Russian Journal of Genetics, Vol. 38, No. 9, 2002, pp. 989–1008. Translated from Genetika, Vol. 38, No. 9, 2002, pp. 1173–1195. Original Russian Text Copyright © 2002 by Altukhov, Salmenkova.

THEORETICAL PAPERS AND REVIEWS

DNA Polymorphism in Population Genetics Yu. P. Altukhov and E. A. Salmenkova Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow, 119991 Russia; fax: (095) 132-89-62; e-mail: [email protected] Received March 2, 2002

Abstract—In the review, the literature evidence on DNA polymorphism obtained in the last 10–15 years using various molecular-genetic methods is summarized. All main types of DNA variation are considered but attention is focused on those extensively used in population genetics. The areas of using DNA markers are outlined and the limitations of their potential in analyzing genetic processes in populations are discussed. Particular emphasis is placed on the relationship between the earlier developed biochemical genetics based on protein polymorphism analysis and modern molecular population genetics based on DNA polymorphism. The possible role of selection in maintaining DNA variation is considered.

By the late 1960s, the advances in immunological and biochemical methods, particularly protein electrophoresis combined with histochemical techniques, have led to the development of biochemical population genetics, which opened new possibilities in understanding intra- and interspecific genetic variation and solving a wide range of theoretical and applied problems of biology (see [1, 2] for review). Based on several hundred of discovered immunological and primarily biochemical markers (see the list of the latter in review [3]) differing in localization and function and regarded as a representative gene sample of the genome, the previously hidden, enormous hereditary variation (genetic polymorphism) has been revealed. This permitted the estimation of basic population-genetic parameters in about 2000 species of animals, plants, and microorganisms as well as in human [2, 4–7]. In the following decades it has been shown that (1) up to one-third of the eukaryotic loci are represented by allelic variants while average heterozygosity can reach 12% and more; (2) this variation is maintained in populations by the known microevolutionary factors, i.e., mutation, migration, random genetic drift and selection, which interact in various combinations; (3) the integral genotype structure by the assemblage of polymorphic genes acts in concert with the universal polygenic system determining such important functional traits as rates of development and growth; (4) gene frequency analysis reveals the systemic organization of native populations of various bisexual species and genetic stability of population systems in space and time; (5) the ratio between the intra- and intergroup components of genetic variation in normally fluctuating environments is maintained on the optimal level, which can be considered as a reference point in the organization of rational management and artificial reproduction of biological resources [8, 9].

In the mid-1980s, after the discovery of DNA polymorphism, a new class of genetic markers has appeared due to the advent of techniques of gene isolation, cloning, and restriction. The discovery of polymerase chain reaction played the key role in the formation and development of the “new genetics.” Since the majority of the genome does not take part in the known and important functions, the corresponding parts of noncoding DNA exhibit the polymorphism levels that are far higher than that of any known protein polymorphism. Advances in the new field are so great that some authors propose to forsake the methodology of biochemical genetics for the sake of DNA polymorphism. The fallacy of such statements is evident even a priori, since protein and DNA polymorphisms are naturally complement each other in relation to the issue examined (see, e.g., [10–12]). Here, we discuss this problem showing in the last section of the paper how the insights from biochemical genetics may help in revealing natural selection that limits the range of some DNA polymorphisms. However, first we consider phenomenology of main types of DNA polymorphism, briefly outline their application in different fields of biology and pay attention to some techniques. RESTRICTION ENZYMES (RESTRICTION ENDONUCLEASES); DNA HYBRIDIZATION Restriction enzymes were discovered by Verner Arber in 1979 upon infecting various Escherichia coli strains by the λ phage. Arber has shown that the phage DNA in the bacterium is cleaved (digested) and loses its infectiousness. Later, it was found that not only phage but any foreign DNA is neutralized in that manner upon entering a bacterial cell. The digestion (restriction) is effected by specific enzymes, restriction endonucleases. Since these enzymes

1022-7954/02/3809-0989$27.00 © 2002 MAIK “Nauka /Interperiodica”

990

ALTUKHOV, SALMENKOVA

a Sites EcoRI

GAATTC CTTAAG

b

Cleavage

G AATTC CTTAA G

A

c

B Largest

Electrophoretic separation

Smallest

Fig. 1. Schemes of DNA digestion by a restriction enzyme and electrophoretic separation of resultant fragments. The depicted DNA molecule has three sites recognized by restriction endonuclease EcoRI (a). Each DNA region having sequence GAATTC (shown by open rectangles) is cleaved by this endonuclease producing sticky ends (b). The resultant four fragments are separated in agarose gel (“profile” A in c). If the population contains an alternative allele lacking this restriction site (encircled in a), the two middle fragments of the A “profile” are absent; instead of them, a single larger fragment is present in the B “profile” (from [175]).

are indifferent to their own DNA, this phenomenon is regarded as a mechanism of cell protection. The question was why do restriction enzymes digest the foreign rather than their own DNA? It was found that restriction endonucleases react only with recognition sites, i.e., specific, demethylated DNA sequences consisting of four to six base pairs, which in homologous bacterial DNA are protected by methyl groups. DNA digestion with restriction endonucleases results in the appearance of` DNA fragments with the so-called “sticky” ends due to the fact that after cleavage of two-stranded DNA, one of the strands turns out to be longer than the other by several nucleotides. The sticky ends of one fragment can readily join with such ends of any other fragment, which underlies the technology of obtaining recombinant DNA molecules of different origin. At present over several hundred restriction enzymes differing in recognition and digestion sites have been identified [13]. Restriction endonucleases are used for different experimental purposes. In particular, they are commonly employed in specific DNA amplification

that require determination of the primary structure (nucleotide sequence) of the molecule or in studying gene expression after their cloning, i.e., introduction into a bacterial cell and amplification. In this context, the use of restriction enzymes for detecting DNA polymorphism is of particular importance. It is known that DNA polymorphism is caused by several reasons, i.e., point mutations (one-nucleotide substitutions), DNA replication errors (insertions and deletions of one to several hundred or thousand nucleotides in length), or other types of DNA reorganization between restriction sites. All changes in the primary DNA structure result in changes in the length of the fragments produced by restriction endonucleases. The corresponding method of analysis was termed restriction fragment length polymorphism (RFLP). Here, DNA fragments are used as simplest genetic markers. A mixture of DNA fragments is separated by electrophoresis in agarose or polyacrylamide gel and visualized via radionuclide end-labeling with subsequent autoradiography or staining with ethidium bromide. In Fig. 1, the simplest scheme of DNA digestion and electrophoretic separation of resulting fragments is presented. This method is ineffective for separating a mixture of numerous fragments. For selective identification of particular fragments in a gel, hybridization with a specific probe, usually according to Southern (Southern blotting), is used [14]. This probe is a cloned DNA sequence complementary to the specific sequence of the fragment and radioactively or fluorescently labeled. Due to the label, the fragment can be visualized by the subsequent procedures. At first hybridization with restriction DNA fragments involved universal multilocus probes, which contained nucleotide sequences that very often occurred in the genome as repeat families [15]. To date specific probes have been obtained for many organisms (e.g., introns of human myoglobin gene, phage M13 DNA, etc.). These probes simultaneously show on the gel many similar loci that are typically heterozygous due to their numerous alleles. These complicated patterns of DNA fragments, which are virtually completely specific for an individual, were termed DNA fingerprints. The patterns exhibit extensive variation both within and among species [15, 16]. DNA fingerprints are very convenient for determining relatedness or origin, but less helpful in studies of interpopulation differences because it is nearly impossible to assign the numerous allelic variants to a given locus and determine allele frequencies. Nevertheless, statistical procedures for estimating heterozygosities, genetic distances and diversity parameters have been developed [17, 18]. At present many specific single locus probes (SLPs) have been created [19–22]. This considerably simplifies analysis since variation detected in hybridization with SLP (“DNA profile”) concerns a particular locus, corresponds to Mendelian variation, and permits esti-

RUSSIAN JOURNAL OF GENETICS

Vol. 38

No. 9

2002

DNA POLYMORPHISM IN POPULATION GENETICS

mation of allele frequencies, heterozygosity, and other population parameters [23–25].

Original template 1. Denaturation

Apart from restriction endonucleases, other enzymes used include polymerases (to synthesize new strands on the one-strand DNA template) and ligases (to link sticky ends of two DNA strands, e.g., in the cloning procedure).

2. Annealing primers 3. Extending primers 4. Denaturation and annealing with primers

POLYMERASE CHAIN REACTION Another very important approach widely used in studies of DNA polymorphism is polymerase chain reaction (PCR) method [26, 27]. Using this technique, the required nucleotide sequences can be relatively easily and rapidly amplified from traces of plant and animal DNA, including that from fossil specimens. In PCR, the DNA region to be amplified (more precisely, each of its two strands) is used as a template for in vitro synthesizing the complementary sequence. The reaction is catalyzed by thermostable Taq polymerase in the presence of two primers, i.e., synthetic oligonucleotides complementary to the sequences flanking the amplified fragment (one primer for each DNA strand), and involves several steps at different temperatures. The procedure is fully automated, and the reaction cycle is repeated many times (Fig. 2). The number of DNA molecules is doubled in each cycle, so that after 30 replication cycles the initial DNA amount is more than millionfold amplified. PCR DNA amplification procedure is more effective than cloning, but the latter method, unlike PCR, permits operating with larger (several thousand base paires and more) DNA fragments [28]. In cloning, a DNA fragment with the use of ligase is inserted into a self-reproducting construction, or a vector. Vectors are DNA molecules of bacterial plasmids or phages capable of penetrating a microbial or yeast cells and many times replicating with it in its reproduction cycle (Fig. 3). DNA POLYMORPHISM MARKERS DNA polymorphism was first described in 1978 [29] in relation to analysis of a DNA sequence tightly linked to the human β-globin gene, which permitted prenatal diagnostics of sickle-cell anemia. Later, it was shown that several hundred of such polymorphisms are spread throughout the genome, which allows researchers to localize genes on chromosomes if a sufficiently complete pedigree is available (see [13] for details). At present polymorphism has been found in mitochondrial (mt) and nuclear DNA, the coding and noncoding parts of the latter, in its unique and repetitive sequences. The coding DNA part, which constitutes only 1% of the genome in mammals, is more conserved whereas the noncoding part is more variable as it is less constrained by selection [30]. RUSSIAN JOURNAL OF GENETICS

Vol. 38

No. 9

991

5. Extending primers Fig. 2. Scheme of polymerase chain reaction (PCR): 1, heat denaturation and cooling of the DNA molecule; 2, short synthetic primers anneal tio each complementary chain; 3, primers are extended by thermostable polymerase, which results in duplication of the template; 4, the heating-cooling cycle is repeated 20–40 times; 5, in each cycle, the newly synthesized DNA strands act as templates for the next replication thus producing more than a millionfold amplification of the original target sequence (from [175]).

Mini- and Microsatellites A considerable part of repeated (satellite) nuclear DNA consists of tandemly repeated copies of the socalled core units of two to several thousand base pairs in length. Insertion/deletion mutations (indels) generated by slipping and mispairing of DNA strands at replication and by unequal crossing over alter the repeat number, i.e., the total length of the multicopy sequence [31]. This variation observed in different chromosomes and individuals was termed VNTR (variable number of tandem repeats). In such tandem repeat families, the attention of researchers is focused on minisatellites consisting of repeated copies (motif) of nine–ten to hundred base pairs each [32, 33] and microsatellites whose copies are typically one to four, sometimes six nucleotides in length [34, 35]; the latter are sometimes designated SSR (simple sequence repeat) or STR (short tandem repeat). A minisatellite locus can contain two to several hundred repeats; microsatellite locus, ten to a hundred repeats. A hypothesis on the evolutionary origin of minisatellites from microsatellites has been advanced [36]. Individual alleles of these loci differ from one another by the number of tandemly repeated copies. Minisatellite loci are examined by restriction fragment hybridization with a multi- or single-locus probe, which is a nucleotide sequence complementary to the repeated “motif” sequence [37]. Individual microsatellite loci are analyzed by PCR using primers complementary to the unique sequences 2002

992

ALTUKHOV, SALMENKOVA Foreign DNA

Plasmid

Restriction endonuclease

TTAA

TT

AA

TT

AATT

Restriction endonuclease TTAA

AATT

AA

AAT

T TTA

A

TT A AA TTA

Ligase

TTAA AATT

Ligase

Ligase Host chromosome

Recombinant plasmids Bacterial cell Fig. 3. Sheme of cloning of a DNA fragment. Restriction fragment of a DNA molecule is joined by lygase to a preliminary cleaved plasmid. The plasmid is a nonchromosomal small circular DNA molecule of bacterial DNA or phage lambda DNA. The cleavage of the plasmid and foreign DNA is carried out by the same restriction endonuclease which provides complementation of the end sequences of the plasmid and DNA fragments and joining of their “sticky” ends. The recombinant construction enters the bacterial host where it replicates (from [13]).

