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Article

Genome-Wide Identification and Analysis of Glycosyltransferases in Colletotrichum graminicola

by
Yafei Wang
1,2,*,
Honglian Li
1,
Jiaxin Chang
1,
Yu Zhang
1,
Jinyao Li
1,
Shaofeng Jia
3 and
Yan Shi
1,*
1
College of Plant Protection, Henan Agricultural University, Zhengzhou 450002, China
2
Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 440307, China
3
Syngenta (China) Investment Co., Ltd., Shanghai 200126, China
*
Authors to whom correspondence should be addressed.
Microorganisms 2024, 12(12), 2551; https://doi.org/10.3390/microorganisms12122551
Submission received: 7 November 2024 / Revised: 5 December 2024 / Accepted: 9 December 2024 / Published: 11 December 2024
(This article belongs to the Special Issue Microbiome-Driven Agriculture: Transforming Sustainability and Resilience Through Functional Microbial Insights and Metagenomics)
Browse Figures
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Abstract

:
Corn leaf blight and stem rot caused by Colletotrichum graminicola are significant diseases that severely affect corn crops. Glycosyltransferases (GTs) catalyze the transfer of sugar residues to diverse receptor molecules, participating in numerous biological processes and facilitating functions ranging from structural support to signal transduction. This study identified 101 GT genes through functional annotation of the C. graminicola TZ–3 genome. Subsequent analyses revealed differences among the C. graminicola GT (CgGT) genes. Investigation into subcellular localization indicated diverse locations of CgGTs within subcellular structures, while the presence of multiple domains in CgGTs suggests their involvement in diverse fungal biological processes through versatile functions. The promoter regions of CgGT genes are enriched with diverse cis-acting regulatory elements linked to responses to biotic and abiotic stresses, suggesting a key involvement of CgGT genes in the organism’s multi-faceted stress responses. Expression pattern analysis reveals that most CgGT genes were differentially expressed during the interaction between C. graminicola and corn. Integrating gene ontology functional analysis revealed that CgGTs play important roles in the interaction between C. graminicola and corn. Our research contributes to understanding the functions of CgGT genes and investigating their involvement in fungal pathogenesis. At the same time, our research has laid a solid foundation for the development of sustainable agriculture and the utilization of GT genes to develop stress-resistant and high-yield crop varieties.

1. Introduction

Protein glycosylation is a crucial process closely associated with the structure and functionality of proteins. In eukaryotic cells, glycosylation is a prevalent post-translational modification of numerous eukaryotic proteins [1,2,3]. Glycosylated eukaryotic proteins account for over half of all proteins [4]. Typically occurring after or during protein synthesis, glycosylation represents a highly diverse form of protein modification [5]. This modification can enhance protein solubility while reducing susceptibility to protein hydrolysis. Researchers have increasingly recognized the significance of protein glycosylation in processes such as protein localization, transport, and intercellular interactions.
Glycosyltransferases (GTs) are widely distributed in various organisms [6]. GTs are present in both prokaryotes and eukaryotes, with a significant proportion existing as Golgi membrane proteins in eukaryotic cells. These essential proteins help transfer sugar residues to receptor molecules, thereby mediating diverse biological functions [3,7,8,9]. GTs play an essential role in cell wall biosynthesis, cell adhesion, and cell signaling [10,11,12]. They play critical roles in synthesizing secondary metabolites and responding to both abiotic and biotic stresses. The metabolites are vital not only for the growth and development of organisms. but also for their ability to withstand pathogens, pests, and other biological stresses [13]. Moreover, GTs are crucial in mediating organisms’ responses to drought, salinity, and low temperatures. They regulate osmotic balance, antioxidant capacity, and signaling pathways by facilitating glycosylation reactions [14,15]. Furthermore, GTs play a key role in synthesizing osmoregulatory substances, such as proline and mannitol, which assist organisms in maintaining cellular hydration under drought and high salinity conditions [16]. Utilizing genetic engineering techniques, researchers can enhance or introduce specific GT genes to improve disease resistance, stress tolerance, and yield in crops [17]. This approach holds significant potential for applications in sustainable agriculture.
Colletotrichum graminicola is a severe pathogen that induces stem rot and leaf blight on corn, ranking among the most devastating diseases affecting corn [18,19,20]. This pathogen primarily impacts corn crops and leads to annual losses of up to $1 billion in the United States alone [19]. The worldwide prevalence of this disease poses a significant obstacle to maize cultivation. The lack of effective resistant varieties sustains a strong reliance on chemical pesticides for disease management, leading to unforeseen environmental consequences. Moreover, pesticide residues present risks to human and livestock health. The increasing resistance of pathogens to pharmaceutical treatments also reduces the effectiveness of chemical control methods. Considering the widespread cultivation of maize globally, there is a critical need for a sustainable and innovative solution to ensure the protection of maize production and food security.
Recent advancements in genome sequencing, annotation, genome editing technologies, whole-genome association studies, genomic selection, and the integration of genomics and phenomics provide researchers with more efficient tools for breeding high-yielding, disease-resistant, and stress-tolerant maize varieties essential for ensuring food security. The application of transgenic technology can enhance plants’ ability to resist pathogens, with GTs playing a crucial role in this process. Research indicates that increasing the expression of specific GT genes can strengthen plant disease resistance, support plant cell wall formation, and improve plants’ ability to withstand various stress factors [21,22]. In recent years, researchers have placed a growing emphasis on studying the genome structure and pathogenic mechanisms of key fungal pathogens in maize. The availability of high-quality genomes of pathogenic fungi has facilitated the analysis of genes associated with crucial pathogenic processes [23]. The primary aims of this study are to identify and analyze the GT genes in C. graminicola and to examine their expression patterns during maize infection. This study enriches the available resources on GT genes and expands the application possibilities of GT genes in sustainable agriculture.

