Next Article in Journal
The Impact Mechanism of Urban Built Environment on Urban Greenways Based on Computer Vision
Previous Article in Journal
Mechanism of the Effects of Phyllostachys edulis Invasion on the Soil Microbial Community in Quercus acutissima Forests
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Forests
Volume 15
Issue 7
10.3390/f15071172
forests-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Identification of Suitable Reference Genes for RT-qPCR Normalization in Amylostereum areolatum Cultured on Pinus sylvestris var. mongholica Wood Powder

by
Chenglong Gao
1,
Ningning Fu
2,
Huayi Huang
1,
Lili Hu
1,
Yinghui Li
3,
Lili Ren
4,* and
Danyang Zhao
1,*
1
Guangdong Provincial Key Laboratory of Forest Culture, Protection and Utilization, Guangdong Academy of Forestry, Guangzhou 510520, China
2
Department of Forest Protection, College of Forestry, Hebei Agricultural University, Baoding 071033, China
3
Linhai Bureau of Natural Resources and Planning, Linhai 317000, China
4
Beijing Key Laboratory for Forest Pest Control, Beijing Forestry University, Beijing 100083, China
*
Authors to whom correspondence should be addressed.
Forests 2024, 15(7), 1172; https://doi.org/10.3390/f15071172
Submission received: 21 May 2024 / Revised: 26 June 2024 / Accepted: 3 July 2024 / Published: 5 July 2024
(This article belongs to the Section Forest Health)
Browse Figures
Review Reports Versions Notes

Abstract

:
Sirex noctilio and Amylostereum areolatum form a highly specific mutualistic symbiosis. The growth and host-degrading activities of the symbiotic fungus are critical to the woodwasps, which directly influence the larval survival rate and adult body size of the woodwasps. Gene expression analysis has been extensively employed to decrypt the intricate growth patterns of symbiotic fungi and identify the associated functional genes underpinning their degradation pathways. Appropriate reference genes are crucial for enhancing the accuracy of studies on gene expression. In an effort to refine gene expression analysis in A. areolatum, our study cultivated the symbiotic fungi on the wood powder medium of Pinus sylvestris var. mongolica, aligning closer to its natural growth conditions. Thirteen reference genes underwent meticulous evaluation via algorithms such as delta Ct, geNorm, BestKeeper, RefFinder, and NormFinder, depending on their stability amidst diverse growth and developmental epochs of A. areolatum. α-TUB, P450, and the combination (α-TUB + P450) were distinguished as the most stable candidates for RT-qPCR analysis, confirmed through AaLac1 expression validation. These findings contribute significantly to the investigation of gene expression in A. areolatum and facilitate a deeper understanding of its symbiotic relationship with S. noctilio.

1. Introduction

Sirex noctilio, a quarantine pest of international concern, has invaded and colonized the northeast region of China, severely damaging the plantations of Pinus sylvestris var. Mongolica [1,2,3,4,5]. Amylostereum areolatum, a fungus vectored by woodwasps, exhibits a strict mutualistic relationship with the S. noctilio [6,7,8,9]. A. areolatum exists as either a spore or mycelial fragment within the female woodwasps and relies on the woodwasps for its transmission [6]. The fungus is introduced into a suitable environment within the host tree along with the woodwasp’s eggs, where it undergoes nutrient growth [1,6,10]. The degradation of the host trees by this fungus is vital for the nutritional intake of the woodwasp’s larvae, significantly affecting their growth and development [11,12]. Studies indicated that the woodwasp larvae lived within the fungal mycelium coverage area until the 8th to 9th instar, at which point they separated from the symbiotic fungus [13]. During this time, the younger feed directly on the fungus for nutrients, while the older consume the host xylem affected by the fungus [14]. The growth of A. areolatum exerted a substantial impact on the larval nutrition and the size of the mature woodwasps [15]. A thriving fungus equates to well-nourished larvae and larger adult woodwasps, whereas fungal suppression can result in delayed egg hatching, larval malnutrition, or mortality [7,14,16]. This process highlighted the direct impact of the symbiotic fungal growth on the woodwasp’s survival rate and adult size.
Fu et al. [17] observed that the growth of A. areolatum was relatively slow at 0–4 days, reached its maximum growth rate at 6–12 days, and then declined. Transcriptome analysis suggested that genes associated with glycolysis/gluconeogenesis metabolism might play crucial roles in the growth and development of the symbiotic fungus [17]. However, these analyses on A. areolatum were all conducted on the PDA (Potato Dextrose Agar) medium. To further explore the symbiotic fungal growth within P. sylvestris var. mongolica environments, our team utilized Mongolian Scots pine wood powder as a cultivation substrate. This cultivation method more accurately reflects the growth status of the fungal symbionts inside Mongolian Scots pine trees. Investigating gene expression changes in the symbiotic fungus under this condition can offer a more detailed understanding of the key genes involved in its growth. This, in turn, can facilitate a deeper insight into its role in the decomposition of P. sylvestris var. mongolica.
RT-qPCR has gained widespread popularity for gene expression assessment because of its exceptional accuracy, specificity, sensitivity, and capacity for expedited analysis [18,19,20]. Nevertheless, the reliability of RT-qPCR results is susceptible to several factors such as the integrity and purity of RNA, cDNA synthesis efficiency, polymerase amplification efficiency, and normalization [21,22]. Utilizing reference genes for the purpose of normalization is crucial in enhancing the precision of experimental outcomes [23]. Optimal reference genes should maintain consistent expression levels across various tissues and cell types. No single reference gene exhibits universal stability under all experimental contexts [24,25,26]. Hence, it is imperative to select reference genes with consistent expression levels based on the required experimental samples and conditions. Previous studies have identified P450, γ-TUB, and CYP as reference genes during the development of A. areolatum on the PDA medium [27]. However, their expression stability during the fungus’s growth and development under Mongolian Scots pine wood powder conditions remains to be investigated. To deepen our understanding of the critical genes influencing the growth and development of the symbiotic fungus in P. sylvestris var. mongolica, 13 candidate reference genes were identified from the transcriptome data generated from the symbiotic fungus under Mongolian Scots pine wood powder conditions. A total of three optimal reference genes were identified under PDA culture conditions. Techniques such as BestKeeper and NormFinder were employed to assess the stability of analyzed candidates during the growth and development of A. areolatum. This study aims to establish appropriate reference genes for future studies on the nutritional interactions between A. areolatum and S. noctilio.

