Molecular Genetics and Genomics最新文献

Autosomal-recessive cutis laxa type 2 (ARCL2) is a rare genetic disorder caused by pyrroline-5-carboxylate reductase 1 (PYCR1) mutations and characterized by loose and sagging skin, typical facial features, intrauterine growth retardation, and developmental delay. To study the effect of PYCR1 mutations on protein function and clinical features, we identified a homozygous missense mutation c.559G > A (p.Ala187Thr) in PYCR1 in a Chinese child with typical clinical features, especially severe developmental delays. The three-dimensional (3D) model showed the modification of the hydrogen bonds produce a misfolding in the mutant PYCR1 protein. Mutagenesis and enzyme assay study revealed decreased activity of the mutant protein in vitro, indicating that this mutation impairs PYCR1 function. Our findings confirmed abnormal enzymatic activity and neurodevelopmental trajectory of this PYCR1 mutation.

The purpose of this study was to analyze and molecularly describe the largest group of patients with ABCA4-associated retinal degeneration in Latin America. Pathogenic variants in ABCA4, a member of the ATP Binding Cassette (ABC) transporters superfamily, is one of the most common causes of inherited visual deficiency in humans. Retinal phenotypes associated with genetic defects in ABCA4 are collectively known as ABCA4-associated retinal degenerations (ABCA4R), a group of recessively inherited disorders associated with a high allelic heterogeneity. While large groups of Caucasian and Asiatic individuals suffering from ABCA4R have been well characterized, molecular information from certain ethnic groups is limited or unavailable, precluding a more realistic knowledge of ABCA4-related mutational profile worldwide. In this study, we describe the molecular findings of a large group of 211 ABCA4R index cases from Mexico. Genotyping was performed using either next generation sequencing (NGS) of a retinal dystrophy genes panel or exome. ABCA4 targeted mutation testing was applied to a subgroup of subjects in whom founder mutations were suspected. A total of 128 different ABCA4 pathogenic variants were identified, including 22 previously unpublished variants. The most common type of genetic variation was single nucleotide substitutions which occurred in 92.7% (408/440 alleles). According to the predicted protein effect, the most frequent variant type was missense, occurring in 83.5% of disease-causing alleles (368/440). Mutations such as p.Ala1773Val are fully demonstrated as a founder effect in native inhabitants of certain regions of Mexico. This study also gives us certain indications of other founder effects that need to be further studied in the near future. This is the largest molecularly characterized ABCA4R Latin American cohort, and our results supports the value of conducting genetic screening in underrepresented populations for a better knowledge of the mutational profile leading to monogenic diseases.

Height is known to be a classically heritable trait controlled by complex polygenic factors. Numerous height-associated genetic variants across the genome have been identified so far. It is also a representative of externally visible characteristics (EVC) for predicting appearance in forensic science. When biological evidence at a crime scene is deficient in identifying an individual, the examination of forensic DNA phenotyping using some genetic variants could be considered. In this study, we aimed to predict 'height', a representative forensic phenotype, by using a small number of genetic variants when short tandem repeat (STR) analysis is hard with insufficient biological samples. Our results not only replicated previous genetic signals but also indicated an upward trend in polygenic score (PGS) with increasing height in the validation and replication stages for both genders. These results demonstrate that the established SNP sets in this study could be used for height estimation in the Korean population. Specifically, since the PGS model constructed in this study targets only a small number of SNPs, it contributes to enabling forensic DNA phenotyping even at crime scenes with a minimal amount of biological evidence. To the best of our knowledge, this was the first study to evaluate a PGS model for height estimation in the Korean population using GWAS signals. Our study offers insight into the polygenic effect of height in East Asians, incorporating genetic variants from non-Asian populations.

Ovarian clear cell carcinoma (OCCC) is a subtype of ovarian cancer and is highly malignant with high chemoresistance. CACNA1H is pivotal in tumor development. However, the role of CACNA1H in the acquisition process of chemotherapeutic resistance in OCCC cells is rarely reported. Therefore, this study aimed to explore the role of CACNA1H in chemotherapy resistance of OCCC cells and its related mechanism. Based on bioinformatics analysis, we found that CACNA1H was downregulated in chemoresistant OCCC patients compared to chemosensitive OCCC patients. Comparing DDP-resistant and sensitive OCCC cell lines, the resistant strain showed lower CACNA1H mRNA expression. CACNA1H expression was associated with calcium signaling pathways in chemoresistant OCCC patients. CACNA1H mRNA expression was significantly downregulated in OCCC cells compared to normal ovarian epithelial cells. When CACNA1H was overexpressed, intracellular Ca²⁺ concentration and protein levels of p-CaMKII and p-Akt were significantly upregulated, while protein levels of LC3-II/LC3-I and Beclin1 were downregulated, indicating a repression of autophagy. The rescue experiment revealed that CACNA1H overexpression in drug-resistant OCCC cells reduced autophagy-induced DDP resistance via CaMKII/Akt signaling. Overall, CACNA1H increased intracellular Ca²⁺ concentration and activated CaMKII/Akt signaling pathway in OCCC, thereby repressing autophagy to maintain the sensitivity of OCCC cells to DDP.

