Temperature-regulated ssupgi gene closely related to wood fiber quality and application thereof

Abstract

This invention belongs to the field of plant genetic engineering technology, specifically relating to a temperature-regulated process closely related to wood fiber quality. SsuPGI Genes and their applications. This invention discloses a temperature-regulated gene that is closely related to wood fiber quality. SsuPGI The gene, whose nucleotide sequence is shown in SEQ ID NO.1, whose CDS sequence is shown in SEQ ID NO.2, and whose encoded protein amino acid sequence is shown in SEQ ID NO.3, is regulated by temperature signals. SsuPGI Gene networks can directionally influence the formation process of wood fibers, thereby achieving precise and controllable regulation of wood fiber quality. The work on improving the anatomical structure and morphology of target material wood fibers by using wood fiber quality-related regulatory genes has important scientific significance and application value.

Description

Technical Field

[0001] This invention belongs to the field of plant genetic engineering technology, specifically relating to a temperature-regulated process closely related to wood fiber quality. SsuPGI Genes and their applications. Background Technology

[0002] Wood lotus ( Schima superba ) belongs to the genus *Schima superba* of the family Theaceae. Schima Reinw. This is an evergreen hardwood broad-leaved tree. According to data from the Ninth National Forest Resources Inventory, it ranks 9th in importance among all tree species in China, making it the most valuable and high-quality broad-leaved afforestation species in southern my country. Its trunk is straight, and its wood is hard, heavy, and dense (air-dry density 0.697 g / cm³). 3 It has a uniform structure, good overall mechanical processing performance, and huge market demand. Studies have found that compared with other hardwood broadleaf tree species, the quality of *Symplocos edulis* wood is higher, which is related to its superior wood fiber anatomy (the length, width, and wall thickness of wood fibers are significantly better than other tree species by 1.6-3.3 times).

[0003] The mechanisms underlying the growth and development of wood fibers in *Symplocos rubrum* have been poorly studied. In model plants *Arabidopsis thaliana* and poplar, genes related to wood fiber cell growth and development are mainly involved in the formation of primary and secondary cell walls. Which substances and their regulatory processes are limiting factors in *Symplocos rubrum* remains unknown, thus lacking a reliable method for the targeted breeding of long-fiber varieties. Summary of the Invention

[0004] To address the problems existing in the prior art, the purpose of this invention is to design and provide a temperature-controlled system that is closely related to the quality of wood fibers. SsuPGI Technical solutions for gene networks and their applications.

[0005] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows: The first aspect of this invention provides a temperature-controlled material that is closely related to the quality of wood fibers. SsuPGI Genes, the ones mentioned SsuPGI The nucleotide sequence of the gene is shown in SEQ ID NO.1.

[0006] Furthermore, the aforementioned SsuPGI The CDS sequence of the gene is shown in SEQ ID NO.2, and the amino acid sequence of the protein it encodes is shown in SEQ ID NO.3.

[0007] The second aspect of the present invention provides the aforementioned SsuPGI Application of genes in regulating the quality of *Symplocos edulis* fiber.

[0008] Furthermore, the regulation specifically refers to SsuPGIHigh expression of the gene can reduce the thickness of the secondary wall of the wood fiber.

[0009] The third aspect of the present invention provides regulation as described in the first aspect. SsuPGI The ASIL2 transcription factor expressed by the gene, which was selected in the northern Zhejiang population of *Symplocos pubescens*, has the CDS sequence shown in SEQ ID NO.4.

[0010] The fourth aspect of this invention provides the regulation of the ASIL2 transcription factor. SsuPGI Applications in gene expression.

[0011] Furthermore, the aforementioned SsuPGI Gene expression is negatively regulated by temperature.

[0012] The fifth aspect of the present invention provides as described in the first aspect. SsuPGI Application of gene-related regulatory networks in influencing the quality of *Symplocos edulis* fiber.

[0013] Furthermore, the aforementioned SsuPGI Genes related to pectin synthesis PG, PME / PMEI, GALT, GH17 There is a mutual effect.

