Genes最新文献

Background/Objectives: The majority of chromosome 22q11.2 deletions are de novo, resulting from meiotic non-allelic homologous recombination (NAHR). While 22q11.2 deletion syndrome (22q11.2DS)-associated phenotypes are well characterized, risk factors leading to NAHR are poorly understood, including the possible relationship with assisted reproductive technology (ART). Here we examined the prevalence of ART conceptions and medical comorbidities in patients with 22q11.2DS vs. spontaneously conceived (SC) patients with 22q11.2DS. Methods: Retrospective analysis, under IRB approval, of medical records on 1184 patients with laboratory-confirmed de novo chromosome 22q11.2 deletions was performed. ART conceptions included IVF with and without ICSI. Deletion size and obstetric, family, and medical histories were examined. Results: We identified 30 pregnancies conceived using ART (2.57%) compared with the U.S. general population rate of 2.3% (p-value = 0.6603). ART and SC sub-cohorts demonstrated no significant differences in deletion size or perinatal outcomes, including preterm birth, multiples, polyhydramnios, or congenital heart disease. Controlling for these factors, neonates conceived via ART were more likely to be admitted to the ICU (aOR = 6.3). Conclusions: Pregnancies conceived via ART, and later found to have 22q11.2DS, demonstrated no significant differences in prevalence or perinatal outcomes compared with the U.S. general population. Moreover, NAHR is unrelated to ART in this population. Likewise, associated phenotypic features are unrelated. These data will be reassuring to those families where ART was employed to conceive children who were later found to have 22q11.2DS.

Background: Due to variability in patterns of consumption as well as well-known difficulties in obtaining valid self-report from heavy drinkers, quantifying the effects of heavy alcohol consumption on mortality is challenging. Using a DNA methylation biomarker of chronic heavy alcohol consumption (HAC) named the alcohol T-score (ATS), we previously showed that chronic HAC was a strong predictor of mortality. However, whether there is a similar effect when measures of shorter-term heavy alcohol use, i.e., recent "binge" drinking, were used to predict mortality was not examined. This is a critical issue because most biomarkers of HAC assess only short-term HAC.

Methods: Therefore, we examined the prediction of all-cause mortality from a DNA methylation biomarker of smoking (cg05575921), the ATS and a short-term biomarker of recent heavy alcohol use (cg07375256) in 708 subjects from the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial using Cox Proportional Hazards Regression Modeling. Models were compared using Akaike's Information Criterion.

Results: The ATS was the best single predictor among three-variable models that included controls for sex and age. Of the possible four variable models, the model consisting of age, sex, cg05575921 methylation and ATS best predicted mortality. The addition of cg07375256 methylation did not improve model performance. In sensitivity analyses using only participants who provided alcohol SR (n = 639), the importance of the ATS and cg05575921 was replicated. We also found that ATS values were higher among those who declined to provide self-report alcohol use, indicating that missing self-report data about alcohol intake are not missing at random, and sometimes reflects elevated alcohol consumption. Finally, cg05575921 methylation was strongly associated with ATS values but only weakly with alcohol SR and not at all with cg07375256 methylation.

Conclusions: Accordingly, this study indicates a strong effect of chronic HAC, but not short-term HAC, on mortality, further highlights the limitations of self-reported alcohol use in the prediction of all-cause mortality and indicates the value of assessing HAC in addition to smoking.

Background: Variants in the GBA gene represent the most common genetic risk factor for Parkinson's disease and are associated with a more aggressive disease course. Deep brain stimulation is an established therapy for advanced Parkinson's disease, yet the influence of GBA status on postoperative outcomes remains incompletely defined. This review aims to summarize the clinical relevance of GBA genotyping prior to DBS and to evaluate its potential contribution to decision-making, risk stratification, and long-term management. Methods: A structured narrative review was conducted. The literature on sequencing methodology, variant interpretation, and postoperative outcomes in GBA-positive and GBA-negative patients was examined. Particular focus was placed on motor, cognitive, and neuropsychiatric outcomes, and on studies comparing trajectories across variant classes. Results: Across all study designs, patients with GBA-associated Parkinson's disease demonstrated robust motor improvement after DBS, with outcomes comparable to those in non-carriers. Cognitive and neuropsychiatric decline occurred more rapidly in GBA carriers. Recent evidence indicates that cognitive and neuropsychiatric decline is influenced more by the genetic profile than the stimulation procedure. Variant severity appears to influence postoperative trajectories. Long-read sequencing improves detection of recombinant alleles and may refine genotype-phenotype associations. Genotyping provides additional value in counseling, expectation management, and postoperative planning. Conclusions: DBS remains an effective motor therapy for patients with GBA-associated Parkinson's disease. Current findings indicate GBA genotyping should inform, and not limit, candidate selection. Integration of clinical, cognitive and genetic data supports more individualized management. Methodological advances in sequencing and the development of prediction models may further enhance personalized DBS planning.

