Genes & genomics最新文献

Background: Hepatocellular carcinoma (HCC) is a highly malignant tumor; however, its immune microenvironment and mechanisms remain elusive. Single-cell sequencing allows for the exploration of immune characteristics within tumor at the cellular level. However, current knowledge regarding the roles of different immune cell populations in liver cancer progression is limited.

Objective: The main objective of this study is to identify molecular markers with NK cell immune characteristics in hepatocellular carcinoma using various machine learning methods based on Single-Cell Sequencing and Bulk RNA Sequencing.

Methods: We collected samples from eight normal liver tissues and eight HCC tumor tissues and performed single-cell RNA sequencing for immune cell clustering and expression profile analysis. Using various bioinformatic approaches, we investigated the immune phenotype associated with natural killer (NK) cells expressing high CD7 level. In addition, we verified the role of CD7 in the growth of HCC after NK cell and HCC cells cocultured by RT-qPCR, MTS and Flow cytometer experiments. Finally, we constructed a machine learning model to develop a prognostic prediction system for HCC based on NK cell-related genes.

Results: Through single-cell typing, we found that the proportions of hepatocytes and NK cells were significantly elevated in the tumor samples. Moreover, we found that the expression of CD7 was high in HCC and correlated with prognosis. More importantly, Overexpression of CD7 in NK cells significantly inhibited the activity of MHCC97 cells and increased the number of apoptosis of HCC cells (p < 0.05). Furthermore, we observed that NK cells with high CD7 expression were associated with an activated immune phenotype.

Conclusion: Our study found that CD7 is an important biomarker for assessing immune status and predicting survival of HCC patients; hence, it is a potential target for immune therapy against HCC.

Background: Darier's disease (DD) is a skin disorder caused by mutations in the ATP2A2 gene. Researchers have been investigating the correlation between genotype and phenotype in DD. Understanding the genotype-phenotype relationship in DD can enhance our comprehension of the genetic background and phenotypic characteristics of the condition, as well as the relationship between its systemic and localized manifestations.

Objectives: This study aimed to investigate the molecular pathogenesis of DD in a Chinese family, and to elucidate the genotype-phenotype correlation in DD by summarizing relevant literature.

Methods: Gene mutations associated with DD were screened by whole-exome sequencing and verified using Sanger sequencing. Genetic analysis assessed the potential impact of these mutations. Genotype-phenotype correlation was obtained by chi-square analysis using literature search test.

Results: (1) A novel ATP2A2 Missense mutation, c.2560T>C (p.W854R), was identified and confirmed by Sanger sequencing. Annotation analysis with the ANNOVAR tool indicated that this mutation disrupts normal protein function and is linked to DD clinical manifestations. (2) Genotype-phenotype analysis showed a significant correlation between the prevalence of DD-related mental disorders and geographic regions (P = 0.00), but no association between mutation type and mental disorder prevalence (P = 0.324). The age of onset varied between sporadic and familial cases (P = 0.032), averaging 33 years in sporadic cases and 16 years in familial cases.

Conclusion: By analyzing the genotype-phenotype correlation, we aim to enhance our understanding of the genetic basis of DD. This research could improve early diagnosis, intervention, and the development of personalized long-term health management plans.

Background: Persicaria amphibia, a member of the Polygonaceae family, exists both aquatic and terrestrial forms. It is native to North America, Asia, Europe, and some parts of Africa.

Objective: This study aimed to determine the genetic diversity within and among populations of P. amphibia and the distribution characteristics of each population to investigate insights into the genetic structure and conservation of P. amphibia.

Methods: In this study, the genetic diversity and structure of 84 P. amphibia individuals from 7 populations in South Korea were analyzed using genotyping-by-sequencing (GBS). We used 2,469 single nucleotide polymorphisms (SNPs) to analyze genetic diversity, principal components, structure, and phylogeny.

Results: Our results showed a mean observed heterozygosity and mean expected heterozygosity of 0.34409 and 0.34082, respectively. Genetic diversity analysis indicated that the variation among populations (60.08%) was greater than that within populations (39.92%). Fixation index values, principal components analysis, structure, and phylogeny analyses showed that the population in Gyodongdo, Ganghwa Island was highly different.

Conclusion: These results provide important insights for better understand the population history and genetic structure of P. amphibia.

Background: Parkinson's disease (PD) is a progressive neuro-degenerative disorder most common in older adults which is associated with impairments in movement and other body functions. Most PD cases are classified as idiopathic PD (IPD), meaning that the etiology remains unidentified.

Objective: To identify key genes and molecular mechanisms to identify biomarkers applicable to IPD.