2. Materials and Methods

2.1. Sample Collection

A. areolatum was isolated from the female woodwasps collected in Xindian Forest Farm, Heilongjiang Province, China. The strain was identified and preserved in the Beijing Key Laboratory for the Control of Forest Pest, Beijing Forestry University, Beijing, China [28]. The Mongolian Scots pine employed in this research was collected from the same location. The pine wood blocks were cut into 1.5 × 0.7 × 0.3 cm pieces, dried at 90 °C, and subsequently ground into fine powder. We employed a 60-mesh sieve so that larger particles were eliminated. The filtered wood powder was then stored in conical flasks. The wood powder was sterilized at 117 °C for 20 min for subsequent use. For the Mongolian Scots pine wood powder culture medium, each liter included 175 g of the sterilized pine wood powder, 15 g of agar, 3 g of malt extract, and 0.3 g of yeast extract. This mixture was homogenized with water, then sterilized at 117 °C for 20 min, ready for use.
A. areolatum was cultured on PDA medium for 1 week. Mycelial plugs of 6 mm in diameter were taken from the edge of the colony and inoculated onto the Mongolian Scots pine wood powder culture medium. Mycelia were collected at 7, 10, and 14 days of incubation, immediately frozen in liquid nitrogen and stored at −80 °C for RNA extraction.

2.2. Total RNA Extraction, Detection and cDNA Synthesis

Total RNA was isolated from the samples with the RNAprep Pure Plant Kit (Tiangen, Beijing, China). The quality and quantity of the extracted RNA were assessed using a NanoDrop 2000 spectrophotometer (Thermo, Waltham, MA, USA) and 1% agarose gel electrophoresis. The gDNA Eraser (Takara Bio Inc., Shiga, Japan) was employed to eliminate DNA from the RNA samples. Then, the first-strand cDNA was synthesized utilizing the PrimeScript™ RT Reagent Kit (Takara Bio Inc., Shiga, Japan). All experimental procedures were followed in accordance with the manufacturers’ recommendations.

2.3. Reference Genes Selection and Primer Design

Drawing upon the transcriptome data from A. areolatum cultivated in the Mongolian Scots pine wood powder medium by our research team (unpublished), 13 genes with relatively stable expression were identified as candidates. These genes included α-TUB, β-TUB, γ-TUB, GPAT, CYP, UBI, PTPA, GAP, Hfl, P450, BAR, ACT2, and UBC (Table S1). Specific primers for these genes were designed using Primer 3.0 (https://primer3.ut.ee/) (accessed on 15 September 2023) [29] following the established primer design criteria. The specificity of these primers was then verified through PCR and 1.5% agarose gel electrophoresis. PCR was carried out using the same reaction as RT-qPCR (The 25 μL reactions contained 12.5 μL of 2× Es Taq MasterMix (Dye) (Cwbio, Beijing, China); the usage of primers, cDNA, and water was the same as that in RT-qPCR reactions). The amplification conditions were as follows: 95 °C for 30 s, 40 cycles of 95 °C for 5 s, and 60 °C for 30 s. The details of the primer sequences are listed in Table 1.

2.4. RT-qPCR Analysis

The RT-qPCR assays were performed utilizing the CFX Connect Real-Time PCR System (Bio-Rad, Hercules, CA, USA). Reaction compositions were as follows: 1 μL of each primer (10 μM), 12.5 μL of TB Green Premix Ex Taq II (2×), 2 μL of cDNA, and sufficient water to reach a total volume of 25 μL. The amplification was initiated at 95 °C for 30 s, proceeding with 40 cycles of 95 °C for 5 s and 60 °C for 30 s. A melting curve analysis was performed after each run from 65 to 95 °C, using the default program. Three independent technical and biological replicates were conducted for each gene across all sample groups. The RT-qPCR reactions for each candidate reference gene were performed using 1-, 1/5-, 1/25-, 1/125-, and 1/625-diluted cDNA as the template. Ct values were obtained for each sample, and standard curves were generated for each candidate reference gene. The amplification efficiency (E) and correlation coefficient (R2) were calculated using the formula E% = [10(−1/slope) − 1] × 100% [30].

2.5. Statistical Analysis

2.5.1. Stability Analysis of Candidate Reference Genes

To evaluate the stability of selected reference genes within A. areolatum samples across different growth and developmental stages, we employed five distinct algorithms—delta Ct, geNorm, NormFinder, BestKeeper, and RefFinder—for comprehensive analysis.
  • The delta Ct method was employed to assess the expression stability of all candidates. The average standard deviation (SD) of Ct values for each gene was calculated in all samples. Genes with lower SD values were considered to be more stably expressed [31].
  • The geNorm method [21] was employed to further assess the expression stability of the candidates. The initial Ct values were first converted to 2−∆Ct values (∆Ct = original Ct value—the lowest Ct in each group). The average expression stability value (M) was used to rank the candidates. Genes with lower M values were considered to be more stably expressed. Genes with an M value > 1.5 were considered unsuitable as reference. Further, geNorm aided in identifying the ideal number of reference genes by examining genes pairwise variations (Vn/Vn+1, pairwise variations between the normalization factors NFn and NFn+1), proposing n as the optimal count when Vn/Vn+1 falls below 0.15, or otherwise suggesting n + 1.
  • The 2−∆Ct value was also required when using NormFinder for gene expression stability evaluation. This approach determines the stability of candidate reference genes by analyzing their variations across and within groups. Candidate reference genes with lower S values exhibited higher expression stability and were thus more appropriate for use as reference genes [32].
  • BestKeeper was used to evaluate the expression stability of all candidates by computing their coefficient of variation (CV) and SD. Genes demonstrating stability were characterized by minimal CV and SD values. Importantly, genes with an SD value greater than 1 were considered unsuitable as reference genes [33].
  • Ultimately, by synthesizing the methodologies of the aforementioned algorithms, RefFinder was employed to perform a comprehensive ranking based on the expression stability of all genes [34,35].

