CropPAL for discovering divergence in protein subcellular location in crops to support strategies for molecular crop breeding

Reliability of plastid and mitochondrial localisation prediction declines rapidly with the evolutionary distance to the training set increasing

Mitochondria and plastids import thousands of proteins. Their experimental localisation remains a frequent task, but can be resource-intensive and sometimes impossible. Hence, hundreds of studies make use of algorithms that predict a localisation based on a protein's sequence. Their reliability across evolutionary diverse species is unknown. Here, we evaluate the performance of common algorithms (TargetP, Localizer and WoLFPSORT) for four photosynthetic eukaryotes (Arabidopsis thaliana, Zea mays, Physcomitrium patens, and Chlamydomonas reinhardtii) for which experimental plastid and mitochondrial proteome data is available, and 171 eukaryotes using orthology inferences. The match between predictions and experimental data ranges from 75% to as low as 2%. Results worsen as the evolutionary distance between training and query species increases, especially for plant mitochondria for which performance borders on random sampling. Specificity, sensitivity and precision analyses highlight cross-organelle errors and uncover the evolutionary divergence of organelles as the main driver of current performance issues. The results encourage to train the next generation of neural networks on an evolutionary more diverse set of organelle proteins for optimizing performance and reliability.

SOS1 gene family in mangrove (Kandelia obovata): Genome-wide identification, characterization, and expression analyses under salt and copper stress

BACKGROUND

Salt Overly Sensitive 1 (SOS1), a plasma membrane Na+/H+ exchanger, is essential for plant salt tolerance. Salt damage is a significant abiotic stress that impacts plant species globally. All living organisms require copper (Cu), a necessary micronutrient and a protein cofactor for many biological and physiological processes. High Cu concentrations, however, may result in pollution that inhibits the growth and development of plants. The function and production of mangrove ecosystems are significantly impacted by rising salinity and copper contamination.

RESULTS

A genome-wide analysis and bioinformatics techniques were used in this study to identify 20 SOS1 genes in the genome of Kandelia obovata. Most of the SOS1 genes were found on the plasma membrane and dispersed over 11 of the 18 chromosomes. Based on phylogenetic analysis, KoSOS1s can be categorized into four groups, similar to Solanum tuberosum. Kandelia obovata's SOS1 gene family expanded due to tandem and segmental duplication. These SOS1 homologs shared similar protein structures, according to the results of the conserved motif analysis. The coding regions of 20 KoSOS1 genes consist of amino acids ranging from 466 to 1221, while the exons include amino acids ranging from 3 to 23. In addition, we found that the 2.0 kb upstream promoter region of the KoSOS1s gene contains several cis-elements associated with phytohormones and stress responses. According to the expression experiments, seven randomly chosen genes experienced up- and down-regulation of their expression levels in response to copper (CuCl2) and salt stressors.

CONCLUSIONS

For the first time, this work systematically identified SOS1 genes in Kandelia obovata. Our investigations also encompassed physicochemical properties, evolution, and expression patterns, thereby furnishing a theoretical framework for subsequent research endeavours aimed at functionally characterizing the Kandelia obovata SOS1 genes throughout the life cycle of plants.

Dataset of wheat HSP90.2 chaperome

Wheat (Triticum aestivum L.) is one of the world's most important staple crops, whose production is critical to feed the expanding population worldwide. The 90-kDa Heat Shock Protein 90 (HSP90) is a highly abundant chaperone protein involved in multiple cellular processes. It facilitates the folding of nascent preproteins for their maturation and functioning. This data described HSP90.2 clients identified from the whole genome of wheat. The HSP90.2 chaperome contains over 1500 proteins, most detected by the C terminus and full-length of HSP90.2. Over 60 % of the clients reside in the cytosol, nucleus, and chloroplasts. Cytoskeleton-related proteins are enriched in the chaperome of the N terminus of HSP90.2. The clients of the middle part of HSP90.2 contains several factors involved in ethylene biosynthesis and extracellular vesicle or organelle-related activities. Some clients related to plant hypersensitive response are induced by stripe rust. The presented dataset could isolate proteins regulated by HSP90.2 at the post-translational level.

Genome-Wide Characterization of Berberine Bridge Enzyme Gene Family in Wheat (Triticum aestivum L.) and the Positive Regulatory Role of TaBBE64 in Response to Wheat Stripe Rust

Berberine bridge enzymes (BBEs), functioning as carbonate oxidases, enhance disease resistance in Arabidopsis and tobacco. However, the understanding of BBEs' role in monocots against pathogens remains limited. This study identified 81 TaBBEs with FAD_binding_4 and BBE domains. Phylogenetic analysis revealed a separation of the BBE gene family between monocots and dicots. Notably, RNA-seq showed TaBBE64's significant induction by both pathogen-associated molecular pattern treatment and Puccinia striiformis f. sp. tritici (Pst) infection at early stages. Subcellular localization revealed TaBBE64 at the cytoplasmic membrane. Knocking down TaBBE64 compromised wheat's Pst resistance, reducing reactive oxygen species and promoting fungal growth, confirming its positive role. Molecular docking and enzyme activity assays confirmed TaBBE64's glucose oxidation to produce H2O2. Since Pst relies on living wheat cells for carbohydrate absorption, TaBBE64's promotion of glucose oxidation limits fungal growth and resists pathogen infection. This study sheds light on BBEs' role in wheat resistance against biotrophic fungi.

