phylogeny of betanodaviruses and molecular evolution of their rna polymerase and coat proteins

Molecular Phylogenetics and Evolution 43 (2007) 298–308www.elsevier.com/locate/ympev

Phylogeny of betanodaviruses and molecular evolution of their RNA polymerase and coat proteins

Vania ToVolo a,1, Enrico Negrisolo b,¤,1, Chiara Maltese c, Giuseppe Bovo c, Paola Belvedere a, Lorenzo Colombo a, Luisa Dalla Valle a

a Department of Biology, University of Padova, Via U. Bassi 58/B, 35131 Padova, Italyb Department of Public Health, Comparative Pathology and Veterinary Hygiene, University of Padova, Agripolis,

Viale dell’Università 16, 35020 Legnaro, Italyc Istituto ZooproWlattico Sperimentale delle Venezie, Legnaro, Italy

Received 29 March 2006; revised 31 July 2006; accepted 1 August 2006Available online 11 August 2006

Abstract

The betanodaviruses are the causative agent of the disease viral nervous necrosis in Wshes. Betanodavirus genome consists of two sin-gle-stranded positive-sense RNA molecules (RNA1 and RNA2). RNA1 gene encodes the RNA polymerase, named also protein A, whileRNA2 encodes the coat protein precursor, the CPp protein. We investigated the evolutionary relationships among betanodaviruses work-ing on partial sequences of both RNA1 and RNA2. Phylogenetic analyses were performed by applying a maximum likelihood approach.The phylogenetic relationships among the major betanodavirus clades SJNNV-IV, TPNNV-III, BFNNV-II and RGNNV-I wereresolved diVerently in the trees obtained, respectively, from RNA1 and RNA2 multiple alignments. The alternative topologies were cor-roborated by strong bootstrap values. The molecular evolution of proteins A and CPp was also investigated. Protein A appeared to haveevolved under strong purifying selection while the CPp protein was subject to both purifying and neutral selection in diVerent amino acidresidues. Intragenic recombination in RNA1 and RNA2 genes was investigated by applying several methods and was not detected. Con-versely reassortment of RNA1 and RNA2 genes was demonstrated in some isolates. Finally RNA1 and RNA2 genes substitution rates donot follow a clock-like behavior thus impeding estimation of a possible origin time for Betanodavirus genus.© 2006 Elsevier Inc. All rights reserved.

Keywords: Fish nodavirdae; Phylogeny; Molecular evolution; RNA1 and RNA2

1. Introduction

The Nodaviridae is a family of small (25–30 nm), non-enveloped isometric RNA viruses divided in two genera:the Alphanodavirus that infects insects and the Betanodavi-rus that infects Wshes (Fauquet et al., 2005).

The betanodavirus is the causative agent of the diseaseviral nervous necrosis (VNN), an infectious neuropatho-logical condition characterized by necrosis of the centralnervous system, including brain and retina, accompanied

* Corresponding author. Fax: +39 049 8272506.E-mail address: [email protected] (E. Negrisolo).

1 These authors equally contributed to this paper.

1055-7903/$ - see front matter © 2006 Elsevier Inc. All rights reserved.doi:10.1016/j.ympev.2006.08.003

by clinical signs like abnormal swimming behavior andoften darkening of the Wsh (Bovo et al., 1999). This diseasehas, in the last few years, caused massive mortalities in lar-vae and juveniles of several marine teleost species in mostparts of the world (Munday et al., 2002). VNN worldwidedistribution has not yet fully investigated thus absence ofnodaviruses in some regions may reXect a lack of informa-tion rather than a true absence (e.g., Ucko et al., 2004).Some infected Wsh hosts are asymptomatic thus the virusdetection is impossible in absence of a thorough molecularinvestigation (Castric et al., 2001).

Similar to the insect nodaviruses, the genome of beta-nodaviruses consists of two single-stranded, positive-senseRNA molecules (RNA1 and RNA2) of about 3.0 and

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V. ToVolo et al. / Molecular Phylogenetics and Evolution 43 (2007) 298–308 299

1.4 kb in length, respectively, without poly(A) extension atthe 3� end (Delsert et al., 1997; Mori et al., 1992). RNA1encodes a non-structural protein of approximately 100 kDathe RNA-dependent RNA polymerase (RdRP) also namedprotein A, that replicates the viral genome. Whereas RNA2encodes the capsid protein precursor (CPp) of about 42kDa.

The complete nucleotide sequence of the RNA1 segmenthas earlier only been obtained for the following threebetanodaviruses: striped jack nervous necrosis virus(SJNNV) (Nagai and Nishizawa, 1999), greasy grouper ner-vous necrosis virus (GGNNV) (Tan et al., 2001) and theAtlantic halibut nodavirus (AHNV) (Sommerset andNerland, 2004).

These sequences are about 3100 bases long and containan ORF encoding 981–983 amino acids of approximately110 kDa. The sequence identities between RNA1 ofbetanodaviruses and RNA1 of insect nodaviruses are low(24–28% at the nucleotide and amino acid levels), althoughthe conserved motifs for the RdRP are located at almostthe same positions in the amino acid sequences (Nagai andNishizawa, 1999; Sommerset and Nerland, 2004).

In the insect nodaviruses, a subgenomic RNA3 is synthe-sized during RNA replication from the 3� terminus ofRNA1. The RNA3 encodes one or two small proteinsnamed B1 and B2 (Ball and Johnson, 1999). The B2 proteinof Xock house virus (FHV) has recently been identiWed as apotent RNA-silencing inhibitor that renders infected plantcells or Drosophila spp. cells less resistant to the virus (Liet al., 2002). Furthermore the B2 protein of Nodamuravirus (NoV) is an inhibitor able to block RNA interferencein mammalian cells (Sullivan and Ganem, 2005).

