Diversity in parasitic nematode genomes: the microRNAs of Brugia pahangi and Haemonchus contortus are largely novel
© Winter et al; licensee BioMed Central Ltd. 2012
Received: 16 September 2011
Accepted: 4 January 2012
Published: 4 January 2012
MicroRNAs (miRNAs) play key roles in regulating post-transcriptional gene expression and are essential for development in the free-living nematode Caenorhabditis elegans and in higher organisms. Whether microRNAs are involved in regulating developmental programs of parasitic nematodes is currently unknown. Here we describe the the miRNA repertoire of two important parasitic nematodes as an essential first step in addressing this question.
The small RNAs from larval and adult stages of two parasitic species, Brugia pahangi and Haemonchus contortus, were identified using deep-sequencing and bioinformatic approaches. Comparative analysis to known miRNA sequences reveals that the majority of these miRNAs are novel. Some novel miRNAs are abundantly expressed and display developmental regulation, suggesting important functional roles. Despite the lack of conservation in the miRNA repertoire, genomic positioning of certain miRNAs within or close to specific coding genes is remarkably conserved across diverse species, indicating selection for these associations. Endogenous small-interfering RNAs and Piwi-interacting (pi)RNAs, which regulate gene and transposon expression, were also identified. piRNAs are expressed in adult stage H. contortus, supporting a conserved role in germline maintenance in some parasitic nematodes.
This in-depth comparative analysis of nematode miRNAs reveals the high level of divergence across species and identifies novel sequences potentially involved in development. Expression of novel miRNAs may reflect adaptations to different environments and lifestyles. Our findings provide a detailed foundation for further study of the evolution and function of miRNAs within nematodes and for identifying potential targets for intervention.
microRNAs (miRNAs) are small, non-coding RNAs that play key roles in regulating gene expression in animals, plants and viruses. The processing of miRNAs from long primary transcripts to their mature functional form by Drosha and Dicer RNase III enzymes has been reviewed recently . The mature ~22-nucleotide single-stranded molecule is incorporated into an RNA-induced silencing complex (RISC), directing it to mRNA targets resulting in their translational repression or destabilisation . In animals, miRNA target sites most often show partial sequence complementarity and, although best characterised in 3'UTRs, can occur anywhere in the gene [3, 4]. Accumulating evidence suggests that the majority of mRNAs may be targets of miRNA regulation , providing an increased level of complexity to global gene control.
miRNAs show temporally controlled and cell-specific patterns of expression [6–8], with the first level of regulation being transcriptional. However, the importance of post-transcriptional regulation is becoming increasingly apparent . In mammals, miRNAs have been shown to regulate diverse and important processes such as B-cell differentiation , adipocyte differentiation , cardiogenesis , insulin secretion , antiviral defence , and the development of cancer [15, 16].
Genetic analysis in the free-living nematode Caenorhabditis elegans led to the discovery of the first miRNA, lin-4, which controls hypodermal cell fate decisions during early larval development [17, 18]. Similarly, C. elegans let-7 and the related miRNAs, mir-48, mir-84 and mir-241, also function to regulate the timing of developmental events [19, 20]. A cell-specific role has been defined for C. elegans lys-6 and mir-273, which act sequentially to control the laterality of chemosensory neurons [21, 22]. However, in most cases, mutation of other C. elegans miRNAs, either individually  or by combined mutation of related sequences , results in no observable effect on development or viability. Exceptions are the early lethality phenotypes resulting from both the combined loss of mir-35-mir-42 and of mir-51-mir-56, [24, 25], as well as the movement and body size defect resulting from combined mutation of mir-58, -80, -81 and -82. Importantly, miRNAs which are unrelated in sequence may function in concert as demonstrated by the phenotypes of individual miRNA mutants, which are revealed only in genetic backgrounds where miRNA levels are globally reduced . Additionally, function may only become apparent after detailed analysis, as demonstrated for C. elegans mir-1, which regulates synaptic signalling at neuromuscular junctions and influences sensitivity to levamisole .
