Molecular Genetics and Genomics最新文献

In familial cancer the genetic etiology can play a significant role in the cancer onset. This study aims to explore the genetic predisposition to familial cancer by analysing germline variants in Indian family across generations through whole exome sequencing (WES). Given the limited genetic data from Indian populations and the under representation in the global data, this research seeks to identify genetic variants from India that may contribute to cancer risk. The detection of such constitutional genetic variants in both symptomatic and asymptomatic individuals, can facilitate risk assessment and personalized management strategies for future generations. We report findings from whole exome sequencing for the proband with right breast fibroadenoma and a strong family history of breast cancer, colon cancer and uterine cancer in her mother and maternal grandmother, niece, and paternal grandmother respectively. Sanger sequencing was implemented in the proband and her asymptomatic father to validate the presence of any inherited genetic variants, previously reported in other ethnic groups however being reported for the first time in Indian Population. We report two germline variants ATR c.2320dup and RNASEL c.1029G > A. The variant effect predictor analysis in the proband revealed two pathogenic variants rs1800566 and rs1799983of the NQO3 c.559 C > T (p. Pro187Ser) and NOS3c.894T > G (p. Asp298Glu) genes. The main findings were evaluated for pathogenicity using various mutation score prediction tools, followed by an in-silico analysis of protein structural and functional changes, which revealed alterations in protein domains impacting DNA damage repair and antiviral pathways. Identifying the novel germline variants in the ATR and RNASEL genes within an Indian familial cancer case, underscores the critical role of comprehensive genetic screening in early detection and risk management of hereditary cancers. Our findings emphasize the importance of integrating genomic analyses for personalized medicine approaches, to better assess familial cancer risk and guide early intervention strategies. Our findings will pave the way for functional validation of these variants through in vitro and in vivo studies evaluating RNA and protein expression. We demonstrate importance of expanding genetic studies to diverse populations, which could enhance risk stratification and inform targeted therapeutic developments.

We sequenced the mitochondrial genome of the freshwater flatfish Hypoclinemus mentalis, analyzed its structural characteristics, and constructed a phylogenetic tree for the order Pleuronectiformes based on sequence data of 13 protein-coding genes (PCGs) to elucidate the mitochondrial genome characteristics of H. mentalis and its phylogenetic position in Pleuronectiformes. The mitochondrial genome of H. mentalis is 16,802 bp in length and encodes 13 PCGs, two rRNA genes, 22 tRNA genes, and one non-coding region. Its base composition shows AT preference (A + T content 56.4%). The PCG nad6 and eight tRNA genes (trnQ, trnA, trnN, trnC, trnY, trnS2, trnE, and trnP) are located on the light strand, whereas the remaining 28 genes are located on the heavy strand. Among the 22 tRNAs, the secondary structure of trnS1 lacks the dihydrouridine arm, whereas the remaining tRNAs form a typical clover secondary structure. In the phylogenetic tree, H. mentalis clustered well with three other species of the family Achiridae. In the order Pleuronectiformes, monophyletic issues existed in three families (Cynoglossidae, Soleidae, and Pleuronectidae) and five genera (Ancylopsetta, Arnoglossus, Citharichthys, Cynoglossus, and Etropus). Our findings elucidate the structural characteristics of the complete mitochondrial genome of H. mentalis and its phylogenetic position and provide key molecular evidence for understanding the taxonomic relationships of this species within Pleuronectiformes.

The exponential growth of genomic data from next-generation sequencing technologies has created an urgent need for advanced computational approaches that can efficiently process, integrate, and interpret complex multi-dimensional biological information. This comprehensive review examines how artificial intelligence (AI), particularly machine learning and deep learning, is transforming genomic data analysis and addressing critical limitations of traditional bioinformatics methods. A thorough literature search was conducted across PubMed, Scopus, and Google Scholar databases, targeting peer-reviewed studies published between 2010 and 2024. This review addresses a critical knowledge gap by synthesizing current AI applications across the genomic analysis pipeline, from variant calling to multi-omics integration and personalized medicine, whilst critically evaluating emerging technologies including explainable AI and federated learning. AI methods have significantly improved accuracy in variant calling, gene expression profiling, and disease risk prediction. Key findings demonstrate that deep learning models achieve superior performance in complex pattern recognition, whilst explainable AI addresses the "black box" problem essential for clinical adoption. Federated learning enables privacy-preserving collaborative research across institutions. However, significant challenges remain, including data standardization, computational costs, algorithm interpretability, and ethical considerations surrounding privacy and algorithmic bias. Future directions include quantum computing integration and AI-enhanced CRISPR technologies. This review concludes that whilst AI represents a transformative force in genomic research, successful clinical translation requires addressing current technical and ethical challenges through interdisciplinary collaboration, robust validation frameworks, and responsible implementation strategies prioritizing patient safety and data security.