The subgenomic RNA3 has been found also in betan-odavirus infected cells (Delsert et al., 1997; Iwamoto et al.,2001; Sommerset and Nerland, 2004). The presence of pro-teins B1 and B2 in the Wsh nodaviruses was conWrmed bysequence analysis of GGNNV, SJNNV and AHNV RNA1(Nagai and Nishizawa, 1999; Sommerset and Nerland,2004; Tan et al., 2001). It has also been proved that RNA3acts as a transactivator in the replication of RNA2 (Eckerleand Ball, 2002; Iwamoto et al., 2005).

Betanodavirus RNA2 contains a highly conservedregion, represented by amino acids 83–216 of the CPp pro-tein of striped jack nervous necrosis virus (SJNNV), and avariable region, corresponding to the amino acids 235–315of the same protein (Nishizawa et al., 1995).

Until present paper all phylogenetic analyses dealingwith betanodaviruses were based on the nucleotidesequences of the RNA2 variable region. These analysesalways identiWed the following four main betanodavirusclades: striped jack NNV (SJNNV), tiger puVer NNV(TPNNV), barWn Xounder NNV (BFNNV), and redgrouper NNV (RGNNV) (Dalla Valle et al., 2001; Nishiz-awa et al., 1997). Recently the existence of a Wfth betanoda-virus group was suggested based on phylogenetic analysesperformed on RNA2 from turbot nodavirus (TNV)(Johansen et al., 2004b).

Thiéry et al. (2004) have proposed a diVerent nomencla-ture/classiWcation for the Betanodavirus genus. Accordingto these authors the betanodavirus isolates should beclassed within four main groups named I, II, III and IV thatcorrespond respectively to RGNNV, BFNNV, TPNNVand SJNNV types. Furthermore group I is split in two sub-groups that possibly should be considered independentgenotypes. Both classiWcations will be used in this paper.

The Betanodavirus genus is a monophyletic group wellseparated from the Alphanodavirus genus (Dalla Valle et al.,2001; Nishizawa et al., 1997; Thiéry et al., 2004). TheSJNNV and TPNNV types are sister groups, and the sameis true for BFNNV and RGNNV genotypes (Dalla Valleet al., 2001). Conversely the TNV isolate is not closelyrelated to other betanodavirus main clades (Johansen et al.,2004b).

Serological relationships among major Betanodavirusgroups have also been investigated and recognized threeserotypes: type A corresponding to SJNNV-IV genotype,type B containing TPNNV-III genotype, and type C includ-ing both BFNNV-II and RGNNV-I genotypes (Mori et al.,2003).

We were able to determine the partial RNA1 and/orRNA2 sequences of 27 betanodavirus isolates. We usedthese sequences combined with others available in Gen-Bank to determine the phylogenetic relationships amongthe main betanodavirus types by using two independentmarkers.

Moreover we investigated the evolution of the RNApolymerase and coat proteins coded by RNA1 and RNA2genes. Finally we discuss the role of some factors in the evo-lution of Betanodavirus.

2. Materials and methods

2.1. Virus isolates

The Wsh nodavirus isolates examined in this work, theirhost species, country of origin and accession numbers ofgenomic sequences available in databases are listed inTable 1.

New determined betanodavirus sequences were obtainedfrom independent isolates collected prevalently at diVerentfarms and/or time. Most of host Wsh specimens exhibitedthe typical symptoms of NNV infections (Munday et al.,2002). In the case of White bream (Diplodus sargus) andFlathead mullet (Mugil cephalus) specimens appeared sickbut did not exhibit the classical NNV symptoms. For bothspecies this is the Wrst case of recorded NNV infection.Conversely specimens of Gilthead seabream (Sparusaurata) were apparently healthy as previously know forthis species as well as for other Wshes (e.g., Castric et al.,2001; Johansen et al., 2004a; Munday et al., 2002). In allcases molecular analyses provided conWrmation of NNVpresence.

No data were collected relative to the age and size of Wshspecimens thus they cannot be provided here.

300 V. ToVolo et al. / Molecular Phylogenetics and Evolution 43 (2007) 298–308

2.2. Virus preparation and titration

Viral isolates were propagated in SSN-1 cells, (Frerichset al., 1996) grown in Eagle MEM (minimum essentialmedium) containing 10% foetal bovine serum, penicillin(100 U/ml), streptomycin (100 �g/ml), amphotericin-B(0.25 �g/ml), and 1% L-glutamine 200 mM.

Inoculated cells were incubated at 25 °C for 10 days. Cul-ture Xuids were harvested from monolayers exhibiting acytopathic eVect and clariWed by centrifugation at 3000g for

15 min at 4 °C. Aliquots of the viral suspension were storedfrozen (¡80 °C) until use.

2.3. RNA extraction and RT-PCR

The total RNA from 100 �l of either Wsh brain homoge-nates or infected cell culture suspensions was extractedusing the TRIZOL reagent, according to the manufac-turer’s instructions (Invitrogen Life Technologies, Milan,Italy). RNA samples were kept at ¡80 °C until use. For

Table 1List of isolates and accession numbers of sequences

FS, Fish status: S, Wsh specimen exhibiting symptoms of sickness; A, asymptomatic Wsh specimen; N, information not available; R, see reference listed intable. *,**, ***;****;§, §§, §§§ isolates having identical sequences. —, data not available/existing. All species if not otherwise stated were farmed.