Parasitic nematodes of medical and veterinary importance have body plans and developmental programs similar to C. elegans. Whether development of parasitic species is regulated by microRNAs, as occurs in C. elegans, is currently unknown. As an essential first step to address this question we have undertaken a comprehensive analysis of miRNAs in two parasitic nematodes: Brugia pahangi, a mosquito-borne parasite closely related to B. malayi and Wuchereria bancrofti, which are the causative agents of lymphatic filariasis, a condition affecting around 120 million people in 73 countries worldwide [28, 29]; and Haemonchus contortus, a prevalent blood-feeding gastrointestinal parasite of ruminants causing substantial losses to livestock production. H. contortus is relatively closely related to C. elegans, with both belonging to nematode clade V, while Brugia spp. (clade III) are more distantly related . Importantly, extensive genome sequence information is available for B. malayi and H. contortus, allowing identification of miRNAs by deep-sequencing and bioinformatic approaches. Here we perform a genome-wide discovery of small RNAs in B. pahangi and H. contortus and compare the repertoire of miRNAs to those in well-studied species, particularly C. elegans. Surprisingly, despite the close phylogenetic relationship, particularly between C. elegans and H. contortus, we find that the majority of miRNAs from the parasitic nematodes are novel, perhaps reflecting adaptations to parasitism.
miRNAs are members of a larger group of small silencing non-coding RNAs, including endogenous small-interfering (endo-si)RNAs and Piwi-interacting (pi)RNAs, which are classified on the basis of their biogenesis and the proteins with which they associate in the RISC complex [1, 33]. Here, our discovery of endo-siRNAs in both parasite species and piRNAs in H. contortus provides an in-depth picture of the small RNA silencing pathways operating in gene regulation and genome stability in these organisms. Identification of these molecules will facilitate detailed study of their function and may ultimately provide novel targets for parasitic nematode control.
Small RNA library sequence analysis
Summary of small RNA library sequencing
B. pahangi L3
B. pahangi adult
H. contortus L3
H. contortus adult
Unique mapped sequences
Total mapped reads
miRNA identification from sequencing data
Two miRNA prediction programs, miRDeep  and MIREAP  were used to identify miRNAs from the small RNA deep-sequencing data, both of which have been used previously for worm (nematode and platyhelminth) miRNA identification [41–43, 45]. These software utilise algorithms which score sequences on the likelihood of representing true miRNAs by folding excised genomic regions flanking mapped reads and scoring these structures based on their free-energy, similarity to miRNA hairpins, and evidence of processing by Drosha and Dicer. Neither program relies on homology to known miRNA sequences for identification thereby enabling novel miRNA discovery.
miRNA numbers discovered by deep sequencing and bioinformatic approaches
Homology-based computational miRNA discovery
Sequencing approaches to miRNA discovery can fail to identify those that are expressed either at low levels, in limited cell types or during developmental stages not sampled. A computational homology-based discovery approach was therefore employed to determine if additional miRNAs could be identified in the available B. malayi and H. contortus genome data. The mature sequences of worm miRNAs present in miRBase (release 15) were used as BLAST  queries against B. malayi and H. contortus genome sequences. The flanking genomic regions from BLAST hits were excised in two orientations and these candidate precursor sequences passed through RNAfold  and CIDmiRNA  filtering steps, followed by manual examination (using criteria described in Supplemental Methods in Additional File 1). As well as identifying 22 Brugia and 25 H. contortus miRNAs that we had already found by deep-sequencing, this bioinformatics approach identified an additional 42 Brugia and 78 H. contortus sequences. Final high confidence sets of five Brugia and 12 H. contortus sequences (Table 2 and Additional File 3) were then generated by retaining only those sequences that passed specific criteria (as described in Supplemental Methods). Therefore through the complementary discovery approaches of deep-sequencing and bioinformatics we identify a total of 132 Brugia miRNA loci encoding 104 unique mature sequences, and for H. contortus 187 loci encoding 192 unique mature sequences (Table 2). The small number of additional homology-identified miRNAs supports the efficiency of the deep-sequencing approach and also suggests that the low number of conserved miRNAs found (see below) is an accurate picture of the miRNA populations in these parasite stages.
A comparison of the Brugia miRNAs discovered here with the 32 B. malayi miRNAs identified previously  showed that all apart from mir-72, -124 and -153 were identified in our analysis. Reads identical to the mir-72 mature sequence were present in the B. pahangi L3 and adult data but were not classified as miRNA by the programs used, possibly as a result of the unusual precursor structure. mir-124 and mir-153 were not identified here as they were originally found from the sequence trace archive  with the full precursor sequences not being contained in the reference genome sequence used here. In contrast to the previous annotation for B. malayi mir-36a and Bma-mir-36b, we found the major products from these loci were derived from the opposite arms of the hairpins, which were > 4-fold more abundant and were represented by > 50,000 reads. This finding could either represent differences between Brugia species and be an example of arm switching (see later section), or represent more accurate annotation due to the depth of our sequencing data.
