Functional Annotation Of Genes Research Articles

In-silico analysis of cattle blood transcriptome to identify lncRNAs and their role during bovine tuberculosis

Long noncoding RNAs (lncRNAs) are RNA molecules with a length greater than 200 nucleotides that do not code for functional proteins. Although, genes play a vital role in immune response against a disease, it is less known that lncRNAs also contribute through gene regulation. Bovine tuberculosis is a significant zoonotic disease caused by Mycobacterium bovis (M. bovis) in cattle. Here, we report the in-silico analysis of the publicly available transcriptomic data of calves infected with M. bovis. A total of 51,812 lncRNAs were extracted across all the samples. A total of 216 genes and 260 lncRNAs were found to be differentially expressed across all the 4 conditions—infected vs uninfected at 8- and 20-week post-infection (WPI), 8 vs 20-WPI of both infected and uninfected. Gene Ontology and Functional annotation showed that 8 DEGs were annotated with immune system GOs and 2 DEGs with REACTOME immune system pathways. Co-expression analysis of DElncRNAs with DEGs revealed the involvement of lncRNAs with the genes annotated with Immune related GOs and pathways. Overall, our study sheds light on the dynamic transcriptomic changes in response to M. bovis infection, particularly highlighting the involvement of lncRNAs with immune-related genes. The identified immune pathways and gene–lncRNA interactions offer valuable insights for further research in understanding host–pathogen interactions and potential avenues for genetic improvement strategies in cattle.

Metagenomic insights into microbial metabolic mechanisms of a combined solid-phase denitrification and anammox process for nitrogen removal in mainstream wastewater treatment

To overcome the significant challenges associated with nitrite supply and nitrate residues in mainstream anaerobic ammonium oxidation (anammox)-based processes, this study developed a combined solid-phase denitrification (SPD) and anammox process for low-strength nitrogen removal without the addition of nitrite. The SPD step was performed in a packed-bed reactor containing poly-3-hydroxybutyrate-co-3-hyroxyvelate (PHBV) prior to employing the anammox granular sludge reactor in the continuous-flow mode. The removal efficiency of total inorganic nitrogen reached 95.7 ± 1.2% under a nitrogen loading rate of 0.18 ± 0.01 kg N·m3·d−1, and it required 1.02 mol of nitrate to remove 1 mol of ammonium nitrogen. The PHBV particles not only served as biofilm carriers for the symbiosis of hydrolytic bacteria (HB) and denitrifying bacteria (DB), but also carbon sources that facilitated the coupling of partial denitrification and anammox in the granules. Metagenomic sequencing analysis indicated that Burkholderiales was the most abundant HB genus in SPD. The metabolic correlations between DB (Betaproteobacteria, Rhodocyclaceae, and Anaerolineae) and anammox bacteria (Candidatus Brocadiac and Kuenenia) in the granules were confirmed through microbial co-occurrence networks analysis and functional gene annotations. Additionally, the genes encoding nitrate reductase (Nap) and nitrite reductase (Nir) in DB primarily facilitated nitrate reduction, thereby supplying nitric oxide to anammox bacteria for subsequent nitrogen removal with hydrazine synthase (Hzs) and hydrazine dehydrogenase (Hdh). The findings provide insights into microbial metabolism within combined SPD and anammox processes, thus advancing the development of mainstream anammox-based processes in engineering applications.

Characterization of a novel multifunctional glycoside hydrolase family in the metagenome-assembled genomes of horse gut