[0014] The beneficial effects of this invention include: Regulated by temperature signal SsuPGI Gene networks can directionally influence the formation process of wood fibers, thereby achieving precise and controllable regulation of wood fiber quality. Utilizing genes related to the regulation of wood fiber quality in *Symplocos rubrum* to improve the anatomical structure and morphology of target wood fibers has significant scientific and practical value. The aim of this study is to design and provide a temperature-regulated gene network closely related to wood fiber quality. SsuPGI Technical solutions for gene networks and their applications. Attached Figure Description

[0015] Figure 1 GWAS reveals SsuPGI Significantly correlated with the wall thickness of *Symplocos edulis* fibers (-log) 10 ( p ( ) = 7.820); Figure 2 SsuPGI The gene is negatively correlated with the cell wall thickness of *Symplocos edulis* fiber; Figure 3 SsuPGI Genes exhibit genotypic variation within the population, with the northern ZJ population showing homozygosity. Figure 4 SsuPGI Start-up sub-region compliant element; Figure 5Dual-luciferase assays were performed to verify the binding of ASIL2 transcription factor (Ssu13G01869.1) to the promoter region of SsuPGI (Ssu06G00650.1). Figure 6 Changes in upstream and downstream metabolites and differentially expressed genes involved in pectin formation; Figure 7 Analysis of upstream and downstream metabolites and differentially expressed gene modules in pectin formation; Figure 8 SsuPGI Interactive networks; Figure 9 In the thick and thin cell wall groups SsuPGI Changes in expression levels; Figure 10 The content of protopectin and soluble pectin in the thick and thin cell wall groups increased with increasing cell wall thickness. SsuPGI Changes in expression levels; Figure 11 The contents of cellulose, hemicellulose, and lignin in the thick and thin cell wall groups increased with... SsuPGI Changes in expression levels. Detailed Implementation

[0016] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be described in detail below with reference to specific embodiments. However, it should be understood that these embodiments are for illustrative purposes only and are not intended to limit the scope of the invention.

[0017] Example 1:

[0018] I. Sample Preparation and Test Methods (I) Preparation of natural population samples The experimental materials were obtained from an 18-year-old provenance forest of *Symplocos edulis* in Jian'ou, Fujian Province. Using 22 provenances from across the country, core samples were taken from the south-facing diameter at breast height (DBH) of the trees for the study of variations in wood fiber anatomy. Secondary xylem complex tissues were collected from 173 individuals, flash-frozen in liquid nitrogen, and stored at -80°C for resequencing, transcriptome sequencing, and subsequent gene function studies.

[0019] After the wood core was brought back to the laboratory and dissected, the wood fiber cells were observed under a Zeiss microscope. The length, width, double wall thickness, and lumen diameter of the fibers were measured and statistically analyzed using ImageJ software. Complete wood fibers in the field of view were measured, with at least 30 wood fibers measured for each material and at least 6 data points measured for each wood fiber, and the average value was taken.

[0020] (ii) Sequencing and bioinformatics analysis Genomic DNA was extracted from secondary xylem complex tissue stored at -80℃ for whole-genome resequencing, and DNA concentration was precisely quantified using Qubit 2.0. Paired-end Illumina libraries were prepared using the NEB Next® Ultra™ DNA Library Sequencing Kit (lpswich, Massachusetts, USA) and sequenced on the Illumina Navaseq 6000 platform in PE150 mode at approximately 20× read depth, 150 bp read length, and 350 bp insert size.

[0021] Using the BWA-MEM module in BWA v.0.7.8 with default parameters, clean reads from 173 individuals were aligned with the SSJ reference genome (Li H, Durbin R. 2009. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25: 1754–1760.). PCR duplicates were identified and removed using Picard; single nucleotide polymorphisms (SNPs) and short insertion and deletion variants (INDELs) of 1–10 bp were identified using the Genome Analysis Toolkit (GATK) (McKenna A, Hanna M, Banks E, Sivachenko A, Cibulskis K, Kernytsky A, Garimella K, Altshuler D, Gabriel S, Daly M, Depristo MA. 2010. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Research 20: 1297–1303.). Genetic variations were identified using GATK v.4.7.1.0 HaplotypeCaller. The effects of environmental factors were analyzed using LFMM.

