rely on biotrophy. Candidate A. besseyi parasitism genes and effector homologs were identified to establish the relationships between the parasite strategy and parasitism genes. All known and annotated putatively secreted proteins from plant-parasitic nematodes were compared with the A. besseyi contigs to identify possible homologs.

In addition to the CAZymes described above, 41 candidate effector homologs were identified (Table S13 in File S1). Thirteen unique A. besseyi potential effector genes were identified (Table 4) from the 41 candidate effector homologs based on the defining characteristic that effector genes that encode proteins have a putative signal peptide but lack a transmembrane helix and have an open reading frame of at least thirty amino acids after the predicted signal peptide cleavage site [42][44]. In contrast to sedentary endoparasites, no plant-hormone mimics or nodulation-related effector homologs were found in the A. besseyi transcriptome.

Because A. besseyi does not establish a long-term feeding relationship with the living cells of their hosts, it was necessary to confirm the 13 potential effectors by functional classification. Similar to B. xylophilus [13], the majority (7 out of the 13) of A. besseyi candidate effectors were also present in other migratory plant nematodes, C. elegans and even animal-parasitic nematodes. Cathepsin-like proteinases were also found in another migratory nematode, R. similis [45]. Chitinase, an egg-hatching-related protein, was found in Caenorhabditis spp. and L. loa. Glutathione peroxidase was found in Caenorhabditis spp., A. suum and Haemonchus contortus. FAR, which was also found in an A. besseyi EST project, was found in Caenorhabditis spp. and H. contortus. PDI was found in Caenorhabditis spp., B. malayi and L. loa. The other 6 effector homologs had unknown functions. Given that all the identified genes are previously assumed to be involved in the process of syncytia or giant cell formation, these findings suggest that the roles of these genes may be different in A. besseyi.

The Presence of Genes Involved in the RNAi Pathway

RNAi is an effective method for gene function identification and will facilitate the identification of potential targets for developing potent antinematodal drugs against A. besseyi. RNAi has been successfully applied in both sedentary and migratory plant-parasitic nematodes, including more than twenty plant-parasitic nematodes [46][50]. Recently, RNAi was successfully applied to A. besseyi [15].

A comparative analysis was conducted with the A. besseyi contigs and C. elegans genes to look for RNAi phenotype orthologs. The 2,899 A. besseyi contigs homologous to C. elegans matched 57 RNAi pathway effectors. The RNAi-related proteins were separated into the following five core functional groups: small RNA biosynthesis, dsRNA uptake and spreading, argonautes (AGOs) and RNA-induced silencing complex (RISC), RNAi inhibitors and nuclear effectors (Table 5 and Tables S14–S18 in File S1). Apparently, A. besseyi encodes more predicted RNAi pathway effectors than B. xylophilus [13] and M. incognita [36].

Neuropeptide Detection

Neuropeptides play important roles in the modulation of synaptic activity and the development of the nervous system and may also function as primary neurotransmitters [24], [51]. According to WormBook, 113 C. elegans neuropeptide genes, which encode over 250 distinct neuropeptides, have been identified [52].

With the sequencing of the A. besseyi transcriptome, 49 neuropeptide genes were identified (Table 6). Of these, 8 genes encode insulin-like peptides (Table S19 in File S1), 17 genes encode FMRFamide-related peptides (Table S20 in File S1) and 24 genes encode non-insulin or non-FLP peptides (Table S21 in File S1).

Peptidase Detection

The MEROPS database classifies peptidases into seven catalytic types: aspartic, glutamic, cysteine, isoleucine, metallo, serine and threonine peptidases. In our analysis, 73 peptidase genes (Table 7 and Table S22 in File S1) were identified in A. besseyi. Proteins belonging to the C01A (41 contigs), I02 (89 contigs), M12A (43 contigs) and S09X (110 contigs) families were particularly expanded in A. besseyi. Peptidase families involved in extracellular digestion and lysosomal activities were also particularly expanded.


This study provides the first detailed description of the transcriptome of A. besseyi, a rice-parasitic nematode without a sequenced genome. We detected and annotated the repertoire of candidate CAZymes in the A. besseyi transcriptome. Our dataset extends the knowledge of the arsenal of enzymes in A. besseyi. Cellulases are classified into 14 glycoside hydrolase families—GH5, 6, 7, 8, 9, 10, 12, 26, 44, 45, 48, 51, 61 and 74 [53] —most of which are typically produced by plant pathogens and plant parasites [54]. GH45 cellulases are present in Bursaphelenchus species and A. besseyi [13], [16]. The discovery of these genes led to the hypothesis that they were acquired from fungi via horizontal gene transfer (HGT) [40].

