A universal reference gene suitable for different populus species stems and its screening method and application

Abstract

The application discloses a universal internal reference gene suitable for stems of different tree species of Populus, and a screening method and application thereof, and belongs to the technical field of molecular biology. The universal internal reference gene comprises CNOT2, VPS35 and CUL4 genes with nucleotide sequences shown in SEQ ID NO:1-3 in sequence. The screening method disclosed by the application can obtain new internal reference genes other than those reported at present, and provides more stable and ideal internal reference genes for stem gene expression analysis of different poplars under various conditions, and has an important guiding role for carrying out poplar molecular biology research and biotechnological breeding; and the expression stability of the new internal reference gene is verified by a qRT-PCR verification experiment; and the method is also suitable for screening of universal internal reference genes of other genus plants, and provides an important reference for screening and identification of universal internal reference genes among different species in the same genus.

Description

Technical Field

[0001] This invention relates to the field of molecular biology, and in particular to a universal internal reference gene applicable to the stems of different Populus species, its screening method, and its application. Background Technology

[0002] RNA sequencing (RNA-Seq) technology plays a crucial role in transcriptomics research due to its accuracy, sensitivity, and resolution. In specific RNA-Seq analyses, researchers typically extract total RNA or specific RNA fragments from samples repeated under different or similar biological conditions to conduct gene expression studies. In recent years, with the cost reduction and technological advancements of next-generation sequencing (NGS) technology, RNA-Seq has become the preferred method for gene expression research. This sequence-based approach has not only revolutionized transcriptomics research but also facilitated the development of various new applications, such as strand-specific expression analysis, transcript fusion identification, alternative splicing isoforms, and genome-guided de novo transcript assembly. Furthermore, compared to microarrays, RNA-Seq is a more advanced alternative, capable of more effectively identifying differentially expressed genes (DEGs) under different biological tissues and growth conditions, and recognizing genes with higher genome coverage (including weakly expressed genes).

[0003] RNA-Seq analyzes transcript abundance by calculating the number of fragments generated and the number of reads for a specific transcript. Since the total RNA content in a particular sample is unknown, researchers can normalize RNA-Seq data based on the total number of reads and transcript length for each sample to obtain RPKM or FPKM (Fragments / Reads Per Kilobase Million) values; alternatively, they can normalize the data using reads from all samples by using different normalization methods, such as TMM (Trimmed Mean of M-values), DESeq2, and upper quartiles (UQ).

[0004] RNA-Seq experiments are primarily used to identify DEGs under specific biological conditions. However, besides DEGs, there are many fixed-expression genes (CEGs) that are unaffected by environmental conditions in different cells or developmental stages. For example, in 39 different rice tissues, 22.7% of rice transcripts are expressed by CEGs. Real-time quantitative PCR (qRT-PCR) is a reliable technique for transcript detection and measurement. According to the MIQE (Minimum Information for Publication of Quantitative Real-Time PCR Experiments) guidelines, obtaining reliable qRT-PCR results requires selecting an appropriate internal control gene (RG) to normalize the expression data. RGs are genes whose expression levels are stable across different plant tissues, developmental stages, or physiological conditions and are unaffected by external treatments, thus requiring no verification of their stability. However, validation of RGs in model plants and comprehensive mining of transcriptome data have revealed that the accuracy of endogenous controls is affected by different plant species, the cells / tissues / organs studied, and growth conditions. Therefore, selecting a suitable RG is a crucial step for qRT-PCR expression analysis; inappropriate RG selection can lead to erroneous results.

[0005] In many plants, gene expression receptors (RGs) are typically selected from basic metabolic genes within the cell, such as glyceraldehyde 3-phosphate dehydrogenase (GAPDH) in tomatoes, α- / β-tubulin in olives, actin in poplars, polyubiquitin (UBQ) in petunias, and ubiquitin conjugating enzyme (UBC) in bananas. However, the expression of these genes varies significantly under different conditions and tissue types. The optimal RG may also differ under specific experimental conditions or tissue types. Therefore, it is crucial to verify the expression stability of RGs before normalizing data. Genes with minimal expression variability across different conditions or tissues can be considered potential RG candidates. Only those RG candidates whose expression stability has been verified can be considered RGs for a specific condition or tissue type. BestKeeper, qBasePlus, geNorm, and NormFinder are commonly used statistical tools for identifying optimal candidate RGs under specific experimental conditions.

[0006] Poplar is one of the most widely distributed tree species in the world, and is extensively used in timber production, environmental protection, and urban greening. As an important woody model plant, the stem growth and development of poplar has been extensively studied, generating a wealth of transcriptome data. This invention downloads and evaluates stem tissue transcriptome data from different poplar species from public databases to predict and assess the best candidate gene expression (RG) for poplar stem tissue gene expression analysis. The expression stability of candidate RGs under different stress conditions is verified using qRT-PCR, and a universal RG for poplar stems is screened. Furthermore, based on a case study of poplar stem candidate RG screening, this invention establishes a general workflow for developing RGs for different poplar species using RNA-Seq data, as well as a general method applicable to designing primers for specific internal reference genes in different poplar species. This invention provides important guidance for conducting molecular biology research and biotechnology breeding of poplar. Summary of the Invention

[0007] The purpose of this invention is to provide a universal internal reference gene applicable to the stems of different poplar species, along with its screening method and application, to solve the problems existing in the prior art. This invention screens out three new internal reference genes for poplar stems applicable to different conditions, which has important guiding significance for carrying out molecular biology research and biotechnology breeding of poplar.

[0008] To achieve the above objectives, the present invention provides the following solution:

[0009] This invention provides a universal internal reference gene applicable to the stems of different Populus species, including the CNOT2, VPS35 and CUL4 genes, the nucleotide sequences of which are shown in SEQ ID NO: 1-3.

[0010] The present invention also provides a primer set for amplifying the aforementioned universal internal reference gene, comprising:

[0011] The primer pairs used to amplify the CNOT2 gene have nucleotide sequences as shown in SEQ ID NO: 4-5;

[0012] The primer pairs used to amplify the VPS35 gene have nucleotide sequences as shown in SEQ ID NO: 6-7;

[0013] The primer pairs used to amplify the CUL4 gene have nucleotide sequences as shown in SEQ ID NO: 8-9.

[0014] The present invention also provides a kit for amplifying the universal internal reference gene, comprising the primer set described above.

[0015] This invention also provides a method for screening the universal internal reference gene, comprising the following steps:

[0016] (1) RNA sequencing transcriptome data were constructed from materials of different stem parts, different stem tissues, different developmental stages and different stress treatments of different Populus species. After the gene expression data in the RNA sequencing transcriptome data were normalized, genes with CV value ≤ 0.3 were selected as candidate internal reference genes.

[0017] (2) Select different varieties of materials for treatment, extract RNA, design interspecific universal primers for candidate internal reference genes, detect the expression levels of candidate internal reference genes and existing internal reference genes by qPCR, analyze the expression stability of each internal reference gene under different treatment conditions using the Ref-Finder algorithm, and screen candidate internal reference genes that can be stably expressed under different varieties of materials and different treatment conditions and whose stability is better than that of existing internal reference genes, which are the universal internal reference genes.

[0018] This invention also provides an application of the universal internal reference gene, the primer set, the kit, or the screening method of the universal internal reference gene in the stem gene expression analysis of different Populus species.

[0019] This invention also provides an application of the universal internal reference gene, the primer set, the kit, or the screening method of the universal internal reference gene in molecular-assisted breeding of different Populus species.

[0020] The present invention discloses the following technical effects:

[0021] This invention discloses a method for screening universal reference genes for stems of different poplar species. This method utilizes 298 transcriptome data from 10 experimental groups of different poplar species under various conditions (different stem development stages, different stem tissues, and different stress treatments) to conduct large-scale analysis of gene expression in the transcriptomes, screening for the most stable genes under different conditions as reference genes. This screening method can obtain novel reference genes beyond those previously reported, providing more stable and ideal reference genes for stem gene expression analysis of different poplar species under various conditions. The expression level of the reference genes was verified using qRT-PCR, confirming the expression stability of the new reference genes. This method is also applicable to the screening of universal reference genes for other genera, providing an important reference for the screening and identification of universal reference genes among different species within the same genus.

[0022] Meanwhile, this invention screened out three new internal reference genes for poplar stems suitable for different conditions, which has important guiding significance for carrying out molecular biology research and biotechnology breeding of poplar. Attached Figure Description

[0023] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0024] Figure 1 The screening process is designed to be applicable to the stems of different Populus species as a general reference gene; CV represents the coefficient of variation.

[0025] Figure 2 Comparison of gene expression level normalization methods: A shows the upper and lower quarter bar charts of gene expression level distribution after normalization by Raw Counts (RC) and FPKM, TPM, TMM, and DESeq2; B shows the CV value distribution of relative expression levels of all genes after normalization by RC, FPKM / RPKM, TPM, DEseq2, and TMM; C shows the CV value distribution and average CV value of reported internal reference genes after normalization by RC, FPKM / RPKM, TPM, DEseq2, and TMM.

[0026] Figure 3 To analyze the relative expression levels of stably expressed genes and reported internal reference genes, and to perform KEGG enrichment analysis: A is a Venn diagram showing the number of stably expressed genes and reported internal reference genes; B is a log value distribution diagram showing the average relative expression levels of all genes in poplar, stably expressed genes, and reported internal reference genes; C is a KEGG enrichment analysis of stably expressed genes; D is a KEGG enrichment analysis of reported internal reference genes.

