BACKGROUND: 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.
BACKGROUND: 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 nematode.net [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. besseyicarbohydrate-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).
Results
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.
Annotation
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.
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 1
The classification of A. besseyi pathways.
Pathways
Members
Metabolism
121
2077
Genetic Information Processing
22
868
Environmental Information Processing
25
478
Cellular Processes
17
583
Organismal Systems
60
957
Human Diseases
61
1396
Total
306
4489
Table 2
The most common 5 A. besseyi pathways consistent with C. elegans.
Pathway
Pathway type
Unigene num
cel01100
Metabolic pathways
602
cel03010
Ribosome
119
cel04141
Protein processing in endoplasmic reticulum
118
cel00190
Oxidative phosphorylation
106
cel03013
RNA transport
99
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.
Table 3
Carbohydrate-active enzymes identified in A. besseyi.
CAZy enzyme classes
CAZy family
A. besseyi contigs
Glycoside hydrolases
10
136
Glycosyl transferases
28
328
Carbohydrate esterases
2
42
Polysaccharide lyases
0
0
Carbohydrate-binding modules
3
18
Total
43
524
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.
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.
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.
Table 4
Potential effectors identified in A. besseyi.
Effector
Function
Contigs with hit
Bit score
Best E-value
4D01
unknown
21
135
2e-32
5G05
unknown
6
175
5e-44
6F06
unknown
56
66
5e-11
Acid phosphatase
digestion
30
324
1e-88
Calreticulin
calcium signaling
24
617
e-177
Cathepsin
protein degradation
2
449
e -126
Chitinase
egg hatching
7
125
9e-29
C-type lectin
unknown
3
48
4e-05
FAR
binding of host fatty acids; reducing defense response
12
177
4e-45
Glutathione peroxidase
detoxification of ROS
10
360
e-100
PDI
protein folding
4
706
0
Putative esophageal gland cell secretory protein 3
unknown
10
135
2e-32
SXP-RAL2
unknown
2
105
1e-23
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].
Table 5
Presence of genes involved in the RNAi pathway.
Number of RNAi effector proteins
A. besseyi contigs*
A. besseyi
C. elegans
B. xylophilus
M. incognita
clade 10B
clade 9A
clade 10B
clade 12B
Small RNA biosynthesis
7
9
8
7
112
dsRNA uptake and spreading
6
11
6
4
84
AGOs and RISC
27
30
12
9
2212
RNAi inhibitors
5
10
2
2
73
Nuclear effectors
12
15
9
6
418
Total
57
75
37
28
2899
*(bitscore>40 and E-value
*(bitscore>40 and E-value
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).
Table 6
Neuropeptide genes in A. besseyi.
Neuropeptide
Genes
Contigs with hit
E-value level
Insulin-like peptides
8
25
0.003-8e-015
FMRFamide-related peptides
17
54
5e-005-6e-028
Non-insulin, non-FLP peptides
24
288
3e-005-2e-032
Total
49
367
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.
Table 7
Summary of peptidases in A. besseyi.
Catalytic types
Family number
Best E value
Aspartic
2
1.50E-106
Cysteine
19
1.60E-108
Isoleucine
6
1.10E-55
Metallo
26
1.50E-148
Serine
16
9.60E-100
Threonine
3
5.50E-202
Unassigned
1
2.10E-46
Total
73
Discussion
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 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.(DOC)Click here for additional data file.Supplementary Dataset. The comparison of unigenes with another A. besseyi transcriptome.(XLSX)Click here for additional data file.
Authors: Byung H Park; Tatiana V Karpinets; Mustafa H Syed; Michael R Leuze; Edward C Uberbacher Journal: Glycobiology Date: 2010-08-09 Impact factor: 4.313
Authors: Taisei Kikuchi; James A Cotton; Jonathan J Dalzell; Koichi Hasegawa; Natsumi Kanzaki; Paul McVeigh; Takuma Takanashi; Isheng J Tsai; Samuel A Assefa; Peter J A Cock; Thomas Dan Otto; Martin Hunt; Adam J Reid; Alejandro Sanchez-Flores; Kazuko Tsuchihara; Toshiro Yokoi; Mattias C Larsson; Johji Miwa; Aaron G Maule; Norio Sahashi; John T Jones; Matthew Berriman Journal: PLoS Pathog Date: 2011-09-01 Impact factor: 6.823