Search Results (5,190)

The Evidential K-Nearest Neighbor (EK-NN) classifier has demonstrated robustness in handling incomplete and uncertain data; however, its application in high-dimensional big data for feature selection, such as genomic datasets with tens of thousands of gene features, remains underexplored. Our proposed Granular–Elastic Evidential K-Nearest Neighbor (GEK-NN) approach addresses this gap. In the context of big data, GEK-NN integrates an Elastic Net within the Genetic Algorithm’s fitness function to efficiently sift through vast amounts of data, identifying relevant feature subsets. This process mimics human cognitive behavior of filtering and refining information, similar to concepts in cognitive computing. A granularity metric is further employed to optimize subset size, maximizing its impact. GEK-NN consists of two crucial phases. Initially, an Elastic Net-based feature evaluation is conducted to pinpoint relevant features from the high-dimensional data. Subsequently, granularity-based optimization refines the subset size, adapting to the complexity of big data. Before applying to genomic big data, experiments on UCI datasets demonstrated the feasibility and effectiveness of GEK-NN. By using an Evidence Theory framework, GEK-NN overcomes feature-selection challenges in both low-dimensional UCI datasets and high-dimensional genomic big data, significantly enhancing pattern recognition and classification accuracy. Comparative analyses with existing EK-NN feature-selection methods, using both UCI and high-dimensional gene datasets, underscore GEK-NN’s superiority in handling big data for feature selection and classification. These results indicate that GEK-NN not only enriches EK-NN applications but also offers a cognitive-inspired solution for complex gene data analysis, effectively tackling high-dimensional feature-selection challenges in the realm of big data. Full article

Background/Objectives: Enterococci, particularly Enterococcus faecalis and Enterococcus faecium, are Gram-positive cocci that can cause severe infections in hospitalized patients. The rise of vancomycin-resistant enterococci (VRE) and vancomycin-variable enterococci (VVE) poses significant challenges in healthcare settings due to their resistance to multiple antibiotics. Methods: We conducted a point prevalence survey (PPS) to assess the prevalence of VRE and VVE colonization in hospitalized patients. Rectal swabs were collected from 160 patients and analyzed using molecular assays (MAs) and culture. Whole-genome sequencing (WGS) and core-genome multilocus sequence typing (cgMLST) were performed to identify the genetic diversity. Results: Of the 160 rectal swabs collected, 54 (33.7%) tested positive for the vanA and/or vanB genes. Culture-based methods identified 47 positive samples (29.3%); of these, 44 isolates were identified as E. faecium and 3 as E. faecalis. Based on the resistance profiles, 35 isolates (74.5%) were classified as VRE, while 12 (25.5%) were classified as VVE. WGS and cgMLST analyses identified seven clusters of E. faecium, with sequence type (ST) 80 being the most prevalent. Various resistance genes and virulence factors were identified, and this study also highlighted intra- and inter-ward transmission of VRE strains. Conclusions: Our findings underscore the potential for virulence and resistance of both the VRE and VVE strains, and they highlight the importance of effective infection control measures to prevent their spread. VVE in particular should be carefully monitored as they often escape detection. Integrating molecular data with clinical information will hopefully enhance our ability to predict and prevent future VRE infections. Full article

Background: More than 1500 genes are associated with developmental delay and intellectual disability, with variants in many of these genes contributing to a shared phenotype. The discovery of variants of uncertain significance (VUS) found in these genes during genetic testing can lead to ambiguity and further delay in diagnosis and medical management. Phenotyping, additional genetic testing, and functional studies can all add valuable information to help reclassify these variants. Here we demonstrate the clinical utility of epigenetic signatures in prioritizing variants of uncertain significance in genes associated with developmental delay (DD) and intellectual disability (ID). Methods: Genome sequencing was performed in a male with developmental delay. He was found to have VUSs in both PHF6 and DDB1 genes, linked with Börjeson–Forssman–Lehmann syndrome (BFLS) and White–Kernohan syndrome (WHIKERS), respectively. These two disorders share a similar phenotype but have distinct inheritance patterns and molecular pathogenic mechanisms. DNA methylation profiling (DNAm) of whole blood was performed using the clinically validated EpiSign assay. Results: The proband’s methylation profile demonstrated a strong correlation with the BFLS methylation signature, supporting the PHF6 variant as a likely cause of his neurodevelopmental disorder. Conclusions: Epigenetic testing for disorders with distinct methylation patterns can provide diagnostic utility when a patient presents with variants of uncertain significance in genes associated with developmental delay. Epigenetic signatures can also guide genetic counselling and family planning. Full article

