Molecular Biology and Evolution 17:284-291 (2000)
© 2000 Society for Molecular Biology and Evolution
Articles |
Intragenomic Variation Within ITS1 and ITS2 of Freshwater Crayfishes (Decapoda: Cambaridae): Implications for Phylogenetic and Microsatellite Studies
Department of Zoology and Monte L. Bean Museum, Brigham Young University
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Abstract |
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Intragenomic variation in ITS1 and ITS2 is known to exist but is widely ignored in phylogenetic studies using these gene regions. The amount of variation in seven crayfish species, including three populations of Orconectes luteus and two of Procambarus clarkii, was assessed by sequencing 3, 5, or 10 clones from the same individuals, for a total of 77 sequences. The ITS1 and ITS2 sequences reported here are some of the longest known, with aligned lengths of 760 and 1,300 bp, respectively. They contain multiple microsatellite insertions, all of which show considerable intragenomic variation in the number of repeat elements. This variation is enough to obscure phylogenetic relationships at the population level, although relationships between species can be estimated. Given the hybridization techniques used to locate microsatellites, multiple-copy regions like ITS1 and ITS2 will be preferentially found if they contain microsatellites, and in these cases the microsatellites will not behave as typical Mendelian markers and could give spurious results.
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Introduction |
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TOPAbstractIntroductionMaterials and MethodsResultsDiscussionAcknowledgementsliterature cited |
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The eukaryotic ribosomal DNA (rDNA) array typically consists of several hundred tandemly repeated copies of the transcription unit, which encodes 18S, 5.8S, and 28S genes, with two internal transcribed spacers, ITS1 and ITS2 (fig. 1 ). Nuclear rDNA sequences have been widely used in estimating phylogenies for many organisms, with ITS1 being particularly widely used at the population and species level due to its high level of sequence variation (Vogler and DeSalle 1994
; Miller, Crabtree, and Savage 1996
; Fabry, Köhler, and Coleman 1999
; Schulenberg, Englisch, and Wägele 1999
). Intragenomic rDNA diversity is generally low due to concerted evolution (Brown, Wensink, and Jordan 1972
)—individual repeats in the multigene family evolve in concert, resulting in the homogenization of all the repeats in an array. Although this appears to be the norm, variation within an individual is known (e.g., Carranza et al. 1996
; Hugall, Stanton, and Mortiz 1999
). Whenever concerted evolution is slower than speciation, a single genome will contain divergent paralogs. Vogler and DeSalle (1994)
showed that sequence variation in ITS1 within individual tiger beetles, Cicindela dorsalis, was high, although they still exhibited phylogenetic separation coinciding with geographic separation of populations. Wesson et al. (1992) reported 0.46% variation within 10 clones of ITS2 from a single mosquito, Aedes simpsoni, while intraspecific variation in Aedes aegypti was only 1.17%.
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We investigated levels of intragenomic variation within the ITS1 and ITS2 regions of freshwater crayfish (Decapoda; Cambaridae). All of the individuals studied, both from different species and from different genera, showed some level of intragenomic variation in sequence composition of ITS1 and ITS2. Although separation between species was well supported, variation within individuals was greater than any differentiation among populations, making these sequences uninformative at this level. Intraspecific variation was primarily due to the presence of a number of microsatellite loci within these regions, which show considerable variation in the number of repeats within individuals. The presence of microsatellites is well documented in many multigene families, such as the human rRNA genes (Gonzalez et al. 1990
) and the primate RNU2 locus (Liao and Weiner 1995
). However, in the absence of breeding studies, microsatellite loci are typically statistically summarized as codominant Mendelian markers, something they are clearly not if they are found in these regions. Implications are therefore important to both microsatellite studies and phylogenetic analyses using ITS sequences. |
Materials and Methods |
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TOPAbstractIntroductionMaterials and MethodsResultsDiscussionAcknowledgementsliterature cited |
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Crayfish Samples
The following crayfish specimens were examined: Orconectes luteus (four individuals, three separate populations), Orconectes macrus, Orconectes neglectus, Orconectes punctimanus, Orconectes longidigitus, Orconectes virilis, and Procambarus clarkii (2 individuals). All of the specimens were collected by hand or net (table 1 ). We used these specimens because they have a well-defined phylogeny based on 16S rDNA sequences (Crandall and Fitzpatrick 1996
), and the populations of O. luteus are easily discernable using 16S rDNA and AFLP data (Fetzner and Crandall 1999
). Upon capture, crayfish were identified, and a tissue sample was taken and preserved in liquid nitrogen until it was placed in permanent storage at -80°C. The remainder of the specimens were preserved in 70% ethanol and housed in the collection of the Monte L. Bean Life Science Museum at Brigham Young University.