Isolate Source of isolate (scientiWc name) FS Year Country Reference Accession number

RNA1 (RdRp) RNA2 (CPp)

Dl-I-98a Sea bass (Dicentrarchus labrax) S 1998 Italy, North-Western Adriatic Sea This report AM085311* AM085333§Em-I-01 Dusky grouper (Epinephelus

marginatus)N 2001 Italy, Central Thyrrenian Sea (wild) This report * §

14V Sea bass (Dicentrarchus labrax) N — Spain This report * §SJNag93 Striped jack (Pseudocaranx dentex) N 1993 Japan Iwamoto et al. (2000) AB056571** AB05657217-2 Sea bass (Dicentrarchus labrax) N — Spain This report ** AM088776Dl-HR-96 Sea bass (Dicentrarchus labrax) S 1996 Croatia, North-East Adriatic Sea This report AM085312*** AM085335Sa-I-97 Gilthead seabream (Sparus aurata) A 1997 Italy, North-Western Adriatic Sea This report *** AM085337Dl-HR-97 Sea bass (Dicentrarchus labrax) S 1997 Croazia, North-Eastern Adriatic Sea This report *** AM085336Dl-I-96a Sea bass (Dicentrarchus labrax) S 1996 Italy, North-Western Adriatic Sea This report AM085327 AM085342Dl-2 Sea bass (Dicentrarchus labrax) S 1998 Italy, South-Western Adriatic Sea This report and Dalla

Valle et al. (2001)AM085318 AJ277804§§

Dl-I-96b Sea bass (Dicentrarchus labrax) S 1996 Italy, North-Western Adriatic Sea This report AM085317 §§Dl-5 Sea bass (Dicentrarchus labrax) S 1995 Italy, Ligurian sea This report and Dalla

Valle et al. (2001)AM085315**** AJ277807

Dl-I-00a Sea bass (Dicentrarchus labrax) S 2000 Italy, Central-Western Adriatic Sea This report **** §§Dl-I-95 Sea bass (Dicentrarchus labrax) S 1995 Italy, South-Western Adriatic Sea This report **** §§Dl-BIH-95 Sea bass (Dicentrarchus labrax) S 1995 Bosnia Herz., Central Eastern

Adriatic SeaThis report **** §§

V26 Sea bass (Dicentrarchus labrax) N 1996 France Thièry et al., 2004 **** §§Ds-I-00 White bream (Diplodus sargus) S 2000 Italy, South Adriatic Sea This report AM085316 §§Dl-I-99 Sea bass (Dicentrarchus labrax) S 1999 Italy, Eastern Tyrrhenian sea This report AM085319 §§Mc-I-01 Flathead mullet Mugil cephalus S 2001 Italy, North-Western Adriatic Sea This report AM085320 §§Dl-I-98b Sea bass (Dicentrarchus labrax) S 1998 Italy, North-Western Adriatic Sea This report AM085321 AM085339Mb-I-00 Red mullet Mullus barbatus A 2000 Italy, North-Western Adriatic Sea This report AM085322 AM085340Sa-I-00 Gilthead seabream (Sparus aurata) A 2000 Italy, North-Western Adriatic Sea This report AM085314 AM085338Dl-I-02 Sea bass (Dicentrarchus labrax) S 2002 Italy, North-Western Adriatic Sea This report AM085328 AM085343Dl-I-98c Sea bass (Dicentrarchus labrax) S 1998 Italy, North-Western Adriatic Sea This report AM085329 AM085344Uc-1 Shi drum (Umbrina cirrosa) S 1996 Italy, North-Western Adriatic Sea This report and Dalla

Valle et al. (2001)AM085313 AJ277811

Dl-1 Sea bass (Dicentrarchus labrax) S 2000 Italy, South-Western Adriatic Sea This report and Dalla Valle et al. (2001)

AM085326 AJ277803§§§

Dl-I-00b Sea bass (Dicentrarchus labrax) S 1999 Italy, South-Western Adriatic Sea This report and Dalla Valle et al. (2001)

AM085325 §§§

Dl-HR-99 Sea bass (Dicentrarchus labrax) S 1999 Croazia, North-Eastern Adriatic Sea This report AM085324 §§§Ea-I-01 White grouper (Epinephelus aeneus) N 2001 Italy, Tyrrhenian Sea (wild) This report AM085323 AM085341GGNNV Greasy grouper Epinephelus tauvina R — Singapore Tan et al. (2001) AF319555 AF318942AH99NorA Atlantic halibut Hippoglossus

hippoglossusR 1999 Norway Sommerset and

Nerland (2004)AJ401165 —

AH95NorA Atlantic halibut Hippoglossus hippoglossus

R 1995 Norway Grotmol et al. (2000) — AJ245641

JFIwa98 Japanese Xounder (Paralichthys olivaceus)

R 1998 Japan Iwamoto et al. (2000) AM085330 AM085345

SGWak97 Sevenband grouper (Epinephelus septemfasciatus)

R 1997 Japan Iwamoto et al. (2000) AM085331 AY324870

TPKag93 Tiger puVer (Takifugu rubripes) R 1993 Japan Iwamoto et al. (2000) AM085332 D38637


cDNA synthesis and ampliWcation, we used the kit Super-Script One-Step RT-PCR System (Invitrogen, Milan, Italy).The ampliWcation of a fragment of the RNA2 was per-formed as previously described (Dalla Valle et al., 2001)except that the concentration of MgSO4 was adjusted to2 mM and the annealing temperature to 60 °C. The RT-PCR primers VNNV1 and VNNV2 (Table 2) were used toamplify the variable region of the coat protein gene (nucle-otides from 158 to 762 of the RGNNV-I type, AccessionNo. D38636) (Nishizawa et al., 1995). With two virus iso-lates (TPKag93 and Dl-HR-97) we used a modiWedVNNV2 primer (VNNV2-M, Table 2) to obtain a betterampliWcation.

