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The WOX (WUSCHEL-related homeobox) is a plant-specific transcription factor involved in plant development and stress response. However, few studies have been reported on the WOX gene in woody plants. In this study, 10 BpWOX genes were isolated from paper mulberry by RACE-PCR and categorized into three clades through phylogenetic analysis, ancient, intermediate and WUS clade. Among them, five members had the transcriptional activity detected by yeast one-hybrid and seven were uniquely localized to the nucleus through green fluorescent protein (GFP) observation. The expression patterns of BpWOX genes in different tissues and under diverse treatments were quantified by the qRT-PCR method. Results showed that BpWUS was expressed in the apical bud, stem and root, BpWOX5 and BpWOX7 functioned only in the root tip, and three BpWOXs regulated leaf development redundantly. BpWOX9 and BpWOX10 were induced by indole-3-acetic acid (IAA) or jasmonic acid (JA), while BpWOX2 was repressed by five phytohormones. Interestingly, most BpWOX genes were responsive to the abiotic stress stimuli of drought, salt, cold, and cadmium (CdCl2). Together, our study revealed that BpWOXs were functionally divergent during paper mulberry development and environmental adaptation, which might be related to their evolutionary relationships. Our work will benefit the systematic understanding of the precise function of WOX in plant development and environmental stress responses. [ABSTRACT FROM AUTHOR]

Sepsis, a disease caused by severe infection, has a high mortality rate. At present, there is a lack of reliable algorithmic models for biomarker mining and diagnostic model construction for sepsis. Programmed cell death (PCD) has been shown to play a vital role in disease occurrence and progression, and different PCD-related genes have the potential to be targeted for the treatment of sepsis. In this paper, we analyzed PCD-related genes in sepsis. Implicated PCD processes include apoptosis, necroptosis, ferroptosis, pyroptosis, netotic cell death, entotic cell death, lysosome-dependent cell death, parthanatos, autophagy-dependent cell death, oxeiptosis, and alkaliptosis. We screened for diagnostic-related genes and constructed models for diagnosing sepsis using multiple machine-learning models. In addition, the immune landscape of sepsis was analyzed based on the diagnosis-related genes that were obtained. In this paper, 10 diagnosis-related genes were screened for using machine learning algorithms, and diagnostic models were constructed. The diagnostic model was validated in the internal and external test sets, and the Area Under Curve (AUC) reached 0.7951 in the internal test set and 0.9627 in the external test set. Furthermore, we verified the diagnostic gene via a qPCR experiment. The diagnostic-related genes and diagnostic genes obtained in this paper can be utilized as a reference for clinical sepsis diagnosis. The results of this study can act as a reference for the clinical diagnosis of sepsis and for target discovery for potential therapeutic drugs. [ABSTRACT FROM AUTHOR]

Hence, the Special Issue "Tree Genetics: Molecular and Functional Characterization of Genes" aimed to collect woody species gene-centered studies, with a special emphasis on functions related to trees' tolerance and resilience to global changes. Two research papers investigate the role of specific genes in the response of trees to pathogens: the function of thaumatin-like proteins (TLP), as most of them exhibit antifungal activity, was investigated in [[4]]; four TLP genes were isolated, identified, and characterized, and their role in defense response demonstrated in I Picea likiangensis i . Indeed, six papers focus on broadleaved trees and four on conifers, including economically relevant species for a plethora of different uses, but also rare/endangered species [[3]] and ecologically important trees [[4]]. [Extracted from the article]

Simple Summary: A bibliometric analysis was carried out to know the evolution of research on genes associated with meat tenderness, of interest for the development of selection programs. Since 1993, studies have been limited to a few researchers in high-income countries due to the costs associated with the techniques. The main findings showed that the scientific production had a discontinuous growth because science experienced a significant change since approximately 2010. Marker-assisted selection was widely used, evaluating mainly CAPN (calpain) and CAST (calpastatin) genes for their contribution to meat tenderness, especially in cattle. However, the effects are small; therefore, genomic selection was implemented by genotyping thousands of single nucleotide polymorphisms (SNPs) for further explanation of genetic variation. The results shown are important for scholars to identify emerging methodologies and gaps in the literature and to know who the prolific authors and institutions in the field for possible collaborations, etc., are. Tenderness is one of the main characteristics of meat because it determines its price and acceptability. This is the first bibliometric study on the trend of research on the role of genes in meat tenderness. A total of 175 original and English-language articles published up to 2021 were retrieved from Scopus. The bibliometric analysis was carried out with VOSviewer (version 1.6.18, Eck and Waltman, Leiden, Netherlands) and complemented with the Analyze search results service from Scopus. Erroneous and duplicate data were eliminated, and incomplete information was added to standardize the results. Scientific production was evaluated by means of quantity, quality and structure indicators. As a first glance, 8.816% of authors have published more than 50% of papers mainly related to genes encoding the calpain (CAPN)-calpastatin (CAST) system and single nucleotide polymorphisms (SNPs). Among other findings, a strong link was found between the contribution of the main countries (led by the United States with) and their institutions (led by the USDA Agricultural Research Service with) to their gross domestic product. Most studies on the topic are published in the Journal of Animal Science, and other journals with high impact according to the number of citations and different metrics. Finally, when evaluating the most cited articles, the occurrence and association of the main keywords, it was confirmed that research is focused on the role of CAPN and CAST genes and of SNPs in beef tenderness. The change in science was emphasized; although marker-assisted selection is still used, genes have an infinitesimal effect on complex traits. Therefore, since about 2010, new research groups adopted genomic selection to evaluate dense panels of SNPs and better explain genetic variation in meat tenderness. [ABSTRACT FROM AUTHOR]

de Magalhães has shown recently that most human genes have several papers in PubMed mentioning cancer, leading the author to suggest that every gene is associated with cancer, a conclusion that contradicts the widely held view that cancer is driven by a limited number of cancer genes, whereas the majority of genes are just bystanders in carcinogenesis. We have analyzed PubMed to decide whether publication metrics supports the distinction of bystander genes and cancer genes. The dynamics of publications on known cancer genes followed a similar pattern: seminal discoveries triggered a burst of cancer-related publications that validated and expanded the discovery, resulting in a rise both in the number and proportion of cancer-related publications on that gene. The dynamics of publications on bystander genes was markedly different. Although there is a slow but continuous time-dependent rise in the proportion of papers mentioning cancer, this phenomenon just reflects the increasing publication bias that favors cancer research. Despite this bias, the proportion of cancer papers on bystander genes remains low. Here, we show that the distinctive publication dynamics of cancer genes and bystander genes may be used for the identification of cancer genes. [ABSTRACT FROM AUTHOR]

Wheat (Triticum aestivum L.) is a fundamental crop essential for both human and animal consumption. Addressing the challenge of enhancing wheat yield involves sophisticated applications of molecular genetics and genomic techniques. This review synthesizes current research identifying and characterizing pivotal genes that impact traits such as grain size, number, and weight, critical factors influencing overall yield. Key genes including TaSPL17, ABP7, TaGNI, TaCKX6, TaGS5, TaDA1, WAPO1, TaRht1, TaTGW-7A, TaGW2, TaGS5-3A, TaSus2-2A, TaSus2-2B, TaSus1-7A, and TaSus1-7B are examined for their roles in these traits. The review also explores genes responsive to environmental changes, which are increasingly significant under current climate variability. Multi-trait regulatory genes and quantitative trait loci (QTLs) that contribute to these traits are discussed, highlighting their dual influences on grain size and yield. Furthermore, the paper underscores the utility of emerging technologies such as CRISPR/Cas9, Case13, and multi-omics approaches. These innovations are instrumental for future discoveries and are poised to revolutionize wheat breeding by enabling precise genetic enhancements. Facing unprecedented challenges from climate change, the identification and utilization of these candidates is crucial. This review aims to be a comprehensive resource for researchers, providing an integrative understanding of complex traits in wheat and proposing new avenues for research and crop improvement strategies. [ABSTRACT FROM AUTHOR]

