Analysis on single nucleotide polymorphisms of the PeTPS-(-)Apin gene in Pinus elliottii.

BACKGROUND: Resin-tapping forests of slash pine (Pinus elliottii) have been set up across Southern China owing to their high production and good resin quality, which has led to the rapid growth of the resin industry. In this study, we aimed to identify molecular markers associated with resin traits in pine trees, which may help develop marker-assisted selection (MAS).
METHODS: PeTPS-(-)Apin gene was cloned by double primers (external and internal). DnaSP V4.0 software was used to evaluate genetic diversity and linkage disequilibrium. SHEsis was used for haplotype analysis. SPSS was used for ANOVA and χ2 test. DnaSP v4.0 software was used to evaluate genetic diversity.
RESULTS: The full length PeTPS-(-)Apin gene was characterized and shown to have 4638 bp, coding for a 629-amino acid protein. A total of 72 single nucleotide polymorphism (SNP) loci were found. Three SNPs (CG615, AT641 and AG3859) were significantly correlated with α -pinene content, with a contribution rate > 10%. These SNPs were used to select P. elliottii with high α-pinene content, and a 118.0% realistic gain was obtained.
CONCLUSIONS: The PeTPS-(-)Apin gene is not uniquely decisive for selection of plus slash pines with stable production, high yield, and good quality, but it can be used as a reference for selection of other resin-producing pines and other resin components.

Introduction

Resin, synthesized in the trunk of a pine tree, is a mixture of terpenoids. It is distilled to produce liquid turpentine and solid resin. Turpentine is a volatile essential oil, mainly a mixture of monoterpenes and semiterpenes. It can be directly used to dilute oil paints and analgesics and can also be processed into camphor, peppermint, terpineol, and spices. Resin is a translucent solid and a mixture of various diterpenoids. It can be used as a raw material in the industrial production of paints, rubber, inks, adhesives, dyes, and coatings [1]. With the introduction of slash pine (Pinus elliottii) from the United States, the available raw material resources of resin have been greatly increased. Previously, 90% of resin in the Chinese market was obtained from masson pine (P. massoniana) and a small amount from Simao (P. kesiya) and Yunnan (P. yunnanensis) pines, which are native trees. We found that the average annual resin yield of a slash pine individual is 5.0 kg, which is the highest resin yield among resin-producing-pines species. In slash pine, the income from resin far exceeds that from wood [2, 3].

The chemical composition of resin has a substantial influence on its quality, and different components have different uses in industrial production. Research has shown that the chemical components and contents of resin are heritable and controlled by additive and dominant gene effects [4]. Li (2012) selected four families with high turpentine content from 49 half-sibling families of slash pine as seed orchard materials, and the realistic genetic gain of turpentine content reached 426.15% [5]. Our group (2015) selected seven individuals with high turpentine content from previously selected 186 plants with high resin content and obtained a genetic gain of 51.57% in turpentine content based on high resin content [2].

However, these breeding efforts are based on mature forests, and we hoped to solve the problem of long generation cycles of trees using molecular biology methods. The way to solve this problem is to identify relevant molecular markers for early selection through association analysis. The methods of association analysis mainly include genome-wide association studies (GWAS) and association analysis of candidate genes. The pine tree, however, has a large genome, more than seven times the size of the human genome, with nearly 80% repeat sequences [6]. Even though the whole genome of loblolly pine (P. taeda, the model organism of pine species) has been sequenced, we were still unable to conduct GWAS studies in a short time [7, 8]. We can only rely on other method—candidate gene association analysis, which assumes candidate genes according to physiological functions and biochemical processes associated with the target trait [9]. Currently, association analysis studies of pine trees mainly focus on functional candidate gene strategies labeled with SNPs [10, 11]. Candidate genes associated with resin traits have been cloned from resin-producing-pines trees such as P. densata [10, 12], P. densiflora [13], P. taeda [14], P. elliottii [15], P. kesiya var.langbianensis [16], and P. massoniana [17]. There are also a few reports on the association between these genes and pine resin traits [11]. However, there are no reports in which these genes have been used to improve the pine tree itself. This may be related to the complexity of the resin trait, which is a quantitative character. The improvement in production capacity and resin quality using molecular biological methods should be an important method for pine trees.

Terpene synthase (TPS) is one of the key enzymes in the biosynthesis of the resin mixture and is also the enzyme found in most species and with the most diversified functions. TPS can be divided into six gene families: Tpsa, Tpsb, Tpsc, Tpsd, Tpse, and Tpsf. Tpsd is a unique gene family in gymnosperms, consisting of three subfamilies: monoterpene synthase gene Tps-d1, sesquiterpene thin synthase gene Tps-d2, and diterpene synthase gene Tps-d3 [18]. Different plants contain the TPS gene, which encodes proteins with highly similar amino acid sequences. Although the genes probably evolved from a common ancestor, the distribution of exons and introns and their quantities are not the same among species [19]. It is generally believed that intron loss occurred during TPS gene evolution, that is, the shorter the length or the lower the number of introns, the higher the degree of evolution. The TPSd gene families in gymnosperms have more number of and longer introns than the TPS gene families in angiosperms [19]. These studies provide evidence for the cloning and expression of TPS gene in P. elliottii.

α-Pinene, a monoterpene compound with the highest content in turpentine mixtures, is a critical resistance molecule against insect, bacterial, and mechanical trauma in pines. It has left- and right-handed forms but is generally present in the left-handed form in resin [20]. The left handed α-pinene synthetase gene ((-)Apin) has been cloned in P. taeda [14], P. contorta [21], and P. banksiana [21]. Studies show that (-)Apin gene expression in pine trunk is correlated with α-pinene content in turpentine [22], which in turn is positively correlated with the production of turpentine and is positively or negatively correlated with other turpentine components. The identification of molecular markers related to high yield, superior quality resin would significantly promote genetic improvement and germplasm innovation. Compared with linkage analysis, correlation analysis can identify important alleles that are closely related to phenotypic traits.

To search for molecular markers related to resin traits to be used in marker-assisted selection (MAS), the PeTPS-(-)Apin gene was cloned, and its single nucleotide polymorphisms (SNPs) and linkage disequilibrium were analyzed. Functional SNPs were screened by ANOVA, 110 samples were typed, and the optimal selection scheme of P. elliottii with high α-pinene content was also considered. Selection of valuable plus trees will provide excellent materials for the breeding of resin-producing-pines and also provide a theoretical basis for the sustainable development of the resin market.

Materials and methods

Plant materials

Progeny tests were conducted at Baiyunshan forest farm (26°51′N, 115°11′E), Ji’an City, Jiangxi Province, China. The slash pines were cultivated on a flat woodland (hilly red soil, subtropical climate, 90 m altitude, 1646 mm rainfall, average temperature of 18.6°C). Three progeny trials comprised 110 open-pollinated families of superior trees that were collected from three seed orchards in the United States and one in China (listed in Table 1) and then planted in the spring of 1990 at Ganzhou, Ji’an, and Jingdezhen in Jiangxi Province, Southern China. The progeny trial had a completely randomized block design with five replicates, each consisting of a four-tree plot, and the distance between each tree was 4 m (Figs 1 and 2). A single plant of each family was randomly selected in the Ⅱ block group of the test forest. If all the plants were missing (those suffering from damage and pests), a single plant of this family was randomly selected in the other block group. A total of 110 samples from 110 families were obtained.

