Subcellular Localization Prediction Research Articles

MMLmiRLocNet: miRNA Subcellular Localization Prediction based on Multi-view Multi-label Learning for Drug Design.

Identifying subcellular localization of microRNAs (miRNAs) is essential for comprehensive understanding of cellular function and has significant implications for drug design. In the past, several computational methods for miRNA subcellular localization is being used for uncovering multiple facets of RNA function to facilitate the biological applications. Unfortunately, most existing classification methods rely on a single sequencebased view, making the effective fusion of data from multiple heterogeneous networks a primary challenge. Inspired by multi-view multi-label learning strategy, we propose a computational method, named MMLmiRLocNet, for predicting the subcellular localizations of miRNAs. The MMLmiRLocNet predictor extracts multi-perspective sequence representations by analyzing lexical, syntactic, and semantic aspects of biological sequences. Specifically, it integrates lexical attributes derived from k-mer physicochemical profiles, syntactic characteristics obtained via word2vec embeddings, and semantic representations generated by pre-trained feature embeddings. Finally, module for extracting multi-view consensus-level features and specific-level features was constructed to capture consensus and specific features from various perspectives. The full connection networks are utilized as the output module to predict the miRNA subcellular localization. Experimental results suggest that MMLmiRLocNet outperforms existing methods in terms of F1, subACC, and Accuracy, and achieves best performance with the help of multi-view consensus features and specific features extract network.

Genome-wide analysis of the SWEET gene family and its response to powdery mildew and leaf spot infection in the common oat (Avena sativa L.)

The nutritional quality and yield of oats (Avena sativa) are often compromised by plant diseases such as red leaf, powdery mildew, and leaf spot. Sugars Will Eventually be Exported Transporters (SWEETs) are newly identified sugar transporters involved in regulating plant growth and stress responses. However, the roles of SWEET genes in biotic stress responses remain uncharacterized in oats. In this study, 13 AsSWEET genes were identified across nine chromosomes of the oat genome, all of which were predicted to contain seven transmembrane regions. Phylogenetic analysis revealed four clades of AsSWEET proteins, with high homology to SWEET proteins in the Poaceae family. Collinearity analysis demonstrated strong relationships between oat and Zea mays SWEETs. Using subcellular localization prediction tools, AsSWEET proteins were predicted to localize to the plasma membrane. Promoter analysis revealed cis-acting elements associated with light response, growth, and stress regulation. Six AsSWEET proteins were predicted to interact in a network centered on AsSWEET1a and AsSWEET11. Gene expression analysis of two oat varieties, ‘ForagePlus’ and ‘Molasses’, indicated significant expression differences in several AsSWEET genes following infection with powdery mildew or leaf spot, including AsSWEET1a, AsSWEET1b, AsSWEET2b, AsSWEET3a, AsSWEET11, and AsSWEET16. These SWEET genes are potential candidates for disease resistance in oats. This study provides a foundation for understanding the regulatory mechanisms of AsSWEET genes, particularly in response to powdery mildew and leaf spot, and offers insights for enhancing oat molecular breeding.

Genome-Wide Identification of UGT Genes and Analysis of Their Expression Profiles During Fruit Development in Walnut (Juglans regia L.)

Walnut (Juglans regia L.) possesses the ability to prevent coronary heart disease and promote cardiovascular health. This ability can be attributed to their rich content of polyphenols, particularly flavonoids. The biosynthesis of flavonoids is reliant on the catalytic activity of uridine diphosphate glycosyltransferase (UGT). However, the identification of UGTs in walnut has not been reported. In the current study, a total of 124 UGT genes containing the PSPG box were identified from the walnut genome. Based on phylogenetic analysis, the 124 UGTs could be classified into 16 distinct groups, which exhibited an uneven distribution across the 16 chromosomes. Subcellular localization prediction analysis revealed that approximately 78.23% of walnut UGT proteins were predominantly localized in the cytoplasmic compartment. Furthermore, motif annotation confirmed that motifs 1, 2, and 3 represented conserved structural features within UGT proteins, while interestingly, around 56.5% of walnut UGT members lacked introns. Through the analysis of promoter cis-regulatory elements, it was revealed that JrUGTs are involved in photoresponse, hormonal regulation, and other physiological responses. In conjunction with transcriptome analysis and quantitative expression, approximately 39% of UGT genes in walnut exhibited high expression levels during early fruit development. Correlation analysis between UGT genes’ expression and phenolic content in walnut indicated that JrUGT6, JrUGT38, JrUGT39, JrUGT58, JrUGT69, JrUGT75, and JrUGT82 might be involved in phenolic biosynthesis in walnut. This comprehensive study provides an overview of the UGT genes in walnut, serving as a valuable reference and theoretical foundation for further investigations into the biological functions of JrUGTs in flavonoid biosynthesis.