Enteric infections remain a major health and economic challenge in swine production, with outcomes determined not only by pathogen virulence but also by the complex interplay between host genetics, immune competence, and the intestinal microbiota. This review synthesises current knowledge on host-pathogen genomic interactions in pigs, with a focus on resilience mechanisms against enteric diseases in swine. For this purpose, 103 articles were used as information sources, retrieved through structured keyword searches in PubMed. The review first addresses host genetic factors, highlighting genomic variants and quantitative trait loci associated with resistance or resilience to viral and bacterial pathogens such as porcine epidemic diarrhoea virus (PEDV) or Escherichia coli. Next, the key factors of the immune system to confer protection are also reviewed, emphasising the role of innate and adaptive responses in controlling each pathogen and disclosing the contribution of regulatory networks that balance pathogen clearance. Finally, the last section of the review is devoted to exploring current knowledge in the involvement of the microbiota in resilience against enteric pathogens, mostly, but not exclusively, enteric bacteria. In this sense, competitive exclusion is a concept which has gained attention in recent years. The review pinpoints and discusses the state of the art about how the microbial community provides colonisation resistance, shapes immune development, and influences pathogen fitness within the intestinal niche. As final perspectives, the review explores future drivers in the genetic immune and microbiota resistance. By bridging host genomic data with functional insights into immunity and microbial ecology, this review underscores the potential of multi-omics approaches to enhance resilience against enteric infections in pigs and advance sustainable swine health management.

Background: YABBY transcription factors play important roles in plant growth and development. Although this gene family has been characterized in many plant species, a comprehensive analysis in cotton remains unavailable. Methods: In this study, we investigated the YABBY gene family in cotton by integrating multiple bioinformatics methods. Results: YABBY genes were identified in the genomes of four cotton species (Gossypium hirsutum, Gossypium barbadense, Gossypium arboretum and Gossypium raimondii) and these identified genes were further classified into six groups. Following this classification, the expansion of the cotton YABBY gene family was examined, and we found that the family exhibits diverse expansion patterns during evolution, with segmental duplication acting as the primary driving force. In contrast, the notably larger repertoire of YABBY genes in G. raimondii is likely attributable to transposon activity. Regarding their evolutionary trajectory, Ka/Ks analysis showed that the YABBY gene family has undergone purifying selection. Beyond evolution, expression and cis-element analyses further demonstrated that YABBY genes possess diverse functions. In addition, we identified YABBY genes involved in different developmental stages of cotton fibers. Conclusions: We clarify the function and evolution of the cotton YABBY gene family in this work, and these results will provide a critical resource for further research on YABBY genes.

Background/Objectives: Lentiviral vectors (LVs) are most commonly pseudotyped with the vesicular stomatitis virus glycoprotein (VSV-G), which lends LVs a wide tropism as it uses the low-density lipoprotein receptor (LDLR) as the main receptor for cell entry. In some gene therapy and research applications, however, alternative pseudotypes can be useful. In this work, we characterized LVs pseudotyped with lymphocytic choriomeningitis virus (LCMV) glycoprotein, particularly in gene transfer to an LDLR-deficient mouse strain used to model cardiovascular disease, Ldlr^-/-ApoB^100/100. Methods: LCMV-LVs were used in vitro to test their transduction efficiency across a variety of cell types. In vivo, the gene transfer efficiency, LV-specific immune responses and biodistribution of VSV-G-LVs and LCMV-LVs were compared after systemic gene transfer. Results: In vitro, LCMV-LVs transduced all tested cell types at high efficiency without the use of transduction enhancers. In vivo, VSV-G-LVs showed a higher gene transfer efficiency at the same LV dose, but increasing the LCMV-LV dose enhanced the measured vector copy numbers. With both pseudotypes, most of the vector accrued in the liver, but with LCMV-LVs, a larger portion of the measured vector copies were found in the lungs. VSV-G-LVs also generated a higher titer of LV-specific IgG antibodies. The gene transfer efficiency of LCMV-LVs was affected by the mouse diet, with a high-fat diet decreasing the transduction. Conclusions: LCMV-LVs can be used as a substitute for VSV-G-LVs if an alternative pseudotype is required; however, they may require the use of a higher LV dose.

Background/objectives: FLOURY ENDOSPERM 2 (FLO2) is known to affect rice endosperm development and starch quality, yet its role in determining flour physicochemical behavior and endosperm structural integrity has not been quantitatively defined. This study aimed to elucidate how loss of FLO2 function alters starch organization and functional properties of rice flour.

Methods: Two independent homozygous, T-DNA-free OsFLO2 knockout lines were generated in the japonica cultivar Dongjin using CRISPR/Cas9. Grain appearance was evaluated in mature seeds. Flour physicochemical properties were analyzed by Rapid Visco Analyzer (RVA) and differential scanning calorimetry (DSC). Amylopectin chain-length distribution was determined by isoamylase debranching followed by HPAEC-PAD, and endosperm microstructure was examined by scanning electron microscopy.

Results: OsFLO2 mutants exhibited floury, opaque endosperms, with chalkiness increasing from 4.8% in the WT to 27-29%. RVA analysis showed a marked reduction in peak viscosity (1193 cP to 263-293 cP) and a decrease in pasting temperature (77.2 °C to 68.9-70.5 °C). DSC indicated a tendency toward reduced gelatinization enthalpy in the mutants. These changes were associated with a reduced proportion of short amylopectin chains (DP 6-12), decreased long chains (DP ≥ 37), and a relative increase in intermediate-long chains (DP 25-36), along with disrupted granule packing and a 1.33-1.36-fold increase in endosperm porosity.

