in Wood Samples Identification

Abstract

This paper proposes a method for determining the microsatellite markers combination used to study the genetic structure of a woody plant population using the example of Pinus sylvestris. The developed method optimizes genetic analyzes conduction in the tasks of the forest genetic resources state monitoring. Over the past decade due to the negative economic and environmental consequences of illegal logging increasing attention has been paid to the origin of timber products in the world [1,2]. Statistics of imports and exports conducted by WWF experts in 2008 showed that a significant amount of illegally harvested wood enters the European and Chinese markets from Russia and Eastern Europe. In the Russian Federation only in 2008-2016 period were recorded 197,228 cases of illegal logging, total damage amounted to 104.5 billion rubles, reimbursed - 2.83 billion rubles. (2.7% of the amount of damage assessed). Illegal forests use has been identified in almost all regions of the Russian Federation [3]. In order to prevent these offenses, law enforcement authority officers should be able to conclusively identify the true origin of the wood transported [4]. One of the promising areas of evidence of the timber trade legality is the use of molecular-genetic methods of analysis. These methods are based on the using of genetic markers - microsatellites - varying regions (loci) in nuclear DNA and DNA of organelles (mitochondria and plastids) consisting of tandemly repeated nucleotide sequences. These markers are characterized by a high level of polymorphism and are often found in the genome [5]. The molecular-genetic method compared with the traditional denrochronological identification avoids timely collection of data such as tree age, diameter, height, thickness. The insufficient number or lack of clear annual rings due to wood decay severely limits the use denrochronological identification of wood samples [6]. However, nowadays there are no methods that allow to obtain minimal combinations of molecular primers that give the lowest probability of a coincidence of related multi-focused genotypes. Thus, the task of developing a method for determining the optimal sequence of microsatellite markers used to study the genetic structure of a woody plant population using the example of Scots pine is an urgent one.

Keywords

• genetic structure
• microsatellite markers
• Pinus sylvestris

Introduction

The microsatellite markers combination determination method

Wood samples of pine (Pinus sylvestris L.) taken from plantations growing near the Balakhta in the Krasnoyarsk Krai served as a reference sample. The selection cotained 29 samples, which is representative and accepted in the analysis of nuclear codominated nuclear markers. In molecular genetic studies, the average number of samples in the selection less than 30 individuals per cenopopulation [ 7-8 ]. Basic methodology for the DNA study relies on the following stages, i.e., DNA extraction (based on the lysis of cell walls), DNA amplification via polymerase chain reaction (PCR) method with specific primers for nuclear microsatellite or organelle alleles, genotyping of the PCR products in automated sequencer, and finally comparison of the DNA profiles obtained for all samples. The wood was thoroughly crushed, homogenized, and the DNA was isolated by the CTAB method [ 9 ]. The method is based on the cells breakdown under the cetyltrimethylammonium bromide (CTAB) effect, the removal of proteins using chloroform and the precipitation of DNA with isopropanol. PCR was performed with the use of a commercial kit of reagents "ScreenMix" (JSC "Eurogen", Russia). Amplification was carried out in the thermal cycle T100 Thermal Cycler (BioRad). The amplification products were separated by electrophoresis on 6% polyacrylamide gel using TrisBorate-EDTA electrode buffer and stained with ethidium bromide. PCR products were visualized by UV using gel documentation system (Figure 1). Data analysis was performed using Vilber Lourmat Bio Capt V. 12.5.0.0 software.

As a result of preliminary work to identify the most polymorphic and stably amplifying loci, 10 microsatellite markers were selected. Table 1 presents the characteristics of recommended nuclear microsatellite loci for Scots pine [ 10–13 ].

Currently, the processing of the results of genetic analysis is carried out using proprietary software GenAlEx [ 14 ], a free add-in for MS Excel. The results obtained using the GenAlEx program are shown in Table 2. The smallest chance of a coincidence of multilocus genotypes (2.2E-08) is achieved only with 10 genetic markers combination: psy119, psy157, PtTx3116, PtTx3107, PtTx4001, lw_isotig21953, PtTx4011, SPAC11.4, lw_isotig04306, lw_isotig27940. This value indicates a low probability of random genotypes coincidence [ 15 ]. The order of genetic markers is presented in table 1 and in figure 2.

Identity probability 1+2 1+2+3 6,3 ∙ 10−3 1,3 ∙ 10−3 6,6 ∙ 10−5 2,3 ∙ 10−5 1,5 ∙ 10−6 2,3 ∙ 10−7 2,2 ∙ 10−8

Genetic analysis conduction of the identity of wood samples determination, using all 10 markers, is very laborious and expensive. To reduce these costs is proposed a method for determining the optimal minimum sequence of markers to eliminate false positive sample identification. The purpose of the method proposed is to find a number and sequence of markers that will give the minimum probability of false-positive sample identification.

The method proposed in this paper is based on the analysis of the alleles pairs occurrence of each locus among the samples of a deliberately unique selection. As a reference selection used samples of Scots pine, taken from natural plantation, growing near the Balakhta in the Krasnoyarsk Krai. The reference selection contains 29 numbered unique samples and initially tested with 10 markers.

1.2E+00 1.0E+00 y t ili 8.0E-01 b a b y t i d I ro6.0E-01 p t en4.0E-01 2.0E-01 0.0E+00

Let us denote

Locus combinations genetic markers.

= { , = 1. .10}, lw_isotig …

SPAC 11.4 146/156 138/142 187/193 187/187 184/187 187/193 175/187

… 184/187 178/187 193/193 187/193 187/187 193/193 lw__isotig04306 175/187 178/187 181/187 184/184 184/187 184/193 187/187 187/193 193/193 247/247 247/247

The next stage of the method is to rank the sets of identifiers grouped in pairs from the sets by the number of unique pairs, i.e. in priority , in which the maximum number | ( )| = 1. intersection of only those sets, which are subsets of a capacity at least two:

Then there is an iterative process of intersection of sets . Each set of grouped genotypes intersects with other sets of grouped genotypes. The first step of the iteration is a pairwise intersection of the sets . The results of the Then are ranked in cardinality ascending. At the next iterations, intersects with the remaining : = { = ( ) ∩ ( ): | | > 1; , , , , ∈ ; , < 30; , ≤ 10}.

=

∩ .

The process continues until the intersection becomes an empty set. Thus, by analyzing a test selectionin a similar way, it is possible to obtain an optimal sequence of markers that uniquely identifies samples of the test species.

For Scots pine samples, taken in natural plantation growing growing near the Balakhta in the Krasnoyarsk Krai, the optimal minimal combination of genetic markers was the sequence lw_isotig21953, SPAC11.4, PtTx3107.

To verify the

method, a control group of Scots pine wood from the same plantation was selected and analyzedTable 5 presents the results of grouping samples of the control group according to the values of the lw_isotig04306 marker alleles.

ids 178/187 181/187 184/184 184/187 184/193 187/187 187/193 193/193

6 6+8 6+8+4 6+8+4+10 {15,16} {24,23} {14,13,22} {9,19,21}

Conclusion

To determine the identity of Scots pine samples , taken in natural plantation growing near the Balakhta of the Krasnoyarsk Krai, the sequence of genetic markers {lw_isotig21953, SPAC11.4, PtTx3107} was the minimum optimal combination. The effectiveness of the selected sequence of markers tested on the control group. The proposed method of the optimal sequence microsatellite markers selection can significantly reduce labor, time and material costs in the wood samples identity determination. In further studies, it is planned to use this algorithm for the marker selection in relation to other sets to similar genetic analysis.

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