[0027] Figure 4 Stability analysis of expression levels of candidate internal reference genes and reported internal reference genes; box plots show the distribution of relative expression levels of 12 candidate internal reference genes and 30 reported internal reference genes, and line plots show the CV values ​​of relative expression levels of 12 candidate internal reference genes and 30 reported internal reference genes;

[0028] Figure 5 This document describes a primer design method for a universal internal reference gene for stems of different Populus species. A represents the primer design process for this gene. B shows the phylogenetic tree constructed using Potri.005G10600 as an example, detailing its primary transcript sequence and its homologous transcript sequences in four different Populus genomes. C describes the design of primers for a universal internal reference gene based on multiple sequence alignment of Potri.005G10600 and its homologous transcript sequences in four different Populus genomes.

[0029] Figure 6To assess the expression stability of candidate internal reference genes, the expression stability of 12 candidate internal reference genes and 6 reported internal reference genes under different stress treatments (A) and different poplar stems (B) was comprehensively ranked and the CT value distribution of internal reference genes was calculated using Ref-finder.

[0030] Figure 7 To assess the stability of the new internal reference gene and its homologs in Arabidopsis thaliana (A) and rice (B). Detailed Implementation

[0031] Example 1

[0032] This embodiment uses, as follows: Figure 1 The screening process for universal internal reference genes applicable to stems of different Populus species is shown below:

[0033] (1) Acquisition and filtering of transcriptome data

[0034] Literature containing transcriptome data of various poplar stem tissues was reviewed, and corresponding transcriptome sequencing data were obtained from NCBI or EMBL-EBI websites. Sequencing data from stem samples with ≥2 biological repeats were retained. A total of 10 sets of experimental data were obtained, containing 298 RNA-seq transcriptome data of stems as the research object (Table 1). These 10 sets of experiments included different internodes of poplar stems, different stem tissues (phloem, xylem, fiber cell tissue, and ray cell tissue), different developmental stages of vascular tissues, and materials subjected to various abiotic or biotic stress treatments.

[0035] Table 1. Transcriptome data used for screening internal reference genes in poplar trees.

[0036]

[0037]

[0038] a The denominator is the total number of samples in the experiment, and the numerator is the stem-related samples used for internal reference gene screening in this invention.

[0039] In the table, ArrayExpress represents EMBL-EBI ArrayExpress, ENA represents European Nucleotide Archive, GEO represents GEO from NCBI, and SRA represents NCBI sequence reads archive.

[0040] The SRA data downloaded from the NCBI database was converted to FastQ format using the sratoolkit (v2.9.2) software. For single-end sequencing data, default parameters were used; for paired-end sequencing data, the parameter `--split-3` was added. Data downloaded from the EMBL-EBI database was in FastQ format and could be directly used for subsequent analysis. FastQC (v0.10.1) was used to assess the quality of the raw data. Trimmomatic (v0.32) was then used to remove adapters and perform quality filtering on the raw data. The parameters for paired-end sequencing data were set to `TruSeq3-PE-2.fa:2:30:10 LEADING:3 SLIDINGWINDOW:5:20 MINLEN:50`, and the parameters for single-end sequencing data were set to `TruSeq3-SE-2.fa:2:30:10 LEADING:3 SLIDINGWINDOW:5:20 MINLEN:50`. After obtaining clean data through trimming and filtering, the clean reads were aligned to the P. trichocarpa v3.0 genome using STAR (v2.3.0e_r291; settings: --readFilesCommand zcat --quantMode TranscriptomeSAM) software. The total number of reads from all samples and the number of reads aligned to the genome were counted, and the alignment rate was calculated. Samples with an alignment rate of over 70% were retained. Finally, the transcriptome data of 292 samples met the requirements and were used for downstream analysis.

[0041] (2) Comparison of gene expression level homogenization methods

[0042] The featureCounts function in the subread software was used to analyze and compare the generated BAM files, obtaining the number of unhomogenized Raw counts (RC) for each gene in each sample. Four homogenization methods—FPKM / RPKM, TPM, TMM, and DESeq2—were used to analyze the BAM files, obtaining the relative expression levels of all genes in each sample. Bar charts were plotted using the RC and the upper and lower quarters of the homogenized gene expression level distribution to observe the numerical distribution. It was found that the differences in gene expression levels between samples after homogenization (FPKM, TPM, TMM, and DESeq2) were all smaller than those without homogenization (RC). The gene expression level distributions after DESeq2 and TMM homogenization were more similar and less different, showing better results than RPKM / FPKM and TPM. Figure 2 (A)

[0043] To find the optimal normalization method, the coefficient of variation (CV) of the relative expression level of each gene in all samples was calculated. Box plots were used to show the distribution of CV values ​​of the relative expression levels of all genes after normalization by RC, FPKM / RPKM, TPM, DEseq2, and TMM. The box plots show that the median CV value distribution for RC is 1.94. The median CV values ​​for FPKM, TPM, TMM, and DESeq2 are 1.52, 1.51, 1.47, and 1.48, respectively. All four normalization methods reduce the coefficient of variation, and TMM and DESeq2 are more effective than FPKM and TPM. Figure 2 (B)

[0044] In addition, 30 reported internal reference genes from poplar stems (such as...) were collected and analyzed. Figure 4 The median CV and mean CV of the relative expression levels of 30 reported internal reference genes were calculated using unhomogenized RC and four different homogenization methods. Box plots and line plots were used to display the CV distribution and mean CV of the genes, and the advantages and disadvantages of the four homogenization methods were evaluated based on the CV values. The results show that the median CV of the unhomogenized RC was 0.90, and the mean CV was 0.97. The median CV of the expression levels after homogenization using FPKM, TPM, TMM, and DESeq2 were 0.52, 0.52, 0.53, and 0.51, respectively, and the mean CVs were 0.58, 0.56, 0.57, and 0.55, respectively. Figure 2 (C)

[0045] Based on the above analysis results, the DESeq2 and TMM methods have similar effects. The DESeq2 method has been reported to have the smallest CV value for normalizing the expression levels of internal reference genes in 30 poplar trees. Therefore, DESeq2 was selected as the method for normalizing gene expression levels.

[0046] (3) Expression level analysis and functional annotation of stably expressed genes and reported internal reference genes.

[0047] To screen for internal reference genes suitable for different poplar species and experimental treatments, this invention utilized transcriptome data from the aforementioned 292 samples. After normalizing the relative expression levels (RCs) using the DESeq2 method, the mean, standard deviation (SD), and CV of the relative expression levels of each gene were calculated. Genes with a CV ≤ 0.3 in all samples were classified as stably expressed genes. A total of 541 stably expressed genes (CV ≤ 0.3) were screened, including four previously reported internal reference genes (PP2A-2, EIF-A, CDPK, and ATPase). Figure 3(A). Further analysis of the relative expression level distribution of stably expressed genes and 30 reported internal reference genes showed that the log values ​​of the average relative expression levels of stably expressed genes ranged from 5.91 to 13.03, while the log values ​​of the average relative expression levels of reported internal reference genes ranged from 7.17 to 16.09. Figure 3 (B). This indicates that the stable expression level of the genes identified in this study is similar to that of previously reported internal reference genes.

[0048] Next, KEGG enrichment analysis was performed on the stably expressed genes and the reported internal reference genes. The results showed that four of the top five pathways with significant KEGG enrichment (P-value ≤ 0.05) were the same for both the stably expressed genes and the reported internal reference genes: Genetic Information Processing, Brite Hierarchies, and Messenger RNAbiogenesis. Figure 3 (CD). KEGG enrichment analysis results indicate that the stably expressed genes identified by this method are functionally similar to the reported internal reference genes.

[0049] (4) Selection and evaluation of candidate internal reference genes

[0050] Twelve genes with the lowest relative expression levels (CVs) from 292 samples were selected as candidate internal control genes. Box plots were used to display the distribution of relative expression levels of these 12 candidate internal control genes and 30 reported internal control genes, and the gene expression stability of the 12 candidate internal control genes and 30 reported internal control genes in all samples was evaluated based on the CV values. The results showed that the CV values ​​of the candidate internal control genes ranged from 0.16 to 0.20, while the CV values ​​of the reported internal control genes ranged from 0.23 to 1.53, indicating that the candidate internal control genes were more stable in expression than the reported internal control genes in these 292 samples. Figure 4 Meanwhile, the six reported reference genes with the lowest CV values ​​were selected and, together with the 12 candidate reference genes, were subjected to qRT-PCR experiments to verify the expression stability of the candidate reference genes.

[0051] (5) Primer design for qRT-PCR experiments

[0052] The expression stability of 12 candidate internal reference genes and 6 reported internal reference genes in the young and old stems of different poplar species (717) under different stress treatments was verified using qRT-PCR experiments. This experiment involved six different poplar species: *P. adenopoda*, *P. alba*, *P. deltoides*, *P. simonii*, *P. tomentosa hybrid 741*, and 717 hybrid poplar. To design universal primers applicable to different poplar species, this invention outlines a process for developing interspecific universal primers. Figure 5 First, blastn was performed using the primary transcript sequences of 18 reference genes (including 12 candidate reference genes and 6 reported reference genes) from *P. trichocarpa* as indexes to retrieve homologous genes in *P. trichocarpa*, *P. euphratica*, *P. deltoides*, and 717 hybrid poplar. Then, MEGAX software was used to construct phylogenetic trees for the primary transcript sequences of the 18 reference genes and their similar transcript sequences, selecting the gene sequences most homologous to the 18 reference genes. Multiple sequence alignment was performed on the primary transcript sequence of each reference gene and its most homologous gene sequence to obtain the nucleotide sequence identity. Primers were designed using Primer3 for the identity sequences. Taking *Potri.005G10600* as an example, blastn was performed on its primary transcript sequence in four poplar genomes, retrieving a total of 13 homologous transcripts. A phylogenetic tree was constructed for the primary transcript sequence of *Potri.005G10600* and the 13 homologous transcript sequences. Figure 5 In the study (B), four transcripts most homologous to Potri.005G10600 were identified and subjected to multiple sequence alignment. A total of 2623 out of 2965 sites were found to be completely identical. Identical sequences were extracted, and primers were designed using Primer3 to match these sequences. Figure 5 (C). The specificity of primers in five poplar genomes was detected using mfeprimer-3.2.0, and interspecific primers were screened. This invention designed qRT-PCR primers for 18 reference genes using the above method, as follows:

[0053] Table 2. Universal primers for 12 candidate reference genes and 6 reported reference genes in 5 poplar genomes.