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Laboratory Procedures
Total genomic DNA was extracted from the frozen tissues using a standard proteinase K extraction followed by the addition of phenol/chloroform and precipitation with isopropanol. DNA was then dried and resuspended in TE buffer. PCR products were amplified using the following primers—ITS1: GTAAAAGTCGTAACAAGG and TCCTCCGCTWAWTGATATGC; ITS2: TGYGAACTGCAGGACACA and TGTGTCCTGCAGTTCRCA (5'–3'). Standard PCR reactions were carried out on a Perkin-Elmer 9600 machine with 35 cycles and an annealing temperature of 50°C. Fresh PCR products were cloned using the TOPO TA cloning kit (Invitrogen). Colonies containing the vector including the cloned PCR product were picked with a sterile pipette tip and put into 20 µl of water. This was shaken for 20 min, and then 1 µl was taken as the DNA template for an additional PCR, following the specifications suggested by the cloning kit literature (25 cycles with a 55°C annealing temperature). Successful PCR products were purified using a GeneClean II kit (Bio 101). Automated sequences were generated on an ABI 377XL automated sequencer using the ABI Big-dye Ready-Reaction kit following the standard cycle sequencing protocol but using a quarter of the suggested reaction size.
Phylogeny Reconstruction
Sequences were aligned using CLUSTAL W (Thompson, Higgins, and Gibson 1994
). Some adjustments were made by eye. The sequences were then imported into PAUP* (Swofford 1999
) for phylogenetic analyses. When estimating phylogenetic relationships among sequences, one assumes a model of evolution regardless of the optimality criteria employed. We therefore employed minimum evolution rather than maximum parsimony, as this method can take into account more of the inherent characteristics of the data set (e.g., differences in nucleotide frequencies, rate heterogeneity, etc.). Determining which model to use given one's data is a statistical problem (Goldman 1993
). We used the approach outlined by Huelsenbeck and Crandall (1997)
to test alternative models of evolution, employing PAUP* and Modeltest (Posada and Crandall 1998
). A starting tree was obtained using neighbor joining. With this tree, likelihood scores were calculated for various models of evolution and then compared statistically using a chi-square test with degrees of freedom equal to the difference in free parameters between the models being tested. The null hypotheses tested in this way included the hypotheses that: (1) nucleotide frequencies are equal, (2) transition rates are equal to transversion rates, (3) transition rates are equal and transversion rates are equal, (4) there is rate homogeneity within the data set, and (5) there is no significant proportion of invariable sites. Once a model of evolution was chosen, it was used to estimate a tree using the minimum-evolution optimality criteria (Rzhetsky and Nei 1992
). Confidence in resulting nodes was assessed using the bootstrap technique (Felsenstein 1985
) with 1,000 replicates (fig. 2
).
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Results |
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TOPAbstractIntroductionMaterials and MethodsResultsDiscussionAcknowledgementsliterature cited |
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Nucleotide sequencing was concentrated on the ITS1 region, as this region is more typically used in phylogenetic analyses than the ITS2 region. The ITS1 sequences were collected from five clones from each individual, except for the first O. luteus individual, from which 10 clones were sequenced, and the P. clarkii individuals, from which 3 clones were sequenced. This gave a total of 56 sequences for 11 individual crayfish. For ITS2, 5 and 10 clones were sequenced for two individuals of O. luteus, and 3 were sequenced for each of the P. clarkii individuals, for a total of 21 sequences. A file containing the aligned sequences can be downloaded from http://bioag.byu.edu/zoology/crandall_lab/data. These sequences have also been submitted to GenBank (accession numbers AF198535–AF198611).
