Primer nucleotide sequence.
Abstract
Kazakhstan has concentrated unique genetic resources of plant agrobiodiversity of world significance. It has received international recognition for fruit agro-biodiversity and, above all, wild apple, which is highly resistant to many diseases, high frost resistance, and wide ecological plasticity. Kazakhstan is the original genetic center of biological variability of wild apples and, historically, has formed their rich gene pool. Wild apple species in Kazakhstan are genetically kindred to cultivated varieties of the world. Genetic diversity and polymorphism of Malus Sieversii (Ledeb.) from Ile Alatau and Dzhungraian Alatau were studied with ISSR markers.
Keywords
- wild apple
- Malus Sieversii
- genetic diversity
- in situ
- conservation
1. Introduction
The
So, the natural forests of wild apple of the Kazakhstan in terms of scale, uniqueness, genetic potential, scientific, and practical significance can be classified as one of the most valuable plant communities of the earth [3]. In this regard, their study and preservation
2. Specific features of Malus wild species of Kazakhstan and implication for their conservation
2.1 Specific features of Malus wild species of Kazakhstan
Sievers’ apple tree is 2–10 (14) m tall. The leaves are large from short-elliptic to oblong with a wedge-shaped, less often rounded base, at the apex usually suddenly turning into a short pointed tip, along the edge the leaf plate is town-shaped. The flowers are 3.5–6 cm in diameter, on long felt pedicels. The petals are pale pink. Fruits are 3–4 cm in diameter, spherical, or flattened-spherical. Along mountainous slopes, gorge bottoms, river valleys in the belt of woody-shrubby vegetation (from 900 to 2300–2600 m above sea level) form apple forests.
Wild apple hybrids are characterized by a huge intraspecific polymorphism as a consequence of genetic differences. Within one population, each apple tree is an independent form with reliably distinctive features and properties from the neighboring apple tree. The practical value of these forms and their hereditary properties vary greatly; therefore, in order to preserve the most valuable and well adapted to the specific environmental conditions of the forms, it is necessary to be planted with planting material genetically corresponding to the selected forms. Vegetative propagation meets this condition.
Recently, the
Therefore, along with the problem of conservation, there is a global problem of restoring wild apple
The general provisions of the theory of conservation of species through their reintroduction have been repeatedly discussed in the literature [6]; however, practical work with a specific species requires the development of a special strategy due to the specific reasons that cause the “rarity” of the species. Most researchers indicate that when reintroducing a species, it is necessary to follow a number of rules to achieve genetic and ecological prosperity of populations mainly in the former habitats of the species [7]. To do this, the mother material must be represented by the most heterozygous plants from the populations with the highest polymorphism indicators. An important step is the identification of parent and daughter plants and their compliance with reintroduction sites [8, 9].
Efficient conservation and use of plant genetic resources require a thorough assessment of the genetic variation they possess.
Genetic variation can be measured at two levels:
Phenotype—combinations of individual traits determined by the genotype and its interaction with the environment.
Genotype—specific genetic structure of the organism.
The reintroduction strategy for biodiversity recovery should involve recovery of population-typical allele frequencies. Historically, all patterns of variability and heredity have been studied by analyzing morphological characteristics, which until now have remained the main criterion in plant taxonomy, in the study of the mutation process, in studies of phylogenetic connections. However, morphological features do not always provide complete informatively, since they are strongly influenced by environmental conditions. In this regard, along with morphological features, physiological and biochemical indicators are widely used, for example, polymorphism of isoenzymes and spare proteins; however, isoenzymes and proteins are products of gene expression, the degree of expression of which is influenced by various factors, for example, plant age and tissue specificity [10]. If we consider that in higher eukaryotes only about 1% of the genome are protein-coding sequences, then the main part of the genome escapes the attention of researchers.
Currently, methods based on polymerase valuable reaction (PCR) using molecular markers characterizing regions of variability in nuclear, chloroplast, and ribosomal DNA are widely used worldwide in taxonomy and population genetics.
Various evolutionary events result in different variants in the DNA sequence that describes the polymorphism. Polymorphism manifests itself in genotype differences and is visualized as different band profiles found when using molecular markers in PCR and electrophoresis of PCR products.