The gut microbiota is a treasure trove of carbohydrate-active enzymes (CAZymes). To explore novel and efficient CAZymes, we analyzed the 4,142 metagenome-assembled genomes (MAGs) of the horse gut microbiota and found the MAG117.bin13 genome (Bacteroides fragilis) contains the highest number of polysaccharide utilisation loci sites (PULs), indicating its high capability for carbohydrate degradation. Bioinformatics analysis indicate that the PULs region of the MAG117.bin13 genome encodes many hypothetical proteins, which are important sources for exploring novel CAZymes. Interestingly, we discovered a hypothetical protein (595 amino acids). This protein exhibits potential CAZymes activity and has a lower similarity to CAZymes, we named it BfLac2275. We purified the protein using prokaryotic expression technology and studied its enzymatic function. The hydrolysis experiment of the polysaccharide substrate showed that the BfLac2275 protein has the ability to degrade α-lactose (156.94 U/mg), maltose (92.59 U/mg), raffinose (86.81 U/mg), and hyaluronic acid (5.71 U/mg). The enzyme activity is optimal at pH 5.0 and 30 ℃, indicating that the hypothetical protein BfLac2275 is a novel and multifunctional CAZymes in the glycoside hydrolases (GHs). These properties indicate that BfLac2275 has broad application prospects in many fields such as plant polysaccharide decomposition, food industry, animal feed additives and enzyme preparations. This study not only serves as a reference for exploring novel CAZymes encoded by gut microbiota but also provides an example for further studying the functional annotation of hypothetical genes in metagenomic assembly genomes.

Network analyses predict major regulators of resistance to early blight disease complex in tomato

BackgroundEarly blight and brown leaf spot are often cited as the most problematic pathogens of tomato in many agricultural regions. Their causal agents are Alternaria spp., a genus of Ascomycota containing numerous necrotrophic pathogens. Breeding programs have yielded quantitatively resistant commercial cultivars, but fungicide application remains necessary to mitigate the yield losses. A major hindrance to resistance breeding is the complexity of the genetic determinants of resistance and susceptibility. In the absence of sufficiently resistant germplasm, we sequenced the transcriptomes of Heinz 1706 tomatoes treated with strongly virulent and weakly virulent isolates of Alternaria spp. 3 h post infection. We expanded existing functional gene annotations in tomato and using network statistics, we analyzed the transcriptional modules associated with defense and susceptibility.ResultsThe induced responses are very distinct. The weakly virulent isolate induced a defense response of calcium-signaling, hormone responses, and transcription factors. These defense-associated processes were found in a single transcriptional module alongside secondary metabolite biosynthesis genes, and other defense responses. Co-expression and gene regulatory networks independently predicted several D clade ethylene response factors to be early regulators of the defense transcriptional module, as well as other transcription factors both known and novel in pathogen defense, including several JA-associated genes. In contrast, the strongly virulent isolate elicited a much weaker response, and a separate transcriptional module bereft of hormone signaling.ConclusionsOur findings have predicted major defense regulators and several targets for downstream functional analyses. Combined with our improved gene functional annotation, they suggest that defense is achieved through induction of Alternaria-specific immune pathways, and susceptibility is mediated by modulating hormone responses. The implication of multiple specific clade D ethylene response factors and upregulation of JA-associated genes suggests that host defense in this pathosystem involves ethylene response factors to modulate jasmonic acid signaling.

Assembly and Annotation of the Complete Genome Sequence of the Paenibacillus Bacteriophage phJNUCC32

A potential biocontrol agent for American foulbrood (AFB), the Paenibacillus bacteriophage phJNUCC32, was isolated from Baengnokdam in Halla Mountain. This study aimed to investigate its genomic characteristics through whole-genome sequencing. The genome of phJNUCC32 was found to be 62,871 base pairs in length, with a G + C content of 51.98%. Phylogenetic analysis classified phJNUCC32 within the unclassified Caudoviricetes bacteriophage category. The genome prediction confirmed the absence of virulence factors and antibiotic-resistance genes, ensuring its genetic safety. A total of 63 coding DNA sequences were identified, revealing a modular arrangement. Notably, the annotation of gene function indicates that phJNUCC32 harbors the holin/lysin system, suggesting significant potential for controlling bacterial infections in AFB and agriculture.