2.5.2. Validation of Reference Genes

Drawing transcriptome data from A. areolatum grown on Mongolian Scots pine wood powder medium, this research utilized the AaLac1 as a probe to evaluate the reliability of the highest four and the lowest two reference genes based on their comprehensive stability ranking by 2−∆∆Ct method [36]. Differences in their expression were compared according to t-test.

3. Results

3.1. Amplification Specificity and Efficiency Analysis

The specificity of gene primers was evaluated using 1.0% agarose gel electrophoresis. All 13 candidate reference genes yielded distinct and single bands, with fragment sizes ranging from 100 to 200 bp, in accordance with the expected amplicon lengths (Figure S1). Furthermore, all genes displayed a single melting peak within the melting curve analysis, indicative of the superior specificity pertaining to the primers and the conspicuous absence of non-specific amplification byproducts (Figure S2). Standard curve analyses indicate that the amplification efficiencies (E) of these genes fall within the range of 90% to 110%. The correlation coefficients (R2) were all exceeding 0.99 (Table 1). These results demonstrate the successful design of specific primers for these candidates, which can be utilized in subsequent experiments.

3.2. Expression Analysis of Reference Genes

The expression levels of these reference genes were critically appraised utilizing RT-qPCR. Ct values, which were inversely correlated with gene expression levels, were determined for each gene. Among these candidates, Ct values ranged from 24 to 31, with α-TUB and β-TUB exhibiting the lowest Ct values, indicative of their highest expression levels. Conversely, γ-TUB, UBI, and ACT2 presented the highest mean Ct values, which are reflective of the lowest expression abundance. Furthermore, genes P450, γ-TUB, and β-TUB exhibited the most concentrated Ct value distribution, suggesting a remarkably consistent expression pattern throughout various stages of growth and development in A. areolatum (Figure 1).

3.3. Stability Analysis of Reference Genes

3.3.1. Delta Ct Analysis

The stability of these reference genes was evaluated by comparing their average SD values using the delta Ct method. As depicted in Figure 2, α-TUB, P450, UBC, and GAP exhibited the lowest average SD values (0.31, 0.32, 0.33, and 0.34, respectively), indicating their superior stability across different samples. Conversely, β-TUB and GPAT had significantly higher average SD values (0.49 and 0.51, respectively), rendering them unsuitable as reference genes.

3.3.2. geNorm Analysis

To further evaluate the stability of analyzed candidates, geNorm was employed to calculate their average expression stability M values. A lower M value indicates higher stability. The M values of all genes were less than 1.5, suggesting their overall stability (Figure 3A). Among them, α-TUB, CYP, P450, and UBC had the lowest M values (0.19, 0.19, 0.21, and 0.23, respectively), demonstrating their superior stability as reference genes. Conversely, β-TUB and GPAT had the highest M values (0.35 and 0.38, respectively), indicating their relatively unstable expression in the analyzed samples and thus making them less suitable as reference genes. These findings are consistent with the results obtained from the delta Ct analysis.
Furthermore, pairwise variation analysis showed that all Vn/Vn+1 values in this present study were less than 0.15 (Figure 3B). This finding implied that the utilization of two reference genes was sufficient for the reliable normalization of RT-qPCR data when investigating the growth of A. areolatum on the Mongolian Scots pine wood powder culture medium.

3.3.3. NormFinder Analysis

The NormFinder approach was employed to assess the stability of candidate reference genes by calculating the variance within and between sample groups. Consistent with the delta Ct analysis results, the stability values (S values) of the candidate reference genes α-TUB, P450, UBC, and GAP were relatively low (0.15, 0.16, 0.17, and 0.22, respectively), indicating that the expression of analyzed candidate reference genes was most stable across different samples. Conversely, β-TUB and GPAT showed higher S values (both at 0.44), rendering them unsuitable as reference genes (Table 2).

3.3.4. BestKeeper Analysis

According to the findings from the BestKeeper analysis, γ-TUB, P450, β-TUB, and UBI stood out for their consistent expression levels across the board, making them the recommended choice for reference genes. In contrast, GPAT and ACT2 showed significantly less stability in all samples, suggesting they were not appropriate choices for reference genes (Table 2).

3.3.5. RefFinder Analysis

Utilizing the RefFinder analysis, a comprehensive evaluation of the expression stability for the candidates was conducted through the geometric averaging of results from four distinct algorithms. The expression stability ranking of the 13 candidate reference genes is presented in Table 2. A comprehensive analysis revealed that α-TUB, P450, UBC, and CYP exhibited the highest expression in all samples. These four genes were suitable to be used as reference genes for growth analysis of A. areolatum under the culture conditions of Mongolian Scots pine wood powder. Conversely, β-TUB, ACT2, and GPAT were ranked lower and thus were not recommended as reference genes. Moreover, the integrated analysis of geNorm and RefFinder indicated that, under the experimental conditions of this study, the combination of α-TUB and P450 was recommended as the superior choice for normalizing gene expression.

3.4. Validation of Reference Genes

In this study, utilizing AaLac1 as the target gene, the reliability of selected reference genes was verified through RT-qPCR analysis. Four most stable candidate reference genes (α-TUB, P450, UBC, and CYP), the expression of AaLac1 in A. areolatum was normalized by using the two least stable reference genes (ACT2 and GPAT), and two combinations of the most stable reference genes (α-TUB+P450+UBC and α-TUB+P450), after culturing on Mongolian Scots pine wood powder culture medium for 7 and 14 days. When α-TUB, P450, and UBC were used for normalization, the expression patterns of AaLac1 were similar to transcriptomic findings (Figure 4). When normalized by the unstable reference genes, the expression patterns of AaLac1 were not compatible, with the expression levels in 14-day and 7-day samples being nearly identical. Unexpectedly, the normalization of AaLac1 expression with CYP, which is ranked fourth in terms of stability, resulted in a trend that deviated from the outcomes of transcriptome analysis. In summary, our findings suggested that under the culture conditions of Mongolian Scots pine wood powder, α-TUB, P450, and UBC, either individually or in combination, were suitable as reference genes for the analysis of gene expression related to the growth of A. areolatum. Conversely, under our experiment conditions, CYP, ACT2, and GPAT were found to be unsuitable as reference genes for gene expression analysis.