Table 1

Basic information of test materials.

Group	Sources of Sample Trees	Number of Families
A	Seed orchards of Georgia, USA	12
B	Seed orchards of Mississippi, USA	48
C	Seed orchards of Florida, USA	45
D	Forestry Research Institute of Ji’an, China	5

Fig 1

Photo of test forest.

Fig 2

Schematic diagram of test forest.

PeTPS-(-)Apin gene cloning

Prior to gene cloning, the tender buds or needles of P. elliottii were collected, labeled, and then stored at -80°C. DNA was extracted using the TIANGEN KIT and diluted to 50 ng/μL. The working solution was kept at 4°C, and the stock solution was kept at -80°C. PeTPS-(-)Apin gene was obtained from genomic DNA using double outer and inner primers (sequences are listed in Table 2). PCR amplification was performed using the PrimeSTAR HS DNA Polymerase (Takara, Japan). The reaction volume in the first round of amplification (outer primes) was 10 μL, and in the second round of amplification (inner primes) 50 μL. PCR products were sequenced by the Shanghai Sango company.

Table 2

Primer sequences for PeTPS-(-)Apin gene cloning.

Primer	Sequences (5’~3’)
outer-F	ATAGTCCTTGAATTGTGGAG
outer-R	GAGAAAAATCCTACTGGTGT
inner-F	GAGACGTATTGCGATGTTAT
inner-R	CCAAATGTATTGATTGAGGG

SNP site analysis and typing

Sequences were analyzed using Chromas 2.3 to contrast the peaks, and Excel software to organize the SNP typing results in an A, T, C, and G format. Insertion/deletion mutations were removed from the combined gene information file, and the results were imported into DnaSP 4.0 software, which was used to calculate basic SNP information such as number of inversions and conversions, frequency, nucleotide polymorphism (π、θw), synonymous mutation diversity, non-synonymous mutation diversity, silencing site diversity, and linkage disequilibrium. SHEsis was used for haplotype analysis. ANOVA and χ2 were performed to evaluate if the results conformed to the Hardy-Weinberg equilibrium using SPSS software.

Results

PeTPS-(-)Apin gene sequence

After cloning, sequencing, and assembly, the full length sequence of the PeTPS-(-)Apin gene was obtained. The genome was of 4638 bp and included 10 exons and 9 introns, and encoded a 629 amino acid protein (Fig 3). Its homology with Pt1 (gb|AF543527.1|), PcTPS-(-)apin1 (gb|JQ240303.1|), PmTPS-(-)apin (gb|KF547035.1|), and bankerson PbTPS-(-)apin1 (gb|JQ240304.1|) was 91–99%, with three long conserved regions (> 50 a.a.). Homology of PeTPS-(-)Apin was 81–87% to north American spruce PsTPS-Pin (gb|AY237645.1|) and European spruce PaTPS-Pin (gb|AY473622.1|), with five short conserved regions (> 15 a.a.). It had a homology of 73–79% with fir Ag3.18 (gb| U87909.1|), PgQ028 (gb| BT105745.1|), and PgWS00725 (gb| HQ426153.1|), with two shor,t conserved regions (> 15 a.a.).

Fig 3

Schematic representation of the PeTPS-(-)Apin gene structure.

Diversity analysis of SNPs

After removing a 46 bp insertion/deletion mutation, the 4592 bp sequence was used for further analysis. A total of 72 SNP loci were observed, with 37 transitions and 35 transversions, and 59 SNP loci were of high information content. The average and high information content SNP frequencies were 1/64.42 and 1/78.61, respectively, with 47 silent mutation sites and 12 non-identical mutation sites. The nucleotide polymorphism of π 0.00276 and θw 0.00259, were at a low level, probably because more polymorphisms were not detected form the small sample size in this study. The diversity of silencing loci of 0.00316, diversity of synonymous mutations of 0.0009, and diversity of non-synonymous mutations of 0.00202 were all at a low level. These results indicated that the nucleotide sequence of this gene is highly conserved. Its haplotype diversity was 0.897, its non-synonymous mutation frequency in the coding region (Ka) was 0.00202, its synonymous mutation frequency in the coding region (Ks) was 0.00317, its minimum number of historical recombination events (Rm) was 4, and its Rm/SNPs was 0.068. In addition, Ka/Ks was 0.6382, which, being less than 1, suggested that the gene was undergoing balanced selection. Furthermore, three methods (Tajiama D, Fu-Li, Fay, and Wu’s H test) were used to detect neutral selection, and the results were 0.23743, 0.20077, and 0.1318, respectively. All three values were greater than 0 (positive), but the test values seldom reached a sufficiently significant level to indicate that this gene followed a neutral model in evolution and is undergoing balanced selection.

Linkage disequilibrium

The level of linkage disequilibrium varied greatly in different species and different gene sequences. A correlation analysis was established based on linkage disequilibrium (LD), and different LD levels determined different strategies for correlation analysis. An LD attenuation diagram of 59 highly informative SNP loci of the PeTPS-(-)Apin gene is shown in Fig 4. As a result, the r2 value decreased to 0.2 at approximately 1000 bp and below 0.1 at approximately 2000 bp, indicating a high level of LD and a close linkage between these markers. To better understand the linkage relationship among SNPs, an LD matrix diagram of the gene was constructed, with darker color representing greater connection (Fig 5).

Fig 4

LD attenuation diagram of PeTPS-(-)Apin.

Fig 5

LD matrix diagram of the PeTPS-(-)Apin gene.

Haplotype block

Owing to the high LD level of the PeTPS-(-)Apin gene, and the close linkage between SNP sites, we firstly separated the 59 SNP sites after removing 12 rare SNPS (MAF < 0.05) into six haplotype blocks (named (-)Apin-1, (-)Apin-2, (-)Apin-3, (-)Apin-4, (-)Apin-5 and (-)Apin-6). Haplotype analysis was performed based on r2 value. All the 110 samples were used for haplotyping, and the length of the haplotype blocks was 150–1400 bp. Theoretically, the number of haplotypes should be twice that of the number of SNPs contained in the block, but the actual number of observed haplotypes scarcely approached the theoretical value. This may result from the close linkage between SNP loci. Additionally, the frequency distribution of genotypes of different haplotype blocks was varied, and there were 1–3 dominant genotypes in each haplotype (frequencies greater than 0.2). An overview of the haplotype blocks is shown in Table 3.

Table 3

PeTPS-(-)Apin gene haplotype blocks of the 110 samples.