Assembly and Annotation of the Complete Genome Sequence of the Paenibacillus Bacteriophage phJNUCC32

A potential biocontrol agent for American foulbrood (AFB), the Paenibacillus bacteriophage phJNUCC32, was isolated from Baengnokdam in Halla Mountain. This study aimed to investigate its genomic characteristics through whole-genome sequencing. The genome of phJNUCC32 was found to be 62,871 base pairs in length, with a G + C content of 51.98%. Phylogenetic analysis classified phJNUCC32 within the unclassified Caudoviricetes bacteriophage category. The genome prediction confirmed the absence of virulence factors and antibiotic-resistance genes, ensuring its genetic safety. A total of 63 coding DNA sequences were identified, revealing a modular arrangement. Notably, the annotation of gene function indicates that phJNUCC32 harbors the holin/lysin system, suggesting significant potential for controlling bacterial infections in AFB and agriculture.

Adaptive adjustment of significance thresholds produces large gains in microbial gene annotations and metabolic insights.

Gene function annotations enable microbial ecologists to make inferences about metabolic potential from genomes and metagenomes. However, even tools that use the same database and general approach can differ markedly in the annotations they recover. We compare three popular methods for identifying KEGG Orthologs, applying them to genomes drawn from a range of bacterial families that occupy different host-associated and free-living biomes. Our results show that by adaptively tuning sequence similarity thresholds, sensitivity can be substantially improved while maintaining accuracy. We observe the largest improvements when few reference sequences exist for a given protein family, and when annotating genomes from non-model organisms (such as gut-dwelling Lachnospiraceae). Our results suggest that straightforward heuristic adjustments can broadly improve microbial metabolic predictions.

Bioinformatic Resources for Plant Genomic Research

Abstract: Genome assembly and annotation are crucial steps in plant genomics research as they provide valuable insights into plant genetic makeup, gene regulation, evolutionary history, and biological processes. In the emergence of high-throughput sequencing technologies, a plethora of genome assembly tools have been developed to meet the diverse needs of plant genome researchers. Choosing the most suitable tool to suit a specific research need can be daunting due to the complex and varied nature of plant genomes and reads from the sequencers. To assist informed decision-making in selecting the appropriate genome assembly and annotation tool(s), this review offers an extensive overview of the most widely used genome and transcriptome assembly tools. The review covers the specific information on each tool in tabular data, and the data types it can process. In addition, the review delves into transcriptome assembly tools, plant resource databases, and repositories (12 for Arabidopsis, 9 for Rice, 5 for Tomato, and 8 general use resources), which are vital for gene expression profiling and functional annotation and ontology tools that facilitate data integration and analysis.

Identification of key genes for triacylglycerol biosynthesis and storage in herbaceous peony (Paeonia lactifolra Pall.) seeds based on full-length transcriptome

BackgroundThe herbaceous peony (Paeonia lactiflora Pall.) is extensively cultivated in China due to its root being used as a traditional Chinese medicine known as ‘Radix Paeoniae Alba’. In recent years, it has been discovered that its seeds incorporate abundant unsaturated fatty acids, thereby presenting a potential new oilseed plant. Surprisingly, little is known about the full-length transcriptome sequencing of Paeonia lactiflora, limiting research into its gene function and molecular mechanisms.ResultsA total of 484,931 Reads of Inserts (ROI) sequences and 1,455,771 full-Length non-chimeric reads (FLNC) sequences were obtained for CDS prediction, TF analysis, SSR analysis and lncRNA identification. In addition, gene function annotation and gene structure analysis were performed. A total of 4905 transcripts were related to lipid metabolism biosynthesis pathway, belonging to 28 enzymes. We use these data to identify 10 oleosin (OLE) and 5 diacylglycerol acyltransferase (DGAT) gene members after de-redundancy. The analysis of physicochemical properties and secondary structure showed them similarity in gene family respectively. The phylogenetic analysis showed that the distribution of OLE and DGAT family members was roughly the same as that of Arabidopsis. Quantitative real-time polymerase chain reaction (qRT–PCR) analyses revealed expression changes in different seed development stages, and showed a trend of increasing and then decreasing.ConclusionIn summary, these results provide new insights into the molecular mechanism of triacylglycerol (TAG) biosynthesis and storage during the seedling stage in Paeonia lactiflora. It provides theoretical references for selecting and breeding oil varieties and understanding the functions of oil storage as well as lipid synthesis related genes in Paeonia lactiflora.