Methods: We applied a bioinformatics approach using a gene expression in whole blood dataset to pinpoint differentially expressed genes (DEGs) and pathways involved in IPD. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses of DEGs were subsequently performed. A protein-protein interaction (PPI) network was then constructed to select hub genes that may influence IPD. We further investigated the levels of differentially methylated regions (DMRs) and differentially expressed microRNA (DEMs) of whole blood of patients with IPD to validate hub genes. Additionally, we examined the hub gene expression patterns in the substantia nigra (STN) using single-cell RNA sequencing datasets.

Results: In total, we identified 124 DEGs in the blood samples of patients with IPD, with GO and KEGG analyses highlighting their significant enrichment. Analysis of PPI networks revealed three major clusters and hub genes: small nuclear ribonucleoprotein polypeptide E (SNRPE), cytochrome C oxidase subunit 7 C (COX7C), and ribosomal protein S27 (RPS27). DMRs and DEMs analyses revealed hub gene regulation via epigenetic and RNA interference. In particular, SNRPE and RPS27 showed identically regulated gene expression in the STN.

Conclusion: This study suggests that SNRPE, COX7C, and RPS27 in whole-blood samples derived from patients may be useful biomarkers for IPD.

Background: Palmoplantar keratoderma (PPK) is a heterogeneous group of disorders characterized by abnormal thickening of the skin on the palms and soles. Striate palmoplantar keratoderma (SPPK) is commonly caused by heterozygous mutations in the desmoglein-1 (DSG1) gene.

Objective: This study aimed to report a case of a 36-year-old Chinese female patient with SPPK caused by a novel DSG1 gene mutation, along with her family history, and explore its potential relationship with other genetic variants.

Methods: Whole-exome sequencing was performed on the patient and their family members to identify the pathogenic mutation, which was validated by Sanger sequencing. Histological and electron microscopy analyses were conducted to examine the pathological characteristics of skin tissue.of skin tissue.

Results: A frameshift mutation, c.1285del, in exon 10 of the DSG1 gene was identified, leading to a loss of protein function and resulting in SPPK. This mutation was also detected in two other family members with similar phenotypes. Additionally, a classical splicing variant, c.313+2dup, in the low-density lipoprotein receptor (LDLR) gene associated with hypercholesterolemia was identified in the patient; however, no direct association with SPPK was observed.

Conclusion: This study was the first to report a novel mutation in the DSG1 gene associated with SPPK and suggested a potential role of the LDLR gene variant in SPPK patients, providing new insights for further research into the genetic mechanisms underlying SPPK.

Streptococcus agalactiae (S. agalactiae) is a highly pathogenic bacterial pathogen in aquatic animals. Our previous study has demonstrated the significant inhibitory effect of baicalin on β-hemolytic/cytolytic activity, which is a key virulence factor of S. agalactiae. In this study, we aimed to elucidate the mechanism underlying baicalin's inhibition of S. agalactiae β-hemolytic/cytolytic activity by transcriptomic analysis. Bacteria were exposed to 39.06 µg/mL baicalin for 6 h, and their β-hemolytic/cytolytic activities were assessed using blood plates. Then, the differentially expressed genes (DEGs) were identified and characterized by RNA sequencing (RNA-Seq), and further confirmed using the qRT-PCR. A total of 10 DEGs with 7 significantly up-regulated and 3 significantly down-regulated, were found to be affected significantly under baicalin treatment. These DEGs were associated with 5 biological processes, 5 cellular components, and 3 molecular functions. They were primarily enriched in 3 pathways: lacD and lacC in galactose metabolism, lrgA and lrgB in the two-component system, and ribH/rib4 in riboflavin metabolism. These suggested that baicalin might inhibit the conversion of pyruvate to acetyl-CoA and malonyl-CoA, which are crucial precursors for β-hemolysin/cytolysin synthesis, and result in the accumulation of pyruvate, suppress the expressions of pyruvate cell membrane channel protein genes lrgA and lrgB. Baicalin could compensatory up-regulate the expressions of tryptophan/tyrosine ABC transporter family genes, ABC.X4.A, ABC.X4.P, and ABC.X4.S by inhibiting the expression of cyl A/B in cyl operons. Moreover, it hinders the conversion of D-glucose 1-phosphate to the dTDP-L-rhamnose pathway and leads to a deficiency of L-rhamnose, an important precursor for β-hemolysin/cytolysin synthesis.

Background: We have previously reported anatomical, histological, and gene expression characteristics of the nodal structure of rat skin surface and suggested its potential as an acupuncture point. However, the specific characteristics of the interactions among the genes expressed in this structure remain unclear.

Objective: We aimed to determine gene expression changes by analyzing interaction networks of genes up-regulated in nodal structures and to explore relationships with acupuncture points.

Methods: We investigated the relationship between the nodal structures and acupuncture points by analyzing the interactions of up-regulated genes, their Gene Ontology biological functions, and the characteristics of Kyoto Encyclopedia of Genes and Genomes pathways. RNA-seq and STRING analysis provided comprehensive information on these gene groups.

