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Article

Genetic Species Identification Using ycf1b, rbcL, and trnH-psbA in the Genus Pinus as a Complementary Method for Anatomical Wood Species Identification

by
Minjun Kim
and
Tae-Jong Kim
*
Department of Forest Products and Biotechnology, Kookmin University, Seoul 02707, Republic of Korea
*
Author to whom correspondence should be addressed.
Forests 2023, 14(6), 1095; https://doi.org/10.3390/f14061095
Submission received: 5 April 2023 / Revised: 10 May 2023 / Accepted: 24 May 2023 / Published: 25 May 2023
(This article belongs to the Special Issue Recent Advances in Wood Identification, Evaluation and Modification)
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Abstract

:
This study proposes the use of genetic analysis as a complementary method for species identification in the genus Pinus, particularly in cases where anatomical identification is challenging. Pinus species were grouped based on anatomical similarities, and the efficacy of using ycf1b, which is the most variable for Pinus species identification, and rbcL, which is a suggested DNA barcode for land plants, was evaluated within each group. Sequences for each species were obtained from the National Center for Biotechnology Information database and were used to perform phylogenetic analysis. Among the species in Group 1 (P. echinata, P. elliottii, P. ponderosa, P. radiata, P. rigida, P. taeda, and P. virginiana), rbcL was only effective in identifying P. radiata and P. ponderosa, while ycf1b classified five species. An additional DNA barcode, trnH-psbA, was needed to identify P. radiata and P. taeda. In Group 2 (P. densiflora, P. sylvestris, and P. thunbergii), most species were identified using both rbcL and ycf1b, with the exception of possible hybrids of P. densiflora and P. sylvestris. In Group 3 (P. koraiensis and P. strobus), two species were identified using rbcL and ycf1b. Combining genetic species identification with anatomical identification can accurately identify species of the genus Pinus.