Comprehensive study of serine/arginine-rich (SR) gene family in rice: characterization, evolution and expression analysis

As important regulators of alternative splicing (AS) events, serine/arginine (SR)-rich proteins play indispensable roles in the growth and development of organisms. Until now, the study of SR genes has been lacking in plants. In the current study, we performed genome-wide analysis on the SR gene family in rice. A total of 24 OsSR genes were phylogenetically classified into seven groups, corresponding to seven subfamilies. The OsSR genes' structures, distribution of conserved domains, and protein tertiary structure of OsSR were conserved within each subfamily. The synteny analysis revealed that segmental duplication events were critical for the expansion of OsSR gene family. Moreover, interspecific synteny revealed the distribution of orthologous SR gene pairs between rice and Arabidopsis, sorghum, wheat, and maize. Among all OsSR genes, 14 genes exhibited NAGNAG acceptors, and only four OsSR genes had AS events on the NAGNAG acceptors. Furthermore, the distinct tissue-specific expression patterns of OsSR genes showed that these genes may function in different developmental stages in rice. The AS patterns on the same OsSR gene were variable among the root, stem, leaf, and grains at different filling stages, and some isoforms could only be detected in one or a few of tested tissues. Meanwhile, our results showed that the expression of some OsSR genes changed dramatically under ABA, GA, salt, drought, cold or heat treatment, which were related to the wide distribution of corresponding cis-elements in their promoter regions, suggesting their specific roles in stress and hormone response. This research facilitates our understanding of SR gene family in rice and provides clues for further exploration of the function of OsSR genes.

Genome-wide characterization of SOS1 gene family in potato (Solanum tuberosum) and expression analyses under salt and hormone stress

Salt Overly Sensitive 1 (SOS1) is one of the members of the Salt Overly Sensitive (SOS) signaling pathway and plays critical salt tolerance determinant in plants, while the characterization of the SOS1 family in potato (Solanum tuberosum) is lacking. In this study, 37 StSOS1s were identified and found to be unevenly distributed across 10 chromosomes, with most of them located on the plasma membrane. Promoter analysis revealed that the majority of these StSOS1 genes contain abundant cis-elements involved in various abiotic stress responses. Tissue specific expression showed that 21 of the 37 StSOS1s were widely expressed in various tissues or organs of the potato. Molecular interaction network analysis suggests that 25 StSOS1s may interact with other proteins involved in potassium ion transmembrane transport, response to salt stress, and cellular processes. In addition, collinearity analysis showed that 17, 8, 1 and 5 of orthologous StSOS1 genes were paired with those in tomato, pepper, tobacco, and Arabidopsis, respectively. Furthermore, RT-qPCR results revealed that the expression of StSOS1s were significant modulated by various abiotic stresses, in particular salt and abscisic acid stress. Furthermore, subcellular localization in Nicotiana benthamiana suggested that StSOS1-13 was located on the plasma membrane. These results extend the comprehensive overview of the StSOS1 gene family and set the stage for further analysis of the function of genes in SOS and hormone signaling pathways.

Crop Proteomics under Abiotic Stress: From Data to Insights

Food security is a major challenge in the present world due to erratic weather and climatic changes. Environmental stress negatively affects plant growth and development which leads to reduced crop yields. Technological advancements have caused remarkable improvements in crop-breeding programs. Proteins have an indispensable role in developing stress resilience and tolerance in crops. Genomic and biotechnological advancements have made the process of crop improvement more accurate and targeted. Proteomic studies provide the information required for such targeted approaches. The crosstalk among cellular components is being analyzed by subcellular proteomics. Additionally, the functional diversity of proteins is being unraveled by post-translational modifications during abiotic stress. The exploration of precise cellular responses and the networking among different cellular organelles help in the prediction of signaling pathways and protein-protein interactions. High-throughput mass-spectrometry-based protein studies are now possible due to incremental advancements in mass-spectrometry techniques, sample protocols, and bioinformatic tools as well as the increasing availability of plant genome sequence information for multiple species. In this review, the key role of proteomic analysis in identifying the abiotic-stress-responsive mechanisms in various crops was summarized. The development and availability of advanced computational tools were discussed in detail. The highly variable protein responses among different crops have provided a wide avenue for molecular-marker-assisted genetic buildup studies to develop smart, high-yielding, and stress-tolerant varieties to cope with food-security challenges.