4. Discussion

A strict mutualistic symbiosis exists between S. noctilio and A. areolatum [6]. As an ectosymbiotic fungus, A. areolatum is integral in degrading the cell walls of the host tree and supplying nutrients essential for the growth and development of S. noctilio [37,38,39]. In pursuit of elucidating the decompositional effects and mechanisms of A. areolatum on the P. sylvestris var. mongolica, our team previously formulated a Mongolian Scots pine wood powder medium that supported the growth of the fungus. By comparing the growth curves of A. areolatum on this medium with those on PDA performing as a pilot, we did not find significant differences. However, a higher growth rate was determined on the Mongolian Scots pine wood powder medium. Gene expression studies under this culture condition might be more conducive to identifying key genes involved in the growth of the symbiotic fungus. We explored the optimal reference genes for A. areolatum at various growth stages under PDA culture conditions in a previous study [27]. However, reference genes are not universally applicable and their selection should be specific to the research subject and experimental conditions. A plethora of studies have demonstrated analogous outcomes [40,41,42,43]. For Chinese cordyceps, Tef1 and Tub1, Tyr and Cox5, and Tyr and Tef1 served as the most stable during its asexual reproduction, fruiting body development, and light-induced conditions, respectively [44]. Likewise, In Floccularia luteovirens, ACT and EF-Tu were suitable for salt stress, β-TUB and UBC-E2 for drought stress, H3 and GPAT for oxidative stress, EF-Tu and γ-TUB for heat stress, UBC-E2 and H3 for extreme pH stress, ACT and UBC-E2 for cadmium stress. Moreover, H3 and GTPBP1 were the most stable across different tissues of F. luteovirens [45]. These results further illustrate the importance of reference genes for accurate gene expression analysis in specific experimental samples and conditions.
In this study, we analyzed the transcriptomic data of A. areolatum during different growth stages under the culture conditions of Mongolian Scots pine wood powder, leading to the preliminary selection of 13 genes with stable expression profiles as candidate reference genes. The stability of analyzed candidates was evaluated using established methods, including delta Ct, geNorm, NormFinder, and BestKeeper. The aforementioned methods may produce discrepant results due to the underlying algorithms employed. Consequently, the integration of these evaluations through RefFinder to rank candidate reference genes was essential in their selection [27,46,47]. Serving as major constituents of the eukaryotic cytoskeleton, tubulin participates in various cellular activities such as cell division and organelle movement. Therefore, it is commonly employed as a reference gene for gene expression analysis in eukaryotes [48,49]. In our findings, α-TUB consistently emerged as the leading candidate across deltaCt, geNorm, and NormFinder evaluations, albeit ranking fifth in BestKeeper’s assessment. In contrast, β-TUB secured the third spot in BestKeeper but landed in the bottom tier across the other platforms, indicating a pronounced disparity. Throughout the developmental stages of Pythium porphyrae, γ-Tubulin and α-Tubulin2 were identified as the most stable reference genes. Despite ranking first in the BestKeeper analysis, the expression of α-Tublin2 was still considered unstable (SD > 1). This discrepancy likely arose from BestKeeper’s inability to accurately assess gene stability across samples with varying template concentrations. However, the other three algorithms effectively compensated for this limitation, culminating in a thorough evaluation of optimal reference gene candidates. Thus, a comprehensive analysis utilizing multiple algorithms proved essential [49]. In addition, we found that α-TUB and P450 were amongst the top contenders in all evaluations, with their position solidified through RefFinder’s integrated ranking, underscoring their expression stability across the board and affirming their suitability as reference genes for gene expression studies.
Research showed that the expression stability of reference genes varies across different culture media. In Candida viswanathii, CvRPB2/CvACT, CvFBA1/CvAGL9, CvPGK1/CvAGL9, and CvACT/CvRPB2 were identified as the best reference gene pairs for the culture media containing olive oil, triolein, tributyrin, and glucose as carbon sources, respectively [50]. EF1a/α-tubulin and RPS5/α-tubulin were identified as the most suitable reference genes for distinct developmental stages and culture media in Litchi chinensis, respectively [51]. Our previous study demonstrated that, under PDA culture conditions, P450, γ-TUB, and CYP, either individually or in combination, served as the most suitable reference genes for quantitative analysis of gene expression in A. areolatum at different growth stages [27]. The comprehensive evaluation results of this study indicated that P450 was a suitable reference gene for quantitative analysis of gene expression in A. areolatum at different growth stages under Mongolian Scots pine wood powder culture conditions. This was further verified by subsequent experiments. Conversely, γ-TUB was found to be less appropriate as a reference gene under this experiment conditions. Although CYP ranked well in the comprehensive evaluation, its normalization led to a discrepancy in the relative expression trend of AaLac1 across RT-qPCR results compared to transcriptomic findings, disqualifying it as a candidate reference gene. The incorporation of two or more reference genes has been shown to refine the precision of relative expression analysis. Under the regimen of PDA cultures, it was recommended to employ at least three reference genes for the quantitative gene expression analysis in A. areolatum at different growth stages. Under the conditions of this study, geNorm analysis indicated that a combination of at least two reference genes was sufficient to meet the requirements of RT-qPCR analysis. Validation analysis revealed similar trends in the relative expression of AaLac1 normalized by the two reference gene combinations (α-TUB+P450+UBC) and (α-TUB+P450) across different growth stages. These results suggest that two reference genes are sufficient for gene expression analysis under the experimental conditions of this study. Moreover, both analytical conditions indicated stable expression of P450, suggesting its suitability as a reference gene for gene expression analysis in A. areolatum across different growth stages in both Mongolian Scots pine wood powder and PDA culture conditions. These findings lay a foundation for further exploring the degradation mechanisms of P. sylvestris var. mongolica by A. areolatum.