1. Introduction

Accurately identifying the species of wood is very important in many tasks, such as forensic identification of illegal timber, restoration without damaging the value of cultural assets, and use of industrially appropriate species [1]. Wood species were mainly identified through anatomy analysis using a microscope [2,3,4,5,6]. However, it may sometimes be difficult to distinguish between structurally similar species based on anatomical features alone. DNA barcoding can provide an alternative and complementary means to identify species of wood by analyzing the gene sequences [7]. It is difficult to obtain DNA for genetic analysis from wood that has been processed, including drying, and has been in use for a prolonged period. However, a method for successfully extracting DNA from old wood using sandpaper and an improved extraction method has been proposed [8].
In addition to DNA barcoding, fluorescence in situ hybridization (FISH) methods are another approach that can be used to identify wood species [9]. FISH utilizes short DNA or RNA probes that selectively bind to a target sequence of interest in a complementary manner. These probes are labeled with fluorescent molecules, which enable the visualization of the presence and location of the target nucleic acid sequences in the wood samples. Target nucleic acid sequences for the FISH method for wood species identification include telomere repeat, centromeric repeat, and rRNA [10]. However, one of the major challenges in using the FISH method to identify plant species is the development of appropriate probes for each species [11].
In addition to FISH, other methods such as random amplified polymorphic DNA (RAPD) and restriction fragment length polymorphisms (RFLP) have been used for plant species identification [12]. While conventional PCR selectively amplifies only the target gene, RAPD performs non-specific gene amplification using short random primers to compare different-sized fragment patterns for species identification. However, a potential weakness with RAPD is the low reproducibility of different-sized fragment patterns obtained in each experiment [12]. RFLP is another method that can suggest a change in the nucleotide sequence of a specific site by observing the pattern of the cut fragment due to the difference in the nucleotide sequence of the DNA site cut by the restriction enzyme. However, a library of polymorphisms of each species is required for plant species identification using RFLP, and the average probability of distinguishing two alleles taken at random is not high [12]. Therefore, in this study, we propose a method for wood species identification using phylogenetic analysis based on the entire nucleotide sequence of DNA barcodes that have been shown to be useful in plant species identification. Although this method may not be suitable for identifying species of the entire Pinus genus, it can be used effectively to identify a limited number of species for which anatomical species identification in wood is difficult.
The genus Pinus has an important ecological role in providing habitats for wildlife. Furthermore, its extracts exhibit antimicrobial, antidiabetic, and anti-inflammatory activities [13,14,15,16]. It accounted for approximately 36% of Korea’s medium-density fiberboard raw materials in 2008 [17]. In addition, the genus Pinus occupied more than 22% of Korean forests in 2015 [18]. In addition, Pinus was used as building material for architectural heritage sites in Korea [19]. Therefore, it is important to accurately identify the wood species of the genus Pinus. Among the species of the genus Pinus, species that are anatomically difficult to distinguish from each other are classified into three groups in Table 1. Species in Group 1 share anatomical features such as distinct growth-ring boundaries, pinoids, and thin-walled epithelial cells [20,21,22,23,24,25,26,27]. Species in Group 2 are characterized by window-like cross-field pits and thin-walled epithelial cells [20,26,28]. Species in Group 3 are characterized by gradual transition from early wood to late wood, thin-walled epithelial cells, and window-like cross-field pits [20]. These common structural features make anatomical identification difficult through microscopic observation.
Plant cells have a characteristic organelle, the plastid, and the plastid has a genome independent of the nucleus and mitochondria. It has been proposed that plant species can be identified using plastid genomes owing to several advantages, such as high copy number, conserved regions, variable regions, rapid evolution, and maternal inheritance [2,3]. In addition, the plastid genome has a higher number of reported nucleotide sequences compared to mitochondrial or nuclear genomes in plants, thus facilitating DNA barcode analysis for species identification [29,30]. In previous studies, matK, rbcL, rpoB, and ycf1 were suggested as genes for DNA barcoding [31,32,33]. matK and rbcL were suggested as DNA barcodes for land plants by the Consortium for the Barcode of Life—Plant Working Group [34]. rpoB was suggested to be more efficient in family level identification than genus level identification [35]. Although ycf1 has been proposed as the most promising plastid DNA barcode for terrestrial plants [30], it is a very large gene encoding approximately 1800 amino acids. As part of the coding region of ycf1, ycf1b with a size of about 1 kb was suggested to be more efficient in species identification in a previous study [36].
In the previous study, effectiveness of the DNA barcoding for species identification in the genus Pinus using matK, rbcL, trnH-psbA, trnL-trnF, rpl20-rps18, trnV, ycf1, and ycf2 was evaluated [37]. However, the results did not provide clear evidence for the possibility to identify genetically closely related species, such as P. mugo, P. uncinata, and P. uliginosa [37]. In this study, we evaluated whether rbcL and ycf1b could be used for genetic species identification within small groups of the genus Pinus, where species identification was difficult by anatomical observation, based on available genetic information reported to date. When the species could not be identified by ycf1b, the possibility of species identification by trnH-psbA was additionally evaluated by limiting the species to which species could not be identified. rbcL and ycf1b were evaluated in this study because rbcL is a suggested DNA barcode for land plants, and ycf1 is the most variable in Pinus species identification [37]. matK was not used in this study because the probability of species identification of the genus Pinus was low, i.e., 23% [30].

2. Research Methods and Data Sources

2.1. Sequences of rbcL, ycf1b, and trnH-psbA in the Genus Pinus

Gene sequences covering more than 90% of the rbcL, ycf1b, and trnH-psbA sequences from the species of the genus Pinus were collected from the National Center for Biotechnology Information (NCBI) gene database (Table 1). In the case of trnH-psbA, only the sequences of P. taeda and P. radiata, which could not be distinguished by ycf1b, were analyzed. For sequences deposited with the chloroplast genome or whole plastid, the nucleotide sequence of the corresponding gene was obtained through alignment using known base sequences of rbcL, ycf1b, and trnH-psbA from the same species [38].

