Comprehensive analysis of the long noncoding RNA-associated competitive endogenous RNA network in the osteogenic differentiation of periodontal ligament stem cells

Enhancer regulatory networks globally connect non-coding breast cancer loci to cancer genes

BACKGROUND

Genetic studies have associated thousands of enhancers with breast cancer (BC). However, the vast majority have not been functionally characterized. Thus, it remains unclear how BC-associated enhancers contribute to cancer.

RESULTS

Here, we perform single-cell CRISPRi screens of 3513 regulatory elements associated with breast cancer to measure the impact of these regions on transcriptional phenotypes. Analysis of > 500,000 single-cell transcriptomes in two breast cancer cell lines shows that perturbation of BC-associated enhancers disrupts breast cancer gene programs. We observe BC-associated enhancers that directly or indirectly regulate the expression of cancer genes. We also find one-to-multiple and multiple-to-one network motifs where enhancers indirectly regulate cancer genes. Notably, multiple BC-associated enhancers indirectly regulate TP53. Comparative studies illustrate subtype specific functions between enhancers in ER + and ER - cells. Finally, we develop the pySpade package to facilitate analysis of single-cell enhancer screens.

CONCLUSIONS

Overall, we demonstrate that enhancers form regulatory networks that link cancer genes in the genome, providing a more comprehensive understanding of the contribution of enhancers to breast cancer development.

Genome-wide exploration of the CONSTANS-like (COL) gene family and its potential role in regulating plant flowering time in foxtail millet (Setaria italica)

In photoperiod-sensitive plants, the CO-like gene (CONSTANS-like, COL) has a crucial function in regulating the timing of flowering. The blooming period in foxtail millet is greatly influenced by the duration of daylight; however, there is a scarcity of data regarding the molecular properties of the COL genes in the foxtail millet. In this study, we conducted a comprehensive analysis of the COL gene family in foxtail millet at the genome-wide level. We identified 11 SiCOL genes and performed gene structure analysis, which showed pronounced variation in gene length and intron number among the genes. The examination of COL proteins in foxtail millet and other plant species using phylogenetic analysis revealed that they could be clustered into three distinct groups. Cis-element analysis identified elements related to light-responsiveness, hormones, and abiotic stress in the promoter region of the SiCOL gene. Furthermore, tissue-specific expression analysis showed widespread expression of all 11 SiCOL genes in various foxtail millet tissues and organs, particularly in leaves and panicles. Collinearity analysis identified 14 syntenic gene pairs in both foxtail millet and rice. The results also revealed diurnal oscillations in the transcription levels of SiCOL genes under different light conditions. Moreover, among the 11 genes, SiCO, SiCOL1, and SiCOL6 expression levels were negatively correlated with flowering time variation in two foxtail cultivars. Additionally, upon constructing a network of predicted molecular interactions, FLOWER LOCUS-like (FTL) and Phytochromea A (PHY A) were suggested to potentially interact with SiCO, SiCOL1, and SiCOL6. SiCO, SiCOL1, and SiCOL6 have the potential for flowering and heading in foxtail millet. This research enhances our comprehension of the role and control of the SiCOL gene family constituents in foxtail millet, establishing a basis for future investigations.

Identification and Validation of Aging- and Endoplasmic Reticulum Stress-Related Genes in Periodontitis Using a Competing Endogenous RNA Network

Periodontitis is a multifactorial chronic inflammatory disease that destroy periodontium. Apart from microbial infection and host immune responses, emerging evidence shows aging and endoplasmic reticulum stress (ER stress) play a key role in periodontitis pathogenesis. The aim of this study is to identify aging-related genes (ARGs) and endoplasmic reticulum stress-related genes (ERGs) in periodontitis. Data were obtained from the Gene Expression Omnibus (GEO), Human Ageing Genomic Resources (HAGR) and GeneCards databases to identify differentially expressed mRNAs/miRNAs/lncRNAs (DEmRNAs/DEmiRNAs/DElncRNAs), ARGs and ERGs, respectively. We used the MultiMiR database for the reverse prediction of miRNAs and predicted miRNA-lncRNA interactions using the STARBase database. Afterwards, we constructed a mRNA-miRNA-lncRNA ceRNA network. A total of 10 hub genes, namely LCK, LYN, CXCL8, IL6, HCK, IL1B, BTK, CXCL12, GNAI1 and FCER1G, and 5 DEmRNAs-ARGs-ERGs were then discovered. Further, weighted gene co-expression network analysis (WGCNA) and single sample gene set enrichment analysis (ssGSEA) were performed to explore co-expression modules and immune infiltration respectively. Finally, we used transmission electron microscope (TEM), inverted fluorescence microscopy, quantitative real-time polymerase chain reaction (qRT-PCR) and Western Blot to verify the bioinformatic results in periodontal ligament stem cells (PDLSCs) infected with Porphyromonas gingivalis (P. gingivalis). The experimental results broadly confirmed the accuracy of bioinformatic analysis. The present study established an aging- and ER stress-related ceRNA network in periodontitis, contributing to a deeper understanding of the pathogenesis of periodontitis.