High abundance miRNAs
Temporal expression profiles of miRNAs
Diversity and conservation of nematode miRNAs
Importantly, comparing the full-length mature sequences (using a criteria of > 70% identity) of the Brugia and H. contortus miRNAs to all miRBase (release 15) entries, demonstrated that the majority were not conserved in other organisms. Using a combination of BLAST and SSEARCH , 42 Brugia miRNAs out of a total of 104 (40%) unique mature sequences, were conserved in other species based on our criteria. For H. contortus, 54 miRNAs out of a total of 192 (28%) unique mature sequences were conserved. The remainder for each species appeared novel. These numbers are comparable to findings from the necromenic nematode Pristionchus pacificus, the only non-Caenorhabditis nematode with a substantial set of miRNA sequences deposited in miRBase (release 15) where 33/124 (27%) were conserved in any other species .
The BLAST analysis was then used to identify the extent of miRNA conservation in other organisms (Additional File 4). Of the parasitic nematode miRNAs with homologues, several are widely conserved in diverse organisms with 20 Brugia and 18 H. contortus miRNAs being found in at least 20 species. Based on this analysis we find 15 miRNAs (seven Brugia, five H. contortus, and three shared) that are found only in nematodes and not in any other species. Additionally, re-analysing these using only a seed match to indicate conservation, confirms that at least mir-36, mir-86, mir-265 and mir-63 are found only in worms. No miRNAs were found which were shared between Brugia and H. contortus only and not in any other species. Interestingly, examination of data from Ascaris suum, recently available in miRBase release 18, revealed several miRNAs identified in our study which are also found in Ascaris but currently in no other species. These are Bpa-mir-5360, -5361, -5363, -5364, -5365a, -5365b, and -5366, and Hco-mir-5352. The greater number of miRNAs conserved between Brugia and Ascaris is consistent with their classification as clade III nematodes.
Conservation of miRNA and host gene organisation
miRNAs can be located intergenically or intragenically. The majority of C. elegans miRNAs are located intergenically with only 17% being found within protein-coding genes , whereas 40-70% of vertebrate miRNAs are intragenic [48, 55]. Examining the genomic context of the parasite miRNAs identified here in relation to annotated genes showed that, like C. elegans, the majority were intergenic, but for those that were embedded within a gene (referred to as its host gene) a clear preference for positioning within introns was evident. For Brugia, 21 miRNAs were found to be located within protein coding genes (Additional File 5). Four loci (producing three unique mature sequences) were found within exons, with two in the sense and two in the antisense orientation relative to the host gene. 17 Brugia miRNAs were intronic, with 15 in the sense and two in the antisense orientation, with the two antisense miRNAs both being part of separate bi-directional pairs, i.e. each has a paired miRNA encoded on the other strand running sense with respect to the host gene. We confirm the previously described  locations of Brugia mir-100a and -100d within an intron and exon, respectively, of the same gene, Bm1_19500 (recombination factor GdRad54, EDP35808), and the location of Brugia mir-100c within the intron of Bm1_29425 (nicalin, EDP33842.1).
The intronic-sense context of Brugia mir-50 was likewise confirmed. Interestingly, we note that C. elegans mir-50 is also located intronically in the sense orientation within an essential gene, Y71G12B.11a, and that the Brugia mir-50 host gene, Bm1_56215 (I/LWEQ domain containing protein, EDP28450), is a clear homologue of this gene. Moreover, an H. contortus mir-50 homologue was identified and, although classified as intergenic by the preliminary gene predictions used here, BLASTX analysis of ~4 kb of sequence surrounding hco-mir-50 against C. elegans proteins also provided a match to Y71G12B.11a (positive strand translation). Deeper conservation of this same miRNA/protein-coding gene organisation was also found: the D. melanogaster rhea gene (NCBI gene ID: 38978) and human talin 2 (NCBI gene ID: 83660) (which show 47% identity and 67% similarity to each other), both show 38% identity and 57% similarity at the amino acid level to the C. elegans mir-50 host gene Y71G12B.11a, and both contain mir-190 homologues (both intronic, sense) which are > 70% identical to the nematode mir-50 mature sequences. Additionally, the host gene for hco-mir-7 shows homology to D. melanogaster bancal (NCBI gene ID: 43862) (39% identity and 59% similarity) and to human heterogeneous nuclear ribonucleoprotein K (NCBI gene ID: 3190) (48% identity and 68% similarity), both of which also contain mir-7, thus indicating strong selective pressure to maintain this organisation over a large evolutionary distance.
