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APPLICABILITY OF SEQUENCE DIVERSITY AT MITOCHONDRIAL GENES ON DIFFERENT TAXONOMIC LEVELS IN GENETICS OF SPECIATION, PHYLOGENETICS AND BARCODING Yuri Ph. Kartavtsev A.V. Zhirmunsky Institute of Marine Biology, Vladivostok 690041, Russia; e-mail: yuri.kartavtsev48@hotmail.com yuri.kartavtsev48@hotmail.comyuri.kartavtsev48@hotmail.com Slide 2 Teacher: Academician, prof. Yuri P. Altukhov, 1992-2006 director, N.Vavilov Institute of General Genetics, Moscow (Russia) Slide 3 MAIN GOALS 1. CBOL & Fish-BOL 2. SPECIES IDENTIFICATION 3. SPECIES DEFINITION AND SPECIES ORIGIN: PROBLEMS, RESTRICTIONS. GENETIC VIEW. Slide 4 1. CBOL & Fish-BOL Slide 5 THE INTERNATIONAL CBOL PROJECT The CBOL is main global initiative. The Fish-BOL, its part, has over 5400 species barcoded by Co-1 from more than 30,000 specimens what makes it unique. P. Hebert and B. Hanner are preparing a $150M grant application for Genome Canada only for 2008. Other nations funds in CBOL are also big in some countries and unions: USA, EU. B. Hanner suggests a recent Fish-BOL paper on Canadian freshwater fishes for your interest, as well as a new paper in press that demonstrates barcoding can identify cases of market substitution in North American seafood. These might be relevant for our meeting and ensuing discussions! In this year there will be held third world-wide international conference (Sept. 2008 Chindao, Peoples Republic of China) and many regional meeting like us were performed. Slide 6 THE INTERNATIONAL FISH-BOL PROJECT Cochairmen: P. Hebert & B. Ward Slide 7 Fish-BOL CURRENT STATE (2006 vs 2008) Class Barco- ded Species Prog- ress Class Barco- ded Species Prog- ress Actinopterygii 3623 5073 27984 13% 18% Cephalaspidom orphi 9 17 42 21% 40% Elasmobranchii 259 358 968 27% 37% Holocephali 15 37 41% Myxini 7878 70 10% 11% Sarcopterygii 0202 11 0% 18% Slide 8 Registration and Barcoding Utilities (BolD; www.boldsystems.org) (1) w w.boldsystems.orgw w.boldsystems.org Slide 9 Registration and Barcoding Utilities (BolD; www.boldsystems.org) (2) w w.boldsystems.orgw w.boldsystems.org Slide 10 Registration and Barcoding Utilities (BolD; www.boldsystems.org) (3) w w.boldsystems.orgw w.boldsystems.org Slide 11 Chair: Masaki MiyaMasaki Miya Vice Chair: Shunping HeShunping He Members: Nina Bogutskaya Seinen Chow Shunping He Yuri Kartavtsev Keiichi Matsuura Masaki Miya Mutsumi Nishida Ekaterina Vasilieva North East Asian Regional Working Group Slide 12 FISH-BOL. RUSSIA DEVELOPMENT Slide 13 2. SPECIES IDENTIFICATION Slide 14 Some Objects Fig. 1. Halibut-like flatfish, Hypoglossus elasodon (A) and obscure flatfish, Pseudopleuronectes obcurus (). A B Slide 15 INTRODUCTION Mitochondrion DNA (mtDNA) is a ring molecule of 16-18 kilo-base pairs (kbp) in length. As literature data show, mtDNA of all fishes has similar organization (Lee et al., 2001; Kim et al., 2004; Kim et al., 2005; Nagase et al., 2005; Nohara et al., 2005) and small differences among all vertebrate animals, including men (Anderson et al., 1981; Bibb et al., 1981; Wallace, 1992; Kogelnik et al., 2005). The complete content of whole mitochondrial genome (mitogenome) includes: control region (CR or D loop), where the site of initiation of replication and promoters are located, big (16S) and small (12S) rRNA subunits, 22 tRNA and 13 polypeptide genes. Usually in phylogenetic research single gene sequences are used for both mtDNA and nuclear genome. However, recently more and more frequent are become complete mitogenome usage. Japanese scientists are leading here for water realm organisms. Most popular in phylogenetics