Platr3/NUDT21/NF-κB Axis Mediates P. gingivalis-Suppressed Cementoblast Mineralization

Porphyromonas gingivalis (P. gingivalis) is one of the major pathogens causing periodontitis and apical periodontitis (AP). Long noncoding RNA (lncRNA) can regulate cellular mineralization and inflammatory diseases. The aim of this study was to investigate the role and mechanism of lncRNA in P. gingivalis-stimulated cementoblast mineralization. In vivo, C57BL/6 mice were divided into the healthy, the AP, and AP + P. gingivalis groups (n = six mice per group). Micro computed tomography, immunohistochemistry staining, and fluorescence in situ hybridization were used to observe periapical tissue. In vitro, cementoblasts were treated with osteogenic medium or P. gingivalis. Pluripotency associated transcript 3 (Platr3), interleukin 1 beta (IL1B), and osteogenic markers were analyzed by quantitative real-time polymerase chain reaction and western blot. RNA pull-down and RNA immunoprecipitation assays were used to detect proteins that bind to Platr3. RNA sequencing was performed in Platr3-silenced cementoblasts. In vivo, P. gingivalis promoted periapical tissue destruction and IL1B expression, but inhibited Platr3 expression. In vitro, P. gingivalis facilitated IL1B expression (P < 0.001), whereas suppressed the expression of Platr3 (P < 0.001) and osteogenic markers (P < 0.01 or 0.001). In contrast, Platr3 overexpression alleviated the repressive effect of P. gingivalis on cementoblast mineralization (P < 0.01 or 0.001). Furthermore, Platr3 bound to nudix hydrolase 21 (NUDT21) and regulated the nuclear factor-κB (NF-κB) signaling pathway. Knocking down NUDT21 suppressed osteogenic marker expression and activated the above signaling pathway. Collectively, the results elucidated that Platr3 mediated P. gingivalis-suppressed cementoblast mineralization through the NF-κB signaling pathway by binding to NUDT21.

Identification and expression analysis of Sox family genes in echinoderms

The Sox gene family, a collection of transcription factors widely distributed throughout the animal kingdom, plays a crucial role in numerous developmental processes. Echinoderms occupy a pivotal position in many research fields, such as neuroscience, sex determination and differentiation, and embryonic development. However, to date, no comprehensive study has been conducted to characterize and analyze Sox genes in echinoderms. In the present study, the evolution and expression of Sox family genes across 11 echinoderms were analyzed using bioinformatics methods. The results revealed a total of 70 Sox genes, with counts ranging from 5 to 8 across different echinoderms. Phylogenetic analysis revealed that the identified Sox genes could be categorized into seven distinct classes: the SoxB1 class, SoxB2 class, SoxC class, SoxD class, SoxE class, SoxF class and SoxH class. Notably, the SoxB1, SoxB2, and SoxF genes were ubiquitously present in all the echinoderms studied, which suggests that these genes may be conserved in echinoderms. The spatiotemporal expression patterns observed for Sox genes in the three echinoderms indicated that various Sox members perform distinct functional roles. Notably, SoxB1 is likely involved in echinoderm ovary development, while SoxH may play a crucial role in testis development in starfish and sea cucumber. In general, the present investigation provides a molecular foundation for exploring the Sox gene in echinoderms, providing a valuable resource for future phylogenetic and genomic studies.

Comparative study of the gut microbial community structure of Spodoptera frugiperda and Spodoptera literal (Lepidoptera)

Background

Spodoptera frugiperda, the fall armyworm is a destructive invasive pest, and S. litura the tobacco cutworm, is a native species closely related to S. frugiperda. The gut microbiota plays a vital role in insect growth, development, metabolism and immune system. Research on the competition between invasive species and closely related native species has focused on differences in the adaptability of insects to the environment. Little is known about gut symbiotic microbe composition and its role in influencing competitive differences between these two insects.