We extended the analysis of genomic context for the Brugia data to include protein coding genes close to miRNAs. Although the average intergenic region for B. malayi is ~3.8 kb  we found 26 intergenic miRNAs positioned within 1 kb of a gene (Additional File 5). Therefore, depending on the accuracy of protein-coding gene predictions, some of these miRNAs could in fact be situated within these genes. 16 miRNAs were in the same orientation as their neighbouring gene, four were located 3' to the gene (with an average of less than 500 nucleotides between gene end and miRNA start) and 12 were located 5' (average of less than 350 intervening nucleotides). The positioning of these miRNAs relative to protein coding genes suggests that they could be transcribed as a single unit, indicating a functional significance of these linkages. In one case a very similar organisation of miRNA and protein coding gene was found to be conserved in C. elegans. Brugia-bantam is located 299 nucleotides 5' of the gene Bm1_08910 (sense orientation). The homologous C. elegans gene, T07D1.2, contains mir-81 (intron 5, antisense) and mir-82 (intron 1, sense), and the mature sequences for both show only two mismatches to bpa-bantam. Therefore, bpa-bantam appears to be homologous to Cel-mir-82 due to their mature sequence identity, conserved host gene, and similar relative positioning with respect to this gene.
Based on preliminary gene annotations, five H. contortus miRNAs were located within predicted protein coding genes, including mir-7 described above, all being within introns in the sense orientation. The lower number of miRNAs found within genes may reflect the greater genome size or the preliminary status of current gene annotations. Evolutionary conservation of mir-coding gene organisation was again demonstrated by the positioning of mir-86 within the homologous host genes in H. contortus and C. elegans (Y56A3A.7), although not in Brugia.
Although our searches of the PicTar, TargetScan and mirWIP target prediction databases provide no indication that C. elegans mir-50, -82 and -86 target their host gene (results not shown), the positional conservation of miRNA and protein coding genes described above suggests that, with the last shared common ancestor of C. elegans, H. contortus and Brugia being ~350 million years ago , there is selective pressure to maintain these genomic contexts.
Potential mechanisms for generating miRNA diversity
Novel miRNAs can arise by a number of mechanisms  including arm switching and gene duplication. We therefore examined whether these processes may contribute to miRNA diversity in Brugia and H. contortus. We find two examples in Brugia and four in H. contortus of the major mature product being generated from alternative arms of the precursor (indicated 5p and 3p) in different lifecycle stages, and one example in H. contortus of identical read numbers from both arms in the same stage. Two related novel H. contortus sequences hco-mir-5894a and hco-mir-5894b provide an example of alternative arm usage in duplicated sequences as the mature form is derived from different arms of the hairpin in each (Additional File 1, Figure S2). Changes in arm usage at different developmental times and in different tissues have been reported previously and may allow for functional evolution of miRNA loci . In addition, as previous work described a bias towards location of the mature miRNA in the 3' arm of the hairpin for three Caenorhabditis species and Pristionchus pacificus, we determined if this bias was conserved in parasitic nematodes. Although a tendency towards location to the 3' arm was found (74/134 Brugia and 121/192 H. contortus major miRNA products were located 3', a 1.2-fold and 1.7-fold increase, respectively), this was not as pronounced as described previously where a 2.1-3.3-fold increase was reported . Duplication followed by sequence divergence can give rise to new miRNA sequences and possible examples of this were also found in Brugia and H. contortus (see Supplemental Results in Additional File 1). In some instances related miRNAs were present in clusters suggesting recent duplication, as detailed below.
Using the same criteria for H. contortus, eight clusters consisting of 23 miRNA loci were identified, five of which contain conserved miRNAs (Figure 6). For every cluster all the miRNAs were orientated in the same direction, with three of these consisting of four miRNA loci, each being contained in a genomic region of < 680 nucleotides. Interestingly, mir-71 and mir-2 are found as a clustered pair in H. contortus. Functional roles have been described for Drosophila mir-2 in suppressing embryonic apoptosis  and for C. elegans mir-71 in lifespan and stress responses . Although the genomic organisation of C. elegans mir-2 and mir-71 (separated by ~7 kb) does not constitute a cluster by the criteria applied here, their relative proximity in C. elegans and tight clustering in H. contortus may suggest functional linkage of these two miRNAs.
Endo-siRNA identification from sequencing data
Sense and antisense transposons reads
Total transposon reads
B. pahangi L3
B. pahangi adult
Unlike mammals, the C. elegans endo-siRNA pathway involves primary endo-siRNAs and secondary molecules generated by RNA-dependent RNA polymerases . These secondary molecules contain 5'-triphosphate residues and, as RNA-dependent RNA polymerases are also present in B. malayi, it would seem likely that similar secondary molecules will also be produced and that many parasite endo-siRNAs could also contain these modifications. Due to the library preparation procedure used here, the libraries are likely to contain only primary endo-siRNAs. However, the major genes targeted can still be identified (Additional File 1, Tables S3C and S4C) as shown previously .