[0054]

[0055]

[0056] (6) qRT-PCR validation of candidate internal reference genes

[0057] Populus 717 hybrid seedlings were transplanted from 1 / 2 MS medium into a greenhouse and planted in pots containing a mixed substrate (peat:perlite:vermiculite = 3:2:1). After 5 months of cultivation, plants with a height of 100-110 cm were selected and subjected to various abiotic stress treatments. For salt stress treatment, the Populus 717 hybrid plants were irrigated with a 150 mM NaCl solution every 24 hours for 2 days (D2), 4 days (D4), and 6 days (D6). For drought stress treatment, simulating a natural soil drying process, watering was stopped for 5 days (D5), 10 days (D10), and 15 days (D15) to obtain mild, moderate, and severe drought stress treatments. Plants in the control group (D0) were watered periodically based on their evaporation rate. Soil relative moisture content was measured using a Field Scout™ TDR 300 soil moisture meter. During shading stress treatment, plants were shaded using two layers of covering (upper layer of black nylon film, lower layer of white plastic film), with a shading rate of 70-80%. Shading stress was applied at time points D5, D10, and D15. Light intensity at each time point was measured using a Lux / Fc photometer (Auto Ranging TM-205). Physiological indicators such as net photosynthetic rate (Pn), stomatal conductance (gs), intercellular CO2 concentration (Ci), and transpiration rate (Tr) were measured using a portable photosynthesis measurement system (LICOR 6400XT, LI-CORInc., Lincoln, NE, USA). Gravity stress was applied to 717 hybrid poplar by bending the plants, and the stressor and contralateral trees were studied at time points D2 and D14. After various stress treatments, samples were taken from the 9th internode of each plant, flash-frozen in liquid nitrogen, and stored at –80°C for use as experimental materials for qRT-PCR. All stress treatments included three biological replicates.

[0058] Meanwhile, young and mature stems of six different poplar species or cultivars were collected from the campus of Huazhong Agricultural University as qRT-PCR experimental verification materials for candidate internal reference genes. All samples contained three biological replicates.

[0059] Total RNA was extracted from each sample using the 2×CTAB method and analyzed using NanoDrop. TM The purity and concentration of RNA were analyzed using PrimeScript (ThermoScientific, USA) in 2000. TM cDNA was synthesized using an RT kit (TaKaRa, Dalian, China). The cDNA was diluted 20-fold with ultrapure water and then used for qRT-PCR verification of the candidate internal reference gene.

[0060] (7) Evaluation of expression stability of candidate internal reference genes

[0061] To evaluate the expression stability of 12 candidate internal reference genes and 6 reported internal reference genes, this invention, based on qRT-PCR experimental results, employs the Ref-Finder algorithm, integrating four commonly used expression stability evaluation programs: delta-Ct, BestKeeper, Normfinder, and geNorm. A comprehensive ranking is generated by calculating the geometric mean (geomean). Figure 6 (AB). Analysis results show that under all stress conditions, Potri.001G349400 (CNOT2), Potri.005G110600 (VPS35), Potri.011G084400 (CUL4), and Potri.008G111700 ranked highest overall and had the best stability. Figure 6 (A) and the Ct values ​​of these four genes in qRT-PCR are also very concentrated. Figure 6 (A). The expression stability of 12 candidate reference genes and 6 reported reference genes in the young and mature stems of different poplar species was analyzed using RefFinder. The results showed that CNOT2, CUL4, VPS35, and Potri.002G157500 had the highest overall ranking in the stems of different poplar species. Figure 6 In the study, it was observed that the Ct values ​​of these four genes in qRT-PCR were also very concentrated. Figure 6 (B)

[0062] Based on the above experimental results, the expression stability of CNOT2, VPS35, and CUL4 is superior to other candidate reference genes and reported reference genes, and they can be used as new reference genes for studies related to Populus stems.

[0063] To verify the applicability of the internal reference genes, this invention compared the expression stability of three novel internal reference genes and six previously reported internal reference genes in the dicotyledonous plant Arabidopsis thaliana and the monocotyledonous plant rice. Using the protein amino acid sequences of nine genes in *P. trichocarpa* v3.0 as an index, homologous genes in Arabidopsis thaliana and rice were retrieved from the Phytozome website using blastp. RNA-seq expression data of these genes related to stems were retrieved from The BAR and other Data Analysis Tools for Plant Biology (http: / / bar.utoronto.ca / ). The CV values ​​of the relative expression levels of these nine genes were calculated. The expression stability of the internal reference genes was evaluated based on the distribution of relative expression levels and the CV values ​​of relative expression levels in different samples. The results showed that the CV values ​​of the expression levels of the nine genes in Arabidopsis thaliana ranged from 0.09 to 0.25, all less than 0.3. The expression variation coefficients of the novel internal reference genes CUL4, VPS35, and CNOT2 were 0.09, 0.15, and 0.17, respectively. Figure 7 (A) In rice, six genes had expression variation coefficients less than 0.3, including two new internal reference genes, VPS35 and CNOT2. Another new internal reference gene, CUL4, had an expression variation coefficient of 0.31, slightly higher than 0.3. Figure 7 (B). Therefore, the universal internal reference genes for stems of different Populus species identified by this method are also qualified internal reference genes in Arabidopsis thaliana and rice stems.

[0064] The three novel internal reference genes and their primers that are universally applicable in the stems of different Populus species obtained by screening in this invention are as follows:

[0065] CNOT2 (SEQ ID NO: 1):

[0066] TTAGGTATTTTGTGCGGACCGTTCATTTGGAAGATAACAAAAAAGAAAAAAAAAGAAGCTTCCTTTTATTTATTCGTCCACGATTGTTCGATATCGAACAATAGATCTATCTCCATACATTTCGATAATTGTATCCGCTGATTTCAACTCTTCACAGCTATCATCGAATTTTTGTAGGGCACTTCCATCGTTCGATCTATTTTTCTCCATCTTCACGTTGCTAAGATCATATTATATTGACAAAAGAAAGCTCTCAAATCGATTGCTATAGGTA ATTCCGTGTTAAACCTAGGTTTCATTTCTTTTTTTAAAAAATAAAATTAATTTGGGATTTTTTTTATTCAGGTTGTAAGAGCAAAAATCATCTCTGAAAGGACTTCTCGCATGATCTTTGACCATTTATGAAATGTCGGCGTTACTTAATGTATTCTTCGCTCTCTCTTTTTTTTTTTAATTATTAATCTGAAGAATAGTTACTGGTTTCTCAATTCTTGAAAGATAAATATTATATGCTTCAATTGTTCTTTTGTGCAAAAAGTCTTAATA