5. Conclusions

To determine appropriate reference genes for the analysis of gene expression in A. areolatum at various growth stages under the culture conditions of Mongolian Scots pine wood powder, we conducted a thorough assessment of 13 candidate genes through the application of the delta Ct, geNorm, BestKeeper, RefFinder, and NormFinder algorithms. We conclusively determined that α-TUB and P450, both individually and in combination, constituted the most suitable reference genes for gene expression analysis within the experimental conditions of the current study. This study not only established a theoretical basis for identifying functional genes associated with the growth of A. areolatum using transcriptome and RT-qPCR methods but also aids in advancing our understanding of the symbiotic relationship between S. noctilio and A. areolatum.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/f15071172/s1, Figure S1: Amplified fragments of 13 candidate reference genes exhibited by agarose gel; Figure S2: Melting curves for the candidate reference genes; Table S1: The genomic DNA sequences of thirteen candidate reference genes.

Author Contributions

Conceptualization, C.G., D.Z. and L.R.; methodology, C.G. and N.F.; software, C.G., N.F. and Y.L.; validation, D.Z. and L.R.; formal analysis, C.G. and Y.L.; investigation, D.Z. and L.R.; resources, C.G. and N.F.; writing—original draft preparation, C.G.; writing—review and editing, D.Z., L.R. and L.H.; visualization, C.G. and H.H.; supervision, D.Z. and L.R.; project administration, D.Z. and L.R.; funding acquisition, D.Z. and L.R. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Forestry Science and Technology Innovation Program of Guangdong Province (2021KJCX006).

Data Availability Statement

Data are contained within the article and Supplementary Materials.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

α-TUB: α-tubulin; β-TUB: β-tubulin; γ-TUB: γ-tubulin; GPAT: Glycerol-3-phosphate acyltransferase; CYP: Cyclophilin; UBI: Ubiquitin; PTPA: Phosphotyrosyl phosphatase activator; GAP: GTPase activating protein; Hfl: ATP-dependent metallopeptidase Hfl; P450: Cytochrome P450; BAR: BAR domain-containing family protein; ACT2: Actin 2; UBC: Ubiquitin-conjugating enzyme.

