Genome-wide identification and characterization of protein phosphatase 2C (PP2C) gene family in sunflower (Helianthus annuus L.) and their expression profiles in response to multiple abiotic stresses.

Plant protein phosphatase 2C (PP2C) plays vital roles in responding to various stresses, stimulating growth factors, phytohormones, and metabolic activities in many important plant species. However, the PP2C gene family has not been investigated in the economically valuable plant species sunflower (Helianthus annuus L.). This study used comprehensive bioinformatics tools to identify and characterize the PP2C gene family members in the sunflower genome (H. annuus r1.2). Additionally, we analyzed the expression profiles of these genes using RNA-seq data under four different stress conditions in both leaf and root tissues. A total of 121 PP2C genes were identified in the sunflower genome distributed unevenly across the 17 chromosomes, all containing the Type-2C phosphatase domain. HanPP2C genes are divided into 15 subgroups (A-L) based on phylogenetic tree analysis. Analyses of conserved domains, gene structures, and motifs revealed higher structural and functional similarities within various subgroups. Gene duplication and collinearity analysis showed that among the 53 HanPP2C gene pairs, 48 demonstrated segmental duplications under strong purifying selection pressure, with only five gene pairs showing tandem duplications. The abundant segmental duplication was observed compared to tandem duplication, which was the major factor underlying the dispersion of the PP2C gene family in sunflowers. Most HanPP2C proteins were localized in the nucleus, cytoplasm, and chloroplast. Among the 121 HanPP2C genes, we identified 71 miRNAs targeting 86 HanPP2C genes involved in plant developmental processes and response to abiotic stresses. By analyzing cis-elements, we identified 63 cis-regulatory elements in the promoter regions of HanPP2C genes associated with light responsiveness, tissue-specificity, phytohormone, and stress responses. Based on RNA-seq data from two sunflower tissues (leaf and root), 47 HanPP2C genes exhibited varying expression levels in leaf tissue, while 49 HanPP2C genes showed differential expression patterns in root tissue across all stress conditions. Transcriptome profiling revealed that nine HanPP2C genes (HanPP2C12, HanPP2C36, HanPP2C38, HanPP2C47, HanPP2C48, HanPP2C53, HanPP2C54, HanPP2C59, and HanPP2C73) exhibited higher expression in leaf tissue, and five HanPP2C genes (HanPP2C13, HanPP2C47, HanPP2C48, HanPP2C54, and HanPP2C95) showed enhanced expression in root tissue in response to the four stress treatments, compared to the control conditions. These results suggest that these HanPP2C genes may be potential candidates for conferring tolerance to multiple stresses and further detailed characterization to elucidate their functions. From these candidates, 3D structures were predicted for six HanPP2C proteins (HanPP2C47, HanPP2C48, HanPP2C53, HanPP2C54, HanPP2C59, and HanPP2C73), which provided satisfactory models. Our findings provide valuable insights into the PP2C gene family in the sunflower genome, which could play a crucial role in responding to various stresses. This information can be exploited in sunflower breeding programs to develop improved cultivars with increased abiotic stress tolerance.

Genome-wide identification, classification, and characterization of lectin gene superfamily in sweet orange (Citrus sinensis L.).

Lectins are sugar-binding proteins found abundantly in plants. Lectin superfamily members have diverse roles, including plant growth, development, cellular processes, stress responses, and defense against microbes. However, the genome-wide identification and functional analysis of lectin genes in sweet orange (Citrus sinensis L.) remain unexplored. Therefore, we used integrated bioinformatics approaches (IBA) for in-depth genome-wide identification, characterization, and regulatory factor analysis of sweet orange lectin genes. Through genome-wide comparative analysis, we identified a total of 141 lectin genes distributed across 10 distinct gene families such as 68 CsB-Lectin, 13 CsLysin Motif (LysM), 4 CsChitin-Bind1, 1 CsLec-C, 3 CsGal-B, 1 CsCalreticulin, 3 CsJacalin, 13 CsPhloem, 11 CsGal-Lec, and 24 CsLectinlegB.This classification relied on characteristic domain and phylogenetic analysis, showing significant homology with Arabidopsis thaliana's lectin gene families. A thorough analysis unveiled common similarities within specific groups and notable variations across different protein groups. Gene Ontology (GO) enrichment analysis highlighted the predicted genes' roles in diverse cellular components, metabolic processes, and stress-related regulation. Additionally, network analysis of lectin genes with transcription factors (TFs) identified pivotal regulators like ERF, MYB, NAC, WRKY, bHLH, bZIP, and TCP. The cis-acting regulatory elements (CAREs) found in sweet orange lectin genes showed their roles in crucial pathways, including light-responsive (LR), stress-responsive (SR), hormone-responsive (HR), and more. These findings will aid in the in-depth molecular examination of these potential genes and their regulatory elements, contributing to targeted enhancements of sweet orange species in breeding programs.