To test for saturation by multiple substitutions within the ITS1 data set, observed pairwise proportions of transitions and transversions were plotted against uncorrected sequence divergence (fig. 3 ). There is a clear separation between the Orconectes sequences and the Procambarus sequences, with genetic divergences within genera being less than 5% but genetic divergence between them being more than 25%. This evidence and the difficulty in accurately aligning Orconectes sequences to those of Procambarus led us to analyze the Orconectes sequences without including those of Procambarus.
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From the aligned Orconectes ITS1 sequences, we compared likelihood scores for various models of evolution. Since the microsatellite regions could affect the choice of model, this was carried out both with these regions included and with them excluded. Our first hypothesis, comparing the Jukes and Cantor (1969)
(JC69) model with the Felsenstein (1981)
(F81) model, was not significant, indicating that the proportions of nucleotides were not significantly different from equal numbers. We then compared the JC69 model with the Hasegawa, Kishino, and Yano (1985)
(HKY85) model. Again, this was not significant, indicating that transition and transversion rates were not significantly different. We then compared the model including a discreet approximation of rate heterogeneity (Yang 1994
) (+G). When the microsatellites were included there was significant rate heterogeneity, but when they were excluded there was not significant rate heterogeneity. Finally, we tested for a significant proportion of invariable sites (+invar). In both cases, there were significant proportions of invariable sites. Therefore, the models we used were the JC69 model with a discreet approximation of rate heterogeneity and an estimated proportion of invariable sites for the data set with the microsatellites included (JC69+G+invar), and the JC69 model with an estimated proportion of invariable sites for the data set with the microsatellites excluded (JC69+invar). With the microsatellite region included, the proportion of invariable sites was estimated to be 0.7194, and the shape parameter of the gamma distribution for incorporating rate heterogeneity was estimated to be 1.0396. With the microsatellite regions excluded, the JC69 model with a gamma-distributed rate heterogeneity model (shape parameter 0.1079) was chosen (table 2
).
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The separate minimum-evolution searches incorporating these models resulted in 6,480 and 73,988 trees, with scores of 0.11 and 0.80, respectively (fig. 2 ). Maximum likelihood was not used to estimate phylogenies, as the extremely short intraspecies nodes on the tree made this method computationally unfeasible. We also used these same models to estimate average genetic distances for a taxonomic hierarchy of crayfishes (table 3 ). We then compared these corrected distances with average distances estimated from 16S mtDNA sequences. Our results show that distances increase as expected for the 16S mtDNA as one moves up the taxonomic hierarchy, except at the highest level (among genera) where the 16S genetic distance is the same as the high end of the among-species distances. Contrary to the 16S data, the ITS1 data show considerable nonhierarchical distances at the lower taxonomic levels. Note that the high end of the within-individual corrected distances are higher than the among-individuals within-population distances and even the among-populations within-species distances. The hierarchical pattern of increasing distance with increasing taxonomic rank is established at the among-species level. Thus, within-individual divergences are as great as or greater than among-individuals and among-populations divergences.
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Discussion |
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TOPAbstractIntroductionMaterials and MethodsResultsDiscussionAcknowledgementsliterature cited |
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The ITS regions of the rDNA repeat in crayfish are much longer than most of those previously published, with aligned lengths of 760 and 1,300 bp. Typically, published ITS1 sequences are around 300 bp (e.g., the tiger beetle C. dorsalis; Vogler and DeSalle 1994
), while ITS2 sequences are typically 400–600 bp (e.g., the mosquito Anopheles nuneztovari; Fritz et al. 1994
). This could be due in part to the large number of simple sequence repeats found in the crayfish sequences, although these are also found in previously published sequences. Interestingly, the ITS2 sequences show considerable variation in length among the crayfishes examined—the sequences from P. clarkii are about 120 bp longer than those of O. luteus.
