Genes最新文献

Background/objectives: Modern sequencing technologies have transformed the identification of medicinal plant species and varieties, overcoming the limitations of traditional morphological and chemical approaches. This review explores the key DNA-based techniques, including molecular markers, DNA barcoding, and high-throughput sequencing, and their contributions to enhancing the accuracy and reliability of plant identification. Additionally, the integration of multi-omics approaches is examined to provide a comprehensive understanding of medicinal plant identity.

Methods: The literature search for this review was conducted across databases such as Google Scholar, Web of Science, and PubMed, using keywords related to plant taxonomy, genomics, and biotechnology. Inclusion criteria focused on peer-reviewed studies closely related to plant identification methods and techniques that contribute significantly to the field.

Results: The review highlights that while sequencing technologies offer substantial improvements, challenges such as high costs, technical expertise, and the lack of standardized protocols remain barriers to widespread adoption. Potential solutions, including AI-driven data analysis and portable sequencers, are discussed.

Conclusions: This review provides a comprehensive overview of molecular techniques, their transformative impact, and future perspectives for more accurate and efficient medicinal plant identification.

Background/objectives: The avascular nature of the follicle creates a hypoxic microenvironment, establishing a niche where granulosa cells (GCs) rely on glycolysis to produce energy in the form of lactate (L-lactate). Autophagy, an evolutionarily conserved stress-response process, involves the formation of autophagosomes to encapsulate intracellular components, delivering them to lysosomes for degradation. This process plays a critical role in maintaining optimal follicular development. However, whether hypoxia regulates autophagy in GCs via lactate remains unclear.

Methods: In this study, we investigated lactate-induced autophagy under hypoxia by utilizing glycolysis inhibitors or silencing related genes.

Results: We observed a significant increase in autophagy in ovarian GCs under hypoxic conditions, indicated by elevated LC3II levels and reduced P62 levels. Suppressing lactate production through glycolytic inhibitors (2-DG and oxamate) or silencing lactate dehydrogenase (LDHA/LDHB) effectively reduced hypoxia-induced autophagy. Further investigation revealed that the HIF1-α/BNIP3/Beclin-1 axis is essential for lactate-induced autophagy under hypoxic conditions. Inhibiting HIF-1α activity using siRNAs or PX-478 downregulated BNIP3 expression and subsequently suppressed autophagy. Similarly, BNIP3 silencing with siRNAs repressed lactate-induced autophagy in hypoxic conditions. Mechanistically, immunoprecipitation experiments showed that BNIP3 disrupted pre-existing Bcl-2/Beclin-1 complexes by competing with Bcl-2 to form Bcl-2/BNIP3 complexes. This interaction released Beclin-1, which subsequently triggered lactate-induced autophagy under hypoxic conditions.

Conclusions: These findings unveil a novel mechanism by which hypoxia regulates GC autophagy through lactate production, highlighting its potential role in sustaining follicular development under hypoxic conditions.

Background/objectives: The ectodysplasin A (EDA) gene, a member of the tumor necrosis factor ligand superfamily, is involved in the early epithelial-mesenchymal interaction that regulates ectoderm-derived appendage formation. Numerous studies have shown that mutations in the EDA gene can cause X-linked ectodermal dysplasia (ED) and non-syndromic oligodontia (NSO). Accordingly, this study aimed to identify the causative genetic mutations of the EDA gene.

Methods: We investigated EDA gene mutations in two X-linked oligodontia families using candidate gene sequencing and whole-exome sequencing, with a single proband identified and studied for each family. The first family included a patient with NSO, while the second family had a patient exhibiting variable expression of ED.

Results: Mutational analysis identified two missense mutations in the EDA gene (NM_001399.5): one novel mutation, c.787A>C p.(Lys263Gln), in family 2; and one previously reported mutation, c.457C>T p.(Arg153Cys), in family 1. All mutated residues are evolutionarily highly conserved amino acids. The p.(Arg153Cys) mutation would destroy the furin recognition site and affect the cleavage of EDA. The p.(Lys263Gln) mutation in a TNF homology domain would interfere with the binding of the EDA receptor. The p.(Lys263Gln) mutation was associated with NSO, while the other mutation demonstrated ED.

Conclusions: This study helps to better understand the nature of EDA-related ED and NSO and their pathogenesis, and it expands the mutational spectrum of EDA mutations.

Background: The gene family of myelomatosis (MYC), serving as a transcription factor in the jasmonate (JA) signaling pathway, displays a significant level of conservation across diverse animal and plant species. Cotton is the most widely used plant for fiber production. Nevertheless, there is a paucity of literature reporting on the members of MYCs and how they respond to biotic stresses in cotton.

