Subcellular Localization Prediction Research Articles

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 1,728 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).

Genome-Wide Comparative Analysis of the Cytochrome P450 Monooxygenase Family in 19 Aphid Species and Their Expression Analysis in 4 Cereal Crop Aphids.

Cytochrome P450 monooxygenases (CYP450s) play a variety of physiological roles, including pesticide resistance, plant allelochemical detoxification, and hormone metabolism catalysis. However, limited information is available on the classification and expression profiles of the CYP450 gene family in aphid species. This is the first study to identify the cytochrome P450 gene family in 19 aphid species at the whole genome level. A total of 1100 CYP450 genes were identified in 19 aphid species. Three hundred CYP450 genes belonged to six cereal crop aphid species, which were further classified into four subfamilies according to the phylogenetic relationship. The conserved motifs, exon-intron structures, and genomic organization of the same subfamilies were similar. Predictions of subcellular localization revealed that the endoplasmic reticulum harbored the majority of CYP450 proteins. In Sitobion avenae and Rhopalosiphum maidis, the increase in the CYP450 gene was primarily caused by segmental duplication events. However, only tandem duplication occurred in the CYP450 gene family of Diuraphis noxia, Rhopalosiphum padi, Schizaphis graminum, and Sitobion miscanthi. Synteny analysis found three continuous colinear CYP450 gene pairs among six cereal crop aphid species. Furthermore, we obtained the expression profiles of four cereal crop aphids, including R. padi, D. noxia, S. graminum, and S. avenae. Differential expression analysis provided growth stage specificity genes, tissue specificity genes, organ specificity genes and some detoxification metabolic genes among these four cereal crop aphids. Meanwhile, their expression patterns were showed. The related functions and pathways of CYP450s were revealed by GO and KEGG enrichment analysis. Above all, we picked the differentially expressed CYP450 genes from all of the differentially expressed genes (DEGs). These differentially expressed CYP450 genes provided some new potential candidates for aphid control and management. This work establishes the foundation for further investigations into the regulatory functions of the CYP450 gene family in aphid species and beyond.

Compilation of resources on subcellular localization of lncRNA

Long non-coding RNAs (lncRNAs) play a vital role in biological processes, and their dysfunctions lead to a wide range of diseases. Due to advancements in sequencing technology, more than 20,000 lncRNA transcripts have been identified in humans, almost equivalent to coding transcripts. One crucial aspect in annotating lncRNA function is predicting their subcellular localization, which often determines their functional roles within cells. This review aims to cover the experimental techniques, databases, and in silico tools developed for identifying subcellular localization. Firstly, we discuss the experimental methods employed to determine the subcellular localization of lncRNAs. These techniques provide valuable insights into the precise cellular compartments where lncRNAs reside. Secondly, we explore the available computational resources and databases contributing to our understanding of lncRNAs, including information on their subcellular localization. These computational methods utilize algorithms and machine learning approaches to predict lncRNA subcellular locations using sequence and structural features. Lastly, we discuss the limitations of existing methodologies, future challenges, and potential applications of subcellular localization prediction for lncRNAs. We highlight the need for further advancements in computational methods and experimental validation to enhance the accuracy and reliability of subcellular localization predictions. To support the scientific community, we have developed a platform called LncInfo, which offers comprehensive information on lncRNAs, including their subcellular localization. This platform aims to consolidate and provide accessible resources to researchers studying lncRNAs and their functional roles (http://webs.iiitd.edu.in/raghava/lncinfo).

SCLpred-ECL: Subcellular Localization Prediction by Deep N-to-1 Convolutional Neural Networks.

The subcellular location of a protein provides valuable insights to bioinformaticians in terms of drug designs and discovery, genomics, and various other aspects of medical research. Experimental methods for protein subcellular localization determination are time-consuming and expensive, whereas computational methods, if accurate, would represent a much more efficient alternative. This article introduces an ab initio protein subcellular localization predictor based on an ensemble of Deep N-to-1 Convolutional Neural Networks. Our predictor is trained and tested on strict redundancy-reduced datasets and achieves 63% accuracy for the diverse number of classes. This predictor is a step towards bridging the gap between a protein sequence and the protein's function. It can potentially provide information about protein-protein interaction to facilitate drug design and processes like vaccine production that are essential to disease prevention.

