Biochemical Genetics最新文献

Type 1 diabetes mellitus (T1DM) and its associated complications result from the interplay between genetic and environmental factors, with inflammation playing a central role in their pathogenesis. This study aimed to assess the association between TGF-β1 gene variants and T1DM, as well as its neuropathy, in the Algerian population. A case-control study was conducted, analyzing 344 blood samples. The TGF-β1 rs1800470 and rs1800471 were genotyped using the PCR-SSP method. Genotype and allele frequencies were compared among participants, and phenotype-genotype interactions were determined.The results revealed that the TGF-β1 rs1800470 CC genotype was significantly more frequent in patients (OR = 2.08, p = 0.016), while the GC genotype was significantly more frequent in controls (OR = 0.49, p = 0.001). The C allele (OR = 2.97, p < 0.0001) and the GC genotype (OR = 2.93, p = 0.0003) of the TGF-β1 rs1800471 were significantly more frequent in T1DM patients, while the G allele (OR = 0.34, p < 0.0001) and GG genotype (OR = 0.32, p < 0.0001) were more frequent in controls. Furthermore, the GG genotype of rs1800471 was associated with diabetic neuropathy (OR = 3.30, p = 0.03), and carrying at least one copy of the minor C allele was linked to higher levels of total cholesterol (p = 0.0096) and triglycerides (p = 0.001). Based on these data, we suggest an association between the TGF-β1 variants rs1800470 and rs1800471 and susceptibility to T1DM. Furthermore, the rs1800471 variant may be involved in the development of diabetic neuropathy with a possible impact on lipid profiles.

Diabetes and Hyperlipidemia are major risk factors for stroke across the world population. TCF7L2, a key regulator of the WNT signaling pathway shows genetic association with these metabolic disorders in ethnicity dependant manner. However, its role in stroke pathogenesis (if any) is not well characterized. Here, we aim to (a) investigate and correlate dysregulation of TCF7L2 expression with diabetes or hyperlipidemia-associated Ischemic Stroke (b) identify genetic risk variants in the TCF7L2 gene, and (c) establish correlations between TCF7L2 mRNA levels and biochemical parameters. Based on radiological findings for Ischemic Stroke, a total of 50 unrelated subjects were recruited with diverse biochemical parameters for TCF7L2 mRNA expression study in PBMC, followed by correlation with fasting blood sugar and lipid profile. Furthermore, mutation screening (31 Cases and 30 Controls) and genetic association studies (rs7901695 & rs7903146) were performed among 326 cases and 258 controls from two different ethnic population of India. In our study, a significant downregulation of TCF7L2 transcript was observed between stroke cases and controls as major finding. Furthermore, stratification of stroke cases, according to their blood lipid and glucose level revealed a lower quantity of TCF7L2 transcript in hyperlipidemia stroke cases than non-hyperlipidemia subjects. However, no such association against diabetic status was observed. A simultaneous finding showing negative correlation of gene expression with total blood cholesterol level (P = 0.0187; r = - 0.4012) but not for diabetes, thus suggests TCF7L2 mediated altered lipid metabolism as a risk for stroke pathogenesis. On the other hand, allelic (P = 0.0207) and genotypic (P = 0.0002) association of functional variants like rs7901695 variants [P = 0.0207] among the majorly Bengali population of Kolkata and rs7903146 [P = 0.0164] among the Gujarati cohort was observed, respectively. Thus, on basis of our findings, genotyping of TCF7L2 variants or quantification of transcript, consumption of low-fat diet may be recommended to hyperlipidemia individuals for risk prediction and preventive treatment regimen, respectively.

Acute ischemic stroke (AIS) is the primary reason for death. CircRNAs have become a hotspot of stroke research. The study aimed to detect the concentration of circ_0020850 and elucidate its prognostic roles. Differently expressed circRNAs and miRNAs were identified based on the GEO database. Serum samples were collected from AIS and healthy persons to assess the levels of circ_0020850 and miR-629 before and after rehabilitation. Their interrelationships with MMSE scores were evaluated using the Spearman method. The targeted connection was verified by luciferase reporter assay. ROC and logistic regression further revealed the prognostic roles of circ_0020850 and miR-629. GO, KEGG, PPI methods were applied for potential functional and pathway analysis of targets of miR-629. The upregulation of circ_0020850 and downregulation of miR-629 were detected in AIS patients. After rehabilitation, both circ_0020850 and miR-629 expression were maintained normal. Circ_0020850 and miR-629 were correlated with MMSE scores and could predict the prognosis of AIS patients. Further analysis indicated that the targets of miR-629 were enriched in the Wnt signaling pathway, ficolin-1-rich granule, and pathways of neurodegeneration or multiple diseases. Circ_0020850 and miR-629 were related to patients' recovery, they are promising prognostic markers of AIS patients.