are sequences of cytochrome b (Cyt-b) and cytochrome oxidase 1 (C-1) genes, which used for taxa comparison at the species - family level (Johns, Avise, 1998; Hebert et al., 2004; Kartavtsev, Lee, 2006). Many sequences that bringing the phylogenetic signal obtained for different taxa at gene 16S rRNA as well. Sequences of separate genes can dive different phylogenetic signal because of differences in substitution rates. This is also true for different sections of genes. Also, under comparison of higher taxa there may be effects of homoplasy. When numerous taxa available there are problems of insufficient information capacity of sequences to cover big species diversity and representative taxa representation is quite important (Hilish et al., 1996). Nevertheless, for the species identification, excluding rare cases, fine results are available even with the usage of short sequences, like -1, with 650 bp. Slide 16 Spacers [ITS-1, 2] mtDNA mtDNA nDNA, nDNA, rDNA rDNA Most substantiated statistically results Most substantiated statistically results Statistically significant results Statistically significant results Species G Genus Family Order C Class P Phylum Applicability of Different DNA Types in Phylogenetics and Taxonomy Slide 17 MATERIAL AND METHODS 2. PCR Amplification Genes DNA 3. Sequence Analysis. In 2006 : 200 seq. 4. Mol. Phylogenetics & Taxonomy 1. DNA Isolation. Slide 18 Aligned flatfish sequences at -1: our and GenBank data Slide 19 Distance Data Slide 20 p-DISTANCES IN GROUPS OF COMPARISON, Catfish Fig. 1. Fig. 1. Resulting graph of mean p-distance values at four levels of differentiation in the catfish species (Siluriformes) for Cyt-b gene. Groups: 1. Intraspecies, among individuals of the same species; 2. Intragenus, among species of the same genera; 3. Intrafamily, among genera of the same family; 4. Intraorder, families of the order Pleuronectiformes. There are statistically significant variation. SE: a standard error of mean; F = 124.74, d.f. = 3; 29, p < 0.0001 (Kartavtsev et al., 2007a, Gene). Slide 21 Fig. 2. Resulting graph of one factor ANOVA and mean p-distance values at four levels of differentiation in the flatfish species (Pleuronectiformes) for Cyt-b gene. Groups: 1. Intraspecies, among individuals of the same species; 2. Intragenus, among species of the same genera; 3. Intrafamily, among genera of the same family; 4. Intraorder, families of the order Pleuronectiformes. Statistically significant variation are shown on top of the graph. SE: a standard error of mean (Kartavtsev et al., 2007b, Marine Biol.). p-DISTANCES IN GROUPS OF COMPARISON, flatfish Slide 22 p-DISTANCES IN GROUPS OF COMPARISON, turtles Fig. 3. Resulting graph of ANOVA and mean p-distance values at four levels of differentiation in turtle species (Testudines) for Cyt-b gene. Groups: 1. Intraspecies, among individuals of the same species; 2. Intragenus, among species of the same genera; 3. Intrafamily, among genera of the same family; 4. Intraorder, families of the same order. Variation among four groups is statistically significant: F = 61.87, d.f. = 3; 152, p < 0.000001 (Jung et al., 2006). -Distances: (1) 2.330.03%, (2) 3.340.48%, (3) 6.410.11% (4) 11.920.37% (Mean SE). Slide 23 p-DISTANCES IN GROUPS OF COMPARISON, Perciformes Fig. 3. Resulting graph of one factor ANOVA and mean p-distance values at four levels of differentiation in fish species (Perciformes) for Co-1 gene sequence data. Comparison groups: 1. Intraspecies, among individuals of the same species; 2. Intragenus, among species of the same genera; 3. Intrafamily, among genera of the same family; 4. Intraorder, families