piRNA identification from sequencing data
piRNAs are critical for germline development in many species and are generated by a distinct mechanism that does not involve Dicer (the biogenesis and functions of piRNAs have been reviewed recently ). In C. elegans, piRNAs are 21 nucleotides in length, start with a uracil, and possess an upstream sequence motif (GTTTC) [34, 62]. These features have been used to identify novel piRNAs in C. elegans and P. pacificus. We therefore investigated if this process could be extended to Brugia and H. contortus. The motif was searched for in a defined region upstream from the mapped positions of all 21 U reads which had not been already assigned to another class of RNA. Table 1 shows the total number of reads corresponding to putative piRNAs identified as having an exact match in the upstream motif (full details in Additional File 8). Read numbers were < 50 for both stages of Brugia and for the L3 stage of H. contortus. However, over 1200 reads, representing 154 loci and 151 unique sequences were identified from the adult H. contortus library (Additional File 8). The percentage of loci with the motif in the same upstream location was determined for all 21 U loci and all other read loci (all non-21 U reads) and this is shown for each library in Additional File 1, Table S5. This analysis demonstrates that only in H. contortus adults are 21 U loci significantly enriched for the presence of the upstream motif (p = 0.000, Chi-square test). In C. elegans, piRNAs are most abundantly expressed in young adult worms , consistent with their roles in germline development and maintenance. Therefore, as significant numbers of 21 U reads were identified only in the adult H. contortus library, and only these loci showed specific enrichment for the presence of the conserved upstream motif, we propose that these represent genuine piRNAs. Their relatively low abundance, in comparison to miRNAs and siRNAs, is in keeping with the results of others , and consistent with the libraries being made from whole animal derived material.
Using a combination of deep sequencing and bioinformatic prediction tools we have identified and characterised small RNAs from different lifecycle stages of the parasitic nematodes Brugia and H. contortus. Comparative analysis with C. elegans small RNA data reveals several points of interest.
The majority of parasitic nematode miRNAs are novel
Many parasite miRNAs identified here were classified as species-specific, based on current sequence data, and did not have homologues in any species, including Caenorhabditis spp., which currently represent the most in-depth catalogue of nematode miRNAs. Only 42 of 104 Brugia and 54 of 192 H. contortus miRNAs were conserved in any other organism. Phylogenetic analysis groups H. contortus in the closest clade of parasitic nematodes to C. elegans. Despite this close relationship, the miRNA repertoire of H. contortus is no more similar to C. elegans than more distantly related parasitic species, including Brugia (this work) and Ascaris. This indicates that the majority of nematode miRNAs are evolutionary diverse and is consistent with comparative studies across the Metazoa showing that most clades contain unique miRNAs. These data suggest that this class of small regulatory RNAs is being continuously expanded [63, 64]
The current version of miRBase (release 18) contains 223 C. elegans miRNAs, with these data derived from detailed studies of miRNA function in the worm as well as from deep sequencing of multiple stages . Our current analysis accounts only for those miRNAs expressed in L3 and adult worms and a small number of bioinformatically predicted conserved miRNAs. It is probable that additional non-conserved miRNAs are present in the Brugia and H. contortus genomes and these will be identified by analysis of additional lifecycle stages. Although we have classified a high number of miRNAs from H. contortus and Brugia as unique, some of these may yet be identified in closely related species. Indeed, several of the miRNAs we describe as currently being found only in Brugia and Ascaris can be found by homology in the genome databases of other filarial nematodes (unpublished data). As additional data from other parasitic nematode genomes becomes available our results will aid the annotation of miRNAs and advance the understanding of nematode miRNA evolution.
An important proviso of this study was that the B. pahangi sequencing reads were, of necessity, mapped to the B. malayi genome. Thus any B. pahangi-specific sequences will not have been identified. While this explanation may account for the lower number of miRNAs found for B. pahangi compared to H. contortus, it is unlikely to fully explain the apparent expansion of miRNAs in H. contortus. In addition, homologous or heterologous probing of the B. malayi V2 gene array with B. malayi and B. pahangi cDNA showed no obvious bias towards B. malayi. An alternative explanation for the difference in number of miRNAs identified may relate to genome sizes for Brugia and H. contortus. From current sequence data, the B. malayi genome is estimated to be 90-95 Mb , similar to C. elegans (100 Mb). However, the current estimate for H. contortus is 300-500 Mb (JSG and MB, unpublished data), a more precise figure awaiting the assembly and annotation of the genome. From studies on H. contortus gene structure to date, it appears that most genes are 2-3 times the size of their orthologues in C. elegans due to the greater size and number of introns . Whether this expansion in non-coding sequence has resulted in a parallel expansion in small RNAs within the H. contortus genome remains speculative for the time being.