Background: The Mediterranean-DASH Intervention for Neurodegenerative Delay (MIND) was a 3-year, multicenter, randomized controlled trial to test the effects of the MIND diet on cognitive decline in 604 individuals at risk for Alzheimer’s dementia. Here, we describe the genotyping, imputation, and quality control (QC) procedures for the genetic data of trial participants. Methods: DNA was extracted from either whole blood or serum, and genotyping was performed using the Infinium Global Diversity Array. Established sample and SNP QC procedures were applied to the genotyping data, followed by imputation using the 1000 Genomes Phase 3 v5 reference panel. Results: Significant study-site, specimen type, and batch effects were observed. A total of 494 individuals of inferred European ancestry and 58 individuals of inferred African ancestry were included in the final imputed dataset. Evaluation of the imputed APOE genotype against gold-standard sequencing data showed high concordance (98.2%). We replicated several known genetic associations identified from previous genome-wide association studies, including SNPs previously linked to adiponectin (rs16861209, p = 1.5 × 10⁻⁵), alpha-linolenic acid (rs174547, p = 1.3 × 10⁻⁷), and alpha-tocopherol (rs964184, p = 0.003). Conclusions: This dataset represents the first genetic resource derived from a dietary intervention trial focused on cognitive outcomes. It enables investigation of genetic contributions to variability in cognitive response to the MIND diet and supports integrative analyses with other omics data types to elucidate the biological mechanisms underlying cognitive decline. These efforts may ultimately inform precision nutrition strategies to promote cognitive health. Full article

It is believed that caspases may play a significant role in the development of cancer, and the expression levels of genes encoding these proteins may influence the prognosis and clinical course of cancer. Taking into account the information presented, we examined the expression profiles of 11 genes from the caspase family in patients diagnosed with triple-negative breast cancer (TNBC). We qualified 29 patients with TNBC. A fragment of the tumor and a fragment of normal tissue surrounding the tumor were collected from each patient. Then, RNA was isolated, and the reverse transcription process was performed. The expression levels of caspase family genes were determined using the real-time PCR method. The obtained data were correlated with clinical data and compared with data from the Cancer Genome Atlas database using the Breast Cancer Gene Expression Miner v4.8 and Ualcan. Based on the results of the conducted research, it can be assumed that the levels of expression of caspase family genes may be correlated with the clinical course of cancer in patients with TNBC, and further research may indicate that profiling the expression levels of these genes may be used in selecting personalized treatment methods. Full article

Xyloglucan endotransglucosylase/hydrolases (XTHs) are a class of cell wall-associated enzymes involved in the construction and remodeling of cellulose/xyloglucan crosslinks. However, knowledge of this gene family in the model monocot Brachypodium distachyon is limited. A total of 29 BdXTH genes were identified from the whole genome, and these were further divided into three subgroups (Group I/II, Group III, and the Ancestral Group) through evolutionary analysis. Gene structure and protein motif analyses indicate that closely clustered BdXTH genes are relatively conserved within each group. A highly conserved amino acid domain (DEIDFEFLG) responsible for catalytic activity was identified in all BdXTH proteins. We detected three pairs of segmentally duplicated BdXTH genes and five groups of tandemly duplicated BdXTH genes, which played vital roles in the expansion of the BdXTH gene family. Cis-elements related to hormones, growth, and abiotic stress responses were identified in the promoters of each BdXTH gene, and when roots were treated with two abiotic stresses (salinity and drought) and four plant hormones (IAA, auxin; GA3, gibberellin; ABA, abscisic acid; and BR, brassinolide), the expression levels of many BdXTH genes changed significantly. Transcriptional analyses of the BdXTH genes in 38 tissue samples from the publicly available RNA-seq data indicated that most BdXTH genes have distinct expression patterns in different tissues and at different growth stages. Overexpressing the BdXTH27 gene in Brachypodium led to reduced root length in transgenic plants, which exhibited higher cellulose levels but lower hemicellulose levels compared to wild-type plants. Our results provide valuable information for further elucidation of the biological functions of BdXTH genes in the model grass B. distachyon. Full article