(domains) flanking each microsatellite locus [38]. Then the “size” of its alleles is estimated in polyacrylamide gel electrophoresis by comparing it with a set of reference DNA fragments of known length. The following properties make these loci very suitable genetic markers having a great potential [16]: 1. Both types of loci are very numerous and dispersed throughout the genome. For instance, rough estimates of the numbers of microsatellites (GT)n and (CT)n in the genome of brown trout Salmo trutta are 109 000 and 33 000, respectively [39]. 2. These loci are mainly located in noncoding genome regions and, consequently, must be selectively neutral. This general rule probably has exceptions when the loci in question are closely linked to adaptive genes. Moreover, although precise functions of miniand microsatellites are unclear, some evidence testifies

to the fact that they act as coding or regulatory elements [40]; sometimes they were found inside exons and associated with diseases [41]. 3. These loci are characterized by rapid evolution. Spontaneous mutation rates of mini- and microsatellite loci are about 10–2 to 10–4 per locus per generation [42], which is far higher than in allozyme genes (about 10–5– 10–6) [30, 43]. Hence, if the divergence of (selectively neutral) allozyme genes is caused only by genetic drift, that of mini- and microsatellite loci must be caused by both drift and mutation [44]. Heterozygosity of minisatellite loci can be more than an order of magnitude higher than that of allozyme loci reaching almost 100% [15, 45] whereas microsatellites exhibit different polymorphism levels which are generally higher than the allozyme ones. 4. Microsatellites and single-locus minisatellites display codominant Mendelian inheritance (Fig. 4). 5. Microsatellites are identical in related species, which permits the use of the same primers and similar protocols. Note, however, that for creating primers in analysis of a new species microsatellites must be isolated de novo. A review of these methods and their more rapid and simplified combination are presented in a study by Zane et al. [46]. 6. Microsatellite analysis requires only a minute amount of blood or a tissue. Consequently, samples can be taken from a live animal (in fishes, for example, dry scales or otoliths can be used). 7. Automated microsatellite analysis is possible. Microsatellite loci are currently extensively used as genetic markers (see [38, 47] for a review). The level of their polymorphism can be seen from the summarized evidence for fishes and other animals given in Table 1. Compare these data with allozyme variation. According to Ward et al. [48], mean population heterozygosity for allozyme genes in 49 freshwater fish species is 0.046 ± 0.005; in 7 species of anadromous fishes, 0.052 ± 0.008; in 57 species of marine fishes, 0.059 ± 0.004; i.e., about an order of magnitude lower than that for microsatellite loci. Although allozymebased estimates usually also include monomorphic loci, this can hardly account for such a great difference. In a number of species the considerable difference in variation of allozyme and microsatellite loci may be associated with the fact that the restoration of genetic variability after a population or a species had passed a bottleneck occurs much faster in the case of microsatellite loci because of their high mutation rate. Conversely, allozyme loci retain traces of such demographic events far longer on historical scale. Because of this, some species are known to have very limited allozyme but high microsatellite variation [49]. Note that the ratios between the variation estimates in the above fish species groups are similar for both marker types. In view of DeWoody and Avise [50], these ratios are likely to reflect a similar response of both types of markers to greater effective population sizes and larger gene

RUSSIAN JOURNAL OF GENETICS

Vol. 38

No. 9

2002

DNA POLYMORPHISM IN POPULATION GENETICS

993

Table 1. Genetic variation at minisatellite loci in fishes and other animals (from [50]) Group of organisms Freshwater fishes Anadromous fishes Marine fishes Other animals

Number of loci Number of species 75 43 66 340

Number of individuals

13 7 12 46

7755 5393 6005 20567

Mean number Mean heterozygosiof alleles per locus ty of species for loci and per species 9.1 (6.1) 10.8 (7.2) 19.9 (6.6) 7.7 (4.6)

0.54 (0.25) 0.68 (0.12) 0.77 (0.19) 0.60 (0.16)

Note: Standard errors are given in parentheses.

exchange in the evolution of sea fishes which, as compared to freshwater fishes, inhabit more historically stable environment. This also may be caused by environmental conditions since sea water medium is selectively more neutral (homogeneous) than fresh water medium; in the latter, selection pressure must be stronger. Indeed, although the localization of micro- and minisatellite loci in the noncoding genome regions suggests their selective neutrality, several examples demonstrate that some of these loci do not always act as neutral, which may be explained by possible tight linkage with adaptive genes. In particular, such situation has been described for Semibalanus balanoides, in which the variation at two out of six microsatellite loci examined correlated with the latitudinal variation of two allozyme loci, and the selective character of the latter was revealed in special experiments [51]. Although the mutation mechanism in microsatellite loci is not yet completely clear, it is supposed to correspond to the model of single step mutation (also referred to as stepwise mode of mutation) [31, 52], which, as noted above, results in changing the tandem repeat number in the locus. Based on this model, new estimates of genetic distances and population-genetic structure have been established from microsatellite data ([23, 24, 53, 54]; for comparison of different measures, see [52, 55]). For instance, to estimate interpopulation divergence for microsatellites, Slatkin [24] introduced parameter RST, which is analogous to the Θ parameter of Weir and Cocherham [56]. RST differs from Θ in the fact that the former parameter accounts for the differences in the size of alleles rather than identity or nonidentity of allelic states as in the infinite allele model. The use of mini and microsatellite loci. The high mutation rate, great allele diversity and high heterozygosity in some cases attaining for minisatellites nearly 100% opens incomparable prospects for individual classification, particularly in forensic medicine (DNA fingerprinting) [15, 33, 45], for studies of induced mutagenesis [57–59], and for various studies in the fields of demography, ecology, and conservation biology [60]. Microsatellite markers often reveal genetic differentiation in the cases when allozyme markers fail to detect it, e.g., in organisms having low variation at allozyme RUSSIAN JOURNAL OF GENETICS

Vol. 38

No. 9

loci [61], in mobile marine fishes [62, 63], at the microgeographic scale, in closely related populations or ecological groups within a species [64–67]. Using these markers, the origin of introduced populations can be successfully determined [68, 69]. Statistical techniques and approaches has been developed for estimating from microsatellite variation the effects of passing a population bottleneck and the migration rates as well as identifying parentage and kinship among individuals (see [60, 70, 71] for review) and assigning individuals to particular populations [72–74]. Based on high allelic diversity of microsatellite loci, the progeny of concrete parents can be identified not only in the first but also in the subsequent generations. This opens new possibilities to examine reproductive success and fitness in individuals differing in biological and ecological characteristics. A particularly important point is that such studies are feasible not only in experimental but also in natural populations [75]. Using the possibility of determining with microsatellite markers the degree of kinship among experimental progeny, Mousseau et al. [76] proposed a novel method of estimating heritability of quantitative traits. This technique allows avoiding prolonged controlled artificial reproduction in such long-lived species as, for example, salmon, by obtaining and analyzing the offspring of spawners taken directly from the wild. Heritabilities estimated by these authors for several traits in chinook salmon from a natural population were in a good agreement with the heritability estimates obtained for salmon using classical methods of quantitative genetics. At the same time, we should like to note that microsatellite loci cannot be used in evolutionary reconstructions (phylogenies) at the interspecific and higher levels because the observed similarity in allele sizes may reflect the so-called homoplasy rather than the common descent. Homoplasy is caused by a high mutation rate, due to which microsatellite alleles of the same size are generated by convergence from different number of direct or reverse mutational events. Another problem of microsatellite analysis consists in the presence of null alleles, which appear by virtue of mutations at the primer binding site. This precludes accurate genotype identification; in addition, null alleles can differ in origin [77]. 2002

994

ALTUKHOV, SALMENKOVA FM a

a b c d e f

g

h

i j

k

kb 6.6 5.6

3.5

2.3 FM b

a b c d e f g h i

j

k

l m n o p q

kb 6.6

5.6 4.8

c

AC G T

AC G T 140

114

98

Fig. 4. Inheritance of minisatellite DNA loci and genetic variation of microsatellite DNA loci in salmonid fishes (electrophoretic analysis): (a) and (b), examples of minisatellite DNA profiles in brown trout detected with single-locus probes pStr-A3 (a) and pStr-A9 (b). In both cases, a brown trout family represented by a parental pair (M, male; F, female) and 11 (a–k) or 17 (a–q) progeny is shown. Male progeny are denoted by black points. DNA fragment size scale is given in kb (from [21]; reproduced with permission from Blackwell Science Ltd, Oxford). (c): PCR-amplified alleles of microsattelite locus Omy77 in several rainbow trout individuals. The size of each allele was estimated by reference to comigrating M13 sequence fragments (A, C, G, T) (from [176]; reproduced with permission from National Research Council of Canada). RUSSIAN JOURNAL OF GENETICS

Vol. 38

No. 9

2002

DNA POLYMORPHISM IN POPULATION GENETICS

Hedrick [12] has conclusively shown that extremely high variation of some microsatellite and similar DNA loci warrants caution in interpretation of the relevant results. This concerns the differentiation (which is underestimated) and genetic distances (which are overestimated) among groups since these estimates are greatly affected by heterozygosities of the highly variable loci. Furthermore, statistically significant intergroup differences at such loci, which are sometimes detected by powerful statistical tests, may be biologically meaningless [12]. RAPD and AFLP Unlike microsatellites or single-locus minisatellites used for examining individual genome loci, markers designated RAPD and AFLP, similarly to multilocus minisatellites, permit investigating the total genome by obtaining the appropriate fingerprints. For RAPD (random amplified polymorphic DNA) analysis, short (usually 10 to 20 nucleotides) primers with random DNA sequences are used. Anonymous DNA sequences are amplified in PCR and subsequently analyzed by electrophoresis. The number and size of the amplified fragments depend on the length and sequence of the arbitrary primer. The primer binding sites are randomly distributed throughout the genome, and polymorphism in such sites is expressed as the presence or the absence of the corresponding fragments in the gel [78]. AFLP (amplified fragment length polymorphism) analysis is based on selective amplification of fragments obtained by restriction of the genomic DNA. This method includes three stages: (1) DNA digestion (typically by two restriction enzymes) and binding sticky fragment ends with oligonucleotides adapters by a ligase; (2) selective PCR amplification of the set of restriction fragments; and (3) electrophoretic analysis of the amplified fragments. The nucleotide sequence of the adapter and an adjoining restriction site serves as a target for the annealing of the primer; the primer sequence complementary to the target is elongated at the 3' end by several arbitrary nucleotides. This permits to selectively amplify only the fragments whose restriction sites are flanked by the corresponding complementary nucleotides. Using this method and RAPD, particular sets of fragments (fingerprints) can be produced by PCR without previously knowing their nucleotide sequence. The fingerprint polymorphism is determined by the polymorphism of restriction sites and flanking nucleotides and is manifested as the presence or absence of particular bands in the gel. The method has high resolution and, in contrast to RAPD, good repeatability [79]. Both RAPD and AFLP markers exhibit Mendelian inheritance generally of a dominant type. However, if the progeny data are available, some codominant markers can also be revealed. These markers constiRUSSIAN JOURNAL OF GENETICS