To amplify and sequence conserved fragments of thepublished sequences of RdRp gene (AF319555; AJ401165and AB056571), we designed and used the primersVNNV5- VNNV8 listed in Table 2. VNNV7 and VNNV8primers were used to extend and complete the sequences onboth strands. Moreover a modiWed VNNV6 primer wasused for the TPKag93 nodavirus isolate ampliWcation(VNNV6-M). In the RdRp RT-PCR cycling conditionswere: one incubation at 54 °C for 30 min followed by 2 minat 94 °C to inactivate the reverse transcriptase; 95 °C for40 s (DNA denaturation), 60 °C for 40 s (annealing), and72 °C for 70 s (extension) for 40 cycles. The extension phaseof the last cycle was prolonged by 10 min.

The ampliWed products were analyzed for purity and sizeby electrophoresis in 1% agarose gel after staining withethidium bromide. The cDNA ampliWcates were puriWed ongel and directly sequenced in both directions using the ABIPRISM dye terminator cycle sequencing core kit (PEApplied Biosystems). Electrophoresis of sequencing reac-tions was completed in an ABI PRISM model 377, version2.1.1, automated sequencer.

2.4. Multiple alignments

Multiple alignments were generated using the ClustalWprogram (Thompson et al., 1994) by applying the defaultsettings. The amino acid multiple alignments derived fromA and CPp proteins were used as a backbone to align thecorresponding nucleotide data sets. Phylogenetic analyseswere performed on nucleotide multiple alignments, whileamino acid multiple alignments were used to identify theputative roots of nucleotide trees. Amino acid multiple

alignments included also the following insect nodavirussequences: Flock house virus (FHV) RNA1 (X77156) andRNA2 (X15959), Black beetle virus (BBV) RNA1 (X02396)and RNA2 (NC_002037). Multiple alignments are freelyavailable upon request to the corresponding author.

2.5. Composition biases and phylogenetic signal detection

Potential compositional biases in the nucleotide multiplealignments were evaluated by analyzing whole alignments,as well as Wrst, second and third positions. Departure fromhomogeneity in base composition across the taxa waschecked by applying the �2 test available in the TREE-PUZZLE 5.2 program (Schmidt et al., 2002). An a prioriestimation of the phylogenetic signal present in the multiplealignments was performed according to maximum likeli-hood mapping method (Strimmer and von Haeseler, 1997).The phylogenetic signal was estimated using the TREE-PUZZLE 5.2 program (Schmidt et al., 2002).

2.6. Trees reconstruction

Phylogenetic trees were inferred using the maximumlikelihood (ML) method (Felsenstein, 2004). The ML anal-yses were performed with the PHYML 4.4 program (Guin-don and Gascuel, 2003) by applying the GTR+I+�evolutionary model (Felsenstein, 2004).

Non-parametric bootstrap resampling (BT) (Felsenstein,2004) was performed to test the robustness of the treetopologies (1000 replicates). Trees were visualized with theNJplot program (Perrière and Gouy, 1996).

2.7. Molecular adaptation

Selective pressures acting on the nodavirus A and CPpproteins were investigated using the nonsynonymous tosynonymous substitution rate ratio � (DdN/dS). Theguidelines, provided by Yang and Bielawski (2000), werefollowed to test if positive (� > 1), neutral (�D1), or purify-ing selection (� < 1) characterized the evolution of the twoproteins. In particular the likelihood approach described byYang et al. (2000) was used. This approach implies theusage of various site-speciWc likelihood models describingthe distribution of � among sites. The M0 (one-ratio), M1(neutral), M2 (selection), M3 (discrete), M7 (�) and M8 (�

Table 2Primers used in RT-PCR analysis and sequencing

Primer Sequence Nucleotide position Accession number

VNNV1 5�-ACACTGGAGTTTGAAATTCA-3� +158! +177 D38636VNNV2 5�-GTCTTGTTGAAGTTGTCCCA-3� +762! +743 D38636VNNV2-M 5�-TTGAAGTTGTCCCAGATGCC-3� +756! +737 D38636VNNV5 5�-GTTGAGGATTATCGCCAACG-3� +178! +197 AF319555VNNV6 5�-ACCGGCGAACAGTATCTGAC-3� +1150! +1131 AF319555VNNV7 5�-CACTACCGTGTTGCTG-3� +640! +655 AF319555VNNV8 5�-CAGCAACACGGTAGTG-3� +655! +640 AF319555VNNV6-M 5�-ACCGGCGAACAGTATCTGA-3� +1150! +1132 AF319555


and �) models were applied to assess negative, positive, orneutral selection acting on each codon (Yang et al., 2000).

All parameters, required by the above mentioned mod-els, were computed with the PAML ver. 3.15 program(Yang, 2005). Multiple runs were done, starting with diVer-ent � values, to avoid trapping in ML multiple local optima(Yang, 2005). The Wtting of the diVerent models to data setswas tested by likelihood ration test (LRT). The signiWcativ-ity level of the LRT values was checked by the �2 test. Anal-yses were performed on complete RNA1 and RNA2 datasets as well as two subsets containing sequences that were atleast 1% diVerent (Anisimova et al., 2002). According toAnisimova and coworkers the presence of very similarsequences diVering for least than 1% may prevent the detec-tion of positively selected sites.

2.8. Recombination

Intragenic recombination was investigated by applyingmultiple approaches. In fact single methods may identifyfalse positive events of recombination or fail to detect theoccurrence of true recombination (Posada, 2002). We per-formed recombination analyses by applying the CHI-MAERA (Posada and Crandall, 2001), GENECONV(Padidam et al., 1999), MAXIMUM �2 (Maynard-Smith,1992), and RDP (Martin and Rybicki, 2000) algorithms asimplemented in the RDP2 program (Martin et al., 2005).

2.9. Molecular clock

Clock-like behavior of the analyzed data sets was inves-tigated using the Hy-Phy computer package (KosakovskyPond et al., 2005). Hy-Phy package implements variousmolecular models and allows to test several evolutionaryhypotheses including the existence of molecular clock. Thepresence/absence of clock-like behavior in a data set ischecked through a maximum likelihood ratio test. Bothglobal and local clocks can be tested. A detailed descriptionof all functions implemented in Hy-Phy is provided in itsmanual (Kosakovsky Pond et al., 2005).