2. Materials and Methods

2.1. Identification and Analysis of GTs

The data for C. graminicola strain TZ-3 were acquired from publicly available genome sequencing databases [23]. The properties of GTs were predicted through ExPASy available at https://web.expasy.org/protparam/ (accessed on 28 September 2024) [24]. The online tool available at https://wolfpsort.hgc.jp/ (accessed on 28 September 2024) was used to analyze subcellular localization.

2.2. Phylogenetic Analysis

GT protein sequences from C. graminicola TZ-3 were analyzed using Clustal W in MEGA 5.0, followed by the construction of a phylogenetic tree in MEGA 5.0. The neighbor-joining method was utilized to construct the evolutionary tree, with a bootstrap value set at 1000 iterations. Subsequently, the tree underwent further refinement through the EVOLVIEW website (http://evolgenius.info//evolview-v2/) (accessed on 30 September 2024).

2.3. Gene Structures and Protein Motifs

We utilized the online tool available at https://gsds.gao-lab.org/index.php (accessed on 28 September 2024) to predict structures of GT genes [25]. The online tool available at http://meme-suite.org (accessed on 28 September 2024) was employed to analyze conserved motifs of GT proteins, using a motif count of 10 [26].

2.4. Identification of Cis-Acting Regulatory Elements (CAREs) and Gene Ontology (GO) Analysis

The 2000 bp upstream promoter sequences of GTs were extracted from C. graminicola TZ-3 [23]. The online tool available at http://bioinformatics.psb.ugent.be/webtools/plantcare/html/ (accessed on 28 September 2024) was employed to identify CAREs, while GO functional analysis was conducted using the online tool available at https://www.omicshare.com/tools (accessed on 28 September 2024).

2.5. Expression Pattern Analysis in GT Family

We obtained RNA-seq data of C. graminicola from prior studies and conducted an analysis to elucidate the expression changes of GT genes [20]. The online tool available at https://www.omicshare.com/tools (accessed on 30 September 2024) was utilized to generate heat maps using FPKM values.

2.6. RT-qPCR

RT-qPCR experiments were performed to validate the transcriptome data. Total RNA was extracted from maize infected with C. graminicola using the Tiangen DP441 assay kit (Tiangen, Beijing, China). Subsequently, cDNA was synthesized using a HiScript III first-strand cDNA synthesis kit (Vazyme, Nanjing, China). The analysis was conducted utilizing a SYBR qPCR Master Mix kit (Vazyme, Nanjing, China) and an ABI 7500 real-time system (Applied Biosystems, Foster, CA USA). The UBQ gene was chosen as the internal reference, and the results were determined using 2−∆∆CT.