Lung Squamous Cell Carcinoma is characterised by significant alterations in RNA expression patterns, and a lack of early symptoms and diagnosis results in poor survival rates. Our study aimed to identify the hub genes involved in LUSC by differential expression analysis and their influence on overall survival rates in patients. Thus, identifying genes with the potential to serve as biomarkers and therapeutic targets. RNA sequence data for LUSC was obtained from TCGA and analysed using R Studio. Survival analysis was performed on DE genes. PPI network and hub gene analysis was performed on survival-relevant genes. Enrichment analysis was conducted on the PPI network to elucidate the functional roles of hub genes. Our analysis identified 2774 DEGs in LUSC patient datasets. Survival analysis revealed 511 genes with a significant impact on patient survival. Among these, 20 hub genes-FN1, ACTB, HGF, PDGFRB, PTEN, SNAI1, TGFBR1, ESR1, SERPINE1, THBS1, PDGFRA, VWF, BMP2, LEP, VTN, PXN, ABL1, ITGA3 and ANXA5-were found to have lower expression levels associated with better patient survival, whereas high expression of SOX2 correlated with longer survival. Enrichment analysis indicated that these hub genes are involved in critical cellular and cancer-related pathways. Our study has identified six key hub genes that are differentially expressed and exhibit significant influence over LUSC patient survival outcomes. Further, in vitro and in vivo studies must be conducted on the key genes for their utilisation as therapeutic targets and biomarkers in LUSC.

The clustered regularly interspaced short palindromic repeats (CRISPR) and their associated protein (Cas) system is a gene editing technology guided by RNA endonuclease. The CRISPR-Cas12a (also known as CRISPR-Cpf1) system is extensively utilized in genome editing research due to its accuracy and high efficiency. In this paper, we primarily focus on the application of CRISPR-Cpf1 technology in the construction of disease models and gene therapy. Firstly, the structure and mechanism of the CRISPR-Cas system are introduced. Secondly, the similarities and differences between CRISPR-Cpf1 and CRISPR-Cas9 technologies are compared. Thirdly, the main focus is on the application of the CRISPR-Cpf1 system in cell and animal genome editing. Finally, the challenges faced by CRISPR-Cpf1 technology and corresponding strategies are analyzed. Although CRISPR-Cpf1 technology has certain off-target effects, it can effectively and accurately edit cell and animal genomes, and has significant advantages in the preclinical research.

Derivation of hypoimmunogenic human cells from genetically manipulated pluripotent stem cells holds great promise for future transplantation medicine and adoptive immunotherapy. Disruption of beta-2-microglobulin (B2M) in pluripotent stem cells followed by differentiation into specialized cell types is a promising approach to derive hypoimmunogenic cells. Given the attractive features of CRISPR/Cas9-based gene editing tool and baculoviral delivery system, baculovirus can deliver CRISPR/Cas9 components for site-specific gene editing of B2M. Herein, we report the development of a baculoviral CRISPR/Cas9 vector system for the B2M locus disruption in human cells. When tested in human embryonic stem cells (hESCs), the B2M gene knockdown/out was successfully achieved, leading to the stable down-regulation of human leukocyte antigen class I expression on the cell surface. Fibroblasts derived from the B2M gene-disrupted hESCs were then used as stimulator cells in the co-cultures with human peripheral blood mononuclear cells. These fibroblasts triggered significantly reduced alloimmune responses as assessed by sensitive Elispot assays. The B2M-negative hESCs maintained the pluripotency and the ability to differentiate into three germ lineages in vitro and in vivo. These findings demonstrated the feasibility of using the baculoviral-CRISPR/Cas9 system to establish B2M-disrupted pluripotent stem cells. B2M knockdown/out sufficiently leads to hypoimmunogenic conditions, thereby supporting the potential use of B2M-negative cells as universal donor cells for allogeneic cell therapy.