Maize Ustilago maydis is a disease that severely affects maize yield and quality. In this paper, we employed transcriptome sequencing and GWAS analysis to identify candidate genes and reveal disease-resistant germplasm resources, thereby laying the foundation for further analysis of the molecular mechanism of maize Ustilago maydis resistance and genetic improvement. The results of transcriptome sequencing revealed that a considerable number of receptor kinase genes, signal-transduction-related protein genes, redox-response-related genes, WRKYs, and P450s genes were significantly upregulated. There was a wide range of mutations of Ustilago maydis in maize inbred lines. Thirty-two high-resistance maize inbred lines were selected, and 16 SNPs were significantly associated with the disease index. By integrating the results of GWAS and RNA-seq, five genes related to disease resistance were identified, encoding the chitinase 1 protein, fatty acid elongase (FAE), IAA9, GATA TF8, and EREB94, respectively. It provides a certain reference for the cloning of maize anti-tumor smut genes and the breeding of new varieties. [ABSTRACT FROM AUTHOR]

Simple Summary: The role of neurogenic locus notch homolog protein 1 (NOTCH1)- and nuclear factor erythroid 2-related factor 2 (NRF2)-related pathways is highly heterogeneous in small cell lung cancer (SCLC) and, when they are both abnormally activated, they can synergistically cause neoplastic proliferation. In this paper, we investigate the possible role of KEAP1 silencing in NRF2 and NOTCH axis deregulation in SCLC by evaluating its impact on the modulation of cellular defense systems, cell growth, and differentiation. We also investigate the impact of these systems' impairment in response to conventional chemotherapies and NOTCH inhibitors in silenced SCLC cell lines with different Kelch-like ECH-associated protein 1 (KEAP1) alterations. The KEAP1/NRF2 pathway is a master regulator of several redox-sensitive genes implicated in the resistance of tumor cells against therapeutic drugs. The dysfunction of the KEAP1/NRF2 system has been correlated with neoplastic patients' outcomes and responses to conventional therapies. In lung tumors, the growth and the progression of cancer cells may also involve the intersection between the molecular NRF2/KEAP1 axis and other pathways, including NOTCH, with implications for antioxidant protection, survival of cancer cells, and drug resistance to therapies. At present, the data concerning the mechanism of aberrant NRF2/NOTCH crosstalk as well as its genetic and epigenetic basis in SCLC are incomplete. To better clarify this point and elucidate the contribution of NRF2/NOTCH crosstalk deregulation in tumorigenesis of SCLC, we investigated genetic and epigenetic dysfunctions of the KEAP1 gene in a subset of SCLC cell lines. Moreover, we assessed its impact on SCLC cells' response to conventional chemotherapies (etoposide, cisplatin, and their combination) and NOTCH inhibitor treatments using DAPT, a γ-secretase inhibitor (GSI). We demonstrated that the KEAP1/NRF2 axis is epigenetically controlled in SCLC cell lines and that silencing of KEAP1 by siRNA induced the upregulation of NRF2 with a consequent increase in SCLC cells' chemoresistance under cisplatin and etoposide treatment. Moreover, KEAP1 modulation also interfered with NOTCH1, HES1, and DLL3 transcription. Our preliminary data provide new insights about the downstream effects of KEAP1 dysfunction on NRF2 and NOTCH deregulation in this type of tumor and corroborate the hypothesis of a cooperation of these two pathways in the tumorigenesis of SCLC. [ABSTRACT FROM AUTHOR]

Functional genes encode various biological functions required for the life activities of organisms. By analyzing the functional genes of edible and medicinal fungi, varieties of edible and medicinal fungi can be improved to enhance their agronomic traits, growth rates, and ability to withstand adversity, thereby increasing yield and quality and promoting industrial development. With the rapid development of functional gene research technology and the publication of many whole-genome sequences of edible and medicinal fungi, genes related to important biological traits have been mined, located, and functionally analyzed. This paper summarizes the advantages and disadvantages of different functional gene research techniques and application examples for edible and medicinal fungi; systematically reviews the research progress of functional genes of edible and medicinal fungi in biological processes such as mating type, mycelium and fruit growth and development, substrate utilization and nutrient transport, environmental response, and the synthesis and regulation of important active substances; and proposes future research directions for functional gene research for edible and medicinal fungi. The overall aim of this study was to provide a valuable reference for further promoting the molecular breeding of edible and medicinal fungi with high yield and quality and to promote the wide application of edible and medicinal fungi products in food, medicine, and industry. [ABSTRACT FROM AUTHOR]

This paper focuses on the creation of an in vitro collection of grapevine hybrids from the breeding program of the Kazakh Scientific Research Institute of Fruit Growing and Viticulture and investigates the presence of Plasmopara viticola resistance mediated by Rpv3 and Rpv12 loci. We looked at the optimization of in vitro establishment using either shoots taken directly from field-grown plants or from budwood cuttings forced indoors. We further screened for the presence of endophyte contamination in the initiated explants and optimized the multiplication stage. Finally, the presence of the resistance loci against P. viticola was studied. The shoots initiated from the field-sourced explants were the more effective method of providing plant sources for in vitro initiation once all plant accessions met the goal of in vitro establishment. The concentration of phytohormones and the acidity of the culture medium have a great effect on the multiplication rate and the quality of in vitro stock cultures. Out of 17 grapevine accessions, 16 showed the presence of single or combined resistance loci against P. viticola. The grapevine accessions identified as carrying Rpv3 and Rpv12 alleles represent important genetic resources for disease resistance breeding programs. These accessions may further contribute to the creation of new elite cultivars of economic interest. [ABSTRACT FROM AUTHOR]

Clostridioides difficile infections (CDIs) continue to be a persistent healthcare concern despite newer antibiotic treatments, enhanced infection control practices, and preventive strategies focused on restoring the protective intestinal microbial barrier. Recent strides in gene sequencing research have identified many genes regulating diverse virulence factors for CDIs. These genes may be over- or under-expressed when triggered by various environmental and nutritional factors. The aims of this paper are to review the important genes involved in C. difficile pathogenesis and to identify modifiable environmental, nutritional, and other factors that may trigger the expression of these genes and thus offer new strategies to prevent CDIs. [ABSTRACT FROM AUTHOR]

Neural tube defects (NTDs) are congenital abnormalities in the central nervous system. The exact etiology of NTDs is still not determined, but several genetic and epigenetic factors have been studied. Folate supplementation during gestation is recommended to reduce the risk of NTDs. In this review we examine single nucleotide polymorphisms (SNPs) of the genes in the folate pathway associated with NTD. We reviewed the literature for all papers discussing both NTDs and SNPs in the folate pathway. Data were represented through five different genetic models. Quality assessment was performed using the Newcastle–Ottawa Scale (NOS) and Cohen's Kappa inter-rater coefficient assessed author agreement. Fifty-nine papers were included. SNPs in MTHFR, MTRR, RFC genes were found to be highly associated with NTD risk. NOS showed that high quality papers were selected, and Kappa Q-test was 0.86. Our combined results support the notion that SNPs significantly influence NTDs across the population, particularly in Asian ethnicity. Additional high-quality research from diverse ethnicities is needed and meta-regression analysis based on a range of criteria may provide a more complete understanding of the role of folate metabolism in NTDs. [ABSTRACT FROM AUTHOR]

Currently, it remains unclear why some children develop invasive group A Streptococcus (iGAS) and how to manage this condition. Therefore, to explore available works in the literature, we performed a scoping review aiming to analyze the current literature on clinical presentation of different illnesses outcomes of iGAS, with a specific focus on predictors of invasive infection, including an assessment of the prodromal stages of the disease and the possible presence of previous non-invasive GAS infections in children that later developed iGAS. Methods: We conducted a systematic search on PubMed and SCOPUS of all pediatric studies reporting iGAS cases, following the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) checklist. For those studies in which multivariable analysis investigating iGAS risk factors was performed, a second review was performed and reported in detail. Results: A total of 209 studies were included. Five studies investigated risk factors for iGAS, the most relevant being varicella infection, chronic underlying illness, presence of the speC gene in GAS strains, acetaminophen and ibuprofen use, children nonwhite, living in low-income households, exposure to varicella at home, persistent high fever, having more than one other child in the home, and new use of NSAIDs. Although we observed a progressive increase in the number of papers published on this topic, no trials investigating the benefits of clindamycin or intravenous immunoglobulins were found and low-to-middle-income countries were found to be poorly represented in the current literature. Conclusions: Our scoping review highlights important gaps regarding several aspects of iGAS in children, including prodromic presentation and optimal treatment strategies. There is also little representation of low–middle-income countries. The current literature does not allow the performance of systematic reviews or meta-analyses, but this work should inform healthcare professionals, policy makers, and funding agencies on which studies to prioritize on this topic. [ABSTRACT FROM AUTHOR]