Methods

We used a culture-independent approach targeting the 16S rRNA gene of gut bacteria of 5th instar larvae of S. frugiperda and S. litura. Larvae were reared continuously on maize leaves for five generations. We analyzed the composition, abundance, diversity, and metabolic function of gut microbiomes of S. frugiperda and S. litura larvae.

Results

Firmicutes, Proteobacteria, and Bacteroidetes were the dominant bacterial phyla in both species. Enterococcus, ZOR0006, Escherichia, Bacteroides, and Lactobacillus were the genera with the highest abundance in S. frugiperda. Enterococcus, Erysipelatoclostridium, ZOR0006, Enterobacter, and Bacteroides had the highest abundance in S. litura. According to α-diversity analysis, the gut bacterial diversity of S. frugiperda was significantly higher than that of S. litura. KEGG analysis showed 15 significant differences in metabolic pathways between S. frugiperda and S. litura gut bacteria, including transcription, cell growth and death, excretory system and circulatory system pathways.

Conclusion

In the same habitat, the larvae of S. frugiperda and S. litura showed significant differences in gut bacterial diversity and community composition. Regarding the composition and function of gut bacteria, the invasive species S. frugiperda may have a competitive advantage over S. litura. This study provides a foundation for developing control strategies for S. frugiperda and S. litura.

Functional annotation and meta-analysis of maize transcriptomes reveal genes involved in biotic and abiotic stress

BACKGROUND

Environmental stress factors, such as biotic and abiotic stress, are becoming more common due to climate variability, significantly affecting global maize yield. Transcriptome profiling studies provide insights into the molecular mechanisms underlying stress response in maize, though the functions of many genes are still unknown. To enhance the functional annotation of maize-specific genes, MaizeGDB has outlined a data-driven approach with an emphasis on identifying genes and traits related to biotic and abiotic stress.

RESULTS

We mapped high-quality RNA-Seq expression reads from 24 different publicly available datasets (17 abiotic and seven biotic studies) generated from the B73 cultivar to the recent version of the reference genome B73 (B73v5) and deduced stress-related functional annotation of maize gene models. We conducted a robust meta-analysis of the transcriptome profiles from the datasets to identify maize loci responsive to stress, identifying 3,230 differentially expressed genes (DEGs): 2,555 DEGs regulated in response to abiotic stress, 408 DEGs regulated during biotic stress, and 267 common DEGs (co-DEGs) that overlap between abiotic and biotic stress. We discovered hub genes from network analyses, and among the hub genes of the co-DEGs we identified a putative NAC domain transcription factor superfamily protein (Zm00001eb369060) IDP275, which previously responded to herbivory and drought stress. IDP275 was up-regulated in our analysis in response to eight different abiotic and four different biotic stresses. A gene set enrichment and pathway analysis of hub genes of the co-DEGs revealed hormone-mediated signaling processes and phenylpropanoid biosynthesis pathways, respectively. Using phylostratigraphic analysis, we also demonstrated how abiotic and biotic stress genes differentially evolve to adapt to changing environments.

CONCLUSIONS

These results will help facilitate the functional annotation of multiple stress response gene models and annotation in maize. Data can be accessed and downloaded at the Maize Genetics and Genomics Database (MaizeGDB).

Differential expression and global analysis of miR156/SQUAMOSA promoter binding-like proteins (SPL) module in oat

SQUAMOSA promoter binding-like proteins (SPLs) are important transcription factors that influence growth phase transition and reproduction in plants. SPLs are targeted by miR156 but the SPL/miR156 module is completely unknown in oat. We identified 28 oat SPL genes (AsSPLs) distributed across all 21 oat chromosomes except for 4C and 6D. The oat- SPL gene family represented six of eight SPL phylogenetic groups, with no AsSPLs in groups 3 and 7. A novel oat miR156 (AsmiR156) family with 21 precursors divided into 7 groups was characterized. A total of 16 AsSPLs were found to be targeted by AsmiR156. Intriguingly, AsSPL3s showed high transcript abundance during early inflorescence (GS-54), as compared to the lower abundance of AsmiR156, indicating their role in reproductive development. Unravelling the SPL/miR156 regulatory hub and alterations in expression patterns of AsSPLs could provide an essential toolbox for genetic improvement in the cultivated oat.

