Advanced genetics (Hoboken, N.J.)最新文献

First detected in poultry in China in 1996, the H5N1 avian influenza virus has evolved into a significant global public health hazard, primarily owing to its high pathogenicity and potential for interspecies transmission. While primarily affecting avian species, H5N1 has repeatedly breached species barriers, infecting mammals including humans, minks, seals, and cattle. This review synthesizes current knowledge on the molecular mechanisms underpinning H5N1's host adaptation, focusing on key mutations in viral proteins-such as hemagglutinin (HA), neuraminidase (NA), and polymerase subunits (PB2)-which boost binding affinity to human-type receptors, increase replicative efficiency in mammalian cells, and facilitate immune evasion. Critical mutations, including HA-Q226L, HA-T199I, PB2-E627K, and NA-H274Y, are discussed in detail, highlighting their roles in altering receptor specificity, promoting antiviral resistance, and expanding viral tropism. The paper also outlines epidemiological trends, global dissemination patterns driven by migratory birds and trade, and current strategies for prevention and control, including antiviral therapeutics and vaccine development. Ultimately, this comprehensive analysis underscores the urgent need for continued surveillance, broad-spectrum countermeasures, and international collaboration to reduce the pandemic risk posed by H5N1.

The Dual Landscape of the Respiratory Virome The bronchial tree is the lung's forest, hosting a complex microbial world. This cover art captures the delicate balance of the respiratory virome. On one side, lush foliage signifies a diverse, healthy ecosystem in homeostasis. On the other, withered branches reveal the impact of viral proliferation and dysbiosis. In article 202500022, Yao et al. comprehensively review the respiratory virome, covering its healthy composition, host-microbiota interactions, and disease-associated alterations, while addressing methodological challenges and future clinical applications.

The DNA Damage Repair (DDR) signaling pathway serves as a crucial molecular hub that regulates chemotherapy efficacy, offering significant translational value in the field of precision oncology. This review systematically analyzes the molecular mechanisms of five core DDR pathways (Homologous Recombination Repair, Non-Homologous End Joining, Base Excision Repair, Nucleotide Excision Repair, and Mismatch Repair) in mediating chemotherapy resistance in tumors, and thoroughly elucidates the correlation between key molecular events-such as BRCA1/2 deficiency, MMR functional abnormalities, and Ataxia Telangiectasia Mutated/Ataxia Telangiectasia and Rad3-related (ATM/ATR) signaling pathway dysregulation-and chemotherapy sensitivity. The DDR deficiency biomarker system established through the integration of multi-omics data provides molecular classification tools for predicting the efficacy of platinum-based drugs. This study focuses on the mechanism by which Poly ADP-Ribose Polymerase inhibitors reverse Homologous Recombination-Deficient tumor resistance through "synthetic lethality" effects while also revealing the synergistic anti-tumor effects of ATM/ATR inhibitors in combination with chemotherapeutic agents. The research presents an innovative molecular synergy model between DDR regulation and Immune Checkpoint Blockade, confirming that tumor neoantigen release induced by DDR deficiency can enhance immunotherapy responses. This article also provides perspectives on multidimensional intervention strategies based on the DDR network, including the development of inhibitors targeting novel DDR targets, the establishment of DDR pathway functional assessment systems based on multidimensional biomarkers, and the investigation of synergistic paradigms between DDR and novel therapeutic modalities. Additionally, we explore the dynamic evolution mechanisms of DDR-mediated chemotherapy resistance by analyzing the interactions between DDR and metabolic reprogramming, as well as other related processes. These breakthrough advances provide theoretical foundations and innovative directions for overcoming chemotherapy resistance and advancing personalized treatment, marking a new era in cancer therapy characterized by precision targeting of DDR pathways.

AI-enabled facial genetics research has transformative potential for biomedical and forensic applications, but raises serious ethical, legal, and social challenges. Candor and clarity promote the advancement of science and facilitate the development of evidence-informed and ethically sound policy guardrails for scientific applications. Expanding upon our recent Comment on Difface, here we examine some of the ethical dimensions of AI-enabled facial genetics research, illuminate a lack of practical guidance for AI-enabled facial genetics research, and contextualize potential impacts within the current legal and policy landscape. Given the lack of standards and benchmarks for DNA-based face generation, we use Difface as a case study to stress the need for transparent performance metrics and clear disclosure of data flows across AI training, validation, and testing pipelines-enabling non-experts to assess accuracy meaningfully. Finally, we offer practical guidance for scientists to promote trustworthiness and stimulate further discussion within professional societies-guidance urgently needed in sociopolitically-turbulent and deregulatory environments. Risks of misinformation, disinformation, and discriminatory application of facial genetics research are too serious to ignore.