Although a GH5 cellulase was found in A. fragariae [55], no transcripts similar to GH5 cellulases were present in the A. besseyi transcriptome. To confirm this result, a TBLASTN search of A. fragariae GH5 cellulase protein sequences (NCBI accession Nos. AFD33557, AFD33558 and AFI63769) against the A. besseyi contigs was performed, but no hits were found with an E-value cutoff of 1e-4. It is worth noting that a small-scale transcriptome project for A. besseyi has been published [16]. GH45 cellulase was found in this transcriptome. However, no transcripts similar to GH5 cellulases were identified in the small-scale transcriptome. These results are consistent with our study.

In our work, a remarkable abundance of GH16 (endo-1, 3-beta-glucanase), which is thought to be important for the degradation of fungal cell walls, was detected. This enzyme has been identified in various fungivorous and plant-parasitic nematodes, first in Bursaphelenchus species [56] and more recently in A. avenae [57]. Because it is a facultative fungal feeder, it makes sense that A. besseyi harbors considerable GH16. This result supports the possibility that these fungi-consuming nematodes acquired endo-1,3-β-glucanase genes from bacteria to obtain their fungal feeding ability and subsequently acquired cellulase genes from fungi, which permitted them to parasitize plants [56], [58].

Of particular interest was the detection of candidate effector homologs such as cytokinins, ubiquitin extension protein, calreticulin, 10A06 and NULG1a [59] (Table S13 in File S1), although these genes were thought to be involved in the process of either syncytia or giant cell formation [47], [60][63]. Because A. besseyi does not generate specific feeding cells, the roles of these genes may indicate a different function. In addition, the effector identification of the small-scale transcriptome project for A. besseyi indicated that almost all (12 out of 13) of the candidate sequences had matches in Caenorhabditis elegans and in other nematodes [16]. These results suggested that whether the identified A. besseyi homologs really play the same roles as the effectors of root knot and cyst nematodes in parasitism is an open question. Obviously, further studies of these homologs are merited.

The present results provide insights into the genetic background of A. besseyi. These insights will be useful in future investigations of nematode parasitism the development of techniques for nematode control and plant protection.

Supporting Information

File S1.

Supporting Figures, Tables, and Text. Figure S1, Length distribution of All-Unigene. Figure S2, GC content frequencies distribution. Figure S3, RPKM distribution of transcript. Table S1, Expressed transcripts. Table S2, RPKM of the A. besseyi transcripts. Table S3, The annotation of A. besseyi unigenes. Table S4, Metabolism related pathways. Table S5, Genetic information processing related pathways. Table S6, Environmental information processing related pathways. Table S7, Cellular processes related pathways. Table S8, Organismal systems related pathways. Table S9, Glycoside hydrolases identified in A. besseyi. Table S10, Glycosyl transferases identified in A. besseyi. Table S11, Carbohydrate esterases identified in A. besseyi. Table S12, Carbohydrate binding modules identified in A. besseyi. Table S13, Candidate effectors or potential parasitism genes identified in A. besseyi. Table S14, Small RNA biosynthesis proteins. Table S15, dsRNA uptake and spreading effectors. Table S16, Argonautes and RNA-induced silencing complex components. Table S17, RNAi inhibitors. Table S18, Nuclear effectors. Table S19, Neuropeptide genes encoding insulin-like peptides. Table S20, Neuropeptide genes encoding FMRFamide-related peptides. Table S21, Neuropeptide genes encoding non-insulin, non-FLP peptides. Table S22, Peptidases identified in A. besseyi. Text S1, Detailed methods of RNAseq libraries construction. Text S2, MIRA assembly yielded sequences were not found in our dataset.


Files S2.

Supplementary Dataset. The comparison of unigenes with another A. besseyi transcriptome.


Author Contributions

Conceived and designed the experiments: FW DL ZW. Performed the experiments: DL FW AD. Analyzed the data: FW DL. Contributed reagents/materials/analysis tools: FW DL LL BW QC XL. Wrote the paper: FW DL QC.