Chloroplast genomes in seven Lagerstroemia species provide new insights into molecular evolution of photosynthesis genes

Lagerstroemia indica is an important commercial tree known for the ornamental value. In this study, the complete chloroplast genome sequence of Lagerstroemia indica "Pink Velour" (Lagerstroemia "Pink Velour") was 152,174 bp in length with a GC content of 39.50%. It contained 85 protein coding genes (PCGs), 37 tRNAs, and 8 rRNA genes. 207 simple sequence repeats (SSRs) and 31 codons with relative synonymous codon (RSCU)value > 1 were detected. Phylogenetic analysis divided 10 Lagerstroemia species into evolutionary branches of clade A and clade B. We conducted a comparative analysis of Lagerstroemia "Pink Velours" complete chloroplast genome with the genomes of six closely related Lagerstroemia species from different origins. The structural features of all seven species were similar, except for the deletion of ycf1 nucleobases at the JSA boundary. The large single-copy (LSC) and the small single-copy (SSC) had a higher sequence divergence than the IR region, and 8 genes that were highly divergent (trnK-UUU, petN, psbF, psbJ, ndhE, ndhD, ndhI, ycf1) had been identified and could be used as molecular markers in future studies. High nucleotide diversity was present in genes belonging to the photosynthesis category. Mutation of single nucleic acid was mainly influenced by codon usage. The value percentage of nonsynonymous substitutions (Ka) and synonymous substitutions (Ks) in 6 Lagerstroemia species revealed that more photosynthesis genes have Ka or Ks only in Lagerstroemia fauriei, Lagerstroemia limii, and Lagerstroemia subcostata. These advances will facilitate the breeding of closely related Lagerstroemia species and deepen understanding on climatic adaptation of Lagerstroemia plants.

Transcriptome and biochemical analyses reveal phenolic compounds-mediated flavor differences in loquat (Eriobotrya japonica Lindl.) cultivars Chunhua No.1 and Dawuxing

The novel loquat cultivar 'Chunhua No.1' (CH1) is a promising commercial cultivar. However, CH1 has texture characteristics different from those of common loquat, and its formation mechanism remains unclear. Here, we first identified the phenolic compounds of CH1 and its parent ('Dawuxing', DWX) and the effect on texture formation. The special presence of stone cells explained the flavor differences in CH1. Chlorogenic acid, neochlorogenic acid, and coniferyl alcohol were the main phenolic compounds in loquat, and the high content of coniferyl alcohol was a potential factor for the rough texture of CH1. Transcriptome reveals that phenylpropanoid metabolism was activated during CH1 fruit texture formation. Kyoto Encyclopedia of Genes and Genomes (KEGG) identified 51 structural genes involved in phenylpropanoid biosynthesis, and Weighted Gene Co-expression Network Analysis (WGCNA) identified four structural genes and 88 transcription factors. These findings provide new insights into the phenolic metabolism and flavor formation of loquat fruit.

EFFECT OF PENICILLIUM SPECIES ON THE ANTIBIOTIC RESISTANCE PROFILE OF ALCALIGENES FAECALIS

Background

Infectious diseases due to antibiotic resistant pathogens are a global public health problem. This study aimed at determining the potential effect of bacterial-fungal interaction on the antibiotic susceptibility profile of Alcaligenes faecalis.

Materials and Methods

Alcaligenes faecalis was isolated from water samples. The isolate was identified using the conventional biochemical tests and the 16S rRNA molecular sequencing technique. Additionally, Penicillium species was isolated and identified based on colony morphological characteristics and microscopic features. Standardized isolates were co-cultured in broth medium. Antibiotic susceptibility evaluation of the Alcaligenes faecalis from the co-culture and the original Alcaligenes faecalis was carried out using the Kirby bauer disk diffusion method.

Results

The antibiotic susceptibility profile of Alcaligenes faecalis before and after co-culture remained largely unchanged except in the case of chloramphenicol, where the isolate showed reduced susceptibility. Molecular analysis of resistance gene revealed the absence of tested gene encoding antibiotic resistance, including the streptomycin resistance (str) genes (stra and strb) and the erythromycin resistance methylase (erm) gene.

Conclusion

The result of this study showed that there is a minimal influence of Penicillium cultures on the susceptibility of A. faecalis. Further research involving a wide spectrum of microorganisms and their interactions should be conducted to acquire a thorough understanding of the influence of microbial interactions on antibiotic susceptibility profiles in order to pave way for novel strategies to combat antimicrobial resistance.