The apple MdGA2ox7 modulates the balance between growth and stress tolerance in an anthocyanin-dependent manner

Apple (Malus domestica Borkh.) is a widely cultivated fruit crop worldwide but often suffers from abiotic stresses such as salt and cold. Gibberellic acid (GA) plays a pivotal in controlling plant development, environmental adaptability, and secondary metabolism. The GA2-oxidase (GA2ox) is responsible for the deactivation of bioactive GA. In this study, seventeen GA2-oxidase genes were identified in the apple genome, and these members could be clustered into four clades based on phylogenetic relationships and conserved domain structures. MdGA2ox7 exhibited robust expression across various tissues, responded to cold and salt treatments, and was triggered in apple fruit peels via light-induced anthocyanin accumulation. Subcellular localization prediction and experiments confirmed that MdGA2ox7 was located in the cytoplasm. Overexpression of MdGA2ox7 in Arabidopsis caused a lower level of active GA and led to GA-deficient phenotypes, such as dwarfism and delayed flowering. MdGA2ox7 alleviated cold and salt stress damage in both Arabidopsis and apple in concert with melatonin (MT). Additionally, MdGA2ox7 enhanced anthocyanin biosynthesis in apple calli and activated genes involved in anthocyanin synthesis. These findings provide new insights into the functions of apple GA2ox in regulating development, stress tolerance, and secondary metabolism.

De Novo Multi-Omics Pathway Analysis Designed for Prior Data Independent Inference of Cell Signaling Pathways

New tools for cell signaling pathway inference from multi-omics data that are independent of previous knowledge are needed. Here, we propose a new de novo method, the de novo multi-omics pathway analysis (DMPA), to model and combine omics data into network modules and pathways. DMPA was validated with published omics data and was found accurate in discovering reported molecular associations in transcriptome, interactome, phosphoproteome, methylome, and metabolomics data, and signaling pathways in multi-omics data. DMPA was benchmarked against module discovery and multi-omics integration methods and outperformed previous methods in module and pathway discovery especially when applied to datasets of relatively low sample sizes. Transcription factor, kinase, subcellular location, and function prediction algorithms were devised for transcriptome, phosphoproteome, and interactome modules and pathways, respectively. To apply DMPA in a biologically relevant context, interactome, phosphoproteome, transcriptome, and proteome data were collected from analyses carried out using melanoma cells to address gamma-secretase cleavage-dependent signaling characteristics of the receptor tyrosine kinase TYRO3. The pathways modeled with DMPA reflected the predicted function and its direction in validation experiments.

MRNA-CLA: An interpretable deep learning approach for predicting mRNA subcellular localization

Messenger RNA (mRNA) is vital for post-transcriptional gene regulation, acting as the direct template for protein synthesis. However, the methods available for predicting mRNA subcellular localization need to be improved and enhanced. Notably, few existing algorithms can annotate mRNA sequences with multiple localizations. In this work, we propose the mRNA-CLA, an innovative multi-label subcellular localization prediction framework for mRNA, leveraging a deep learning approach with a multi-head self-attention mechanism. The framework employs a multi-scale convolutional layer to extract sequence features across different regions and uses a self-attention mechanism explicitly designed for each sequence. Paired with Position Weight Matrices (PWMs) derived from the convolutional neural network layers, our model offers interpretability in the analysis. In particular, we perform a base-level analysis of mRNA sequences from diverse subcellular localizations to determine the nucleotide specificity corresponding to each site. Our evaluations demonstrate that the mRNA-CLA model substantially outperforms existing methods and tools.

GP-HTNLoc: A graph prototype head-tail network-based model for multi-label subcellular localization prediction of ncRNAs

Numerous research results demonstrated that understanding the subcellular localization of non-coding RNAs (ncRNAs) is pivotal in elucidating their roles and regulatory mechanisms in cells. Despite the existence of over ten computational models dedicated to predicting the subcellular localization of ncRNAs, a majority of these models are designed solely for single-label prediction. In reality, ncRNAs often exhibit localization across multiple subcellular compartments. Furthermore, the existing multi-label localization prediction models are insufficient in addressing the challenges posed by the scarcity of training samples and class imbalance in ncRNA dataset. To address these limitations, this study proposes a novel multi-label localization prediction model for ncRNAs, named GP-HTNLoc. To mitigate class imbalance, GP-HTNLoc adopts separate training approaches for head and tail location labels. Additionally, GP-HTNLoc introduces a pioneering graph prototype module to enhance its performance in small-sample, multi-label scenarios. The experimental results based on 10-fold cross-validation on benchmark datasets demonstrate that GP-HTNLoc achieves competitive predictive performance. The average results from 10 rounds of testing on an independent dataset show that GP-HTNLoc outperforms the best existing models on the human lncRNA, human snoRNA, and human miRNA subsets, with average precision improvements of 31.5%, 14.2%, and 5.6%, respectively, reaching 0.685, 0.632, and 0.704. A user-friendly online GP-HTNLoc server is accessible at https://56s8y85390.goho.co.