The selection of critical features from microarray data as biomarkers holds significant importance in disease diagnosis and drug development. It is essential to reduce the number of biomarkers while maintaining their performance to effectively minimize subsequent validation costs. However, the processing of microarray data often encounters the challenge of the "curse of dimensionality". Existing feature-selection methods face difficulties in effectively reducing feature dimensionality while ensuring classification accuracy, algorithm efficiency, and optimal search space exploration. This paper proposes a hybrid feature-selection algorithm based on an enhanced version of the Max Relevance and Min Redundancy (mRMR) method, coupled with differential evolution. The proposed method improves the quantization functions of mRMR to accommodate the continuous nature of microarray data attributes, utilizing them as the initial step in feature selection. Subsequently, an enhanced differential evolution algorithm is employed to further filter the features. Two adaptive mechanisms are introduced to enhance early search efficiency and late population diversity, thus reducing the number of features and balancing the algorithm's exploration and exploitation. The results highlight the improved performance and efficiency of the hybrid algorithm in feature selection for microarray data analysis. [ABSTRACT FROM AUTHOR]

Omics technologies accumulated an enormous amount of data that advanced knowledge about the molecular pathogenesis of type 1 diabetes mellitus and identified a number of fundamental problems focused on the transition to personalized diabetology in the future. Among them, the most significant are the following: (1) clinical and genetic heterogeneity of type 1 diabetes mellitus; (2) the prognostic significance of DNA markers beyond the HLA genes; (3) assessment of the contribution of a large number of DNA markers to the polygenic risk of disease progress; (4) the existence of ethnic population differences in the distribution of frequencies of risk alleles and genotypes; (5) the infancy of epigenetic research into type 1 diabetes mellitus. Disclosure of these issues is one of the priorities of fundamental diabetology and practical healthcare. The purpose of this review is the systemization of the results of modern molecular genetic, transcriptomic, and epigenetic investigations of type 1 diabetes mellitus in general, as well as its individual forms. The paper summarizes data on the role of risk HLA haplotypes and a number of other candidate genes and loci, identified through genome-wide association studies, in the development of this disease and in alterations in T cell signaling. In addition, this review assesses the contribution of differential DNA methylation and the role of microRNAs in the formation of the molecular pathogenesis of type 1 diabetes mellitus, as well as discusses the most currently central trends in the context of early diagnosis of type 1 diabetes mellitus. [ABSTRACT FROM AUTHOR]

Soybean being a major cash crop provides half of the vegetable oil and a quarter of the plant proteins to the global population. Seed size traits are the most important agronomic traits determining the soybean yield. These are complex traits governed by polygenes with low heritability as well as are highly influenced by the environment as well as by genotype x environment interactions. Although, extensive efforts have been made to unravel the genetic basis and molecular mechanism of seed size in soybean. But most of these efforts were majorly limited to QTL identification, and only a few genes for seed size were isolated and their molecular mechanism was elucidated. Hence, elucidating the detailed molecular regulatory networks controlling seed size in soybeans has been an important area of research in soybeans from the past decades. This paper describes the current progress of genetic architecture, molecular mechanisms, and regulatory networks for seed sizes of soybeans. Additionally, the main problems and bottlenecks/challenges soybean researchers currently face in seed size research are also discussed. This review summarizes the comprehensive and systematic information to the soybean researchers regarding the molecular understanding of seed size in soybeans and will help future research work on seed size in soybeans. [ABSTRACT FROM AUTHOR]

The functional gene is a product of functional information expression methods inspired by biological genes. Product innovation design is essentially a process of functional problem-solving, which has an intrinsic connection with biological gene expression. The analogy of biological genes, which standardize product function information into functional genes and apply them in product innovation design, holds enormous potential. This paper provides a comprehensive analysis of relevant literature. Firstly, it elaborates on the development of functional genes from the refinement of product genes, clarifying the relationship between functional genes and product genes. Then, it discusses the theoretical foundations of functional gene research, such as the concept, characteristics, and information transmission pathways of functional genes. Moreover, it analyzes key technologies for the application of functional genes, such as functional information encoding forms, and functional gene structure, while summarizing research case studies on functional gene applications. Finally, it explores three key challenges: determining functional gene information content, protecting intellectual property rights, and identifying defects. It also proposes research entry points, aiming to provide references for the field of product innovation design. [ABSTRACT FROM AUTHOR]

Mast cell tumors are a large group of diseases occurring in dogs, cats, mice, as well as in humans. Systemic mastocytosis (SM) is a disease involving the accumulation of mast cells in organs. KIT gene mutations are very often seen in abnormal mast cells. In SM, high KIT/CD117 expression is observed; however, there are usually no KIT gene mutations present. Mastocytoma (MCT)—a form of cutaneous neoplasm—is common in animals but quite rare in humans. KIT/CD117 receptor mutations were studied as the typical changes for human mastocytosis. In 80% of human cases, the KIT gene substitution p.D816H was present. In about 25% of MCTs, metastasis was observed. Changes in the gene expression of certain genes, such as overexpression of the DNAJ3A3 gene, promote metastasis. In contrast, the SNORD93 gene blocks the expression of metastasis genes. The panel of miR-21-5p, miR-379, and miR-885 has a good efficiency in discriminating healthy and MCT-affected dogs, as well as MCT-affected dogs with and without nodal metastasis. Further studies on the pathobiology of mast cells can lead to clinical improvements, such as better MCT diagnosis and treatment. Our paper reviews studies on the topic of mast cells, which have been carried out over the past few years. [ABSTRACT FROM AUTHOR]

Biological data at the omics level are highly complex, requiring powerful computational approaches to identifying significant intrinsic characteristics to further search for informative markers involved in the studied phenotype. In this paper, we propose a novel dimension reduction technique, protein–protein interaction-based gene correlation filtration (PPIGCF), which builds on gene ontology (GO) and protein–protein interaction (PPI) structures to analyze microarray gene expression data. PPIGCF first extracts the gene symbols with their expression from the experimental dataset, and then, classifies them based on GO biological process (BP) and cellular component (CC) annotations. Every classification group inherits all the information on its CCs, corresponding to the BPs, to establish a PPI network. Then, the gene correlation filter (regarding gene rank and the proposed correlation coefficient) is computed on every network and eradicates a few weakly correlated genes connected with their corresponding networks. PPIGCF finds the information content (IC) of the other genes related to the PPI network and takes only the genes with the highest IC values. The satisfactory results of PPIGCF are used to prioritize significant genes. We performed a comparison with current methods to demonstrate our technique's efficiency. From the experiment, it can be concluded that PPIGCF needs fewer genes to reach reasonable accuracy (~99%) for cancer classification. This paper reduces the computational complexity and enhances the time complexity of biomarker discovery from datasets. [ABSTRACT FROM AUTHOR]

Cancer, a genetic disease, is considered one of the leading causes of death globally and affects people of all ages. Ribonucleic acid sequencing (RNA-Seq) is a technique used to quantify the expression of genes of interest and can be used to classify cancer tumor types. This paper describes a machine learning technique to classify cancer tissue samples by tumor type, such as breast cancer, lung cancer, colon cancer, and others. More than 60,000 RNA-Seq features were analyzed using six different machine learning classification algorithms, both individually and as an ensemble. Numerous dimensionality reduction techniques addressed the challenges of working with enormous amounts of genetic data. In particular, we were able to reduce the number of features from over 60,000 to 660 in the random forest feature selection and to 68 factor features using factor analysis with an accuracy of 99% in classifying tumor types. [ABSTRACT FROM AUTHOR]