A genome­wide approach to the systematic and comprehensive analysis of LIM gene family in sorghum (Sorghum bicolor L.).

The LIM domain-containing proteins are dominantly found in plants and play a significant role in various biological processes such as gene transcription as well as actin cytoskeletal organization. Nevertheless, genome-wide identification as well as functional analysis of the LIM gene family have not yet been reported in the economically important plant sorghum (Sorghum bicolor L.). Therefore, we conducted an in silico identification and characterization of LIM genes in S. bicolor genome using integrated bioinformatics approaches. Based on phylogenetic tree analysis and conserved domain, we identified five LIM genes in S. bicolor (SbLIM) genome corresponding to Arabidopsis LIM (AtLIM) genes. The conserved domain, motif as well as gene structure analyses of the SbLIM gene family showed the similarity within the SbLIM and AtLIM members. The gene ontology (GO) enrichment study revealed that the candidate LIM genes are directly involved in cytoskeletal organization and various other important biological as well as molecular pathways. Some important families of regulating transcription factors such as ERF, MYB, WRKY, NAC, bZIP, C2H2, Dof, and G2-like were detected by analyzing their interaction network with identified SbLIM genes. The cis-acting regulatory elements related to predicted SbLIM genes were identified as responsive to light, hormones, stress, and other functions. The present study will provide valuable useful information about LIM genes in sorghum which would pave the way for the future study of functional pathways of candidate SbLIM genes as well as their regulatory factors in wet-lab experiments.

Investigating the Precise Identification of Citrullination Sites with High-Performance Score Metrics using a Powerful Computation Predicting Tool.

BACKGROUND: To elucidate the detailed mechanisms of citrullination at the molecular level and design drugs applicable to major human diseases, predicting protein citrullination sites (PCSs) is essential. Using experimental approaches to predict PCSs is time-consuming and costly. However, there is a limited scope of the current PCS predictors. In particular, most predictors are commonly used for PCS prediction and have limited performance scores. OBJECTIVE: This work aims to provide an improved sophisticated predictor of citrullination sites using a benchmark dataset in a machine learning platform. METHODS: This study presents a reliable citrullination site predictor based on a benchmark dataset containing a 1:1 ratio of positive and negative samples. We classified citrullination sites using the Composition of the K-Spaced Amino Acid Pairs (CKSAAP) and Support Vector Machine (SVM). RESULTS: We developed PCS predictors using integrated machine-learning methods that produced the highest average scores. Using 10-fold cross-validation on test datasets, the True Positive Rate (TPR) was 98.34%, the True Negative Rate (TNR) was 99.44%, the accuracy was 98.89%, the Mathew Correlation Coefficient (MCC) was 98.21%, the Area Under the ROC Curve (AUC) was 0.999, and the partial Area Under the ROC Curve (pAUC) was 0.1968. CONCLUSION: According to overall performance, our developed predictor has a significantly higher implementation in comparison with the current tools on the same benchmark dataset. Moreover, it showed better performance metrics on both test and training datasets. Our developed predictor is promising and can be implemented as a complementary technique for identifying fast and precise citrullination sites.

Genome-wide identification of DCL, AGO and RDR gene families and their associated functional regulatory elements analyses in banana (Musa acuminata).