Methods: Bioinformatics analysis was used to mine the MYC gene family in cotton based on InterPro, cottongen, etc. Results: The gene structure, conserved motifs, and upstream open reading frames of 32 GhMYCs in Gossypium hirsutum were identified. Moreover, it was anticipated that the GT1-motif is the most abundant in GhMYCs, indicating that the GT1-motif plays a significant role in light-responsive GhMYCs. The expression patterns of GhMYCs under biotic stresses including V. dahliae and Aphid gossypii were evaluated, suggesting that GhMYCs in class-1 and -3 GhMYCs, which function as negative regulators, are involved in resistance to verticillium wilt and aphids. The class-3 GhMYCs genes were found to be mostly expressed in female tissues. Interestingly, it was also determined that the homeologous expression bias within GhMYCs in cotton was uncovered, and results showed that the gene expression of class-1A and class-2 GhMYCs in the Dt sub-genome may have a direct impact on gene function.

Conclusions: This study provides a research direction for researchers and breeders to enhance cotton traits through manipulating individual or multiple homeologs, which laid a foundation for further study of the molecular characteristics and biological functions of GhMYC gene.

Background/objectives: Metabolic syndrome (MetS) is a complex condition linking obesity, diabetes, and hypertension, representing a major challenge in clinical care. Its rising global prevalence, driven by urbanization, sedentary lifestyles, and dietary changes, underscores the need for effective management. This study aims to explore the genetic mechanisms behind MetS, including adiposity, inflammation, neurotransmitters, and β-cell function, to develop a prognostic tool for MetS risk.

Methods: We genotyped 40 genetic variants across these pathways in 279 MetS patients and 397 healthy individuals. Using logistic regression, we evaluated the prognostic capability of a polygenic score model for MetS risk, both independently and with other factors like sex and age.

Results: Logistic regression analysis identified 18 genetic variants significantly associated with MetS. The optimal predictive model used polygenic scores calculated with weights assigned to the 18 loci (AUC 82.5%, 95% CI 79.4-85.6%), with age and sex providing a minimal, non-significant improvement (AUC 83.3%, 95% CI 80.2-86.3%). The addition of the polygenic score significantly improved net reclassification (NRI = 1.03%, p = 3.42 × 10^-50). Including all 40 variants did not enhance prediction (NRI = -0.11, p = 0.507).

Conclusions: Polygenic scores could aid in predicting MetS risk and health outcomes, emphasizing the need for diagnostic tools tailored to specific populations. Additional research is warranted to corroborate these conclusions and explore the molecular mechanisms of MetS.

In many human rights and criminal contexts, skeletal remains are often the only available samples, and they present a significant challenge for forensic DNA profiling due to DNA degradation. Ancient DNA methods, particularly capture hybridization enrichment, have been proposed for dealing with severely degraded bones, given their capacity to yield results in ancient remains.

Background/objectives: This paper aims to test the efficacy of genome-wide capture enrichment on degraded forensic human remains compared to autosomal STRs analysis.

Methods: Six highly degraded human bones from the Spanish Civil War (1936-1939) were quantified with Quantifiler^™ Trio and amplified with GlobalFiler^™. Independently, partially UDG-treated double-stranded DNA libraries were generated and shotgun sequenced to screen for endogenous human DNA content. Subsequently, libraries were enriched with the Twist Bioscience "Twist Ancient DNA" reagent enrichment kit, which had not been previously tested for forensic purposes.

Results: The results show that the samples behave similarly with both approaches (well-preserved samples yield good results). However, capture enrichment provides some new relevant insights, suggesting that its implementation in current NGS forensic platforms could be beneficial.

Conclusions: Shotgun results show that the analyzed samples exhibit the same characteristics as ancient DNA samples in terms of DNA fragmentation and molecular damage, which may enhance the value of this approach when authenticating the endogenous DNA of forensic samples.

Background/objectives: Frailty is a complex geriatric syndrome resulting in decreased physiological reserve. While genetics plays a role, the underlying mechanisms remain unsolved. Metallothioneins (MTs), metal-binding proteins with high affinity for zinc, an essential mineral for many physiological functions, are involved in processes including oxidative stress and inflammation. We investigated the impact of genetic variations in MTs on frailty.

Methods: 448 subjects (235 females and 213 males, median age of 76 years) were categorized into three frailty groups (non-frail/pre-frail/frail), by hierarchical cluster analysis based on cognitive status (MMSE), functional capacity (ADL), and physical strength (HGS). Subjects were analyzed for selected SNPs in MT1A, MT1B, MT2A, and MT3 genes by PCR-RFLP.