2.2. Gene Alignment and Phylogenetic Analysis

Nucleotide sequence alignment of the collected genes was performed using ClustalW [38]. The aligned sequences were exported using BioEdit 7.2. [39]. In this study, the size of the compared sequence was presented for each group using aligned sequences. The ability of each gene to identify species was assessed by the number of non-identical sites. The phylogenetic analysis was conducted using the maximum likelihood method and the Kimura 2-parameter model with 1000 bootstrap replications in the MEGA 11 software [40]. A cut-off value of 50% was applied to the condensed tree. As an outgroup, the corresponding genes of Chamaecyparis pisifera, which belongs to the same class, Pinopsida, as the genus Pinus, were used.

3. Results and Discussion

3.1. Species Identification of P. echinata, P. elliottii, P. ponderosa, P. radiata, P. rigida, P. taeda, and P. virginiana in Group 1 of Table 1 through Phylogenetic Analysis

Phylogenetic analysis was performed using the rbcL and ycf1b gene sequences in Group 1 of Table 1, where it is difficult to identify species by anatomical microscopic observation (Figure 1 and Figure 2, respectively). When using rbcL, only two species, P. radiata and P. ponderosa, were classified independently from other species, so rbcL could be used for identification of these two species. However, it was difficult to distinguish between P. echinata and P. elliottii, between P. taeda and P. virginiana, and between P. rigida and P. taeda (Figure 1). In the phylogenetic analysis using ycf1b (Figure 2), five species were classified independently and the remaining two species, P. taeda and P. radiata, could not be distinguished. In the genus Pinus, rbcLb showed discrimination success of more than 20%, and ycf1b showed discrimination success of more than 50% [30]. This is consistent with the higher discrimination success of ycf1b in our results.
In general, single nucleotide polymorphism genotyping is one of the effective tools in DNA barcoding [41,42], but while it is suitable for identification of individuals, it has limitations in distinguishing species [8]. The size of the compared sequences used for species identification and the ratio of bases that show variable sites between species or individuals are summarized in Table 2. As the overhang parts were trimmed after alignment, the size of the compared sequences used in this study is slightly different compared to other studies. In the comparison of rbcL in Group 1, 2.4% of the bases were non-identical. In the case of ycf1b in Group 1, the size of the compared base sequence was 1057 bases, which was smaller than the 1325 bases of the compared region of rbcL, but the number of non-identical bases was 83, which was more than 32 of rbcL. This different non-identical base ratio suggested that ycf1b had more information for species identification than rbcL. In the results of species identification, five species were independently classified by ycf1b compared to two species independently classified by rbcL in Group 1. Therefore, ycf1b is more useful for species identification than rbcL in Group 1.
According to a study on DNA barcoding of genera other than Pinus, the discrimination success percentage of ycf1b was found to be about 60% in Iris, 100% in Armeniaca, 50% in Paeonia, 40% in Quercus, and approximately 60% in Panax [30]. Additionally, the discrimination success percentage of rbcLb, a part of rbcL, was about 50%, 0%, 10%, 25%, and 60%, respectively [30]. These results suggest that ycf1b is more effective in discriminating between closely related species compared to rbcLb, which has a lower discrimination success percentage. Other previous studies have also reported that rbcL is unsuitable for identifying species of Sweretia chirayita and its adulterant species, as well as species of the genus Ardisia [43,44]. These previous results in many plants support that ycf1b is better than rbcL in species identification.
To discriminate P. radiata and P. taeda, which are indistinguishable even in species identification using ycf1b, species identification was performed using trnH-psbA, which was proposed to be used for tree species identification (Figure 3). The non-coding spacer region, trnH-psbA, has been extensively utilized for DNA barcoding in the past [45,46,47]. However, due to its lower primer universality compared to rbcL and difficulties in alignments caused by its variable sequence size [48,49], trnH-psbA was not used as the primary analysis DNA region in this study. Phylogenetic analysis using trnH-psbA classified P. radiata and P. taeda independently. Therefore, according to the currently available genetic information, if ycf1b is used for species identification in Group 1 and trnH-psbA is used additionally, the identification of seven species, which are anatomically difficult-to-identify species, is possible by genetic analysis. This result is consistent with a previous study showing a higher discrimination success percentage of trnH-psbA than rbcLb but lower than ycf1b in the genus Pinus [30]. In order to show in detail which bases differ between species, the nucleotide sequences of species that are difficult to classify in Figure 1 and Figure 2 are aligned (Supplementary Figures S1–S4).