3. Results

3.1. Identification and Physicochemical Properties Analysis of GTs in C. graminicola

All 101 GTs (named CgGT1–CgGT101) were found in the C. graminicola TZ–3 genome. Their detailed characteristics are listed in Table 1. The corresponding proteins consist of 238 to 2429 amino acids (aa) and have molecular weights ranging from 26.30 to 272.73 kDa. They can be categorized based on their isoelectric points (PI), with 35 CgGT proteins being alkaline (PI > 7.5), 50 being acidic proteins (PI < 6.5), and the remaining CgGT proteins being neutral. The grand average of hydropathicity (GRAVY) varies from –0.728 to 0.584. Among the CgGT proteins, 15 exhibit a GRAVY greater than 0, while the remaining proteins display a GRAVY less than 0. Subcellular localization analysis revealed that 43 CgGT proteins are found in the plasma membrane, 18 in the mitochondria, 18 in the extracellular space, 13 in the cytoplasm, 5 in the nucleus, 3 in the Golgi apparatus, and 1 in the endoplasmic reticulum (Table 1).

3.2. Phylogenetic Relationship

We constructed a phylogenetic tree using MEGA5 and analyzed the phylogeny of the CgGTs (Table S1). The results indicated that CgGTs were classified into nine groups, specifically Groups I to IX, comprising 16, 12, 14, 12, 14, 11, 10, 4, and 8 members, respectively (Figure 1). Certain groups exhibited closer genetic relationships, such as Groups I and II, while others, such as Groups I and IX, demonstrated more distant relationships.

3.3. Sequence and Structural Analysis of CgGTs

We conducted a comprehensive analysis of the structural characteristics of all CgGT genes (Figure S1, Table S1). The analysis revealed significant variations in the gene structure among the CgGT genes. Specifically, the CgGTs exhibited a range of 0 to 13 introns and 1 to 14 exons. Notably, CgGT12 stood out, with the highest count of both exons and introns, whereas 18 CgGTs were intronless. Moreover, structural domain analysis revealed a diverse array of superfamily domains present in CgGT, such as the PRK14501, glycosyltransferase GTB-type, and PMT 2 superfamily domains, among others. Particularly noteworthy were CgGT6 and CgGT19, each harboring six distinct superfamily domains.
To gain further insight into the functionality of the CgGTs, we analyzed conserved motifs within these CgGT proteins. Subsequently, we identified ten motifs in CgGT proteins (Figure 2 and Figure S2). Among these motifs, motif 9 stood out as the most prevalent, being present in eight CgGT proteins. Additionally, seven CgGT proteins exhibited motif 1, six contained motifs 2 and 9, five featured motif 10, and four showcased motifs 4 and 7. Furthermore, CgGT27 and CgGT45 shared four identical motifs, specifically motifs 3, 5, 6, and 8.

3.4. Sequence Analysis of CgGT Gene Family Promoters

The upstream promoter regions of CgGT genes were analyzed (Table S1). The promoter sequences of these CgGT genes contain various CAREs related to stress response, pathogenicity, and development (Figure 3, Table S2). Further analysis revealed that these promoter sequences predominantly contain the response elements associated with jasmonate, abscisic acid, salicylic acid, auxin, gibberellin, drought, low-temperature, defense stress, and light. Notably, methyl jasmonate (MeJA) response elements are the most abundant (808), followed by light response elements (791) and abscisic acid response elements (396) (Figure 4, Table S2). These findings suggest that CgGTs may have significant roles in responding to diverse stresses, as well as in fungal growth and pathogenicity. The CgGT genes also contain CAREs related to zein metabolism regulation, anoxic-specific inducibility, and anaerobic induction (Table S2). These results indicates that CgGTs may be associated with various biological processes.

3.5. GO Analysis of CgGTs

We conducted GO enrichment analysis on the CgGTs here. Our results revealed that CgGTs were significantly associated with multiple GO terms, including glycosylation (GO:0070085), monomer carbohydrate metabolic processes (GO:0044723), protein glycosylation (GO:0006486), and glycoprotein metabolic processes (GO:0009100), among others (Figure 5, Table S3). The research results indicate that CgGTs mainly contribute to glycosylation and metabolic processes.