3. Results

3.1. Sequences description and comparison

Starting data sets included RNA1 and RNA2 sequencesobtained from 35 betanodavirus isolates (Table 1). Newlydetermined RNA1 and/or RNA2 sequences for 27 isolatesformed the bulk of starting data sets. Four isolates, previ-ously characterized, were also resequenced to check theDNA stability of frozen isolates (Table 1). Most of rese-quenced data were identical to the original sequences. TheRNA2 of SJNag93 was the exception exhibiting a singlenucleotide diVerence (G vs. A). The starting data sets werecompleted with some sequences downloaded from GenBank.

RNA1 sequences span from base 121 to base 1050 of thecomplete CDS of SJNNV-IV betanodavirus RNA1

(AB025018; Nagai and Nishizawa, 1999). They cover aboutone third of the whole RNA1 ORF and encompass the N-termini portion of protein A (Johnson et al., 2001). Pair-wise comparisons identiWed 25 unique RNA1 that wereused in successive analyses. RNA2 sequences span frombase 388 to base 894 of the complete CDS of the SJNNV-IV betanodavirus RNA2 (D30814; Nishizawa et al., 1995).These sequences cover almost 50% of the RNA2 CDS andinclude also the variable region of the coded CPp protein.Pair-wise comparisons identiWed 22 nucleotide diVerentsequences of the gene RNA2 that were used in successiveanalyses.

Betanodavirus isolates exhibiting identical RNA1sequences not always shared identical RNA2 sequences andvice versa (see Table 1).

3.2. Multiple alignments description

The multiple alignment (hereafter named RNA1-ALN),including the 25 unique RNA1 sequences, is 930 positionslong and does not contain gaps. The multiple alignment(hereafter named RNA2-ALN), including 22 uniquesequences of RNA2, is 507 positions long. RNA2-ALNincorporates a gap of six positions, present in the BFNNV-II and RGNNV-I types, spanning from base 700 to base705 of the complete CDS of the SJNNV RNA2.

Both RNA1-ALN and RNA2-ALN contain at least onerepresentative isolate of the four major Wsh nodavirusclades (i.e. SJNNV-IV, TPNNV-III, BFNNV-II, andRGNNV-I).

3.3. Composition biases and phylogenetic signal detection

Compositional biases were not detected in both RNA1-ALN and RNA2-ALN whole alignments as well as in thesingle position subsets. Every analyzed sequence proved tobe homogeneous (P 7 0.1205) by applying the �2 test.

Results obtained from likelihood mapping analyses arepresented in Table 3. The phylogenetic signal is maximumwhen all positions of RNA1-ALN and RNA2-ALN datasets are considered as revealed by the best percentage offully resolved quartets. Both full length alignments presenta non-negligible percentage of fully unresolved quartets.Among single positions the second ones exhibit always thepoorest signal while third positions have the best signal inRNA1-ALN. Conversely Wrst positions show the best sig-nal in RNA2-ALN data set. In both data sets third posi-tions are not saturated thus justifying their inclusion in thesuccessive analyses.

3.4. Trees reconstruction

Preliminary phylogenetic analyses were performed onamino acid data sets of both A and CPp proteins includingalso the sequences of insects nodaviruses (data not pre-sented here). These analyses were useful to identify theplacement of the roots for trees obtained from RNA1-ALN


and RNA2-ALN (see below). Conversely it was impossibleto use Alphanodavirus nucleotide sequences due to theirvery high divergence with respect to Betanodavirussequences.

The result of the phylogenetic analysis performed onRNA1-ALN is presented in Fig. 1. The ML phylogram wasrooted according to the root placement identiWed in theprotein tree (see above). The basal nodes show a verystrong BT support. The SJNNV-IV, BFNNV-II andRGNNV-I major groups are statistically well sustained. Asister group relationship between the TPNNV-III +BFNNV-II clade and SJNNV-IV taxon is strongly favored.Most of the sequenced isolates belong to the RGNNV-Iclade. Phylogenetic relationships among RGNNV-I iso-lates receive a mixed BT support that is absent or very poorfor some closely related taxa.

Phylogenetic analysis done on RNA2-ALN provided thetree depicted in Fig. 2. The ML tree is rooted according tothe phylogram obtained from protein data. Basal nodesreceive very strong BT support as well as several othernodes. The tree topology favors a sister group relationshipbetween SJNNV-IV and TPNNV-III clades. This groupingis supported by very high BT support. Moreover a sistergroup relationship between BFNNV-II and RGNNV-Igroups is supported by the analysis on RNA2-ALN and isalso corroborated by BT support. Both results stronglycontrast with tree obtained from RNA1-ALN.

Finally the phylogenetic position of Dl-HR-96 and Dl-I-96b isolates is markedly diVerent than that observed on theRNA1-ALN tree. The above mentioned isolates areincluded within the SJNNV-IV in the RNA1 tree while theyare nested in the RGNNV-I clade and contained in twoseparate groups in the analysis performed on RNA2-ALN.

3.5. Molecular adaptation

Results of parameters estimation for the site-speciWcmodels applied to A and CPp proteins are presented inTable 4. Inclusion/exclusion of sequences diVerent less than1% did not provide diVerent results thus we present here

Table 3Likelihood mapping results for RNA1 and RNA2 multiple alignments

a Number of quartets D 10,000.b number of quartets D 7315 (all possible). LNG, length of alignment;

QFR, quartets fully resolved; QPU, quartets partly unresolved; QFU,quartets fully unresolved; P1, P2, and P3, Wrst, second, and third codonpositions. Values are expressed in percent.