Nodule bacteria (rhizobia) represent a suitable model to address a range of fundamental genetic problems, including the impacts of natural selection on the evolution of symbiotic microorganisms. Rhizobia possess multipartite genomes in which symbiotically specialized (sym) genes differ from core genes in their natural histories. Diversification of sym genes is responsible for rhizobia microevolution, which depends on host-induced natural selection. By contrast, diversification of core genes is responsible for rhizobia speciation, which occurs under the impacts of still unknown selective factors. In this paper, we demonstrate that in goat's rue rhizobia (Neorhizobium galegae) populations collected at North Caucasus, representing two host-specific biovars orientalis and officianalis (N2-fixing symbionts of Galega orientalis and G. officinalis), the evolutionary mechanisms are different for core and sym genes. In both N. galegae biovars, core genes are more polymorphic than sym genes. In bv. orientalis, the evolution of core genes occurs under the impacts of driving selection (dN/dS > 1), while the evolution of sym genes is close to neutral (dN/dS ≈ 1). In bv. officinalis, the evolution of core genes is neutral, while for sym genes, it is dependent on purifying selection (dN/dS < 1). A marked phylogenetic congruence of core and sym genes revealed using ANI analysis may be due to a low intensity of gene transfer within and between N. galegae biovars. Polymorphism in both gene groups and the impacts of driving selection on core gene evolution are more pronounced in bv. orientalis than in bv. officianalis, reflecting the diversities of their respective host plant species. In bv. orientalis, a highly significant (P0 < 0.001) positive correlation is revealed between the p-distance and dN/dS values for core genes, while in bv. officinalis, this correlation is of low significance (0.05 < P0 < 0.10). For sym genes, the correlation between p-distance and dN/dS values is negative in bv. officinalis but is not revealed in bv. orientalis. These data, along with the functional annotation of core genes implemented using Gene Ontology tools, suggest that the evolution of bv. officinalis is based mostly on adaptation for in planta niches while in bv. orientalis, evolution presumably depends on adaptation for soil niches. New insights into the tradeoff between natural selection and genetic diversity are presented, suggesting that gene nucleotide polymorphism may be extended by driving selection only in ecologically versatile organisms capable of supporting a broad spectrum of gene alleles in their gene pools. [ABSTRACT FROM AUTHOR]

As seen in earlier and present pandemics, monitoring pathogens in the environment can offer multiple insights on their spread, evolution, and even future outbreaks. The present paper assesses the opportunity to detect microbial pathogens and associated antibiotic resistance genes, in relation to specific pathogen sources, by using nanopore sequencing in municipal waters and wastewaters in Romania. The main results indicated that waters collecting effluents from a meat processing facility exhibit altered communities' diversity and abundance, with reduced values (101–108 and 0.86–0.91) of Chao1 and, respectively, Simpson diversity indices and Campylobacterales as main order, compared with other types of municipal waters where the same diversity index had much higher values of 172–214 and 0.97–0.98, and Burkholderiaceae and Pseudomonadaceae were the most abundant families. Moreover, the incidence and type of antibiotic resistance genes were significantly influenced by the proximity of antibiotic sources, with either tetracycline (up to 45% of total reads) or neomycin, streptomycin and tobramycin (up to 3.8% total reads) resistance incidence being shaped by the sampling site. As such, nanopore sequencing proves to be an easy-to-use, accessible molecular technique for environmental pathogen surveillance and associated antibiotic resistance genes. [ABSTRACT FROM AUTHOR]

Putative methyltranferase LaeA and LaeA-like proteins, conserved in many filamentous fungi, regulate fungal growth, development, virulence, the biosynthesis of secondary metabolites, and the production of cellulolytic enzymes. Penicillium oxaliucm is a typical fungus that produces cellulolytic enzymes. In this study, we reported the biological function of eight putative methyltransferases (PoMtr23C/D/E/F/G/H and PoMtr25A/B) containing a methyltransf_23 or methyltransf_25 domain, with a focus on their roles in the production of cellulolytic enzymes. In P. oxalicum, various methyltransferase genes displayed different transcriptional levels. The genes Pomtr23C and Pomtr25A exhibited high transcriptional levels, while Pomtr23D/E/F/G/H and Pomtr25B were transcribed constantly at low levels. The gene deletion mutants (Δmtr23C/D/E/F/G/H and Δmtr25A/B) were constructed. Various mutants have different patterns in cellulolytic enzyme production. Compared to the WT, the largest increase in filter paper activity (FPA, indicating total cellulase activity) was observed in the Δmtr23G mutant, the only mutant with a cellulolytic halo surrounding the colony. Three mutants (Δmtr23C/D and Δmtr25A) also showed increased cellulolytic enzyme production. The Δmtr23E and Δmtr25B mutants displayed decreased FPA activity, while the Δmtr23F and Δmtr23H mutants displayed similar patterns of cellulolytic enzyme production compared with the WT. The assay of transcriptional levels of cellobiohydrolase gene Pocbh1 and β-1,4-endoglucanase Poeg1 supported that higher cellulolytic gene transcription resulted in higher production of cellulolytic enzymes, and vice versa. The transcriptional levels of two transcription factors, activator XlnR and repressor CreA, were measured. The high transcription level of the PoxlnR gene in the Δmtr23D mutant should be one reason for the increased transcription of its cellulolytic enzyme gene. Both XlnR and CreA transcriptional levels increased in the Δmtr23G mutant, but the former showed a more significant increase than the latter, indicating that the activation effect predominated. The PoMtr25A is localized in the nucleus. The catalytic subunit SNF2 of the SWI/SNF chromatin-remodeling complex was found as one of the interacting proteins of PoMtr25A via tandem affinity purification coupled with mass spectrometry. PoMtr25A may affect not only the transcription of repressor CreA but also by recruiting SWI/SNF complexes that affect chromatin structure, thereby regulating the transcription of target genes. [ABSTRACT FROM AUTHOR]

Simple Summary: Changes in the gut microbiome are associated with bowel cancers, however, less is known about the microbiome during the pre-cancerous bowel polyp stage. This study compared two DNA sequencing technologies to identify the gut microbiome from mucosa of colonoscopy patients diagnosed with bowel polyps or without bowel polyps. We found that different sequencing technologies and bioinformatic pipelines impact on bacterial taxonomy assignments. Overall, there were only minor differences in gut microbiome communities between participants with bowel polyps and those without. However, Ruminococcus gnavus, a bacteria commonly associated with inflammatory bowel disease (IBD) was shown to be more abundant in participants with polyps, despite participants with IBD being exclude from this study. This paper adds to our knowledge of the gut microbiome associated with bowel neoplasia. Numerous studies have correlated dysbiosis in stool microbiota with colorectal cancer (CRC); however, fewer studies have investigated the mucosal microbiome in pre-cancerous bowel polyps. The short-read sequencing of variable regions in the 16S rRNA gene has commonly been used to infer bacterial taxonomy, and this has led, in part, to inconsistent findings between studies. Here, we examined mucosal microbiota from patients who presented with one or more polyps, compared to patients with no polyps, at the time of colonoscopy. We evaluated the results obtained using both short-read and PacBio long-read 16S rRNA sequencing. Neither sequencing technology identified significant differences in microbial diversity measures between patients with or without bowel polyps. Differential abundance measures showed that amplicon sequence variants (ASVs) associated with Ruminococcus gnavus and Escherichia coli were elevated in mucosa from polyp patients, while ASVs associated with Parabacteroides merdae, Veillonella nakazawae, and Sutterella wadsworthensis were relatively decreased. Only R. gnavus was consistently identified using both sequencing technologies as being altered between patients with polyps compared to patients without polyps, suggesting differences in technologies and bioinformatics processing impact study findings. Several of the differentially abundant bacteria identified using either sequencing technology are associated with inflammatory bowel diseases despite these patients being excluded from the current study, which suggests that early bowel neoplasia may be associated with a local inflammatory niche. [ABSTRACT FROM AUTHOR]