3.6. The Response of CgGT Family Genes in the Infection Process of C. graminicola

To investigate CgGT family genes associated with the pathogenesis of C. graminicola, RNA-seq data was used to analyze the expression changes of 101 CgGT genes during pathogen infection [20]. A heatmap was constructed based on FPKM values of the 101 CgGT family genes, illustrating their expression dynamics at three time points (24, 36, and 60 h) post-inoculation (Figure 6). Our findings revealed that based on expression profiles, the 101 CgGT family genes could be categorized into seven distinct classes. In Class I, consisting of 7 CgGTs, gene transcription initially increased and then decreased during infection. Class II comprised 25 CgGTs, while Class IV included 16 CgGTs, showing a progressive upregulation in transcription levels throughout the infection process. Notably, Class VI and VII encompassed a total of 29 CgGTs, with their transcription levels gradually decreasing during infection. Eight CgGT genes were randomly chosen for RT-qPCR validation, and primers were designed accordingly (Table S4). The RT-qPCR validation results confirmed the reliability of the transcriptome data (Figure 7). These CgGT family genes exhibited substantial alterations in expression patterns during pathogen infection, suggesting their potential involvement in the pathogenic mechanisms of the pathogen.

4. Discussion

GTs are essential for numerous fundamental biological processes, mediating many functions [3,7,8]. These enzymes catalyze sugar transfer reactions, transferring sugar moieties from substrate molecules to another molecule. GTs are involved in many biosynthetic pathways, including the synthesis and modification of secondary metabolites and cell walls [27,28]. Moreover, GT genes regulate organisms’ responses to various stresses, contributing to the synthesis of polysaccharides in biological cell walls. As structural polysaccharides are crucial for organisms’ growth and stress resistance, the regulation of GT genes can improve the stability of biological cell membranes and enhance tolerance to adversity. Research conducted in the past has demonstrated the capability of a barley UDP-glucose GT, known as HvUGT13248, to efficiently detoxify deoxynivalenol, a toxin produced by Fusarium graminearum [22]. Expression of this enzyme in transgenic wheat results in a significant type II resistance response against fungi that produce deoxynivalenol, offering a promising strategy for mitigating Fusarium head blight in wheat. Considering the pivotal role of GTs in plants’ defense mechanisms against pathogen infiltration, the numerous GT genes pinpointed in this investigation could serve as valuable assets for the development of resilient maize cultivars that promote sustainable agricultural practices.
We identified GTs in the C. graminicola TZ-3 genome and analyzed their characteristics in this study. The analysis results showed that most CgGT proteins were hydrophilic, and nearly half of CgGT proteins were acidic. Phylogenetic analysis revealed that 8 CgGTs in group IX exhibited distant relationships with CgGTs in other groups, suggesting potential significant structural and functional variances compared to other CgGTs. The phylogenetic analysis demonstrates that CgGTs sharing similar structural domains tend to cluster together, while certain CgGTs cluster in distinct branches, potentially indicating functional diversity. The diverse nature of fungal GTs expands the scope of their potential applications. The correlation between the number of introns with gene function suggests that a lower intron count can enhance gene activation speed [29,30,31]. Discrete features characterize the distribution pattern of introns in microbial genes [32]. Among the CgGT genes, CgGT12 possesses 13 introns, while 18 CgGTs lack introns, indicating potential variations in intron numbers within CgGT genes throughout the evolutionary processes.
Subcellular localization analysis reveals that the CgGT proteins exhibit diverse distribution patterns across various cellular compartments. Among the 43 CgGT proteins identified in the plasma membrane, their presence suggests potential involvement in intercellular interactions and membrane architecture. The 18 CgGT proteins found extracellularly may either undergo secretion or be transported outside the cell membrane to exert their functional effects. Moreover, the 18 CgGT proteins localized within the mitochondria are likely associated with mitochondrial metabolic activities and structural integrity. In the cytoplasm, the presence of 13 CgGT proteins indicates a role in influencing cellular functions, growth, and metabolism. Additionally, five CgGT proteins are situated within the nucleus, suggesting their involvement in nuclear structure maintenance and genetic information processing. Furthermore, through bioinformatics analysis, we identified a diversity of protein domains within CgGTs, indicating their potential multifunctionality. The varied subcellular distribution of CgGT proteins implies their participation in fungal biological processes through multiple pathways, influencing the interactions between pathogenic fungi and their hosts. These results are consistent with previous reports highlighting the versatile roles of GTs in mediating various biological functions, from structural maintenance to signal transduction, thereby playing a crucial role in numerous cellular processes [7,8].