MiRLoc: predicting miRNA subcellular localization by incorporating miRNA-mRNA interactions and mRNA subcellular localization

Subcellular localization of microRNAs (miRNAs) is an important reflection of their biological functions. Considering the spatio-temporal specificity of miRNA subcellular localization, experimental detection techniques are expensive and time-consuming, which strongly motivates an efficient and economical computational method to predict miRNA subcellular localization. In this paper, we describe a computational framework, MiRLoc, to predict the subcellular localization of miRNAs. In contrast to existing methods, MiRLoc uses the functional similarity between miRNAs instead of sequence features and incorporates information about the subcellular localization of the corresponding target mRNAs. The results show that miRNA functional similarity data can be effectively used to predict miRNA subcellular localization, and that inclusion of subcellular localization information of target mRNAs greatly improves prediction performance.

Subcellular Proteomics as a Unified Approach of Experimental Localizations and Computed Prediction Data for Arabidopsis and Crop Plants

In eukaryotic organisms, subcellular protein location is critical in defining protein function and understanding sub-functionalization of gene families. Some proteins have defined locations, whereas others have low specificity targeting and complex accumulation patterns. There is no single approach that can be considered entirely adequate for defining the in vivo location of all proteins. By combining evidence from different approaches, the strengths and weaknesses of different technologies can be estimated, and a location consensus can be built. The Subcellular Location of Proteins in Arabidopsis database ( http://suba.live/ ) combines experimental data sets that have been reported in the literature and is analyzing these data to provide useful tools for biologists to interpret their own data. Foremost among these tools is a consensus classifier (SUBAcon) that computes a proposed location for all proteins based on balancing the experimental evidence and predictions. Further tools analyze sets of proteins to define the abundance of cellular structures. Extending these types of resources to plant crop species has been complex due to polyploidy, gene family expansion and contraction, and the movement of pathways and processes within cells across the plant kingdom. The Crop Proteins of Annotated Location database ( http://crop-pal.org/ ) has developed a range of subcellular location resources including a species-specific voting consensus for 12 plant crop species that offers collated evidence and filters for current crop proteomes akin to SUBA. Comprehensive cross-species comparison of these data shows that the sub-cellular proteomes (subcellulomes) depend only to some degree on phylogenetic relationship and are more conserved in major biosynthesis than in metabolic pathways. Together SUBA and cropPAL created reference subcellulomes for plants as well as species-specific subcellulomes for cross-species data mining. These data collections are increasingly used by the research community to provide a subcellular protein location layer, inform models of compartmented cell function and protein-protein interaction network, guide future molecular crop breeding strategies, or simply answer a specific question-where is my protein of interest inside the cell?

Fast-forward breeding for a food-secure world

Crop production systems need to expand their outputs sustainably to feed a burgeoning human population. Advances in genome sequencing technologies combined with efficient trait mapping procedures accelerate the availability of beneficial alleles for breeding and research. Enhanced interoperability between different omics and phenotyping platforms, leveraged by evolving machine learning tools, will help provide mechanistic explanations for complex plant traits. Targeted and rapid assembly of beneficial alleles using optimized breeding strategies and precise genome editing techniques could deliver ideal crops for the future. Realizing desired productivity gains in the field is imperative for securing an adequate future food supply for 10 billion people.

Genome-wide survey and expression analysis of NIN-like Protein (NLP) genes reveals its potential roles in the response to nitrate signaling in tomato

BACKGROUND

Tomato (Solanum lycopersicum) is one of the most important horticultural crops, with a marked preference for nitrate as an inorganic nitrogen source. The molecular mechanisms of nitrate uptake and assimilation are poorly understood in tomato. NIN-like proteins (NLPs) are conserved, plant-specific transcription factors that play crucial roles in nitrate signaling.

RESULTS

In this study, genome-wide analysis identified six NLP members in tomato genome. These members were clustered into three clades in a phylogenetic tree. Comparative genomic analysis showed that SlNLP genes exhibited collinear relationships to NLPs in Arabidopsis, canola, maize and rice, and that the expansion of the SlNLP family mainly resulted from segmental duplications in the tomato genome. Tissue-specific expression analysis showed that one of the close homologs of AtNLP6/7, SlNLP3, was strongly expressed in roots during both the seedling and flowering stages, that SlNLP4 and SlNLP6 exhibited preferential expression in stems and leaves and that SlNLP6 was expressed at high levels in fruits. Furthermore, the nitrate uptake in tomato roots and the expression patterns of SlNLP genes were measured under nitrogen deficiency and nitrate resupply conditions. Four SlNLPs, SlNLP1, SlNLP2, SlNLP4 and SlNLP6, were upregulated after nitrogen starvation. And SlNLP1 and SlNLP5 were induced rapidly and temporally by nitrate.

CONCLUSIONS

These results provide significant insights into the potential diverse functions of SlNLPs to regulate nitrate uptake.