The anticancer drug mithramycin (MTH), has been proposed for drug repurposing after the finding that it is a potent inducer of fetal hemoglobin (HbF) production in erythroid precursor cells (ErPCs) from β-thalassemia patients. In this respect, previously published studies indicate that MTH is very active in inducing increased expression of γ-globin genes in erythroid cells. This is clinically relevant, as it is firmly established that HbF induction is a valuable approach for the therapy of β-thalassemia and for ameliorating the clinical parameters of sickle-cell disease (SCD). Therefore, the identification of MTH biochemical/molecular targets is of great interest. This study is inspired by recent robust evidence indicating that the expression of γ-globin genes is controlled in adult erythroid cells by different transcriptional repressors, including Oct4, MYB, BCL11A, Sp1, KLF3 and others. Among these, BCL11A is very important. In the present paper we report evidence indicating that alterations of BCL11A gene expression and biological functions occur during MTH-mediated erythroid differentiation. Our study demonstrates that one of the mechanisms of action of MTH is a down-regulation of the transcription of the BCL11A gene, while a second mechanism of action is the inhibition of the molecular interactions between the BCL11A complex and specific sequences of the γ-globin gene promoter. [ABSTRACT FROM AUTHOR]

The MYB transcription factor family is one of the largest families of plant transcription factors (TFs), and it plays a vital role in the entire process of a plant's growth and development. Well known in China, Eucommia ulmoides (E. ulmoides) produces a form of natural rubber called Eucommia ulmoides gum (EUG). Nevertheless, there is little research on the evolutionary history and expression patterns of its MYBs, as well as on the regulation of EUG by MYB TFs. This research provides a comprehensive description, classification, and potential functional analysis of the EuMYB gene family. A total of 119 MYB members of E. ulmoides were identified based on the whole genome sequencing data, and their gene structure, phylogenetics, chromosome location, conserved motifs, etc., were analyzed. Based on the phylogenetic tree results, EuMYBs could be divided into 35 sub-groups. In addition, chromosomal localization and collinearity analysis revealed the heterogeneous distribution of the MYB family in the E. ulmoides' genome, indicating the expansion of its gene family. Moreover, promoter cis-acting elements showed that the promoter contained abundant light-responsive elements, anaerobic-induction-responsive elements, and abscisic-acid-responsive elements. A co-expression regulatory network between the EUG biosynthesis genes and the EuMYBs was built. Meanwhile, regarding the six EuMYBs with high expression in the gum-forming tissues selected that correlated with the farnesyl diphosphate synthase (FPS1) structural gene, RT-qPCR experiments showed a possible regulatory relationship between EuMYBs and FPS1, which played an important role in EUG biosynthesis. In conclusion, this paper defines a research gap and lays a foundation for further studies on the biological functions of EuMYBs. [ABSTRACT FROM AUTHOR]

This correction notice from the Horticulturae journal addresses an error in the affiliation of one of the authors, Prashant Kaushik. The correct affiliation should be listed as "Independent Researcher, 46022 Valencia, Spain." The authors assure that this correction does not affect the scientific conclusions of the paper. The correction has been approved by the Academic Editor and the original publication has been updated. [Extracted from the article]

Simple Summary: Immunity combined with ferroptosis is being considered as a new tumor treatment modality, and its regulation in head and neck squamous cell carcinoma is still unknown. The purpose of this study was to look into the potential molecular biological roles of immune ferroptosis genes in head and neck squamous cell carcinoma. The 12-IFRM signatures were successfully constructed and classified into high- and low-risk groups using the TCGA database and related data resources. In patients with head and neck squamous cell carcinoma, feature-based risk scores were more predictive of survival than traditional clinicopathological features. Furthermore, the expression of CD8+T cells and macrophage M0 differed significantly between the two groups. The expression of TNFSF9 and CD44 in the high-risk groups was significantly increased compared with the low-risk groups. Next, we found a higher proportion of high-risk mutations than in the low-risk group. In addition, the high-risk group was more sensitive to some chemotherapy drugs. Finally, we performed correlation analysis on the model genes. In this paper, the 12-IFRM signatures was developed with promising application prospects for predicting the clinical outcomes and treatment outcomes in head and neck squamous cell carcinoma. Ferroptosis is a new type of programmed cell death that plays a pivotal role in a variety of tumors. Moreover, immunity is closely related to ferroptosis. However, immune-ferroptosis-related mRNAs (IFRMs) are still not fully understood in the regulation of head and neck squamous cell carcinoma (HNSC). The purpose of this paper was to investigate the IFRMs prediction of HNSC and its possible molecular biological role. RNA-Seq and related clinical data were mined from the TCGA database, ImmPort database, GeneCards database, FerrDb database, and previous data. In R software, the "DESeq2" package was used to analyze the differential expression of IFRMs. We used univariate Cox analysis to judge the prognosis of the IFRMs. Using the least absolute shrinkage and selection operator (LASSO) and Cox regression, a prediction model for 12 IFRMs was established. In this study, the Kaplan–Meier survival curve and receiver operating characteristic (ROC) curve analysis were used to evaluate the prediction results. Moreover, factors such as immune landscape, somatic mutations, and drug susceptibility are also discussed. We successfully constructed the signature of 12-IFRMs. The two risk groups were classified according to the risk score obtained by this signature. Compared with conventional clinicopathological features, the characteristic-based risk score was more predictive of survival in patients with HNSC. Furthermore, the expression of CD8+T cells and macrophage M0 differed significantly between the two groups. Moreover, the expression of TNFSF9 and CD44 in high-risk groups was significantly increased compared with the low-risk groups. Then, we found a higher proportion of high-risk mutations than in the low-risk group. Next, the high-risk group was more sensitive to chemotherapy drugs such as bosutinib, docetaxel, erlotinib, gefitinib, imatinib, lapatinib, and sorafenib. Finally, an in-depth analysis of the association and potential value of the 12 genes was performed. In summary, the 12-IFRM signatures established in this paper had good application prospects and could be effectively used to predict the clinical outcome and treatment response of head and neck squamous cell carcinoma. [ABSTRACT FROM AUTHOR]

A large volume of high-dimensional genetic data has been produced in modern medicine and biology fields. Data-driven decision-making is particularly crucial to clinical practice and relevant procedures. However, high-dimensional data in these fields increase the processing complexity and scale. Identifying representative genes and reducing the data's dimensions is often challenging. The purpose of gene selection is to eliminate irrelevant or redundant features to reduce the computational cost and improve classification accuracy. The wrapper gene selection model is based on a feature set, which can reduce the number of features and improve classification accuracy. This paper proposes a wrapper gene selection method based on the slime mould algorithm (SMA) to solve this problem. SMA is a new algorithm with a lot of application space in the feature selection field. This paper improves the original SMA by combining the Cauchy mutation mechanism with the crossover mutation strategy based on differential evolution (DE). Then, the transfer function converts the continuous optimizer into a binary version to solve the gene selection problem. Firstly, the continuous version of the method, ISMA, is tested on 33 classical continuous optimization problems. Then, the effect of the discrete version, or BISMA, was thoroughly studied by comparing it with other gene selection methods on 14 gene expression datasets. Experimental results show that the continuous version of the algorithm achieves an optimal balance between local exploitation and global search capabilities, and the discrete version of the algorithm has the highest accuracy when selecting the least number of genes. [ABSTRACT FROM AUTHOR]