The CAREs present in promoter regions exert noteworthy influences on gene functionality [33]. GTs are pivotal for the biosynthesis of various secondary metabolites, crucial for organism development and resilience against biological stressors [13]. Unsurprisingly, we identified CAREs in CgGT promoter regions associated with stress and defense response. We also identified CAREs related to growth and light responsiveness. GTs are related to plant hormone synthesis and modification, thereby regulating plant growth and development. The ABRE regulatory elements are also related to abiotic stress responses [34,35]. CAREs associated with plant hormones and developmental processes were also found in CgGT promoter regions. Numerous CAREs related to various plant hormones, including elements for MeJA, abscisic acid, gibberellin, and auxin responses, were detected. GTs are essential for mediating biological responses to salinity, drought, and low temperatures [14,15]. They also play an important role in synthesizing osmotic adjustment substances that aid in cellular hydration maintenance in drought-prone and high-salinity environments [16]. Several CAREs associated with low-temperature response, stress response, and defense mechanisms were also identified. Additionally, many CAREs are closely linked to gene family functions [36,37,38,39,40,41,42]. GT genes are characterized by abundant CAREs that are indispensable for stress responses, offering a promising avenue for the creation of maize varieties resistant to diseases. The findings of this study align with prior research [21]. Previous studies have highlighted the essential role of the maize glycosyltransferase UFGT2 in modifying flavonols, thereby enhancing plant resilience to abiotic stress. Mutants with knocked-out ufgt2 genes exhibit marked sensitivity to salt and drought stress. These ufgt2 mutants show a notable decrease in total flavonol levels and reduced ability to scavenge H2O2.
The results of the GO analysis for CgGT genes indicate their primary involvement in glycosylation and metabolic processes, particularly in the metabolism of monomeric carbohydrates and glycoproteins. Glycosylation modifications are critical for biological development and are likely associated with the roles of glycoproteins in cellular recognition and signal transduction [43,44]. Glycoproteins serve multiple essential functions in organisms, including cellular recognition, signal transduction, cell adhesion, and immune response [44]. They play a vital role in host-microbe interactions. These analytical findings suggest that CgGT genes are implicated in pathogen–host interactions and are closely associated with pathogenic mechanisms. The functions of these genes suggest that they may contribute to the creation of resistant maize varieties, thereby reducing the use of chemical pesticides and promoting the development of sustainable agriculture.
Moreover, we investigated the changes in CgGT gene expression levels during the infection of maize hosts by C. graminicola. The function of genes is closely related to their expression characteristics [45,46,47]. Our analysis revealed varying levels of differential expression of CgGT genes at different stages of pathogen infection, implicating their involvement in pathogen–host interactions. The heatmap suggests that certain CgGT genes are primarily associated with the initiation of fungal infections, showing a gradual decrease in transcription levels as the infection progresses. Conversely, some genes seem to contribute to lesion enlargement, as evidenced by an increase in their transcription levels over time. Additionally, certain genes may affect the intermediate stage of fungal infection, displaying an initial increase and subsequent decrease in transcription levels with infection progression. These findings underscore the diverse roles of CgGT genes across different infection time points, indicating functional variability. Overall, these genes are involved in pathogen infection and disease expansion. Their important role in the interaction between pathogens and hosts will help to apply them to crop disease resistance research and provide ideas for sustainable agricultural construction.
Whole genome analysis of the GT genes provides a foundation for studying the function of CgGTs. It is important to note that the conclusions drawn in this article are based on bioinformatics analysis. The subsequent reactions following the expression of these genes in C. graminicola remain unclear. Future research should focus on the interactions between CgGTs and host-triggered genes. Furthermore, GT genes are crucial in sustainable agriculture as they confer resistance to biotic and abiotic stresses. This study offers a comprehensive analysis of GT genes in C. graminicola, enriching the available GT gene resources. By thoroughly investigating the functions and regulatory mechanisms of these genes, researchers can aid in developing stress-tolerant, high-yield crop varieties. Understanding the characteristics and functions of GT genes will enable deeper exploration of their potential applications in agriculture, thereby advancing sustainable agricultural practices. Through genetic engineering, researchers can enhance or integrate specific GT genes to improve crops’ resilience to biotic and abiotic stresses, consequently reducing reliance on pesticides and fertilizers.