[0022] (III) Transcriptome, proteome and metabolome analysis A whole-forest survey was conducted on five plantations of *Symplocos edulis* (4, 6, 10, 20, and 54 years old) from Jian'ou, Fujian Province. Secondary xylem tissues from the heartwood and stems were collected for transcription, proteomics, and metabolomics sequencing. Total RNA was extracted using the Takara MiniBEST Plant RNA Kit (Takara Bio Inc., Bashan, Shanghai, China), and libraries were constructed using the NEBNext Ultra RNA Library Preparation Kit. Sequencing was performed on an Illumina HiSeq 2500 platform, producing 150 bp paired-end reads (approximately 8 Gb per sample). Raw reads were quality-pruned using Trimmermatic v.0.36 and aligned with a reference genome using HISAT2 v.2.1.0. Transcriptional abundance was quantified using StringTie v.1.3.4, and DEGs were identified using DESeq2.

[0023] Proteins were extracted from samples ground in liquid nitrogen using urea / SDS buffer, digested with trypsin, and labeled with TMT reagent (Thermo Fisher Scientific, Waltham, MA). Labeled peptides were fractionated by HPLC and analyzed by LC-MS / MS in DDA mode on an Orbitrap Q Exactive HF-X. The *Symplocos spp.* proteome was spectroscopically identified using ProteomeDiscoverer 2.2, with an FDR ≤ 1%. DEPs were screened using p < 0.05 and |log2FC| > 0.58. Functional annotation of DEPs was performed using InterProScan, followed by enrichment analysis using the OmicShare and Novogene platforms. WGCNA analysis was used to analyze the differences in DEPs across developmental stages (β = 7, minModuleSize = 30, cutHeight = 0.9). Modules with the strongest correlation between characteristic proteins and 10-year developmental age were selected as core modules for further analysis.

[0024] Metabolites were extracted with methanol and separated by UHPLC (Hypersil Gold column, 17-minute gradient) coupled with an Orbitrap HF / HF-X mass spectrometer (Thermo Fisher Scientific, Waltham, MA, USA). Raw data were processed in Compound Discoverer 3.1 for peak alignment and normalization. Metabolites were annotated by matching with the mzCloud, mzVault, and MassList databases, and functional classification was performed using KEGG, HMDB, and LIPIDMaps. Differentially expressed metabolites (DMs) with VIP>1, p<0.05, and |FC|≥2 were identified by metaX-based multivariate (PCA, PLS-DA) and univariate analyses. Functional and pathway enrichment analyses were performed in KEGG. WGCNA analysis was used to analyze the relationship between DMs and developmental stages (β=10, minModuleSize=30, cutHeight=0.9), and the module with the best correlation between characteristic metabolites and 10-year development was selected as the core. We used WGCNA (β=8 and 12) to identify key genes and proteins that regulate the 11 identified target metabolites and DEG and DEP, respectively.

[0025] JASPER and MEMM are used to predict promoter features and TF binding.

[0026] (iv) LFMM gene-environment association analysis Nineteen climatic factors from 22 geographic provenances of *Symplocos pubescens* were obtained from the WorldClim website (https: / / www.worldclim.org / ). Significantly correlated variables were removed, leaving 12 climatic variables to describe the geographic climatic factors of *Symplocos pubescens* provenances (Pearson r < 0.77). We employed a latent factor mixture model (LFMM) analysis, using the Rv.3.2.5 package “lfmm2” to determine the association between the genome and the environment. The latent variable K was set to 2 to account for the influence of population structure. The association between the allele frequency of each SNP in the 22 provenances and the aforementioned 12 environmental factors was calculated, and the significance of the p-values ​​was adjusted for multiple tests using the false discovery rate (FDR). Candidate SNPs with allele frequencies associated with each environmental factor were selected, with an FDR < 5%. The study identified 38,410 SNPs that were significantly associated with five climatic factors (AMT, annual mean temperature; MDR, diurnal temperature range; ISO, isotherm; TS, seasonal temperature variation coefficient; WQT, mean temperature of the wettest season) (FDR < 0.05), and 10,176 SNPs that were associated with 2,213 genes (including 144 transcription factors).