Vol. 38

No. 9

995

tute 2–3% of all RAPD markers in plants [80] and 4–15% of all AFLP markers in various organisms [79]. In their new modifications, RAPD and AFLP are combined with PCR of microsatellites; the corresponding modifications are referred to as RAMP (randomly amplified microsatellite polymorphism) [81] and microsatellite AFLP, or SAMPL (selective amplification of microsatellite polymorphic loci) [77, 82]. These combinations permit working with a great number of codominant microsatellite markers. RAPD and AFLP markers are supposed to be located mostly in the noncoding DNA regions since these regions constitute an overwhelming part of the eukaryotic genome. Mutation rates in noncoding DNA are about two times higher than in its coding part [30]. In addition, RAPD (and possibly AFLP) markers are sometimes amplified from the repetitive DNA regions [77] and can thus reflect high rates of their mutation. Application of RAPD and AFLP markers. Since by RAPD and AFLP methods one can obtain numerous (up to several hundred) markers dispersed throughout the genome, these markers are particularly suitable for constructing genetic maps [81] or linkage maps with quantitative trait loci (QTL), for instance, with loci for commercially important traits (see review in [80]). This review also considers the use of AFLP markers for studies on systematics and biodiversity, population and conservation genetics as well as for individual identification and kinship analysis. (The above discussion to some extent also refers to RAPD markers although the latter are not always reproducible and tend to produce artifacts). AFLP markers proved to be very helpful for detecting hidden variation in lines and closely related species that could not be discriminated on the basis of morphology or using other molecular methods. Using these markers to analyze phylogenetic relationships for higher taxa is thought to be problematic because of very high variation of these markers. Nevertheless, a study of RAPD fingerprints of several conifer species has revealed, along with RAPD markers exhibiting intraspecific variation, invariant markers that lacked individual and geographic variability but differentiated species within the genus [83]. It was suggested to distinguish this DNA (termed random amplified monomorphic DNA, or RAMD) from polymorphic DNA and regard the former as the manifestation of genetic monomorphism, which had been discovered earlier for protein markers, at the DNA level [84–86]. These species-specific RAMD markers may be common among other organisms and helpful in solving taxonomic issues. Mitochondrial DNA Mitochondrial DNA (mtDNA) of vertebrates can be formally classified as repeated DNA, since a cell can contain hundreds of mitochondria, and each mitochondrium can have from two to ten copies of DNA mole2002

996

ALTUKHOV, SALMENKOVA

cytb

tRNAthr

tRNApro ORI(H)

tRNAglu

tRNAphe 12S rRNA tRNAval

ND6

16S rRNA ND5 tRNAleu tRNAleu ND1

tRNAser tRNAhis

12000

16569 bp

4000 tRNAile tRNAgln tRNAF-met ND2

ND4

ND4L tRNAarg ND3 tRNAgly COIII ATPase6 ATPase8

tRNAtrp tRNAala tRNAasn ORI(L) tRNAcys

8000

tRNAtyr COI COII tRNAlys

tRNAser tRNAasp

Fig. 5. Scheme of a circular molecule of human mitochondrial DNA. Genes shown in dark gray code for the following proteins: three subunits of cytochrome c oxidase (COI, COII, COIII), cytochrome b (cytb), subunits 6 and 8 of the ATP-ase complex and subunits of the NADH-dehydrogenase complex (ND1–ND6). Genes coding for different ribosomal RNAs (rRNAs) are shown in light gray; narrow segments indicate transport RNA (tRNA) genes; they flank regions of protein-coding genes. Two RNAs are transcribed clockwise from the heavy (H) chain as a template; the transcripts are shown by wavy lines within the circle. The short transcript produces rRNA, and the long one, mRNA and most of tRNAs. Only one full-size transcript is synthesized on the light (L) chain. The regions shown with dots—ORI (H) and ORI(L)—are origin of DNA replication. The 5' to 3' direction on the sense chain of different genes is indicated by arrows (from [87]).

cules. DNA of human and animal mitochondria is a closed circular molecule (Fig. 5) of the size typically not exceeding 20 000 bp. In plants, cells of one plant sometimes have mtDNAs of different sizes (from several hundred to several thousand base pairs), which are represented by both circular and linear molecules; in very large mitochondrial genomes, the greatest part of redundant DNA consists of noncoding sequences [87]. In what follows, we restrict our discussion to animal mtDNA. Complete sequencing of mtDNA in vertebrates revealed 37 genes (2 ribosomal genes, 22 genes for transport RNAs, and 13 protein-coding genes) and noncoding control region that participates in replication and is referred to as the D-loop [88]. The control region consists of the central conserved sequence, usually flanked by polymorphic domains containing tandem repeats of four to several hundred base pairs. Tandem repeats of mtDNA are frequently highly polymorphic,

varying in number not only among individuals but, in some organisms, even within an individual causing heteroplasmy [89], i.e., the presence of different mtDNAs in one individual. MtDNA is transmitted to the progeny with the cytoplasm, i.e., it is haploid and strictly maternally inherited. This DNA mostly lacks recombination (rare cases of heteroplasmy in higher organisms are analogous to ordinary somatic mosaicism but currently the possibility of recombination is under discussion; see [90, 91]) and displays clonal inheritance. Hence, although mtDNA contains more than 30 different genes, in terms of formal genetics it is regarded as one locus, and mtDNA haplotypes are considered alleles of this locus or separate clones. Correspondingly, the effective population size for mtDNA is equal to 1/4 of the analogous estimate for nuclear genes [92]. Because of this, mtDNA variation is more subjected to random gene drift and the bottleneck effect upon a

RUSSIAN JOURNAL OF GENETICS

Vol. 38

No. 9

2002

DNA POLYMORPHISM IN POPULATION GENETICS

997

Vysokogornyi 108 553 574

Rishiri 243

339 477

624 144 592

Shiretoko Yufutsu

Poronaisk Furano Haboro Sarobetsu

292

Akkeshi

444

Samani

219

Nikolaevsk-na-Amure 53 438

42

Nevel’sk

Busse Starodubskoe Urozhainoe

Rebun Teshikaga

151 315 579 438

Magadan 519

Chelomdza Fig. 6. Phylogenetic relationships among 14 haplotypes identified by nucleotide sequences (630 nucleotides) of the mitochondrial cytochrome b gene in 19 individuals of Sorex gracillimus. Open circles indicate undetected putative haplotypes; shaded circles indicate haplotypes found in the marked localities. The numerals by the short lines on the branches show nucleotide substitution positions (from [177]; reproduced with permission from Blackwell Science Ltd, Oxford).

drastic decrease in population size. Moreover, the rate of nucleotide substitutions in the mitochondrial genome is at least 5 to 10 times greater than in nuclear genome [93]. Consequently, the divergence of mtDNA, which is caused by more intense mutation and drift, must be higher than in nuclear allozyme genes. The mutation rate is maximum in the D-loop, mostly in its hypervariable segment I (HVI; see [94]). In addition, the high polymorphism of the tandem repeat number in the control mtDNA region observed in some species implies the mutation rate of 10–2 [95] but this is not recorded in all species [96, 97]. The mutation rate in RNA genes is minimal. The average nucleotide substitution rate in mtDNA of different organisms is 1–2% per million years [98, 99]. Application of mitochondrial DNA. Due to the features of inheritance and variation described above, mtDNA is widely and successfully used in various studies of evolution and phylogeny [100–103], in analysis of population structure and historical biogeography (phylogeography) of the species [94, 104–106], in analyses of hybridization, introgression of mitochondrial genome, consequences of introduction and acclimatization ([104, 107–109], and many others). Note also that the traces of former isolation of populations are preserved in mtDNA longer than in nuclear DNA. Furthermore, if males of a given species during reproduction migrate more often than females, the population divergence may not manifest in allozyme variation but will be expressed in maternally inherited RUSSIAN JOURNAL OF GENETICS

Vol. 38

No. 9

mtDNA. With equal migration of both sexes, the fourfold greater migration exchange is required to prevent divergence in mtDNA as compared to nuclear genes [107]. An important property of mtDNA lies in the fact that, in contrast to allozyme and VNTR alleles, mtDNA haplotypes can be linked together by a series of consecutive evolutionary transformations. This refers to the minimum number of stepwise mutational changes required for transformation of haplotypes via the appearance/loss of restriction sites or any other alterations of the primary sequence (Fig. 6). Having the data on all used restriction endonucleases or on the nucleotide sequence, a phylogeny (genealogy) of the complex haplotypes can thus be constructed with the use of specially designed computer programs [110, 111]. The molecular distances between mtDNA haplotypes can be included in the estimates of genetic differentiation [112]. Based on the haplotypes phylogeny, additional information on genetic relatedness and historical relationships among species and populations can be obtained. Y-Chromosomal DNA The use of mtDNA polymorphism in evolutionary studies is well supplemented by analysis of Y-chromosomal DNA polymorphism since it provides information both on the maternal and paternal contributions to the evolutionary process [113]. Due to haploidy, the Y chromosome mostly lacks meiotic recombination 2002

998

ALTUKHOV, SALMENKOVA

being transferred from father to son as an integral entity. Hence, each particular set of loci making up the nonrecombining part of the Y chromosome (NRY) is regarded as one haplotypes [114]. Upon the equal numbers of males and females, the total number of Y chromosomes in a population is equal to one-fourth of the copy number of any autosome, and, consequently, the effective population size inferred from the Y chromosome must be equal to one-fourth of the analogous value for the autosomes. In addition, the effective population size in this case is reduced due to high variability of the progeny number in males [114, 115]. The relatively lower level of Y-chromosomal DNA polymorphism is related to the lower effective size and positive selection on NRY [116]. This polymorphism is represented by (1) unique point mutations (10–9 per base pair per year) or, for example, an insertion of the Alu sequence (one of the types of dispersed repeats in the genome) [117] and (2) polymorphism of micro- and minisatellite sequences of Y-chromosomal DNA (with the mutation rate of 10–2–10–3 per locus per generation (see [114]). Due to the absence of the “shattering” effect of recombination in the main segment of the Y chromosome and to the fourfold smaller effective size, the historic changes in the corresponding DNA molecule are easier to trace than in autosomal DNA [115]. For this reason, Y-chromosomal DNA is a unique, paternally inherited genetic system, which is particularly successfully used in such fields as the origin and evolution of humans, migration, and genetic contacts of populations [113, 118]. For instance, in the native human populations, males generally more often stay at the place of their birth than females (so-called patrilocality), which is expressed in more pronounced geographical and probably social clustering of Y-chromosomal variants (see [115]). Patrilocality explains a type of differentiation frequent in human populations: high diversity in mtDNA and low diversity in Y-chromosomal DNA within groups but great differences in Y-chromosomal DNA and small differences in mtDNA among groups [119]. Interestingly, exactly these and directly opposite pictures of genetic differentiation were recorded in two different groups of tribes (villages) in North Thailand, which differed in the fact that in one group, men, and in the other, women, were traditionally more settled [120]. The Y chromosome determines male sex via the effect of one gene, SRY (sex-determining region Y) [121]. In addition, numerous genes participating in the key cell processes have been detected in this chromosome [122]. Consequently, selection must play an important role in the formation of haplotypic diversity of the Y chromosome in populations. The discovery of numerous polymorphic DNA markers on the Y chromosome has initiated extensive investigation of the possible role of various haplotypes in diseases, particularly their relation to sterility and oncology [115].

