Molecular Genetics and Genomics最新文献

There is ever increasing evidence for significant amounts of translation upstream of known AUG start codons in protein coding genes. Some of this translation is from upstream open reading frames (ORFs) that are unconnected to the main coding exons, but upstream initiation codons that are in-frame with coding exons can produce N-terminally extended protein isoforms. N-terminal extensions have much more proteomics support than the shorter proteins predicted to be produced from upstream ORFs. The upstream regions that produce N-terminal extensions have certain characteristics in common. They are highly GC-rich, most of the predicted start codons are non-AUG, and most do not conserve their reading frames beyond simians. The extended isoforms themselves are found significantly more frequently in dysregulated cells than in normal tissues. Approximately one in seven of these N-terminal extensions are upstream of signal peptides and would almost certainly block their recognition by the signal recognition particle. As a result, N-terminally extended isoforms containing exposed, hydrophobic signal peptides would be expected to accumulate in the cytoplasm. However, this analysis finds that those N-terminal extensions that would block signal recognition are practically not detected at the protein level even though the transcripts that would produce these extensions are found as expected in ribosome profiling experiments. This is a clear indication that these mislocated proteins are degraded after translation. Theprobable degradation of these extended proteins strongly suggests that their translation is a side effect of inefficient translation initiation.

Microorganisms rapidly adapt to non-lethal stress through mutations, a process central to microbial evolution. In this study, we investigate the molecular mechanism of adaptive mutagenesis in the bacterial strain Escherichia coli K-12 harboring a frameshift lac mutation. A non-random mutational spectrum, featuring a prominent - 1 bp deletion hot-spot is an intriguing unsolved phenomenon seen in the revertants of starving cells of this strain. The very-short-patch mismatch repair, a stationary-phase specific DNA repair pathway, has been hypothesized to create this hot-spot. To test this, we independently inactivated two main players of this pathway: dcm involved in DNA cytosine methylation and vsr encoding a sequence-specific DNA repair endonuclease. Contrary to the prediction of our hypothesis, the stationary-phase mutational spectra of Δdcm and Δvsr strains were indistinguishable from that of the wild-type strain, i.e., the frequency of mutations at the hot-spot remained unchanged. Unexpectedly, both Δdcm and Δvsr strains showed a two-fold increase in stationary-phase reversion frequency with respect to the wild-type strain. This result differed from an earlier finding where simultaneous deletion of both genes had no effect. We conclude that the adaptive mutation hot-spot is not caused by very-short-patch mismatch repair. Instead, our data suggest that dcm and vsr independently influence adaptive mutagenesis rate, possibly through previously unrecognized 'moonlighting' functions. Future work will aim to uncover the mechanism behind this unique adaptive mutational spectrum, advancing our understanding of stress-induced mutagenesis.

Cardiovascular diseases are the leading causes of mortality globally, of which coronary artery disease (CAD) is the most frequent. Several epigenomics and transcriptomics studies of CAD have been conducted, however, only a few studies have utilized the statically powerful discordant twin pair design, which reduces the confounding introduced by genetics. Finally, no study has investigated the link between the DNA methylation position and gene expression levels. The present study aims at filling this knowledge gap, to present novel biomarkers of CAD. We investigated 44 Danish twin pairs that were discordant for incident CAD, for whom, both genome-wide DNA methylation (CpG) and gene expression (probe) data were available. We identified CpGs and probes, which were more different within the twin pairs than expected by change, and investigated these by Cox regression analysis. CpGs and probes belonging to the same gene were divided into groups based on their directions of effect, and these genes were investigated by gene set enrichment and interaction network analyses. Overall, we found that CAD co-twins showed DNA methylation patterns leading to up-regulated gene expression; especially with demethylation of promoters and methylation of gene bodies, compared to their non-CAD co-twin. Generally, we found that the largest biological group of up-regulated pathways related to immune-inflammation processes, whereas down-regulated pathways related to muscle system biology, among others. Hence, the present study uncovers a specific pattern between DNA methylation position and gene expression levels relating to CAD, pointing to a need for additional studies. However, such multi-omics designs are surprisingly rare.

Objective: Temozolomide (TMZ) resistance is a major cause of treatment failure in glioblastoma (GBM). This study investigates the role and mechanism of the RNA-binding protein RNA-binding motif protein 7 (RBM7) and F-box and leucine-rich repeat protein 16 (FBXL16) in TMZ resistance in GBM, focusing on mitochondrial dysfunction and ferroptosis. TMZ-resistant GBM cell lines (TR/U87) were established through gradient induction. Cell viability and proliferation were assessed using the Cell Counting Kit-8 assay and colony formation assays. Western blot analysis and immunohistochemistry were performed to measure FBXL16, activating transcription factor 4, and peroxisome proliferator-activated receptor gamma coactivator 1-alpha protein expression. Transwell assays evaluated TR/U87 cell migration and invasion. Co-immunoprecipitation and RNA immunoprecipitation assays verified the interaction between RBM7 and FBXL16. An actinomycin D assay analyzed FBXL16 mRNA stability. Flow cytometry was used to detect reactive oxygen species, iron levels, and apoptosis. A nude mouse xenograft model was used to validate in vivo effects. RBM7 was highly expressed in TMZ-resistant cells. Knockdown of RBM7 suppressed TR/U87 cell proliferation and migration, induced mitochondrial structural damage, and triggered ferroptosis. Mechanistically, RBM7 interacted with FBXL16 and reduced its mRNA stability. FBXL16 knockdown reversed RBM7 deficiency-induced ferroptosis and chemosensitivity. In vivo experiments confirmed that RBM7 knockdown combined with TMZ significantly inhibited tumor growth. RBM7 promotes TMZ resistance by suppressing mitochondrial dysfunction and ferroptosis through destabilization of FBXL16. Targeting the RBM7-FBXL16 axis may represent a novel strategy to overcome GBM chemoresistance.

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.

Harvest index (HI), a key yield-related trait in wheat, is influenced by genetic, phenological, environmental, and stress factors. In the Indo-Gangetic Plains (IGP) of India, spot blotch (SB) poses a major biotic stress, reducing grain yield by affecting photosynthesis and HI. Identifying stable wheat genotypes and genomic regions controlling these traits are essential for developing resilient wheat for the IGP. We evaluated 1500 elite wheat lines in four environments at IGP, including SB and disease-free (DF) conditions. On average, in the SB condition HI (%) reduced by 4.3% compared to its DF environment. Genome-wide association studies identified important SNPs:1A_494392059, 1A_495192503, 2A_32931719, 3B_10249157, 3B_10644041, 3B_6127880, 5B_538548049, 6A_96651968, 7A_49592941 and 7D_326728664, and a favourable haplotype TTGTCG (n = 303), which showed higher average HI (39.75%) under SB conditions. Additionally, most of candidate genes associated with the identified SNPs were involved in senescence and disease resistance. Stability analysis using AMMI and genotype selection index identified a set of genotypes with consistently high and stable HI under both SB and DF conditions. Further, genotypes with favourable alleles at all these identified significant MTAs, and stable genotypes identified for HI shared common genetic contributors, including the SR50 gene and prominent wheat varieties such as KACHU, PASTOR, and PRL. These genetic backgrounds play a pivotal role in conferring both disease resistance and yield stability, highlighting their importance in wheat breeding programs for IGP. Further, Genomic predictions using genome-wide markers demonstrated moderate predictive accuracy, ranging from 0.22 to 0.39, with higher accuracy observed under SB conditions. The stable genotypes and genomic regions identified in this study could serve as important resources and knowledge for developing resilient genotypes adapted to the IGP.

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.