Haplotype	Location	Length (≈bp)	Number of SNPs	Number of haplotypes	Dominant haplotype block	Frequency
(-)Apin-1	5’-UTR, 1ex	600	11	11	AACCAGGTCGA	0.636
(-)Apin-2	1in	150	9	16	AAGGTCAAA	0.554
(-)Apin-3	2-3ex	500	10	12	CAACGCGAGA	0.346
					TAATTCGAGA	0.218
					TAGTTCGAGG	0.255
(-)Apin-4	4-5ex	1000	10	15	CTGCCAAGGA	0.300
					TATTGGAGTT	0.291
(-)Apin-5	6-10ex	1400	12	11	TAGTGTTCGCAT	0.364
					ATAGTGTTCTAT	0.291
					CGCCGTCCAGAT	0.200
(-)Apin-6	3’-UTR	300	7	12	ACTCCC	0.355
					TACCCC	0.236

Haplotypes with frequencies greater than 0.2 were considered dominant.

Genotyping of SNPs association with resin traits

A total of 29 resin traits, including two related to resin-producing capacity and 27 resin components, were examined. The traits related to resin-producing capacity included basic resin-producing capacity (W), and potential resin-producing capacity (W). The resin components included turpentine, resin, 7 kinds of turpentine, and 18 kinds of resin. The seven types of turpentine components were α-pinene, camphene, β-pinene, dipentene, cymene, myrcene, and cycloisilongifolene. The 18 types of resin components were pimanthrene, pimarinal, pimaric acid, elliotinoic acid, sandaracopimaric acid, dehydroabietic aldehyde, isopimaric acid, levopimaric acid, palustric acid, 6,8,11,13-abietatetraenoic acid, dehydroabietic acid, abietic acid, neoabietic acid, mercusic acid, 7,13,15-abietatrienoic acid, 8,14-dihydro pimaric acid, 15-hydroxyl hydrogen abietic acid, and 7-hydroxyl hydrogen abietic acid. The determination methods of these resin traits were shown in S1 Text and S1 Table. The variation statistics of the 29 resin characters is shown in S1 Schedule. The correlation between 59 SNP loci of the PeTPS-(-)Apin gene and 29 types of resin traits was analyzed. Three SNPs (CG615, AT641 and AG3859) were associated with the phenotypic trait of α-pinene content, and with a higher contribution rate (R2 ≥ 10%) (Table 4). Genotyping and polymorphism analysis were performed on 110 samples of Pinus elliottii. The expected heterozygosity, had an average of 0.5365, and the observed heterozygosity, had an average of 0.5030 (Table 5). Therefore, PeTPS-(-)Apin is a candidate gene for positive tree screening with high α -pinene content.

Table 4

Overview of SNPs association with α-pinene content.

SNPs	Haplotype blocks	Effect R2 (%)
CG615	(-)Apin-1	15.548
AT641	(-)Apin-1	10.271
AG3859	(-)Apin-5	11.445

Table 5

Genotypes frequency and polymorphisms of 110 Pinus elliottii samples based on 3 SNPs.

SNP	Genotype frequency			Allele frequency		H e	H o	χ 2	HWE
	G	N	F	A	F
CG615	CC	15	0.1364	C	0.5909	0.5489	0.5091	0.0351	0.8514
	CG	50	0.4545
				G	0.8636
	GG	45	0.4091
AT641	AA	15	0.1364	A	0.6000	0.5118	0.4636	0.0013	0.9710
	AT	51	0.4636
				T	0.8636
	TT	44	0.4000
AG3859	AA	23	0.2091	A	0.7455	0.5489	0.5364	0.6179	0.4318
	AG	59	0.5364
				G	0.7909
	GG	28	0.2545

G, genotype; A, allele; N, number; F, frequency; H, expected heterozygosity; H, observed heterozygosity; χ, chi-square test value; HWE, Hardy-Weinberg equilibrium (when the value > 0.05, it indicated a Hardy-Weinberg equilibrium; the data came from the same Mundell population).

Discussion

Three SNPs (CG615, AT641 and AG3859) were selected as TagSNPs related to α-pinene content. Among them, mutations in AG3859 may lead to increased activity of some enzymes regulating the synthesis of α-pinene. In this study, 12 plus trees were selected, and the actual gain of α-pinene content was increased by 44.39% without decreasing the contents of W, W, turpentine or β-pinene content.

Analysis of the TagSNPs

As the HapMap project progressed, a large amount of SNP site information accumulated in the human genome database, and tagging SNPs (i.e., TagSNPs) need to be screened from these data to reduce interference from redundant data for more precise location of disease-associated SNP sites [23]. The subject of this work was slash pine (P. elliottii), a less studied biological species, for which there is still very little SNP data [24]. Loblolly pine (P. taeda) is the most thoroughly studied pine species and its complete genome sequence is available, but repeat sequences hamper the expansion of the SNP database. There is no GWAS report of related species in the short term [8]. Moreover, as a complex quantitative trait, pine resin trait needs a large number of samples for its gene association studies. Most literature reports are of 200–400 individuals, and these individuals are naturally pollinated populations with distant genetic relationships [25].

In this study, however, we only analyzed 110 families introduced from the United States, because slash pine is not a native species. To ensure a distant genetic relationship between individuals, it is difficult to collect more than 200 individuals as association groups. Based on a small data volume of nucleotides database (less than 300), our existing SNP data cannot cover the genome-wide. Moreover, it is difficult to obtain more SNP data in the short term due to the enormous genome (>20,000 Mbp). Therefore, simple associations (ANOVA) were used for association analysis, which may be controversial. Nevertheless, PeTPS-(-)Apin gene was considered as an important candidate gene for α -pinene content, and three TagSNPs (CG615, AT641 and AG3859) were associated with α -pinene content.

Molecular mechanism of mutations

Using candidate gene association analysis, we found three TagSNPs (CG615, AT641, and AG3859) that may be related to α-pinene content, and analyzed the molecular mechanisms of these three mutations (Fig 6). These three mutations were all non-synonymous mutations in exon 1 (haplotype block (-) APin-1) and exon 10 (haplotype block (-) APin-5): G at CG615 was mutated to C, resulting in a change from arginine, to proline; T at AT641 was mutated to A, changing phenylalanine, to tyrosine; and G at AG3859 was mutated to A, changing arginine to lysine. We used the tools ElM and CDD to predict the possible functional sites of PeTPS-(-)Apin gene: AG3859 is the first amino acid of the LIG_FHA ligand functional domain. This domain binds forkhead-associated (FHA) phosphopeptide ligands that consist of seven amino acids, the phosphopeptide identification domain of many regulatory proteins [26]. The mutation at AG3859 may lead to increased activity of some enzymes that regulate the synthesis of α-pinene. The functions of CG615 and AT641 have not yet been predicted, but we do know that the mutations are at the N-terminus of the protein, near the conserved domain of the TPS gene families, and are closely linked (amino acids are at positions 10 and 19, respectively). Whether the linkage of mutations and α-pinene content is an artifactual event caused by sample size and population structure, or a real event caused by natural selection, is unclear, and its molecular mechanism remains to be studied.

Fig 6

Molecular mechanism underlying the effects of the three TagSNPs on α-pinene content.

A large number of studies have shown that some traits can be controlled by a single gene (or even a single site mutation), such as that related to resistance. Although most complex traits are controlled by multiple genes, there may be dominant, additive, epistatic, and interaction effects among these genes, such as those that occur in tree height, weight, and yield. Studies have shown that the synthesis of α-pinene is controlled by a specific synthetase, that is, the internal mutation of PeTPS-(-)Apin gene may lead to more active functional sites, thus increasing the content of α-pinene. However, in actual production, we found that the content of α-pinene was affected by time and space, and therefore is a more complex quantitative trait. More candidate genes related to it need to be mined.