Medicago falcata is one of the most important perennial forage legumes in the Medicago genus. In this study, we reported the complete chloroplast genome of two M. falcata ecotypes grown in different regions, and compared them with those of Medicago truncatula and Medicago sativa. We found that the M. falcata chloroplast genome lacks a typical quadripartite structure, containing 78 protein-coding genes, 30 tRNA genes, and four ribosomal RNA genes. They shared high conservation in size, genome structure, gene order, gene number and GC content with those of M. truncatula and M. sativa. High nucleotide diversity occurred in the coding gene regions of rps16, rps3, and ycf4 genes. Meanwhile, mononucleotide repeats are the most abundant repeat type, followed by the di-, tri-, tetra-, and pentanucleotides, and forward repeats were more abundant than reverse and palindrome repeats for all these three Medicago species. Phylogenetic analyses using both coding sequences and complete chloroplast genomes revealed that M. falcata shares the closest phylogenetic relationship with M. hybrida and M. sativa. This study provided valuable information for further studies on the genetic relationship of the Medicago genus. Full article

Legumes are vital sources of protein, dietary fibre and nutrients, making them crucial for global food security and sustainable agriculture. However, their widespread acceptance and consumption are often limited by undesirable sensory characteristics, such as “a beany flavour”, bitterness or variable textures. Addressing these challenges requires a comprehensive understanding of the complex molecular mechanisms governing appearance, aroma, taste, flavour, texture and palatability in legumes, aiming to enhance their sensory appeal. This review highlights the transformative power of multi-omics approaches in dissecting these intricate biological pathways and facilitating the targeted enhancement of legume sensory qualities. By integrating data from genomics, transcriptomics, proteomics and metabolomics, the genetic and biochemical networks that directly dictate sensory perception can be comprehensively unveiled. The insights gained from these integrated multi-omics studies are proving instrumental in developing strategies for sensory enhancement. They enable the identification of key biomarkers for desirable traits, facilitating more efficient marker-assisted selection (MAS) and genomic selection (GS) in breeding programs. Furthermore, a molecular understanding of sensory pathways opens avenues for precise gene editing (e.g., using CRISPR-Cas9) to modify specific genes, reduce off-flavour compounds or optimise texture. Beyond genetic improvements, multi-omics data also inform the optimisation of post-harvest handling and processing methods (e.g., germination and fermentation) to enhance desirable sensory profiles and mitigate undesirable ones. This holistic approach, spanning from the genetic blueprint to the final sensory experience, will accelerate the development of new legume cultivars and products with enhanced palatability, thereby fostering increased consumption and ultimately contributing to healthier diets and more resilient food systems worldwide. Full article

Background/Objectives: Hepatic cancers, including hepatocellular carcinoma (HCC) and cholangiocarcinoma (CCA), are major global health concerns due to rising incidence and limited therapeutic success. While traditional risk factors include chronic liver disease and environmental exposures, recent evidence underscores the significance of genetic alterations and gut microbiota in liver cancer development and progression. This review aims to integrate emerging knowledge on the interplay between host genomic changes and gut microbial dynamics in the pathogenesis and treatment of hepatic cancers. Methods: We conducted a comprehensive review of current literature on genetic and epigenetic drivers of HCC and CCA, focusing on commonly mutated genes such as TP53, CTNNB1, TERT, IDH1/2, and FGFR2. In parallel, we evaluated studies addressing the gut–liver axis, including the roles of dysbiosis, microbial metabolites, and immune modulation. Key clinical and preclinical findings were synthesized to explore how host–microbe interactions influence tumorigenesis and therapeutic response. Results: HCC and CCA exhibit distinct but overlapping genomic landscapes marked by recurrent mutations and epigenetic reprogramming. Alterations in the gut microbiota contribute to hepatic inflammation, genomic instability, and immune evasion, potentially enhancing oncogenic signaling pathways. Furthermore, microbiota composition appears to affect responses to immune checkpoint inhibitors. Emerging therapeutic strategies such as probiotics, fecal microbiota transplantation, and precision oncology based on mutational profiling demonstrate potential for personalized interventions. Conclusions: The integration of host genomics with microbial ecology provides a promising paradigm for advancing diagnostics and therapies in liver cancer. Targeting the gut–liver axis may complement genome-informed strategies to improve outcomes for patients with HCC and CCA. Full article