Effects of concentrate feeding sequence on VFA production, and cecal microbiota of Dezhou donkeys by metagenomic technology.

Microorganisms residing in the cecum of donkeys are crucial for physiological processes, nutrient metabolism, and immune function. Feeding methods can affect the dynamic balance of animal gut microbiota, thereby affecting indicators such as volatile fatty acids. This study explores suitable feeding methods to promote actual production by changing the feeding order of concentrate. Fifteen Dezhou donkeys with similar age and weight profiles were randomly divided into three groups with the concentrate feeding sequence: fiber-to-concentrate (FC), concentrate-to-fiber (CF), and total mixed ration (TMR). The experiment spanned a duration of 82 days. The analyses conducted were primarily aimed at determining the effects of feeding on gut microbes, primarily using metagenomic sequencing techniques. The experimental findings revealed that the levels of valeric acid were notably higher in the CF and TMR groups compared to the FC group (p < 0.05). These results suggest that the feeding sequence exerts a certain impact on the microbial composition within the cecum of Dezhou donkeys. At the phylum level, the predominant microbiota consisted of Firmicutes and Bacteroidetes, with the CF group displaying a higher relative abundance of Firmicutes compared to both the FC and TMR groups. At the genus level, Prevotella, Bacteroides, and Fibrobacter were the dominant bacterial genera identified in cecum. The functional gene annotation analysis indicated a significantly lower abundance of lacZ (K01190), Por/nifJ (K03737), and ppdK (K01006) genes in CF group relative to the FC and TMR groups (p < 0.05), highlighting their roles in galactose metabolism and glycolysis, respectively. Moreover, the CF group exhibited a higher concentration of antibiotic resistance genes (tetO and tet44) in the gut microbiota compared to the TMR and FC groups (p < 0.05), underscoring the presence of numerous antibiotic resistance genes within the phyla Bacteroidetes, Firmicutes, and Proteobacteria. In conclusion, different precision feed sequences significantly impact the levels of volatile fatty acids in Dezhou fattening donkeys, modify the composition and functional genes of the cecal microbiota, and elucidate the microbial mechanisms influenced by the feeding sequence on the growth and metabolism. These insights are anticipated to provide a foundation for the rational design of precision feed sequences in practical agricultural settings.

Bioinformatics analysis of the potential biomarkers of Multiple Sclerosis and Guillain-Barré syndrome.

Recent research emphasizes the intricate interplay of genetics and epigenetics in neurological disorders, notably Multiple Sclerosis (MS) and Guillain-Barre Syndrome (GBS), both of which exhibit cardiovascular dysregulation, with GBS often featuring serious bradyarrhythmias requiring prompt recognition and treatment. While cardiovascular autonomic dysfunction in MS is typically less severe, orthostatic intolerance affects around half of MS patients. Their distinction lies in their autoimmune responses, MS is an autoimmune disease affecting the central nervous system, causes demyelination and axon damage, leading to cognitive, ocular, and musculoskeletal dysfunction. In contrast, GBS primarily affects the peripheral nervous system, resulting in paralysis and respiratory complications. Despite their differences, both diseases share environmental risk factors such as viral infections and Vitamin D deficiency. This study aims to explore shared gene expression pathways, functional annotations, and molecular pathways between MS and GBS to enhance diagnostics, pathogenesis understanding, and treatment strategies through molecular analysis techniques. Through the gene expression analysis, five significant genes were found UTS2, TNFSF10, GBP1, VCAN, FOS. Results shows that Common DEGs are linked to apoptosis, bacterial infections, and atherosclerosis. Molecular docking analysis suggests Aflatoxin B1 as a potential therapeutic compound due to its high binding affinity with common differentially expressed proteins.

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

BackgroundEnvironmental 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.ResultsWe 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.ConclusionsThese 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).