Results: An association was found between the rs8052394-A/G (Lys51Arg) polymorphism in the MT1A gene and frailty in females both in binary (OR = 0.345, p = 0.037) and multinomial logistic regression (OR = 0.343, p = 0.036) corrected for age and sex, with carriers of the minor G-allele less likely to transition from non-frail to pre-frail status. Additionally, a significant association with albumin levels (beta = 0.231; p = 0.027) and a trend of association with CRP levels (beta = -1.563; p = 0.097) were observed for this SNP in non-frail females, both indicative of a low inflammatory status. However, Bonferroni correction for multiple SNPs and physiological parameters tested renders these results statistically non-significant.

Conclusions: Although its associations do not survive Bonferroni correction, this exploratory study suggests a sex-specific influence of MT1A variability in frailty, likely affecting zinc availability, aligning with ongoing research on sex differences in frailty risk and progression. Larger studies are needed to validate these findings and clarify the mechanisms behind MTs' variability in frailty progression.

Background: Polyphenol oxidases (PPOs) form a multigene family that is widely distributed in plants, animals, and insects. To date, PPOs have been identified in plants such as Populus L. and Solanum tuberosum L., but studies on PPOs in soybean (Glycine max (L.) Merr.) and wild soybean (Glycine soja Sieb. and Zucc.) remain limited.

Methods: To clarify the nature, structure, evolution, expression pattern, and interaction network of PPOs in these plants, we performed bioinformatics analysis and evaluated the expression patterns of PPOs in soybean and wild soybean throughout the growth period and under salt stress.

Results: We identified 17 and 15 genes belonging to the PPO family. These genes were distributed across chromosomes 7 and 6 and could be divided into three groups. Most of these genes only contained one coding sequence (CDS), and their gene structure, conserved motifs, and 3D structures were very similar. Although there were a few intraspecies gene duplications, 75 gene replication pairs between soybean and wild soybean were detected. A Ka/Ks analysis showed that the PPOs in these plants were mainly subjected to purity selection. Moreover, the expression of the PPO genes varied greatly during different stages of the growth period and under salt stress, showing high temporal and spatial specificity. The protein interaction networks of these genes appeared to be quite distinct. Through the interaction analysis of the candidate gene GmPPO2 selected under salt stress, Glyma.07G059000, Glyma.10G279000, and Glyma.03G167900 were identified as the candidate genes regulating salt stress tolerance in soybean.

Conclusions: These findings provide a foundation for further research on the evolution of soybean and wild soybean, as well as the functions of the PPO gene family.

Plasma membrane intrinsic proteins (PIPs), as members of the aquaporin (AQPs) family, can transport not only water but also urea, CO₂, H₂O₂, metal ions, and trace elements. They are crucial for maintaining water balance, substance transport, and responding to various stresses. This article delves into the structure, function, response mechanism, molecular mechanism, and regulatory mechanism of PIPs as a result of biological and abiotic stresses. It also summarizes current research trends surrounding PIPs and highlights potential research directions for further exploration. The aim is to assist researchers in related fields in gaining a more comprehensive understanding and precise insight into the advancements in PIP research.

Background/objectives: A prominent endophenotype in Autism Spectrum Disorder (ASD) is the synaptic plasticity dysfunction, yet the molecular mechanism remains elusive. As a prototype, we investigate the postsynaptic signal transduction network in glutamatergic neurons and integrate single-cell nucleus transcriptomics data from the Prefrontal Cortex (PFC) to unveil the malfunction of translation control.

Methods: We devise an innovative and highly dependable pipeline to transform our acquired signal transduction network into an mRNA Signaling-Regulatory Network (mSiReN) and analyze it at the RNA level. We employ Cell-Specific Network Inference via Integer Value Programming and Causal Reasoning (CS-NIVaCaR) to identify core modules and Cell-Specific Probabilistic Contextualization for mRNA Regulatory Networks (CS-ProComReN) to quantitatively reveal activated sub-pathways involving MAPK1, MKNK1, RPS6KA5, and MTOR across different cell types in ASD.

Results: The results indicate that specific pivotal molecules, such as EIF4EBP1 and EIF4E, lacking Differential Expression (DE) characteristics and responsible for protein translation with long-term potentiation (LTP) or long-term depression (LTD), are dysregulated. We further uncover distinct activation patterns causally linked to the EIF4EBP1-EIF4E module in excitatory and inhibitory neurons.

Conclusions: Importantly, our work introduces a methodology for leveraging extensive transcriptomics data to parse the signal transduction network, transforming it into mSiReN, and mapping it back to the protein level. These algorithms can serve as potent tools in systems biology to analyze other omics and regulatory networks. Furthermore, the biomarkers within the activated sub-pathways, revealed by identifying convergent dysregulation, illuminate potential diagnostic and prognostic factors in ASD.