  1. 1. Chitwood DJ (2003) Research on plant-parasitic nematode biology conducted by the United States Department of Agriculture-Agricultural Research Service. Pest Manage Sci 59: 748–753.
  2. 2. Fortuner R, Williams KJO (1975) Review of literature on Aphelenchoides besseyi Christie, 1942, the nematode causing “White tip” disease in rice. Helminthological abstracts Series B, Plant Nematology 44: 1–40.
  3. 3. Rajan AL, Mathur VK, Lal A (1989) Improved culturing technique for Aphelenchoides besseyi by inducing anhydrobiosis. Indian J Nematology 19: 10–13.
  4. 4. Duncan LW, Moens M (2006) Migratory endoparasitic nematodes. In: Perry RN, Moens M, editors. Plant Nematology: CABI publishing. pp. 123–152.
  5. 5. da Silva GS (1992) White tip and national rice production. Informe Agropecuario Belo Horizonte 16: 57–59.
  6. 6. Lin MS, Ding XF, Wang ZM, Hou FM, Lin N (2004) Description of Aphelenchoides besseyi from abnormal rice with ‘small grains and erect panicles’ symptom in China. Rice Science 12: 289–294.
  7. 7. Tiwari SP, Khare MN (2003) White tip caused by Aphelenchoides besseyi, an important seed borne disease of rice. In: Trivedi PC, editors. Advances in Nematology. Scientific Publishers. pp. 103–114.
  8. 8. Togashi K, Hoshino S (2001) Distribution pattern and mortality of the white tip nematode, Aphelenchoides besseyi (Nematoda: Aphelenchoididae), among rice seeds. Nematology 3: 17–24.
  9. 9. Wang KM, Tsay TT, Lin YY (1993) The occurrence of Aphelenchoides besseyi on strawberry and its ecology in Taiwan. Plant Prot Bull 35: 14–29.
  10. 10. Yu PC, Tsay TT (2004) Occurrence of a foliar nematode disease of fern in Taiwan. Plant Pathol Bull 13: 35–44.
  11. 11. Tsay TT, Cheng YH, Chen HY, Lin YY, Wu WS (1995) Occurrence and control of nematode diseases on bulbous flowers. Plant Pathol Bull 4: 180–192.
  12. 12. Van Megen H, Van den Elsen S, Holterman M, Karssen G, Mooyman P, et al. (2009) A phylogenetic tree of nematodes based on about 1200 full-length small subunit ribosomal DNA sequences. Nematology 11: 927–950.
  13. 13. Kikuchi T, Cotton JA, Dalzell JJ, Hasegawa K, Kanzaki N, et al. (2011) Genomic insights into the origin of parasitism in the emerging plant pathogen (Bursaphelenchus xylophilus). PLoS Pathog 7: e1002219.
  14. 14. Haegeman A, Joseph S, Gheysen G (2011) Analysis of the transcriptome of the root lesion nematode (Pratylenchus coffeae) generated by 454 sequencing technology. Molecular & Biochemical Parasitology 178: 7–14.
  15. 15. Cheng X, Xiang Y, Xie H, Xu CL, Xie TF, et al. (2013) Molecular Characterization and Functions of Fatty Acid and Retinoid Binding Protein Gene (Ab-far-1) in Aphelenchoides besseyi. PLoS ONE 8: e66011.
  16. 16. Kikuchi T, Cock PJA, Helder J, Jones JT (2013) Characterisation of the transcriptome of Aphelenchoides besseyi and identification of a GHF 45 cellulase. Nematology 16: 99–107.
  17. 17. Jones JT, Haegeman A, Danchin EGJ, Gaur HS, Helder J, et al. (2013) Top 10 plant-parasitic nematodes in molecular plant pathology. Molecular Plant Pathology 14: 946–961.
  18. 18. Schuster SC (2008) Next-generation sequencing transforms today's biology. Nat Methods 5: 16–18.
  19. 19. Cantacessi C, Gasser RB, Strube C, Schnieder T, Jex AR, et al. (2011) Deep insights into Dictyocaulus viviparus transcriptomes provides unique prospects for new drug targets and disease intervention. Biotechnol Adv 29: 261–271.
  20. 20. Cantacessi C, Jex AR, Hall RS, Young ND, Campbell BE, et al. (2010) A practical, bioinformatic workflow system for large data sets generated by next generation sequencing. Nucleic Acids Res 38: e171.
  21. 21. Cantacessi C, Mitreva M, Campbell BE, Hall RS, Young ND, et al. (2010) First transcriptomic analysis of the economically important parasitic nematode, Trichostrongylus colubriformis, using a next-generation sequencing approach. Infect Genet Evol 10: 1199–1207.