Phylogenetics
Phylogenetically, ITS1 sequences are not informative in separating the three populations of O. luteus, despite the fact that these populations are uniquely defined using amplified fragment length polymorphisms and 16S mtDNA (Fetzner and Crandall 1999
). This is due to the high level of intragenomic variation examined. This variation, although particularly prevalent in the microsatellite regions, is not confined to them. Removal of the microsatellites reduces bootstrap support for all species groups except O. punctimanus. However, with one exception, the clones of O. luteus from the Big Piney and Niangua rivers are then separated (62% bootstrap) from the two individuals from the Meramec River, indicating that it is these regions in particular that cause problems for phylogenetic construction at the population level.
At the generic level, at least between Orconectes and Procambarus, the ITS1 sequences are too divergent to be phylogenetically useful, but at the species level, ITS1 sequences are partially informative, with high bootstrap support for a clade of O. punctimanus, O. longidigitus, and O. virilis. This relationship is not altered by the presence or absence of the microsatellite regions. It is, however, different from the hypothesis of relationships derived from 16S mtDNA sequence data (Crandall and Fitzpatrick 1996
), which has been used to estimate a phylogeny of (((((O. punctimanus, O. virilis), O. luteus), O. longidigitus), O. neglectus), O. macrus), i.e., the positions of O. luteus and O. longidigitus are reversed. The topology derived from 16S sequence data is significantly different from the minimum-evolution tree estimated from the ITS1 data set using the Kishino and Hasegawa (1989)
likelihood ratio test (likelihood of minimum-evolution tree = -1,173, likelihood of tree constrained to topology derived from 16S sequence data = -1,197, SD = 10; T = 2.24; P = 0.025). This could be due to the limited sampling of species for the ITS data sets, but it does highlight the problems of using only a single gene phylogeny to estimate organismal relationships.
Despite the fact that such variation has been known to exist for some time (e.g., Vogler and DeSalle 1994
), very few of the recent phylogenetic analyses using ITS sequences take this into account by examining multiple sequences from single individuals. The impact of this kind of variation on phylogenetic studies is increased if many phylogenetically distinct groups show similar intragenomic variation. In all cases so far reported where intraindividual variation has been looked for within ITS1 and ITS2, it has been found to some degree. This includes studies on beetles (Vogler and DeSalle 1994
), crayfish (this study), yellow monkey flowers Mimulus (Ritland et al. 1993), maize Zea mays (Buckler and Holtsford 1996
), fungus Fusarium (O'Donnell and Cigelnik 1997), and coral Acropora (Odorico and Miller 1997). ITS sequence data are extremely widely used in plant systematics and population studies. However, for example, none of the papers using ITS sequence variation to examine phylogenies in Plant Systematics and Evolution in 1999 to date investigate this problem (Koch et al. 1999; Leskinen and Alstrom-Rapaport 1999; Susanna et al. 1999), despite analyses that show that major NOR loci (which contain rDNA arrays) may move within and among chromosomes and that this movement may occur via magnification of minor loci consisting of a few rDNA copies (Dubcovsky and Dvorak 1995
). Deletion of major rDNA sites and their replacement by minor, potentially paralogous, rDNA sites can lead to sudden stochastic fluctuations in the rDNA consensus sequence in an evolutionary lineage. Therefore, if paralogous copies are present, phylogenetic reconstruction should be treated extremely cautiously.
In some cases in which genomes contain considerable diversity of paralogous rDNA, the divergent paralogs are probably rDNA pseudogenes, since they have low predicted secondary structure stability (Buckler, Ippolito, and Holtsford 1997
). In their analysis of Zea relationships, Buckler and Holtsford (1996)
found four putative pseudogenes from Z. mays, which were basal to all other Z. mays ITS sequences. The pseudogenes had undergone many substitutions relative to the normal alleles. This was unlike the situation for Mimulus ITS types that were closely related to each other within types (Ritland et al. 1993). The crayfish ITS sequences do not appear to be pseudogenes, as the minimum-energy secondary structures (calculated using the program mFold [Zuker 1989]) were all very similar from the different ITS copies (approximately -266kcal/mol at 37°C for ITS1). Given that the different sequences are not pseudogenes, the level of intragenomic variation is much higher than those reported in other cases. This is almost certainly due to the presence of the microsatellites in both the ITS1 and the ITS2 sequences. Therefore, in studies which have microsatellites within their rDNA sequences, one should be particularly cautious about inferring relationships without investigating the levels of intragenomic variation.