[0067] CTCACTGGATTGCAGTCTGGTCTAAATGGATCAGCTTCAAATCTTCCGGACAACACGGC

[0068] GCGATCTTTTGCTACATCCTTCTCTGGCCAGTCCGGTGCGGCAGCCTCTCTCCTGTTTTTCAT

[0069] CACAGTGGTGGTTAGATTTTGCCTGAGATTCACTCGTGTCCTCGTCTTCTCCTGCTTCTT

[0070] GTATCAGTTTTCCTTGTGATTCTAAATAAGGTTATCTTATTGCGCGCAGGAACTATTCAAG

[0071] GGCTGCATAATATTCATGGGAGCTTTAATGTACCCAACATGCCTGGAACTTTTGCTTCAA

[0072] GAAACTCTACAATCAATAACATTCCTTCAGGTGGGGTTCAACAACCTACTGGAAGCCTC

[0073] TCCAGTGGACGGTTTGCGTCCAATAATCTTCCAGTTGGTCTCTCTCAGGTATGTAATTTGC

[0074] TTTTATTCTAGTAACTGTATCCTGTTTTTTTTTACAGTAGTAAACTTCTTGAATGTTTTCCC

[0075] TGTGCAGCTGTCTCATGGCAGTTCCCATGGACATTCTGGGGTTACAAATAGAGGAGGTTT

[0076] AAGTGTTGTAGGAAATCCAGGATATGGTAGCAACACCAATGGAATTGGTGGTTCTATACC

[0077] TGGTATTCTCCCAACCTCTGCTGGAATAGGTAACCGGAATGCTGTTCCTGGATTGGGGGT

[0078] TTCCCAAATTTTGGGCAATACAGGTCCTAGGATTACGAGTTCTGGAGGAAACATGGTTG

[0079] GTGGTGGGAACATTGGGAGAAGCTTAAGCTCGGGTGGAGGACTATCTGTCCCTGGTCTT

[0080] GCATCTCGTTTGAATTTAACTGCAAATAGCGGATCTGGCAGCTTAGGCATGCAAGGACA

[0081] AAATAGATTAATGACTGGTGTGCTTCCACAAGGTTTGTGTGCAAGGAAGAAACAAATCA

[0082] ATGCTTTATTTTCTTGACCATACAATTTACTGGTGCCTTGGTTTGAATGTGATAAAATATCT

[0083] TTGCCACTGGCTTTGCTAGCTTGGAAATTGTGTTGATGCTCGTTTTGAATTTTATTTTTGC

[0084] ATGTTGAAAGCTTGCTAGAATTTCTTGTATTGTTCTTGTCTGTAATTTCTTATAGCTGACCC

[0085] CTACTAGTCTGGGATTAAGGCCTTTTAAAGTGCACTGTTGTTTTCACTTGAAAAGAATGT

[0086] CATTATCTTTTAGATTGTATGGAAGATTCAAGCTTGTGAGTCTTTCTGGGTGTTAAAAAAC

[0087] AAAGGTGATTCAGGTGGATGCTTAGTTTTATATGATTCACCCACTTGGTCTTATATCCTGA

[0088] ACAATTAATTTAACTGTTCGCTGCCCTATTAGTTCTTATGTTCACAGATTGTTTAGATTTTC

[0089] AAATGTTAATTTCCAAGTTTAGCTATATTTGCTTGTGTAAATGACATTTTGTGGATTCAGG

[0090] AAATCCACAGGTGATTCCTATGTTAGGAAACTCCTACCCCACTGCCATTGGTCCTCTTTC

[0091] CCAAAGCCATGTTCAAGGTGTGAACAATCTCAGCTCTATGGGAATGTTGAATGATGTGAT

[0092] CTCCAATGACAGTTCCCCCTTTCGACATTAACAATGATTTCCCTCAGTTGACAAGTCGTCC

[0093] TAGTTCTGCTGGAGGGCCTCAAGGTCAATTGGGTAATTAAAATATGCTTTTGCTATTTGTT

[0094] TATGGTTATTTCTGTCTCTGCTTTCACCTGTATTTGGTGATAAAATACAATGAAACTACTT

[0095] GCAGGTTCACTACGAAAACCTGGTCTTGGAGTTAGTCCCATTGTTCAACAAAGCCAAGA

[0096] GTTCAGCATTCAGAATGAAGATTTTCCAGCTTTACCAGGATTTAAAGGTTCCAAACTCAT

[0097] TCTTGCAAGCTCCTTACTTTCTGTATAATGCTAACACACTGCCTCCTTGGTTGGTGGGAAT

[0098] AGAAGCTCATCGGTCCTGTAATTTCCCATCTTCACGTGTTTGCTCATTGACGTGATGCTG

[0099] CGTTTTAATCAGTAGATGATGTCCCTGTATAAGTTACAATAAAGATTTTCCTAATGCATGC

[0100] TTAAGCAATATTTTGTGATTGGATCTATAACATTTTTAATGTCGTGTCTTCTGGACTTGGCT

[0101] GTAGCTGTGTTTGTGATTTTGCCCCTTGCCAGAACAAAAACCTACATCTGCATAGTTGTT

[0102] ATCCTAATTTTTCTCCAATCAGTAATGCATTTTTCACACGTTGACTATGATATTGGATTTGA

[0103] TTCAGGTGGTAATGCTGATTACACTATGGATTTGCATCAGAAAGAACAATTGCACGACAA

[0104] TACCTTGTCAATGATGAATCTCAGCACTTCTCTGTGAGCCTCTATGTGAAATGGAAATTT

[0105] AGCAATAGCAAATGTTATCTGTTTGTACTTTCTGACACCTCATTCTGCACTCTGCAGATA

[0106] GGGAGATCTGCTGGGGTTCAACTTAGGAGAGGCTTTATTCATCCTATCGTCCTCAGCAGCAA

[0107] CAGCAACATGCCCCAGCTGTCAGTAGTGGCGTCTCTTTTGCATCTGTAAAACAATCAAGAT

[0108] CTTCATGGTTCAGAACTATTTCCGTCTTCACATTCAGCCTATCACCCACAGGTGTGGGAAG

[0109] TTTAGTCCTGTTAATAGTTTTTTGCATTGCCATTTAGAGGGTCTCCATTGCCTCAAGTGAA

[0110] TGTGGTTTTAATATCTAATGAAAGTGGTCAATTTCAAGTCCTTGCGTGGTTACAGTACATT

[0111] AAAAAAAGGGTAACAAAAAAATAGCCCCTCACGAATAAGTTTGTTATTAATGTTGCC

[0112] CTGTACCTATTGGATCTGTCAAGTTTACCCTTATTGTTACCTTGAATTTCCAATTCAACCCT

[0113] TCTGTCCACTCTTCCATCCAAATCAGTTAATATAGATCCATTAAATACCATGCGGCAACTCAT

[0114] TAAGATTTATTTACTTTAGAATTTATTATGAGTGAAATAAACAAAACTAATAGTAAAAGCA

[0115] TTGAAATAATTTGAAACCCATGAAATTGAATTTGTGTACTTTTGAGTTTAAAATGGCATTGA

[0116] TTTTTCCAAAATTTTTAGTTTAGATTGAATTTCATTGTCATTAATTTTGTTATTTTTAAA

[0117] CAATAAATATGATTGTTCTTTAATTTATGGAGTTGCCACGTGGATACTTAACGTATCCTCGT

[0118] AACAATTGGGATGGAGAATTAACTGATGGGTATAATTTGAAAACAACTGGTAATGTTAAG

[0119] AATTAAATTGATAGATATCATGGTGAAGGGCAACACTGACAACATTAACCCAGAAGAAA

[0120] ATTTTCTTGGATTCAATAATTTGCTACTGATGGTTACCACACCAACTGTTTTCATAACTTC

[0121] ATGTTGGGGTGGTACAATAGCTATCATTTTTTTTACTTTATCTATGGTTATTCATTTTTCCT

[0122] CTTAAGAAATCTTTTAAACTATCCTGTCATCTGTGGTTTAGACCAGTGGACCACCAGGAA

[0123] TTGGGCTGAGACCTTTAAATTCTCCGAATACGGTATCTGGTGTTGGATCATATGACCAGC

[0124] TCATCCAGCAGTATCAACACCAGAACCAGCCCCAGTTTCGACTACAACAAATGTCGACT

[0125] GTCAATCAACCATTTAGATCAGGGCATAAAGTCCATGCAGACAGCACAATCTGCACC

[0126] TGATCCATTTGGGTTACTTGGCTTGTTAAGTGTTATAAGGATGAGTGATCCTGATCTGACC

[0127] TCCCTGGCACTTGGAATTGATTTAACAACTCTTGGATTGAATTTGAATTCAGCTGAGAGT

[0128] CTTCACAAGACTTTTGGCTCCCCATGGTCTGACGAGCCAGCAAAGGGTGATCCAGAGTT

[0129] CAATGTTCCAAAGTGTTATTATGCTAAGCCACCACCTCCACTGGATGTGAGTTTGCTGTT

[0130] GTCCTTTTTCTATAATTTTGTTATTTAATCCTAACCTCTTATTTCCATAATTGACTTTTCTTT

[0131] TGGGTCTTGGTTGCAGCATAATTACTTTTCAAAGCTCTGGACAGAAACGTTGCTCTATGC

[0132] CTTTTACAGGTGCAGTTGTTTAGTGGATTTTTGCTGTTTTCTTTCCTTATGTTTCAAGTTTTC

[0133] ACTAATGCCTTTCTTTATCCTGTTGCTTTTCAGCATGCCAAAAGATGAAGCTCAATTACAT

[0134] GCCGCAAACATACTGTAAGCTCTGATACTGATGAATTGAATGTTGTAGTTTTGTATCCATG

[0135] TAACCTCCACTACCTGCCCATTTCCTTACCTTTCCCGCCTTTTTGAGTCCGTCTTATGCTC

[0136] GGGGAAAAAAGACCATTCAGGATTTTGAATACCTGCAATTTTGCTAATTAAAAAATATGAC

[0137] TAATGGTGGGATATTCTCTGTTGGCAGTTATGAAAGAGGCTGGTTATACCACAAGGAGCA

[0138] GCGGCGTTGGTTAAAAAGAGTCCCCAACACAGAGCCACTTGTTAAAACGAGCGCATATG

[0139] AGAGAGGGTCTTACCATTGTTTTGAACCGAACACATTTGAGATAACACTCAAGGTCTTG

[0140] ATTTGTTTGTAATTAGTTCGTATGTTTGCAATCTTTTCTTGCTCTACGAATGCAGGCTTGAT

[0141] TGATTTCTGATCCCCATTGGTAAAATCGATGTTGATGCAGGAAAATTTCGTTCTCCATTAT

[0142] GAGATGGTGGAAAAGAGACCGGGTCTGCCTCAACATTAACCAGTGTTCTATTTTGAAAT

[0143] GTAAACACGCATCATTGATTAGAACAAAGGAGGTCAATTTCCAGTGTTAGTGCCTGCTTG

[0144] AAATTTGGTTATTTTCAGCAATTGTATAGCCATCATGTTGCGCAGGGATTTTTCATTTTAA

[0145] CCAACAACTCTATATCTTCTCAACATGTGTTCACAGCGATTGTTGATAATTCTCGTAAAAC

[0146] TTGATGCATTCATTCCTACCATGGACGAGGGATCAAATTTCATCTGTAATGCTGTGTGGAC

[0147] AACTAAACGTTAAATTGTTTTTGGTCCAATTTTGATTTTATTGGACGTTTTGAAGTTCTTG

[0148] CCGCCACCATACATGGCAGGCTTTTATGCTGCCGTGTGCTAGGGGCAGCATTACTTTTATTCAAATATTAAACGCTGCAAGCCTTTCAA;

[0149] Forward:GGTCTGACGAGCCAGCAAAGGGT(SEQ ID NO:4),

[0150] Reverse:CGCCGCTGCTCCTTGTGGT(SEQ ID NO:5)。

[0151] VPS35(SEQ ID NO:2):