The most simple and preferable in experiments where DNA of a large number of representatives at several loci is studied are methods using DNA amplification by single primers with an arbitrary sequence of SSR [11] and ISSR nucleotides [12].
ISSR uses known microsatellite sequences as primers and carries at one end a sequence of two to four arbitrary nucleotides. Such primers allow amplification of DNA fragments that are located between two sufficiently close microsatellite sequences (usually unique DNA). The obtained PCR product patterns are species-specific [13]. ISSR markers refer to markers of dominant inheritance type whose polymorphism is tested by the presence/absence of a band. The method has good reproducibility and, along with AFLP, is used to identify interspecies and intraspecific genetic variation, identify species, populations, lines, and individual genotyping [14].
2.2 Molecular genetic assessment of M. Sieversii in Kazakhstan1
With ISSR markers, polymorphism and genetic diversity of
Plant material
№ primer | Nucleotide sequence (5′-3′) | № primer | Nucleotide sequence (5′-3′) |
---|---|---|---|
М2 | аса сас аса сас аса с(сt)g | М8 | gtg gtg gtg gtg gtg |
М3 | gag aga gag aga gag a(ct)c | М9 | gac acg aca cga cac gac ac |
М4 | aga gag aga gag aga g(ct)c | М11 | cac aca cac aca (ag) |
М7 | cag cag cag cag cag | М12 | cac aca cac aca (ag)(ct) |
In the course of work on the selection of ISSR markers, polymorphic between the studied genotypes for all markers, the same PCR conditions were used (primer annealing was set individually), allowing to obtain the maximum amount of reaction product.
PCR parameters used for analysis included: 3 minutes at 95°C—initial denaturation, the following 35 cycles:
30 seconds denaturation at 94°C, annealing primers at the appropriate temperature—30 seconds,
40 seconds elongation at 72°C + addition of 2 seconds per cycle.
The reaction mixture (20 μl) contained 10–20 ng of DNA, 20 pmoles of primer and a finished reaction mix (Biocom) containing Taq-inhibited DNA polymerase, deoxynucleoside triphosphates, and magnesium chloride with final concentrations of 1u, 200 μM, and 2.5 mM, respectively, as well as an optimized buffer system for PCR.
Initially, the annealing temperature of primers was calculated using the formula:
where C, G, A, and T are the amount of cytosine, guanidine, adenine, and thymine bases, respectively. Subsequently, the optimal annealing temperature of the primers was empirically selected by decreasing or increasing it, depending on the quality of the PCR product obtained. The primer annealing temperature was specifically for primers M11 to 44.8°C, M12 to 49.5°C, M2 to 49.5°C, M9 to 50°C, M8 to 52.7°C, M3 to 52.7°C, M4 to 50.8°C, and M7 to 52.7°C.
For electrophoretic separation of PCR products, 1.7% agarose gel in 1x tris-borate buffer (50 mM Tris, 50 nM boric acid, 1 mM EDTA, pH 8.0) with ethidium bromide (0.5 μg/mL) was used when 100V for 45 minutes, followed by photographing the obtained PCR products and photo-processing in adobe program. Photographs of agarose gels were analyzed in Cross Checker 2.91 [13] with the composition of binary arrays of the presence/absence of fragments of the same length.
The level of heterozygosity of marker data is identified according to the average similarity frequency of alternative alleles. At the same time, 50% of the main alleles versus 50% of alternative alleles (0.5) correspond to a high level of heterozygosity, while 0.9 by 0.1 (90% versus 10%) corresponds to a low level.