Results: Interactions between up-regulated genes in nodal structures were classified into three groups. The first group, which includes Wnt7b, Wnt3, and Wnt16, showed significant interactions in pathways such as Wnt signaling, Alzheimer's disease, and regulation of stem cell pluripotency. The second group, composed of Fos, Dusp1, Pla2g4e, Pla2g4f, and Fgfr3, demonstrated a notable association with the MAPK signaling pathway. Lastly, the third group, consisting of Adcy1, Pla2g4e, Pla2g4f, and Dusp1 exhibited effective interactions with the inflammatory mediator regulation of TRP channels and serotonergic synapse.

Conclusion: Continued research on nodal structures where these genes are expressed is needed to improve our understanding of skin anatomy and physiology as well as their potential clinical utility as acupuncture points.

Background: The permutation test has been widely used to provide the p-values of statistical tests when the standard test statistics do not follow parametric null distributions. However, the permutation test may require huge numbers of iterations, especially when the detection of very small p-values is required for multiple testing adjustments in the analysis of datasets with a large number of features.

Objective: To overcome this computational burden, we suggest a novel enhanced adaptive permutation test that estimates p-values using the negative binomial (NB) distribution. By the method, the number of permutations are differently determined for individual features according to their potential significance.

Methods: In detail, the permutation procedure stops, when test statistics from the permuted dataset exceed the observed statistics from the original dataset by a predefined number of times. We showed that this procedure reduced the number of permutations especially when there were many insignificant features. For significant features, we enhanced the reduction with Stouffer's method after splitting datasets.

Results: From the simulation study, we found that the enhanced adaptive permutation test dramatically reduced the number of permutations while keeping the precision of the permutation p-value within a small range, when compared to the ordinary permutation test. In real data analysis, we applied the enhanced adaptive permutation test to a genome-wide single nucleotide polymorphism (SNP) dataset of 327,872 features.

Conclusion: We found the analysis with the enhanced adaptive permutation took a feasible time for genome-wide omics datasets, and successfully identified features of highly significant p-values with reasonable confidence intervals.

Background: Identifying the origins of biological traces is critical for the reconstruction of crime scenes in forensic investigations. Traditional methods for body fluid identification rely on chemical, enzymatic, immunological, and spectroscopic techniques, which can be sample-consuming and depend on simple color-change reactions. However, these methods have limitations when residual samples are insufficient after DNA extraction.

Objective: This study aimed to develop a method for body fluid identification by leveraging bacterial DNA profiling to overcome the limitations of the conventional approaches.

Methods: Bacterial profiles were determined by sequencing the hypervariable region of the 16 S rRNA gene, using DNA metabarcoding of evidence collected from criminal cases. Amplicon sequence variants (ASVs) were analyzed to identify significant microbial patterns in different body fluid samples.

Results: The bacterial profile-based method demonstrated high discriminatory power with a machine learning model trained using the naïve Bayes algorithm, achieving an accuracy of over 98% in classifying samples into one of four body fluid types: blood, saliva, vaginal secretion, and mixture traces of vaginal secretions and semen.

Conclusion: Bacterial profiling enhances the accuracy and robustness of body fluid identification in forensic analysis, providing a valuable alternative to traditional methods by utilizing DNA and microbial community data despite the uncontrollable conditions. This approach offers significant improvements in the classification accuracy and practical applicability in forensic investigations.

Background: In Korea, only Polygala tenuifolia is registered as Polygalae Radix in the pharmacopoeia, while in China, both P. tenuifolia and P. sibirica are used equally. Accurate identification of herbal medicines is crucial for their safety and efficacy, but commercial products are typically sold in dried form, making morphological distinction difficult. Therefore, a quick and accurate method to distinguish P. tenuifolia is necessary for proper utilization of medicinal herb.

Objective: We aimed to identify specific molecular markers for P. tenuifolia to avoid confusion regarding its pharmacological efficacy and to evaluate the classification of Polygala using plastid phylogenetic data.

Methods: We analyzed the sequences of three species distributed in Korea, P. tenuifolia, P. japonica, and P. sibirica, and assembled their chloroplast genome sequences. Comparative analysis revealed regions of local divergence, and six molecular markers were developed from these hotspots. Additionally, a phylogenetic tree was constructed to determine the phylogenetic positions of the three Polygala species.

Results: The marker successfully identified the three Polygala species, and all commercial products and breeding lines tested were confirmed to be P. tenuifolia and recognized as authentic. Phylogenetic analysis revealed that P. tenuifolia forms a distinct cluster from P. sibirica and P. japonica.

Conclusions: We determined the chloroplast genomes of the three Polygala species and performed phylogenetic tree analysis and marker development. Indel markers were developed to identify the critical herbal species, P. tenuifolia. This comprehensive study of the Polygala chloroplast genome provides useful information for P. tenuifolia identification.