The signaling pathways involved in non-coding RNA regulation during osteogenic differentiation of periodontal tissue-derived cells in the field of periodontitis

Periodontitis is a prevalent oral disease caused by chronic inflammation of the periodontal tissues surrounding the teeth, which can lead to bone loss, tooth loosening, and even tooth loss. This inflammation has a negative impact on the osteogenic differentiation capacity of periodontal tissue-derived cells. Non-coding RNAs (ncRNAs) are a class of RNA molecules that do not encode proteins but can regulate various physiological processes. In this review, we summarized the critical signaling pathways that ncRNAs modulate in osteogenic differentiation of periodontal tissue-derived cells, such as the Wnt, BMP/Smad, NF-κB, and PI3-K/Akt/mTOR pathways. This comprehensive exploration of ncRNA-mediated modulation offers fresh and promising insights for prospective approaches in the management of periodontitis and the advancement of periodontal regeneration therapies.

Comparative Transcriptome Combined with Morphophysiological Analyses Revealed Carotenoid Biosynthesis for Differential Chilling Tolerance in Two Contrasting Rice (Oryza sativa L.) Genotypes

Early spring cold spells can lead to leaf chlorosis during the rice seedling greening process. However, the physiological and molecular mechanisms underlying the rice greening process under low-temperature conditions remain unknown. In this study, comparative transcriptome and morphophysiological analyses were performed to investigate the mechanisms mediating the responses of the Koshihikari (Kos) and Kasalath (Kas) rice cultivars to chilling stress. According to their growth-related traits, electrolyte leakage, and chlorophyll fluorescence parameters, Kos was more tolerant to low-temperature stress than Kas. Moreover, chloroplast morphology was more normal (e.g., oval) in Kos than in Kas at 17 °C. The comparative transcriptome analysis revealed 610 up-regulated differentially expressed genes that were common to all four comparisons. Furthermore, carotenoid biosynthesis was identified as a critical pathway for the Kos response to chilling stress. The genes in the carotenoid biosynthesis pathway were expressed at higher levels in Kos than in Kas at 17 °C, which was in accordance with the higher leaf carotenoid content in Kos than in Kas. The lycopene β-cyclase and lycopene ε-cyclase activities increased more in Kos than in Kas. Additionally, the increases in the violaxanthin de-epoxidase and carotenoid hydroxylase activities in Kos seedlings resulted in the accumulation of zeaxanthin and lutein and mitigated the effects of chilling stress on chloroplasts. These findings have clarified the molecular mechanisms underlying the chilling tolerance of rice seedlings during the greening process.

Investigation of the BERT model on nucleotide sequences with non-standard pre-training and evaluation of different k-mer embeddings

MOTIVATION

In recent years, pre-training with the transformer architecture has gained significant attention. While this approach has led to notable performance improvements across a variety of downstream tasks, the underlying mechanisms by which pre-training models influence these tasks, particularly in the context of biological data, are not yet fully elucidated.

RESULTS

In this study, focusing on the pre-training on nucleotide sequences, we decompose a pre-training model of Bidirectional Encoder Representations from Transformers (BERT) into its embedding and encoding modules to analyze what a pre-trained model learns from nucleotide sequences. Through a comparative study of non-standard pre-training at both the data and model levels, we find that a typical BERT model learns to capture overlapping-consistent k-mer embeddings for its token representation within its embedding module. Interestingly, using the k-mer embeddings pre-trained on random data can yield similar performance in downstream tasks, when compared with those using the k-mer embeddings pre-trained on real biological sequences. We further compare the learned k-mer embeddings with other established k-mer representations in downstream tasks of sequence-based functional prediction. Our experimental results demonstrate that the dense representation of k-mers learned from pre-training can be used as a viable alternative to one-hot encoding for representing nucleotide sequences. Furthermore, integrating the pre-trained k-mer embeddings with simpler models can achieve competitive performance in two typical downstream tasks.

AVAILABILITY AND IMPLEMENTATION

The source code and associated data can be accessed at https://github.com/yaozhong/bert_investigation.