Simple Summary: This review of several recent developments and findings in molecular and radiation biology and medical physics was put together to improve the treatment of cancer. An improved understanding of the effect of radiation on tumors and normal tissue responses makes it possible to treat tumors more effectively and with less damage to normal tissues. This paper is based on a new, improved understanding of the cellular damage and repair processes and the associated internal cellular program to eliminate itself when critically damaged (apoptosis) to avoid severe mutations of the hereditary material of the individual. An improved radiation dose–time fractionation method is proposed to more effectively cure cancer without damaging the surrounding normal tissues. Furthermore, the best possible radiation beams of intensity-modulated electrons, photons, and the lightest ions from lithium to boron are proposed to obtain the best possible treatment results, increasing the tumor cure probability by about 20%. The new biological interaction cross-section-based repairable–homologically repairable (RHR) damage formulation for radiation-induced cellular inactivation, repair, misrepair, and apoptosis was applied to optimize radiation therapy. This new formulation implies renewed thinking about biologically optimized radiation therapy, suggesting that most TP53 intact normal tissues are low-dose hypersensitive (LDHS) and low-dose apoptotic (LDA). This generates a fractionation window in LDHS normal tissues, indicating that the maximum dose to organs at risk should be ≤2.3 Gy/Fr, preferably of low LET. This calls for biologically optimized treatments using a few high tumor dose-intensity-modulated light ion beams, thereby avoiding secondary cancer risks and generating a real tumor cure without a caspase-3-induced accelerated tumor cell repopulation. Light ions with the lowest possible LET in normal tissues and high LET only in the tumor imply the use of the lightest ions, from lithium to boron. The high microscopic heterogeneity in the tumor will cause local microscopic cold spots; thus, in the last week of curative ion therapy, when there are few remaining viable tumor clonogens randomly spread in the target volume, the patient should preferably receive the last 10 GyE via low LET, ensuring perfect tumor coverage, a high cure probability, and a reduced risk for adverse normal tissue reactions. Interestingly, such an approach would also ensure a steeper rise in tumor cure probability and a higher complication-free cure, as the few remaining clonogens are often fairly well oxygenated, eliminating a shallower tumor response due to inherent ion beam heterogeneity. With the improved fractionation proposal, these approaches may improve the complication-free cure probability by about 10–25% or even more. [ABSTRACT FROM AUTHOR]

Gene therapy is the ultimate therapeutic technology for diseases related to gene abnormality. However, the use of DNA alone has serious problems, such as poor stability and difficulty in entering target cells. The development of a safe and efficient gene delivery system is the cornerstone of gene therapy. Of particular interest, multifunctional peptides are rationally designed as non-viral vectors for efficient gene delivery. As components of gene delivery vectors, these peptides play critically important roles in skeleton construction, the implementation of targeting strategies, cell membrane penetration, endosome rupture, and nuclear transport. In recent years, the research of functional peptide-based gene delivery vectors has made important progress in improving transfection efficiency. The latest research progress and future development direction of peptide-based gene delivery vectors are reviewed in this paper. [ABSTRACT FROM AUTHOR]

Gene sequencing is an important means for modern life sciences research and clinical diagnosis. In recent years, dual-color synchronous gene sequencing has developed rapidly due to its excellent properties such as high throughput, fast speed, miniaturization, and low cost. In this paper, a type of dual-color synchronous gene sequencing optical path structure, which is based on the fluorescence-detection principle, was designed. FAM and TAMRA were selected as the fluorophores, which corresponded to excitation light sources with 488 nm laser and 543 nm laser, respectively. Combining the optical system and fluorophores, we designed the parameters of the filter sets, including the details of design methods for dual-bandpass filters and dual-notch dichromic mirrors. Moreover, these filters were successfully manufactured by ion-assisted deposition and magnetron-sputtering methods with extreme precision. The satisfying application effect was demonstrated when these products were applied in customer-desktop medium-throughput gene sequencers. [ABSTRACT FROM AUTHOR]

The expanded GGGGCC hexanucleotide repeat (HRE) in the non-coding region of the C9ORF72 gene (C9ORF72-HRE) is the most common genetic cause of familial forms of amyotrophic lateral sclerosis (ALS), FTD, and concurrent ALS and FTD (ALS-FTD), in addition to contributing to the sporadic forms of these diseases. Both syndromes overlap not only genetically, but also sharing similar clinical and neuropathological findings, being considered as a spectrum. In this paper we describe the clinical-genetic findings in a Basque family with different manifestations within the spectrum, our difficulties in reaching the diagnosis, and a narrative review, carried out as a consequence, of the main features associated with C9ORF72-HRE. Family members underwent a detailed clinical assessment, neurological examination, and genetic analysis by repeat-primed PCR. We studied 10 relatives of a symptomatic carrier of the C9ORF72-HRE expansion. Two of them presented the expansion in the pathological range, one of them was symptomatic whereas the other one remained asymptomatic at 72 years. Given the great intrafamilial clinical variability of C9ORF72-HRE, the characterization of patients and family members with particular clinical and genetic subgroups within ALS and FTD becomes a bottleneck for medication development, in particular for genetically focused medicines for ALS and FTD. [ABSTRACT FROM AUTHOR]

The existence of current species can be attributed to a dynamic interplay between evolutionary forces and the maintenance of genetic information. Heterochromatin is a major structural feature of the eukaryotic genome stability, a specialized type of chromatin that contains a complex and still poorly understood genomic compartment, extremely enriched in repeats and transposable elements [[15]] in which expressed genes are rare but not completely absent [[16]]. While mutations are the primary drivers of evolution, there are cellular mechanisms that counterbalance excessive variation and contribute to the stability of genes and genomes and preserve the faithful pass down of the genetic material from generation to generation. This form of symbiosis results in the destabilization of the mitochondrial genome (mtDNA) when mutations hit a subset of nuclear genes. [Extracted from the article]

Single-cell RNA sequencing (scRNA-seq) has become a powerful technique to investigate cellular heterogeneity and complexity in various fields by revealing the gene expression status of individual cells. Despite the undeniable benefits of scRNA-seq, it is not immune to its inherent limitations, such as sparsity and noise, which would hinder downstream analysis. In this paper, we introduce scCGImpute, a model-based approach for addressing the challenges of sparsity in scRNA-seq data through imputation. After identifying possible dropouts using mixed models, scCGImpute takes advantage of the cellular similarity in the same subpopulation to impute and then uses random forest regression to obtain the final imputation. scCGImpute only imputes the likely dropouts without changing the non-dropout data and can use information from the similarity of cells and genetic correlation simultaneously. Experiments on simulation data and real data were made, respectively, to evaluate the performance of scCGImpute in terms of gene expression recovery and clustering analysis. The results demonstrated that scCGImpute can effectively restore gene expression and improve the identification of cell types. [ABSTRACT FROM AUTHOR]

Cadmium (Cd) is a non-essential, highly phytotoxic metal and damages ramie plant growth and development even at low concentrations. Ramie is one of the most significant crops in China, with excellent fiber quality and immense industrial importance. Planting Cd-tolerant ramie cultivars can prevent yield loss on contaminated soil. Previously, significant efforts have been made to develop Cd tolerance in ramie. However, the Cd tolerance mechanism is still not fully understood; hence, breeding industrial crops is critical to tackling the ongoing challenges. Cd tolerance is a complex genetic mechanism requiring high-level molecular studies to clarify the genes network. Genetic studies have identified several Cd-tolerant genes in ramie, which led to the development of several ramie cultivars suitable to grow on toxic soils; however, due to the continuous rise in Cd toxicity, potent molecular tools are critical in modern-day breeding programs. Genetic engineering, and transcriptome analysis have been used to develop abiotic stress tolerance in ramie, but QTL mapping and clustered regularly interspaced short palindromic repeats (CRISPR) are rarely studied. However, studies are still limited in addressing this issue. This review critically elaborated on using QTL mapping, transcriptomes, transcription factors, CRISPR/Cas9, and genetic engineering to enhance Cd tolerance in ramie. These genes/QTL should be transferred or edited into sensitive cultivars using genetic engineering or CRISPR/Cas9. CRISPR/Cas9 is highly recommended because it provides targeted gene editing in ramie, its use is limited and can address the research gaps, and it would revolutionize the field of agriculture. Limitations, gaps, and future potential are briefly discussed. This review paper presents new clues to help future researchers comprehensively understand Cd tolerance in ramie and develop tolerant cultivars for industrial purposes. [ABSTRACT FROM AUTHOR]