Identification of HSP70 gene family members in Fritillaria cirrhosa and expression analysis in different tissues under high temperature stress

The heat shock protein 70 family contains the stress proteins ubiquitous in plants. These proteins are involved in the responses to different abiotic stress conditions and have highly conserved gene sequences. However, little is known about the molecular mechanisms of Fritillaria cirrhosa in response to high-temperature stress. Here, 26 HSP70s, FcHSP70-1 to FcHSP70-26, were identified from the transcriptome data of root, bulb, stem, leaf, and fruit samples of F. cirrhosa. The proteins encoded by FcHSP70s had the lengths ranging from 560 aa to 944 aa, with the molecular weight of 61.64-100.01 kDa and the theoretical isoelectric point between 5.00 and 6.59. The secondary structural elements of HSP70s were mainly random coils and α-helixes. Subcellular localization prediction revealed that FcHSP70s were distributed in mitochondria, chloroplasts, nuclei, endoplasmic reticulum, and cytoplasm. The phylogenetic tree showed that 7 members of the HSP70 family belonged to the Dnak subfamily and 19 members belonged to the HSP110/SSE subfamily. In addition, the qRT-PCR results showed that the expression of FcHSP70-5, FcHSP70-8, FcHSP70-17, FcHSP70-18, and FcHSP70-23 in F. cirrhosa was significantly up-regulated at 35 ℃, which indicated that these genes might play a role in the response to high temperature stress. In addition, compared with other tissues, stems and leaves were sensitive to high temperature stress, with the expression of 18 genes up-regulated by 18.18 and 8.03 folds on average, respectively. These findings provide valuable information about the molecular mechanism of HSP70s of F. cirrhosa in response to high temperature stress.

Identification and expression profiles of Tubby‑like proteins coding genes in walnut (Juglans regia L.) in response to stress and hormone treatments

Tubby-like proteins (TLPs) constitute a diverse multigene family found across a broad range of eukaryotic organisms, from single-celled to multicellular eukaryotes. Despite their importance, the existence of TLPs in walnuts (Juglans regia L.) has not been reported until now. In this study, we identified 12 members of the JrTLP gene family in the walnut genome, revealing a pattern of gene replication events. Notably, all JrTLPs exhibited a split gene structure, containing two to eight introns, and these genes could be divided into five distinct categories based on their evolutionary relationships. The majority of TLP proteins possess two signature domains: the F-box and Tubby domains. Subcellular localization prediction and experiments confirmed that JrTLP2 was located in the nucleus and membrane. Expression profiling revealed that multiple JrTLPs respond to a range of stimuli, including pathogen infection, hormonal treatment (such as auxin, ABA, MeJA, and GA), and abiotic stress conditions such as cold, heat, and salt. This study represents the first comprehensive identification of the walnut TLP family, providing valuable insights into the function and regulation of TLP in walnut and laying the foundation for future functional dissection, particularly in the context of stress tolerance.

Genome-wide identification of toll-like receptors in Octopus sinensis and expression analysis in response to different PAMPs stimulation

Toll-like receptors (TLRs) are one of the extensively studied pattern recognition receptors (PRRs) and play crucial roles in the immune responses of vertebrates and invertebrates. In this study, 14 TLR genes were identified from the genome-wide data of Octopus sinensis. Protein structural domain analysis showed that most TLR proteins had three main structural domains: extracellular leucine-rich repeats (LRR), transmembrane structural domains, and intracellular Toll/IL-1 receptor domain (TIR). The results of subcellular localization prediction showed that the TLRs of O. sinensis were mainly located on the plasma membrane. The results of quantitative real-time PCR (qPCR) showed that the detected TLR genes were differentially expressed in the hemolymph, white bodies, hepatopancreas, gills, gill heart, intestine, kidney, and salivary gland of O. sinensis. Furthermore, the present study investigated the expression changes of O. sinensis TLR genes in hemolymph, white bodies, gills, and hepatopancreas in different phases (6 h, 12 h, 24 h, 48 h) after stimulation with PGN, poly(I: C) and Vibrio parahaemolyticus. The expression of most of the TLR genes was upregulated at different time points after infection with pathogens or stimulation with PAMPs, a few genes were unchanged or even down-regulated, and many of the TLR genes were much higher after V. parahaemolyticus infection than after PGN and poly(I:C) stimulation. The results of this study contribute to a better understanding of the molecular immune mechanisms of O. sinensis TLRs genes in resistance to pathogen stimulation.