of the order Perciformes. Variation is statistically significant. Bars are confidence intervals for mean (95%). Slide 24 Fig. 4. Categorized plot of distribution of weighted mean p-distances among four groups of comparison at Cyt-b and Co-1 genes. Groups here: 1. Intra-species, among individuals of the same species; 2. Intra-sibling species, 3. Intra-genus, among species of the same genera; 4. Intra-family, among genera of the same family (Kartavtsev, Lee, 2006). p-DISTANCES IN GROUPS OF COMPARISON, Review Slide 25 GENETIC SIMILARITY IN TAXA OF DIFFERENT RANK: MEAN FOR THE GROUPS Fig. 5. Genetic similarity in taxa of different rank based on protein markers: mean for the groups. 1. Subspecies, 2. Semispecies and sibling species, 3. Species, 4. Genera. Intraspecies genetic distances were measured for many groups of organisms (Lewontin, 1974, Nei, 1987, Altukhov, 1989). Mean genetic similarity on this level is near I = 0.95 (see details in Kartavtsev, 2005). mtDNA data were presented above. Thus, data available suggest that in general a phyletic evolution prevail in animal world, and so far, the Geographic speciation events (Type 1a) prevail in nature. Do data presented assume that speciation is always follows the Type 1a mode? I guess, no. Few examples below let to support this answer. Slide 26 DISTANCE VS TAXA SPLITTING Has punctuation an impact in species origin on molecular level? Avise, Ayala, 1976; Kartavtsev et al., 1980; current No. Pegel et al., 2006 Yes. Number of Splittings Transformed p-distance r s = 0.22, p < 0.05 Fig. 6. Plot of p-distance on number of splittings at Cyt-b sequence data for catfishes and flatfishes. Slide 27 GENETIC DISTANCES AMONG SPECIES IN SEPARATE ANIMAL GENERA (After Avise, Aquadro, 1982) This plot illustrate a thought that different animal groups of the same rank are unequal in structural gene divergence; i.e. the rate of evolution differ either at genes or at morphology or both. Slide 28 GENETIC DISTATNCES IN TAXA OF SALMON FISHES 1 Populations within species, 2 Subspecies, 3 - Species D This plot support a thought that in salmon even a very small structural gene change can create separate biological species. Slide 29 Comparison of chars Table 2.1. COMPARISON OF ISOZYME ACTIVITY IN THREE WHITEFISH FORMS (COREGONIDAE) AND GRAYLING (THYMALLIDAE) LOCUS/ FORM LEVELS OF DIFFERENCES IN ACTIVITY Note. Total number of loci analyzed are: Whitefish 22, Grayling 23, - Activity do not differ significantly, + Iterative activity difference, ++ two-fold difference, +++ three-fold or greater difference Ratio, % EXAMPLES OF REGULATORY DIVERGENCE IN FISH TAXA Slide 30 WHAT IS MAIN OUTCOME Distance measure alone is not satisfactory descriptor. Data on intraspecies diversity (heterozygosity) at structural genes are necessary. Measures of regulatory genome changes should be necessary to describe transformative modes of speciation. Other descriptors of genomic change are required (e.g. chromoseme number, NF, etc.). Slide 31 3. SPECIES DEFINITION AND SPECIES ORIGIN: PROBLEMS, RESTRICTIONS. GENETIC VIEW Slide 32 WHAT SPECIES IS? Species is a biological unity which reproductively isolated from other unities and consisting from one to several more or less stable populations of sexually reproducing individuals that occupy certain area in nature (my definition). In principal points, this is the definition of BSC (Biological Species Concept). In one of the original BSC definitions A species is a reproductive community of populations (reproductively isolated from others) that occupies a specific niche in nature (Mayr, 1982, p. 273). We will accept BSC