Frontiers in Genetics最新文献

Background: Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy characterized by a dismal prognosis. Treatment outcomes exhibit substantial variability across patients, underscoring the urgent need for robust predictive models to effectively estimate survival probabilities and therapeutic responses in PDAC.

Methods: Metabolic and immune-related genes exhibiting differential expression were identified using the TCGA-PDAC and GTEx datasets. A genetic prognostic model was developed via univariable Cox regression analysis on a training cohort. Predictive accuracy was assessed using Kaplan-Meier (K-M) curves, calibration plots, and ROC curves. Additional analyses, including GSAE and immune cell infiltration studies, were conducted to explore relevant biological mechanisms and predict therapeutic efficacy.

Results: An 8-gene prognostic model (AK2, CXCL11, TYK2, ANGPT4, IL20RA, MET, ENPP6, and CA12) was established. Three genes (AK2, ENPP6, and CA12) were associated with metabolism, while the others were immune-related. Most genes correlated with poor prognosis. Validation in TCGA-PDAC and GSE57495 datasets demonstrated robust performance, with AUC values for 1-, 3-, and 5-year OS exceeding 0.7. The model also effectively predicted responses to adjuvant therapy.

Conclusion: This 8-gene signature enhances prognostic accuracy and therapeutic decision-making in PDAC, offering valuable insights for clinical applications and personalized treatment strategies.

Introduction: The blue mussel is one of the major aquaculture species worldwide. In France, this species faces a significant threat from infectious disease outbreaks in both mussel farms and the natural environment over the past decade. Diseases caused by various pathogens, particularly Vibrio spp., have posed a significant challenge to the mussel industry. Genetic improvement of disease resistance can be an effective approach to overcoming this issue.

Methods: In this work, we tested genomic selection in the blue mussel (Mytilus edulis) to understand the genetic basis of resistance to one pathogenic strain of Vibrio splendidus (strain 14/053 2T1) and to predict the accuracy of selection using both pedigree and genomic information. Additionally, we performed a genome-wide association study (GWAS) to identify putative QTLs underlying disease resistance. We conducted an experimental infection involving 2,280 mussels sampled from 24 half-sib families containing each two full-sib families which were injected with V. splendidus. Dead and survivor mussels were all sampled, and among them, 348 dead and 348 surviving mussels were genotyped using a recently published multi-species medium-density 60K SNP array.

Results: From potentially 23.5K SNPs for M. edulis present on the array, we identified 3,406 high-quality SNPs, out of which 2,204 SNPs were successfully mapped onto the recently published reference genome. Heritability for resistance to V. splendidus was moderate ranging from 0.22 to 0.31 for a pedigree-based model and from 0.28 to 0.36 for a genomic-based model.

Discussion: GWAS revealed the polygenic architecture of the resistance trait in the blue mussel. The genomic selection models studied showed overall better performance than the pedigree-based model in terms of accuracy of breeding values prediction. This work provides insights into the genetic basis of resistance to V. splendidus and exemplifies the potential of genomic selection in family-based breeding programs in M. edulis.

Relationships between cellular senescence and gastrointestinal cancers have gained prominence in recent years. The currently accepted theory suggests that cellular senescence and cancer occurrence exhibit "double-edged sword" effects. Cellular senescence is related to cancer via four "meta-hallmarks" i.e., genomic instability, epigenetic alterations, chronic inflammation, and dysbiosis, along with two "antagonistic hallmarks" i.e., telomere attrition and stem cell exhaustion. These relationships are characterized by both agonistic and antagonistic elements, but the existence of an intricate dynamic balance remains unknown. Non-coding RNAs (ncRNAs) have vital roles in post-transcriptional regulation, but how they participate in agonistic and antagonistic relationships between cellular senescence and gastrointestinal cancers remains to be fully investigated. In this article, we systematically review how ncRNAs (including microRNAs (miRNAs), long ncRNAs (lncRNAs), and circularRNAs (circRNAs)) participate in interactions between cellular senescence and gastrointestinal cancers. Our aim is to elucidate a triangular relationship between "ncRNAs-senescence-gastrointestinal cancers" which considered these three elements as an equal important standing. We are keen to identify prognostic or therapeutic targets for gastrointestinal cancers from, i.e., aging-related ncRNAs, or discover novel strategies to treat and manage in the elderly. We seek to clarify complex relationships where ncRNAs participate in "senescence-gastrointestinal cancers" interactions.

Background: Sarcopenia is a prevalent condition associated with aging. Inflammation and pyroptosis significantly contribute to sarcopenia.