Selection of plus trees

As the demand for processed resin products has exceeded supply, the prices of certain chemical components have rapidly increased each year. Therefore, the supply of industrial raw materials can only be guaranteed by increasing the content of specific components of the resin itself. There are significant differences between species, even of the same species, although the chemical composition of resin is similar. For example, in turpentine of P. kesiya, α-pinene accounts for over 90% of monoterpene content, β-pinene content is as high as 25.9%, and there is even a high content of Δ3-carene in rare breeds [27]. In the resin of P. elliottii, pimaric type acid content is 9.93% and that of isopimaric acid up to 7.6%, whereas isopimaric acid content in P. massoniana is less than 1% [28]. We suggest that the chemical composition and content should be considered important criteria of resin quality. Prior to evaluating the quality of resin, one should consider the content of the expensive ingredients that are widely used in industry [29]. Studies have shown that single components in resin are synthesized under the control of single genes, and its content is controlled by a gene that has a dominant effect [30]. These gene variants can be targeted for improvement through artificial selection. The heritability of main components of turpentine is from 0.2 to 0.6, and the α-pinene is 0.3–0.5 [2]. In recent years, there has been an increasing number of directional selection and breeding programs of resin components in resin-producing-pines in China. The breeding targets involve α-pinene, β-pinene, Δ3-carene, dipentene, abietic acid, isopimaric acid, pimanthrene, and pimaric acid) [2, 5]. The application of molecular markers in the directional selection of specific components has not yet been reported.

In this study, three TagSNPs (CG615, AT641 and AG3859) were used for genotyping (Fig 7) and were used to select P. elliottii with high α-pinene content. There were only 10 genotypes were observed (27 are possible in Fig 7). Six genotypes with high α-pinene content (over 20%) were observed: AaBbCC, AABBCC, AABBCc, AABBcc, aaBbCc, and aabbCC. Among them, the α-pinene content of AABBCC was over 40%. Based on only AABBCC selection, two trees were selected (S2 Schedule, Fig 8). With a selection ratio of 1.82% and a selection differential of 24.32, we achieved a real gain of 118.0% in α-pinene content. In this way, W, W, and turpentine were not reduced, but there an 8.97% reduction in β-pinene content. Multiple studies have shown a significantly negative correlation between α-pinene and β-pinene contents, which may be related to these two synthase genes and their regulatory genes. The genetic correlation coefficients ranged from 0.36 to 0.46 [1, 2, 5]. We also tried another selection method. The α-pinene content of AABBCc reached 26%, and it was also considered an excellent genotype. Based on the selection of these two genotypes (AABBCC and AABBCc), 12 trees were selected (Fig 9, S2 Schedule), the selection ratio was 10.91%, and the selection difference was 9.15. This can increase the real gain of α-pinene content by 44.39% without reducing W, W, turpentine, or β-pinene content. In actual industrial production, β-pinene is also an important material, and we can choose the scheme according to different breeding objectives.

Fig 7

Schematic diagram of genotypes.

Dotted lines indicate the possible genotypes that were not observed.

Fig 8

Box map of α-pinene content for 9 genotypes.

Among them, the genotype AABBCC was only 1, and the box map was not drawn.

Fig 9

Box map of α-pinene and β-pinene content in two different selection methods.

Conclusions

Above all, the yield and quality of resin are complex quantitative traits. PeTPS-(-)Apin gene variants can be used to select P. elliottii trees with high α-pinene content. Although selection of plus P. elliottii for stable production, high yield, and quality resin with high α-pinene content is not only contingent on the PeTPS-(-)Apin gene, this gene can certainly be used as a reference for selection of high yield pines and other components. However, further studies are needed.

High definition view of Fig 1.

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Determination method for resin traits.

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Group structure analysis method and results.

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Full length sequence of PeTPS-(-)Apin gene.

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Original data of Figs 4 and 5.

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Original data of resin traits.

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Original data of Tables 4 and 5.

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Original data of Figs 7–9.

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Variation in 29 resin traits of 110 slash pines.

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Overview of 12 plus trees with high α-pinene content.

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5 Jun 2021

PONE-D-21-06793

Association of single nucleotide polymorphisms in the PeTPS-(-)Apin gene with resin traits in Pinus elliottii

PLOS ONE

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The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: In this study the authors aimed to identify molecular markers associated with 29 resin traits in Pinus elliotii, for their possible later use in marker-assisted selection. They use 110 trees and 120 SSRs to assess population structure, and then identify 72 SNPs in gene PeTPS-(-)Apin, related to rosin quality. They find evidence of 10 SNPs in this gene significantly associated with 7 resin traits, and suggest using the target gene for plus tree selection within a species’ breeding program.

Overall, this manuscript tackles an interesting topic by bringing together genetic and phenotypic data, for further tree breeding purposes. However, the manuscript is not properly structured and I think that several limitations of the analysis may compromise the findings. In its current state and in light of my major comments below, I do not think this manuscript is suitable for publication in PLOS ONE. However, if these issues below were to be comprehensively addressed, I would be happy to review a new version of the document.

Major comments:

1. The papers needs to be streamlined, and will benefit from rigorous scientific editing. While the english language is largely correct, the poor structure of the manuscript (intro, m&m, results, discussion, conclusions) makes it difficult to read and understand. Many unimportant details are provided along the text, while the most important ideas and hypothesis to be tested are not so much highlighted.

2. Regarding the methods, considering that this is a paper focused on breeding, I have missed important basic data, like for example heritability. Also genetic correlations among resin components. Are there correlations or trade-offs between the studied resin traits? I think it could be helpful to look for pairwise correlations between these traits. A classic breeding approach, including quantitative genetic data, would complement the understanding of the document, provided that the data are already available.

3. From the described methods, I have not found a justification for all the steps. Starting from the genetic structure analysis. A great number of SSRs (120) is used to assess population structure. But, how are the results taken into account in the discussion? For example: from the final 12 selected trees, do they come from different genetic pools? What can be done to widen the genetic basis of the breeding population? These are important questions regarding the sustainability of a breeding program.

4. However, my major concern is about the statistical methods used for association analysis. A said by authors, they cannot discard false positives because of the small population size, population structure and a reliable genetic distance matrix (L328-330). LD between markers and false positives due to kinship relations and population structure are indeed key issues to be solved in association analysis. First of all, I am concerned that the number (59) and distribution of SNPs used in this study may bias the results. The authors recognize that there is actually a high level of LD and close linkage between markers (L262-263, L278). This could certainly affect the results of the association test, increasing the number of associated markers. The number of trees (110) is also quite small for association testing. Regarding kinship, how where the genotyped trees selected within families? The K matrix was calculated using SSRs or SNPs? If that is the case, I would not rely too much on a K matrix calculated with only 59 SNPs. Regarding population structure, admixture coefficients would improve if averaged across replicated runs (using for example software CLUMPP). Moreover, after association analysis, multiple testing correction is also needed to control for false positives when a large number of traits are tested. One option could be using the false discovery rate (FDR) method (Storey and Tibshirani 2003). Overall, I have reasonable doubts that the associations described as significant are really significant, or could rather be false positives.