for further discussion, although will keep in mind that it is restricted mainly to bisexual organisms (Mayr, 1963, Timofeev-Resovsky et al., 1977, Templeton, 1998). The Linnaean Species The Biological Species Concept (BSC) (Mayr, 1942, 1963) BSC Modification II (Mayr, 1982) The Recognition Species Concept (Paterson, 1978, 1985) The Cohesion Species Concept (Templeton, 1989) Evolutionary Species Concept Simpson (1961) Evolutionary Species Concept. Wileys (1978) Evolutionary Species Concept. The Ecological Species Concept (Van Vallen, 1976). The Phylogenetic Species Concept (Crawcraft, 1983). Slide 33 GENERAL GENETIC APPROACH: ADVANCES AND LIMITATIONS The problem of biological species, and speciation are main focus of this report. These problems took researchers attention since establishing the biology as a science. Most popular now among biologist is the Synthetic Theory of Evolution (STE), which part is comprised by the Biological Species Concept (BSC). Origin and systematic description of STE concept was presented in fundamental books by Haldane (1932), Dobzhansky (1937, 1943, 1951), Huxley (1954), Mayr and co-workers (Mayr, 1942, Mayr, 1963). A popular in Russia summary of STE became a book by Timofeev-Resovsky with co-authors (1977). Good, constructive ideas in STE support were developed by Vorontsov (1980). One of weak point in STE is absence as a rule a possibility to prove experimentally one of key criteria of BSC i.e., reproductive isolation of the species in nature. There are a lot of other criticisms that were summarized for example by King (1993). Nowadays, the new controversy between BSC and Phylogenetic Species Concept arise (Avise, Wollenberg, 1997). The theory of speciation is also not well developed in STE. Exactly speaking, in a quantitative meaning there is no theory as real matter at all. In should be outlined, nevertheless, that many directions of STE and genetics of speciation are developing. Thus, a diverse analysis performed to understand a genetic sense and conceptual basements of speciation (Fox, Morrow, 1981, Grant, 1984, King, 1992). The genetic basis for creation of a reproductive isolation was subjected to the analysis too (Leslie, 1982, Templeton, 1981, Nei et al., 1983, Coyne, 1992). As well there were considered: a possibility of a sympatric speciation (Bush, 1975, Genermon, 1991), the role of saltations or revolutions in evolution (Altukhov, Rychkov, 1970, Carson, 1974, Altukhov, 1985, 1997) and the genetic differentiation during formation of living forms and taxa (Avise, 1975, Avise, Aquadro, 1982, Nevo, Cleve, 1978, Thorpe, 1982, Nei, 1975, 1987). What in general are the advances and limitations in contemporary genetic approach? Slide 34 ADVANCES 1. Data reduction up to genotypic codes (values) give us a possibility to use genetic theory in the analysis. 2. It is possible to perform a comparative investigation of a variability among structural and regulatory elements of the genome and genetic divergence of taxa. 3. Investigations on protein and nucleotide divergence of species from nature discovered a Molecular clock. 4. A possibility of phylogenetic reconstruction occurred: 1) not by similarity, but by kinship and 2) by in time dating of a divergence. Slide 35 LIMITATIONS 1. Deduction is limited by genotypic descriptions and genetic theory. 2. Analysis is connected with preliminary laborious experimental investigation (with its own limitations). 3. Investigation of a species from nature is frequently limited by originality or rare repetition of an event (phenomenon). 