Conclusions: These results demonstrate that FLO2 plays an important role in maintaining the structural integrity of rice endosperm by harmonizing the microstructure of amylopectin with the thermal and gelatinization properties of starch.

Background/objectives: Speech and language delay (SLD) is one of the most prevalent developmental conditions in childhood, with post-pandemic data indicating a notable increase in identified cases. Within this group, expressive language disorder (ELD) frequently appears alongside neurodevelopmental disorders such as autism spectrum disorder (ASD), epilepsy, and intellectual disability. Although awareness of ELD has grown, the role of genetic testing in its evaluation remains unclear, as such testing is not routinely pursued for isolated expressive language concerns. This gap highlights the need to better define the diagnostic value of genetic analysis and to examine the interval between an ELD diagnosis and the return of genetic testing results.

Methods: This study investigated genetic contributions to ELD using the National Brain Gene Registry (BGR), a multisite database of rare neurodevelopmental disorders. Participants with ICD-10 code F80.1 were identified through electronic health records; demographic data, comorbidities, genetic variants, inheritance patterns, age at diagnosis, and timing of interventions were analyzed.

Results: Of 687 BGR participants, 32 (4.7%) had documented ELD. The cohort, aged 3-19 years, presented with common comorbidities like developmental delays, ASD, epilepsy, and hypotonia. Across 42 genes, 49 unique variants were identified: 26 pathogenic or likely pathogenic, 22 variants of uncertain significance, and one benign variant. Seventeen variants were de novo, and 10 participants carried multiple variants. Most children (80%) received an expressive language diagnosis prior to genetic testing, with reports returned an average of 1.5 years following the diagnosis.

Conclusions: Overall, children with ELD commonly carry genetic variants and neurodevelopmental comorbidities, yet genetic testing is typically pursued well after diagnosis and does not currently alter early management. These findings underscore the need for clearer, evidence-based guidelines to define when genetic testing adds diagnostic or prognostic value in the evaluation of ELD.

Expanded carrier screening (ECS) has emerged as a cornerstone of reproductive genetics, enabling the identification of couples at risk of transmitting autosomal recessive and X-linked disorders. Advances in next-generation sequencing and the increasing adoption of exome- and genome-based strategies have greatly expanded its clinical scope. However, despite existing national and international recommendations, substantial heterogeneity remains in gene panel composition, inclusion criteria, and interpretation frameworks. A key novelty of the current genomic era is the availability of large, publicly accessible human genome datasets encompassing broader ancestral diversity. These resources are transforming our understanding of variant frequencies and disease penetrance across populations, supporting the development of evidence-based and ancestry-informed gene panels. In parallel, recent studies investigating the genetic contribution of pathogenic variants to euploid pregnancy losses are opening new perspectives for ECS. Incorporating genes associated with lethal conditions in utero may enhance the predictive power of screening and deepen our understanding of reproductive outcomes, while also demanding careful consideration of clinical validity and counseling implications. This mini-review synthesizes current evidence on ECS, examines ongoing interpretive and implementation challenges, and discusses how population-scale genomic resources and emerging data on reproductive lethality are shaping the next generation of evidence-based carrier screening.

Background/Objectives: Forensic DNA phenotyping (FDP) enables the prediction of externally visible characteristics (EVCs) such as eye, hair, and skin color, ancestry, and age from biological traces. However, low template DNA (LT-DNA), often derived from degraded or trace samples, poses significant challenges due to allelic dropout, contamination, and incomplete profiles. This review evaluates recent advances in FDP from LT-DNA, focusing on the integration of machine learning (ML) models to improve predictive accuracy and operational readiness, while addressing ethical and population-related considerations. Methods: A comprehensive literature review was conducted on FDP and ML applications in forensic genomics. Key areas examined include SNP-based trait modeling, genotype imputation, epigenetic age estimation, and probabilistic inference. Comparative performance of ML algorithms (Random Forests, Support Vector Machines, Gradient Boosting, and deep learning) was assessed using datasets such as the 1000 Genomes Project, UK Biobank, and forensic casework samples. Ethical frameworks and validation standards were also analyzed. Results: ML approaches significantly enhance phenotype prediction from LT-DNA, achieving AUC > 0.9 for eye color and improving SNP recovery by up to 15% through imputation. Tools like HIrisPlex-S and VISAGE panels remain robust for eye and hair color, with moderate accuracy for skin tone and emerging capabilities for age and facial morphology. Limitations persist in admixed populations and traits with polygenic complexity. Interpretability and bias mitigation remain critical for forensic admissibility. Conclusions: L integration strengthens FDP from LT-DNA, offering valuable investigative leads in challenging scenarios. Future directions include multi-omics integration, portable sequencing platforms, inclusive reference datasets, and explainable AI to ensure accuracy, transparency, and ethical compliance in forensic applications.