Hypertension is a major public health concern, affecting more than one billion adults worldwide. The etiology of hypertension is associated with various genetic and epigenetic interactions. The candidate genes from various signaling pathways, such as RAAS, KKS and endothelin system, play a significant role in the progression of hypertension. The research aimed to develop a comprehensive knowledge base pertaining to hypertension, which would facilitate the integration of information related to SNPs associated with hypertension, pertinent biological pathways, risk assessment factors, molecular mechanisms, pharmacogenomic aspects of hypertension, a blood pressure calculator, and the existing literature on hypertension. This database has been implemented using HTML and Java programming languages. The deployment of the HTSNPedia database is expected to enhance the efficiency of identifying novel pharmacological drug candidates for the treatment of hypertension. A comprehensive understanding of the interrelationships among signaling pathways, molecular mechanisms, and risk-associated SNPs related to hypertension may significantly contribute to advancements in human health, particularly for individuals affected by this condition. The HTSNPedia is an openly accessible database, available at the following URL: https://www.generisk.in/HTSNPedia/main.html.

Long non-coding RNAs (lncRNAs) have become an essential factor in gastric cancer (GC) initiation and metastasis. This study is aimed to uncover the functional significance of EBLN3P in GC. In GC, EBLN3P and HMGCS1 was significantly increased. In contrast, miR-141-3p was decreased. Localization assay revealed that EBLN3P primarily localized in the cytoplasm rather than the nucleus. In MKN28 and SGC7901 cells, EBLN3P knockdown suppressed cell proliferation, metastasis and stemness. On the contrary, overexpression of EBLN3P facilitated these cellular processes. The EBLN3P/miR-141-3p/HMGCS1 axis was identified to play crucial functions in GC progression.

Glioblastoma multiforme (GBM) is an aggressive brain tumor characterized by metabolic plasticity and resistance to therapy. Understanding the mechanisms underlying GBM's adaptability to metabolic stress is crucial for developing effective treatments. This study investigates the role of Brain Protein I3 (BRI3) in regulating lipid metabolism and autophagy in GBM, and its potential as a therapeutic target. We performed integrative bioinformatics analysis using TCGA-GBM and CGGA datasets to identify lipophagy-related gene signatures. BRI3's function was examined through in vitro studies using GBM cell lines and patient-derived samples. Lipid metabolism and autophagy were assessed under normal and oxygen-glucose deprivation (OGD) conditions in BRI3-knockdown and control GBM cells. Bioinformatics analysis revealed a lipophagy-related gene signature associated with poor prognosis in GBM. BRI3 emerged as a key upregulated gene in GBM, correlating with altered lipid homeostasis and enhanced autophagy. In vitro studies demonstrated that BRI3 knockdown led to lipid accumulation, impaired autophagy, reduced proliferation, and increased apoptosis in GBM cells. Under OGD conditions mimicking the tumor microenvironment, BRI3-depleted cells showed compromised lipid mobilization, autophagy induction, and cell survival compared to controls. Our findings suggest BRI3 as a critical regulator of lipophagy in GBM, enhancing tumor cell resilience to metabolic stress. This study provides insights into GBM's metabolic adaptability and identifies BRI3 as a potential therapeutic target for modulating tumor cell survival in the challenging glioblastoma microenvironment.

Genome editing technologies have revolutionized molecular biology, enabling precise manipulation of gene functions across diverse organisms. In this study, we introduce a novel liposome-mediated delivery system for CRISPR-Cas9 components targeting the Juvenile Hormone Acid Methyltransferase (JHAMT) gene in honey bees (Apis mellifera anatoliaca). This approach leverages drone sperm cells as vectors for CRISPR-Cas9 transfection, overcoming the technical challenges of embryo microinjection in honey bees, such as low survival rates and labor-intensive procedures. The study involved artificial insemination of queen bees with transfected sperm and subsequent evaluation of gene-editing efficiency across generations.Our findings demonstrate the successful generation of both heterozygous and homozygous mutants, with gene-editing efficiencies reaching approximately 43%. This innovative method highlights the potential of liposome-mediated delivery systems for non-invasive, efficient, and scalable genome editing in eusocial insects. The results pave the way for broader applications in honey bee genetic research, offering a viable alternative to traditional methods. Furthermore, this study underscores the importance of genetic tools in advancing apiculture and addressing ecological challenges linked to pollinator health.