In silico analysis of the wheat BBX gene family and identification of candidate genes for seed dormancy and germination

BackgroundB-box (BBX) proteins are a type of zinc finger proteins containing one or two B-box domains. They play important roles in development and diverse stress responses of plants, yet their roles in wheat remain unclear.ResultsIn this study, 96 BBX genes were identified in the wheat genome and classified into five subfamilies. Subcellular localization prediction results showed that 68 TaBBXs were localized in the nucleus. Protein interaction prediction analysis indicated that interaction was one way that these proteins exerted their functions. Promoter analysis indicated that TaBBXs may play important roles in light signal, hormone, and stress responses. qRT-PCR analysis revealed that 14 TaBBXs were highly expressed in seeds compared with other tissues. These were probably involved in seed dormancy and germination, and their expression patterns were investigated during dormancy acquisition and release in the seeds of wheat varieties Jing 411 and Hongmangchun 21, showing significant differences in seed dormancy and germination phenotypes. Subcellular localization analysis confirmed that the three candidates TaBBX2-2 A, TaBBX4-2 A, and TaBBX11-2D were nuclear proteins. Transcriptional self-activation experiments further demonstrated that TaBBX4-2A was transcriptionally active, but TaBBX2-2A and TaBBX11-2D were not. Protein interaction analysis revealed that TaBBX2-2A, TaBBX4-2A, and TaBBX11-2D had no interaction with each other, while TaBBX2-2A and TaBBX11-2D interacted with each other, indicating that TaBBX4-2A may regulate seed dormancy and germination by transcriptional regulation, and TaBBX2-2A and TaBBX11-2D may regulate seed dormancy and germination by forming a homologous complex.ConclusionsIn this study, the wheat BBX gene family was identified and characterized at the genomic level by bioinformatics analysis. These observations provide a theoretical basis for future studies on the functions of BBXs in wheat and other species.

Genome-wide identification of polyamine metabolism and ethylene synthesis genes in Chenopodium quinoa Willd. and their responses to low-temperature stress

BackgroundQuinoa (Chenopodium quinoa Willd.) is valued for its nutritional richness. However, pre-harvest sprouting poses a significant threat to yield and grain quality. This study aims to enhance our understanding of pre-harvest sprouting mitigation strategies, specifically through delayed sowing and avoiding rainy seasons during quinoa maturation. The overarching goal is to identify cold-resistant varieties and unravel the molecular mechanisms behind the low-temperature response of quinoa. We employed bioinformatics and genomics tools for a comprehensive genome-wide analysis of polyamines (PAs) and ethylene synthesis gene families in quinoa under low-temperature stress.ResultsThis involved the identification of 37 PA biosynthesis and 30 PA catabolism genes, alongside 227 ethylene synthesis. Structural and phylogenetic analyses showcased conserved patterns, and subcellular localization predictions indicated diverse cellular distributions. The results indicate that the PA metabolism of quinoa is closely linked to ethylene synthesis, with multiple genes showing an upregulation in response to cold stress. However, differential expression within gene families suggests a nuanced regulatory network.ConclusionsOverall, this study contributes valuable insights for the functional characterization of the PA metabolism and ethylene synthesis of quinoa, which emphasize their roles in plant low-temperature tolerance and providing a foundation for future research in this domain.

A validation strategy to assess the role of phase separation as a determinant of macromolecular localization

Liquid-liquid phase separation (LLPS) of putative assembly scaffolds has been proposed to drive the biogenesis of membraneless compartments. LLPS scaffolds are usually identified through invitro LLPS assays with single macromolecules (homotypic), but the predictive value of these assays remains poorly characterized. Here, we apply a strategy to evaluate the robustness of homotypic LLPS assays. When applied to the chromosomal passenger complex (CPC), which undergoes LLPS invitro and localizes to centromeres to promote chromosome biorientation, LLPS propensity invitro emerged as an unreliable predictor of subcellular localization. Invitro CPC LLPS in aqueous buffers was enhanced by commonly used crowding agents. Conversely, diluted cytomimetic media dissolved condensates of the CPC and of several other proteins. We also show that centromeres do not seem to nucleate LLPS, nor do they promote local, spatially restrained LLPS of the CPC. Our strategy can be adapted to purported LLPS scaffolds of other membraneless compartments.