4. Genotypic effects of the marker loci on phenotype are weak. 5. The theory is not sufficiently developed in some directions. Slide 36 WHAT DATA ARE NECESSARY? Data that support (reject) central dogma of Neodarwinism Evolution can occurred the only on the base of genetic change. Data on variability at different levels of biological organization in genetic terms (by loci quantitative genotypic values AA, ) single-dimensioned data tables (DT). Data on genotypic values of an individual at the set of loci (genotype AA Bb) or whole gene sequence set multi-dimensional DT. Complementary data: Morphology traits, data on abiotic variability etc. (at least as an expert estimate grouping variables). Slide 37 SCHEMATIC REPRESENTATION OF SPECIES DIVERGENCE AND ORIGIN (From Dobzhansky, 1955) Fig. 3.1. Dobzhanskys (1955) scheme of in time divergence. Single species population. B Initial phase of divergence (subspecies). C Different species. A B C The keystone of STE (Synthetic Theory of Evolution) may be represented by Dobzhanskys scheme (Fig. 3.1), in which the gene pool separation is a key to speciation. If one provides a fact that evolution is possible without genetic change in lineages, then the evolutionary genetic paradigm and STE in particular can be rejected. Slide 38 Fig. 3.1. Main Modes of Speciation Bush, 1975) FIG. 3.2. DIAGRAMMATIC REPRESENTATION OF BASIC MODES OF SPECIATION (From Bush, 1975) The gene flow breaks are able to create Reproductive Isolating Barriers (RIB) or Reproductive Isolation Mechanisms (RIM), which in their turn lead to further origin of species; under different situation in nature, the different modes of speciation acted (Fig. 3.2). Neither, the scheme above, nor the paper itself (Bush, 1975), answer many fundamental questions of speciation. For instance, it is unclear, what mode is most frequent and is a gene flow the sole primary factor, that alter gene pools or there are others? In other words we have to conclude that there is no a theory of speciation in scientific meaning at all. Slide 39 SPECIATION MODES (SM): POPULATION GENETIC VIEW ABSENCE OF QUANTITATIVE THEORY OF SPECIATION (QTS) We have mentioned in preceding section that the speciation theory in evolutionary genetics is absent in exact scientific meaning, which expects the ability to predict future by the theory. In this case this is to predict species origin, or at least discriminate among several speciation modes on the basis of some quantitative parameters or their empirical estimates. Attempts made in this direction (Avise, Wollenberg, 1997, Templeton, 1998) do not fit the above criteria. That is why we attempted to step in the discrimination of the speciation modes on the basis of main population genetic measurements available in literature, and that may be laid in the frame of a genetic speciation concept. BASEMENT FOR THE QTS As a basis for the set of evolutionary genetic concepts we used the descriptions made by Templeton (1981). As a result the classification scheme for 7 different modes of speciation was created (Fig. 3.3). This approach leads to quite simple experimental scheme that permits: (i) to arrange further investigation of speciation in different groups of organisms, and (ii) to derive analytical relations for each speciation mode (Fig. 3.4). The approach is based on a set theory but it is a knowledge-based approach. I believe, this approach is best for such complicated matter. Slide 40 Fig. 3.3. SPECIATION MODES (SM): POPULATION GENETIC VIEW (Kartavtsev et al, 2002) DIVERGENCE SM D1. ADAPTIVED2. CLINALD3. HABITAT Necessary Conditions for Speciation D1. a) Erection of extrinsic Isolating barriers followed by gene flow break; b) Pleotropic