Understanding the functional relevance of diversity in miRNA sequences in these parasitic nematodes will require additional study; key to this will be defining their mRNA targets and demonstrating their biological relevance. As small non-coding RNAs provide a mechanism for altering levels of gene expression, their analysis may provide clues as to the evolution of parasitic life styles. The findings of this study provide the basis for further detailed analysis of miRNA expression profiles, both temporal and spatial, and of their target genes, using computational and experimental approaches. Of particular interest will be novel miRNAs that are abundantly expressed, such as bpa-mir-5364, and those with stage-restricted expression profiles, which will be relevant to understanding mechanisms of parasite development and responses to host signals.
Conservation of miRNA-host gene positioning
In the midst of such diversity, comparison of the few evolutionary conserved miRNAs identified in this study demonstrates a remarkable degree of conservation in genomic positioning of certain miRNAs. For example, the observation that mir-50 is located within a homologous gene in three different nematode species, argues strongly for the conservation of miRNA function and suggests a strong selective pressure to maintain this genomic positioning. That these partnerships have been maintained over ~350 million years of evolution adds further weight to this hypothesis. This conservation is particularly surprising as there is little conserved microsynteny between these species [31, 66, 67] and thus may indicate that the function of these miRNAs and their host genes are linked. In some cases, conservation of miRNA and host gene positioning was conserved even in higher eukaryotes, suggesting an ancient origin of such associations.
Expression of piRNAs in H. contortus
A recent study detailing small RNAs from Ascaris suggested that the piRNA pathway has been lost from this parasitic nematode . It was speculated that this may reflect adaptation to development at 37°C within a vertebrate host, altering the role of piRNAs in temperature sensitive pathways, such as germline maturation . Our identification of piRNAs in H. contortus adult worms, suggests that, at least within clade V parasitic nematodes, the potential roles of piRNAs are conserved. Absolute confirmation of these sequences as piRNAs will require further study to show their association with Piwi proteins in the relevant tissues. However, sequence comparison studies have identified the Piwi related gene, prg-1, from H. contortus and related clade V parasitic species , supporting the presence of this pathway. This provides further evidence of the diversity of small RNAs in nematodes and questions why and when the piRNA pathway has arisen. It is possible that the role of piRNAs has altered in species protected from extreme environmental conditions (the L1-L3 stage of Ascaris develops within an egg, those of Brugia within a mosquito vector, while the larval stages of H. contortus are found free within the environment), but sequence data from more species will help test such speculation.
Using deep-sequencing and homology-based bioinformatics we have carried out the first in-depth study of small regulatory RNAs in Brugia and H. contortus, and compared these to C. elegans. Our findings demonstrate that many miRNAs in both parasitic species are unique and show little overlap with those of C. elegans or any other organism. Some of these novel microRNAs are both abundantly expressed and developmentally regulated. The association of certain miRNAs within host genes is highly conserved across species indicating a functional association. siRNAs and piRNAs were also identified, the latter only in H. contortus adult stage, supporting a conserved role of piRNAs in reproduction of some parasitic nematodes. Our results highlight the evolutionary diversity in microRNA repertoire between free-living and pathogenic species, and may provide clues to the evolution of parasitic lifestyles and adaptation to different environments. The availability of genome data for additional parasitic nematode species in the next few years  will greatly improve our understanding of novel miRNAs in these organisms, their expansion/loss and potential mRNA targets.
Nematode strains and maintenance
The B. pahangi strain used in this study was derived from the original isolate reported by Buckley and Edeson . Aedes aegypti mosquitoes (refm strain) were infected with B. pahangi by membrane feeding on rabbit blood containing first stage larvae (microfilariae). L3 were isolated from mosquitoes after 10 days at 27°C. L3 were used to infect the laboratory host, the jird (Meriones unguiculatus) and adult B. pahangi worms were isolated after 3-4 months . H. contortus worms were a gift from the Moredun Research Institute (Edinburgh) and were the strain MHco3(ISE), which is used for the on-going genome sequencing project. Ensheathed L3 stage larvae were harvested from faecal cultures, while mixed sex adult worms were collected at necropsy (day 28) from Suffolk lambs (5-9 months old) infected with 5,000 L3 larvae and maintained indoors to eliminate risk of other nematode infections. All procedures were carried out in accordance with the Animal (Scientific Procedures) Act, UK.