Identifying and classifying different cattle populations as per their breed and utility holds immense practical importance in effective breeding management. For accurate identification and classification of cattle breeds, a reference panel of 10 breeds, 657 identified ancestry informative markers and different machine learning classifiers were employed. To boost the accuracy of breed identification, three distinct machine learning classification models: logistic regression, XGBoost, and random forest, each one having an accuracy of > 95%, were ensembled achieving an accuracy of > 98% with just 207 markers [breed informative markers (BIMs)]. Further, for classification of dairy and draft purpose cattle, the breed informative markers along with those in selection signatures specific to dairy and draft utility were explored, and 17 utility informative markers (UIMs) including 12 BIMs and 5 markers in selection signatures were identified based on an ensemble approach. The accuracy of classification of cattle based on the utility (dairy or draft) was > 96%. To demonstrate the application of UIMs, these markers were used to identify the utility of non-descript cattle of Maharashtra, India and found that many of these cattle were draft purpose and were aligning with their production performance. This information can further be used for taking breeding decisions for their grading up to dairy or draft cattle. Here, a novel pipeline which utilized [R-] reference panel, [A-] ancestry informative markers, [S-] selection signatures and the power of [EL-] ensemble machine learning for identifying and classifying the cattle, breed- and utility-wise, was developed, and we called it as RASEL (available at: https://github.com/kkokay07/RASEL ).

Pancreatic cancer is a highly aggressive malignancy with a poor prognosis, mainly due to late diagnosis and early metastatic spread. The underlying mechanisms of pancreatic cancer metastasis, particularly the role of hepatic stellate cell (HSC) activation, are not fully understood. This study tried to find potential biomarkers for pancreatic cancer progression and prognosis by analyzing extracellular vesicle (EV)-associated miRNA profiles in plasma from pancreatic cancer patients and non-cancer controls. Functional assays, including transfection, western blotting, immunofluorescence, and enzyme-linked immunosorbent assay (ELISA), were used to assess the ability of the identified miRNA to activate HSCs and promote cancer progression. Our findings revealed that miR-25-3p was significantly upregulated in EVs derived from pancreatic cancer patients, correlating with increased metastasis and worse survival outcomes. EV-associated miR-25-3p from metastatic pancreatic cancer cells activated HSCs by regulating the expression of Krüppel-like factor 4 (KLF4). Additionally, activated HSCs secreted vascular endothelial growth factor (VEGF), further driving pancreatic cancer metastasis and progression. These results suggest that miR-25-3p could serve as a novel biomarker for pancreatic cancer progression and a potential therapeutic target to improve patient outcomes.

Deciphering cis-regulatory regions in genomes is essential for understanding various physiological processes and pathological mechanisms. Regulatory signatures, namely promoter motifs, transcription factor binding sites, enhancers, GC content, CpG islands, DNA structural motifs, and other cis-regulatory features, are well-established for their roles in transcriptional regulation. However, these features often exhibit species-specific variations, challenging the identification of conserved regulatory principles across different genomes. In this study, we introduce DNA sequence perplexity as an innovative and efficient information-theoretic metric for characterizing cis-regulatory regions. Derived from information theory and natural language processing, perplexity quantifies the complexity and predictability of sequence, offering a motif-independent framework for DNA analysis. By examining transcription and translation start site regions across 1180 species spanning diverse taxa, we demonstrate that cis-regulatory regions consistently exhibit lower perplexity compared to adjacent flanking regions. This trend persists irrespective of taxonomic classification, establishing perplexity as an evolutionarily conserved pattern of regulatory DNA. Additionally, we observe an inverse correlation between perplexity and promoter strength in yeast datasets, suggesting that higher transcriptional outputs are associated with markedly reduced sequence perplexity. Our findings reveal that perplexity may hold valuable insights into the generalizable aspects of cis-regulatory DNA architecture. Integrating this abstraction-based strategy with motif-based approaches and high-throughput functional datasets could enhance its applicability in predictive applications across comparative and functional genomics.