origin of RIB (Reproductive Isolatiion Barriers) in long time D2. a) Selection on a cline with isolation by distance; b) Pleotropic origin of RIB D3. a) Selection over multiple habitats with no isolation by distance; b) RIB origin by disruptive selection at genes determined behavior Sufficient Conditions for Speciation Lack of efficient hybridi- zation in the zone of contact DESCRIPTORS: D Genetic distance at structural genes: D T in suggested parent taxa, D S among conspecific demes, D D among subspecies or sibling species; H D Mean heterozygosity in suggested daughter population; H p Mean heterozygosity in suggested parent population; E P Divergence in regulatory genes among suggested parent taxa; E D Divergence in regulatory genes among suggested daughter taxa; TM + - Test for modification (positive); TM - - Test for modification (negative). RIB Reproductive isolation Barriers. Lack of efficient hybridi- zation outside the zone of contact Lack of efficient hybridi- zation inside and outside the zone of contact 1. D T > D S 1 (S) 2. E D = E P 3. H D = H P 4. TM - 1. D T > D S 2 (S) 2. E D E P 3. H D = H P 4. TM - 1. D T = D S 3 (S) 2. E D E P 3. H D =< H P 4. TM - Experimentally measurable features and possible descriptors for the model (theory), (S) Slide 41 Fig. 3.4. ANALITICAL DESCRIPTION OF SEVEN TYPES OF SPECIATION MODES 1 (S) {(D T > D S ) (E D = E P ) (H D = H P ) TM - } (D1) 2 (S) {(D T = D S ) (E D E P ) (H D = H P ) TM - } (D2) 3 (S) {(D T = D S ) (E D E P ) (H DD D ) (E D E P ) (H D < H P ) TM - } (T1) 5 (S) {(D T = D D ) (E D = E P ) (H D < H P ) TM - } (T2) 6 (S) {(D T > D D ) (E D E P ) (H D > H P ) TM - } (T3) 7 (S) {(D T > D S ) (E D E P ) (H D < H P ) TM - } (T4) Note. Descriptors are explained in previous figure. Slide 42 THE QTSEMPIRICAL PROVING THE QTS EMPIRICAL PROVING Salmon (Kartavtsev, Mamontov, 1983, Kartavtsev et al., 1983), Cypriniformes (Kartavtsev et al., 2002), Turtles, flatfishes, catfishes (Jung et al., 2006, Kartavtsev et al., 2006, 2007). Slide 43 PHYLOGENETICS & BARCODING Slide 44 SPECIES IDENTIFICATION AND PHYLOGENETICS Identification + Taxonomy Phylogenetics + Taxonomy Slide 45 Fig. 3.5. Rooted consensus (50%) trees (A-B) showing phylogenetic interrelationships on the basis of Cyt-b sequence data for the analyzed flatfish species (Pleuronectiformes) and four out-group taxa. A tree based on NJ clustering technique with bootstrap support shown in the nodes (n=1000), B Bayesian tree; repetition frequencies for n=106 simulated generations are shown (%) in the nodes. The tree was built based on the TrN+I+G model and was rooted with the sequences of four out- group species: three are Perciformes and one is Cypriniformes. The scales in the left bottom corners indicate relative branch lengths. Slide 46 Fig. 3.6. Consensus (50%) tree showing phylogenetic interrelationships on the basis of Co-1 sequence data for the analyzed flatfish species (Pleuronectiformes) and two outgroup taxa. Rooted Bayesian tree; repetition frequencies (probabilities) for n=10 6 simulated generations are shown in the nodes (%).The tree was built based on the TVM+I+G model and rooted with the sequences of two outgroup species, Perciformes. The scale in the left bottom corners indicate the relative branch lengths. Slide 47 Fig. 3.7. Rooted consensus (50%) tree showing phylogenetic interrelationships on the basis of Cyt-b sequence data for the analyzed flatfish species (Pleuronectiformes) and three outgroup taxa. Bayesian tree; repetition frequencies for n=10 6 simulated generations are shown (%) in the nodes. The trees were built based on the TrN+I+G model, and