Figures 1–5 show electropherograms of amplification of DNA fragments of
Table 2 shows the genetic diversity of
Sample no. | Common amplicons with cultural apple, % | Genetic diversity, % | Sample no. | Common amplicons with cultural apple, % | Genetic diversity, % |
---|---|---|---|---|---|
1-1 | 40 | 60 | 23 | 40 | 60 |
1-2 | 50 | 50 | 29, 32, 33 | 50 | 50 |
1-3 | 50 | 50 | 37 | 67 | 33 |
1-4 | 33 | 67 | 41, 44 | 50 | 50 |
1-5 | 28,5 | 71,5 | 42 | 50 | 50 |
1-6, 1-15 | 50 | 50 | 43 | 43 | 57 |
1-7, 1-13 | 33 | 67 | 45 | 50 | 50 |
1-8, 1-9, 1-14 | 50 | 50 | 47 | 75 | 25 |
1-10 | 50 | 50 | 48, 49, 52 | 33 | 67 |
1-11 | 40 | 60 | 51 | 60 | 40 |
1-12 | 50 | 50 | 53 | 66 | 34 |
1 | 50 | 50 | 54, 55 | 50 | 50 |
4,7 | 67 | 33 | 56 | 40 | 60 |
12, 16, 27, 40 | 40 | 60 | 57 | 78 | 22 |
AP, GD, 13, 36 | 100 | – | 58 | 67 | 33 |
18,19 | 50 | 50 | 60 | 50 | 50 |
21 | 50 | 50 |
Sample no. | Common amplicons with cultural apple, % | Genetic diversity, % | Sample no. | Common amplicons with cultural apple, % | Genetic diversity, % |
---|---|---|---|---|---|
1 | 93 | 7 | 18 | 50 | 50 |
2 | 78 | 22 | 19 | 30 | 70 |
3 | 45 | 55 | 20 | 50 | 50 |
4 | 30 | 70 | 21 | 50 | 50 |
5 | 74 | 26 | 22 | 60 | 40 |
6 | 70 | 30 | 23 | 50 | 50 |
7 | 85 | 15 | 24 | 33 | 67 |
8 | 80 | 20 | 25 | 60 | 40 |
9 | 56 | 44 | 26 | 90 | 10 |
10 | 43 | 57 | 27 | 36 | 64 |
11 | 47 | 53 | 28 | 43 | 57 |
12 | 43 | 57 | 29 | 46 | 54 |
13 | 50 | 50 | 30 | 45 | 55 |
14 | 45 | 55 | 31 | 42 | 58 |
15 | 43 | 57 | 32 | 44 | 56 |
16 | 26 | 74 | 33 | 46 | 54 |
17 | 80 | 20 | 34 | 42 | 58 |
As can be seen from Tables 4–8, the Golden
Sample no. | Common amplicons with cultural apple, % | Genetic diversity, % | Sample no. | Common amplicons with cultural apple, % | Genetic diversity, % |
---|---|---|---|---|---|
50, 56, 57, 58, 59, 61, 62, 63, 83, 89, 92: 97 | 100 | 79; 81; 82 | 40 | 60 | |
52; 53 | 49 | 51 | 86; 87 | 35 | 65 |
79; 81; 82 | 30 | 70 | 98; 99; 100; 101; 103 | 50 | 50 |
64; 65 | 45 | 55 | 51; 55; 60; 68; 69; 70; 71; 73; 74; 76; 83; 84; 88; 90; 93; 94; 95; 102; 104 | 100 | |
78; 80 | 43 | 57 |
Sample no. | Common amplicons with cultural apple, % | Genetic diversity, % | Sample no. | Common amplicons with cultural apple, % | Genetic diversity, % |
---|---|---|---|---|---|
ChR-17; ChR-21; ChR-22; ChR-11; ChR-20 | 100 | KR-1; KR-2 | 45 | 55 | |
ChR-2; ChR-12 and ChR-23 | 48 | 52 | KR-18; KR-4; KR-22 | 40 | 60 |
ChR-16; ChR-24 | 49 | 51 | SR-3-4 | 100 | |
ChR-9; ChR-10 | 50 | 50 | SR-3-6; SR-3-11 | 49 | 51 |
ChR-25; ChR-3; ChR-8; ChR-18; ChR-7; ChR-6; ChR-1; ChR-14; ChR-15; ChR-5 | 100 | SR-3-13; SR-3-3 | 45 | 55 | |
KR-19; KR-24; KR-14; KR-23; KR-26 | 100 | SR-2; SR-3-11; SR-3-9; SR-3-7; SR-3-8; SR-3-10; SR-3-5 | 100 | ||
KR-5; KR-3; KR-6; KR-21; KR-12; KR-13; KR-10; KR-11; KR-25; KR-27; KR-7; KR-15; KR-28; KR-8; KR-20; KR-18 | 100 |