Genome-wide analysis of fatty acid desaturase (FAD) gene family in Camellia sinensis: Identification, expression and their biochemical functions in low temperature resistance

Fatty acid desaturase (FAD) is critical for unsaturated fatty acids (UFAs) biosynthesis and plays crucial roles in plants' response to low temperature. Nevertheless, a comprehensive genomic analysis of the FAD gene family in Camellia sinensis remain unreported. This study employed bioinformatics to identify 17 CsFAD genes, which are unequally distributed across 9 chromosomes. CsFAD proteins are localized to chloroplasts and/or endoplasmic reticulum (ER) by subcellular localization predictions. Phylogenetic categorization divides CsFADs into six subfamilies. The cis-elements are related to hormonal regulation and adversity response. Additionally, differential expression patterns of CsFADs across various tissues were observed. qRT-PCR analysis revealed a marked upregulation in the expression of CsSLD3 and CsSLD4 (encoding sphingolipid Δ8 desaturase) under cold stress conditions. Moreover, subcellular localization assays in tobacco leaves confirmed the presence of CsSLD3 and CsSLD4 within ER. Yeast heterologous expression demonstrated the capacity of CsSLD3/4 to transform ceramide(t18:0) into ceramide(t18:1), and overexpression of CsSLD3/4 enhanced yeast tolerance to low temperature. Thus, this comprehensive analysis of the CsFAD gene family furnishes a robust foundation for future study into the biological functions of CsFAD genes, and offers a profound insight into their regulatory roles in stress resilience.

In silico analysis and functional validation of sinf-yc genes in foxtail millet setaria italica (l.)

Nuclear transcription factor YCs (NF-YCs) are universally involved in plant development and abiotic stress response. As a typical C4 crop, foxtail millet has significant research value for studies of functional genes and mechanisms of plant stress resistance. To further investigate the correlation between the structure and function of the SiNF-YC genes in foxtail millet (Setaria italica), bioinformatic analysis of the SiNF-YCs on the subcellular localization, physicochemical properties, and cis acting elements were performed in this study. The results showed that a total of 12 SiNF-YC subfamily genes that distributed on chromosomes 1-9 were identified from the foxtail millet genome, which encoding 129-469 amino acids. The subcellular localization prediction results showed that the proteins encoded by this gene subfamily are mainly located in the nucleus, with a few being extracellular secreted. The multiple cis-elements related to drought resistance and light response are contained in the gene promoter region. Through haplotype analysis on the phenotypes of drought treated and heading dates that from five different regions, obvious haplotypes were identified except for SiNF-YC8 and SiNF-YC14. At last, drought regulation related gene SiNF-YC5 and heading date regulation related gene SiNF-YC10 were selected to explore superior gene haplotypes, laying a foundation for further exploring the functional genes involved in drought resistance and development within this gene family. Bangladesh j. Bot. 53(3): 535-543, 2024 (September)

Genome-wide identification and characterization of pectin methylesterase inhibitor gene family members related to abiotic stresses in watermelon.

Pectin is a vital component of plant cell walls and its methylation process is regulated by pectin methylesterase inhibitors (PMEIs). PMEIs regulate the structural and functional modifications of cell walls in plants and play an important role in plant processes such as seed germination, fruit ripening, and stress response. Although the PMEI gene family has been well characterized in model plants, the understanding of its molecular evolution and biological functions in watermelon remains limited. In this study, 60 ClPMEI genes were identified and characterized, revealing their dispersion on multiple chromosomes. Based on a systematic developmental analysis, these genes were classified into three subfamilies, which was further supported by the exon, intron, and conserved motif distribution. Analysis of cis-elements and expression patterns indicated that ClPMEIs might be involved in regulating the tolerance of watermelon to various abiotic stresses. Moreover, distinct ClPMEI genes exhibit specific functions under different abiotic stresses. For example, ClPMEI51 and ClPMEI54 showed a significant upregulation in expression levels during the late stage of drought treatments, whereas ClPMEI3 and ClPMEI12 displayed a significant downregulation under low-temperature induction. Subcellular localization prediction and analysis revealed that the ClPMEI family member proteins were localized to the cell membrane. This study provided an important foundation for the further exploration of the functions of ClPMEI genes in watermelon.