Minor comments:

- Introduction: I found excess literature about non-relevant information for the scope of the paper, such as information about resin production (L38-43, L50-52), while lacking key information about the genetic control of resin traits.

-Overall, the manuscript lacks bibliographic references. Examples: L58, 70, 83, 90, 258. I would encourage authors to upgrade their references with publications of high impact international journals.

-Materials and methods: regarding plant materials, it is not clear how the 110 trees genotyped and phenotyped for resin traits where selected from the 110 families of the progeny trials. In population structure analysis, I would clarify how the 0,1 format data was transformed to round numbers, corresponding to a bp position.

-L336-338: Why are SNPs in HWE discarded for further analysis and breeding pourposes?

-Discussion: a first short paragraph with main findings would be appreciated.

- Figure 1 should preferably belong to supplementary material.

- Figures 2 an 3 are redundant. They show the same information, in different scale. It would be useful to see how are progeny trial populations or families distributed in the x-axis.

- Suggestion for associated SNP data figure: Instead of table, a boxplot for each SNP marker, showing median and interquantile range of phenotype variation would be more visual and informative for the reader.

Reviewer #2: Manuscript may be considered after addressing the following comments, importantly point 2.

1. Provide details and references fr the methods used such as GC and MS procedures.

2. Attach a picture of cultivated plants (field trial) and plots made along with distances between each plants on which genetic analysis was performed. This is the core of the study.

3. Verify the data in Table 3. example red group totals 16.

4. Provide a heading Figure legends.

5. Some figures lacks legends.

6. Figure 5 needs more details about intron and exons or put it in the legend.

7. Mention the details of structure parameters used. Ex. Burn-in period, MCMC etc.

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

12 Jul 2021

I have received your email, and have modified it one by one according to reviewer and editor comments , and uploaded it to the submission system.Thanks a lot.

Submitted filename: Response to Reviewers .docx

Click here for additional data file.

12 Aug 2021

PONE-D-21-06793R1

Association of single nucleotide polymorphisms in the PeTPS-(-)Apin gene with resin traits in Pinus elliottii

PLOS ONE

Dear Dr. Zhang,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Sep 26 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

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If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see:  http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols . Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at  https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols .

We look forward to receiving your revised manuscript.

Kind regards,

Himanshu Sharma

Academic Editor

PLOS ONE

Journal Requirements:

Additional Editor Comments (if provided):

Dear Authors I have received the reports from experts in the field on your manuscript one reviewer is still not agree for possible publication of the manuscript in the Plosone. So based on the decision I have to go with reviewer. and again manuscript has to be revised thoroughly. I am attaching comments which have to be revised.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: (No Response)

Reviewer #2: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Partly

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: No

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Overall the authors tried to address most comments, improving the manuscript. However, I still think that statistical analysis may compromise their findings, and thus their results and conclusions. I’m especially concerned about association testing results, as highlighted in major comment 4. Thus, I do not think this manuscript is suitable for publication in PLOS ONE in its present form.

Response to authors for major comments review:

2. Authors now provide a citation about heritability for turpentine and alfa-pinene in the species. My sense was that there is a need for trustable genetic control if then you are going to perform an association test, which consists in stablishing an statistic relationship between fenotypes (SNPs) and genotypes.

My interest in testing for genetic correlations between traits is to avoid false positives. If the studied traits are strongly correlated, we cannot say that the associated SNPs are responsible for variation in all those traits, indepently. We cannot ignore that they could rather be just associated with one of these traits, or them in all.

3. Despite the huge genome of pine tree species, I cannot agree that population structure can only be assessed through EST-SSR data. The genome is huge but highly repetitive. Population structure can be assessed using SNP data in selected genes or a higher number of SNPs distributed along the genome. However, population structure assessed with SSRs could be ok. But, if the computed population structure does not represent the structure of the studied population, as said by authors… How could it be used to correct for population structure in the mixed linear model implemented in the association analysis?

4. The statistical methods used for association analysis are still my major concern about the manuscript. I think the authors have not addressed what was highlighted about basic statistical problems which I think are at the base of their results and main findings. If you do not apply a false discovery rate correction method, neither know about genetic correlations between phenotypes in the studied traits, in my opinion, association analysis results are not reliable.

Reviewer #2: All the comments have been address appropriately and manuscript may be accepted for publication. For future publications remember to provide comment by comment response in separate sheet (response sheet) not in the revised manuscript.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

12 Sep 2021

Response Letter

I have received the modification suggestions of two experts, and the modification has been completed according to the expert suggestions. The reply to the expert suggestions is as follows:

Reviewer #1:

1. Overall the authors tried to address most comments, improving the manuscript. However, I still think that statistical analysis may compromise their findings, and thus their results and conclusions. I’m especially concerned about association testing results, as highlighted in major comment 4. Thus, I do not think this manuscript is suitable for publication in PLOS ONE in its present form. Response to authors for major comments review:

Response: We really appreciate your suggestions that would improve the manuscript. Thus, we have carefully revised the manuscript according to your comments.

2. Authors now provide a citation about heritability for turpentine and alfa-pinene in the species. My sense was that there is a need for trustable genetic control if then you are going to perform an association test, which consists in stablishing an statistic relationship between fenotypes (SNPs) and genotypes.

My interest in testing for genetic correlations between traits is to avoid false positives. If the studied traits are strongly correlated, we cannot say that the associated SNPs are responsible for variation in all those traits, indepently. We cannot ignore that they could rather be just associated with one of these traits, or them in all.

Response: Thank you again for your comments. As you said, if the traits are correlated, it is hard to say that the SNPs are responsible for variation in it. In fact, many studies have shown that there was a significant negative correlation between α-pinene and β-pinene content. That is why I use to different methods when we are choosing plus trees. Before I start this article, we used four genes, including PeTPS-Bpin (β-pinene synthetase gene), not just PeTPS-(-)Apin gene, but no SNPs associated with any of the other traits. Addtionally, candidate gene association analysis is not as accurate as the GWAS method, but the only advantage is to save the cost of the test. We believe that our research has some reference value even though there are shortcomings in technology. I added some correlation data and references in L441-442.

3. Despite the huge genome of pine tree species, I cannot agree that population structure can only be assessed through EST-SSR data. The genome is huge but highly repetitive. Population structure can be assessed using SNP data in selected genes or a higher number of SNPs distributed along the genome. However, population structure assessed with SSRs could be ok. But, if the computed population structure does not represent the structure of the studied population, as said by authors… How could it be used to correct for population structure in the mixed linear model implemented in the association analysis?

Response: Thank you again for your comments. As you said, SNP in selected genes or distributed along the genome can be used to evaluate population structure. However, only a limited number of specific genes have been published in Pinus elliottii, and there were few SNPs in the database. Conversely, there were a large number of SSR markers for P. elliottii itself, as well as general markers for other species of Pinus. The use of SSR markers is also aimed at greatly reducing our research costs. So we selected SSR markers after referring to studies on other Pinus such as Loblolly pine (P. taeda) (Eckert, 2010). Although this method would not perfectly perform an accurate result, it is a reasonable method and has certain reference value. I have made supplementary explanations in the text according to your suggestions (L136-137).