Data set LNG QFR QPU QFUa RNA1 ¡ LP1+P2+P3 930 79.86 3.44 16.70a RNA1 ¡ LP1+P2 620 69.07 5.35 25.58a RNA1 ¡ LP1 310 65.08 4.94 29.98a RNA1 ¡ LP2 310 25.61 0.00 74.39a RNA1 ¡ P3 310 73.29 8.36 18.35b RNA2 ¡ P1+P2+P3 507 87.40 2.76 9.84b RNA2 ¡ P1+P2 338 78.39 2.42 19.19b RNA2 ¡ P1 169 76.83 3.72 19.45b RNA2 ¡ P2 169 61.76 2.79 35.45b RNA2 ¡ P3 169 74.29 6.38 19.33

data obtained from the complete RNA1-ALN and RNA2-ALN multiple alignments.

A brief description of the evolutionary models (i.e. M0,M1, M2, M3, M7 and M8) used to investigate the molecularadaptation is provided below. The one ratio model (M0)assumes the same � ratio for all sites. Model M1 (neutral)assumes two site classes in the sequence: the conserved siteswith �0D0 and the neutral sites with �1D1. This model hasthe same number of parameters as M0 (one-ratio). ModelM2 (selection) adds another site class to M1 (neutral), with afree � ratio estimated from the data, thus allowing for thepossibility of positive selection. Model M3 (discrete)assumes three site classes with the proportions (p0, p1, p2)and � ratios (�0, �1, �2) estimated from the data. M7 (�)speciWes that individual codons take 1 of 10 categories of �,all estimated from the data but where no category has �> 1so that the model allows only neutral evolution. The M8model, however, allows positive selection by specifying an11th category of codons in which � can exceed 1.

The one ratio model M0 applied to RNA1-ALN (lnLD¡3379.121995) favors the presence of strong purifyingselection (�D0.0418). Model M1 (ln LD¡3424.355097) Wts

Fig. 1. Evolutionary relationships among betanodavirus isolates based onRNA1 gene. Maximum likelihood tree (¡Ln D 3715.652610) inferredfrom the RNA1-ALN multiple alignment. Bar represents 0.05 substitutionper site. Bootstrap values are in percent. Major betanodavirus groups arelabeled according to Nishizawa et al. (1997) (RGNNV, BFNNV, TPNNVand SJNNV) and Thiéry et al. (2004) (I, II, III and IV). Dl-HR-96 and Dl-I-96b are in bold (see Section 3.4).


the data set worse than model M0. The model M2 Wts RNA1-ALN better than M0 and M1 models. Furthermore LRTtests (M2 vs. M1; M2 vs. M0) are highly signiWcant (PD0).Model M2 does not identify positively selected amino acid

Fig. 2. Evolutionary relationships among betanodavirus isolates based onRNA2 gene. Maximum likelihood tree (¡Ln D 2422.024057) inferredfrom the RNA2-ALN alignment. Bar represents 0.05 substitution per site.Bootstrap values are in percent. Major betanodavirus groups are labeledaccording to Nishizawa et al. (1997) (RGNNV, BFNNV, TPNNV andSJNNV) and Thiéry et al. (2004) (I, II, III and IV). Dl-HR-96 and Dl-I-96b are in bold (see Section 3.4).

residues in protein A. Model M3 (lnLD¡3349.860763) WtsRNA1-ALN better than nested models M0, M1 and M2.LRT tests are signiWcant only for M3 vs. M0 and M3 vs. M1(PD0), but not for M3 vs M2 (PD0.136). M3 also does notidentify positively selected sites and supports the action ofpurifying selection (�60.30782). The M7 model(lnLD¡3350.461697) Wts RNA1-ALN slightly worse thanM8 (lnLD¡3350.124102). However the LRT test is not sig-niWcant (PD0.713). The M8 model does not identify posi-tively selected sites. M3 results the best Wtting evolutionarymodel to RNA1-ALN. The posterior probabilities for � sitesclasses under model M3 are shown in Fig. 3.

The model M0 (ln LD¡2304.474856) applied to RNA2-ALN favors the presence of strong purifying selection(�D0.1420). Model M1 (ln LD¡2271.021860) Wts the dataset better than model M0. Model M2 Wts RNA2-ALN betterthan M0 and M1 models and the LRT tests are highly signiW-cant (PD0). Model M2 does not identify positively selectedsites. Moreover it supports the existence of strong purifyingselection (�60.14683) acting on CPp protein. Model M3 (lnLD¡2241.620616) Wts RNA2-ALN better than nested mod-els M0, M1 and M2. The LRT tests are signiWcant for M0 andM1 (PD0) but not for M2 (PD0.981). The M3 model identi-Wes a very strong purifying selection acting on 85% of sites(�60.14187). Conversely 15% of sites appears to haveevolved under almost neutral evolution (�D0.95640). TheM7 model (lnLD¡2242.964427) Wts RNA2-ALN slightlyworse than M8 (lnLD¡2242.036206). However the LRT testis not signiWcant (PD0.395). The M8 model identiWes 14% ofsites as evolving under near neutral evolution (�D0.95665).Model M3 results the best Wtting evolutionary model toRNA2-ALN. The posterior probabilities for � sites classesunder model M3 are presented in Fig. 4.

3.6. Recombination

Analyses performed by using the suite of programsincluded in the RDP2 package did not detect any event of

Table 4Adaptive evolution parameters estimate for betanodavirus A and CPp proteins

a site-speciWc models according to Yang et al. (2000); p is the number of free parameters for the � ratios. ln L D log likelihood. Parameters in parenthesesare presented for clarity only but are not free parameters; for example, under M8 (� and �), p1 D 1 ¡ p0. Protein A reference sequence from SJNag93 iso-late. Protein CPp reference sequence from SJNag93 isolate.