5. Conclusions

The study conducted a detailed analysis of the CgGT genes and their expression patterns during pathogen infection, enhancing our understanding of this gene family. The research identified 101 GT genes in the C. graminicola TZ-3 genome, revealing their presence in various subcellular structures. These CgGT genes contain multiple conserved domains, indicating diverse functions and involvement in fungal biological processes that affect the interaction between pathogenic fungi and hosts. Promoter regions of these genes are rich in conserved CAREs associated with biotic and abiotic stress responses, suggesting their role in the organism’s stress response. Expression analysis demonstrated differential expression of most CgGT genes during pathogen–host interactions, with functional analysis highlighting their involvement in host–microbe interactions and the pathogenic mechanisms of pathogens. This study not only enriches GT gene resources but also presents new opportunities for leveraging GT genes in sustainable agriculture.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/microorganisms12122551/s1, Table S1. CgGT genomic, CDS, protein and promoter sequences. Table S2. Cis-acting regulatory elements are present in the CgGT gene promoter regions. Table S3. Gene ontology enrichment analysis of CgGT genes. Table S4. The primers used in this study. Figure S1. The gene structure and domain analysis of CgGTs. Note: (A) Structures of CgGT genes. (B) Domains of CgGTs. Figure S2. The sequences of CgGT proteins’ conserved motifs.

Author Contributions

Y.W., Y.S. and H.L. designed and directed the research. Y.W., J.C., Y.Z. and J.L. performed the experiments and wrote the original draft. Y.W., Y.S., H.L. and S.J. revised and polished the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Natural Science Foundation of China (No. 32102159), the National Key Research and Development Program of China (2023YFD1401502), Key Research and Development Project of Henan Province (231111111100) and Henan Province Corn Industry Technology System Plant Protection Post Scientists Research Special Project (HARS-22-02-G3).

Data Availability Statement

The original contributions presented in the study are included in the article/Supplementary Materials, further inquiries can be directed to the corresponding authors.