Prediabetes is one of the main health concerns in public health, and various etiological factors contribute to its onset. This study aimed to evaluate genetic associations and gene-macronutrient interaction with prediabetes-related metabolites to understand how genetic variation and dietary intake contribute to dysglycemia. We analyzed a total of 482 self-identified Mexican American participants recruited from Starr County, Texas in 2018-2019. Untargeted metabolomic profiling was performed using LC-MS. Nutrient densities of six macronutrients were derived from a 106-item food frequency questionnaire. Genetic associations for each metabolite were tested using Generalized linear Mixed Model Association Tests (GMMAT). Gene-macronutrient interactions on prediabetes-associated metabolites were assessed with the Mixed Model Association Test for GEne-Environment Interaction (MAGEE). Age, gender, and BMI were included as covariates in all association tests. Among 308 named and 2,471 unnamed metabolites, 17 novel variant-metabolite pairs were discovered, including rs10947898 in LRFN2 associated with diacylglycerol DG32:1(p-value: 8.95E-09). Among 145 named and 687 unnamed metabolites after filtering, gene-macronutrient interaction analyses identified seven named metabolites, including a variant(rs111251222) in MXD3 that interacted with monounsaturated fat to influence eicosadienoic acid levels (Interaction p-value: 9.88E-09). Prediabetes and nutrient-related metabolites in Mexican Americans showed significant genetic associations and gene-nutrient interactions.

Cultural heritage sites are commonly exposed to outdoor environments, resulting in severe damage to heritage objects from biotic and abiotic processes. Control of outdoor environments is impossible for heritage conservation, and we cannot prevent the abiotic processes. However, a variety of mitigation management can be developed for biotic damage, such as microbial colonization and biodeterioration. Over the past few decades, both conventional cultivation-dependent and modern cultivation-independent techniques have been employed to elucidate the microbiomes associated with the biodeterioration of cultural heritage. However, many studies are limited to segmentary analyses or simply stop at examining the community composition of the microbiomes, lacking solid evidence of microbial metabolism and biochemical reactions between microorganisms and heritage materials to support the core microbiomes associated with the biodeterioration. Here, we recommend thoroughly exploring the benefits of more advanced multi-omics techniques for analyzing cultural heritage microbiomes. We propose establishing a professional open-access database to standardize analytical procedures, integrating both culture-dependent and culture-independent approaches, and bio-archive valuable information on the core microbiomes, including their biodeterioration mechanisms, timelines, causes, and environmental conditions. This bio-archive of cultural heritage microbiomes will empower conservators and researchers worldwide to develop evidence-based, sustainable approaches for cultural heritage conservation under environmental change.

Multisystem inflammatory syndrome in children (MIS-C) is a pediatric complication of SARS-CoV-2 infection characterized by multiorgan inflammation and frequently by cardiovascular dysfunction. In a single-center prospective cohort study, optical genome mapping (OGM) was performed on 14 patients, including 11 meeting CDC criteria for MIS-C and 3 with MIS-C-like (MIS-CL) presentations. SVs and CNVs were filtered against population and internal OGM control databases. Seven patients (50%) harbored prioritized variants within or near genes implicated in immune regulation or SARS-CoV-2 response. These included intronic insertions or deletions in ORAI1, STAT4, and ITPR1 (n = 4 patients); a heterozygous insertion disrupting BATF; a large deletion spanning exons 2-10 of CFHR5; and an upstream insertion near DOCK2. Application of OGM to patients with MIS-C and MIS-CL revealed SVs potentially impacting inflammation, COVID-19 severity, and Kawasaki Disease susceptibility. Although causality cannot yet be assigned, the identification of rare structural variants highlights biologically plausible mechanisms that may contribute to disease heterogeneity. These findings establish the feasibility and value of OGM in the assessment of complex pediatric syndromes, such as children with MIS-C or a severe course of SARS-CoV-2 infection.

The human respiratory virome is an underexplored component of the microbiome that includes diverse DNA and RNA viruses such as eukaryotic viruses, bacteriophages, and archaeal viruses. Recent advances in metagenomics have revealed the complexity and dynamic nature of the human respiratory virome, which interacts closely with the host and the bacterial microbiome to influence respiratory health and disease. In healthy individuals, the virome is characterized by low biomass and high temporal variability, with Anelloviruses predominant in the upper airways, whereas Streptococcus phages and herpesviruses are most commonly detected in the lower airways. Common respiratory viruses, such as respiratory syncytial virus, human rhinovirus, and influenza A virus, can persist after acute infection and modulate host immunity. The respiratory virome also plays a significant role in chronic respiratory diseases. Despite its importance, research on the respiratory virome is hampered by technical challenges, including low viral abundance and limited reference databases. This review summarizes current understanding of the composition and determinants of the respiratory virome in healthy individuals, describes its interactions with the host and respiratory microbiota, including the potential modulatory roles of bacteriophages, outlines virome alterations in respiratory diseases, examines methodological challenges, and highlights potential clinical applications and future research directions.

Heterosis, the universal phenomenon in which F₁ hybrids exhibit superior performance compared to their parental lines, is widely exploited in modern agriculture for improving crop yield, yet its genetic mechanisms remain incompletely understood. The contributions of parental genomic sequence variants to heterosis have been extensively investigated. Recent advances in transcriptomics, proteomics, and metabolomics offer new quantitative perspectives on the molecular basis of crop heterosis. This review summarizes current evidence on inheritance patterns: additive, partially dominant, dominant, and overdominant effects. We highlight that the contributions of these effects to heterosis vary by genotypes, traits, tissues, populations, developmental stages, omics datasets, growth environments, and species. The additive effect, which can be utilized to predict heterosis for F₁ hybrids and accelerate the breeding of hybrid crops, has been identified as a predominant inheritance pattern in complete diallel crosses. We propose that integrating multi-omics data and quantitative analysis of inheritance patterns can deepen our understanding of its genetic mechanisms and accelerate the breeding of elite hybrid varieties. This approach provides a framework for predicting breeding and the rational design of high-yield crops.