Diabetic cardiomyopathy (DCM) significantly contributes to cardiovascular complications in diabetes. This study investigated the protective effects of Resveratrol (RES) in combination with evidence-based nursing on DCM and the underlying molecular mechanisms. Eighty elderly patients with type 2 diabetes mellitus (T2DM) and DCM were randomly assigned to a control group or an RES group. The RES group received RES (800 mg/day) along with evidence-based nursing, while the control group received a placebo with nursing care for six months. Clinical indicators, including glucose and lipid metabolism, lactate dehydrogenase (LDH) activity, inflammatory markers, and cardiac function parameters, were evaluated. Additionally, T2DM rat models were used to examine oxidative stress, cells proliferation, fats accumulation, mitochondrial dysfunction, apoptosis and autophagy, while high glucose (HG)-induced H9C2 myocardial cells were used to investigate cellular mechanisms involving the SIRT1/PPAR-α/PGC-1 pathway. RES combined with evidence-based nursing improved glucose and lipid metabolism, reduced LDH activity, decreased inflammatory markers (TNF-α, IL-6), and enhanced cardiac function in T2DM patients with DCM. In rats, RES restored left ventricular ejection fraction (LVEF) and fractional shortening (LVFS) while reducing myocardial apoptosis with lower Bax and cleaved caspase-3 levels and higher Bcl-2 expression, reduced fibrosis and fat accumulation. Additionally, RES alleviated oxidative stress by decreasing reactive oxygen species (ROS) and malondialdehyde (MDA) levels, suppressed myocardial apoptosis, improved mitochondrial function while increasing ATP and superoxide dismutase (SOD) activity as well as enhancing autophagy. SIRT1 inhibitor (EX527) injections in rats reversed the beneficial effects of RES. In HG-treated H9C2 cells, RES improved cell viability, reduced apoptosis, alleviated oxidative stress and enhanced autophagy. RES ameliorates DCM through SIRT1/PPAR-α/PGC-1 signaling pathway in rats and improves efficacy of elderly DM patients in combination with evidence-based care.

Severe fever with thrombocytopenia syndrome (SFTS) is a tick-borne infectious disease caused by severe fever with thrombocytopenia syndrome virus (SFTSV) which results in a high mortality rate and poses a public health threat. Gene variation of SFTSV is one of the major forces driving its persistence and widespread prevalence. However, how genetic variations affect virus invasion is not yet fully understood. In this study, we evaluated the adaptive advantage of three stable high-frequency substitutions D170N, I323V, and K619R located on the envelope glycoprotein of SFTSV based on 1041 M segments of their genomes. The result demonstrated that single mutation of D170N, or K619R reduced infectivity of mutant. However, the combined presence of both D170N, and K619R mutation enhanced infectivity of mutants. Structure model and SPR assay studies indicated that the substitution at the 170 site reduced the binding affinity between Gn glycoprotein and host C-C motif chemokine receptor 2 (CCR2). Additionally, neutralization assay showed I323/K619R mutant exhibited completely resistance to neutralizing antibodies pressure. This study reveals that SFTSV balances its entry ability by gene variation of different loci on its glycoprotein via a trade-off between Gn and Gc. In addition, a weakened invasion strategy facilitated by site mutations benefits its immune evasion. The findings provide mechanistic insights into its prevalence, thereby enabling early warnings for potential future outbreaks.

Reduced seed shattering is a key yield-improving trait selected during the domestication of the Asian rice, Oryza sativa, from its wild ancestor, O. rufipogon. Three quantitative trait loci, qSH1, sh4, and qSH3, are reported to be involved in the reduced seed-shattering behaviour of cultivated rice. Genotyping surveys of these loci have shown that the sh4 mutation is conserved in all cultivars, whereas the qSH1 mutation is only observed in some japonica cultivars. Furthermore, the qSH3 mutation is observed in indica and japonica cultivars; however, aus cultivars carry a functional allele of wild rice at qSH3, indicating there may be distinct genetic mechanisms in aus for its reduced seed-shattering behaviour independently of qSH1 and qSH3. Through genetic analysis of the segregating populations between an aus cultivar, Kasalath, and wild rice introgression lines carrying the domesticated allele at sh4, we detected three loci associated with the reduced seed-shattering behaviour of Kasalath. Subsequent progeny tests validated their effects on this trait. These findings indicate that there are common and distinct genetic loci governing seed-shattering reduction in rice cultivars, providing novel insights into the complex process of rice domestication. This knowledge may help improve breeding strategies to optimise yield through targeted genetic selection.