[0152]

[0153] AAATTATGCAATTCCTTTAAGTCTTTAACAACTAAATTGATATCTTTAGATGAAGACCATT

[0154] TGTTCTGTCTGTGCTGTTTCTTTAGTTTGCGTGTCTGATATTTTTGAAGTAGAAAATGTAT

[0155] TTAGTAAGTTTGAACATGAAGGTAGCAGATATTTTGCAAGTGAGAACTTAGAAGACTGA

[0156] AAATGTTTACTGAAAATGACAATGAAGCTTCTCAATTGTAACTTCATAATTTCTCTTTTTG

[0157] TGTCTGTGTGCTTATTGGTTTCTGCTAGCAATGAGTATCTTTGATCATATCAGATCGGTCCTC

[0158] TTGTTAATGAACTCTGCCAAGCTATTTGGAGTCTGCTGCAAGGATACTTTTTTTTCATTTC

[0159] TGCTCTCACTATAGAGATGTCAGTCAGTCACGTAAAATTATCAGTGTTTGTGTATGCATTTT

[0160] TTTGAGCTTTACTGCAATATTTTGTCCTTCCAGGTATCTCCTATGTACTGTAGGATCTGTAT

[0161] ACATTAAATCTAAAGAAGCTCCAGCAAAAAGATGTTCTTAAAGATCTTGTTGAAATGTGTC

[0162] GCGGCATTCAGCATCCTGTACGTGGCCTCTTCTTAAGGAGTTACCTTTCTCAAGTCAGTA

[0163] GGGATAAATTACCTGATATCGGTTCAGAGTATGAAGGGTAAGGATATGAGATGATCGTTAT

[0164] GGGTTCCATTTAATTTTAGGAGAAAGGCATTTATTTATGTGGTTATAGAGAGCAAATTTGG

[0165] TGGTCTGGAGACCATTGTGGCTGGTTGGGCTTGACTTTGATCAGGTCATAGCTAATACTT

[0166] GAAAGTGGATCTGCCTATCTGAGGTGACGGCTGGAGCCAGGGTGACCAGATCCTCAATG

[0167] AACTATGCATCCATCTTTACTTGCATTGAGATTATACAAAATGAATAGCTATATAAGTCTTT

[0168] TGTTTGCTCTTATAATGGTGGCATCCAAACACTTTAATTCAAGTTACTGACCATAAGCTGA

[0169] TGGAAAGTATTCTTGTCAGTTTTGTTGTTTCCCCATGATCCTGTTGGTGGATTGGTTTTGG

[0170] AACTGACTAAATGAGTTGCTTCCTGAACCCCTGCAGAGATGCTGACACGGTTGTGGATG

[0171] CTGTGGAATTTGTTCTGCAAAATTTCACTGAGATGAACAAGCTATGGGTGCGAATGCAA

[0172] CATCAGGTTGGTTGAAATATATGTGACTACCTGCTCTCATGTTCAGCATGCATGTGCAATG

[0173] CTTGCATGTCATAAAGGTAAAATGTATCATGAGGGCATGATTTCTGGTCATGCAGGTCTTA

[0174] TAGTGCTTATGAATCATTCATACTCTTTGCTGATCATGAGTTGAGGCTTGGTATCGGGCTT

[0175] TCTGGTCTGCAGGGACCTGCCCGGGAAGGAGAAGCGGGAGAAAGAAAGGAGCGAG

[0176] CTGCGTGATCTTGTAATGCCCGTGACCTGTAAATGGTTAATTTCACTGCAATACAACTTTG

[0177] TGAAGTATGTGGTTGCAGTTTTAAAAGCTTAGCATTTGTTCCCCTCATATGTTATTAGGT

[0178] TGGCAAGAACCTGCATGTCCTCAGCCAGATAGAGGGTGTTGACCTTGACATGTACAAAG

[0179] ATACTGTGCTTCCCAGAGTTCTTGAACAGGCCTGACCTTTACACTTTGATAAAATATTGTA

[0180] TTTTGAGCTCGTGGATGGGATGCATGCTTGCCAACTATCCCAAACTGAACTCTGTTTTTC

[0181] AATTGTTTTGATAGGTTGTCAATTGTAAAGATGAAATCGCTCAGTTCTATTCTGATGGATTG

[0182] CATAATTCAAGTCTTCCCTGATGAATATCATTTGCAAACTCTTGAGATATTGTTGGGTGCT

[0183] TGCCCCCAACTTCAGGTGTGTAATTTTGTACTCATTGTTTCTATTTGACATGGTCACATGT

[0184] TAGCTTGTTATTCTCCCTCCTTTGATATATTTGCTTAAATGCAACGATTAAACTGCTTCTTTG

[0185] TTTCCAACTTGTGTTTCTCAGCCATCTGTTGACATCAAGACAGTGTTATCTAGATTGATGG

[0186] AGAGGCTATCAAATTACGCTGCTTCAAGCGCAGAAGTTTTACCTGAATTCTTGCAAGTAG

[0187] AAGCCTTCTCCAAATTGAACAATGCCATAGGAAAGGTAAATCTAGTCTACCAGCCCTTTT

[0188] AGATTGCTAGACCAGAAAAGGAGCAGAATTTGGTAACTTCATTTTTTGAGAAGAGTACA

[0189] GGATTTTATGATGCTCTGTCTCTGTGCTTATCATTGTTGAAGTGCTGTTTTCCTGTTAAAA

[0190] GTTTCCCATTTCGAAATCTCTACAAATTTCAGGAGATTTTGATGTTGCCTTTCAAAATGAC

[0191] TATTCTTACTGATATTTGTTTTGACTCCATATGTTAAGTTACAGTGATTAGTCTACATAGCG

[0192] TATGCTAAAACAATTGAAATATAGTAATACAAATGTGTTGATGCAGGTGATAGAAGCACA

[0193] AGTTGATATGCCAATTTTTGGAGCTGTAACTCTATATTCATCTCTTCTTACATTTACACTCC

[0194] ATGTTCACCCTGACCGGCTGGATTATGCTGATCAAGTGCTGGTATATATGACTCCCTAAAA

[0195] TGCTTCTACATTGCAATTTACATCATGGTTTTGTAAAATTTATTTTATCATATACCAATTAGA

[0196] GATATAACCACTTAACATTTCTGTTCTGTCCTCTATTGTTTTTCTGGTTATGCCTTCAGAAA

[0197] GTAGTTAAAGATGCATTGAACTAACTATACACGCGCTATGTAACATCATATAATGGGGCTT

[0198] GCTTTCTAACTGGGATGAATTTTTTACTTGACCCAAGAGAAGGCAGGATTTGTTTTCCTA

[0199] GTAATTTGAAAAGAGAACTGTCAAGCACTGTAAGAAATTAAATTTGACAGGGAAAATCA

[0200] TGACTGGTTGGGACACAAATTTTTATGCATGAAAGGTTTCTAGAATTTATACTCTGCTGTC

[0201] CTCTTTGGGCAGTGTTCAGCAGTCATTTTGGCTTGCAGAAATAGTCAATGAGTAATTTCA

[0202] TCAAAGAAATTAAGAAAGATCACGTGCATTGAAATTCCAATTATGCGAAACAGGTTGAT

[0203] TCTCTTAAAACTAATTTATTAAAACAAGAAACTATTTATATTATTTTGTTCCGCTGTATATTT

[0204] TAACAGGTGAGCTGATTCTTTTGTTTGTTATTCAGGGAGCATGTGTTAAGAAACTATCCA

[0205] GCAAAGGAAAGCTTAACGACAGCAAAGCCACAACAACAAATTGTTGCTCTTTTGAGTGC

[0206] TCCATTAGAGAAATATATATGATATTGTCACTGCATTGAAGCTTTCAAACTATCCTCGTGTA