The main efforts in common wheat (Triticum aestivum L.) breeding focus on yield, grain quality, and resistance to biotic and abiotic stresses. One of the major threats affecting global wheat cultivation and causing significant crop production losses are rust diseases, including leaf rust caused by a biotrophic fungus Puccinia triticina Eriks. Genetically determined resistance to leaf rust has been characterized in young plants (seedling resistance) as well as in plants at the adult plant stage. At the seedling stage, resistance is controlled vertically by major R genes, conferring a race-specific response that is highly effective but usually short-lived due to the rapid evolution of potentially virulent fungi. In mature plants, horizontal adult plant resistance (APR) was described, which provides long-term protection against multiple races of pathogens. A better understanding of molecular mechanisms underlying the function of APR genes would enable the development of new strategies for resistance breeding in wheat. Therefore, in the present study we focused on early transcriptomic responses of two major wheat APR genes, Lr34 and Lr67, and three complementary miRNAs, tae-miR9653b, tae-miR9773 and tae-miR9677b, to inoculation with P. triticina. Plant material consisted of five wheat reference varieties, Artigas, NP846, Glenlea, Lerma Rojo and TX89D6435, containing the Lr34/Yr18 and Lr67/Yr46 resistance genes. Biotic stress was induced by inoculation with fungal spores under controlled conditions in a phytotron. Plant material consisted of leaf tissue sampled before inoculation as well as 6, 12, 24 and 48 h postinoculation (hpi). The APR gene expression was quantified using real-time PCR with two reference genes, whereas miRNA was quantified using droplet digital PCR. This paper describes the resistance response of APR genes to inoculation with races of leaf rust-causing fungi that occur in central Europe. The study revealed high variability of expression profiles between varieties and time-points, with the prevalence of downregulation for APR genes and upregulation for miRNAs during the development of an early defense response. Nevertheless, despite the downregulation initially observed, the expression of Lr34 and Lr67 genes in studied cultivars was significantly higher than in a control line carrying wild (susceptible) alleles. [ABSTRACT FROM AUTHOR]

Simple Summary: This paper proposes a deep learning model for prognosis estimation and an attention mechanism for gene expression. In the prognosis estimation of low-grade glioma (LGG), the proposed model, Gene Attention Ensemble NETwork (GAENET), demonstrated superior performance compared to conventional models, where GAENET exhibited an improvement of 7.2% compared to the second-best model. By the proposed gene attention, HILS1 was discovered as the most significant prognostic gene for LGG. While HILS1 is classified as a pseudogene, it functions as a biomarker for predicting the prognosis of LGG and has been shown to have the ability to regulate the expression of other prognostic genes. While estimating the prognosis of low-grade glioma (LGG) is a crucial problem, it has not been extensively studied to introduce recent improvements in deep learning to address the problem. The attention mechanism is one of the significant advances; however, it is still unclear how attention mechanisms are used in gene expression data to estimate prognosis because they were designed for convolutional layers and word embeddings. This paper proposes an attention mechanism called gene attention for gene expression data. Additionally, a deep learning model for prognosis estimation of LGG is proposed using gene attention. The proposed Gene Attention Ensemble NETwork (GAENET) outperformed other conventional methods, including survival support vector machine and random survival forest. When evaluated by C-Index, the GAENET exhibited an improvement of 7.2% compared to the second-best model. In addition, taking advantage of the gene attention mechanism, HILS1 was discovered as the most significant prognostic gene in terms of deep learning training. While HILS1 is known as a pseudogene, HILS1 is a biomarker estimating the prognosis of LGG and has demonstrated a possibility of regulating the expression of other prognostic genes. [ABSTRACT FROM AUTHOR]

This document is a reply to a comment on a previous paper about choroideremia, a genetic eye disorder. The authors address the concerns raised by the commenters and provide further explanation and evidence for their hypothesis. They discuss the potential partial escape from X chromosome inactivation (XCI) of the CHM gene and its effect on the severity of the disease in female carriers. They also address the dominant negative effect of a specific variant and its impact on the phenotype in both males and females. The authors suggest that further studies should be conducted to confirm their findings and explore potential genotype-phenotype correlations. [Extracted from the article]

Pepsinogen A (PGA) plays an important role in the treatment of human gastrointestinal diseases. At present, PGA is mainly extracted from pig stomach, so its source is very limited and its price is very expensive. Production of PGA by microbial fermentation using an engineered strain with high PGA yield would be an ideal solution. This paper presents a new system for the high-level expression of PGA from Homo sapiens (hPGA) in Aspergillus niger. The hPGA5 gene codon was optimized according to the codon bias of A. niger and then connected to a strong promoter and signal peptide to construct an hPGA5 expression cassette. An ingenious multi-copy knock-in expression strategy mediated by the CRISPR/Cas9 tool was used to improve the production of hPGA in A. niger. By optimizing the copy number and integration sites of the hPGA5 gene, an engineering strain with a high yield of hPGA was constructed. After shake-flask fermentation for 7 d, the enzyme activity of recombinant hPGA reached 542.3 U/mL, which is the highest known activity. This lays a foundation for the production of hPGA by microbial fermentation. [ABSTRACT FROM AUTHOR]

Antheraea pernyi is one of the most famous edible and silk-producing wild silkworms of Saturniidae. Structural cuticular proteins (CPs) are the primary component of insect cuticle. In this paper, the CPs in the genome of A. pernyi were identified and compared with those of the lepidopteran model species Bombyx mori, and expression patterns were analyzed based on the transcriptomic data from the larval epidermis/integument (epidermis in the following) and some non-epidermis tissues/organs of two silkworm species. A total of 217 CPs was identified in the A. pernyi genome, a comparable number to B. mori (236 CPs), with CPLCP and CPG families being the main contribution to the number difference between two silkworm species. We found more RR-2 genes expressed in the larval epidermis of fifth instar of A. pernyi than B. mori, but less RR-2 genes expressed in the prothoracic gland of A. pernyi than B. mori, which suggests that the hardness difference in the larval epidermis and prothoracic gland between the two species may be caused by the number of RR-2 genes expressed. We also revealed that, in B. mori, the number of CP genes expressed in the corpus allatum and prothoracic gland of fifth instar was higher than that in the larval epidermis. Our work provided an overall framework for functional research into the CP genes of Saturniidae. [ABSTRACT FROM AUTHOR]

Barley leaf rust (Puccinia hordei Otth.) is considered a harmful disease that occurs in barley-growing regions worldwide. In Russia, the disease is among the most prevalent in the Krasnodar region, which is the leader in the production of barley grain and has a favorable climate for disease development. In this paper, we studied the efficiency of 17 varieties and lines of barley from the International and Australian sets containing currently known Rph resistance genes or their combinations to P. hordei in the field, and 15 varieties and lines in the seedling phase in greenhouse conditions during 2019–2021. We concluded that the lines carrying the Rph7 and Rph13 genes remained immune throughout the three years of studies in the seedling and adult plant stages. The Rph1 and Rph23 genes showed moderate efficiency during the three years. The Rph2, Rph3, Rph4, Rph5, Rph6+2, Rph8, Rph12, Rph19, and Rph21+2 genes showed low efficiency over the three years. This was also confirmed by the results of their assessment in the seedling phase: the number of monopustular isolates virulent to lines with the majority of the studied genes for three years was above 90%. Fluctuations in the virulence of the P. hordei population were observed under sufficiently unfavorable weather for disease development in 2019, 2020, and 2021. This proves the ability of the fungus to adapt to changing conditions. Therefore, annual monitoring of the response of lines and varieties carrying resistance genes and studying the virulence of the pathogen are crucial for the selection of rust-resistant varieties, and, hence, the prevention of barley leaf rust epidemics in all grain-producing regions worldwide. [ABSTRACT FROM AUTHOR]

Orphan genes (OGs) may evolve from noncoding sequences or be derived from older coding material. Some shares of OGs are present in all sequenced genomes, participating in the biochemical and physiological pathways of many species, while many of them may be associated with the response to environmental stresses and species-specific traits or regulatory patterns. However, identifying OGs is a laborious and time-consuming task. This paper presents an automated predictor, XGBoost-A2OGs (identification of OGs for angiosperm based on XGBoost), used to identify OGs for seven angiosperm species based on hybrid features and XGBoost. The precision and accuracy of the proposed model based on fivefold cross-validation and independent testing reached 0.90 and 0.91, respectively, outperforming other classifiers in cross-species validation via other models, namely, Random Forest, AdaBoost, GBDT, and SVM. Furthermore, by analyzing and subdividing the hybrid features into five sets, it was proven that different hybrid feature sets influenced the prediction performance of OGs involving eudicot and monocot groups. Finally, testing of small-scale empirical datasets of each species separately based on optimal hybrid features revealed that the proposed model performed better for eudicot groups than for monocot groups. [ABSTRACT FROM AUTHOR]