GC–MS analysis of Lactobacillus plantarum YW11 metabolites and its computational analysis on familial pulmonary fibrosis hub genes

Abstract The purpose of this research was to examine the interaction between metabolites of Lactobacillus plantarum YW11, characterized through GC–mass spectra (MS) analysis, and the FN1 protein in cases of familial pulmonary fibrosis, found from hub genes analysis. GC–MS analysis was performed to identify metabolites in L. plantarum. Then, gene expression analysis and functional annotations were conducted to investigate the hub genes. A network of hub genes and transcription factors (TFs) was constructed, highlighting the significance of FN1 in the disease’s etiology. Molecular docking was employed to explore the interaction between the characterized metabolites and the FN1 protein. Toxicity analysis was also carried out. Thirty-two active compounds of L. plantarum YW11 were characterized by GC–MS. The gene expression analysis identified 295 differentially expressed genes, including 10 hub genes and 6 TFs, providing further support for the involvement of FN1 protein in the disease. The results of the molecular docking studies suggest the therapeutic potential of targeting FN1, with the best docking result observed for the interaction between FN1 and the 2,4-di-tert-butylphenol metabolite (energy of −6.9 kcal/mol). The toxicity analysis and molecular dynamic simulations support the suitability of 2,4-di-tert-butylphenol as a candidate for targeting FN1.

SapBase: A central portal for functional and comparative genomics of Sapindaceae species.

The Sapindaceae family, encompassing a wide range of plant forms such as herbs, vines, shrubs, and trees, is widely distributed across tropical and subtropical regions. This family includes economically important crops like litchi, longan, rambutan, and ackee. With the wide application of genomic technologies in recent years, several Sapindaceae plant genomes have been decoded, leading to an accumulation of substantial omics data in this field. This surge in data highlights the pressing need for a unified genomic data center capable of storing, sharing, and analyzing these data. Here, we introduced SapBase, that is, the Sapindaceae Genome Database. SapBase houses seven published plant genomes alongside their corresponding gene structure and functional annotations, small RNA annotations, gene expression profiles, gene pathways, and synteny block information. It offers user-friendly features for gene information mining, co-expression analysis, and inter-species comparative genomic analysis. Furthermore, we showcased SapBase's extensive capacities through a detailed bioinformatic analysis of a MYB gene in litchi. Thus, SapBase could serve as an integrative genomic resource and analysis platform for the scientific exploration of Sapinaceae species and their comparative studies with other plants.

New insights into the dominance of mixed fermentation of Staphylococcus cohnii and Staphylococcus saprophyticus in Chinese bacon: Complete genomic and comparative genomic perspectives

Previous studies have demonstrated that Staphylococcus cohnii WX_M8 and S. saprophyticus MY_A10 significantly enhanced the flavor of Chinese bacon in a mixed fermentation. However, due to the complexity of the processing, the contribution of the bacteria is deceptive when investigating only the phenotypic changes at the time of fermentation. In order to clarify the metabolic mechanisms of mixed fermentation, a technological characterization, whole genome and comparative genomics analysis, and metabolites were approached in this study. Results showed that differences in tolerance characteristics existed between WX_M8 and MY_A10. And the genomes of both the two strains consisted of one chromosome and four circular plasmids. Their genome sizes were 2.74 Mp and 2.62 Mp, the GC contents were 32.45% and 33.18%, and the predicted coding genes (CDS) were 2564 and 2541, respectively. Based on the annotation of gene functions and assessment of metabolic pathways in the KEGG database, WX_M8 and MY_A10 strains were found to harbor complete protein degradation and amino acid metabolic pathways, pyruvate and butanol metabolic pathways, and isoleucine metabolic pathways, and their diverse enzyme-encoding genes superimposed the metabolic functions, whereas the alcohol dehydrogenase genes, adh and frmA, achieved complementary functions in the production of esters. Comparative genomics analysis revealed a diversity of encoding genes of aminotransferases and a greater metabolism for sulfur-containing amino acids, aromatic amino acids, and branched-chain amino acids in the mixed fermentation of strains WX_M8 and MY_A10. Metabolites analysis showed that MY_A10 focused on the production of soluble peptides and free amino acids (FAAs), while WX_M8 focused on volatile organic compounds (VOCs), resulting in a significant enhancement of the flavor of Chinese bacon when the two were mixed fermented. This result may provide direction for strains WX_M8 and MY_A10 to be used as starter cultures and targeted to regulate flavor.