Methods: Two sarcopenia-related datasets (GSE111016 and GSE167186) were obtained from the Gene Expression Omnibus (GEO), followed by batch effect removal post-merger. The "limma" R package was utilized to identify differentially expressed genes (DEGs). Subsequently, LASSO analysis was conducted on inflammation and pyroptosis-related genes (IPRGs), resulting in the identification of six hub IPRGs. A novel skeletal muscle aging model was developed and validated using an independent dataset. Additionally, Gene Ontology (GO) enrichment analysis was performed on DEGs, along with Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and gene set enrichment analysis (GSEA). ssGSEA was employed to assess differences in immune cell proportions between healthy muscle groups in older versus younger adults. The expression levels of the six core IPRGs were quantified via qRT-PCR.

Results: A total of 44 elderly samples and 68 young healthy samples were analyzed for DEGs. Compared to young healthy muscle tissue, T cell infiltration levels in aged muscle tissue were significantly reduced, while mast cell and monocyte infiltration levels were relatively elevated. A new diagnostic screening model for sarcopenia based on the six IPRGs demonstrated high predictive efficiency (AUC = 0.871). qRT-PCR results indicated that the expression trends of these six IPRGs aligned with those observed in the database.

Conclusion: Six biomarkers-BTG2, FOXO3, AQP9, GPC3, CYCS, and SCN1B-were identified alongside a diagnostic model that offers a novel approach for early diagnosis of sarcopenia.

Background: Zanthoxylum L., an important genus in the Rutaceae family, has great edible and medical values. However, the high degree of morphological similarity among Zanthoxylum species and the lack of sufficient chloroplast (cp) genomic resources have greatly impeded germplasm identification and phylogenetic analyses of Zanthoxylum.

Methods: Here we assembled cp genomes of five widespread species (Zanthoxylum bungeanum, Z. armatum, Z. nitidum, Z. ailanthoides and Z. piasezkii) in China as a case study, comparative analysis of these assembled cp genomes.

Results: Each of them, ranging from 157,231 to 158,728 bp, has a quadripartite structure. Except for one extra gene in Z. piasezkii, 132 genes were identified in each species, including 87 encode protein genes, 37 transfer ribose nucleic acid (tRNA) genes, and eight ribosomal RNA (rRNA) genes. Substantial variation was observed among these five cp genome sequences in the IR/SC boundary regions. Variation in insertions and deletions were observed in the cp genomes of the five species over three different intervals, and a large number of single-nucleotide polymorphism variants were detected in the rps3-rpl22-rps19 region. Phylogenetic analysis of complete cp genome sequences revealed the evolutionary relationships among 23 Zanthoxylum species (29 samples).

Conclusion: Comparative analysis revealed that rps3-rpl22-rps19 is a highly variable divergent region in Zanthoxylum that could be developed as candidate markers for phylogenetic studies and species identification. This study identified a pair of molecular markers from hypervariable regions that can be used to distinguish between the five Zanthoxylum species and validated their utility. Overall, the results of this study provide new insights into the genetic breeding, germplasm exploration, and phylogeny of Zanthoxylum species.

Background: IgA nephropathy (IgAN) is a leading cause of renal failure, but its pathogenesis remains unclear, complicating diagnosis and treatment. The invasive nature of renal biopsy highlights the need for non-invasive diagnostic biomarkers. Bulk RNA sequencing (RNA-seq) of urine offers a promising approach for identifying molecular changes relevant to IgAN.

Methods: We performed bulk RNA-seq on 53 urine samples from 11 untreated IgAN patients and 11 healthy controls, integrating these data with public renal RNA-seq, microarray, and scRNA-seq datasets. Machine learning was used to identify key differentially expressed genes, with protein expression validated by immunohistochemistry (IHC) and drug-target interactions explored via molecular docking.

Results: Urine RNA-seq analysis revealed differential expression profiles, from which TYROBP and HCK were identified as key biomarkers using machine learning. These biomarkers were validated in both a test cohort and an external validation cohort, demonstrating strong predictive accuracy. scRNA-seq confirmed their cell-specific expression patterns, correlating with renal function metrics such as GFR and serum creatinine. IHC further validated protein expression, and molecular docking suggested potential therapeutic interactions with IgAN treatments.

Conclusion: TYROBP and HCK are promising non-invasive urinary biomarkers for IgAN. Their predictive accuracy, validated through machine learning, along with IHC confirmation and molecular docking insights, supports their potential for both diagnostic and therapeutic applications in IgAN.

[This corrects the article DOI: 10.3389/fgene.2021.625867.].

Objectives: Investigate the predictive value of Vasculogenic mimicry (VM) related genes for the survival and prognosis of Hepatocellular carcinoma (HCC) patients and its role in the tumor microenvironment (TME).