Genome-Wide Identification of MsICE Gene Family in Medicago sativa and Expression Analysis of the Response to Abiotic Stress

To predict the role of the MsICE gene family in the response to abiotic stress, in this study, bioinformatics analysis and real-time fluorescence quantitative PCR were performed. Alfalfa (Medicago sativa) is one of the most economically valuable crops globally. Inducer of CBF expression (ICE), which is part of the basic helix–loop–helix (bHLH) transcription factor (TF) family, acts as a key regulator of cold tolerance. Despite this, there is little information available about ICE genes in alfalfa. Therefore, we studied the function of ICE TFs in alfalfa. We identified 11 MsICE genes from the alfalfa genome and classified them into two groups. Analysis of the protein motif and gene structure revealed relatively high conservation among subgroups of the tightly clustered MsICE genes. Through synteny analysis, we detected duplication events in the MsICE gene family, suggesting that the ICE gene family was formed through fragment duplications. All the MsICE proteins were located in the nucleus according to subcellular localization predictions. The promoter cis-regulatory elements of MsICE genes are largely involved in light (Box 4), hormone (ABRE), and stress (MYB) responses. The MsICE01/MsICE07/MsICE09/MsICE10/MsICE11 genes contained MYB- and MYC-binding motifs, indicating an association with abiotic stress. The specific expression patterns of MsICE genes in leaves were revealed by examining their expression patterns in different tissues. These findings suggest that these genes may sense external environmental changes through leaves. Abiotic stress can cause striking upregulation of MsICE07 (PCA score: −4.03) and MsICE10 (PCA score: −4.05) expression. In this study, candidate genes associated with cold stress were identified, and subsequent molecular biological analyses allowed elucidation of the biological functions of these genes in alfalfa. This research provides a theoretical foundation for enhancing alfalfa yield and quality under cold conditions.

SGCL-LncLoc: An Interpretable Deep Learning Model for Improving IncRNA Subcellular Localization Prediction with Supervised Graph Contrastive Learning

SGCL-LncLoc: An Interpretable Deep Learning Model for Improving IncRNA Subcellular Localization Prediction with Supervised Graph Contrastive Learning

DRpred: A Novel Deep Learning-Based Predictor for Multi-Label mRNA Subcellular Localization Prediction by Incorporating Bayesian Inferred Prior Label Relationships.

The subcellular localization of messenger RNA (mRNA) not only helps us to understand the localization regulation of gene expression but also helps to understand the relationship between RNA localization pattern and human disease mechanism, which has profound biological and medical significance. Several predictors have been proposed for predicting the subcellular localization of mRNA. However, there is still considerable room for improvement in their predictive performance, especially regarding multi-label prediction. This study proposes a novel multi-label predictor, DRpred, for mRNA subcellular localization prediction. This predictor first utilizes Bayesian networks to capture the dependencies among labels. Subsequently, it combines these dependencies with features extracted from mRNA sequences using Word2vec, forming the input for the predictor. Finally, it employs a neural network combining BiLSTM and an attention mechanism to capture the internal relationships of the input features for mRNA subcellular localization. The experimental validation on an independent test set demonstrated that DRpred obtained a competitive predictive performance in multi-label prediction and outperformed state-of-the-art predictors in predicting single subcellular localizations, obtaining accuracies of 82.14%, 93.02%, 80.37%, 94.00%, 90.58%, 84.53%, 82.01%, 79.71%, and 85.67% for the chromatin, cytoplasm, cytosol, exosome, membrane, nucleolus, nucleoplasm, nucleus, and ribosome, respectively. It is anticipated to offer profound insights for biological and medical research.

Genome-Wide Characterization of Glyceraldehyde-3-Phosphate Dehydrogenase Genes and Their Expression Profile under Drought Stress in Quercus rubra.

Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) is crucial in plant metabolism and responses to various abiotic stresses. In the glycolysis pathway, glyceraldehyde-3-phosphate (G3P) is oxidized to 1,3-bisphosphate glycerate (1,3-BPG) through the catalytic action of GAPDH. However, the GAPDH gene family in Quercus rubra has been minimally researched. In this study, we identified 13 GAPDH-encoding genes in Q. rubra through a bioinformatics analysis of genomic data. Evolutionary studies suggest that these QrGAPDH genes are closely related to those in Glycine max and Triticum aestivum. We conducted a comprehensive whole-genome study, which included predictions of subcellular localization, gene structure analysis, protein motif identification, chromosomal placement, and analysis of cis-acting regions. We also examined the expression of GAPDH proteins and genes in various tissues of Q. rubra and under drought stress. The results indicated diverse expression patterns across different tissues and differential expression under drought conditions. Notably, the expression of Qurub.02G290300.1, Qurub.10G209800.1, and Qrub.M241600.1 significantly increased in the leaf, stem, and root tissues under drought stress. This study provides a systematic analysis of QrGAPDH genes, suggesting their pivotal roles in the drought stress response of trees.

Advancing mRNA subcellular localization prediction with graph neural network and RNA structure.

The asymmetrical distribution of expressed mRNAs tightly controls the precise synthesis of proteins within human cells. This non-uniform distribution, a cornerstone of developmental biology, plays a pivotal role in numerous cellular processes. To advance our comprehension of gene regulatory networks, it is essential to develop computational tools for accurately identifying the subcellular localizations of mRNAs. However, considering multi-localization phenomena remains limited in existing approaches, with none considering the influence of RNA's secondary structure. In this study, we propose Allocator, a multi-view parallel deep learning framework that seamlessly integrates the RNA sequence-level and structure-level information, enhancing the prediction of mRNA multi-localization. The Allocator models equip four efficient feature extractors, each designed to handle different inputs. Two are tailored for sequence-based inputs, incorporating multilayer perceptron and multi-head self-attention mechanisms. The other two are specialized in processing structure-based inputs, employing graph neural networks. Benchmarking results underscore Allocator's superiority over state-of-the-art methods, showcasing its strength in revealing intricate localization associations. The webserver of Allocator is available at http://Allocator.unimelb-biotools.cloud.edu.au; the source code and datasets are available on GitHub (https://github.com/lifuyi774/Allocator) and Zenodo (https://doi.org/10.5281/zenodo.13235798).

In silico Identification and Characterization of Novel Drug Targets in Treponema denticola (strain ATCC 35405 / DSM 14222 / CIP 103919 / JCM 8153 / KCTC 15104): A Subtractive Genomics Approach

Treponema denticola is a gram-negative, highly drug resistant bacterium found in primary dentition infections and around teeth. It causes inflammation and tissue homeostasis, linked to periodontal diseases like earlyonset periodontitis, necrotizing ulcerative gingivitis, and acute pericoronitis. Research is needed to develop powerful, cost-effective, secure, and environmentally friendly antibiotics and techniques to control and manage infections caused by this bacterium. This study exploits the sophisticated in silico subtractive genomics approach to investigate potential therapeutic targets that are exclusive to the pathogen T. denticola. The full sequencing data of the Treponema denticola (strain ATCC 35405 / DSM 14222 / CIP 103919 / JCM 8153 / KCTC 15104) proteome has facilitated the computational analysis of its genome. Our analysis found 126 proteins of the pathogen that had no resemblance to the human genome. The Database of Essential Genes (DEG) identified 12 bacterial proteins which were indispensable to the pathogen, while the KEGG Automated Annotation Server (KAAS) found in the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways database analysis of the non-homologous proteins revealed 11 T. denticola enzymes that can be targeted for drug development. Moreover, based on sub-cellular localization prediction, all selected proteins were cytoplasmic proteins and the no outer membrane proteins were present among the non-homologous proteins, and virulent protein predictions revealed no virulent proteins among the selected proteins. Therefore, eleven proteins were selected based on their involvement in unique metabolic pathways inside the pathogen that were not present in the host. The study further revealed the protein-protein interactions of these eleven essential proteins, and successfully anticipated, assessed, and verified the three-dimensional structures of these proteins. Undertaking a screening process to detect functional inhibitors for these newly revealed targets may lead to the discovery of novel therapeutic drugs that can effectively combat Treponema denticola. CBMJ 2024 July: vol. 13 no. 02 P: 251-264

Genome-Wide Identification of Glutathione S-Transferase Family from Dendrobium officinale and the Functional Characterization of DoGST5 in Cadmium Tolerance.