3.2. Species Identification of P. densiflora, P. sylvestris, and P. thunbergii in Group 2 of Table 1 through Phylogenetic Analysis

In Group 2, both genes, rbcL and ycf1b, were clearly identified in P. thunbergii, but could not differentiate between P. densiflora and P. sylvestris (Figure 4). In a previous study, ycf1 also did not distinguish well between P. densiflora and P. sylvestris [33]. In China, the possibility of hybridization between P. densiflora and P. sylvestris has been reported because of overlapping habitats [35,50]. The P. densiflora genes used in this study, MZ677091, NC_062639, and NC_062640, are plastid genes of species from China. If such hybridization has happened, species identification using the chloroplast gene will be fundamentally impossible between P. densiflora and P. sylvestris. In order to show the difference in nucleotide sequence between P. densiflora and P. sylvestris, which are difficult to discriminate in Figure 4, the nucleotide sequences of rbcL and ycf1b from the species were aligned (Supplementary Figures S5 and S6). Many bases of P. densiflora, MZ677091, NC_062639, and NC_062640, were identical to the corresponding bases of P. sylvestris. This observation supported the hybridization between P. densiflora and P. sylvestris in China. Excluding individuals presumed to have hybridization, phylogenetic analysis using rbcL and ycf1b can discriminate the species of P. densiflora and P. sylvestris. In Group 2, the ratio of non-identical bases in rbcL and ycf1b was 1.3% and 2.3%, respectively, and there was no significant difference (Table 2).
In addition to species identification using DNA barcoding, there was also a study that identified P. densiflora and P. sylvestris through a chemical analysis method using near-infrared spectroscopy and multivariate analysis [19]. P. densiflora and P. thunbergii were also identified through the same method [51]. However, since the results were not obtained for P. densiflora and P. sylvestris in China, additional research is needed to understand the differences in the case of hybridized species. These previous studies suggest the possibility of using chemical methods for identifying wood between anatomically similar species, in addition to biological methods.

3.3. Species Identification of P. koraiensis and P. strobus in Group 3 of Table 1 through Phylogenetic Analysis

In Group 3, P. koraiensis and P. strobus were each independently classified in phylogenetic analysis using rbcL and ycf1b (Figure 5). The ratio of non-identical bases in rbcL and ycf1b was 0.5% and 1.8%, respectively, which were low compared to other groups (Table 2). Despite these low base variations, they showed high species–specific discrimination and contained sufficient information for species identification of P. koraiensis and P. strobus.
The present study indicates that ycf1b is a more suitable DNA barcode for species identification in all three species groups of the genus Pinus in Table 1 compared to rbcL, as ycf1b was more variable. This finding is consistent with a previous study that observed a non-identical base ratio of approximately 22% in ycf1 from 55 Pinus species [33]. Furthermore, previous study has also indicated that rbcL is more effective in identifying species in lower plants compared to seed plants [52]. Notably, our results demonstrated the efficacy of ycf1b in discriminating between species in the genus Pinus, which are challenging to identify anatomically. However, it is worth noting that the use of ycf1b as DNA barcode for species identification may not be universally applicable to all plants, given that the family Poaceae has a severe deletion of the ycf1 gene [53]. Therefore, it is essential to confirm the presence or absence of such a gene deletion when using ycf1 for identifying plant species other than the genus Pinus.
Despite the use of various DNA barcodes, accurately identifying all species within the genus Pinus remains a challenge [30,37]. This underscores the limitations of relying solely on DNA barcodes for species identification. Therefore, for accurate identification of wood species within the genus Pinus, anatomical identification can be used first, followed by molecular identification using ycf1b and trnH-psbA as DNA barcodes.