Methods: VM-related genes were obtained from previous literature, the expression profiles, single-cell data and clinical information of HCC patients were downloaded from public databases. The HCC patients were divided into different clusters by unsupervised clustering, the differences in prognosis and immune characteristics of VM-related clusters were analyzed. A prognostic model related to VM (VM Score) was constructed based on LASSO regression and univariate and multivariate Cox regression, the correlation between this model and chemotherapy drugs and immunotherapy was studied. Seurat package was used to standardize single-cell data for single-cell level analysis. The expression of risk factors in VM Score was verified by RT-qPCR.

Results: VM Score composed of SPP1, ADAMTS5 and ZBP1 was constructed and validated. VM Score was an independent prognostic factor for HCC. Through the analysis of single cell data further reveals the VM Score influence on TME. In addition, VM Score could provide ideas for the selection of immunotherapy and chemotherapy drugs. RT-qPCR showed that the expression of risk factors was different in HCC cell lines.

Conclusion: Our results suggest that VM Score may serve as a promising prognostic biomarker for HCC and provide new ideas for immunotherapy in HCC patients.

Introduction: Malaria molecular surveillance (MMS) can provide insights into transmission dynamics, guiding national control programs. We previously designed AmpliSeq assays for MMS, which include different traits of interest (resistance markers and pfhrp2/3 deletions), and SNP barcodes to provide population genetics estimates of Plasmodium vivax and Plasmodium falciparum parasites in the Peruvian Amazon. The present study compares the genetic resolution of the barcodes in the AmpliSeq assays with widely used microsatellite (MS) panels to investigate population genetics of Amazonian malaria parasites.

Methods: We analyzed 51 P. vivax and 80 P. falciparum samples from three distinct areas in the Loreto region of the Peruvian Amazon: Nueva Jerusalén (NJ), Mazan (MZ), and Santa Emilia (SE). Population genetics estimates and costs were compared using the SNP barcodes (P. vivax: 40 SNPs and P. falciparum: 28 SNPs) and MS panels (P. vivax: 16 MS and P. falciparum: 7 MS).

Results: The P. vivax genetic diversity (expected heterozygosity, He) trends were similar for both markers: He _MS = 0.68-0.78 (p > 0.05) and He _SNP = 0.36-0.38 (p > 0.05). P. vivax pairwise genetic differentiation (fixation index, F_ST) was also comparable: F_ST-MS = 0.04-0.14 and F_ST-SNP = 0.03-0.12 (pairwise p > 0.05). In addition, P. falciparum genetic diversity trends (He _MS = 0-0.48, p < 0.05; He _SNP = 0-0.09, p < 0.05) and pairwise F_ST comparisons (F_ST-MS = 0.14-0.65, F_ST-SNP = 0.19-0.61, pairwise p > 0.05) were concordant between both panels. For P. vivax, no geographic clustering was observed with any panel, whereas for P. falciparum, similar population structure clustering was observed with both markers, assigning most parasites from NJ to a distinct subpopulation from MZ and SE. We found significant differences in detecting polyclonal infections: for P. vivax, MS identified a higher proportion of polyclonal infections than SNP (69% vs. 33%, p = 3.3 × 10^-5), while for P. falciparum, SNP and MS detected similar rates (46% vs. 31%, p = 0.21). The AmpliSeq assay had a higher estimated per-sample cost compared to MS ($183 vs. $27-49).

Discussion: The SNP barcodes in the AmpliSeq assays offered comparable results to MS for investigating population genetics in P. vivax and P. falciparum populations, despite some discrepancies in determining polyclonality. Given both panels have their respective advantages and limitations, the choice between both should be guided by research objectives, costs, and resource availability.

Acylation represents a pivotal biochemical process that is instrumental in the modification of secondary metabolites throughout the growth and developmental stages of plants. The BAHD acyltransferase family within the plant kingdom predominantly utilizes coenzyme A thioester as the acyl donor, while employing alcohol or amine compounds as the acceptor substrates to facilitate acylation reactions. Using bioinformatics approaches, the LjBAHD gene family members in the genome of Leonurus japonicus (L. japonicus) were identified and characterized including gene structure, conserved motifs, cis-acting elements, and potential gene functions. To elucidate the roles of BAHD genes in various tissues of L. japonicus, the expression profiles of LjBAHD family members across different organs were scrutinized. Under drought stress treatment, some LjBAHDs were upregulation, suggesting their potential involvement in drought response. Notably, a detailed study was conducted on a specific HCT gene (i.e., LjBAHD25) within the BAHD gene family. Analysis of its expression patterns suggested a role for LjBAHD25 in the phenylpropanoid metabolism pathway in L. japonicus, contributing to the biosynthesis of secondary metabolites with unique bioactivity. The findings of this study have established a scientific foundation for the subsequent development and functional validation of the BAHD gene family in L. japonicus.