References

  1. Li, D.; Shi, J.; Luo, Y. Mutualism Between the Eurasian Woodwasp, Sirex noctilio (Hymenoptera: Siricidae) and Its Fungal Symbiont Amylostereum areolatum (Russulales: Amylostereaceae). Acta Entomol. Sin. 2015, 58, 1019–1029. [Google Scholar]
  2. Groot, P.; Nystrom, K.; Scarr, T. Discovery of Sirex noctilio (Hymenoptera: Siricidae) in Ontario, Canada. Great Lakes Entomol. 2006, 39, 49–53. [Google Scholar] [CrossRef]
  3. Ajó Fernández, A.A.F.; Martínez, A.S.; Villacide, J.M.; Corley, J.C. Behavioural response of the woodwasp Sirex noctilio to volatile emissions of its fungal symbiont. J. Appl. Entomol. 2015, 139, 654–659. [Google Scholar] [CrossRef]
  4. Ciesla, W.M. European woodwasp: A potential threat to North America’s conifer forests. J. For. 2003, 101, 18–23. [Google Scholar] [CrossRef]
  5. Carnegie, A.; Eldridge, R.H.; Waterson, D.G. History and Management of Sirex Wood Wasp in Pine Plantations in New South Wales, Australia. N. Z. J. For. Sci. 2005, 35, 3–24. [Google Scholar]
  6. Slippers, B.; Coutinho, T.; Wingfield, B.; Wingfield, M. A Review of the Genus Amylostereum and Its Association with Woodwasps. S. Afr. J. Sci. 2003, 99, 70–74. [Google Scholar]
  7. Slippers, B.; De Groot, P.; Wingfield, M.J. The Sirex Woodwasp and Its Fungal Symbiont: Research and Management of a Worldwide Invasive Pest; Springer: Dordrecht, The Netherlands, 2012. [Google Scholar]
  8. Li, H.; Young, S.E.; Poulsen, M.; Currie, C.R. Symbiont-Mediated Digestion of Plant Biomass in Fungus-Farming Insects. Annu. Rev. Entomol. 2021, 66, 297–316. [Google Scholar] [CrossRef] [PubMed]
  9. Biedermann, P.H.W.; Vega, F.E. Ecology and Evolution of Insect-Fungus Mutualisms. Annu. Rev. Entomol. 2020, 65, 431–455. [Google Scholar] [CrossRef]
  10. Wang, M.; Wang, L.; Li, D.; Fu, N.; Li, C.; Luo, Y.; Ren, L. Advances in the Study of Mutualism Relationship between Amylostereum areolatum and Sirex noctilio. J. Temp. For. Res. 2020, 3, 1–11. [Google Scholar]
  11. Talbot, P.H.B. The Sirex-Amylostereum-Pinus Association. Annu. Rev. Phytopathol. 1977, 15, 41–54. [Google Scholar] [CrossRef]
  12. Hajek, A.E.; Nielsen, C.; Kepler, R.M.; Long, S.J.; Castrillo, L. Fidelity Among Sirex Woodwasps and Their Fungal Symbionts. Microb. Ecol. 2013, 65, 753–762. [Google Scholar] [CrossRef]
  13. Thompson, B.M.; Bodart, J.; McEwen, C.; Gruner, D.S. Adaptations for Symbiont-Mediated External Digestion in Sirex noctilio (Hymenoptera: Siricidae). Ann. Entomol. Soc. Am. 2014, 107, 453–460. [Google Scholar] [CrossRef]
  14. Humber, R.A.; Batra, L.R. Insect-Fungus Symbiosis: Nutrition, Mutualism, and Commensalism. Mycologia 1980, 72, 848. [Google Scholar] [CrossRef]
  15. Wang, L. The Influence of Host Tree Endophytic Fungi on the Invasive Species Sirex noctilio (Hymenoptera: Siricidae). Ph.D. Thesis, Beijing Forestry University, Beijing, China, 2019. [Google Scholar]
  16. Madden, J. Egg and Larval Development in the Woodwasp, Sirex noctilio F. Aust. J. Zool. 1981, 29, 493. [Google Scholar] [CrossRef]
  17. Fu, N.; Wang, M.; Gao, C.; Ren, L.; Luo, Y. Transcriptomics Analysis of Amylostereum areolatum at Different Development Stages. Mycosystema 2021, 40, 2771–2784. [Google Scholar]
  18. Gao, P.; Wang, J.; Wen, J. Selection of Reference Genes for Tissue/Organ Samples of Adults of Eucryptorrhynchus scrobiculatus. PLoS ONE 2020, 15, e0228308. [Google Scholar] [PubMed]
  19. Zhao, M.; Fan, H.; Tu, Z.; Cai, G.; Zhang, L.; Li, A.; Xu, M. Stable Reference Gene Selection for Quantitative Real-Time PCR Normalization in Passion Fruit (Passiflora edulis Sims.). Mol. Biol. Rep. 2022, 49, 5985–5995. [Google Scholar] [CrossRef]
  20. Derveaux, S.; Vandesompele, J.; Hellemans, J. How to Do Successful Gene Expression Analysis Using Real-Time PCR. Methods 2010, 50, 227–230. [Google Scholar] [CrossRef] [PubMed]
  21. Vandesompele, J.; De Preter, K.; Pattyn, F.; Poppe, B.; Van Roy, N.; De Paepe, A.; Speleman, F. Accurate Normalization of Real-Time Quantitative RT-PCR Data by Geometric Averaging of Multiple Internal Control Genes. Genome Biol. 2002, 3, research0034.1. [Google Scholar] [CrossRef]
  22. Kozera, B.; Rapacz, M. Reference Genes in Real-Time PCR. J. Appl. Genet. 2013, 54, 391–406. [Google Scholar] [CrossRef]
  23. Yang, Z.; Zhang, R.; Zhou, Z. Identification and Validation of Reference Genes for Gene Expression Analysis in Schima superba. Genes 2021, 12, 732. [Google Scholar] [CrossRef] [PubMed]
  24. Gutierrez, L.; Mauriat, M.; Guénin, S.; Pelloux, J.; Lefebvre, J.; Louvet, R.; Rusterucci, C.; Moritz, T.; Guerineau, F.; Bellini, C.; et al. The Lack of a Systematic Validation of Reference Genes: A Serious Pitfall Undervalued in Reverse Transcription-polymerase Chain Reaction (RT-PCR) Analysis in Plants. Plant Biotechnol. 2008, 6, 609–618. [Google Scholar] [CrossRef] [PubMed]
  25. Chen, X.; Chen, X.; Tan, Q.; He, Y.; Wang, Z.; Zhou, G.; Liu, J. Selection of Potential Reference Genes for RT-QPCR in the Plant Pathogenic Fungus Colletotrichum fructicola. Front. Microbiol. 2022, 13, 982748. [Google Scholar] [CrossRef] [PubMed]
  26. Guenin, S.; Mauriat, M.; Pelloux, J.; Van Wuytswinkel, O.; Bellini, C.; Gutierrez, L. Normalization of QRT-PCR Data: The Necessity of Adopting a Systematic, Experimental Conditions-Specific, Validation of References. J. Exp. Bot. 2009, 60, 487–493. [Google Scholar] [CrossRef] [PubMed]
  27. Fu, N.; Li, J.; Wang, M.; Ren, L.; Zong, S.; Luo, Y. Identification and Validation of Reference Genes for Gene Expression Analysis in Different Development Stages of Amylostereum areolatum. Front. Microbiol. 2022, 12, 827241. [Google Scholar] [CrossRef]