Sources of genome assemblies and annotations
The Brugia malayi genome assembly  (Brugia _assembly.ghedin.fasta) was obtained from the Sanger Institute FTP site . B. malayi coding sequences were downloaded from NCBI  by exporting GenBank coding sequence files. The H. contortus genome data (combined_worms_supercontigs200808.fasta) was obtained from the Sanger Institute FTP site . H. contortus gene annotations were provided pre-publication from The Wellcome Trust Sanger Institute.
tRNA and rRNA sequences
The predicted locations of tRNA encoding sequences were identified from the B. malayi and H. contortus assemblies using tRNAscan-SE [74, 75]. Except where noted the default settings were used for all computer algorithms. Brugia (B. malayi and B. pahangi) and H. contortus nuclear rRNA sequences were retrieved from the NCBI nucleotide database  using the search phrases "Brugia rRNA" or "Haemonchus contortus rRNA". Additional Brugia sequences not already identified were retrieved from the SILVA database [77, 78], while the Rfam database  provided Brugia 5S and 5.8S sequences. No further H. contortus sequences were identified from either SILVA or Rfam databases. The combined sequences for each organism were compared to a list of C. elegans rRNAs derived from WormBase  which indicated that the Brugia rRNA list contained partial sequences for B. malayi 28S (AAQA01003089, ~3000 bases, ~600 bases missing at the 5' end), and 18S (AF036588, ~40 bases missing at the 5' end); B. malayi and B. pahangi sequences for full length 5.8S (with internal transcribed spacer sequences) (EU373625 and EU373655), and B. malayi and B. pahangi sequences for full length 5S rRNA (with SL1 sequences) (D87037 and D87038), as well as a number of redundant and partial sequences for all forms. The H. contortus rRNA list contained full length sequences for 28S (AM039742), 18S (L04153), 5.8S (with internal transcribed spacer sequences) (EU084689) and 5S rRNA sequences (U32122) as well as a number of redundant and partial sequences.
Small RNA library preparation and sequencing
For both organisms, small RNA libraries were constructed from two developmental stages, infective third stage larvae (L3) and mixed-sex adult worms. Total RNA was extracted by re-suspending frozen nematodes in at least six volumes of TRIzol Reagent (Invitrogen). The material was disrupted using a 3 ml glass hand-held homogeniser (Jencons) and the RNA isolated following the manufacturer's protocol. RNA integrity was determined using an Agilent 2100 Bioanalyzer and RNA Nano kit . For each library, 10 μg of total RNA was treated with 2 units of (RNase-Free) DNase I (Ambion), the reaction stopped by addition of EDTA to 5 mM, and the RNA precipitated by addition of 1/10 volume 3 M NaCl, 2.5 volumes of 100% ethanol at -80°C. A Small RNA Sample Prep kit (Illumina) was used to prepare the libraries, as described in Supplemental Methods in Additional File 1. Libraries were analysed with an Agilent 2100 Bioanalyzer and DNA 1000 kit to determine size and molarity. DNA was diluted to 4 nM for direct sequencing using an Illumina Cluster Station and 3G Genome Analyzer following the manufacturer's protocols.
Small RNA library sequence processing and miRNA identification
Two algorithms were employed to identify miRNAs from the small RNA library sequences data, miRDeep [43, 82], and MIREAP [44, 45, 83] both of which also require RNAfold (part of the Vienna RNA package) [50, 84]. Importantly, scoring by these programs takes into account that reads should map in a manner consistent with the cellular processes by which miRNAs are generated. Therefore the relative positions of putative mature and star strands within the hairpin are assessed on their similarity to that expected from the products of Drosha/Dicer processing. Illumina sequence reads were processed for input to these programs and mapped to the genome as detailed in Supplemental Methods in Additional File 1. miRDeep has been shown to perform equally well either with data filtered to remove sequences representing regions of annotated function or on unfiltered data . Unfiltered data was therefore used with both programs and miRNA predictions that overlapped with other classes of non-coding RNA subsequently removed. The prediction outputs of miRDeep and MIREAP were processed to remove any with minimum free energies (MFE) > -25 kcal/mol. The prediction sets produced from both programs were merged, then further processed to identify identical or near identical sequences mapping to different genomic locations and to find predictions common to both the L3 and adult libraries. These candidate precursors sequences were then analysed using BLASTN  against sets of tRNA and rRNA (produced as described above) and any with > 20 bases of > 93% identity removed. Brugia precursors were also analysed by BLASTN against transposable element genomic sequences (derived from co-ordinates given in the supporting online material of ) and genomic repeat element sequences (accession numbers, M12691.1, M12692.1 and M34369.1). A final high confidence set of miRNAs was then generated by i) retaining all predictions supported by at least one read corresponding to the star strand ii) predictions where no star strand was identified were retained only if the mature sequence was supported by 10 or more reads (combined from both lifecycle stages) and the precursor sequence passed the hairpin classifier CIDmiRNA [47, 85]. This algorithm was developed as a tool for ab inito miRNA identification in the human genome and has also been employed as a filtering step for miRNA identification from deep sequencing [86, 87]. It was verified as suitable for application to the parasitic nematode data by first testing it using worm (nematode and platyhelmith) precursor sequences from miRBase release 15 . From 788 sequences, three with ambiguous bases were removed and the program identified 683 of the remaining 785 (87%) as miRNA hairpins (for the test sequences Window Length lower value was set to 50 to account for the short length of some sequences). For analysis of miRNA abundance levels read counts were normalised to the total number of reads mapping for each library.