[0027] (v) Select Clear Analysis XP-CLR analysis based on haplotype homozygosity identified selected scan signals. All possible pairwise comparisons between five taxa (HNS, HGJ, ZJ, JF, and FJS) were evaluated using a 50kb genomic sliding window. The D values ​​for FST and Tajima were calculated using VCFtools within the 50kb sliding window with 20kb steps. To identify candidate genes under selected scans, the top 5% of the XP-CLR genomic window was filtered, taking into account the overlap between the top 5% of the FST window and the bottom -5% of the Tajima D window.

[0028] (vi) Dual-fluorescein analysis Will SsuASIL2 The encoding sequence incorporates pGreenII 62-SK, constructing it as 35S::SsuASIL2. SsuPGI The promoter sequence was introduced into the pGreenII 0800-LUC vector. These two plasmids were then transferred to... N.benthamiana In order to identify LUC signals, a ChemiScope chemiluminescence imaging system (ChemiScope 66100, Lexiang, Shanghai) was used.

[0029] II. Analysis of Experimental Results 1. SsuPGI Related to the thickness of secondary wall formation A genome-wide association study (GWAS) was conducted using the wood fiber anatomy phenotypes (fiber length, width, wall thickness, lumen diameter, etc.) of 173 samples from 22 provenances in natural populations. The results showed that... SsuPGI (Ssu06G00650, pectin methylesterase inhibitor protein, chr06_20493943~20498382, full length 4439bp, including 2 exon regions (nucleotide sequence as shown in SEQ ID NO.1; CDS sequence as shown in SEQ ID NO.2, encoding amino acid sequence as shown in SEQ ID NO.3)) The SNP_C06_20511806 at 13.4kb upstream of the protein is significantly associated with wood fiber wall thickness (-log 10 ( p =7.820) Figure 1 Transcriptome data from the same population showed that... SsuPGI The expression level was significantly correlated with the thinning of the cell wall of wood fibers. r =-0.17, p <0.05)( Figure 2 This shows SsuPGI Negative regulation of wood fiber cell wall thickness affects wood fiber morphological variation.

[0030] 2. SsuPGI Affected by temperature Compared with other distribution areas, the northern provenance ZJ (Zhejiang) has... SsuPGI Expression levels increased by 1.3-2.4 times, cell wall thickness decreased by 7-9%, and the temperature in the suitable growing area of ​​ZJ seed source in the north was low (WQT). ZJ =20.14°C, WQT mean =22.03°C) Figure 2 Using a latent factor mixture model (LFMM), gene-environment associated loci were identified. Three SNPs (FDR < 0.05) associated with WQT were determined: SNP_C06_20491738, SNP_C06_20492230, and SNP_C06_20496075. Within a 5kb window of these three SNPs, [the following was observed / identified]. SsuPGI Genes. Furthermore, GWAS showed... SsuPGI The two exons contain 12 additional candidate SNPs (-log10( )) that are significantly correlated with wall thickness. p ()>5), and more than 90% of ZJ individuals have homozygous genotypes on these 12 SNPs () Figure 3 Among them, 12 SNP loci are chr06_20494099, chr06_20494168, chr06_20494332, chr06_20494577, chr06_20494657, chr06_20494662, chr06_20494681, chr06_20494807, chr06_20494906, chr06_20498293, chr06_20498361, and chr06_20498373. These 12 loci belong to the CATTCCAGGCCC genotype, corresponding to short and thin fibers. Therefore, it is believed that... SsuPGI The thin-walled phenotype of wood fibers is determined by the specific genotype formed under the influence of WQT and in a colder environment (ZJ source in the north).

[0031] 3. SsuPGI SsuASIL2 transcriptional elements regulated by northern population selection SsuPGI Starter subregion follow-factor analysis shows ( Figure 4 This transcription factor, SsuASIL2 (MA2039), can be regulated by elements such as low temperature and light response, and has a nearby binding site for ASIL2 (MA2039). Population scanning analysis showed that the selected transcription factor SsuASIL2 (Ssu13G01869.1) (CDS sequence shown in SEQ ID NO.4, amino acid sequence shown in SEQ ID NO.5) in the ZJ population binds to... SsuPGI The correlation is relatively strong ( r ZJ = 0.34, rmean = 0.12, p<0.05), this transcription factor SsuASIL2 belongs to the Trihelix family and is regulated by temperature, light signals, hormone signals, etc. Dual-luciferase assays have demonstrated that SsuASIL2 can positively regulate activation SsuPGI The expression ( Figure 5 ).