Microsatellites
Known variation within microsatellite regions of ITS1 from single individuals has had little or no impact on microsatellite studies—few of these report the positions of microsatellite loci within the genome, and the regions are routinely assumed to behave as independent codominant markers. This is probably due to the shortness of the microsatellites previously reported within multicopy genes. For example, Vogler and DeSalle (1994)
showed the presence of two microsatellites in their ITS1 data set, (TA)5–9 and (GA)4–8, while Koch et al. (1999), in their study of the Brassicaceae, reported a (TA)6 repeat in one species. The repeat units found in ITS2 sequences have also typically been short: Fritz et al. (1994)
reported a (GA)4–8 repeat in mosquito Anopheles populations. All of these repeat sequences are shorter than most new microstatellite loci that are published (e.g., 30 microsatellite loci reported for red drum, Sciaenops ocellatus, ranged from (TG)5 to (CA)22(GT)5— Turner et al. 1998). However, the microsatellite regions from this study are considerably longer, e.g., (CAG)5–8 in ITS2 and (TGC)3–6(TCC)3–6, (GA)3–12, and (CAG)5–8 in ITS1 (table 4
), and other long microsatellites have been reported, such as the (GA)11–20 repeat found in the 5' half of human ITS clones (Gonzalez et al. 1990
). Although shorter than many reported microsatellite loci, they are within the range of those used in population studies. Given the hybridization techniques used to locate microsatellites (Strassmann et al. 1996
), microsatellites in multiple-copy regions like ITS1 and ITS2 will be preferentially found. The occurrence of microsatellites in such regions may explain why length variation of microsatellites has not always correlated with predicted phylogenies in previous studies, e.g., in the case of the horseshoe crab Limulus polyphemus (Orti, Pearse, and Avise 1997
). One indirect way of detecting this sort of variation would be through mismatches between known mother-offspring pairs or by significant deviation from Hardy-Weinberg equilibria—the same methods that are used to identify nonamplifying alleles (Pemberton et al. 1995
). A more direct method, sequencing multiple clones from a single individual, will show whether variation is prevalent, and this method should be used as a standard in the microsatellite technique to avoid spurious results.
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Acknowledgements |
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TOPAbstractIntroductionMaterials and MethodsResultsDiscussionAcknowledgementsliterature cited |
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We thank Jack Sites, Mike Whiting, David Posada, and two anonymous reviewers for suggestions improvements to the manuscript. This work was supported by NSF IBN-97-02338 and the Alfred P. Sloan Foundation (to K.A.C.).
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Footnotes |
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Stephen Palumbi,
1 Present address: Unidade de Genética Animal e Conservação, Campus Agrário de Vairão, R. Monte-Crasto, Portugal. 
2 Keywords: ITS1
ITS2
Orconectes,
Procambarus,
microsatellites
phylogeny
crayfish
rDNA
3 *Address for correspondence and reprints: Keith A. Crandall, Department of Zoology and Monte L. Bean Museum, Brigham Young University, 574 Widtsoe Building, Provo, Utah 84602-5255. E-mail: kac{at}email.byu.edu
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TOPAbstractIntroductionMaterials and MethodsResultsDiscussionAcknowledgementsliterature cited |
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J. H. G. von der Schulenburg, J. M. Hancock, A. Pagnamenta, J. J. Sloggett, M. E. N. Majerus, and G. D. D. Hurst Extreme Length and Length Variation in the First Ribosomal Internal Transcribed Spacer of Ladybird Beetles (Coleoptera: Coccinellidae) Mol. Biol. Evol., April 1, 2001; 18(4): 648 - 660. [Abstract] [Full Text] [PDF]
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