Aegilops tauschii is one of the malignant weeds that affect wheat production and is also the wild species ancestor of the D genome of hexaploid wheat (Triticum aestivum, AABBDD). It contains many disease resistance genes that have been lost in the long-term evolution of wheat and is an important genetic resource for the mining and utilization of wheat disease resistance genes. In recent years, the genome sequence of Aegilops tauschii has been preliminarily completed, which has laid a good foundation for the further exploration of wheat disease resistance genes in Aegilops tauschii. There are many studies on disease resistance genes in Aegilops tauschii; in order to provide better help for the disease resistance breeding of wheat, this paper analyzes and reviews the relationship between Aegilops tauschii and wheat, the research progress of Aegilops tauschii, the discovery of disease resistance genes from Aegilops tauschii, and the application of disease resistance genes from Aegilops tauschii to modern wheat breeding, providing a reference for the further exploration and utilization of Aegilops tauschii in wheat disease resistance breeding. [ABSTRACT FROM AUTHOR]

For several decades, intensive research for understanding gene activity and its role in organism's lives is the research focus of scientists in different areas. A part of these investigations is the analysis of gene expression data for selecting differentially expressed genes. Methods that identify the interested genes have been proposed on statistical data analysis. The problem is that there is no good agreement among them, as different results are produced by distinct methods. By taking the advantage of the unsupervised data analysis, an iterative clustering procedure that finds differentially expressed genes shows promising results. In the present paper, a comparative study of the clustering methods applied for gene expression analysis is presented to explicate the choice of the clustering algorithm implemented in the method. An investigation of different distance measures is provided to reveal those that increase the efficiency of the method in finding the real data structure. Further, the method is improved by incorporating an additional aggregation measure based on the standard deviation of the expression levels. Its usage increases the gene distinction as a new amount of differentially expressed genes is found. The method is summarized in a detailed procedure. The significance of the method is proved by an analysis of two mice strain data sets. The differentially expressed genes defined by the proposed method are compared with those selected by the well-known statistical methods applied to the same data set. [ABSTRACT FROM AUTHOR]

Sparse data with a high portion of zeros arise in various disciplines. Modeling sparse high-dimensional data is a challenging and growing research area. In this paper, we provide statistical methods and tools for analyzing sparse data in a fairly general and complex context. We utilize two real scientific applications as illustrations, including a longitudinal vaginal microbiome data and a high dimensional gene expression data. We recommend zero-inflated model selections and significance tests to identify the time intervals when the pregnant and non-pregnant groups of women are significantly different in terms of Lactobacillus species. We apply the same techniques to select the best 50 genes out of 2426 sparse gene expression data. The classification based on our selected genes achieves 100% prediction accuracy. Furthermore, the first four principal components based on the selected genes can explain as high as 83 % of the model variability. [ABSTRACT FROM AUTHOR]

DNA sequence variants (single nucleotide polymorphisms or variants, SNPs/SNVs; copy number variants, CNVs) associated to neurodevelopmental disorders (NDD) and traits often map on putative transcriptional regulatory elements, including, in particular, enhancers. However, the genes controlled by these enhancers remain poorly defined. Traditionally, the activity of a given enhancer, and the effect of its possible alteration associated to the sequence variants, has been thought to influence the nearest gene promoter. However, the obtainment of genome-wide long-range interaction maps in neural cells chromatin challenged this view, showing that a given enhancer is very frequently not connected to the nearest promoter, but to a more distant one, skipping genes in between. In this Perspective, we review some recent papers, who generated long-range interaction maps (by HiC, RNApolII ChIA-PET, Capture-HiC, or PLACseq), and overlapped the identified long-range interacting DNA segments with DNA sequence variants associated to NDD (such as schizophrenia, bipolar disorder and autism) and traits (intelligence). This strategy allowed to attribute the function of enhancers, hosting the NDD-related sequence variants, to a connected gene promoter lying far away on the linear chromosome map. Some of these enhancer-connected genes had indeed been already identified as contributive to the diseases, by the identification of mutations within the gene's protein-coding regions (exons), validating the approach. Significantly, however, the connected genes also include many genes that were not previously found mutated in their exons, pointing to novel candidate contributors to NDD and traits. Thus, long-range interaction maps, in combination with DNA variants detected in association with NDD, can be used as "pointers" to identify novel candidate disease-relevant genes. Functional manipulation of the long-range interaction network involving enhancers and promoters by CRISPR-Cas9-based approaches is beginning to probe for the functional significance of the identified interactions, and the enhancers and the genes involved, improving our understanding of neural development and its pathology. [ABSTRACT FROM AUTHOR]

Simple Summary: Papillary thyroid carcinoma is still the most common endocrine tumor, most of which can be diagnosed by pathological results. However, there is still a small number of cases that are difficult to judge malignancy. In this study, we performed an integrative analysis of DNA methylation and RNA array from our cohort for potential papillary thyroid cancer-specific indicators. SERINC2, one of the differentially methylated and expressed genes, was first identified as a potential tumor-driven indicator in papillary thyroid carcinoma. We confirmed the influence of SERINC2 on proliferation and apoptosis in vitro after intervention or overexpression. Furthermore, we found tryptophan metabolism as a potential pathway targeted by SERINC2 through the investigation of data from the Cancer Dependency Map. In conclusion, our results demonstrate the whole-genome DNA methylation and gene expression profiles of papillary thyroid carcinoma, identify a new tumor-driven indicator, and provide a novel insight into the etiology of papillary thyroid cancer. Most papillary thyroid carcinomas (PTCs) can be diagnosed preoperatively by routine evaluation, such as thyroid ultrasonography and fine-needle aspiration biopsy. Nevertheless, understanding how to differentiate indolent thyroid tumors from aggressive thyroid cancers remains a challenge, which may cause overtreatment. This study aimed to identify papillary thyroid cancer-specific indicators with whole-genome DNA methylation and gene expression profiles utilizing Infinium Methylation EPIC BeadChip (850k) and RNA arrays. In this paper, we report SERINC2 as a potential tumor-driven indicator in PTC. The up-regulated expression levels of SERINC2 were verified in PTC cell lines via qPCR. Then, cell counting kit 8 (CCK-8), wound healing, and flow cytometric assays were performed to confirm the influence of SERINC2 on proliferation and apoptosis in PTC cell lines after intervention or overexpression. Moreover, the investigation of data from the Cancer Dependency Map (DepMap) provided a potential pathway targeted by SERINC2. The activation of the tryptophan metabolic pathway may reduce the dependency of SERINC2 in thyroid cancers. In conclusion, our results demonstrate the whole-genome DNA methylation and gene expression profiles of papillary thyroid carcinoma, identify SERINC2 as a potential tumor-driven biomarker, and preliminarily verify its function in PTC. [ABSTRACT FROM AUTHOR]

Single-cell Assay for Transposase-Accessible Chromatin using sequencing (scATAC-seq) is rapidly becoming a powerful technology for assessing the epigenetic landscape of thousands of cells. However, the sparsity of the resulting data poses significant challenges to their interpretability and informativeness. Different computational methods are available, proposing ways to generate significant features from accessibility data and process them to obtain meaningful results. Foremost among them is the peak calling, which interprets the raw scATAC-seq data generating the peaks as features. However, scATAC-seq data are not trivially comparable with single-cell RNA sequencing (scRNA-seq) data, an increasingly pressing challenge since the necessity of multimodal experiments integration. For this reason, this study wants to improve the concept of the Gene Activity Matrix (GAM), which links the accessibility data to the genes, by proposing an improved version of the Genomic-Annotated Gene Activity Matrix (GAGAM) concept. Specifically, this paper presents GAGAM v1.2, a new and better version of GAGAM v1.0. GAGAM aims to label the peaks and link them to the genes through functional annotation of the whole genome. Using genes as features in scATAC-seq datasets makes different datasets comparable and allows linking gene accessibility and expression. This link is crucial for gene regulation understanding and fundamental for the increasing impact of multi-omics data. Results confirm that our method performs better than the previous GAMs and shows a preliminary comparison with scRNA-seq data. [ABSTRACT FROM AUTHOR]