Conflicts of Interest

Author Shaofeng Jia was employed by the company Syngenta (China) Investment Co., Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Microorganisms 12 02551 g001
Figure 1. Phylogenetic tree of glycosyltransferases from Colletotrichum graminicola. Note: CgGTs are divided into nine groups (I–IX) and each color represents a group.
Figure 1. Phylogenetic tree of glycosyltransferases from Colletotrichum graminicola. Note: CgGTs are divided into nine groups (I–IX) and each color represents a group.
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Microorganisms 12 02551 g002
Figure 2. The motifs of CgGTs. Note: Boxes of different colors represent different conserved motifs.
Figure 2. The motifs of CgGTs. Note: Boxes of different colors represent different conserved motifs.
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Microorganisms 12 02551 g003
Figure 3. Cis-acting regulatory elements in the promoter regions of CgGT genes. Note: Different colored boxes represent different cis-acting regulatory elements.
Figure 3. Cis-acting regulatory elements in the promoter regions of CgGT genes. Note: Different colored boxes represent different cis-acting regulatory elements.
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Microorganisms 12 02551 g004
Figure 4. The numbers of predicted cis-acting regulatory elements in the promoter regions of CgGT genes.
Figure 4. The numbers of predicted cis-acting regulatory elements in the promoter regions of CgGT genes.
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Microorganisms 12 02551 g005
Figure 5. Gene ontology enrichment analysis of CgGT genes.
Figure 5. Gene ontology enrichment analysis of CgGT genes.
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Microorganisms 12 02551 g006
Figure 6. The expression level of CgGTs based on RNA-seq data. Note: CgGT genes were categorized into seven distinct classes (I–VII) based on expression profiles. Red and green indicate high and low expression levels of CgGTs, respectively.
Figure 6. The expression level of CgGTs based on RNA-seq data. Note: CgGT genes were categorized into seven distinct classes (I–VII) based on expression profiles. Red and green indicate high and low expression levels of CgGTs, respectively.
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Microorganisms 12 02551 g007
Figure 7. RT-qPCR verification of CgGT expression pattern. Note: * p < 0.05, ** p < 0.01, *** p < 0.001.
Figure 7. RT-qPCR verification of CgGT expression pattern. Note: * p < 0.05, ** p < 0.01, *** p < 0.001.
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Table 1. Characteristics of putative glycosyltransferases in Colletotrichum graminicola.
Table 1. Characteristics of putative glycosyltransferases in Colletotrichum graminicola.
Proposed Gene NameGene IDCDS Length (bp)Protein Length (aa) Mw (KDa)pIGRAVYPredicted Subcellular Localization
CgGT1EVM0000312111937242.136.73−0.221extracellular, including cell wall
CgGT2EVM0000372214271381.256.05−0.448cytosol
CgGT3EVM0000427101433738.216.31−0.313extracellular, including cell wall
CgGT4EVM0000494224474782.135.77−0.728nucleus
CgGT5EVM000052058231940221.57.49−0.156plasma membrane
CgGT6EVM000057744281475164.955.08−0.286plasma membrane
CgGT7EVM0000595224774883.708.940.207plasma membrane
CgGT8EVM0000840156652158.418.01−0.019mitochondrion
CgGT9EVM000087871723826.588.79−0.104mitochondrion
CgGT10EVM0001034165955261.659.04−0.142cytosol
CgGT11EVM0001072134144649.095.77−0.052cytosol
CgGT12EVM000151052891762199.246.85−0.414cytosol
CgGT13EVM0001638113737844.076.68−0.425extracellular, including cell wall
CgGT14EVM0001682129643146.305.430.028cytosol
CgGT15EVM00016892931976109.096.71−0.022plasma membrane
CgGT16EVM0001718156352059.606.29−0.578extracellular, including cell wall
CgGT17EVM0001804123040946.035.95−0.189extracellular, including cell wall
CgGT18EVM0001965130243349.349.18−0.012mitochondrion
CgGT19EVM00020012742913103.246.13−0.172plasma membrane
CgGT20EVM0002094210670178.527.03−0.525mitochondrion
CgGT21EVM0002104159653161.218.26−0.510plasma membrane
CgGT22EVM0002238110436741.317.75−0.380extracellular, including cell wall
CgGT23EVM0002239174358062.329.660.430plasma membrane
CgGT24EVM0002267221773883.807.38−0.011plasma membrane
CgGT25EVM0002284129343048.389.470.511plasma membrane
CgGT26EVM0002503138346053.155.31−0.468extracellular, including cell wall
CgGT27EVM000250671732390264.755.71−0.164plasma membrane
CgGT28EVM0002539224774883.786.40−0.314mitochondrion
CgGT29EVM0002695220573483.179.280.203mitochondrion
CgGT30EVM0002790128742850.205.89−0.724Golgi apparatus
CgGT31EVM0002951158452758.456.17−0.307extracellular, including cell wall
CgGT32EVM0003094126642147.717.71−0.271mitochondrion
CgGT33EVM0003195117939245.806.02−0.564mitochondrion
CgGT34EVM0003225180360067.319.540.381plasma membrane
CgGT35EVM0003259180960269.159.70−0.719plasma membrane
CgGT36EVM0003732120940245.637.67−0.023cytosol