[0207] ATGGAATACCTTGATATTGAGACAAATAAAATTATGGCAACTGTTATAATTCAAAGTATTA

[0208] TGAAAAATAACACACGCATCTCTACTGTGACAAGGTATGTTTCTGTCCCTTGTGCATCC

[0209] TAATCTTTCTAACATGCTCTGAATACTCAATCTTAGTTTAATTTTATTCTGTAGGTTGAGGC

[0210] GTTATTTGAATTAATGACAGGGCTTATCAAGGATCTGGATGGGGCTGAAGAAGAGGTTAT

[0211] TTGAAAATTACTTCACTTTTCATGTTATGAAATTTGTGCTGCAGAAGTTTGATTTTTCTTAA

[0212] AACTTCTAATGCTGATAACCACATATGCTATGGTTGTTTCTTATTGCCATCCAGCTAACAG

[0213] TATTTACCTGTTCTCCTCTAATGTGCTCATGAAACTAAGCCTTTGAATTGTGTAATGTGATT

[0214] ATTGTTTTGTTCCTTTATCTTTAGGTTGATGAAGATGATTTCAAAGAGGAGCAGAATTCC

[0215] GTTGCACGTCTTATTCAGATGCTGTACAATGACGATCAAGAGGAAATGTTTCAGGTACAT

[0216] GTTCGTTTCAAAATCTTCATGTCAGCTTTTTTCAAGAGTTAAATGGCTAGCACCCATTTTA

[0217] TTTTACTGAAGCAAATTGTGGGTGGTGATTAATCAGTAGAACGATTTCCGCCTAATTTTGT

[0218] ATTTTGGTTTTGAACTTTTCTTATATATTATATCCACCCTAAATTGCAGATTCATATGTACGGT

[0219] GAAGAAACATATCATGACAGGAGGACCAAAGCGCTTACCCTTCACAGTTCCCCCACTTG

[0220] TTTTTTTGTCTCTCAAGGTTTGCTTTTGCCCAATGCTAACAACCTTGAAGTTGGCAAAAT

[0221] TGCTGCTGCACATTCTGGAATGAGAATGTCATTGTTCATCAGATTTGGCATCTGACATGA

[0222] ATAATTGCTGGTCACATCACGTGAATCATGCTTTAATCTCTTTTCTAGTATCCATAATTTGA

[0223] TGGCCGCCCTATCTTTTTCTACGAATGCCAATTTGGATTCCTAACTTATTCTCAGCCTTTT

[0224] GTTTGTGGTGTACAGTTGGTAAGGAGACTTCAAGGCAGCAGCCAAGATCAGGAGGAAA

[0225] ACCCTTTTGGAGACGATTCATCAACTTCACCTAAGAAAATTTTCCAGCTCTTGAATCAGG

[0226] TAGCGCTTCATTGAAAGTTGTCTATCATGTACATAGATTTGGTTAAATGATCATTCATTAG

[0227] AATAGCTGACGATGTAATCCATTCTCTTACAGACAATTGAGGCTCTGTCAATTGTTCCAG

[0228] CACCTGAATTGGCATTACGATTGTACTTGCAGTGTGCTGAGGTACATGAACTTGGCACTG

[0229] CCGTTTACTTGGTATTTTAATTACTCTCAAGGACCATTTGATGAAGCTGCCTCTCTTACTT

[0230] ATTACTTTTGATTTCTAATCGAGCAGGCTGCCAATGACTGTGATCTAGAGCCTGTTGCATA

[0231] TGAATTTTTCACCCAAGCATATATTCTATACGAGGAAGAAGTCTCAGTGAGTTGATTCGA

[0232] TTCACATCTATTTCAACCTTTATATTGCTTTATTTAAAGTTGCAAAATCAGTCATGTTTTTT

[0233] CTCGTGCATATTTGCTGCAACAGGATTCAAAAGCACAGGTGACGGCACTGCATTTAATAG

[0234] TAGGCACCCTTCAGAGGATGCATGTTTTTGGTGTAGAGAATAGGGATACTTTAACCCACA

[0235] AGGCCACGGGGGTAAATCCTATAGCATTGTTTTGCTATAATTAAAGTTTTTCAAATCACAT

[0236] TTTTGAAGCTATTTGTGTGAAGATGCTGATATGATACCTTGCTTGAGCAGTATTCGGCTAA

[0237] GCTTTTAAAGAAGCCTGATCAGTGTAGAGCGGTTTATGGGTGTGCACATCTATTCTGGGT

[0238] TGACGATCAGGATAACATGAAAGATGGAGAGAGGTGAGTGCCATGCTTTTAGTATTGGT

[0239] AAAGCCCAATAGTGATTAAGGGGACAGCAATATTCTATTATGTATCTTGTCATGATGTCGC

[0240] CTTGGACAGGCTGGTTGCATGCGATTGTAGTATACAGTAGGAGAGGAAGTATTATGGCTG

[0241] TATTTAACTTGACTAATTGTGGGAGTAGTGGGCTGCTTCTGAGTGCATTTTAAATCTTTTT

[0242] CCTAATGGCTTATGATTAATTTTCTCTCTATCTACTTCTTTTGAACCAGGGTTCTGATTTGC

[0243] CTGAAGCGTGCTTTGCGAATTGCAAATGCTGCTCAACAAATGTCCAATGCGGCGCGGGG

[0244] TAACACTGGATCAGTGTTGCTCTTTGTTGAGATTCTGAACAAGTAATTCTTCTACTCCAAT

[0245] GAACTCATTTAATTTGCTTCTCTGTATTTTATCTTATGATCTTTGATAATGGAAATGCCAAC

[0246] CTTCCTTCTACATGAAGGTATCTTTACTTCTACGAGAAGGGAAACCCACAAATCACAGTG

[0247] GCTGCAATCCAGAGCCTGATTGAATTGATTACAACTGAGATGCAAAGTGACAACAGTCC

[0248] ACCAGATCCTGCTGCTGATGCATTCTTAGCCAGCACACTTAGATACCTTCAGTTCCAGAA

[0249] ACAGAAAGGTGGTGCAATTAGTGAAAAATACGAGGCCATCAAGGTGTGAAACAATGAC

[0250] CGGATGCCACGAACAACTTTCCATGTTATTGGTTTGAACGTGACTGCTGTTGATATTTTT

[0251] GTGGAGTGAGCTGCGTATCTGGCATTCCTGGTGGTCTGAGGAGCTTGATGCGTCTAACA

[0252] CCAGTTCAATGTTGACACCATGTGTGCTTATAAGGTCTATTATGTTGCATAACCTGCTGAT

[0253] ATTTATTGATTGTCAATGGAATTGACTCTTTAGCACAAAGTCAACCCTGTCAATTTTTTTC

[0254] AGGTTTTGGTGAATGACACTGTCGTTATCTTTACAGAGCTGCATGACCTGTCCGTTTAGT

[0255] TACATTTTTGCTAATAAGCATTCCATGATTAAGAACGCAGATAGTAAACATCCTTGGACCT

[0256] CTTTCTGGATATTGTTTGATTTCATTGAGAATAAGATTGGGAACGCATGCCTGATTATAGA

[0257] CCCCCCCCCCCCAAAAAAAAAAAAAAAAAGAAAAAAAAGTGTAGCAGACAGTTTTGAGTTCTAAAAGTTTCATTTGCTTTCCACATCCGAGCTACAGCCTATTTTC;

[0258] Forward:AAGGCCACGGGGTATTCGGC(SEQ ID NO:6);

[0259] Reverse:CGCAAAGCACGCTTCAGGCA(SEQ ID NO:7)。

[0260] CUL4(SEQ ID NO:3):

[0261]