  22. 22. Cantacessi C, Mitreva M, Jex AR, Young ND, Campbell BE, et al. (2010) Massively parallel sequencing and analysis of the Necator americanus transcriptome. PLoS Negl Trop Dis 4: e684.
  23. 23. Choi YJ, Ghedin E, Berriman M, McQuillan J, Holroyd N, et al. (2011) A deep sequencing approach to comparatively analyze the transcriptome of lifecycle stages of the filarial worm, Brugia malayi. PLoS Negl Trop Dis 5: e1409.
  24. 24. Nicol P, Gill R, Fosu-Nyarko J, Jones MGK (2012) de novo analysis and functional classification of the transcriptome of the root lesion nematode, Pratylenchus thornei, after 454 GS FLX sequencing. International Journal for Parasitology 42: 225–237.
  25. 25. Yoshida K, Hasegawa K, Mochiji N, Miwa J (2009) Early embryogenesis and anterior-posterior axis formation in the white-tip nematode Aphelenchoides besseyi (Nematoda: Aphelenchoididae). Journal of Nematology 41: 17–22.
  26. 26. Wang F, Wang ZhY, Li DL, Chen QL (2012) Identification and characterization of a Bursaphelenchus xylophilus (Aphelenchida: Aphelenchoididae) thermotolerance-related gene: Bx-HSP90. Int J Mol Sci 13: 8819–8833.
  27. 27. Grabherr MG, Haas BJ, Yassour M, Levin JZ, Thompson DA, et al. (2011) Full-length Transcriptome assembly from RNA-Seq data without a reference genome. Nat Biotechnol 29: 644–652.
  28. 28. Mortazavi A, Williams BA, McCue K, Schaeffer L, Wold B (2008) Mapping and quantifying mammalian transcriptomes by RNA-Seq. Nat Methods 5: 621–628.
  29. 29. Martin J, Abubucker S, Heizer E, Taylor CM, Mitreva M (2012) update 2011: addition of data sets and tools featuring next-generation sequencing data. Nucleic Acids Res 40: D720–D728.
  30. 30. Kanehisa M, Goto S (2000) KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res 28: 27–30.
  31. 31. Moriya Y, Itoh M, Okuda S, Yoshizawa AC, Kaehisa M (2007) KAAS: an automatic genome annotation and pathway reconstruction server. Nucleic Acids Res 35 (suppl 2) W182–W185.
  32. 32. Park BH, Karpinets TV, Syed MH, Leuze MR, Uberbacher EC (2010) CAZymes Analysis Toolkit (CAT): Web-service for searching and analyzing carbohydrate-active enzymes in a newly sequenced organism using CAZy database. Glycobiology 20: 1574–1584.
  33. 33. Haegeman A, Mantelin S, Jones JT, Gheysen G (2012) Functional roles of effectors of plant-parasitic nematodes. Gene 492: 19–31.
  34. 34. Haegeman A, Bauters L, Kyndt T, Rahman MM, Gheysen G (2013) Identification of candidate effector genes in the transcriptome of the rice root knot nematode Meloidogyne graminicola. Molecular Plant Pathology 14: 379–390.
  35. 35. Petersen TN, Brunak S, Von Heijne G, Nielsen H (2011) SignalP 4.0: discriminating signal peptides from transmembrane regions. Nature Methods 8: 785–786.
  36. 36. Krogh A, Larsson B, Von Heijne G, Sonnhammer ELL (2001) Predicting transmembrane protein topology with a hidden markov model: application to complete genomes. J Mol Biol 305: 567–580.
  37. 37. Dalzell JJ, McVeigh P, Warnock ND, Mitreva M, Bird DM, et al. (2011) RNAi Effector Diversity in Nematodes. PLoS Negl Trop Dis 5: e1176.
  38. 38. Rawlings ND, Morton FR (2008) The MEROPS batch BLAST: a tool to detect peptidases and their non-peptidase homologues in a genome. Biochimie 90: 243–259.
  39. 39. De Boer JM, Yan Y, Smant G, Davis EL, Baum TJ (1998) In situ hybridization to messenger RNA in Heterodera glycines. J Nematol 30: 309–312.
  40. 40. Bakhetia M, Urwin PE, Atkinson HJ (2007) QPCR analysis and RNAi define pharyngeal gland cell-expressed genes of (Heterodera glycines) required for initial interactions with the host. Mol Plant-Microbe Interact 20: 306–312.
  41. 41. Kikuchi T, Jones JT, Aikawa T, Kosaka H, Ogura N (2004) A family of glycosyl hydrolase family 45 cellulases from the pine wood nematode Bursaphelenchus xylophilus. FEBS Letters 572: 201–205.
  42. 42. Davis EL, Hussey RS, Mitchum MG, Baum TJ (2008) Parasitism proteins in nematode-plant interactions. Current Opinion in Plant Biology 11: 360–366.