Modela p Protein A (RNA1) Protein CPp (RNA2)

ln L Estimates of parameters Positively selected sites

ln L Estimates of parameters Positively selected sites

M0: one ratio 1 ¡3379.121995 �D 0.0418 None ¡2304.474856 �D 0.1420 NoneM1: neutral 1 ¡3424.355097 p0 D 0.80737 (p1 D 0.19263) Not allowed ¡2271.021860 p0 D 0.64820 (p1 D 0.35180) Not allowedM2: selection 3 ¡3351.857206 p0 D 0.70483 p1 D 0.00957

(p2 D 0.28560) �2 D 0.14261None ¡2241.640025 p0 D 0.50346 p1 D 0.14385

(p2 D 0.35269) �2 D 0.14683None

M3: discrete (K D 3)

5 ¡3349.860763 p0 D 0.30961 p1 D 0.56878 (p2 D 0.12161) �0 D 0.01348 �1 D 0.01349�2 D 0.30782

None ¡2241.620616 p0 D 0.50030 p1 D 0.35144 (p2 D 0.14826) �0 D 0.00001 �1 D 0.14187�2 D 0.95640

None

M7: � 2 ¡3350.461697 pD 0.16165 q D 2.85156 Not allowed ¡2242.964427 p D 0.15478 q D 0.70349 Not allowedM8: � and � 4 ¡3350.124102 p0 D 0.69036 p D 0.17065

qD 2.30781 (p1 D 0.30964) �D 0.01587

None ¡2242.036206 p0 D 0.85894 pD 0.32538 q D 4.43304 (p1 D 0.14106) �D 0.95665

None


intragenic recombination on either RNA1-ALN andRNA2-ALN multiple alignments. Of course we cannotexclude intragenic recombination in the portions of genesnot covered by present analyses (see Section 4).

3.7. Molecular clock

Both RNA1-ALN and RNA2-ALN multiple align-ments did not show the existence of a general clock(RNA1-ALN, P < 0.001) (RNA2-ALN, P < 0.01) as

proved by applying several molecular models (HKY85,TN93, GTR) implemented in the Hy-Phy package (Kosa-kovsky Pond et al., 2005). Conversely local clocks weredetected but they were restricted to near-terminal or ter-minal nodes thus involving only few sequences. Theabsence of a clock-like behavior of both RNA1-ALN andRNA2-ALN multiple alignments did not allow to esti-mate a possible origin time for the Betanodavirus isolates.Moreover the substitution rate could not be linked to timedue to the lack of a clock.

Fig. 3. Posterior probabilities of site classes for sites along the RNA1 CDS under the model M3 (discrete). This model assumes three site classes with theproportions (p0, p1, p2) and � ratios (�0, �1, �2) estimated from the data (Table 4). Reference sequence: SjNag93.

Fig. 4. Posterior probabilities of site classes for sites along the RNA2 CDS under the model M3 (discrete). This model assumes three site classes with theproportions (p0, p1, p2) and � ratios (�0, �1, �2) estimated from the data (Table 4). Reference sequence: SjNag93.


4. Discussion

4.1. Phylogeny of Betanodavirus

All sequences included in our study were composition-ally homogeneous thus satisfying a fundamental require-ment of the applied molecular models. Furthermore bothRNA1-ALN and RNA2-ALN present a phylogenetic sig-nal adequate to properly infer the evolutionary relation-ships among major Betanodavirus clades.

Trees obtained from RNA1-ALN and RNA2-ALNdepict contrasting phylogenetic relationships that are cor-roborated by very strong statistical support (Figs. 1 and 2).These discrepancies reXect the diVerent evolutionary histo-ries experienced by RNA1 and RNA2 genes. Such dissimi-lar behavior is widespread among positive-sense single-stranded RNA viruses (e.g., Finetti-Sialer and Gallitelli,2003; Stuart et al., 2004).

Moreover the occurrence of RNA reassortment in someBetanodavirus taxa makes more complicated to establishthe true phylogenetic relationships. In this paper we presentfor the Wrst time a clear evidence of such phenomenon intwo nodaviruses from Sea bass (Dl-HR-96 and Dl-I-96b).Both isolates belong to the SJNNV-IV clade in the RNA1-ALN phylogram (Fig. 1) while they are clearly nestedwithin the RGNNV-I group in the in RNA2-ALN tree(Fig. 2). This completely diVerent placement can beexplained in terms of RNA reassortment.

Mechanisms responsible for RNA reassortment are wellknow in insect nodaviruses (e.g., Ball, 1997) and very simi-lar mechanisms may be responsible of the recombinationobserved in the Wsh nodaviruses. Moreover RNA recombi-nation appears to be a common event in the positive strandRNA viruses (e.g. Lin et al., 2004). Finally RNA recombi-nation can occur in strains lacking diVerent essential partsof the viral RNA-dependent RNA polymerase of replica-tion as recently proved for the genus Pestivirus (Galleiet al., 2004).

Thus recombination is a non-negligible source of possi-ble erroneous phylogenies. However the recognition ofrecombination can be relatively simple if this phenomenonoccurred in the recent past of virus evolution. Conversely itis much more diYcult or even impossible to detect oldevents particularly if they were multiple.

The Betanodavirus capability to infect a host Wsh isdependent upon the type (i.e. SJNNV-IV, TPNNV-III,BFNNV-II and RGNNV-I) of coat protein coded byRNA2 gene (Iwamoto et al., 2004). Shift to new Wsh hostscan however occur through RNA reassortment. Dl-HR-96and Dl-I-96b isolates belong to SJNNV-IV clade in RNA1analysis while they result nested in RGNNV-I in the RNA2phylogram. This dramatic diVerence due to recombinationcan be explained in terms of host shift. Dl-HR-96 and Dl-I-96b infect the Sea bass. This Wsh species hosts betanodavi-ruses of RGNV-I type but not of the SJNNV-IV. It can behypothesize that the parents of Dl-HR-96 and Dl-I-96b iso-lates, originally having not a RGNV-I RNA2 type, went in

contact with Sea bass and became able to attack this Wshspecies trough the gain of a CPp of the RGNNV-I type.