4. The statistical methods used for association analysis are still my major concern about the manuscript. I think the authors have not addressed what was highlighted about basic statistical problems which I think are at the base of their results and main findings. If you do not apply a false discovery rate correction method, neither know about genetic correlations between phenotypes in the studied traits, in my opinion, association analysis results are not reliable.

Response: Thank you very much for your advice. As you said, the results of our previous association analysis are not reliable. I have tested the results of my association analysis with The FDR method as suggested by you, and finally eliminated seven false positives, so that the phenomena I failed to explain before can be scientifically explained. The article has made a large number of modifications (L21-26, 193-195, 312-317, 327, 354-357, 431 ).

Reviewer #2:

All the comments have been address appropriately and manuscript may be accepted for publication. For future publications remember to provide comment by comment response in separate sheet (response sheet) not in the revised manuscript.

Response: Thank you again for your approval of this article.

Submitted filename: Response to Reviewers .docx

Click here for additional data file.

11 Nov 2021

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Himanshu Sharma

Academic Editor

PLOS ONE

Journal Requirements:

Additional Editor Comments (if provided):

Based on reviewers recommendation the manuscript needs revision So authors are required to revise the manuscript thoroughly.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #3: (No Response)

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #3: No

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #3: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #3: No

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #3: No

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #3: The work's goal is good, and the authors put forth a lot of effort to convey the findings.

The customized association analysis methodologies, on the other hand, are unreliable.

I don't believe this manuscript is ready for publishing.

There are numerous errors, some of which are as follows:

Correct the spelling ‘TASSLE’ to TASSEL at line 21, 22. Similarly on line 186. Go through the manuscript.

Change ‘rosin’ to resin line 17, 172

Spell out ‘RY’ when you use it first time in the manuscript it is better.

Statements don’t match about the population structure: You write sub-population (K) K1 to K9 in Method section while in K = 2 to 7 is mention in result part.

The method of ∆K was not mention in method section

The value of MCMC reps is also missing

Method is not clear at line 183 – 187 (GC procedure and GC-MS procedure)

Line 188-189: It is structure based association analysis. My main concern is that how could SSR based Q value be used in the MLM model of association mapping which is based on SNPs data. It is difficult to compare population structure data of different molecular marker. You should do structure analysis and generate Q value for SNPs data also. The association analysis data is not reliable.

The used K matrix is based on SSRs data or SNPs data? If this is based on SSRs data again I shocked how you could use this in SNPs based association mapping. You should use SNPs based K matrix as well.

The total no. of sample used in this study is 110 but the sum of all samples from four groups comes 109 in Table 3 line 221

236-237: Nucleotide diversity (0.00276) and watterson’s theta value (0.00259) is low might be due to the less sample size not moderate.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #3: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

9 Dec 2021

Response to comments and suggestions of reviewers:

________________________________________

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #3: (No Response)

________________________________________

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #3: No

Response: In this manuscript, 29 resin traits were determined by methods of bark stress wounding and GC-MS, and the sampling and experiment were repeated to ensure accurate and authentic data. Structure V2.3.3 software was used to analyze population structure and genetic relationship, MLM program of TASSEL software was used for SNP association analysis, and FDR program was used to adjust P values. Finally, three SNPs of PeTPS-(-)Apin gene were found to be significantly correlated with α-pinene content, and realistic gain of 118.0 % of α-pinene content was obtained. The research of this manuscript has a certain reference value.

________________________________________

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #3: Yes

Response: Thank you very much for your recognition of the statistical analysis method in this manuscript.

________________________________________

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #3: No

Response: We have provided woodland photos at 3072×1728 and 3456×4608 resolutions in the support information, along with all raw data summaries and software analysis results. After your reminder, we have checked the uploaded support information. We uploaded the support information S5 as a supplement, and modified the incorrect format of S9, to ensure compliance with the PLOS data policy.

________________________________________

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #3: No

Response: The manuscript was edited by Editage. Under your reminding, we checked the manuscript and corrected some mistakes. We returned the manuscript to the Editage's office, re-edited it in English, and uploaded the English editor certificate (filename: Certificate_of_editing.docx) through the submission channel.

________________________________________

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #3: The work's goal is good, and the authors put forth a lot of effort to convey the findings.

The customized association analysis methodologies, on the other hand, are unreliable.

I don't believe this manuscript is ready for publishing.

There are numerous errors, some of which are as follows:

(1) Correct the spelling ‘TASSLE’ to TASSEL at line 21, 22. Similarly on line 186. Go through the manuscript.

Change ‘rosin’ to resin line 17, 172

Response: Thanks for your reminding, and I'm sorry to let you see these careless error. I have checked carefully the whole manuscripts, and corrected these mistakes. In addition, I also corrected other language and grammatical errors through the Editage company.

(1) Lines 21, 198.—“TASSLE” corrected to “TASSEL”.

(2) Lines 16, 17, 35, 37, 94, 173, 306, 306(2), 308, 312, 407, 452 and Table 5 (13 errors in total).—“rosin” corrected to “resin”.

(2) Spell out ‘RY’ when you use it first time in the manuscript it is better.

Response: Thanks for your reminding, and I'm sorry to let you see this careless error. I checked the whole manuscript carefully and corrected all of similar errors.

(1) Lines 157, 168.—“RY”, is not a professional noun abbreviation, and it only appears twice in the manuscript, both corrected to “resin yield”.

(2) Lines 75.— “TPS”, is used for the first time in the manuscript, and corrected to “Terpene synthase (TPS)”.

(3) Lines 97.—“MAS”, is used for the first time in the manuscript, and corrected to “marker-assisted selection (MAS)”.

(4) Lines 382.—“FHA”, is used for the first time in the manuscript, and corrected to “forkhead-associated (FHA)”.

(3) Statements don’t match about the population structure: You write sub-population (K) K1 to K9 in Method section while in K = 2 to 7 is mention in result part.

Response: Thanks for your reminding, and it's my carelessness. I checked the whole manuscript carefully and corrected all of similar errors.

(1) Lines 134.—The K value in the result section is correct, “set K to 1~9” in the material method part is corrected to “K set to 2~7”.

(2) Lines 133.—There is a parameter value error, and modified “100,000” to correct value “10,000”.

(3) Lines 223.—There is a numerical value error, and modified “37” to the correct value “35”.

(4) The method of ∆K was not mention in method section

The value of MCMC reps is also missing

Method is not clear at line 183 – 187 (GC procedure and GC-MS procedure)

Response: Thanks for your comments. I have added the following contents:

(1) Lines 134-137.—added the method of optimal K and ΔK value.

“The optimal value of K was determined using the ΔK method with the online program (Structure Harvester: http://taylor0.biology.ucla.edu/struct_harvest/).”

(2) Lines 133.—added the parameter of "Number of MCMC Reps after Burnin".

“"Number of MCMC Reps after Burnin" set to 10,000”.