Genetic improvement of economic traits in Murrah buffalo using significant SNPs from genome-wide association study

GWAS helps to identify QTL and candidate genes of specific traits. Buffalo breeding has primarily focused on milk production, but its negative correlation with reproduction traits resulted in unfavorable decline of reproductive performance among buffaloes. A genome wide scan was performed on a total of 120 Murrah buffaloes genotyped by ddRAD sequencing for 13 traits related to female fertility, production, and growth. The identified 25 significant single nucleotide polymorphisms (SNPs) (P <1×10⁶) are associated with age at first calving (AFC), age at first service (AFS), period from calving to 1^st Artifical Insemination (AI), service period (SP) and 6 month body weight (6M). Fifteen genetic variants overlapped with different QTL regions of reported studies. Among the associated loci, outstanding candidate genes for fertility, including AQP1, TRNAE-CUC, NRIP1, CPNE4, and VOPP1, have effect in different fertility traits. AQP1 gene is expressed in ovulatory phase and various stages of pregnancy. TRNAE-CUC gene is associated with AFC and number . of calvings after 4 years of age. Glycogen content-associated gene CPNE4 regulates muscle glycogen and is upregulated during early pregnancy. NRIP1 generegulates ovulation, corpus luteum at pregnancy, and mammary gland development. The objective is to identify potential genomic regions and genetic variants associated with economic traits and to select the most significant SNP which have positive effect on all the traits.

Genome-wide identification and comparative analysis of Dmrt genes in echinoderms

The Dmrt (Doublesex-mab3-related transcription factor) gene family is a class of crucial transcription factors characterized by one or several conserved DM (Doublesex/Mab-3) domains. Dmrt family genes can participate in various physiological developmental processes, especially in sex determination/differentiation. Echinoderms are extremely important research objects in various fields, such as sex determination/differentiation and neuroscience. However, to date, the genome-wide characterization and analysis of Dmrt genes in echinoderms have not been investigated. In this study, the identification and analysis of Dmrt genes in 11 representative echinoderms were performed using bioinformatics methods. A total of 43 Dmrt genes have been found in the studied echinoderms, and the number of Dmrt genes in different species ranges from 2 to 5. The phylogenetic tree showed that all Dmrt genes from echinoderms can be subdivided into 5 classes, the Dmrt2-like class, Dmrt3-like class, Dmrt4/5-like class, Dsx-like class, and a novel Dmrt (starfish-specific) class. Furthermore, selective pressure assessment suggested that the Dmrt genes underwent purifying selection pressure. In general, this study provides a molecular basis for echinoderm Dmrt genes and may serve as a reference for in-depth phylogenomics.

Krein support vector machine classification of antimicrobial peptides

Antimicrobial peptides (AMPs) represent a potential solution to the growing problem of antimicrobial resistance, yet their identification through wet-lab experiments is a costly and time-consuming process. Accurate computational predictions would allow rapid in silico screening of candidate AMPs, thereby accelerating the discovery process. Kernel methods are a class of machine learning algorithms that utilise a kernel function to transform input data into a new representation. When appropriately normalised, the kernel function can be regarded as a notion of similarity between instances. However, many expressive notions of similarity are not valid kernel functions, meaning they cannot be used with standard kernel methods such as the support-vector machine (SVM). The Kreĭn-SVM represents generalisation of the standard SVM that admits a much larger class of similarity functions. In this study, we propose and develop Kreĭn-SVM models for AMP classification and prediction by employing the Levenshtein distance and local alignment score as sequence similarity functions. Utilising two datasets from the literature, each containing more than 3000 peptides, we train models to predict general antimicrobial activity. Our best models achieve an AUC of 0.967 and 0.863 on the test sets of each respective dataset, outperforming the in-house and literature baselines in both cases. We also curate a dataset of experimentally validated peptides, measured against Staphylococcus aureus and Pseudomonas aeruginosa, in order to evaluate the applicability of our methodology in predicting microbe-specific activity. In this case, our best models achieve an AUC of 0.982 and 0.891, respectively. Models to predict both general and microbe-specific activities are made available as web applications.

Development of Ferroptosis-Associated ceRNA Network in Periodontitis

OBJECTIVES

Periodontitis is a chronic inflammatory illness that may lead to tooth loosening and even loss, and its pathogenesis is not fully understood. Ferroptosis is an iron-dependent, regulated cell death. The present study aims to find the key ferroptosis-related genes (FRGs) in periodontitis and develop an mRNA-miRNA-lncRNA network to deeply explore the pathogenesis of periodontitis.

METHODS

Data from the Gene Expression Omnibus (GEO) database and FerrDb database were downloaded to discover the differentially expressed mRNA, miRNA, and FRGs. Functional enrichment analysis was conducted for the differentially expressed FRGs (DE-FRGs), including gene ontology, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and protein-protein interaction (PPI) network analysis. Targetscan and miRtarbase were used to estimate the miRNAs that DE-FRGs may interact with, whilst StarBase v3.0 was used for lncRNA-miRNA interaction.