[0032] 4. SsuPGI Related regulatory networks influence the formation of secondary walls. During the rapid growth and development period of wood fibers (10 years), the content of the pectin precursor UDP-galacturonate gradually increased, while the content of the pectin degradation product D-galacturonate was relatively high. Figure 6 Using this substance for differential gene analysis (WGCNA), the blue module was found to be significantly associated with it. p <0.05)( Figure 7 Interactive network display () Figure 8 ), SsuPGI Genes related to pectin synthesis PG , PME / PMEI , GALT , GH17 There is a interaction effect ( PG , PME / PMEI , GALT , GH1 The CDS sequences of the genes are shown in SEQ ID NO. 6-10, and they play important roles in signal transduction, environmental stress, lipid metabolism, and glucose metabolism pathways. Pectin synthesis-related genes play a crucial role in cell wall relaxation and expansion; therefore, it is inferred that… SsuPGI During fiber elongation, it maintains cell wall integrity, balances pectin degradation and remodeling, and brings cell wall strength and plasticity to a steady state, while secondary walls accumulate slowly.

[0033] 5. SsuPGI Further validation of the effects of gene regulation on pectin on cell wall characteristics Transcriptome and phenotypic data analysis of 133 individuals from the F1 generation of 10-year-old *Symplocos edulis* hybrids revealed that the cell wall thickness group (SWT) was... 平均 =19.05μm) SsuPGI Expression levels were significantly lower than in the thin-film group (SWT). 平均 =11.78μm) Figure 9 The thick-walled group had higher protopectin and lignin content, lower soluble pectin and cellulose content, while the thin-walled group showed the opposite. Figure 10 , Figure 11Pectin is typically found in the primary cell wall and middle lamella, maintaining the rigidity and adhesion of the cell wall, while lignin strengthens the rigidity of the cell wall. Therefore, thick-walled materials have stronger mechanical properties. In thin-walled materials, SsuPGI Excessive inhibition of soluble pectin degradation maintains the accumulation level of soluble pectin in the cell wall. Figure 10 This accumulation, in turn, inhibits further conversion of protopectin, leading to an overall "stiffness" in the metabolism of pectin in the cell wall, which interferes with the normal deposition of lignin in the secondary cell wall. Figure 11 This results in thin fiber walls. Therefore, SsuPGI It plays an important role in regulating homeostasis during cell wall formation.

Claims

1. A temperature-regulated material closely related to wood fiber quality SsuPGI Genes, characterized by, The SsuPGI The nucleotide sequence of the gene is shown in SEQ ID NO.

1.

2. As described in claim 1 SsuPGI Genes, characterized by, The SsuPGI The CDS sequence of the gene is shown in SEQ ID NO.2, and the amino acid sequence of the protein it encodes is shown in SEQ ID NO.

3.

3. As described in claim 1 or 2 SsuPGI Application of genes in regulating the quality of *Symplocos edulis* fiber.

4. The application as described in claim 3, characterized in that, The regulation specifically refers to SsuPGI High expression of the gene can reduce the thickness of the secondary wall of the wood fiber.

5. Regulation as described in claim 1 SsuPGI The ASIL2 transcription factor expressed by the gene is characterized by, The CDS sequence of the ASIL2 transcription factor is shown in SEQ ID NO.

4.

6. The ASIL2 transcription factor as described in claim 5 in regulating... SsuPGI Applications in gene expression.

7. The application as described in claim 6, characterized in that, The SsuPGI Gene expression is negatively regulated by temperature.

8. As described in claim 1 or 2 SsuPGI Application of gene-related regulatory networks in regulating the quality of *Symplocos edulis* fiber.

9. The application as described in claim 8, characterized in that, The SsuPGI Gene-related regulatory networks include genes related to pectin synthesis. PG , PME / PMEI , GALT and GH17 .

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