rooted with the sequences of outgroup species Perciformes. The scales in the left bottom corners indicate the relative branch lengths. (Kartavtsev et al., 2007, Marine Biol.). Slide 48 Fig. 3.8. Consensus (50%) trees showing phylogenetic interrelationships on the basis of Co-1 sequence data for 7 analyzed perch- like fish species (Perciformes) and two outgroup sequences. Rooted Bayesian tree was build for sample purposes; posterior probabilities for n=10 6 simulated generations are shown in the nodes (%). The tree was built based on the HKY+G model. Two other numbers in the nodes show tree bootstrap support based on similar clustering for NJ and ML techniques; support scores are given in the order NJ/ML/BA. Outgroup are two sequences of a representative of Cypriniformes. The scale in the left bottom corner indicate the relative branch lengths. Slide 49 Conclusions Speciation mode must be specified with a set of descriptors not exclusively by distances Both Co-1 and Cyt-b are generally good barcoding tools for species identification For phylogenetic reconstructions we need to cover both taxa diversity and several genes sequence diversity Slide 50 THANKS FOR ATTENTION! ! Slide 51 FEW RECENT PUBLICATIONS Kartavtsev YP. 2005. Molecular evolution and population genetics. Far Eastern State Univ. Press., Vladivostok, 234 p. Kartavtsev YP, Lee J-S. Analysis of nucleotide diversity at genes Cyt-b and Co-1 on population, species, and genera levels. Applicability of DNA and allozyme data in the genetics of speciation. Genetika, 2006. 42: 437-461. Jung S-O, Lee Y-M, Kartavtsev YP, Park I-S, Kim D-S, Lee J-S. The complete mitochondrial genome of the Korean soft-shelled turtle Pelodiscus sinensis // DNA Sequence, 2006. 17(6): 471-483. Sasaki T, Kartavtsev YP, Uematsu T, Sviridov VV, Hanzawa N. Phylogenetic independence of Far Eastern Leuciscinae (Pisces: Cyprinidae) inferred from mitochondrial DNA analysis. Gene and Genetic Systems, 2007. 82: 329-340. Kartavtsev YP, Lee Y-M, Jung S-O, Byeon H-K, Son Y-, Lee J-S. Complete mitochondrial genome in the bullhead torrent catfish, Liobagrus obesus (Siluriformes, Amblycipididae) and phylogenetic considerations. Gene, 2007a. 396: 13-27. Kartavtsev YP, Park T-J, Vinnikov KA, Ivankov VN, Sharina SN, Lee J-S. Cytochrome b (Cyt-b) gene sequences analysis in six flatfish species (Pisces, Pleuronectidae) with phylogenetic and taxonomic insights. Journal Marine Biology, 2007b. 152(4): 757-773. Slide 52 Terminal taxa: A B C D E F G H Outgroup: TERMSRoot Nodes, Speciation events Internal nodes Branches Ingroups: group Sister group Slide 53 A B C D E A C E B D A E C B D Slide 54 . Slide 55 - . , . Slide 56 A B C A A B B C C a bca b c : Slide 57 - - 4N - - Slide 58 1. .. (, -. , . , ) 2. .. (, ..., . ) 3. .. (, ...) 4. .. (, ...) 5. .. (, ...) 6. .. (, -. , . ) 6. .. (, ...) 7. A.A. (, ...) 1. .. (, ...) 2. .. (, ...) 3. .. (, ) 4. .. (, ..., . ) 5. .. (, ...) 6. .. (, ..., . ) 7. .. (, ) 8. O.. (, ) Slide 59 (4) .. (...., , . ) .. (...) .. (...) .. (..., . ) .. (...) (4) .. (...) .. (...) .. () .. ( ) (3) .. (-. , ) .. (...) .. () -, , . (7) .. (..., . ) .. (..., . ) .. (...) .. (...) .. (..., . ) .. (..., . ) .. (...) Slide 60 GenBank (NCBI) Slide 61 () , 16-18 (.). , (Lee et al., 2001; Kim et al., 2004; Kim et al., 2005; Nagase et al., 2005; Nohara et al., 2005) , , (Anderson et al., 1981; Bibb et al., 1981; Wallace, 1992; Kogelnik et al., 2005). () : (CR D ), , (16S) (12S) , 22 13 . , , . b (Cyt-b) 1 (C-1), (Johns, Avise, 1998; Hebert et al., 2004; , , 2006). , , 16S . - / ( ). . , , , (Hilish et al., 1996, Miya et al., 2001). , , , , 1 (-1, 654 ).