SNP SNP, or single nucleotide polymorphism, is a polymorphism of a single nucleotide site. As a rule, it is represented by two allelic variants (substitutions) of a single nucleotide in a DNA sequence. At present, due to the improvement and automation of sequencing procedure, the development of DNA microarrays [123], and other analytical methods, these markers are extensively studied in the human genome [124] for detecting their association with different complex diseases [125–127], for understanding various aspects of genetic differentiation of populations and evolution of humans [128]. According to Cargill et al. [125], the SNP number per gene in humans ranges from zero to 29, while the coding gene sequences on average contain four polymorphic sites (cSNPs). A typical individual must be heterozygous at about 24 000–40 000 nonsynonymous (i.e., altering an amino acid in an encoded protein) substitutions. According to Halushka et al. [126], the total human genome contains approximately one million SNPs, of which about 500 000 are noncoding, 200 000, synonymous coding, and 200 000, nonsynonymous coding ones. Based on SNPs in 75 studied human genes recalculation of mean heterozygosity for proteins produced the estimate of 17% [126], which exceeds the value summarized by Nevo et al. [6] from several sources (12.5%). Some features of the main polymorphic DNA markers are presented in Table 2. Below, we briefly discuss other marker types that are of more limited utility. EST, STS EST (expressed sequence tag) is polymorphism of the expressed, coding genomic sequences also referred to as ESTR. These are usually fragments or total sequences of complementary DNA, which is obtained with reverse transcriptase from mRNA isolated from various tissues and representing the genes expressed in these tissues [129]. Using the EST sequences, PCR primers are generated to amplify EST from the individual genomic DNA; then, polymorphism of this DNA is examined by means of some methods of amplification product analysis. These markers are very often employed in genetic mapping. In particular, they were used to identify several genes in the human genome [130], to determine many candidate genes for complex diseases [131]. In plants and animals, these markers are used as candidate genes for analysis of QTL controlling adaptive or productive traits [129]. ESTs constitute an important component of the DNA microarray method, which has been currently intensely developed. This method opens unprecedented perspectives in various areas of genomics and in investigation of molecular bases of evolution and ecology (see [123, 129] for review).

RUSSIAN JOURNAL OF GENETICS

Vol. 38

No. 9

2002

DNA POLYMORPHISM IN POPULATION GENETICS

999

Table 2. Types of DNA polymorphism (from [13] with modifications) Variation type

Cause of polymorphism

Detection methods

Restriction fragment length polymorphism (RFLP)

Nucleotide differences in Cleavage of double-stranded DNA by rerestriction sites striction enzymes; electrophoresis; vizualization of fragments by Southern blotting with a DNA probe or ethidium bromide staining. Used for analysis of genomic DNA, mtDNA, or their individual segments Minisatellites (vary- Varying number of tan- DNA cleavage by restriction enzymes; ing number of tandem demly repeated nucleSouthern blotting with a specific DNA repeats, VNTR) otide DNA sequences probe complementary to the repeated sequence. Multilocus probes are complewith repeat size of 10– 100 nucleotides mentary to repeats commonly occurring in the genome; single-locus probes, to rare and unique repeats Microsatellites (single tandem repeats, STR; simple nucleotide repeats, SSR)

Varying number of short repeated nucleotide DNA sequences with repeat size of 1–6 nucleotides

Randomly amplified polymorphic DNA fragments (RAPD)

Nucleotide differences in PCR amplification of random DNA segsites of binding primers ments using short (10–20 nucleotides) primers with arbitrary nucleotide sequence; electrophoresis of the amplification products Nucleotide differences in Restriction, typically by two restriction restriction sites and flank- enzymes recognizing frequent and rare ing sites restriction sites; linking of nucleotide adapters by ligase; selective PCR amplification; electrophoresis Substitutions of single Sequencing of PCR-amplified DNA segnucleotides in a DNA se- ments; hybridization of labeled PCR quence products with microarrays of DNA probes for detection of variants; denaturation of PCR products at critical temperatures and heteroduplex analysis; denaturation fluid chromatography, etc.

Amplified fragment length polymorphism (AFLP)

Single-nucleotide polymorphism (SNP)

PCR amplification with primers complementary to the unique sequences flanking the repeat family; electrophoresis of the amplification products

STS (sequence tag sites) markers are simpler and dispersed throughout the genome. They are represented by short, PCR-amplified genomic sequences. These markers are widely used for physical mapping of the human genome and analysis of human polymorphism [124]. SINEs and LINEs SINEs and LINEs (short and long interspersed elements) are repeated, unblocked, and dispersed throughout the genome sequences [132]. They also can serve as genetic markers. These sequences represent retroposons, i.e., included in the genome transcripts of intracellular RNA. They constitute more than 20% of the genome of humans and other mammals [133]. SINEs turned out to be very useful markers for phylogenetic analysis because species exhibit variation in the genomic localization of SINE inserts [134]. RUSSIAN JOURNAL OF GENETICS

Vol. 38

No. 9

Fields of application Population genetics, systematics, phylogeny, genetic mapping, QTL

Population genetics (single-locus polymorphisms); multilocus polymorphisms are effective for identification of individual genotypes, for estimation of kinship and pedigree analysis, for studying induced mutation process Population genetics, evolutionary, demographic, and ecological genetics; identification of kinship and population assignment, genetic mapping Population genetics, systematics, phylogeny. Identification of plant cultivars and animal breeds, genetic mapping, QTL Population genetics, systematics, phylogeny, identification of individual genotypes, analysis of kinship and pedigrees, genetic mapping, QTL Evolutionary and population genetics; genetic mapping; particularly often used in studying SNP associations with diseases

Note that the markers considered above reflect main types of DNA polymorphism but do not exhaust their continually extending list (see, e.g., [38, 47]). The dramatic progress in methods of molecular biology, including automation and computerization of different procedures, the development of the appropriate statistical techniques and software, the creation of available databases required for DNA polymorphism studies promote the growth of the arsenal of molecular markers and their ever increasing use in diverse fields of fundamental and applied biology including evolutionary, ecological, and population genetics. SELECTIVE CONSTRAINTS OF DNA VARIATION As in the case of biochemical population genetics, whose development was based on hereditary protein polymorphism, molecular population genetics is at 2002

1000

ALTUKHOV, SALMENKOVA

present ready to tackle the problem of the role of selection in maintenance of polymorphism of various DNA segments in the eukaryotic genome. Indeed, as shown by comparing mtDNA sequences of different species, the amount of variation in mitochondrial genes is selectively constrained by the amino-acid composition and function of their protein products [135, 136], and the gene position relative to the replication origin on the heavy strand [137]. An analysis of the variation distribution in nucleotide sequences using various neutrality tests has shown deviations from neutrality for mtDNA of genes ND5 and cytb in Drosophila, ND3 in mouse, ND3 and COII in human and chimpanzee (see [138]). The detection of mutations, duplications, deletions, and inversions in mtDNA of human carriers of various maternally inherited diseases also testifies to non-neutrality of mtDNA [139]. Apparently, there are selective constraints on the limiting size of the mtDNA molecules, i.e., on the tandem repeat number in its control region determining size variation of the total molecule [140]. MtDNA codes for 13 polypeptides, which, together with the numerous peptides encoded by nuclear genes, constitutes the respiratory chain, that is, the system of electron transport functioning in mitochondria. Because of this, mtDNA variation can significantly affect metabolism, and, consequently, fitness of the organism. The functional association among all these proteins must be maintained by strict selection for the concerted interaction of the mitochondrial and nuclear genomes, i.e., their coadaptation [141]. The mitochondrial genome must be a leading component of such coadaptation since the mtDNA mutation rate is higher than the nuclear one. The discovery of numerous SNPs in the human genome has made possible to identify the effect of selection on this polymorphism. In turn, this will permit explanation of molecular differences among species and determination of functional significance of different genomic regions. Let us briefly consider some approaches to detecting selection on the basis of molecular data. Based on the neutrality theory of molecular evolution [142, 143], various statistical tests have been designed that permit to evaluate deviations from the theory predictions as a possible evidence for selection (see, e.g., [144]). Reviewing these tests, Nielsen [145] distinguished among them two major groups: (1) tests based on allele distributions or levels of variation and (2) tests based on comparing divergence among different mutation classes within a locus, such as synonymous (i.e., silent, not changing the amino-acid sequence of the encoded protein) and nonsynonymous (changing the amino-acid sequence) nucleotide substitutions. Deviations from the neutrality theory detected by the first group of tests may be explained not only by selection but also by certain demographic factors (a reduction or growth in the population size or population subdivision) but tests of the second group clearly indi-

cate operation of selection [145]. As shown by analyzing SNP frequencies in human gene samples, nucleotide variation in coding gene regions is considerably limited at the sites whose replacements change the amino-acid sequence of the protein molecule. These sites also exhibited a significant excess of rare alleles. In all, this suggests the action of stabilizing (purifying) selection against nonsynonymous SNPs, especially those producing nonconservative amino-acid alterations [125, 127, 146]. According to calculations of Halushka et al. [126], who examined SNPs in 75 human genes, purifying selection together with genetic drift eliminate 62% of nonsynonymous SNPs. Some noncoding DNA regions (e.g., nontranslated sequences flanking the coding gene regions) perform important regulatory functions, and their mutations must be eliminated by strong selection. Indeed, variation, i.e., SNP frequency in such sequences, turned out to be several times lower than in degenerate sites of the coding region, where any substitution is synonymous and the level of variation was the highest and comparable to the neutral one [125, 146]. In our view, the problem of selection at the population level can be most successfully resolved on the basis of advances in biochemical genetics of populations. During 30 years of the existence of this field of genetics, not only the evidence on the selection effect on polymorphism at diverse allozyme loci has been obtained but also an approach to the estimation of functional loading of genes has been established. The latter involves comparing parameters of the observed spatial genetic differentiation ( F ST0 or G ST0 ) with the theoretically expected values ( F STe or G STe ). This was possible due to the unique information on such key demographic parameters as effective population size Ne and the coefficient of gene migration m in native human population [147–150] and a number of zoological species [8, 150, 151]. Under the conditions of stationary or quasi-stationary selectively neutral genetic process, the actual value of F ST0 or G ST0 averaged over a set of independent loci is identical with the theoretically expected F STe or G STe value obtained from the demographic data. At the same time, individual enzyme genes behave differently depending on their functional loading. If the gene is selectively neutral at the given time and in the given part of the range, F STi is approximately equal to F ST0 . If the polymorphic gene is subject to stabilizing selection, F STi < F ST0 , whereas at disruptive or directional selection, F STi > F ST0 . The method of comparing standardized gene frequency variances F STi for individual loci with the variance expected at selective neutrality based on demographic parameters Ne and m, can be applied to both protein and DNA loci, except such

RUSSIAN JOURNAL OF GENETICS

Vol. 38

No. 9

2002

DNA POLYMORPHISM IN POPULATION GENETICS

highly variable ones as many microsatellites and other loci with similarly high variation level [12]. It is not surprising that in the case of an intact structured gene pool reproducing in an optimal environment, the coefficient of local genetic differentiation averaged over many allozyme genes ( F ST0 ) corresponds to the expected one ( F STe ) for the selectively neutral process and virtually cannot be distinguished from the F ST0 value based on polymorphisms of random DNA fraction samples from the eukaryotic genome. This regularity found in the studies of human populations based on numerous DNA markers [152, 153] and 20 immunobiochemical polymorphic systems [148] was first pointed out by Rychkov and Balanovskaya [154]. Analogous data obtained for a wide range of animal and plant species were much later tabulated by Allendorf and Seeb [10] who did not attribute to them due significance. However, in the results reported by the latter authors, the levels of local differentiation for protein and DNA markers in 12 out of 16 species examined completely coincided, while only four cases showed any discrepancy (see Table 6 in [10]). For instance, the FST values for proteins and DNA coincided in Atlantic salmon Salmo salar (proteins = VNTRs [155]), maize Zea mays (RFLP = proteins [156]), spruce Pseudotsuga menziensii (RAPDs = proteins [157]), red ant Solenopsis invicta (RAPDs = VNTRs = proteins [158]), sea beet Beta vulgaris ssp. maritima (scnRFLPs = proteins [159], etc. As to the discrepancies, they should be explained by sampling errors (different participation of various marker groups in the samples from the populations examined) or, probably more often, the prevalence of one of the above marker groups in the examined sample of protein markers. Apparently, in the case of an excess of overdominant protein loci, genetic differentiation of the species is characterized by considerable spatial similarity or even uniform frequencies of the corresponding alleles against the background of marked local differentiation of subpopulations at DNA loci. This is exemplified by the data obtained for cod Gadus morhua (RFLPs > proteins [160]), pine Pinus flexilis (RAPDs > proteins [161]), and oyster Crassostrea virginica scnDNA > proteins [162]). Only in one case, that of the common toad Bufo bufo, the pattern was reversed (proteins > VNTRs [163]). In view of the population structure of the latter species, this can be explained by a contribution of diversifying selection. An example of interpreting uniform allozyme frequencies in Pacific pink salmon as a result of stabilizing selection has been discussed earlier [4, 150, 151, 164]. It is stabilizing selection acting simultaneously on numerous loci that is responsible for the uniformity (or close similarity) of allele frequencies on the ranges of diverse species, which is characteristic, e.g., for Pacific pink salmon [4, 9, 150], populations of Drosophila RUSSIAN JOURNAL OF GENETICS