[0262] TTCTGTCAATGGGTTTCACATCTATCCTGACAACTTCTGTGTCCTGTATGTGTATTTGTTCT

[0263] TTAAAATTTCTTTCAAAACTATTTCTACTAATAACATAGGTGCTAATAAGAGTTGAGTTTGA

[0264] TGAACTGGTATCAATACTTGACTGGAACACAGACTACTTGCAAGTTGTAACATGAAGAC

[0265] ATGCTTTCATTCTCCAATTTGATTATTAAACATTTAGTGACAGAATGAATTGCCAATAAAT

[0266] GAAAACTAAATATCTGCAAACCTTGGAAGTAAATCGTTCCACTCCCTTTTCCCACAGATTG

[0267] GAAAAAAGGAAACTTGTTTCTAGTATATAGGAGATCAATTTATGGAGTGGTCACAAATCTT

[0268] GCAATTGAGAACTTTGTGACATTAGATTATTGGAGTATTTTGAAGTATTATAGTTTACTTC

[0269] TTGGACACTTCATAGAGATCCTTTTTCTGTGATTGCAGATTAGGTGAATCAGCTGATAGAT

[0270] CTCTCCTTGACCATCTCTTGAAGATGTTCACTTCACTAGGAATTTATGCAGAAAGTTTTG

[0271] AAAGACCTTTCCTTGAGTGCACATCTGAATTCTATGCTGCTGAAGGCATGAAATACATGC

[0272] AGCAATCGGATGTTCCAGATTACTTGAAGCACGTGGAGGTGCCTTTTGTTTTTTCCTCTGA

[0273] TATTATCTGGGATTAAAGTGGAATATGAAAATCACTTTTGCTTTTATCTGCAGCTTTTTTTTT

[0274] TAGTTCTTTTACTTAATTTGTTTGCCCTTGGAACATTTGGTGGGTTACATATTCCTGCAG

[0275] TCAAGATTGAATGAAGAACAAGATCGATGTAATATTTACATTGATGCAAGCACTAAAAAG

[0276] CCACTAATAGCAACTGCAGAAACGCAGCTACTTGAACGCCATATATCCGCGATTCTTGAT

[0277] AAGGTGCAAATGCCCTTTAGTTATACATAGCTTCCTTCAAAAGTGCAATCTATTTTCATTG

[0278] CTTGAATAATCATTTGTTTCTCCTTCTGTCCAGGGGTTCATGATGCTGATGGATGGACAT

[0279] CGGATTAAGGACCTTCAGACAATGTACTCATTGTTTTTAAGGGTCAATGCCCTTGAGTCA

[0280] TTAAGGCAGGCCCTTAGCATGTACATCAGAAGAACCGGGCAGGGCATTGTCATGGATGA

[0281] AGAGAAGGACAAAGATATGGTTTCCTCCCTGTTAGAATTTAAGGCTTCTCTTGACTCAAT

[0282] ATGGGAAGAAAGCTTCTCCAAGAATGAAGGATTCTGCATCACCATAAAGGATGCATTTG

[0283] AGCATCTAATTAATCTTCGCCAGGTTAGTCTATTGCTTTGTTGGTCCGATCTTAATTGGTT

[0284] GCAAAATTTTATCATATTCAACAAGCTTATCACCTGTGTGCTGCATGAGATTACTACAAAA

[0285] TGTTTGCAATAGCTATAAATGTTCTTGAAAATTTTCTAAAAGAATAAGAGAAAAAAATGA

[0286] TACCTTTTCACATACAATTTACAGTAAATTCTGATAATCAAACCCCACAAAATGTTGAGTT

[0287] CAAATCTTTACAAGTTTTCACCATTGTCATGTTGAAAGAAAATGGAAAGACAAGTAAAA

[0288] TAAAAGGTAAATGAGGAGTTAGGAAAGTAAACAACAATCAAATGAACAGCGACACTTA

[0289] CCTTTAGAAATACTAAAGTGGAGATAAAAATATGAATGAAATTTTCCAGCAAATGATAG

[0290] GTATTTTCAACCTTTTGCTCCATACTTATGTCTACTGATTATGCATGGATATATATTTTTTTT

[0291] TGGTTAAAAAAGTAATTAGTGGTACCTAAAAAGTTAATGCTGGTAAGAGAGGAAAAAAGA

[0292] GCTATTGAACTTTTCCATGAATGTTCTAACATGTTTTCTTAAAACACTTTAAATGCCATAA

[0293] AGGCAGGCTTAAATGTAATTGTTAAAGAAATGTCACCAAATGACTCTTAGTTTGCAGATC

[0294] TGGTGAGGCTAAGGTAAAACTTTTCTGGGCTTCAGACGTGTCTGAAGTATTTTAATTGTT

[0295] AAATTTACAGCATACATACTGACATATCTGAAGTGGTTAATGGTAGAATTTGCATATAAA

[0296] TGGACAATATTAGAGTGGGGAAGTTAGATTAATTTAGCTTTAAAAATAATGCAGTGATTT

[0297] GCATTTGCAGTGTTATTCAACAAAATGGCACATCTTTTATTGATAGAATCAGACTACTGTT

[0298] CAATCAAAATTGATATTGGGATCATATGCTAGTTTTTCTACCAAAAGTAACACATTAAGAA

[0299] AATGTCCTGTGGTACAATTTATCATGCAATATCTTTCCTGAGAAAATCGTAGTGTGGGATT

[0300] CTCCGGGTAATTTGATGGAGAGAAAAAGTAGTTTGGTTGCTATTGCTCTCAGCTTCTT

[0301] TTAGCCACTTTTGTTTCTTAAAAGTATAGAGCTTTGAATAATTGAAGAAAAGCACCTATA

[0302] CCTAGCAAGATTATGTGAACACCTAAAATTGTTGTCATTTTAATTTCTATCTTACCATACAT

[0303] AACAAAAAAATGGTAAAGATTCTTCAAGAGTCTTGGGTCCTAGAAGTGCATGATAAATA

[0304] ACATCAAAGCCCAATATTGCAGAGGAAATTATGTGAAGCACACCTGATTCAAAGTATGG

[0305] AAAGGTGCATATAACTTCCATGCCATGACCCACCCTCCAACCTAGAGTAGCTAGTGGGGA

[0306] TGTAAAATTAATCCTTGTTCATACATTGGCTTCTCCGGTATGAAATGGGCACTGGTTAAGG

[0307] TGATCTGTCTTGAAAAAAAAAGAAACATTAACCTCTATAAAGGAATTGCTTTGTTTTTG

[0308] GATCAAAATAAGGTACCTGTGTTCAACCAAAACAAAGGAACTTGTAGTCAAGTCTATC

[0309] AAGTAAAAATATAATTTTTTAAAAACTGCAGTAGTTAGTTACCTAACATTGTTTCTACTAGT

[0310] GCTACTTTCATTTCAAACTGTAGCTCAGCAGCTGCAGCTGCCACATCCCTACACATCAATA

[0311] CTGAACAGGTGTTACAACTGCTTATTTATTGGTTAAGCCGTGTCAGAAATAGCACTTTGT

[0312] CAGGTAAGTGCTAAGGGCTCTTGGAGCCTAGTTGTACACTTGAGCAAAGCAAGGCACAT

[0313] CCCTACACATCAATACTGAACAGGTGTTACAACTGCTTATTTATTGGTTAAGCTATGTCAG

[0314] AAATAGCACTTTGTCAGGTAAGTGCTAAGGGCTCTTGGAGCCTAGTTGTACACTTGAGC

[0315] AAAGCAAGGCCTATAATACCTAATATTGATGGTTTTTCTCTTTCTCTCTCGTTAGTTTTTT

[0316] TTGTTTTTGGGGTGGGGGAATCATAAATCGAATCTTTCCTCTGCTTACAAAAATATCCCCCGG

[0317] TAAAACTTGTGTGGCCATAAGAATGTGGCTGAAAAGTCTTTTTTTTCTTGGTAGAAACCA

[0318] CTGTAGATCATAACTAATATCACCTAAACTTCTAAATATCATTCACATAACCTTATAAAACT

[0319] TGATATGAAAAAAGAAATAGATGACATCTTCATCTAGCAAATGTTATTTTTTTACTTTTTATT

[0320] TTTTTTCCCGGAGTGTTTTTAGCAGACCCTTGTTCCTTGTTTATGGTGCCTCCCCTAGGGT

[0321] TTGAAAAGTGTTTTAGTTTTGTGCTTAGCACCTAAGGTGCGGTGCACCTTGTAACAGCA

[0322] CTGGGGCTAGGTTATGGGAAAATATAGAATTTCCAGGTTTTGATTTTGACTAAGGGGCTC

[0323] TCAAAATAAAGTGATCGGGTTATAAAGCTATGGGTTAGAGACAAAATTGGGTCTTG

[0324] CATGAAGCAAATATTTATCAGTGTCAGAAATTCCATTGAAGATGTTATGTATAATTTATTAG

[0325] TTCAGAACAAGTTACAGTTGGCCAGTTGCCCAAGTCACTTATAATTTCATCAAATTGTAA

[0326] TGTGGTTTTTTAAGTAGTAAGCCAAATGGGTCATCATCTTCTTACATGTGTGTTTACCTT

[0327] TCTTTCTTTAACTAATAAAATAAAATGTTCTTGTCTATTGTGTATTTCTTCCGAGTGTTTTT

[0328] CCTATGCTTGTTCTTCATGATCTCTCGCTCTGTAATGTCCTTCCAGCATTTCTAATTAGGAA

[0329] TGAAAGAGACAAAGTTTCCTATAAGTTTTTCCTGTATGTTTTTTAATCCCTTGGGAAAGC

[0330] CTCCCTGATGCATAGCTCCCGTATCGTTGCTAGAGGATATGCGTACATAATCCATCATTGA

[0331] ATTGGATATATACCTAAATACTGTGCAGAAAAGAGAAAAGAAATAAAGAAACACTA

[0332] AACTGTTTGGGTTAAGTGCTTTTGTCCTTGTTATTTTCATCCTCATCCATGAATCTATGTTAC

[0333] TATTTGTGGCATTCTTTTCTTTGGGGAGAAGGGGAGGTGGAGAGGAGGACAAAGCTGTC

[0334] TGATTTCTTTATTGTGGGAAATTACGTATTCAATAAATTGAGTTTTTTGAGTTCTACAATTT

[0335] ACATGTTTAATGATCAGCCAAGCATATCGCATTGGAAGAATATTCATTTTGCGTGTAGTA

[0336] ATCACAAGATAGCCATGGAAAAAAAACATTCGTCAAGCGTTTTCTTTTACTTGATATATTTT

[0337] TTTGCTTAAATCAGCTTTTAGTTTCTTTTGTGAGATAAAATATCTTTAAGCATGATAAGGA

[0338] CTGCTATTTTCACACCTATTTGGGCCCAAGCATGTAACAAGGCTAGGCAGCTGCTAAGTC

[0339] AATGACCAACTGAAAAAATCCTCCTCGGTATTAGGTTGTAATTTGAAAAGAATTTCATGA

[0340] TGTATTGTTGGAATTTACAGAAATGTGTATTTAGGCAATAATAGATTATTAGTGGGGTGG

[0341] TCATTGGGCTCTTGAAGATTACCGTTCTTTTCCCTCTTTTTTTTTTCTTAATGCTCTTCTTCTT

[0342] CTTCTTTGTTCCGGTTCATATTATTAGATGTTTGTATATTCGCAAACCCCAGTAATGATA

[0343] TTCCATGTGACTTGTATTCTTTTGGTGCAAGGAGGTCGCACGCTTTCCCTATGCTTTTATG

[0344] ATCATTAATTGACGTCAGAAAATACTAGTGATTTCTTATGGTTTGCAATAGGACTAAAATA

[0345] TAAAGTTATATGATGCAATGTGTTGATTCCATTTGGAAGACATCAGAAATAACACAACCT

[0346] CACACCCATGCCAAAACAAATGTATATACTTGAGGGTGCTTTCTATGTTGTTTTTTTACTA

[0347] GTTTCTGGTGATAGTTGATTTCGTCATGGGAATACAATTTAATCTTGTACGTCTCTGTTTAT

[0348] TGGCGAAAGATTTTGGTGCACACATGATATCTAATAGTTTGTGAACTGTAGATGAAA

[0349] TCCCATAAATTGTTGTTTTTCATTGTTCTATGAGTTTTTATTAGTTGGCTGTCAATACTCAT

[0350] TCTATAGTGTTGTTTTTGACTTCCTAAATTTCTAATTTTGTTCTCCATTTGATAGAACCGTC

[0351] CTGCTGAGCTGATTGCAAAGTTTTTGGACGAGAAGCTTCGTGCTGGGAATAAGGGTACA

[0352] TCCGAGGAAGAGTTGGAGGGTACACTTGATAAAGTTTTGGTTTTATTCAGGTTTTATTCAG

[0353] GTAATCTTATGTGTTAAAGAAGTCAGTATTTTCACTACTAGCTCACCAGGTTTTTCCTTAC