CgGT37EVM0003755192063972.948.81−0.531mitochondrion
CgGT38EVM000389356011866207.166.65−0.204plasma membrane
CgGT39EVM0003945120039943.586.87−0.011plasma membrane
CgGT40EVM000398130931030116.356.17−0.258plasma membrane
CgGT41EVM0004307118239346.505.76−0.637extracellular, including cell wall
CgGT42EVM0004462149449756.996.09−0.176Golgi apparatus
CgGT43EVM0004588123341045.478.94−0.391plasma membrane
CgGT44EVM000471239271308141.695.69−0.447cytosol
CgGT45EVM000472372902429272.736.30−0.216plasma membrane
CgGT46EVM0004757155151659.079.420.272plasma membrane
CgGT47EVM000489653521783197.365.54−0.179plasma membrane
CgGT48EVM000497248241607177.578.27−0.373nucleus
CgGT49EVM000497537921263140.207.16−0.328plasma membrane
CgGT50EVM0005005150950257.919.00−0.173plasma membrane
CgGT51EVM000521136751224137.198.82−0.303plasma membrane
CgGT52EVM0005219162654159.939.05−0.034mitochondrion
CgGT53EVM0005273133544450.516.50−0.422mitochondrion
CgGT54EVM0005326139546449.505.77−0.018mitochondrion
CgGT55EVM0005437147649154.505.89−0.157mitochondrion
CgGT56EVM0005573161153658.655.85−0.167extracellular, including cell wall
CgGT57EVM0005623195064974.188.77−0.039plasma membrane
CgGT58EVM0005717143747853.558.74−0.056plasma membrane
CgGT59EVM0005768148249356.505.88−0.605nucleus
CgGT60EVM00057892745914100.189.22−0.264plasma membrane
CgGT61EVM0005882159953259.835.48−0.261cytosol
CgGT62EVM0006207142847552.695.54−0.356extracellular, including cell wall
CgGT63EVM0006283187862570.689.460.116plasma membrane
CgGT64EVM0006286186362071.526.78−0.642Golgi apparatus
CgGT65EVM0006578159653159.565.76−0.334extracellular, including cell wall
CgGT66EVM0006633129943245.576.140.011mitochondrion
CgGT67EVM000683390330033.556.520.158plasma membrane
CgGT68EVM0006930216972282.175.73−0.289plasma membrane
CgGT69EVM00070872712903102.806.00−0.486nucleus
CgGT70EVM0007165130243349.725.71−0.313extracellular, including cell wall
CgGT71EVM0007204121540446.016.37−0.402mitochondrion
CgGT72EVM000722030601019114.745.97−0.471nucleus
CgGT73EVM0007383166255362.316.17−0.386plasma membrane
CgGT74EVM0007715133844550.676.17−0.333extracellular, including cell wall
CgGT75EVM0007775146148655.295.55−0.492extracellular, including cell wall
CgGT76EVM0007855148549455.725.39−0.199extracellular, including cell wall
CgGT77EVM000805294231335.949.08−0.396plasma membrane
CgGT78EVM0008073238279389.938.97−0.074plasma membrane
CgGT79EVM0008174216672178.617.96−0.026plasma membrane
CgGT80EVM0008429140746851.598.230.039extracellular, including cell wall
CgGT81EVM0008593111937242.425.63−0.373Endoplasmic reticulum
CgGT82EVM0008674131443747.139.140.584plasma membrane
CgGT83EVM000896391230333.717.13−0.159mitochondrion
CgGT84EVM0009050138646151.977.26−0.378mitochondrion
CgGT85EVM0009152232277388.168.86−0.089plasma membrane
CgGT86EVM00092532856951106.496.64−0.195plasma membrane
CgGT87EVM0009723265288399.225.570.019plasma membrane
CgGT88EVM0009853206768877.577.88−0.041plasma membrane
CgGT89EVM001007272324026.305.06−0.128mitochondrion
CgGT90EVM0010156180360067.928.950.156plasma membrane
CgGT91EVM0010249108336041.408.15−0.432plasma membrane
CgGT92EVM00102692664887100.265.62−0.346cytosol
CgGT93EVM0010555115238343.464.85−0.213cytosol
CgGT94EVM0010706254784895.616.42−0.239plasma membrane
CgGT95EVM0010719145248354.166.200.067cytosol
CgGT96EVM0010739102033938.345.37−0.518cytosol
CgGT97EVM0010808152150658.495.98−0.477plasma membrane
CgGT98EVM001082270562351262.096.01−0.176plasma membrane
CgGT99EVM001116638071268137.488.75−0.602cytosol
CgGT100EVM00112802712903101.025.57−0.034plasma membrane
CgGT101EVM0011800115538443.206.97−0.264extracellular, including cell wall
ID: identity; bp: base pair; aa: amino acids; KDa: kilo dalton; pI: isoelectric point; Mw: molecular weight; GRAVY: grand average of hydropathicity.
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Wang, Y.; Li, H.; Chang, J.; Zhang, Y.; Li, J.; Jia, S.; Shi, Y. Genome-Wide Identification and Analysis of Glycosyltransferases in Colletotrichum graminicola. Microorganisms 2024, 12, 2551. https://doi.org/10.3390/microorganisms12122551

AMA Style

Wang Y, Li H, Chang J, Zhang Y, Li J, Jia S, Shi Y. Genome-Wide Identification and Analysis of Glycosyltransferases in Colletotrichum graminicola. Microorganisms. 2024; 12(12):2551. https://doi.org/10.3390/microorganisms12122551

Chicago/Turabian Style

Wang, Yafei, Honglian Li, Jiaxin Chang, Yu Zhang, Jinyao Li, Shaofeng Jia, and Yan Shi. 2024. "Genome-Wide Identification and Analysis of Glycosyltransferases in Colletotrichum graminicola" Microorganisms 12, no. 12: 2551. https://doi.org/10.3390/microorganisms12122551

APA Style

Wang, Y., Li, H., Chang, J., Zhang, Y., Li, J., Jia, S., & Shi, Y. (2024). Genome-Wide Identification and Analysis of Glycosyltransferases in Colletotrichum graminicola. Microorganisms, 12(12), 2551. https://doi.org/10.3390/microorganisms12122551

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