Prognostic markers such as overall survival (OS) and tertiary lymphoid structure (TLS) ratios, alongside diagnostic signatures like primary cancer-type classification, provide critical information for treatment selection, risk stratification, and longitudinal care planning across the oncology continuum. However, extracting these signals solely from sparse, high-dimensional multi-omics data remains a major challenge due to heterogeneity and frequent missingness in patient profiles. To address this challenge, we present SeNMo, a self-normalizing deep neural network trained on five heterogeneous omics layers—gene expression, DNA methylation, miRNA abundance, somatic mutations, and protein expression—along with the clinical variables, that learns a unified representation robust to missing modalities. Trained on more than 10,000 patient profiles across 32 tumor types from The Cancer Genome Atlas (TCGA), SeNMo provides a baseline that can be readily fine-tuned for diverse downstream tasks. On a held-out TCGA test set, the model achieved a concordance index of 0.758 for OS prediction, while external evaluation yielded 0.73 on the CPTAC lung squamous cell carcinoma cohort and 0.66 on an independent 108-patient Moffitt Cancer Center cohort. Furthermore, on Moffitt’s cohort, baseline SeNMo fine-tuned for TLS ratio prediction aligned with expert annotations (p < 0.05) and sharply separated high- versus low-TLS groups, reflecting distinct survival outcomes. Without altering the backbone, a single linear head classified primary cancer type with 99.8% accuracy across the 33 classes. By unifying diagnostic and prognostic predictions in a modality-robust architecture, SeNMo demonstrated strong performance across multiple clinically relevant tasks, including survival estimation, cancer classification, and TLS ratio prediction, highlighting its translational potential for multi-omics oncology applications. Full article

In late 2019, a new virus, SARS-CoV-2, emerged in Wuhan, China, causing COVID-19 and the subsequent global pandemic. As of 30 April 2023, more than 774 million cases of COVID-19 had been reported worldwide, including over 7.5 million in Mexico. Despite advances in vaccination, epidemic surges of COVID-19 continued to occur globally, highlighting the importance of sharing and disseminating the experiences gained during these first years to better understand the virus’s evolution and respond accordingly. For this reason, the National Council for Science and Technology (CONACYT) organized the meeting “Challenges and Opportunities for Genomic Surveillance of SARS-CoV-2 in Mexico” from 15 to 17 August 2022, to present the efforts and results accumulated over more than two years of the pandemic. In this meeting report, we summarize the key findings of each participant and provide their contact information. Full article

The morphological diversity of Moroccan honey bees (Apis mellifera) was investigated using geometric morphometrics to assess wing venation patterns among three populations representing three climatic zones: desert, semiarid, and Mediterranean. A total of 193 honey bee samples were analyzed and compared to historical reference samples from the Morphometric Bee Data Bank in Oberursel, representing the three subspecies: A. m. intermissa, A. m. sahariensis, and A. m. major. Principal component analysis and linear discriminant analysis revealed significant, yet overlapping morphological differences among the climatic groups. Spatial modeling showed a significant southwest–northeast clinal gradient in wing morphology. Almost all samples were assigned to the African evolutionary lineage, except one, suggesting a dominant African genetic background. Interestingly, all three populations showed greater morphological affinity to A. m. intermissa than to A. m. sahariensis, which could indicate introgression or limitations in the current reference dataset. These discrepancies highlight the necessity of revising subspecies boundaries using updated morphometric and genomic approaches. These findings improve our understanding of honey bee biodiversity in Morocco and provide valuable information for conservation and breeding programs. Full article