(3) Lines 183-186.—supplemented the programs of GC and GCMS.

“GC was carried out using the following parameters: 60 ℃ for 2 min, 5 ℃·min-1 to 80 ℃, 30 ℃·min-1 to 230 ℃, finally 5℃·min-1 to 260 ℃, for 10 min. Injection volume: 0.4 μL. GC-MS was carried out using the following parameters: 60 ℃ for 2 min, 5 ℃·min-1 to 80 ℃, 30 ℃·min-1 to 230 ℃, finally 5℃·min-1 to 260 ℃, for 10 min. Injection volume: 0.1 μL.”.

(5) Line 188-189: It is structure based association analysis. My main concern is that how could SSR based Q value be used in the MLM model of association mapping which is based on SNPs data. It is difficult to compare population structure data of different molecular marker. You should do structure analysis and generate Q value for SNPs data also. The association analysis data is not reliable.

The used K matrix is based on SSRs data or SNPs data? If this is based on SSRs data again I shocked how you could use this in SNPs based association mapping. You should use SNPs based K matrix as well.

Response: Thanks very much for your comments. As you said, it is difficult to compare data of different molecular markers. And we also would like to be able to use more SNP markers distributed along the genome to obtain population structure data. However, it is a pity that this manuscript did not get more SNP markers.

TPS genes were cloned, sequenced, and found SNP loci, and performed a simple correlation analysis (ANOVA) between these SNPs and phenotypic traits. There was a significant association between PeTPS-(-)Apin gene and resin traits. In order to find the association loci suitable for MAS, we tried to add two fixed effects, K-matrix and Q-matrix, into the independent variables of association analysis. However, we obtained only 59 SNPs with an average distance of 78.61 bp, which is difficult to be used for population structure analysis. What is more, it is difficult to obtain more SNPs from the genome in the short term in the case of the P. elliottii genome-wide unknown.

SSR is a broad-spectrum marker distributed throughout the genome and widely used in population structure research. Based on the related research of P. taeda. (Eckert, 2010: https://doi.org/10.1534/genetics.114.164087), we tried to use SSR markers to obtain K matrix and Q matrix. I think the manuscript still has some reference value, even though this method may be not the best.

The discussion section of the manuscript talked about the issues, but it wasn't comprehensive enough. I made some improvements.

Line 347-353.— The original: “We still cannot rule out the possibility of false positives in the association analysis because of the K matrix and Q matrix were calculated using SSR markers, since the available SNP markers in the association analysis of candidate genes could did not cover the whole genome. Nevertheless, some information can be obtained from the limited data. ”

The revised: “Based on a small data volume of nucleotides database (less than 300 ), our existing SNP data cannot cover the genome-wide. Moreover, it is difficult to obtain more SNP data in the short term due to the enormous genome (>20,000 Mbp). Therefore, the K-matrix and q-matrix in association analysis are calculated using SSR markers, which may be controversial. However, some information can be obtained from the limited data.”

(6) The total no. of sample used in this study is 110 but the sum of all samples from four groups comes 109 in Table 3 line 221

Response: Thanks very much for your reminding. There were 110 samples in the manuscript. But in subgroups grouping, we classified the sample with proportion of a single color exceeded 40 % (Q≥0.4) into the subpopulation of that color. However, the maximum Q value of sample No.59 was less than 0.4, which could not meet the grouping conditions. Therefore, there were only 109 samples in Table 3.

I supplemented the method of subgroups grouping and the description of related problems:

Line 220-222 : “When the proportion of a single color exceeded 40 % (Q≥0.4), we classified the individual into the subpopulation of that color, but the maximum Q value of sample No. 59 was less than 0.4, so no statistics were collected. ”

(7) 236-237: Nucleotide diversity (0.00276) and watterson’s theta value (0.00259) is low might be due to the less sample size not moderate.

Response: I agree with you and revise the manuscript accordingly.

Line 253-255: “The nucleotide polymorphism of π 0.00276 and θw 0.00259, were at a low level, probably because more polymorphisms were not detected from the small sample size in this study.”.

________________________________________

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2 Feb 2022

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Journal Requirements:

Additional Editor Comments:

The manuscript entitled "Association of single nucleotide polymorphisms in the PeTPS-(-)Apin gene with resin traits in Pinus elliottii " by Lu Zhang, is not acceptable in the present form and one of the reviewer again has some queries So manuscript again needs to be revised.

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Reviewers' comments:

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Comments to the Author

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Reviewer #3: (No Response)

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #3: Partly

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #2: Yes

Reviewer #3: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

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Reviewer #3: Yes

**********

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Reviewer #3: Yes

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Reviewer #3: Dear Editor,

Most of the writing is now ok, and the authors’ provides substantial information. But again my main concern is about the association mapping approaches adapted by the authors in the manuscript. Authors used Q value of SSRs in SNP based association mapping. It is unacceptable as the population structure reduced the biasness of association by clustering of genotypes on the basis of polymorphic/unlinked marker irrespective of other variables. It is difficult to relate the location of SSRs and SNPs marker (linked or unlinked). In this paper there is a chance of highly wrong association. The genetic proportion value of admixture level will be totally different with different molecular marker if the nature of marker is different. If Q value of SSR is used in SNPs based association analysis it gives false association. The association analysis based on ANOVA is ok moreover the population structure /diversity analysis of P. elliotti based on SSR data is ok but Q matrix and K matrix generated through SSRs data cannot be used in SNPs based association analysis it can only be used when the physical location of the both markers is within the LD range. Have you compare the physical location of those SSRs to the SNPs? In my suggestion, population structure based association data should be remove from the manuscript and revised the manuscript accordingly.

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11 Mar 2022

Response to comments and suggestions of reviewers:

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Reviewer #3: (No Response)

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2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #3: Partly

Response: Thanks for your recognition. We deleted the association data based on population structure in accordance with your requirement, and focused on SNP analysis of PeTPS-(-)Apin gene. Genotyping of the population based on three SNPs, and the plus trees with high α-pinene content was selected. Finally, the actual α-pinene content was 118.0%. The research of this paper has certain reference value.

________________________________________

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #3: Yes

Response: Thank you very much for your recognition of the statistical analysis method in this manuscript.

________________________________________

4. Have the authors made all data underlying the findings in their manuscript fully available?

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Reviewer #3: Yes

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Reviewer #3: Dear Editor,

Most of the writing is now ok, and the authors’ provides substantial information. But again my main concern is about the association mapping approaches adapted by the authors in the manuscript. Authors used Q value of SSRs in SNP based association mapping. It is unacceptable as the population structure reduced the biasness of association by clustering of genotypes on the basis of polymorphic/unlinked marker irrespective of other variables. It is difficult to relate the location of SSRs and SNPs marker (linked or unlinked). In this paper there is a chance of highly wrong association. The genetic proportion value of admixture level will be totally different with different molecular marker if the nature of marker is different. If Q value of SSR is used in SNPs based association analysis it gives false association. The association analysis based on ANOVA is ok moreover the population structure /diversity analysis of P. elliotti based on SSR data is ok but Q matrix and K matrix generated through SSRs data cannot be used in SNPs based association analysis it can only be used when the physical location of the both markers is within the LD range. Have you compare the physical location of those SSRs to the SNPs? In my suggestion, population structure based association data should be remove from the manuscript and revised the manuscript accordingly.