Sample no. | Common amplicons with cultural apple, % | Genetic diversity, % | Sample no. | Common amplicons with cultural apple, % | Genetic diversity, % |
---|---|---|---|---|---|
Ssh -2 №7 and Ssh -2 №9 | 49 | 51 | AP, PS-17; PS-7; PS-12 and PS-18 | 100 | |
Ssh -2 №4 кв9; Ssh -1-2; Ssh -1-3 | 100 | 105, 106 and 107 (Kuznetsova Gorge) | 45 | 55 | |
DA KD –2 №17 and DA KD–2 №18; DA KD–2 №16 and DA KD–2 №19; DA Ssh 1-5; DA Ssh 1-2 and DA Ssh 1-1; | 40 | 60 | PS-8; PS-9; PS-14; PS-15; PS-11; PS-10; 108 and 109 (Kuznetsova Gorge); DA KD–2 №14; DA KD–2 №15; DA Ssh 1-3 and DA Ssh 1-4 | 100 |
Sample no. | Common amplicons with cultural apple, % | Genetic diversity, % | Sample no. | Common amplicons with cultural apple, % | Genetic diversity, % |
---|---|---|---|---|---|
KD 1-8; 1-13; 1-14; 1-15; 1-16 | 35 | 65 | 2-№19; 2-№20 | 35 | 65 |
KD 1-2;1-3; 1-4; 1-12; 1-16; 1-6; 1-11; 1-1;1-7; 1-9 and 1-10 | 100 | 2-№4; 2- №5; 2- №9 | 100 | ||
2-№11; 2-№12 | 40 | 60 | AP, DA Ssh 1-6; Ssh 1-7; Ssh 1-8; Ssh 1-9; Ssh 1-10; Ssh 1-15; Ssh 1-16; Ssh 1-17 | 100 | |
2-№1; 2-№6; 2-№7; 2-№8; 2-№10; 2-№13 | 33 | 67 | Ssh 1-20; Ssh 1-21 | 50 | 50 |
2-№2; 2-№3 | 35 | 65 | Ssh 1-12; Ssh 1-14; Ssh 1-18; Ssh 1-19 | 100 | |
2-№14; 2-№15; 2-№16 | 45 | 55 |
Sample no. | Common amplicons with cultural apple, % | Genetic diversity, % | Sample no. | Common amplicons with cultural apple, % | Genetic diversity, % |
---|---|---|---|---|---|
KZh-22; KZh-18; KZh-38; KZh-40 | 100 | KZh-43 and KZh-44 | 45 | 55 | |
KZh-23; KZh-25 and KZh-34 | 49 | 51 | D-9; гз-14 and GZ-15 | 40 | 60 |
KZh-20 and KZh-21 | 45 | 65 | USh-4 and USh -5 | 35 | 65 |
KZh-32; KZh-33 and KZh-46 | 49 | 51 | DA Ssh -2 №9 and DA Ssh -2 №11 | 49 | 51 |
KZh-45; KZh-47; KZh-48 and KZh-49 | 49 | 51 | KZh-19; KZh-24; KZh-26; KZh-27; KZh-28; KZh-29; KZh-30; KZh-31; KZh-35; KZh-36; KZh-37; KZh-39; KZh-41; KZh-42; KZh-50; D-7; D-8; D-10; D-11; D-12; GZ-13; GZ-16; GZ-17; KT-1; KT-2; KT-3; UB-6; DA Ssh -2 №2; DA Ssh - №5 | 100 | |
51х, 52х and 54х | 50 | 50 | 53х | 100 |
3. Conclusion
Thus, through molecular genetic analysis of 400 wild apple samples from the Ile Alatau and Dzungarian Alatau populations, ISSR markers have established the presence of loci that can serve as markers for identifying species and populations and identifying intraspecific genetic variation. To create living collections of
Acknowledgments
Studies were carried out within the framework of the Project of the Government of the Republic of Kazakhstan, GEF/UNDP “Conservation
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Notes
- Studies were carried out within the framework of the Project of the Government of the Republic of Kazakhstan, GEF/UNDP “Conservation in situ of mountain agro-biodiversity in Kazakhstan.”