Vol. 38

No. 9

1001

pseudoobscura [165], cod Gadus morhua [160], and a number of other species, particularly conifers [166, 167]. In all cases, the gene frequencies are “skewed,” i.e., the most common alleles of allozyme loci occur at the frequencies that are very far from the intermediate ones, when the segregation load reaches maximum [164]. Apparently, in these cases excessive migration is absolutely excluded (see [168–170] for comparison) since selection only masks the subpopulation structure of the species, which can be easily revealed by analyzing morphobiological traits or by enlarging the marker sample through inclusion of selectively neutral genes (see [9] for details). An example of this situation is provided by the studies of cod Gadus morhua and sea beet Beta vulgaris in which RFLP analysis of nuclear DNA revealed spatial heterogeneity of allele frequencies. The very expressive pattern was revealed in Beta vulgaris via approximating the observed allozyme and DNA marker data by the model of isolation by distance (Fig. 7). Based on longterm analysis of mtDNA polymorphism in pink salmon, not only interpopulation but also intrapopulation heterogeneity of haplotype frequencies was found [171, 172]. In all, new data of molecular genetics support the general conclusions of studies [4, 8, 147–150, 154, 173] that were based on immunobiochemical polymorphism and contributed to the understanding of the role of balancing selection in maintaining this variation in human, plant, and animal populations. Only very recently, in connection with the development of molecular evolutionary genetics, these issues have attracted attention of our Western colleagues. The very title of a paper [174] published in Proc. Natl. Acad. Sci. USA in January 2001 (“Order emerging from chaos in human evolutionary genetics”) is significative. The author of this study arrives at the conclusion that polymorphisms maintained by balancing selection can also occur at the DNA level. However, for us it is clear that the genetic differentiation that only on average corresponds to selective neutrality (here M. Kimura was right) is accompanied by oppositely directed selective processes, which normally promotes stabilization of the species. This mode of reproduction of the species gene pool, when the ration between the intra- and intergroup components of variation remains constant, was termed normal. It provides a natural reference point in the estimation of population-genetic dynamics upon various environmental impacts [8]. Note also that if selective values of different groups of genes are unclear, gross errors in phylogenetic reconstructions may ensue because the estimates of genetic distances (time of divergence) may be biased, “constricting” in the case of overdominant genes and “extending” when loci subject to disruptive selection prevail in the sample under study (see, e.g., [174]). 2002

1002

ALTUKHOV, SALMENKOVA logNm

(a) Y = 0.426 + 0.003X; R2 = 0

logNm

1.0

(b) Y = 1.05 – 0.822X; R2 = 398

1.5

0.5

0.5

0 –0.5 0

0.5

1.0

logD

0

0.5

1.0

logD

Fig. 7. Linear regressions of logarithm (log) of gene flow Nm (estimated from isozyme of RFLP data) against log of distance between all population pairs in sea beet Beta vulgaris. P (probability of the null hypothesis, Mantel’s test) = 0.4913 for isozymes (a) and 0.0006 for RFLP (b) (from [159]; reproduced by permission of the Nature Publishing Group).

CONCLUSION In closing, we give a brief summary of the relationship between biochemical population genetics born 35 years ago and new molecular population genetics that has experienced a tremendous growth in the past decade. It is clear that the use of tools with higher resolving power revealing variation at the level of nucleotide DNA sequences allows the researchers to tackle the issues that would remain unresolved only on the basis of protein polymorphism analysis. First, mtDNA polymorphism permits to trace the dispersal pathways of species and populations via analyzing spatial haplotype distributions, successfully reveal the results of isolation and hybridization of populations or species and gene introgression, determine differential migration of sexes (together with DNA analysis of the Y-chromosomal or other nuclear genes). Based on the clonal mode of mtDNA inheritance and the nonrecombining part of the Y chromosome, genealogy of the corresponding genotypes can be constructed providing a possibility to develop our knowledge of the origin and evolution of human and other species. Second, the use of mini- and microsatellites has opened a unique possibility for solving a number of demographic and ecological problems, issues of individual identification and population assignment, reconstruction of pedigrees, estimation of kinship and family structure, when a reproductive contribution of parents into the progeny gene pool, and, consequently, genotype fitness can be accurately determined. Due to high spontaneous mutation rates, the minisatellite system may prove to be very convenient for estimating the rates of mutation induced by radiation or chemical environmental pollution. Third, unprecedented possibilities have been opened by the use of DNA markers for genetic mapping and marking of loci that are linked or tightly associated with diseases and adaptive or commercial traits.

Nevertheless, we should like to emphasize that in understanding specific genetic processes occurring upon the reproduction of population gene pools in time and space, molecular genetics is far behind biochemical genetics as the latter field is more mature with regard to methodology; the general conclusions reached by biochemical genetics were considered in Introduction to the present paper. Regardless, the joint use of protein and various DNA markers already to date allows researchers to obtain principally new information on intraspecific genetic differentiation, at least in estimation of the role of natural selection in maintaining genetic polymorphism and in more accurate description of both population and social structure of the species, which is of considerable importance for ecology and population and conservation biology. In not so distant future, we expect more profound and organic penetration and merging of researches using the approaches of biochemical and molecular genetics as well as genetics of quantitative characters. ACKNOWLEDGMENTS We thank V.T. Omel’chenko for his help in preparing the manuscript. This work was supported by the Russian Foundation for Basic Research (grant nos. 99-04-48591, 02-04-49224), the Russian State Program “Leading Scientific Schools” (grant no. 00-15-97914), and the Program of the Russian Academy of Sciences “Regulatory Mechanisms of Functioning and Development of Organisms.” REFERENCES 1. Altukhov, Yu.P., Korochkin, L.I., and Rychkov, Yu.G., Genetic Biochemical Diversity in Evolution and Individual Development, Genetika (Moscow), 1996, vol. 32, no. 11, pp. 1450–1473.

RUSSIAN JOURNAL OF GENETICS

Vol. 38

No. 9

2002

DNA POLYMORPHISM IN POPULATION GENETICS 2. Rychkov, Yu.G., Zhukova, O.V., Sheremet’eva, V.A., et al., Genofond i genogeografiya narodonaseleniya (Gene Pool and Gene Geography of Population: 1. Gene Pool of Populations of Russia and Contiguous Countries), Rychkov, Yu.G., Ed., St. Petersburg: Nauka, 2001. 3. Manchenko, G.H., Handbook of Detection of Enzymes on Electrophoretic Gels, Boca Raton: CRC, 1994. 4. Altukhov, Yu.P., Geneticheskie protsessy v populyatsiyakh (Genetic Processes in Populations), Moscow: Nauka, 1983. 5. Sozinov, A.A., Polimorfizm belkov i ego znachenie v genetike i selektsii (Protein Polymorphism and Its Importance for Genetics and Breeding), Moscow: Nauka, 1985. 6. Nevo, E., Beiles, A., and Ben-Shlomo, R., The Evolutionary Significance of Genetic Diversity: Ecological, Demographic, and Life-History Correlates, Evolutionary Dynamics of Genetic Diversity, Mani, G.S., Ed., Berlin: Springer-Verlag, 1984, pp. 13–213. 7. Ward, R.D., Skibinski, D.O.F., and Woodwark, M., Protein Heterozygosity, Protein Structure and Taxonomic Differentiation, Evolutionary Biology, Hecht, M.K., et al., Eds., New York: Plenum, 1992, vol. 26, pp. 73– 159. 8. Altukhov, Yu.P., Intraspecific Genetic Diversity: Monitoring and Principles of Conservation, Genetika (Moscow), 1995, vol. 31, no. 10, pp. 1331–1357. 9. Altukhov, Yu.P., Salmenkova, E.A., and Omel’chenko, V.T., Populyatsionnaya genetika lososevykh ryb (Population Genetics of Salmonids), Moscow: Nauka, 1997. 10. Allendorf, F.W. and Seeb, L.W., Concordance of Genetic Divergence among Sockeye Salmon Populations at Allozyme, Nuclear, DNA, and Mitochondrial DNA Markers, Evolution, 2000, vol. 54, no. 2, pp. 640– 651. 11. Beaumout, M.A. and Nichols, R.A., Evaluating Loci for Use in the Genetic Analysis of Population Structure, Proc. R. Soc. London, B, 1996, vol. 263, pp. 1619– 1626. 12. Hedrick, P.W., Highly Variable Loci and Their Interpretation in Evolution and Conservation, Evolution, 1999, vol. 53, no. 2, pp. 313–318. 13. Vogel, F. and Motulsky, A.G., Human Genetics: Problems and Approaches, Berlin: Springer-Verlag, 1997, 3rd ed. 14. Southern, E.M., Detection of Specific DNA Fragments Separated by Gel Electrophoresis, J. Mol. Biol., 1975, vol. 98, pp. 503–517. 15. Jeffreys, A.J., Royle, N.J., Wilson, V., and Wong, Z., Spontaneous Mutation Rates to New Length Alleles at Tandem Repetitive Hypervariable Loci in Human DNA, Nature, 1988, vol. 332, pp. 278–281. 16. Wright, J., DNA Fingerprinting in Fishes, Biochemistry and Molecular Biology of Fishes, Hochachka, P. and Mommsen, T., Eds., Amsterdam: Elsevier, 1993, vol. 2, pp. 57–91. 17. Jin, L. and Chakraborty, R., Estimation of Genetic Distance and Coefficient of Gene Diversity from SingleProbe Multilocus DNA Fingerprinting Data, Mol. Biol. Evol., 1994, vol. 11, pp. 12–127. RUSSIAN JOURNAL OF GENETICS