Glutathione S-transferases (GSTs) are members of a protein superfamily with diverse physiological functions, including cellular detoxification and protection against oxidative damage. However, there is limited research on GSTs responding to cadmium (Cd) stress. This study classified 46 GST genes in Dendrobium officinale (D. officinale) into nine groups using model construction and domain annotation. Evolutionary analysis revealed nine subfamilies with diverse physical and chemical properties. Prediction of subcellular localization revealed that half of the GST members were located in the cytoplasm. According to the expression analysis of GST family genes responding to Cd stress, DoGST5 responded significantly to Cd stress. Transient expression of DoGST5-GFP in tobacco leaves revealed that DoGST5 was localized in the cytoplasm. DoGST5 overexpression in Arabidopsis enhanced Cd tolerance by reducing Cd-induced H2O2 and O2- levels. These findings demonstrate that DoGST5 plays a critical role in enhancing Cd tolerance by balancing reactive oxygen species (ROS) levels, offering potential applications for improving plant adaptability to heavy metal stress.

Genome-wide identification, phylogeny and expression analysis of Hsf gene family in Verbena bonariensis under low-temperature stress

BackgroundThe heat shock transcription factor (Hsf) is a crucial regulator of plant stress resistance, playing a key role in plant stress response, growth, and development regulation.ResultsIn this study, we utilized bioinformatics tools to screen 25 VbHsf members, which were named VbHsf1-VbHsf25. We used bioinformatics methods to analyze the sequence structure, physicochemical properties, conserved motifs, phylogenetic evolution, chromosome localization, promoter cis-acting elements, collinearity, and gene expression of Hsf heat shock transcription factor family members under low-temperature stress. The results revealed that the majority of the Hsf genes contained motif1, motif2, and motif3, signifying that these three motifs were highly conserved in the Hsf protein sequence of Verbena bonariensis. Although there were some variations in motif deletion among the members, the domain remained highly conserved. The theoretical isoelectric point ranged from 4.17 to 9.71, with 21 members being unstable proteins and the remainder being stable proteins. Subcellular localization predictions indicated that all members were located in the nucleus. Phylogenetic analysis of the Hsf gene family in V. bonariensis and Arabidopsis thaliana revealed that the Hsf gene family of V. bonariensis could be categorized into three groups, with group A comprising 17 members and group C having at least two members. Among the 25 Hsf members, there were 1–3 exons located on seven chromosome fragments, which were unevenly distributed. Collinearity analysis demonstrated the presence of seven pairs of homologous genes in the VbHsf gene family. The Ka/Ks ratios were less than one, indicating that the VbHsf gene underwent purification selection pressure. Additionally, nine genes in V. bonariensis were found to have collinearity with A. thaliana. Promoter analysis revealed that the promoters of all VbHsf genes contained various types of cis-acting elements related to hormones and stress. Based on RNA-seq data, qRT-PCR analysis of six highly expressed genes was performed, and it was found that VbHsf5, VbHsf14, VbHsf17, VbHsf18, VbHsf20 and VbHsf21 genes were highly expressed at 12 h of low-temperature treatment, and the expression decreased after 24 h, among which VbHsf14 was up-regulated at 12 h of low-temperature by 70-fold.ConclusionsOur study may help reveal the important roles of Hsf in plant development and show insight for the further molecular breeding of V. bonariensis.

Prediction of protein subcellular localization in single cells.