  43. 43. Elling AA, Mitreva M, Gai XW, Martin J, Recknor J, et al. (2009) Sequence mining and transcript profiling to explore cyst nematode parasitism. BMC Genomics 10: 58.
  44. 44. Roze E, Hanse B, Mitreva M, Vanholme B, Bakker J, et al. (2008) Mining the secretome of the root-knot nematode Meloidogyne chitwoodi for candidate parasitism genes. Molecular Plant 9: 1–10.
  45. 45. Jacob J, Mitreva M, Vanholme B, Gheysen G (2008) Exploring the transcriptome of the burrowing nematode Radopholus similis. Mol Genet Genomics 280: 1–17.
  46. 46. Rosso MN, Jones JT, Abad P (2009) RNAi and functional genomics in plant parasitic nematodes. Annu Rev Phytopathol 47: 207–232.
  47. 47. Tytgat T, Vanholme B, De Meutter J, Claeys M, Couvreur M, et al. (2004) A new class of ubiquitin extension proteins secreted by the dorsal pharyngeal gland in plant parasitic cyst nematodes. Mol Plant-Microbe Interact 17: 846–852.
  48. 48. Rosso MN, Dubrana MP, Cimbolini N, Jaubert S, Abad P (2005) Application of RNA interference to root-knot nematode genes encoding esophageal gland proteins. Mol Plant-Microbe Interact 18: 615–620.
  49. 49. Geldhof P, Visser A, Clark D, Saunders G, Britton C, et al. (2007) RNA interference in parasitic helminths: current situation, potential pitfalls and future prospects. Parasitology 134: 609–619.
  50. 50. Bakhetia M, Charlton WL, Urwin PE, McPherson MJ, Atkinson HJ (2005) RNA interference and plant parasitic nematodes. TRENDS in Plant Science 10: 362–367.
  51. 51. Li C, Nelson LS, Kim K, Nathoo A, Hart AC (1999) Neuropeptide gene families in the nematode Caenorhabditis elegans. Ann NY Acad Sci 897: 239–252.
  52. 52. Li C, Kim K (2008) WormBook. Sep 25: 1–36
  53. 53. Henrissat B (1991) A classification of glycosyl hydrolases based on amino-acid-sequence similarities. Biochem J 280: 309–316.
  54. 54. Lynd LR, Weimer PJ, Van Zyl WH, Pretorius IS (2002) Microbial cellulose utilization: fundamentals and biotechnology. Microbiol Mol Biol Rev 66: 506–577.
  55. 55. Fu Zh, Agudelo P, Wells CE (2012) Differential expression of a β-1,4-Endoglucanase induced by diet change in the foliar nematode Aphelenchoides fragariae. Phytopathology 102: 804–811.
  56. 56. Kikuchi T, Shibuya H, Jones JT (2005) Molecular and biochemical characterization of an endo-beta-1,3-glucanase from the pinewood nematode Bursaphelenchus xylophilus acquired by horizontal gene transfer from bacteria. Biochem J 389: 117–125.
  57. 57. Karim N, Jones JT, Okada H, Kikuchi T (2009) Analysis of expressed sequence tags and identification of genes encoding cell-wall-degrading enzymes from the fungivorous nematode Aphelenchus avenae. BMC Genomics 10: 525.
  58. 58. Jones JT, Furlanetto C, Kikuchi T (2005) Horizontal gene transfer from bacteria and fungi as a driving force in the evolution of plant parasitism in nematodes. Nematology 7: 641–646.
  59. 59. Lin B, Zhuo K, Wu P, Cui R, Zhang LH, et al. (2013) A novel effector protein, MJ-NULG1a, targeted to giant cell nuclei plays a role in Meloidogyne javanica parasitism. Mol Plant Microbe Interact 26: 55–66.
  60. 60. Abad P, Gouzy J, Aury JM, Castagnone-Sereno P, Danchin EGJ, et al. (2008) Genome sequence of the metazoan plant-parasitic nematode Meloidogyne incognita. Nature biotechnology 26: 909–915.
  61. 61. De Meutter J, Tytgatt T, Witters E, Gheysen G, Van Onckelen H, et al. (2003) Identification of cytokinins produced by the plant-parasitic nematodes Heterodera schachtii and Meloidogyne incognita. Molecular Plant Pathology 4: 271–277.
  62. 62. Ithal N, Recknor J, Nettleton D, Hearne L, Maier T, et al. (2007) Parallel genome-wide expression profiling of host and pathogen during soybean cyst nematode infection of soybean. Molecular Plant-Microbe Interactions 20: 293–305.
  63. 63. Hewezi T, Howe PJ, Maier TR, Hussey RS, Mitchum MG, et al. (2010) Arabidopsis spermidine synthase is targeted by an effector protein of the cyst nematode Heterodera schachtii. Plant Physiol 152: 968–984.