If this scenario is plausible the presence of a CPp type intwo Betanodavirus isolates can be the result of an ancestralcommon evolutionary origin of both isolates or simplyreXects the sharing of the same kind of host. PossiblyBetanodavirus strains can change repeatedly CPp type toinfect diVerent Wsh hosts.

This Wnding has strong impact on the exclusive use ofRNA2 sequences to infer the placement of a single isolatewithin betanodavirus major clades.

Previous phylogenetic analyses on Wsh nodaviruses havebeen based solely on RNA2 sequences (e.g., Dalla Valleet al., 2001; Johansen et al., 2004b; Nishizawa et al., 1997;Thiéry et al., 2004).

However RNA2 reassortment alters the identiWcation oftrue phylogenetic relationships as proved by data presentedin this paper. Thus both RNA1 and RNA2 must be consid-ered for phylogenetic purposes. Moreover the RNA1 gene isnot tightly involved with the host-shift process thus it couldbe a better marker to assess the origin of a single isolate.

4.2. Molecular evolution of A and CPp proteins

The portion of protein A considered in this paperevolved under a very strong purifying selection. This aspectis corroborated by the best Wtting evolutionary modelwhich favors the existence of an excess of synonymous sub-stitutions (�6 0.30782). Pair-wise comparisons amongamino acid sequences coded by RNA1 data set exhibited anaverage amino acid identity of 84% which is slightly higherthan values obtained from full length protein A (80%).Thus, it is plausible to extend our results to the full lengthprotein. Protein A plays a key role in the virus replicationas a consequence the action of stabilizing selection wasexpected for the maintenance of its function.

CPp protein resulted also characterized by purifyingselection but at least 15% of the considered CPp portionevolved under almost neutral evolution (�D 0.95640). Thisportion includes the most variable part of CPp protein that,according to a recent three dimensional reconstruction(Tang et al., 2002), is directly exposed on the outer surfaceof the capsid i.e. in direct contact with the immune defensesof the Wsh host. The CPp protein plays a key role for theinfectivity of betanodaviruses that attack a broad array ofWsh species (Iwamoto et al., 2004). Therefore the detectionof some positively selected sites on the capsid outer surfacewas expected. The absence of such amino acid residues canbe due to lack of statistical power of the applied method orrepresents the true evolutionary history of the protein. Weapplied all strategies necessary to avoid false positiveresults as well as to maximize the detection of sites subjectto positive selection (Anisimova et al., 2002). An analysis(data not shown) performed according to the alternativeapproach described by Kosakovsky Pond and Muse (2005)provided the same results presented here thus supportingthe overall evolutionary trend described in this paper.


The absence of clock-like behavior of both RNA1 andRNA2 indicate that nucleotide changes were not constantduring the time. The absence of clock-behavior made mean-ingless the calculation of molecular evolution rates, thus wedid not make comparison with rates previously obtained byother researches (Nishizawa et al., 1997; Ucko et al., 2004).

4.3. Evolution of Betanodavirus

The evolution of Betanodavirus strains has been charac-terized by diVerent factors. Genetic diVerentiation wasfavored by the possibility to infect diVerent teleost Wshes.The shift to new hosts was further helped by RNA reassort-ment mechanisms. However the capsid protein, directly incontact with the host defenses, did not evolve under astrongly diversifying selection as proved by the absence ofpositively selected amino-acid residues (see Section 4.2).This Wnding indicates that infection of new hosts was char-acterized by small sequence changes not exhibiting a con-stant rate of genetic diVerentiation. The absence of a clock-like behavior for CPp protein is consistent with an oppor-tunistic host shift that requires a rapid adaptation to newWsh species. Betanodaviruses of the RGNNV-I type infectseveral species of bony Wshes. Conversely BFNNV-II typeis restricted to cold-water marine species whilst TPNNV-IIIand SJNNV-IV genotypes attack single or few species (e.g.,Dalla Valle et al., 2001; Johansen et al., 2004b; Nishizawaet al., 1997; Thiéry et al., 2004). Why major betanodavirusclades exhibit a diVerent capability to infect new hosts is atpresent not well understood.

Current phylogenetic evidence does not support a stronginXuence of geography on virus evolution. Isolates collectedin very diVerent locations may belong to the same groupand conversely strains obtained from the same area areincluded in diVerent Betanodavirus genotypes (e.g., thispaper; Dalla Valle et al., 2001; Thiéry et al., 2004). Thespreading of viruses among distant geographic areas is notcompletely known but a key role is played by commerce ofcultured Wsh (Munday et al., 2002). The dissemination ofBetanodavirus is further enhanced by the action of appar-ently healthy Wsh species performing as carriers (Castricet al., 2001; Munday et al., 2002; Johansen et al., 2004a).Temperature plays a role in the evolution of Betanodavirusas proved by the fact that diVerent virus genotypes areinfective at diVerent temperatures (Iwamoto et al., 2004).However current knowledge does not allow a clear appreci-ation of the importance of this factor in shaping Betanoda-virus evolution. More aspects (e.g., year/time infection)require a thorough investigation and a better knowledge ofviruses biology before their role in Betanodavirus evolutionis fully understood.

Acknowledgment

This work was supported by a grant to L.D.V. providedby the Italian Ministry of University and Research.Authors thank an anonymous reviewer that provided very

useful comments and constructive criticisms to an earlierversion of the manuscript.

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