MiRNA-seq provides novel insight into the response to hyper- and hypo- salinity acclimation in Crassostrea hongkongensis

The Hong Kong oyster, Crassostrea hongkongensis, is a significant bivalve species with economic importance. It primarily inhabits the estuarine intertidal zones in southern China, making it susceptible to salinity fluctuations. Consequently, investigating the molecular mechanisms governing salinity regulation in C. hongkongensis is essential. In this study, we conducted miRNA-seq on C. hongkongensis to compare miRNA expression differences under varying salinities (5‰, 25‰, and 35‰). The miRNA sequencing revealed 51 known miRNAs and 95 novel miRNAs across nine small RNA libraries (S5, S25, and S35). Among these miRNAs, we identified 6 down-regulated differentially expressed (DE) miRNAs in response to hypo-salinity stress (5‰), while 1 up-regulated DE miRNA and 5 down-regulated DE miRNAs were associated with hyper-salinity stress (35‰). Additionally, we predicted 931 and 768 potential target genes for hypo- and hyper-salinity stress, respectively. Functional gene annotation indicated that the target genes under hypo-salinity stress were linked to vesicle-mediated transport and metal ion binding. Conversely, those under hyper-salinity stress were primarily involved in signal transduction and metabolic processes. These findings have provided insights into the regulatory role of miRNAs, their potential target genes and associated pathways in oyster hypo- and hyper-salinity stress, which establish a foundation for future studies on the roles of miRNAs in salinity acclimation mechanisms in C. hongkongensis.

Differential Gene Analysis of Langerhans Cell Histiocytosis and the Significance of MMP1-Targeted Drug Repositioning.

Langerhans cell histiocytosis (LCH) is a rare condition predominantly affecting young children. Activation of the MAPK pathway has offered key new insights into the pathogenesis of LCH; however, the precise mechanisms underlying its occurrence and development are still far from being completely elucidated. There is still a relapse/reactivation rate in patients with multisystem LCH. Therefore, this study aimed to investigate other potential LCH pathophysiologies and prospective therapeutic targets. The gene expression omnibus (GEO) database was used to retrieve gene expression profiles of LCH (GSE16395). Three distinct types of analyses were performed after identifying the common differentially expressed genes (DEGs) in LCH: hub gene identification, functional annotation, module construction, drug repositioning, and expression analysis via immunohistochemistry (IHC). We identified 417 common DEGs and 50 central hub genes. This functional study highlighted the significance of keratinization, skin development, and inflammation. In addition, we predicted new drug candidates (RS2 drugs targeting matrix metalloprotease1, MMP1) that could be used for LCH treatment. Finally, gene-miRNA and gene-TF networks and immune cell infiltration were analyzed for MMP1-related genes. MMP1 expression levels in LCH tissues were validated by IHC. Our study identified the central communal genes and novel drug candidates. These shared pathways and hub genes offer new perspectives on future mechanisms of action and therapeutic targets.

Integrating transcriptomic and proteomic data for a comprehensive molecular perspective on the association between sarcopenia and osteoporosis