  28. Wang, M.; Fu, N.; Gao, C.; Wang, L.; Ren, L.; Luo, Y. Multilocus Genotyping and Intergenic Spacer Single Nucleotide Polymorphisms of Amylostereum areolatum (Russulales: Amylostereacea) Symbionts of Native and Non-Native Sirex Species. J. Fungi 2021, 7, 1065. [Google Scholar] [CrossRef] [PubMed]
  29. Kõressaar, T.; Lepamets, M.; Kaplinski, L.; Raime, K.; Andreson, R.; Remm, M. Primer3_masker: Integrating Masking of Template Sequence with Primer Design Software. Bioinformatics 2018, 34, 1937–1938. [Google Scholar] [CrossRef] [PubMed]
  30. Radonić, A.; Thulke, S.; Mackay, I.M.; Landt, O.; Siegert, W.; Nitsche, A. Guideline to Reference Gene Selection for Quantitative Real-Time PCR. Biochem. Biophys. Res. Commun. 2004, 313, 856–862. [Google Scholar] [CrossRef] [PubMed]
  31. Silver, N.; Best, S.; Jiang, J.; Thein, S.L. Selection of Housekeeping Genes for Gene Expression Studies in Human Reticulocytes Using Real-Time PCR. BMC Mol. Biol. 2006, 7, 33. [Google Scholar] [CrossRef]
  32. Andersen, C.L.; Jensen, J.L.; Ørntoft, T.F. Normalization of Real-Time Quantitative Reverse Transcription-PCR Data: A Model-Based Variance Estimation Approach to Identify Genes Suited for Normalization, Applied to Bladder and Colon Cancer Data Sets. Cancer Res. 2004, 64, 5245–5250. [Google Scholar] [CrossRef]
  33. Pfaffl, M.W.; Tichopad, A.; Prgomet, C.; Neuvians, T.P. Determination of Stable Housekeeping Genes, Differentially Regulated Target Genes and Sample Integrity: BestKeeper–Excel-Based Tool Using Pair-Wise Correlations. Biotechnol. Lett. 2004, 26, 509–515. [Google Scholar] [CrossRef] [PubMed]
  34. Xie, F.; Wang, J.; Zhang, B. RefFinder: A Web-based Tool for Comprehensively Analyzing and Identifying Reference Genes. Funct. Integr. Genom. 2023, 23, 125. [Google Scholar] [CrossRef] [PubMed]
  35. Xie, F.; Xiao, P.; Chen, D.; Xu, L.; Zhang, B. MiRDeepFinder: A MiRNA Analysis Tool for Deep Sequencing of Plant Small RNAs. Plant Mol. Biol. 2012, 80, 75–84. [Google Scholar] [CrossRef] [PubMed]
  36. Schmittgen, T.D.; Livak, K.J. Analyzing Real-Time PCR Data by the Comparative CT Method. Nat. Protoc. 2008, 3, 1101–1108. [Google Scholar] [CrossRef] [PubMed]
  37. Thompson, B.M.; Grebenok, R.J.; Behmer, S.T.; Gruner, D.S. Microbial Symbionts Shape the Sterol Profile of the Xylem-Feeding Woodwasp, Sirex noctilio. J. Chem. Ecol. 2013, 39, 129–139. [Google Scholar] [CrossRef] [PubMed]
  38. Van der Merwe, E.; Slippers, B.; Dittrich-Schröder, G. Mechanical Egg Activation and Rearing of First Instar Larvae of Sirex noctilio (Hymenoptera: Siricidae). Insects 2023, 14, 931. [Google Scholar] [CrossRef] [PubMed]
  39. Bordeaux, J.M. Characterization of Growth Conditions for Production of a Laccase-like Phenoloxidase by Amylostereum areolatum, a Fungal Pathogen of Pines and Other Conifers. Ph.D. Thesis, University of Georgia, Athens, GA, USA, 2008. [Google Scholar]
  40. Chen, Z.; Bai, X.; Li, X.; Zeng, B.; Hu, B. Selection of Reference Genes for Gene Expression Analysis in Acacia melanoxylon under Different Conditions. Forests 2023, 14, 2245. [Google Scholar] [CrossRef]
  41. Wang, G.; Cheng, H.; Li, M.; Zhang, C.; Deng, W.; Li, T. Selection and Validation of Reliable Reference Genes for Tolypocladium guangdongense Gene Expression Analysis under Differentially Developmental Stages and Temperature Stresses. Gene 2020, 734, 144380. [Google Scholar] [CrossRef] [PubMed]
  42. Liu, Y.; Zhou, J.; Qiu, Z.; Hu, P.; Chen, X.; Yang, Z. Identification and Validation of Reference Genes for Expression Analysis Using RT-qPCR in Leptocybe invasa Fisher and La Salle (Hymenoptera: Eulophidae). Insects 2023, 14, 456. [Google Scholar] [CrossRef]
  43. Li, R.; Xie, W.; Wang, S.; Wu, Q.; Yang, N.; Yang, X.; Pan, H.; Zhou, X.; Bai, L.; Xu, B.; et al. Reference gene selection for qRT-PCR analysis in the sweetpotato whitefly, Bemisia tabaci (Hemiptera: Aleyrodidae). PLoS One 2013, 8, e53006. [Google Scholar] [CrossRef]
  44. Tong, C.; Wei, J.; Mao, X.; Pan, G.; Li, C.; Zhou, Z. Stable Reference Gene Selection for Ophiocordyceps sinensis Gene Expression Studies under Different Developmental Stages and Light-Induced Conditions. PLoS ONE 2023, 18, e0284486. [Google Scholar] [CrossRef] [PubMed]
  45. Ni, Y.; Zhang, Q.; Li, W.; Cao, L.; Feng, R.; Zhao, Z.; Zhao, X. Selection and Validation of Reference Genes for Normalization of Gene Expression in Floccularia luteovirens. Fungal Biol. 2024, 128, 1596–1606. [Google Scholar] [CrossRef] [PubMed]
  46. Jia, D.; Wang, B.; Li, X.; Tan, W.; Gan, B.; Peng, W. Validation of Reference Genes for Quantitative Gene Expression Analysis in Auricularia cornea. J. Microbiol. Meth. 2019, 163, 105658. [Google Scholar] [CrossRef] [PubMed]
  47. Lv, Y.; Li, Y.; Liu, X.; Xu, K. Identification of Ginger (Zingiber officinale Roscoe) Reference Genes for Gene Expression Analysis. Front. Genet. 2020, 11, 586098. [Google Scholar] [CrossRef] [PubMed]
  48. Alexandraki, D.; Ruderman, J. Sequence Heterogeneity, Multiplicity, and Genomic Organization of Alpha- and Beta-tubulin Genes in Sea Urchins. Mol. Cell. Biol. 1981, 1, 1125–1137. [Google Scholar] [CrossRef]
  49. Yang, H.; Yan, Y.; Weng, P.; Sun, C.; Yu, J.; Tang, L.; Li, J.; Mo, Z. Evaluation of Reference Genes for Quantitative Real-time PCR Normalization in The Neopyropia (Pyropia) Oomycete Pathogen Pythium porphyrae. J. Appl. Phycol. 2023, 35, 219–231. [Google Scholar] [CrossRef]
  50. Daúde, M.M.; Teixeira, R.C.; Cardon, C.H.; de Araujo Santos, G.C.; de Almeida, A.F.; Chalfun-Junior, A.; Barreto, H.G. Selection and Validation of Reference Genes for RT-qPCR Gene Expression Studies in Candida viswanathii Cultivated under Different Grown Conditions. J. Microbiol. Methods 2023, 211, 106777. [Google Scholar] [CrossRef]