miRNA prediction by homology
All miRNA mature and star sequences reported for the following worm species: C. briggsae (cbr), C. elegans (cel), C. remanei (crm), P. pacificus (ppc), S. japonicum (sja), S. mansoni (sma) and Schmidtea mediterranea (sme), were downloaded from miRBase  release 15 . These sequences were then used to query the B. malayi and H. contortus genome assemblies using the BLASTN algorithm with parameters adjusted to account for the short query length (word size set to 7 and e-value threshold to 85). All BLAST hits were then extended to match the length and positioning of the query sequence to give hits of ~22 bases representing candidate mature sequences. For each of these, two candidate precursors were generated by extracting genomic sequences corresponding to i) 70 nucleotides upstream and 10 nucleotides downstream and, ii) 10 nucleotides upstream and 70 nucleotides downstream, with respect to the ~22 nucleotide region. Candidates were then filtered using RNAfold, CIDmiRNA and manual scoring as detailed in Supplemental Methods in Additional File 1.
miRNA families and conservation
miRNAs were identified as homologous to known miRNAs present in miRBase 15 using BLASTN (word size 7, e-value 85) to compare full-length mature sequences, allowing only sense matches and applying a 70% nucleotide identity cut-off. This process was used to assign gene names for conserved miRNA identified by deep-sequencing and to determine inter-species conservation of miRNAs. To provide additional homology assignments for gene naming, mature sequences were searched against sequences using SSEARCH  at miRBase (e-value cutoff 200) and homology assigned if a seed match and at least 16 nucleotides of identity over an 18 base region were present. All final miRNA names were assigned by miRBase.
To identify related miRNAs within each species, the complete sets of full-length mature sequences were examined using ClustalX. In addition, to identify sequences related by seed sequence (identical 5' bases 1-7 or 2-8) identity over the first 10 bases was examined. The full-length sequences for miRNAs identified using either criteria were then aligned using ClustalX and Boxshade alongside C. elegans miRNA family members where available (C. elegans families defined essentially as described previously ).
miRNA genomic context
For B. pahangi, all miRNAs were classified as exonic, intronic or intergenic (with protein coding genes within 1 kb noted) by analysing B. malayi genomic scaffold GenBank annotation files via NCBI Batch Entrez (accession numbers for miRNA scaffolds in Additional File 2) using the Vector NTi sequence analysis suite (Invitrogen). For H. contortus, genomic positioning was determined by BLAST analysis on sequence sets extracted using the annotated genome file data. For C. elegans and other species data on genomic context and miRNA clustering was derived from miRBase .
Identification of siRNAs and piRNAs from deep sequencing data
siRNAs were identified by matching library sequences to the coding sequences (Brugia) or exons (H. contortus) using BLASTN. Only sequences with perfect identity along the full length of the read sequence were retained and those already identified as miRNAs excluded. A custom Perl script was used to map the retained sequences to coding sequences/exons. To identify putative piRNAs, library sequences of 21 nucleotides in length starting with a uracil were assessed. 21 U sequences that had been previously annotated as miRNA, coding sequence/exons, rRNA or tRNA were removed (for Brugia 21 U reads that mapped to transposons were not excluded due to the potential overlap in these classes) and a custom Perl script used to extract 80 nucleotides of upstream genomic sequence. The presence of a consensus motif, GTTTC, between positions -48 and -42 of the upstream region was then determined [34, 42, 53].
The authors thank Kerry O'Neil and Margaret McFadyen for maintaining the Brugia pahangi life cycle at The University of Glasgow, Alison Donnan (Moredun Research Institute, Edinburgh) for provision of Haemonchus contortus parasites, members of the Pathogen Sequencing Unit at the Wellcome Trust Sanger Institute, Victoria Gillan (University of Glasgow) for advice on qRT-PCR, and Sam Griffiths-Jones (miRBase) for miRNA naming. The sequencing data in this study were produced by the Wellcome Trust Sanger Institute with funding from the Wellcome Trust (WT 085775/Z/08/Z). We are grateful to colleagues Dr Andrew Hamilton and Professor Andy Tait (both University of Glasgow) for critical reading of the manuscript. This work was funded by a project grant awarded to ED and CB by the Wellcome Trust (WT 086823/Z/08/Z).
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