RESULTS

Seven DE-FRGs were identified through differential expression analysis. Interleukin 1 beta (IL1B) interacted with XBP1 and MMP13 in the PPI network. After taking the intersection between DE-miRNAs and predicted miRNAs, a ceRNA network containing IL1B, has-miR-185, has-miR-204, has-miR-211, has-miR-4306, and 28 lncRNAs was established.

CONCLUSIONS

Seven FRGs in periodontitis were identified, which might promote deeper understanding of ferroptosis in periodontitis.

The plastid genome of twenty-two species from Ferula, Talassia, and Soranthus: comparative analysis, phylogenetic implications, and adaptive evolution

BACKGROUND

The Ferula genus encompasses 180-185 species and is one of the largest genera in Apiaceae, with many of Ferula species possessing important medical value. The previous studies provided more information for Ferula, but its infrageneric relationships are still confusing. In addition, its genetic basis of its adaptive evolution remains poorly understood. Plastid genomes with more variable sites have the potential to reconstruct robust phylogeny in plants and investigate the adaptive evolution of plants. Although chloroplast genomes have been reported within the Ferula genus, few studies have been conducted using chloroplast genomes, especially for endemic species in China.

RESULTS

Comprehensively comparative analyses of 22 newly sequenced and assembled plastomes indicated that these plastomes had highly conserved genome structure, gene number, codon usage, and repeats type and distribution, but varied in plastomes size, GC content, and the SC/IR boundaries. Thirteen mutation hotspot regions were detected and they would serve as the promising DNA barcodes candidates for species identification in Ferula and related genera. Phylogenomic analyses with high supports and resolutions showed that Talassia transiliensis and Soranthus meyeri were nested in the Ferula genus, and thus they should be transferred into the Ferula genus. Our phylogenies also indicated the monophyly of subgenera Sinoferula and subgenera Narthex in Ferula genus. Twelve genes with significant posterior probabilities for codon sites were identified in the positively selective analysis, and their function may relate to the photosystem II, ATP subunit, and NADH dehydrogenase. Most of them might play an important role to help Ferula species adapt to high-temperatures, strong-light, and drought habitats.

CONCLUSION

Plastome data is powerful and efficient to improve the support and resolution of the complicated Ferula phylogeny. Twelve genes with significant posterior probabilities for codon sites were helpful for Ferula to adapt to the harsh environment. Overall, our study supplies a new perspective for comprehending the phylogeny and evolution of Ferula.

Epigenetic regulation of dental-derived stem cells and their application in pulp and periodontal regeneration

Dental-derived stem cells have excellent proliferation ability and multi-directional differentiation potential, making them an important research target in tissue engineering. An increasing number of dental-derived stem cells have been discovered recently, including dental pulp stem cells (DPSCs), stem cells from exfoliated deciduous teeth (SHEDs), stem cells from apical papilla (SCAPs), dental follicle precursor cells (DFPCs), and periodontal ligament stem cells (PDLSCs). These stem cells have significant application prospects in tissue regeneration because they are found in an abundance of sources, and they have good biocompatibility and are highly effective. The biological functions of dental-derived stem cells are regulated in many ways. Epigenetic regulation means changing the expression level and function of a gene without changing its sequence. Epigenetic regulation is involved in many biological processes, such as embryonic development, bone homeostasis, and the fate of stem cells. Existing studies have shown that dental-derived stem cells are also regulated by epigenetic modifications. Pulp and periodontal regeneration refers to the practice of replacing damaged pulp and periodontal tissue and restoring the tissue structure and function under normal physiological conditions. This treatment has better therapeutic effects than traditional treatments. This article reviews the recent research on the mechanism of epigenetic regulation of dental-derived stem cells, and the core issues surrounding the practical application and future use of pulp and periodontal regeneration.

Comparative analysis of detoxification-related gene superfamilies across five hemipteran species

Background

Hemiptera is one of the most speciose orders of insects, and the most speciose considering Hemimetabola. Through their evolutive history, hemipterans with different feeding habits have adapted to deal with different chemical challenges. Three major gene families are involved in xenobiotic detoxification in insects: the cytochromes P450 (CYPs), carboxyl/cholinesterases (CCEs), and glutathione transferases (GSTs). Here we perform a comparative analysis on the complement of these gene superfamilies across five hemipteran species; four heteropterans (the pentatomid plant feeders Nezara viridula and Halyomorpha halys; the hematophagous Cimex lectularius, Cimicidae, and Rhodnius prolixus, Reduviidae), and one Auchenorrhyncha plant feeder (Nilaparvata lugens).