[0354] TATCATATTTTTGGTTGTTGTACAAAACAAAATGATGCTGAGATACGTGCATCTTCCGTTTC

[0355] TTTTGTTTTATGAAGGGTAAGGATGTCTTTGAAGCATTTTATAAGAAGGATCTTGCAAAA

[0356] AGACTGCTGTTGGGAAAAAGCGCTTCTATTGATGCAGAAATCTATGATATCTAAGGTT

[0357] AACCACAACAACTTTTATGAGTAAATGTTTTCCGAGTCCTTTTCTTCTATCAATGAAATCA

[0358] ATATGTTTGTGTTGTCATTGCAGCTGAAAACTGAATGTGGTAGCCAGTTTACAAACAAGC

[0359] TTGAAGGAATGTTTAAGGTCTGCACTATTTATACAAGTTCATCAACGACTCGTCTTTGTTC

[0360] TACTTTTCTCACTAACTACTAATTGGAGGATGGTAATTTATTGTTATACAACATAAATTTTG

[0361] TGAAGCTCTCATGCCCCCGGCAATGCTTTCATGCCAAATACACTAACAGAGGTGGCAATA

[0362] TTAAATGGATGAAGCTCAGATTAACACGGAGAAACTTTATATCCCTCTCACCCATTTTCA

[0363] GTTTTCCCACATTACATGAGTGCATGTGCTACTTTTGCCTCCAACTCCCAATCCCTACAAC

[0364] ATTGCATGCATGTGCACCCAAACAGAAATAATGATAAAAGATAAAAAGTAAATGTAAACT

[0365] TTGATTCTCAATGTCTGTAAAACATTTCTTGACCGCTGAATGTGTGGTTTTATATACATA

[0366] ATATAACATGTCTGTTGAAATGGTTCTTGATTGGACTCCGTGAGTGACACAGGGTTGTCA

[0367] TTTCTTGAAGGTAGTTGAAATGTTAGAAGAAAATTAAGTTTGAACTCAGTAACATGCATG

[0368] TACAATGATAAAATTGTTTCCCTGAGGAAAAAAAATGCATATTCTTGATGCTGGTTTCATA

[0369] CATGGATTTTTGTTTATTGAATTTTATTTTTGGGAAGTAACCATTGCTTTGAATTTCTTAGA

[0370] TTTAGAATTGAGGTTCTATATGCCATTGTATCTATTAAATCCTAATATCCTTCTTCTTTCATT

[0371] TAGTAACTTCATATGGATTACCAGTGAATGAAGATGGCTTATTTTTATCGTTTTCTTTGTCTT

[0372] GGTGGTGCTTTTTCAGGATATTGAACTATCAAAGGAGATAAATGAGTCCTTCCGACAATC

[0373] ATCTCAGGCCAGGACAAAACTTCCATCAGGGATTGAAATGAGTGTACATGTTTTAACCA

[0374] CTGGGTTGGTTTTGGATCCTTTTTGTTTGTATTTGATGTAAAATTTGTATATTTAGTTCCTT

[0375] AATTCCTACAGAAATTTAATTTATTTGGTTGGCTGGACTGCAGGTACTGGCCCACATATCC

[0376] ACCCATGGATGTTAGGCTTCCTCATGAGCTGAATGTTTATCAGGTATTTTGCAAAAGACC

[0377] TGATGTTTCTCCCACATCTACAGCCACTAAAATATTGAATAAACAATTGCCTTATATATAG

[0378] GATATATTCAAAGAATTCTACTTAAGCAAGTATAGTGGTAGGCGCTTAATGTGGCAAAAC

[0379] TCATTGGGTCATTGTGTATTGAAAGCTGAGTTTCCAAAAGGTAAAAAGGAGCTGGCAGT

[0380] TTCTCTATTTCAGGTTGGTCTTTTTTAGTTTTCAATGCATAGCCCTTTACATTGTCTCTTAC

[0381] TGTTCATTTGTTTTTATGGATGCGACCTGTGTTAGTGGACATCTTCTAATTGTTGACCATC

[0382] TCATGCCTTCTACTCCAGACTGTCGTTCTGATGCTGTTTAATGATGCCCAAAAGCTTAGTT

[0383] TTCAAGATATCAAAGACTCTACTGGCATAGAAGACAAGGAGCTTAGAAGAACTTTGCAG

[0384] TCTCTGGCATGTGGAAAAGTTCGGGTTCTGCAAAAGGTAGGCGATGATTAACTGTATCG

[0385] CGTGTGTGATCTTACAAATGCTGATAAAATTGTTTAATGTTGGGTTTTTTGCTCATCCCCTTTT

[0386] TTCCTTATTATAAAATTATGGTTTACAGCTGCCCAAAGGGAGGGATGTGGAGGAGGATGA

[0387] TTCCTTTGTGTTCAATGAAGGATTTACAGCTCCACTCTATCGAATAAAGGTATCAGTTTCA

[0388] TATCTATCTACAGTCAAAATAGCTTTTTTTTTCTACTTGCATGAGCATGGCTAATGCGAAG

[0389] AGTTGACCTTGTGAAGTAAAGTGCTTTTATAATTATTAAGGTACTTCCATGATTTTTCTTT

[0390] GCCAGTCGTATTTTGGATCTTTGAGGCAACACTTGTTTTGGGATGCAGGTCAATGCAATC

[0391] CAGATGAAGGAAACTGTAGAAGAGAACACAAGCACCACTGAGAGAGTGTTTCAGGATC

[0392] GTCAATACCAGGTTAACCTTCACTCAAGTTCCATTTTTAATAAAATCAGTTTCTTGTAATG

[0393] AAAATTCAACAAAGATGTGAAATTGCTGGATGTAATATTTGTGATATTGCCTAATATGTTA

[0394] CAGGTCGATGCTGCGATTGTTCGGATAATGAAGACAAGGAAAGTGCTAAGTCACACGCT

[0395] TCTTATAACTGAACTATTCCAGCAGGTAAATCTGCTTCATTTTATTTTTCGTGAGTAGGGA

[0396] TGAATCCAGACTTTGTGGGTTCTTGATCATCTTCTTCGTTTTACTTTATGAAATGTCACCCA

[0397] AATGTACTGTGATTGGTCACTTTGGTAGATGAATGAAATTGGGAGGCAAACTTTACCCAG

[0398] TTCTGAAACTTTCTTGCTGGATATTGATATTCATGAAACAAATATTTTATGTGCAAACAG

[0399] CTGAAGTTTCCTATAAAGCCGGCTGATTTGAAGAAAAGGATAGAAAGTCTTATCGACAG

[0400] GGAATACCTGGAGCGAGACAAGAACAACCCTCAGATATACAATTACTTGGCTTAACACA

[0401] CTGCCACACCAATTGTGTCCTTGTAAATGGCACGGGAAACTTCTGTCCCATCCAAGAGG

[0402] CAGGTGTTCCATTGTGGTCAGATTAATGTACAGTATGTAGTTGTTTATTTTTGCTGCAATC

[0403] AACACTGTAGTTGTAAAGCGTATTCTGCCTCAGTCCATTACTTTCTCTGCTGTTATATGTT

[0404] CTCTGAGTCGCCTGAGGTAAAGGGGGGAATTTGATTCAAAAGAAAAGGGGAAATTAAG

[0405] CTCCGCTCCCAGGAGTGGCTTATGCGAGAGACAGGAGAGGTGAGAAAAGCAAACTGGC

[0406] ATTTTCACCAGCCATAATAAGAATGATGGAGCTTTAATAGGACTGGGGATGATGCATGTTT

[0407] ACTTACACCTCGAACTTTACAATTCATGTTCAAATCGAGCTCATAGTTTTATTCTTATTCA

[0408] ACGGCTGTTGTTGCATTTGAAGGCATAGTTCTCATGTTGCCCTTTGTTCTGATTTTACTAC

[0409] TTTGGTTCTTTTATTTTCATCTCAAATTTTATAGGTAACTTCACCCGTATAAATCCTATTACCAATATAGTCCCAAACCTTGTACAATTGTTACTGATCGATTCAATCTAATTAATTTG;

[0410] Forward: TCCCGCCGCCGCTAATTTGTCT (SEQ ID NO: 8);

[0411] Reverse: GGGCAGAGTTGGTTTAGCCTTGACG (SEQ ID NO: 9).

[0412] The expression stability of internal reference genes is crucial for qRT-PCR expression analysis. Currently, the expression stability of commonly used internal reference genes (such as GAPDH, α- / β-tubulin, actin, UBQ, UBC, etc.) is often affected by specific experimental conditions or tissue types. The purpose of this invention is to provide a universal internal reference gene applicable to different species within the *Populus* genus under different treatment conditions and tissue types, along with its screening method and application, thereby providing a theoretical reference and technical foundation for conducting molecular biology research and biotechnology breeding of poplar. This method is also applicable to the screening of universal internal reference genes in other genera.

[0413] The embodiments described above are merely preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Various modifications and improvements made by those skilled in the art to the technical solutions of the present invention without departing from the spirit of the present invention should fall within the protection scope defined by the claims of the present invention.

Claims

1. A universal internal reference gene applicable to the stems of different Populus species, characterized in that, The universal internal reference gene is: CNOT2, VPS35 and CUL4 Genes, the ones mentioned CNOT2, VPS35 and CUL4 The nucleotide sequences of the gene are shown in SEQ ID NO: 1-3.

2. A primer set for amplifying the universal internal reference gene of claim 1, characterized in that, Used to amplify CNOT2 The primer pairs for the gene, with nucleotide sequences as shown in SEQ ID NO: 4-5; Used to amplify VPS35 The primer pairs for the gene, with nucleotide sequences as shown in SEQ ID NO: 6-7; Used to amplify CUL4 The primer pairs for the gene, with nucleotide sequences as shown in SEQ ID NO: 8-9.

3. A kit for amplifying the universal internal reference gene of claim 1, characterized in that, It includes the primer set as described in claim 2.

4. The application of the universal internal reference gene as described in claim 1, the primer set as described in claim 2, or the kit as described in claim 3 in the stem gene expression analysis of different Populus species.

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