The subcellular localization of a protein is important for its function and interaction with other molecules, and its mislocalization is linked to numerous diseases. While atlas-scale efforts have been made to profile protein localization across various cell lines, existing datasets only contain limited pairs of proteins and cell lines which do not cover all human proteins. We present a method that uses both protein sequences and cellular landmark images to perform Predictions of Unseen Proteins' Subcellular localization (PUPS), which can generalize to both proteins and cell lines not used for model training. PUPS combines a protein language model and an image inpainting model to utilize both protein sequence and cellular images for protein localization prediction. The protein sequence input enables generalization to unseen proteins and the cellular image input enables cell type specific prediction that captures single-cell variability. PUPS' ability to generalize to unseen proteins and cell lines enables us to assess the variability in protein localization across cell lines as well as across single cells within a cell line and to identify the biological processes associated with the proteins that have variable localization. Experimental validation shows that PUPS can be used to predict protein localization in newly performed experiments outside of the Human Protein Atlas used for training. Collectively, PUPS utilizes both protein sequences and cellular images to predict protein localization in unseen proteins and cell lines with the ability to capture single-cell variability.

Structure based functional identification of an uncharacterized protein from Coxiella burnetii involved in adipogenesis

Coxiella burnetii, the causative agent of Q fever, is an intracellular pathogen posing a significant global public health threat. There is a pressing need for dependable and effective treatments, alongside an urgency for further research into the molecular characterization of its genome. Within the genomic landscape of Coxiella burnetii, numerous hypothetical proteins remain unidentified, underscoring the necessity for in-depth study. In this study, we conducted comprehensive in silico analyses to identify and prioritize potential hypothetical protein of Coxiella burnetii, aiming to elucidate the structure and function of uncharacterized protein. Furthermore, we delved into the physicochemical properties, localization, and molecular dynamics and simulations, and assessed the primary, secondary, and tertiary structures employing a variety of bioinformatics tools. The in-silico analysis revealed that the uncharacterized protein contains a conserved Mth938-like domain, suggesting a role in preadipocyte differentiation and adipogenesis. Subcellular localization predictions indicated its presence in the cytoplasm, implicating a significant role in cellular processes. Virtual screening identified ligands with high binding affinities, suggesting the protein’s potential as a drug target against Q fever. Molecular dynamics simulations confirmed the stability of these complexes, indicating their therapeutic relevance. The findings provide a structural and functional overview of an uncharacterized protein from C. burnetii, implicating it in adipogenesis. This study underscores the power of in-silico approaches in uncovering the biological roles of uncharacterized proteins and facilitating the discovery of new therapeutic strategies. The findings provide valuable preliminary data for further investigation into the protein’s role in adipogenesis.

Structural proteomics guided annotation of vaccine targets and designing of multi-epitopes vaccine to instigate adaptive immune response against Francisella tularensis

Francisella tularensis can cause severe disease in humans via the respiratory or cutaneous routes and a case fatality ratio of up to 10 % is reported due to lack of proper antibiotic treatment, while F. novicida causes disease in severely immunocompromised individuals. Efforts are needed to develop effective vaccine candidates against Francisella species. Thus, in this study, a systematic computational work frame was used to deeply investigate the whole proteome of Francisella novicida containing 1728 proteins to develop vaccine against F. tularensis and related species. Whole-proteome analysis revealed that four proteins including (A0Q492) (A0Q7Y4), (A0Q4N4), and (A0Q5D9) are the suitable vaccine targets after the removal of homologous, paralogous and prediction of subcellular localization. These proteins were used to predict the T cell, B cell, and HTL epitopes which were joined together through suitable linkers to construct a multi-epitopes vaccine (MEVC). The MEVC was found to be highly immunogenic and non-allergenic while the physiochemical properties revealed the feasible expression and purification. Moreover, the molecular interaction of MEVC with TLR2, molecular simulation, and binding free energy analyses further validated the immune potential of the construct. According to Jcat analysis, the refined sequence demonstrates GC contents of 41.48 % and a CAI value of 1. The in-silico cloning and optimization process ensured compatibility with host codon usage, thereby facilitating efficient expression. Computational immune simulation studies underscored the capacity of MEVC to induce both primary and secondary immune responses. The conservation analysis further revealed that the selected epitopes exhibit 100 % conservation across different species and thus provides wider protection against Francisella.

Genome-Wide Analysis of Polygalacturonase Gene Family Reveals Its Role in Strawberry Softening.