BackgroundOsteoporosis and sarcopenia are common age-related conditions characterized by the progressive loss of bone density and muscle mass, respectively. Their co-occurrence, often referred to as osteosarcopenia, presents significant challenges in elderly care due to increased fragility and functional impairment. Existing studies have identified shared pathological mechanisms between these conditions, including inflammation, hormonal imbalances, and metabolic dysregulation, but a comprehensive understanding of their molecular interplay remains incomplete. ObjectiveThis study aims to deepen our understanding of the molecular interactions between sarcopenia and osteoporosis through an integrated omics approach, revealing potential therapeutic targets and biomarkers. MethodsEmploying a combination of proteomics and transcriptomics analyses, this study analyzed bone and muscle tissue samples from patients diagnosed with osteoporosis and osteosarcopenia. Techniques included high-throughput sequencing and label-free proteomics, supported by advanced bioinformatics tools for data analysis and functional annotation of genes and proteins. ResultsThe study found marked differences in gene and protein expressions between osteoporosis and osteosarcopenia tissues. Specifically, genes like PDIA5, TUBB1, and CYFIP2 in bone, along with MYH7 and NCAM1 in muscle, exhibited differential expression at both mRNA and protein levels. Pathway analyses revealed the significance of oxidative-reduction balance, cellular metabolism, and immune response in the progression of these conditions. Importantly, the study pinpointed osteoclast differentiation and NF-kappa B signaling pathways as critical in the molecular dynamics of osteosarcopenia, suggesting potential targets for therapy. ConclusionsThis study utilized transcriptomics and proteomics to identify key genes and proteins impacting sarcopenia and osteoporosis, employing advanced network tools to delineate interaction networks and crucial signaling pathways. It highlighted genes like PDIA5 and TUBB1, consistently expressed in both analyses, involved in pathways such as osteoclast differentiation and cytokine interactions. These insights enhance understanding of the molecular interplay in bone and muscle degeneration with aging, suggesting directions for future research into therapeutic interventions and prevention strategies for age-related degenerative diseases.

Bulked Segregant RNA-Seq Reveals Different Gene Expression Patterns and Mutant Genes Associated with the Zigzag Pattern of Tea Plants (Camellia sinensis).

The unique zigzag-patterned tea plant is a rare germplasm resource. However, the molecular mechanism behind the formation of zigzag stems remains unclear. To address this, a BC1 genetic population of tea plants with zigzag stems was studied using histological observation and bulked segregant RNA-seq. The analysis revealed 1494 differentially expressed genes (DEGs) between the upright and zigzag stem groups. These DEGs may regulate the transduction and biosynthesis of plant hormones, and the effects on the phenylpropane biosynthesis pathways may cause the accumulation of lignin. Tissue sections further supported this finding, showing differences in cell wall thickness between upright and curved stems, potentially due to lignin accumulation. Additionally, 262 single-nucleotide polymorphisms (SNPs) across 38 genes were identified as key SNPs, and 5 genes related to zigzag stems were identified through homologous gene function annotation. Mutations in these genes may impact auxin distribution and content, resulting in the asymmetric development of vascular bundles in curved stems. In summary, we identified the key genes associated with the tortuous phenotype by using BSR-seq on a BC1 population to minimize genetic background noise.

Small molecule drug discovery for glioblastoma treatment based on bioinformatics and cheminformatics approaches.

Background: Glioblastoma (GBM) is a common and highly aggressive brain tumor with a poor prognosis for patients. It is urgently needed to identify potential small molecule drugs that specifically target key genes associated with GBM development and prognosis. Methods: Differentially expressed genes (DEGs) between GBM and normal tissues were obtained by data mining the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Gene function annotation was performed to investigate the potential functions of the DEGs. A protein-protein interaction (PPI) network was constructed to explore hub genes associated with GBM. Bioinformatics analysis was used to screen the potential therapeutic and prognostic genes. Finally, potential small molecule drugs were predicted using the DGIdb database and verified using chemical informatics methods including absorption, distribution, metabolism, excretion, toxicity (ADMET), and molecular docking studies. Results: A total of 429 DEGs were identified, of which 19 hub genes were obtained through PPI analysis. The hub genes were confirmed as potential therapeutic targets by functional enrichment and mRNA expression. Survival analysis and protein expression confirmed centromere protein A (CENPA) as a prognostic target in GBM. Four small molecule drugs were predicted for the treatment of GBM. Conclusion: Our study suggests some promising potential therapeutic targets and small molecule drugs for the treatment of GBM, providing new ideas for further research and targeted drug development.