Vol. 38

No. 9

1003

18. Lynch, M., The Similarity Index and DNA Fingerprinting, Mol. Biol. Evol., 1990, vol. 7, pp. 478–484. 19. Bentzen, P., Harris, A.S., and Wright, J.M., Cloning of Hypervariable Minisatellite and Simple Sequence Microsatellite Repeats for DNA Fingerprinting of Important Aquacultural Species of Salmonids and Tilapia, DNA Fingerprinting Approaches and Applications, Burke, T., Dolf, G., Jeffreys, A.J., and Wolf, R., Eds., Birkhauser, 1991, pp. 243–262. 20. Heath, D.D., Iwama, G.K., and Delvin, R.H., DNA Fingerprinting Used to Test for Family Effects on Precocious Sexual Maturation in Two Populations of Oncorhynchus tshawytscha (Chinook Salmon), Heredity, 1994, vol. 73, pp. 616–624. 21. Prodohl, P.A., Taggart, J.B., and Ferguson, A., Single Locus Minisatellite Variation in Brown Trout, Salmo trutta L., Populations, Genetics and Evolution of Aquatic Organisms, Beaumont, A.R., Ed., London: Chapman and Hall, 1994, pp. 263–270. 22. Taggart, J.B. and Ferguson, A., Hypervariable Minisatellite DNA Single Locus Probes for the Atlantic Salmon, Salmo salar L., J. Fish Biol., 1990, vol. 37, pp. 991–993. 23. Goldstein, D.B., Linares, A.R., and Cavalli-Sforza, L.L., An Evaluation of Genetic Distances for Use with Microsatellite Loci, Genetics, 1995, vol. 139, pp. 463–471. 24. Slatkin, M., A Measure of Population Subdivision Based on Microsatellite Allele Frequencies, Genetics, 1995, vol. 139, pp. 457–462. 25. Zhivotovsky, L.A. and Feldman, M.W., Microsatellite Variability and Genetic Distance, Proc. Natl. Acad. Sci. USA, 1995, vol. 92, pp. 11 549–11 552. 26. Mullis, K., Faloona, F., Scharf, S., et al., Specific Enzymatic Amplification of DNA in Vitro: The Polymerase Chain Reaction, Cold Spring Harbor Symp. Quant. Biol., 1986, vol. 51, pp. 263–273. 27. Saiki, R.K., Gelfand, D.H., Stoffel, S., et al., PrimerDirected Enzymatic Amplification of DNA with Thermostable DNA Polymerase, Science, 1988, vol. 239, pp. 487–491. 28. Datta, U., Datta, P., and Mandal, R.K., Cloning and Characterization of Highly Repetitive Fish Nucleotide Sequence, Gene, 1988, vol. 62, pp. 331–336. 29. Kan, Y.W. and Dozy, A.M., Polymorphism of DNA Sequence Adjacent to the β-Globin Structural Gene: Its Relation to the sickle Mutation, Proc. Natl. Acad. Sci. USA, 1978, vol. 75, pp. 5631–5635. 30. Nei, M., Molecular Evolutionary Genetics, New York: Columbia Univ. Press, 1987. 31. Levinson, G. and Gutman, G.A., Slipped-Strand Mispairing: A Major Mechanism for DNA Sequence Evolution, Mol. Biol. Evol., 1987, vol. 4, pp. 2203–2221. 32. Jeffreys, A.J., Wilson, V., and Thein, S.L., Hypervariable “Minisatellite” Regions in Human DNA, Nature, 1985, vol. 316, pp. 67–73. 33. Jeffreys, A.J., Wilson, V., and Thein, S.L., Individual Specific “Fingerprints” of Human DNA, Nature, 1985, vol. 316, pp. 76–79. 34. Tautz, D., Hypervariability of Simple Sequences as a General Source for Polymorphic DNA Markers, Nucleic Acids Res., 1989, vol. 17, pp. 6463–6471. 2002

1004

ALTUKHOV, SALMENKOVA

35. Wright, J.M. and Bentzen, P., Microsatellites: Genetic Markers for the Future, Rev. Fish Biol. Fish., 1994, vol. 4, pp. 384–388. 36. Wright, J.M., Mutation at VNTRs: Are Minisatellites the Evolutionary Progeny of Microsatellites?, Genome, 1994, vol. 37, pp. 345–347. 37. Armour, J.A.L., Alegre, S.A., Miles, S., et al., Minisatellites and Mutation Processes in Tandemly Repetitive DNA, Microsatellites. Evolution and Application, Goldstein, D.B. and Schlotterer, C., Eds., New York: Oxford Univ. Press, 1999, pp. 24–33. 38. Microsatellites: Evolution and Application, Goldstein, D.B. and Schlotterer, C., Eds., New York: Oxford Univ. Press, 1999. 39. Estoup, A., Presa, P., Krieg, F., et al., (CT)n and (GT)n Microsatellites: A New Class of Genetic Markers for Salmo trutta L. (Brown Trout), Heredity, 1993, vol. 71, pp. 488–496. 40. Kashi, Y. and Soller, M., Functional Roles of Microsatellites and Minisatellites, Microsatellites: Evolution and Application, Goldstein, D.B. and Schlotterer, C., Eds., New York: Oxford Univ. Press, 1999, pp. 10–23. 41. Hancock, J.M., Microsatellites and Other Simple Sequences: Genomic Context and Mutational Mechanisms, Microsatellites: Evolution and Application, Goldstein, D.B. and Schlotterer, C., Eds., New York: Oxford Univ. Press, 1999, pp. 1–9. 42. Weber, J.L. and Wong, C., Mutation of Human Short Tandem Repeats, Hum. Mol. Genet., 1993, vol. 2, pp. 1123– 1128. 43. Neel, J.V., Satoh, Ch., Goriki, K., et al., The Rate with Which Spontaneous Mutation Alters the Electrophoretic Mobility of Polypeptides, Proc. Natl. Acad. Sci. USA, 1986, vol. 83, pp. 389–393. 44. Ward, R.D. and Grewe, P., Appraisal of Molecular Genetic Techniques in Fisheries, Rev. Fish Biol. Fish., 1994, vol. 4, pp. 300–325. 45. Huang, T., Cottingham, R., Ledbetter, D., and Zoghbi, H., Genetic Mapping of Four Dinucleotide Repeat Loci, DXS453, DXS458, DXS454, and DXS424, on the X Chromosome Using Multiplex Polymerase Chain Reaction, Genomics, 1992, vol. 13, pp. 375–380. 46. Zane, L., Bargelloni, L., and Patarnello, T., Strategies for Microsatellite Isolation: A Review, Mol. Ecol., 2002, vol. 11, no. 1, pp. 1–16. 47. DNA Markers: Protocols, Applications and Overviews, Caetano-Anolles, G. and Gresshoff, P.M., Eds., New York: Wiley, 1997. 48. Ward, R.D., Woodwark, M., and Skibinski, D.O.F., A Comparison of Genetic Diversity Levels in Marine, Freshwater and Anadromous Fishes, J. Fish. Biol., 1994, vol. 44, pp. 213–232. 49. Hughes, C.R. and Queller, D.C., Detection of Highly Polymorphic Microsatellite Loci in a Species with Little Allozyme Polymorphism, Mol. Ecol., 1993, vol. 2, pp. 131–137. 50. De Woody, J.A. and Avise, J.C., Microsatellite Variation in Marine, Freshwater and Anadromous Fishes Compared with Other Animals, J. Fish Biol., 2000, vol. 56, pp. 461–473. 51. Dufresne, F., Bourget, E., and Bernatchez, L., Differential Patterns of Spatial Divergence in Microsatellite and

Allozyme Alleles: Further Evidence for Locus-Specific Selection in the Acorn Barnacle, Semibalanus balanoides?, Mol. Ecol., 2002, vol. 11, no. 1, pp. 113–124. 52. Balloux, F. and Lugon-Moulin, N., The Estimation of Population Differentiation with Microsatellite Markers, Mol. Ecol., 2002, vol. 11, pp. 155–165. 53. Shriver, M.D., Jin, L., Boerwinkle, L.E., et al., A Novel Measure of Genetic Distance for Highly Polymorphic Tandem Repeat Loci, Mol. Biol. Evol., 1995, vol. 12, pp. 914–920. 54. Zhivotovsky, L.A., A New Genetic Distance with Application to Constrained Variation at Microsatellite Loci, Mol. Biol. Evol., 1999, vol. 16, pp. 467–471. 55. Ruzzante, D.E., A Comparison of Several Measures of Genetic Distance and Population Structure with Microsatellite Data: Bias and Sampling Variance, Can. J. Fish. Aquat. Sci., 1998, vol. 55, pp. 1–14. 56. Weir, B.S. and Cockerham, C.C., Estimating F-Statistics for the Analysis of Population Structure, Evolution, 1984, vol. 38, pp. 1358–1370. 57. Dubrova, Yu.E., Jeffreys, A.J., and Malashenko, A.M., Mouse Minisatellite Mutations Induced by Ionizing Radiation, Nat. Genet., 1993, vol. 5, pp. 92–94. 58. Dubrova, Yu.E., Nesterov, V.N., Krouchinsky, N.G., et al., Human Minisatellite Mutation Rate after the Chernobyl Accident, Nature, 1996, vol. 380, pp. 683–686. 59. Dubrova, Yu.E., Plumb, M., Brown, J., et al., Stage Specificity, Dose Response, and Doubling Dose for Mouse Minisatellite Germline Mutation Induced by Acute Radiation, Proc. Natl. Acad. Sci. USA, 1998, vol. 95, pp. 6251–6255. 60. Ryskov, A.P., Multilocus DNA Fingerprinting in Population Genetic Studies of Biodiversity, Mol. Biol. (Moscow), 1999, vol. 33, no. 6, pp. 997–1011. 61. Fontaine, P.M., Dodson, J.J., Bernatchez, L., and Slettan, A., A Genetic Test of Metapopulation Structure in Atlantic Salmon (Salmo salar) Using Microsatellites, Can. J. Fish. Aquat. Sci., 1997, vol. 54, pp. 2434–2442. 62. Shaw, P.W., Turan, C., Wright, J.M., et al., Microsatellite DNA Analysis of Population Structure in Atlantic Herring (Clupea harengus), with Direct Comparison to Allozyme and mtDNA RFLP Analysis, Heredity, 1999, vol. 83, pp. 490–499. 63. Wirth, T. and Bernatchez, L., Genetic Evidence against Panmixia in the European Eel, Nature, 2001, vol. 409, pp. 1037–1040. 64. Banks, M.A., Rashbrook, V.K., Calavetta, M.J., et al., Analysis of Microsatellite DNA Resolves Genetic Structure and Diversity of Chinook Salmon (Oncorhynchus tshawytscha) in California’s Central Valley, Can. J. Fish. Aquat. Sci., 2000, vol. 57, pp. 915–927. 65. Bernatchez, L., Dempson, J.B., and Martin, S., Microsatellite Gene Diversity Analysis in Anadromous Arctic Charr, Salvelinus alpinus, from Labrador, Canada, Can. J. Fish. Aquat. Sci., 1998, vol. 55, pp. 1264–1272. 66. Brunner, P.C., Douglas, M.R., and Bernatchez, L., Microsatellite and Mitochondrial DNA Assessment of Population Structure and Stocking Effects in Arctic Charr Salvelinus alpinus (Teliostei, Salmonidae) from Central Alpine Lakes, Mol. Ecol., 1998, vol. 7, pp. 209–223. 67. Primmer, C.R., Aho, T., Piironen, J., et al., Microsatellite Analysis of Hatchery Stocks and Natural Popula-