4. Conclusions

In the genus Pinus, while identifying species by anatomical analysis of wood is difficult, genetic analysis can be used as a supplementary method to identify species accurately. Among a group comprising seven species, i.e., P. echinata, P. elliottii, P. ponderosa, P. radiata, P. rigida, P. taeda, and P. virginiana, five species can be identified using ycf1b, while P. radiata and P. taeda could be identified using trnH-psbA in addition. In Group 2 with three species, i.e., P. densiflora, P. sylvestris, and P. thunbergii, P. thunbergii could be identified using rbcL and ycf1b, and P. densiflora and P. sylvestris could also be classified, except for individuals in which hybridization may have occurred. In Group 3 with P. koraiensis and P. strobus, two species were independently classified using rbcL and ycf1b. This study suggests that wood species of the genus Pinus can be first identified anatomically using microscopic methods. Additionally, the DNA barcoding method using ycf1b and trnH-psbA can be used to identify species that are difficult to identify anatomically, in order to accurately identify the wood species of the genus Pinus.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/f14061095/s1, Figure S1: Alignment of rbcL from P. echinata and P. elliottii; Figure S2: Alignment of rbcL from P. rigida and P. taeda; Figure S3: Alignment of rbcL from P. taeda and P. virginiana; Figure S4: Alignment of ycf1b from P. radiata and P. taeda; Figure S5: Alignment of rbcL from P. densiflora and P. sylvestris; Figure S6: Alignment of ycf1b from P. densiflora and P. sylvestris.

Author Contributions

Conceptualization, M.K. and T.-J.K.; methodology, M.K.; software, M.K.; validation, M.K.; formal analysis, M.K.; investigation, M.K.; resources, M.K.; data curation, M.K. and T.-J.K.; writing—original draft preparation, M.K.; writing—review and editing, T.-J.K.; visualization, M.K.; supervision, T.-J.K.; project administration, T.-J.K.; funding acquisition, M.K. and T.-J.K. All authors have read and agreed to the published version of the manuscript.

Funding

This paper was supported by the Korea Institute for Advancement of Technology (KIAT) grant funded by the Ministry of Trade, Industry and Energy (MOTIE) (P0012725).

Data Availability Statement

The data presented in this study are available on request from the corresponding author. The data are not publicly available due to intellectual property protection.

Acknowledgments

All authors thank Jung-Ae Oh from the Korea Forestry Promotion Institute for suggesting three groups that are difficult-to-identify species of the genus Pinus owing to their similar anatomical structures.

Conflicts of Interest

The authors declare no conflict of interest.