Fruit softening is a prominent attribute governing both longevity on shelves and commercial worth. Polygalacturonase (PG) plays a major role in strawberry fruit softening. However, the PG gene family in strawberry has not been comprehensively analyzed. In this study, 75 FaPG genes were identified in the octoploid strawberry genome, which were classified into three groups according to phylogenetic analysis. Subcellular localization prediction indicated that FaPGs are mostly localized to the plasma membrane, cytoplasm, and chloroplasts. Moreover, the expression of FaPGs during strawberry development and ripening of 'Benihoppe' and its softer mutant was estimated. The results showed that among all 75 FaPGs, most genes exhibited low expression across developmental stages, while two group c members (FxaC_21g15770 and FxaC_20g05360) and one group b member, FxaC_19g05040, displayed relatively higher and gradual increases in their expression trends during strawberry ripening and softening. FxaC_21g15770 was selected for subsequent silencing to validate its role in strawberry softening due to the fact that it exhibited the highest and most changed expression level across different developmental stages in 'Benihoppe' and its mutant. Silencing FxaC_21g15770 could significantly improve strawberry fruit firmness without affecting fruit color, soluble solids, cellulose, and hemicellulose. Conversely, silencing FxaC_21g15770 could significantly suppress the expression of other genes related to pectin degradation such as FaPG-like, FaPL, FaPME, FaCX, FaCel, FaGlu, FaXET, and FaEG. These findings provide basic information on the FaPG gene family for further functional research and indicate that FxaC_21g15770 plays a vital role in strawberry fruit softening.

Genome-wide identification and molecular evolution of Dof transcription factors in Cyperus esculentus

Dof transcription factor family in Cyperus esculentus genome was identified and analyzed using bioinformatics. The analysis results revealed that C.esculentus genome contains 29 Dof genes (CesDof), all of which are located in the nucleus according to subcellular localization prediction. CesDof proteinrs have a range of 124 to 512 amino acids, with most being basic proteins. Their secondary structure was mainly irregular curl. The promoter sequence of CesDof genes contains cis-acting elements that respond to light, drought, hormones, low temperature, and circadian rhythm. Codon preference analysis showed that CesDof genes' codon preference ends in T/A. Collinearity analysis revealed that C.esculentus had three pairs of collinear CesDof genes. Additionally, there were 15 pairs of collinear genes between C.esculentus and Arabidopsis thaliana. The genetic relationship between C.esculentus and Rhynchospora pubera was found to be the closest. Phylogenetic tree analysis revealed that 29 CesDof genes of C.esculentus can be classified into 4 subgroups. Additionally, 144 miRNAs were predicted to target these CesDof genes. Furthermore, protein interaction analysis indicated that 15 Dof proteins in C.esculentus had interactions. The qRT-PCR verification results of drought stress and salt stress treatment experiments showed that most CesDof genes were involved in drought stress and salt stress responses, and the gene expression trends under drought stress and salt stress conditions were consistent. These results lay a theoretical foundation for further studying the molecular functions of Dof gene family in C.esculentus and its molecular mechanisms in regulating the life activities of C.esculentus.

Identification of Wheat Glutamate Synthetase Gene Family and Expression Analysis under Nitrogen Stress.

Nitrogen (N), as the main component of biological macromolecules, maintains the basic process of plant growth and development. GOGAT, as a key enzyme in the N assimilation process, catalyzes α-ketoglutaric acid and glutamine to form glutamate. In this study, six GOGAT genes in wheat (Triticum aestivum L.) were identified and classified into two subfamilies, Fd-GOGAT (TaGOGAT2s) and NADH-GOGAT (TaGOGAT3s), according to the type of electron donor. Subcellular localization prediction showed that TaGOGAT3-D was localized in mitochondria and that the other five TaGOGATs were localized in chloroplasts. Via the analysis of promoter elements, many binding sites related to growth and development, hormone regulation and plant stress resistance regulations were found on the TaGOGAT promoters. The tissue-specificity expression analysis showed that TaGOGAT2s were mainly expressed in wheat leaves and flag leaves, while TaGOGAT3s were highly expressed in roots and leaves. The expression level of TaGOGATs and the enzyme activity of TaGOGAT3s in the leaves and roots of wheat seedlings were influenced by the treatment of N deficiency. This study conducted a systematic analysis of wheat GOGAT genes, providing a theoretical basis not only for the functional analysis of TaGOGATs, but also for the study of wheat nitrogen use efficiency (NUE).