RUSSIAN JOURNAL OF GENETICS

Vol. 38

No. 9

2002

DNA POLYMORPHISM IN POPULATION GENETICS tions of Arctic Charr, Salvelinus alpinus, from the Nordic Region: Implications for Conservation, Hereditas (Lund, Swed.), 1999, vol. 130, pp. 277–289. 68. Burger, C.V., Scribner, K.T., Spearman, W.J., et al., Genetic Contribution of Three Introduced Life History of Sockeye Salmon to Colonization of Frazer Lake, Alaska, Can. J. Fish. Aquat. Sci., 2000, vol. 57, pp. 2096– 2111. 69. Ruzzante, D.E., Hansen, M.M., and Meldrup, D., Distribution of Individual Inbreeding Coefficients, Relatedness and Influence of Stocking on Native Anadromous Brown Trout (Salmo trutta) Population Structure, Mol. Ecol., 2001, vol. 10, pp. 2107–2128. 70. Estoup, A. and Angers, B., Microsatellites and Minisatellites for Molecular Ecology: Theoretical and Empirical Considerations, Advances in Molecular Ecology: NATO Sciences Series, Carvalho, G.R., Ed., IOS Press, 1998, pp. 55–86. 71. Luikart, G. and England, P.R., Statistical Analysis of Microsatellite DNA Data, Trends Ecol. Evol., 1999, vol. 14, pp. 253–256. 72. Paetkau, D., Calwert, W., Stirling, I., and Strobeck, C., Microsatellite Analysis of Population Structure in Canadian Polar Bears, Mol. Ecol., 1995, vol. 4, pp. 347– 354. 73. Banks, M.A. and Eichert, W., WHICHRUN (Version 3.2): A Computer Program for Population Assignment of Individuals Based on Multilocus Genotype Data, J. Hered., 2000, vol. 91, pp. 87–89. 74. Hansen, M.M., Kenchington, E., and Nielsen, E., Assigning Individual Fish to Populations Using Microsatellite DNA Markers, Fish Fisheries, 2001, vol. 2, no. 2, pp. 93–112. 75. Ferguson, A., Molecular Genetics in Fisheries: Current and Future Perspectives, Molecular Genetics in Fisheries, Carvalho, G.R. and Pitcher, T.G., Eds., London: Chapman and Hall, 1995, pp. 111–115. 76. Mousseau, T.A., Ritland, K., and Heath, D.D., A Novel Method for Estimating Heritability Using Molecular Markers, Heredity, 1998, vol. 80, pp. 218–224. 77. Karp, A. and Edwards, K., DNA Markers: A Global Overview, DNA Markers: Protocols, Applications and Overview, Caetano-Anolles, G. and Gressnoff, P.M., Eds., New York: Wiley, 1977, pp. 1–13. 78. Williams, J.G.K., Hanafey, M.K., Rafalski, J.A., and Tingey, S.V., Genetic Analysis Using Random Amplified Polymorphic DNA Markers, Methods in Enzymology, Wu, R., Ed., San Diego: Academic, 1993, pp. 704– 740. 79. Mueller, U.G. and Wolfenbarger, L.L., AFLP Genotyping and Fingerprinting, Trends Ecol. Evol., 1999, vol. 14, pp. 389–394. 80. Krutovskii, K.V., Vollmer, S.S., Sorensen, F.C., et al., RAPD Genome Map of Douglas Fir, J. Hered., 1998, vol. 89, no. 3, pp. 197–205. 81. Schierwater, B., Ender, A., Schroth, W., et al., Arbitrarily Amplified DNA in Ecology and Evolution, DNA Markers: Protocols, Applications and Overview, Caetano-Anolles, G. and Gresshoff, P.M., Eds., New York: Wiley, 1997, pp. 313–330. 82. Paglia, G. and Morgante, M., PCR-Based Multiplex DNA Fingerprinting Techniques for the Analysis of RUSSIAN JOURNAL OF GENETICS

Vol. 38

No. 9

1005

Conifer Genomes, Mol. Breed., 1998, vol. 4, pp. 173– 177. 83. Altukhov, Yu.P. and Abramova, A.B., Monomorphic Species-Specific DNA Detectable by the Polymerase Chain Reaction with Arbitrary Primers, Genetika (Moscow), 2000, vol. 36, no. 12, pp. 1674–1681. 84. Altukhov, Yu.P., On the Relationship of Monomorphism and Polymorphism of Hemoglobins in Fish Microevolution, Dokl. Akad. Nauk SSSR, 1969, vol. 189, no. 5, pp. 115–117. 85. Altukhov, Yu.P. and Rychkov, Yu.G., Genetic Monomorphism of Species and Its Biological Significance, Zh. Obshch. Biol., 1972, vol. 33, pp. 281–300. 86. Omel’chenko, V.T., Electrophoretic Analysis of Hemoglobin in Fish of the Russian Far East, Genetika (Moscow), 1974, vol. 10, no. 9, pp. 35–43. 87. Singer, M. and Berg, P., Genes and Genomes, Mill Valley, California Univ. Sci. Books, 1991. 88. Ferris, S.D. and Berg, W.J., The Utility of Mitochondrial DNA in Fish Genetics and Management, Population Genetics and Fishery Management, Ryman, N., and Utter, F., Eds., Seattle: Univ. of Washington Press, 1987, pp. 277–301. 89. Bentzen, P., Wright, J.M., Bryden, L.T., et al., Tandem Repeat Polymorphism in the Mitochondrial Control Region of Redfishes (Sebastes: Scorpaenidae), J. Hered., 1998, vol. 89, pp. 1–7. 90. Eyre-Walker, A., Do Mitochondrial Genomes Recombine in Humans?, Philos. Trans. R. Soc. London, B, 2000, vol. 355, pp. 1573–1580. 91. Wallis, G.P., Do Animal Mitochondrial Genomes Recombine?, Trends Ecol. Evol., 1999, vol. 14, pp. 209– 210. 92. Nei, M. and Tajima, F., DNA Polymorphism Detectable by Restriction Endonucleases, Genetics, 1981, vol. 105, pp. 207–217. 93. Moritz, C., Dowling, T.E., and Brown, W.M., Evolution of Animal Mitochondrial DNA: Relevance for Population Biology and Systematics, Annu. Rev. Ecol. Syst., 1987, vol. 18, pp. 269–292. 94. Van Hooft, W.F., Groen, A.F., and Prins, H.H.T., Phylogeography of the African Buffalo Based on Mitochondrial and Y-Chromosomal Loci: Pleistocene Origin and Population Expansion of the Cape Buffalo Subspecies, Mol. Ecol., 2002, vol. 11, pp. 267–279. 95. Wilkinson, G.S. and Ghapman, A.M., Length and Sequence Variation in Evening Bat D-Loop Mitochondrial DNA, Genetics, 1991, vol. 128, pp. 607–617. 96. Park, L.K., Brainard, M.A., Dingman, D.A., and Winans, G.A., Low Levels of Intraspecific Variation in the Mitochondrial DNA of Chum Salmon (Oncorhynchus keta), Mol. Mar. Biol. Biotechnol., 1993, vol. 2, no. 6, pp. 362–370. 97. Churikov, D., Matsuoka, M., Luan, X., et al., Assessment of Concordance among Genealogical Reconstructions from Various mtDNA Segments in Three Species of Pacific Salmon (Genus Oncorhynchus), Mol. Ecol., 2001, vol. 19, no. 9, pp. 2329–2339. 98. Brown, W.M., George, M., and Wilson, A.C., Rapid Evolution of Animal Mitochondrial DNA, Proc. Natl. Acad. Sci. USA, 1979, vol. 76, pp. 1967–1971. 2002

1006

ALTUKHOV, SALMENKOVA

99. Ferris, S.D., Sage, R.D., Prager, E.M., et al., Mitochondrial DNA Evolution in Mice, Genetics, 1983, vol. 105, pp. 681–721. 100. Cann, R.L., Stoneking, M., and Wilson, A.C., Mitochondrial DNA and Human Evolution, Nature, 1987, vol. 325, pp. 31–36. 101. Harrison, R.G., Animal Mitochondrial DNA as a Genetic Marker in Population and Evolutionary Biology, Trends Ecol. Evol., 1989, vol. 4, pp. 6–11. 102. Horai, S., Hoyasaka, K., Kondo, R., et al., Recent African Origin of Modern Humans Revealed by Complete Sequences of Hominoid Mitochondrial DNAs, Proc. Natl. Acad. Sci. USA, 1995, vol. 92, pp. 532–536. 103. Ingman, M., Kaessmann, H., Paabo, S., and Gyllensten, U., Mitochondrial Genome Variation and the Origin of Modern Humans, Nature, 2000, vol. 408, pp. 708– 712. 104. Avise, J.C., Molecular Markers, Natural History and Evolution, New York: Chapman and Hall, 1994. 105. Avise, J.C., Phylogeography: The History and Formation of Species, Cambridge, Ma: Harvard Univ. Press, 2000. 106. Bernatchez, L. and Wilson, C.C., Comparative Phylogeography of Nearctic and Palearctic Fishes, Mol. Ecol., 1998, vol. 7, pp. 431–452. 107. Billington, N. and Hebert, P.D.H., Mitochondrial DNA Diversity of Fishes and Its Implications for Introductions, Can. J. Fish. Aquat. Sci., 1991, vol. 48, suppl. 1, pp. 80–94. 108. Wayne, R.K. and Jenks, S.M., Mitochondrial DNA Analysis Supported Extensive Hybridization of the Endangered Wolf (Canis rufus), Nature, 1991, vol. 351, pp. 565–568. 109. Wilson, C.C. and Bernatchez, L., The Ghost of Hybrid Past: Fixation of Arctic Charr (Salvelinus alpinus) Mitochondrial DNA in Introgressed Population of Lake Trout (S. namaycush), Mol. Ecol., 1998, vol. 7, pp. 127– 132. 110. Felsenstein, J., PHYLIP (Phylogeny Inference Package), Version 3.4, Department of Genetics, SK-540, Seattle: Washington Univ., 1992. 111. Schneider, S., Roessli, D., and Excoffier, L., Arlequin: A Software for Population Genetics Data Analysis, Ver. 2000, Geneva: Univ. of Geneva, 2000. 112. Excoffier, L., Smouse, P.E., and Quattro, J.M., Analyses of Molecular Variance Inferred from Metric Distances among DNA Haplotypes: Application to Human Mitochondrial DNA Restriction Data, Genetics, 1992, vol. 131, pp. 479–491. 113. Cavalli-Sforza, L.L., The DNA Revolution in Population Genetics, Trends Genet., 1998, vol. 14, no. 2, pp. 60–65. 114. Santos, F. and Tyler-Smith, C., Reading the Human Y-Chromosome: Emerging DNA Markers and Human Genetic History, Braz. J. Genet., 1996, vol. 18, pp. 669– 672. 115. Jobling, M.A. and Tyler-Smith, C., New Uses for New Haplotypes: The Human Y Chromosome, Disease and Selection, Trends Genet., 2000, vol. 16, no. 8, pp. 356– 362.

116. Underhill, P.A., Shen, P., Lin, A.A., et al., Y Chromosome Sequence Variation and the History of Human Populations, Nat. Genet., 2000, vol. 26, pp. 358–361. 117. Hammer, M., A Recent Insertion of an Alu Element on the Y Chromosome Is a Useful Marker for Human Population Studies, Mol. Biol. Evol., 1994, vol. 11, pp. 749– 761. 118. Underhill, P.A., Jin, L., Zemans, R., et al., A PreColumbian Y Chromosome-Specific Transition and Its Implications for Human Evolutionary History, Proc. Natl. Acad. Sci. USA, 1996, vol. 93, pp. 196–200. 119. Seielstad, M.T., Minch, E., and Cavalli-Sforza, L.L., Genetic Evidence for a Higher Female Migration Rate in Humans, Nat. Genet., 1998, vol. 20, pp. 278–280. 120. Ota, H., Settheetham-Ishida, W., Tiwawech, D., et al., Human mtDNA and Y-Chromosome Variation Is Correlated with Matrilocal versus Patrilocal Residence, Nat. Genet., 2001, vol. 29, pp. 20–21. 121. Sinclair, A.H., Berta, P., Palmer, M.S., et al., A Gene From the Human Sex-Determining Region Encodes a Protein with Homology to a Conserved DNA-Binding Motif, Nature, 1990, vol. 346, pp. 240–244. 122. Lahn, B.T. and Page, D.C., Functional Coherence of the Human Y Chromosome, Science, 1997, vol. 278, pp. 675–680. 123. Gibson, G., Microarrays in Ecology and Evolution: A Preview, Mol. Ecol., 2002, vol. 11, no. 1, pp. 17–24. 124. Wang, D.G., Fan, J.-B., Siao, C.J., et al., Large-Scale Identification: Mapping and Genotyping of SingleNucleotide Polymorphism in the Human Genome, Science, 1998, vol. 280, pp. 1077–1082. 125. Cargill, M., Altshuler, D., Ireland, J., et al., Characterization of Single-Nucleotide Polymorphism in Coding Regions of Human Genes, Nat. Genet., 1999, vol. 22, pp. 231–238. 126. Halushka, M.K., Fan, J.-B., Bentley, K., et al., Pattern of Single-Nucleotide Polymorphism in Candidate Genes for Blood-Pressure Homeostasis, Nat. Genet., 1999, vol. 22, pp. 239–247. 127. Lander, E.S., The New Genomics: Global Views of Biology, Science, 1996, vol. 274, pp. 536–539. 128. Przeworski, M., Hudson, R.R., and Di Rienzo, A., Adjusting the Focus on Human Variation, Trends Genet., 2000, vol. 16, no. 7, pp. 282–290. 129. Krutovskii, K.V. and Neale, D.B., Forest Genomics for Conserving Adaptive Genetic Diversity, Forest Genetics Resources: Working Papers, Rome: Forest Resources Dev. Serv., 2001. 130. Wolfsberg, T.G. and Landsman, D., A Comparison of Expressed Sequence Tags (ESTs) to Human Genomic Sequences, Nucleic Acids Res., 1997, vol. 26, pp. 1626– 1632. 131. Chakravarti, A., Population Genetics—Making Sense out of Sequence, Nat. Genet., 1999, vol. 21, pp. 56–60. 132. Singer, M.F., SINEs and LINEs: Highly Repeated Short and Long Interspersed Sequences in Mammalian Genomes, Cell (Cambridge, Mass.), 1982, vol. 28, pp. 433–434. 133. Rogers, J.H., The Origin and Evolution of Retroposons, Int. Rev. Cytol., 1985, vol. 93, pp. 187–279.