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Forests 14 01095 g001 550
Figure 1. Species identification of P. echinata, P. elliottii, P. ponderosa, P. radiata, P. rigida, P. taeda, and P. virginiana in Group 1 of Table 1 through phylogenetic analysis using rbcL gene sequences.
Figure 1. Species identification of P. echinata, P. elliottii, P. ponderosa, P. radiata, P. rigida, P. taeda, and P. virginiana in Group 1 of Table 1 through phylogenetic analysis using rbcL gene sequences.
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Forests 14 01095 g002 550
Figure 2. Species identification of P. echinata, P. elliottii, P. ponderosa, P. radiata, P. rigida, P. taeda, and P. virginiana in Group 1 of Table 1 through phylogenetic analysis using ycf1b gene sequences.
Figure 2. Species identification of P. echinata, P. elliottii, P. ponderosa, P. radiata, P. rigida, P. taeda, and P. virginiana in Group 1 of Table 1 through phylogenetic analysis using ycf1b gene sequences.
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Forests 14 01095 g003 550
Figure 3. Species identification of P. radiata and P. taeda through phylogenetic analysis using trnH-psbA sequences.
Figure 3. Species identification of P. radiata and P. taeda through phylogenetic analysis using trnH-psbA sequences.
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Forests 14 01095 g004 550
Figure 4. Species identification of P. densiflora, P. sylvestris, and P. thunbergii in Group 2 of Table 1 through phylogenetic analysis using (a) rbcL and (b) ycf1b gene sequences.
Figure 4. Species identification of P. densiflora, P. sylvestris, and P. thunbergii in Group 2 of Table 1 through phylogenetic analysis using (a) rbcL and (b) ycf1b gene sequences.
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Forests 14 01095 g005 550
Figure 5. Species identification of P. koraiensis and P. strobus in Group 3 of Table 1 through phylogenetic analysis using (a) rbcL and (b) ycf1b gene sequences.
Figure 5. Species identification of P. koraiensis and P. strobus in Group 3 of Table 1 through phylogenetic analysis using (a) rbcL and (b) ycf1b gene sequences.
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Table
Table 1. Species groups of the genus Pinus that are difficult-to-identify species owing to similar anatomical characteristics under a microscope.
Table 1. Species groups of the genus Pinus that are difficult-to-identify species owing to similar anatomical characteristics under a microscope.
GroupGeneSpecies NameNCBI Accession Number
Group 1rbcLP. echinataAY724754, AY947435, JN854204, MZ424449, NC_065458
P. elliottiiAY724755, JN854202, NC_042788
P. ponderosaAY497234, DQ353721, FJ899555, JN854171, JN854172, NC_067715
P. radiataAY497250, JN854165, X58134
P. rigidaAY724757, JN854163, JQ512587, JQ512589, MZ424450, NC_065459,
P. taedaAF119177, AY724758, FJ899561, JQ512592, KC427273, KY964286
P. virginianaAY947430, JN854155, JQ512596
ycf1bP. echinataKC157080, KC157180, JN854204, MZ424449, NC_065458
P. elliottiiJN854202, KC157104, NC_042788
P. ponderosaFJ899555, JN854171, JN854172, KC157087, KC157140, KC157195, KP089392, KP128671
P. radiataJN854165, KC157129,
P. rigidaJN854163, KC157079, KC157177, KP128673, KP205539, MZ424450, NC_065459, NC_067715, OL547484
P. taedaFJ899561, KC157082, KC427273, KY964286
P. virginianaJN854155, KC157196
trnH-psbAP. radiataFR832544, JN854165, KC157276, KC157332, KC157399,
P. taedaFJ899561, KC157213, KC427273, KY964286, MF945991, MK895630
Group 2rbcLP. densifloraJN854210, MF990371, MT786135, MZ677091, NC_042394, NC_062639, NC_062640
P. sylvestrisJN854158, KR476379, MT787466, MT796488
P. thunbergiiD17510, JQ512594, MH612862, MW599991
ycf1bP. densifloraJN854210, KP089385, MF990371, MT786135, MZ677091, NC_042394, NC_062639, NC_062640
P. sylvestrisJN854158, KP089414, KR476379, MT787466, MT796488
P. thunbergiiD17510, FJ899562, KP089381, MH612862, MW599991
Group 3rbcLP. koraiensisAB019797, AY228468, EF440596, JQ512578, JQ512579, NC_004677
P. strobusAB019798, AF479880, AY497219, FJ899560, JQ512590, KP099650, NC_026302
ycf1bP. koraiensisAY228468, KP089410, KP128638, KP128639, NC_004677
P. strobusFJ899560, KP089389, KP099650, KP128655, KP128656, NC_026302
Table
Table 2. Sequence information used for genetic species identification in three groups.
Table 2. Sequence information used for genetic species identification in three groups.
GroupGene NameCompared Sequence Size (Bases)Number of Non-Identical Sites
(Percentage of Non-Identical Bases)
1rbcL132532 (2.4%)
ycf1b105783 (7.9%)
2rbcL142718 (1.3%)
ycf1b118427 (2.3%)
3rbcL13027 (0.5%)
ycf1b125622 (1.8%)
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Kim, M.; Kim, T.-J. Genetic Species Identification Using ycf1b, rbcL, and trnH-psbA in the Genus Pinus as a Complementary Method for Anatomical Wood Species Identification. Forests 2023, 14, 1095. https://doi.org/10.3390/f14061095

AMA Style

Kim M, Kim T-J. Genetic Species Identification Using ycf1b, rbcL, and trnH-psbA in the Genus Pinus as a Complementary Method for Anatomical Wood Species Identification. Forests. 2023; 14(6):1095. https://doi.org/10.3390/f14061095

Chicago/Turabian Style

Kim, Minjun, and Tae-Jong Kim. 2023. "Genetic Species Identification Using ycf1b, rbcL, and trnH-psbA in the Genus Pinus as a Complementary Method for Anatomical Wood Species Identification" Forests 14, no. 6: 1095. https://doi.org/10.3390/f14061095

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