RNA silencing is mediated through RNA interference (RNAi) pathway gene families, i.e., Dicer-Like (DCL), Argonaute (AGO), and RNA-dependent RNA polymerase (RDR) and their cis-acting regulatory elements. The RNAi pathway is also directly connected with the post-transcriptional gene silencing (PTGS) mechanism, and the pathway controls eukaryotic gene regulation during growth, development, and stress response. Nevertheless, genome-wide identification of RNAi pathway gene families such as DCL, AGO, and RDR and their regulatory network analyses related to transcription factors have not been studied in many fruit crop species, including banana (Musa acuminata). In this study, we studied in silico genome-wide identification and characterization of DCL, AGO, and RDR genes in bananas thoroughly via integrated bioinformatics approaches. A genome-wide analysis identified 3 MaDCL, 13 MaAGO, and 5 MaRDR candidate genes based on multiple sequence alignment and phylogenetic tree related to the RNAi pathway in banana genomes. These genes correspond to the Arabidopsis thaliana RNAi silencing genes. The analysis of the conserved domain, motif, and gene structure (exon-intron numbers) for MaDCL, MaAGO, and MaRDR genes showed higher homogeneity within the same gene family. The Gene Ontology (GO) enrichment analysis exhibited that the identified RNAi genes could be involved in RNA silencing and associated metabolic pathways. A number of important transcription factors (TFs), e.g., ERF, Dof, C2H2, TCP, GATA and MIKC_MADS families, were identified by network and sub-network analyses between TFs and candidate RNAi gene families. Furthermore, the cis-acting regulatory elements related to light-responsive (LR), stress-responsive (SR), hormone-responsive (HR), and other activities (OT) functions were identified in candidate MaDCL, MaAGO, and MaRDR genes. These genome-wide analyses of these RNAi gene families provide valuable information related to RNA silencing, which would shed light on further characterization of RNAi genes, their regulatory elements, and functional roles, which might be helpful for banana improvement in the breeding program.

Single-base deletion in GmCHR5 increases the genistein-to-daidzein ratio in soybean seed.

Novel mutant alleles related to isoflavone content are useful for breeding programs to improve the disease resistance and nutritional content of soybean. However, identification of mutant alleles from high-density mutant libraries is expensive and time-consuming because soybean has a large, complicated genome. Here, we identified the gene responsible for increased genistein-to-daidzein ratio in seed of the mutant line F333ES017D9. For this purpose, we used a time- and cost-effective approach based on selective genotyping of a small number of F2 plants showing the mutant phenotype with nearest-neighboring-nucleotide substitution-high-resolution melting analysis markers, followed by alignment of short reads obtained by next-generation sequencing analysis with the identified locus. In the mutant line, GmCHR5 harbored a single-base deletion that caused a change in the substrate flow in the isoflavone biosynthetic pathway towards genistein. Mutated GmCHR5 was expressed at a lower level during seed development than wild-type GmCHR5. Ectopic overexpression of GmCHR5 increased the production of daidzein derivatives in both the wild-type and mutant plants. The present strategy will be useful for accelerating identification of mutant alleles responsible for traits of interest in agronomically important crops.

Identification of novel MYB transcription factors involved in the isoflavone biosynthetic pathway by using the combination screening system with agroinfiltration and hairy root transformation.

Soybean isoflavones are functionally important secondary metabolites that are mainly accumulated in seeds. Their biosynthetic processes are regulated coordinately at the transcriptional level; however, screening systems for key transcription factors (TFs) are limited. Here we developed a combination screening system comprising a simple agroinfiltration assay and a robust hairy root transformation assay. First, we screened for candidate MYB TFs that could activate the promoters of the chalcone synthase (CHS) gene GmCHS8 and the isoflavone synthase (IFS) genes GmIFS1 and GmIFS2 in the isoflavone biosynthetic pathway. In the agroinfiltration assay, we co-transformed a LjUbi (Lotus japonicus polyubiquitin gene) promoter-fused MYB gene with target promoter-fused GUS (ß-glucuronidase) gene constructs, and identified three genes (GmMYB102, GmMYB280, and GmMYB502) as candidate regulators of isoflavone biosynthesis. We then evaluated the functional regulatory role of identified three MYB genes in isoflavone biosynthesis using hairy roots transformation assay in soybean for the accumulation of isoflavones. Three candidate MYB genes showed an increased accumulation of total isoflavones in hairy root transgenic lines. Accumulation of total isoflavones in the three MYB-overexpressing lines was approximately 2-to 4-folds more than that in the vector control, confirming their possible role to regulate isoflavone biosynthesis. However, the significant accumulation of authentic GmCHS8, GmIFS1, and GmIFS2 transcripts could not be observed except for the GmMYB502-overexpressing line. Therefore, the analysis of isoflavone accumulation in transgenic hairy root was effective for evaluation of transactivation activity of MYB TFs for isoflavone biosynthetic genes. Our results demonstrate a simple and robust system that can potentially identify the function of orphan TFs in diverse plant metabolic pathways.