RUSSIAN JOURNAL OF GENETICS

Vol. 38

No. 9

2002

DNA POLYMORPHISM IN POPULATION GENETICS 134. Okada, N., SINEs: Short Interspersed Repeated Elements of the Eukaryotic Genome, Trends Ecol. Evol., 1991, vol. 6, pp. 358–361. 135. Kocher, T.D., Thomas, W.K., Meyer, A., et al., Dynamics of Mitochondrial DNA Evolution in Animals: Amplification and Sequencing with Conserved Primers, Proc. Natl. Acad. Sci. USA, 1989, vol. 86, pp. 6196– 6200. 136. Saccone, C., Pesole, G., and Sbisa, E., The Main Regulatory Region of Mammalian Mitochondrial DNA: Structure–Function Model and Evolutionary Pattern, J. Mol. Evol., 1991, vol. 33, pp. 83–91. 137. Bielawski, J.P. and Gold, J.R., Unequal Synonymous Substitution Rate within and between Two ProteinCoding Mitochondrial Genes, Mol. Biol. Evol., 1996, vol. 13, pp. 889–892. 138. Wise, C.A., Sraml, M., and Easteal, S., Departure from Neutrality at the Mitochondrial NADP Dehydrogenase Subunit 2 Gene in Humans, but Not in Chimpanzees, Genetics, 1998, vol. 148, pp. 400–421. 139. Chinnery, P.F. and Turnbull, D.M., Mitochondrial DNA Mutations in the Pathogenesis of Human Diseases, Mol. Med. Today, 2000, vol. 6, pp. 425–432. 140. Rand, D.M., Endotherms, Ectotherms and Mitochondrial Genome-Size Variation, J. Mol. Evol., 1993, vol. 37, pp. 281–295. 141. Blier, P.U., Dufresne, F., and Burton, R.S., Natural Selection and the Evolution of mtDNA-Encoded Peptides: Evidence for Intergenomic Co-Adaptation, Trends Genet., 2001, vol. 17, no. 7, pp. 400–406. 142. Kimura, M., Genetic Variability Maintained in a Finite Population Due to Mutational Production of Neutral and Nearly Neutral Isoalleles, Genet. Res., 1968, vol. 11, pp. 247–269. 143. King, J.L. and Jukes, T.H., Non-Darwinian Evolution: Random Fixation of Selectively Neutral Mutations, Science, 1969, vol. 164, pp. 788–798. 144. Otto, S.P., Detecting the Form of Selection from DNA Sequence Data, Trends Genet., 2000, vol. 16, no. 12, pp. 526–529. 145. Nielsen, R., Statistical Tests of Selective Neutrality in the Age Genomics, Heredity, 2001, vol. 86, no. 6, pp. 641–647. 146. Sunyaev, S.R., Lathe, W.C. III, Ramensky, V.E., and Bork, P., SNP Frequencies in Human Genes: An Excess of Rare Alleles and Differing Modes of Selection, Trends Genet., 2000, vol. 16, no. 8, pp. 335–337. 147. Balanovskaya, E.V. and Rychkov, Yu.G., Ethnic Genetics: The Adaptive Gene-Pool Structure of the Global Population as Inferred from the Data on Human Polymorphic Genetic Markers, Genetika (Moscow), 1990, vol. 26, no. 4, pp. 739–748. 148. Rychkov, Yu.G. and Balanovskaya, E.V., Ethnic Genetics: The Relationship between Adaptive and Neutral Genetic Differentiation of Ethnic Groups, Genetika (Moscow), 1990, vol. 26, no. 3, pp. 541–549. 149. Rychkov, Yu.G. and Sheremetyeva, V.A., The Genetics of Circumpolar Populations of Eurasia Related to the Problem of Human Adaptation, The Human Biology of Circumpolar Populations, Milan, F.A., Ed., Cambridge: Cambridge Univ. Press, 1979, vol. 21, pp. 37– 80. RUSSIAN JOURNAL OF GENETICS

Vol. 38

No. 9

1007

150. Altukhov, Yu.P., Geneticheskie protsessy v populyatsiyakh (Genetic Processes in Populations), Moscow: Nauka, 1989, 2nd ed. 151. Altukhov, Yu.P., Salmenkova, E.A., and Omelchenko, V.T., Salmonid Fishes: Population Biology, Genetics, and Management, Oxford: Blackwell Sci., 2000. 152. Bowcock, A.M., Bucci, C., Hebert, J.M., et al., Study of 47 DNA Markers in Five Populations of Four Continents, Gene Geogr., 1987, no. 1, pp. 47–64. 153. Cooper, D.N. and Schmidke, J., DNA Restrictions Fragment Length Polymorphism and Heterozygosity in Human Genome, Hum. Genet., 1984, vol. 66, pp. 1–16. 154. Rychkov, Yu.G. and Balanovskaya, E.V., Genetic Differentiation of Human Populations: Can DNA Polymorphism Be Predicted from Immunobiochemical Polymorphism?, Molekulyarnye mekhanizmy geneticheskikh protsessov (Molecular Mechanisms of Genetic Processes), Moscow: Nauka, 1990, pp. 67–83. 155. Sanchez, J.A., Clabby, C., Ramos, D., et al., Protein and Microsatellite Single-Locus Variability in Salmo salar L. (Atlantic Salmon), Heredity, 1996, vol. 77, pp. 423– 432. 156. Dubreuil, P. and Charcosset, A., Gene Diversity within and among Maize Populations: A Comparison Between Isozyme and Nuclear RFLP Loci, Theor. Appl. Genet., 1998, vol. 96, pp. 577–587. 157. Aagaard, J.E., Krutovsky, K.V., and Strauss, S.H., RAPDs and Allozymes Exhibit Similar Levels of Diversity and Differentiation among Populations and Races of Douglas-Fir, Heredity, 1998, vol. 81, pp. 69–78. 158. Ross, K.G., Shoemaker, D.D., Krieger, M.J., et al., Assessing Genetic Structure with Multiple Classes of Molecular Markers: A Case Study Involving the Introduced Fire Ant Soenopsis invicta, Mol. Biol. Evol., 1999, vol. 16, pp. 525–543. 159. Raybould, A.F., Goudet, J., Mogg, R.J., et al., Genetic Structure of a Linear Population of Beta vulgaris ssp. maritime (Sugar Beet) Revealed by Isozyme and RFLP Analysis, Heredity, 1996, vol. 76, pp. 111–112. 160. Pogson, G.H., Mesa, K.A., and Boutilier, R.G., Genetic Population Structure and Gene Flow in Atlantic Cod, Gadus morhua: A Comparison of Allozyme and RFLP Loci, Genetics, 1995, vol. 139, pp. 375–385. 161. Latta, R.G. and Mitton, J.B., A Comparison of Population Differentiation across Four Classes of Gene Markers in Limber Pine (Pinus flexilis James), Genetics, 1997, vol. 146, pp. 1153–1163. 162. Karl, S.A. and Avise, J.C., Balancing Selection at Allozyme Loci in Oysters: Implications from Nuclear RFLPs, Science, 1992, vol. 256, pp. 100–102. 163. Scribner, K.T., Arntzen, J.W., and Burke, T., Comparative Analysis of Intra- and Interpopulation Genetic Diversity in Bufo bufo, Using Allozyme, Single-Locus Microsatellite, Minisatellite and Multilocus Minisatellite Data, Mol. Biol. Evol., 1994, vol. 11, pp. 737–748. 164. Altukhov, Yu.P., Balancing Selection as a Factor in Maintaining Allozyme Polymorphism, Usp. Sovrem. Biol., 1989, vol. 107, pp. 323–340. 165. Lewontin, R.C., The Genetic Basis of Evolutionary Change, New York: Columbia Univ. Press, 1974. 166. Politov, D.V., Krutovskii, K.V., and Altukhov, Yu.P., Characterization of the Gene Pools of Cedar Pine Pop2002

1008

ALTUKHOV, SALMENKOVA

ulations with Respect to Several Isozyme Loci, Genetika (Moscow), 1992, vol. 28, no. 1, pp. 93–114. 167. Politov, D.V. and Krutovskii, K.V., Phylogenetics, Phylogeography and Hybridization of Five-Needle Pines in Russia and Neighboring Counties, Breeding and Genetic Resources of Five-Needle Pines: Adaptability and Pest Resistance: Proc. Conf. IUFRO Working Party 2.02.15 (July 23–27, 2001), Medford, Oreg.: USS Forest Serv., publ. no. RMRS-P-000 (in press). 168. Glubokovsky, M.K. and Zhivotovsky, L.A., The Population Structure of Pink Salmon: A System of Fluctuating Stocks, Biol. Morya, 1986, no. 2, pp. 39–44. 169. Zhivotovsky, L.A., Glubokovsky, M.K., Viktorovsky, R.M., et al., Genetic Differentiation of Pink Salmon, Genetika (Moscow), 1989, vol. 25, no. 7, pp. 1261–1274. 170. Glubokovsky, M.K., Zhivotovsky, L.A., Viktorovsky, R.M., et al., Organization of Pink Salmon Populations, Genetika (Moscow), 1989, vol. 25, no. 7, pp. 1275–1284. 171. Brykov, V.A., Polyakova, N.E., Skurikhina, L.A., et al., The Population Genetic Structure of Pink Salmon Oncorhynchus gorbuscha (Walbaum) as Revealed by Restriction Enzyme Analysis of Mitochondrial DNA: Temporal Heterogeneity at the Period of Spawning

Run, Genetika (Moscow), 1999, vol. 35, no. 5, pp. 666– 673. 172. Brykov, V.A., Polyakova, N., Skurihina, L.A., and Kukhlevsky, A.D., Geographical and Temporal Mitochondrial DNA Variability in Populations of Pink Salmon, J. Fish. Biol., 1996, vol. 48, pp. 899–909. 173. Altukhov, Yu.P., The Role of Balancing Selection and Overdominance in Maintaining Allozyme Polymorphism, Genetics (Netherl.), 1991, vol. 85, pp. 79–90. 174. Rogers, A., Order Emerging from Chaos in Human Evolutionary Genetics, Proc. Natl. Acad. Sci. USA, 2001, vol. 98, no. 3, pp. 779–780. 175. Park, L.K. and Moran, P., Developments in Molecular Genetic Techniques in Fisheries, Rev. Fish Biol., 1994, vol. 4, pp. 272–299. 176. Morris, D.B., Richard, K.R., and Wright, J.M., Microsatellites from Rainbow Trout (Oncorhynchus mykiss) and Their Use for Genetic Study in Salmonids, Can. J. Fish. Aquat. Sci., 1996, vol. 53, pp. 120–126. 177. Ohdachi, S., Dokuchaev, N.E., Hasegava, M., and Masuda, R., Intraspecific Phylogeny and Geographical Variation of Six Species of Northeastern Asiatic Sorex Shrews Based on the Mitochondrial Cytochrome B Sequences, Mol. Ecol., 2001, vol. 10, pp. 2199–2213.

RUSSIAN JOURNAL OF GENETICS

Vol. 38

No. 9

2002