Results

Our results point to an expansion of several enzyme families associated with xenobiotic detoxification in heteropterans with respect to other species and the existence of a dynamic evolution pattern including CYP3 clan, hormone and pheromone processing class in the CCE superfamily, and sigma class in GST superfamily. Other detoxification-related families are reduced in the hemipteran species analyzed here: reduction or even absence of epsilon class and reduced delta class in GST superfamily; absence of mitochondrial CYP12 family; absence of CYP9 family in CYP3 clan; and reduction or even absence of some dietary/detoxification groups of CCEs. Interestingly, the most polyphagous species analyzed here (H. halys) is also the one that presents the largest repertoire of detoxification enzymes. Gene cluster analysis suggests that this could be due to gene duplication events.

Conclusions

The evolutionary analysis performed here reveals characteristics that are both common and particular for heteropterans. The composition and organization of detoxification-related gene families could shed light on evolutionary forces that shaped their divergence. These families are important for both the detoxification of diet products and for conferring tolerance or resistance to synthetic insecticides. Furthermore, we present the first comprehensive analysis of detoxification gene superfamilies in N. viridula, an understudied species in spite of its economic relevance as a crop pest. The information obtained is of interest for basic insect science as well as for the control of harmful species and the management of insecticide resistance.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08974-y.

Transcriptomic analysis of the thyroid and ovarian stroma reveals key pathways and potential candidate genes associated with egg production in ducks

The importance of thyroid-related genes has been repeatedly mentioned in the transcriptome studies of poultry with different laying performance, yet there are few systematic studies to unravel the regulatory mechanisms of the thyroid-ovary axis in the poultry egg production process. In this study, we compared the transcriptome profiles in the thyroid and ovarian stroma between high egg production (GP) and low egg production (DP) ducks, and then revealed the pathways and candidate genes involved in the process. We identified 1,114 and 733 differentially expressed genes (DEGs) in the thyroid and ovarian stroma, separately. The Gene Ontology (GO) analysis showed that a total of 504 and 189 GO terms were identified in the thyroid and ovarian stroma (P < 0.05). Three common GO terms were identified from the top 5 GO terms with the highest significant level in two tissues, including extracellular space, calcium ion binding, and integral component of plasma membrane. The enrichment analysis of the Kyoto Encyclopedia of Genes and Genomes (KEGG) showed that 15 and 14 KEGG pathways were significantly (P < 0.05) enriched in the thyroid and ovarian stroma, respectively. And, there were 8 common pathways, including neuroactive ligand-receptor interaction, calcium signaling pathway, ECM-receptor interaction, PPAR signaling pathway, melanogenesis, wnt signaling pathway, vascular smooth muscle contraction, and cytokine-cytokine receptor interaction. Notably, the neuroactive ligand-receptor interaction pathway was the most significantly enriched by the DEGs both in the thyroid and ovarian stroma. The interaction among DEGs enriched in the neuroactive ligand-receptor interaction and ECM-receptor interaction suggested that the thyroid may regulate ovarian development by these genes. Through integrated analysis of the protein-protein interaction (PPI) network and KEGG pathway maps, 9 key DEGs (PTH, THBS2, THBS4, CD36, ADIPOQ, ACSL6, PRKAA2, CRH, and PCK1) were identified, which could play crucial roles in the thyroid to regulate ovarian function and then affect egg-laying performance between GP and DP. This study serves as a basis to explore the molecular mechanism of the thyroid affecting ovarian function and egg production in female ducks and may help to identify molecular markers that can be used for duck genetic selection.

Non-coding RNA delivery for bone tissue engineering: progress, challenges and potential solutions

More than 20 million individuals worldwide suffer from congenital or acquired bone defects annually. The development of bone scaffold materials that simulate natural bone for bone defect repair remains challenging. Recently, ncRNA-based therapies for bone defects have attracted increasing interest because of the great potential of ncRNAs in disease treatment. Various types of ncRNAs regulate gene expression in osteogenesis-related cells via multiple mechanisms. The delivery of ncRNAs to the site of bone loss through gene vectors or scaffolds is a potential therapeutic option for bone defect repair. Therefore, this study discusses and summarizes the regulatory mechanisms of miRNAs, siRNAs, and piRNAs in osteogenic signaling and reviews the widely used current RNA delivery vectors and scaffolds for bone defect repair. Additionally, current challenges and potential solutions of delivery scaffolds for bone defect repair are proposed, with the aim of providing a theoretical basis for their future clinical applications.