Codon usage bias (CUB), the uneven usage of synonymous codons encoding the same amino acid, differs among genes within and across bacteria genomes. CUB is known to be influenced by gene expression and accordingly, CUB differs between the high-expression and low-expression genes in several bacteria. In this article, we have extended codon usage study considering gene essentiality as a feature. Using machine learning (ML) based approaches, we have analysed Relative Synonymous Codon Usage (RSCU) values between essential and non-essential genes in Escherichia coli and thirty-four other bacterial genomes whose gene essentiality features were available in public databases. We observed significant differences in codon usage patterns between essential and non-essential genes for majority of the bacterial genomes and accordingly, ML based classifiers achieved high area under curve (AUC) scores, with a minimum score of 70.0 across twenty-eight organisms. Further, importance of the codons towards classifying genes found to differ among the codons in each genome. Arg codon CGT and Gly codon GGT were observed to be the most preferred codons among essential genes in Escherichia coli. Interestingly, some of the codons like CGT, ATA, GGT and GGG observed to be contributing consistently towards classifying essential genes across thirty-five bacteria genomes studied. In other hand, codons TGY and CAY encoding amino acids Cys and His respectively were among the least contributing codons towards classification among all these bacteria. This study demonstrates the gene essentiality based differences in synonymous codon usage in bacteria genomes and presents a common codon usage pattern across bacteria.

Exploring the intricate relationships between plants and their resident microorganisms is crucial not only for developing new methods to improve disease resistance and crop yields but also for understanding their co-evolutionary dynamics. Our research delves into the role of the phyllosphere-associated microbiome, especially Actinomycetota species, in enhancing pathogen resistance in Theobroma grandiflorum, or cupuassu, an agriculturally valuable Amazonian fruit tree vulnerable to witches’ broom disease caused by Moniliophthora perniciosa. While breeding resistant cupuassu genotypes is a possible solution, the capacity of the Actinomycetota phylum to produce beneficial metabolites offers an alternative approach yet to be explored in this context. Utilizing advanced long-read sequencing and metagenomic analysis, we examined Actinomycetota from the phyllosphere of a disease-resistant cupuassu genotype, identifying 11 Metagenome-Assembled Genomes across eight genera. Our comparative genomic analysis uncovered 54 Biosynthetic Gene Clusters related to antitumor, antimicrobial, and plant growth-promoting activities, alongside cutinases and type VII secretion system-associated genes. These results indicate the potential of phyllosphere-associated Actinomycetota in cupuassu for inducing resistance or antagonism against pathogens. By integrating our genomic discoveries with the existing knowledge of cupuassu’s defense mechanisms, we developed a model hypothesizing the synergistic or antagonistic interactions between plant and identified Actinomycetota during plant-pathogen interactions. This model offers a framework for understanding the intricate dynamics of microbial influence on plant health. In conclusion, this study underscores the significance of the phyllosphere microbiome, particularly Actinomycetota, in the broader context of harnessing microbial interactions for plant health. These findings offer valuable insights for enhancing agricultural productivity and sustainability.

Background: DNA methylation is an important epigenetic modification that plays a crucial role in the development and progression of various tumors. However, the association between methylation‑driven genes and diagnosis, prognosis, and immune characteristics of head and neck squamous cell carcinoma (HNSCC) remains unclear.

Methods: We obtained transcriptome, methylation, and clinical data from HNSCC patients in TCGA database, and used MethylMix algorithm to identify methylation-driven genes. A methylation driven gene-related risk model was constructed using Lasso regression analysis, and validated using data from GEO database. Immune infiltration and immune function analysis of the expression profiles were conducted using ssGSEA. Differences in immune checkpoint-related genes were analyzed, and the efficacy of immunotherapy was evaluated using TCIA database. Finally, a series of cell functional experiments were conducted to validate the results.

Results: Five methylation-driven genes were identified and utilized to construct a prognostic risk model. Based on the median risk score, all patients were categorized into high-risk and low-risk groups. The K-M analysis revealed that patients in the high-risk group have a worse prognosis. Additionally, the risk model demonstrated better prognostic predictive value as indicated by ROC analysis. GSEA enrichment analysis indicated that gene sets in the high and low-risk groups were primarily enriched in pathways associated with tumor immunity and metabolism. Our subsequent investigations showed that high-risk patients exhibited more immunosuppressive phenotypes, while low-risk patients were more likely to respond positively to immunotherapy.

Conclusion: These findings of our research have the potential to improve patient stratification, guide treatment decisions, and advance the development of personalized therapies for HNSCC.