Porcine reproductive and respiratory syndrome virus remains one of the most economically significant pathogens in swine production, with PRRSV-2 being the dominant variant in the United States. While lineage classification has traditionally relied on ORF5 sequencing, recent studies suggest that this single-gene approach may overlook key evolutionary events such as recombination. In this study, we performed whole-genome sequencing and phylogenetic analysis of seven PRRSV-2 isolates collected in the U.S. between 2006 and 2024. Using reference-guided assembly, lineage assignment, and recombination detection with RDP5 and SIMplot, we identified discordant phylogenetic placements between ORF5 and whole genomes in four of the seven isolates. These discordances were explained by multiple recombination events affecting different genomic regions, particularly ORF2–ORF7. In contrast, three isolates showed phylogenetic concordance and no strong evidence of recombination. Our findings demonstrate that recombination plays a significant role in shaping PRRSV-2 evolution and highlight the limitations of ORF5-based lineage classification. Whole-genome surveillance is therefore essential to accurately track viral diversity, detect recombinant strains, and inform control strategies. This work underscores the need for a broader adoption of full-genome analysis in routine PRRSV surveillance and research. Full article

Aging in sexually reproducing organisms is shaped by the declining force of natural selection after reproduction begins. In Drosophila melanogaster, experimental evolution shows that altering the age of reproduction shifts the timing of aging. Using the Drosophila experimental evolution population (DEEP) resource, which includes long- and short- lived populations evolved under distinct reproductive schedules, we investigated how immune defense against Beauveria bassiana changes with age and evolved lifespan. We tested survival post-infection at multiple ages and examined genomic differentiation for immune-related genes. Both population types showed age-related declines in immune defense. Long-lived populations consistently exhibited age-specific defense when both long- and short-lived populations were tested. Genomic comparisons revealed thousands of differentiated loci, yet no enrichment for canonical immune genes or overlap with gene sets from studies of direct selection for immunity. These results suggest that enhanced immune defense can evolve alongside extended lifespan, likely via general physiological robustness rather than traditional immune pathways. A more detailed analysis may reveal that selection for lifespan favors tolerance-based mechanisms that reduce infection damage without triggering immune activation, in contrast to direct selection for resistance. Our findings demonstrate the utility of experimentally evolved populations for dissecting the genetic architecture of aging and immune defense to inform strategies to mitigate age-related costs associated with immune activation. Full article

During a prolonged domestication and environmental selection, Brassica rapa has formed diverse morphological types during a cultivation process of up to 8000 years, such as root-type turnips (Brassica rapa var. rapa), leaf-type Chinese cabbage (Brassica rapa var. pekinensis), oil-type rapeseed (Brassica rapa L.), and other rich types. China is one of the origins of Brassica rapa L., which is spread all over the east, west, south, and north of China. Studying its origin and evolution holds significant importance for unraveling the cultivation history of Chinese oilseed crops, intraspecific evolutionary relationships, and the utilization value of genetic resources. This article summarizes the cultivation history, evolution, classification research progress, and germplasm resource diversity of Brassica rapa var. oleifera in China. Combining karyotype analysis, genomic information, and wild relatives of Brassica rapa var. oleifera discovered on the Qinghai–Tibet Plateau, it is proposed that Brassica rapa var. oleifera has the characteristic of polycentric origin, and Gansu Province in China is one of the earliest regions for its cultivation. Brassica rapa var. oleifera, originating from the Mediterranean region, was diffused to the East Asian continent through two independent transmission paths (one via the Turkish Plateau and the other via Central Asia and Siberia). Analyzing the genetic diversity characteristics and evolutionary trajectories of these two transmission paths lays a foundation for clarifying the origin and evolutionary process of Brassica rapa var. oleifera and accelerating the breeding of Brassica rapa var. oleifera in China. Despite existing research on the origin of Brassica rapa L., the domestication process of this species remains unresolved. Future studies will employ whole-genome resequencing to address this fundamental question. Full article