Response: Thank you very much for your comments and suggestions, and I agree with you.

According to your suggestion, I deleted the section of association analysis based on population structure. I changed the title to "Analysis on single nucleotide polymorphisms of the PeTPS-(-)Apin gene in Pinus Elliottii". The focus of this manuscript was changed to SNPs analysis of PeTPS-(-)Apin gene, avoiding highly wrong association. However, due to the particularity of the samples, I still retained the contents of phenotypic determination and population structure analysis in the form of supporting information.

Changes to the framework of the article were as follows:

(1) Lines 126,178, “Materials and methods” section — “Population structure analysis”, “Determination of resin production capacity”, “Determination of turpentine composition”, and “Association analysis” section was completely deleted. At the same time, added support information files S3 (Determination method for resin traits) and S5 (Group structure analysis method and results).

(2) Lines 128,139. “Materials and methods” section — The section “PeTPS-(-)Apin gene cloning and SNP site typing” was divided into two parts “PeTPS-(-)Apin gene cloning” and “SNP site analysis and typing”.

(3) Line 179. “Results” section — “Group structure and kinship” section was completely deleted. And added it to the support information files S5 (Text. Group structure analysis method and results).

(4) Lines 182,376. “Results” section — The section “PeTPS-(-)Apin gene sequence and SNP sites” was divided into two parts “PeTPS-(-)Apin gene sequence” and “Diversity analysis of SNPs”.

(5) Lines 371,389. “Results” section — The section “Linkage disequilibrium and haplotype block” was divided into two parts “Linkage disequilibrium” and “Haplotype block”.

(6) Line 409. “Results” section — Change the section “Resin traits and SNP association analysis” to “Genotyping of SNPs association with resin traits”.

Other corresponding modifications are as follows:

(1) Lines 22-24. “Abstract - Methods” section — Change “Bark stress wounding and GC-MS were used to determine 29 resin traits. Structure v2.3.3 software was used to analyze population structure and genetic relationships, DnaSP v4.0 software was used to evaluate genetic diversity, the MLM program of TASSEL was used for SNP association analysis, and false discovery rate (FDR) was used for adjusting the p value.”

to “PeTPS-(-)Apin gene was cloned by double primers (external and internal). DnaSP V4.0 software was used to evaluate genetic diversity and linkage disequilibrium. SHEsis was used for haplotype analysis. SPSS was used for ANOVA and χ2 test.”.

(2) Lines 98-100. “Introduction” section — Change “the PeTPS-(-)Apin gene was cloned, 29 resin traits were determined, and functional single nucleotide polymorphisms (SNPs) were screened by association analysis. The optimal selection scheme of P. elliottii with high α-pinene content was also considered.”

to “the PeTPS-(-)Apin gene was cloned, and its single nucleotide polymorphisms (SNPs) and linkage disequilibrium were analyzed. Functional SNPs were screened by ANOVA, 110 samples were typed, and the optimal selection scheme of P. elliottii with high α-pinene content was also considered.”.

(3) Lines 178-179. “Materials and methods” section — Added the sentence “SHEsis was used for haplotype analysis. ANOVA and χ2 were performed to evaluate if the results conformed to the Hardy-Weinberg equilibrium using SPSS software.”.

(4) Line 423. “Results - Genotyping of SNPs association with resin traits” section — The original Table 5 was deleted, and added it to Schedule 1.

(5) Line 433. “Results - Genotyping of SNPs association with resin traits” section — A new table 5 was added “Genotypes frequency and polymorphisms of 110 Pinus elliottii samples based on 3 SNPs”.

(6) Line 422. “Results - Genotyping of SNPs association with resin traits” section — Added the sentence “The determination methods of these resin traits were shown in supporting information (S3, S4).”.

(7) Lines 426-428. “Results - Genotyping of SNPs association with resin traits” section — Added the sentence “Genotyping and polymorphism analysis were performed on 110 samples of Pinus elliottii. The expected heterozygosity, had an average of 0.5365, and the observed heterozygosity, had an average of 0.5030 (Table 5).”.

(8) Lines 474-477. “Discussion” section — Change “Therefore, the K-matrix and q-matrix in association analysis are calculated using SSR markers, which may be controversial. Nevertheless, some information can be obtained from the limited data. Using candidate gene association analysis, we divided the PeTPS-(-)Apin gene sequence into six haplotypes (Fig 7), screened out 3 loci associated with α-pinene content from 59 SNPs, and performed polymorphism analysis (Table 7). The expected heterozygosity, had an average of 0.5365, and the observed heterozygosity, had an average of 0.5030. The linkage disequilibrium r2 values of the TagSNPs are listed in Table 8. There was a strong linkage between CG615 and AT641 in haplotype block (-)Apin-1 (r2=1). We found that the contribution rate of the PeTPS-(-)Apin gene to α-pinene content was 37.264 %; thus it was considered an important candidate gene for this trait.”

to “Therefore, simple associations (ANOVA) were used for association analysis, which may be controversial. Nevertheless, PeTPS-(-)Apin gene was considered as an important candidate gene for α -pinene content, and three TagSNPs (CG615, AT641 and AG3859) were associated with α -pinene content.”.

(9) Line 567. “Discussion” section — “Among the 12 trees, 2 (16.67%) were from the Red group, 3 (25%) are from the Green group, and 7 (58.33%) are from the Blue group.” was deleted.

Submitted filename: Response to Reviewers.docx

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23 Mar 2022

Analysis on Single Nucleotide Polymorphisms of the PeTPS-(-)Apin Gene in Pinus elliottii

PONE-D-21-06793R4

Dear Dr. Zhang,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Additional Editor Comments (optional):

The manuscript entitled Analysis on Single Nucleotide Polymorphisms of the PeTPS-(-)Apin Gene in Pinus elliottii is extensively revised by the authors and answered all the queries by each reviewer.

There are always chances of improvement like correction in grammatical errorrs and many others, which can be corrected at the time of revision.

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #2: All comments have been addressed

Reviewer #3: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #2: Yes

Reviewer #3: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #2: Yes

Reviewer #3: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #2: Yes

Reviewer #3: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #2: Yes

Reviewer #3: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #2: The paper entitled "Analysis on Single Nucleotide Polymorphisms of the PeTPS-(-) Apin Gene in Pinus elliottii" may be accepted for publications as all the comments raised were addressed.

Reviewer #3: Dear Editor,

Authors provided substantial information and extensively revised the manuscript. Now it can be accepted for publication.

Minor correction

Sentence "MLM program of TASSEL was used for SNP association analysis

, and false discovery rate ( FDR) was used for adjusting the p value" should be removed/corrected from abstract. As the revised manuscript described the association analysis result based on ANOVA.

**********

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Reviewer #2: No

Reviewer #3: No

5 Apr 2022

PONE-D-21-06793R4

Analysis on Single Nucleotide Polymorphisms of the PeTPS-(-)Apin Gene in Pinus elliottii

Dear Dr. Zhang:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

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