  51. Dong, D.; Huang, R.; Hu, Y.; Yang, X.; Xu, D.; Jiang, Z. Assessment of Candidate Reference Genes for Gene Expression Studies Using RT-qPCR in Colletotrichum fructicola from Litchi. Genes 2023, 14, 2216. [Google Scholar] [CrossRef]
Forests 15 01172 g001
Figure 1. The cycle threshold (Ct) values of 13 candidate reference genes span all samples. The box demarcates the range between the 25th and 75th percentiles, while the line within the box designates the median value.
Figure 1. The cycle threshold (Ct) values of 13 candidate reference genes span all samples. The box demarcates the range between the 25th and 75th percentiles, while the line within the box designates the median value.
Forests 15 01172 g001
Forests 15 01172 g002
Figure 2. The average SD values of these reference genes calculated by delta Ct.
Figure 2. The average SD values of these reference genes calculated by delta Ct.
Forests 15 01172 g002
Forests 15 01172 g003
Figure 3. Average expression stability and pairwise variation of all genes calculated by geNorm: (A) Expression stability of analyzed candidate genes; (B) Pairwise variation of 13 reference genes. A threshold of 0.15 is established as the optimal number of reference genes for RT-qPCR normalization.
Figure 3. Average expression stability and pairwise variation of all genes calculated by geNorm: (A) Expression stability of analyzed candidate genes; (B) Pairwise variation of 13 reference genes. A threshold of 0.15 is established as the optimal number of reference genes for RT-qPCR normalization.
Forests 15 01172 g003
Forests 15 01172 g004
Figure 4. The expression level of AaLca1 using the most stable and least stable reference genes for normalization: (A) Relative expression levels of AaLca1 normalized by α-TUB, P450, UBC, ACT2, and GPAT, and two combinations, α-TUB+P450+UBC and α-TUB+P450; (B) Transcriptomic sequencing data of AaLca1 from A. areolatum grown on Mongolian Scots pine wood powder medium at 7 and 14 days.
Figure 4. The expression level of AaLca1 using the most stable and least stable reference genes for normalization: (A) Relative expression levels of AaLca1 normalized by α-TUB, P450, UBC, ACT2, and GPAT, and two combinations, α-TUB+P450+UBC and α-TUB+P450; (B) Transcriptomic sequencing data of AaLca1 from A. areolatum grown on Mongolian Scots pine wood powder medium at 7 and 14 days.
Forests 15 01172 g004
Table 1. Primer sequences and amplification efficiency of the candidates.
Table 1. Primer sequences and amplification efficiency of the candidates.
SymbolGene DescriptionPrimer (5′-3′)Product (bp)E (%)R2
α-TUBα-tubulinF: CGTGTTTCGAGAGCGGTAAT
R: GGATCGTGCGCTTAGTCTTAAT		11490.10.993
β-TUBβ-tubulinF: CATTGACAACGAGGCTCTCTAC
R: GACATGACGATGGAAACGAGAT		9992.70.992
γ-TUBγ-tubulinF: TGTGTCGGCATGATTGAGAG
R: TGCGTGTGATTGAGCATTTAAC		102104.40.998
GPATGlycerol-3-phosphate acyltransferaseF: AACTCTGTCCTCTCCTCGCT
R: TGAGAAGGGTGAAAACGCGA		8891.10.993
CYPCyclophilinF: CTCGATGACGGGTTTGGATATAA
R: GTCACCACCCTGGATCATAAA		7592.30.991
UBIUbiquitinF: ACGCATTTGAGCCATCGAGA
R: GAGGTACGAGTCCAGAACGC		8498.60.992
PTPAPhosphotyrosyl phosphatase activatorF: GCCGCAGTTCTGGATGTACT
R: AACGTCCTAAATGCCGGGTT		10495.00.997
GAPGTPase activating proteinF: CCTCCACGAAGCACCAGAAT
R: CAAGCGTCGAGTCCAGTTCT		13497.70.993
HflATP-dependent metallopeptidase HflF: CATCGACCCAGTCCTCATCG
R: CGTCAGTACCTTGGGCAGAG		14792.90.993
P450Cytochrome P450F: CACCTTTGCAGTCTACCTACTT
R: CAGCTCCTTCAGATCGTCTATG		11894.40.997
BARBAR domain-containing family proteinF: CTTGTGCAGAAGACCGAGGT
R: TCGTTCAGGTTCTTGACGGG		8099.40.997
ACT2Actin 2F: CGACAATGGCTCTGGGATGT
R: ACGATGGATGGGAAGACAGC		7592.70.992
UBCUbiquitin-conjugating enzymeF: CATCTTGCGGGATCAGTGGA
R: TCCTTCAGTTGTGCAGCGAT		12694.90.993
Table 2. Expression stability of analyzed candidates based on five algorithms.
Table 2. Expression stability of analyzed candidates based on five algorithms.
Reference GenesDelta CtgeNormNormFinderBestKeeperRefFinder
Avg. SDRankMRankSVRankSDCVRankGMRank
α-TUB0.3110.1910.1510.301.1751.501
P4500.3220.2130.1620.240.8722.212
UBC0.3330.2340.1730.311.1273.983
CYP0.3580.1920.2370.351.36104.864
GAP0.3440.2560.2240321.1285.575
BAR0.3560.2880.2250.301.1265.836
γ-TUB0.43110.33110.34100.220.7415.907
Hfl0.3550.2670.2360.341.2596.598
UBI0.3690.3090.2490.291.0047.149
PTPA0.3570.2550.2480.361.25117.6710
β-TUB0.49120.35120.44120.281.1338.4911
ACT20.43100.31100.36110.461.541310.9412
GPAT0.51130.38130.44130.381.361212.7413
Note: SD, standard deviation; M, expression stability value; SV, stability value; CV, coefficient of variation; GM, geometric mean; Rank, the stability rankings of candidate reference gene evaluated by diverse distinct algorithms.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Gao, C.; Fu, N.; Huang, H.; Hu, L.; Li, Y.; Ren, L.; Zhao, D. Identification of Suitable Reference Genes for RT-qPCR Normalization in Amylostereum areolatum Cultured on Pinus sylvestris var. mongholica Wood Powder. Forests 2024, 15, 1172. https://doi.org/10.3390/f15071172

AMA Style

Gao C, Fu N, Huang H, Hu L, Li Y, Ren L, Zhao D. Identification of Suitable Reference Genes for RT-qPCR Normalization in Amylostereum areolatum Cultured on Pinus sylvestris var. mongholica Wood Powder. Forests. 2024; 15(7):1172. https://doi.org/10.3390/f15071172

Chicago/Turabian Style

Gao, Chenglong, Ningning Fu, Huayi Huang, Lili Hu, Yinghui Li, Lili Ren, and Danyang Zhao. 2024. "Identification of Suitable Reference Genes for RT-qPCR Normalization in Amylostereum areolatum Cultured on Pinus sylvestris var. mongholica Wood Powder" Forests 15, no. 7: 1172. https://doi.org/10.3390/f15071172

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop