Search Results (2,953)

Exserohilum spike blight, caused by Exserohilum rostratum, is an emerging constraint in wheat production, and improving host resistance is a sustainable strategy because the disease is governed largely by quantitative, environment-responsive loci rather than single major genes. Identifying genomic regions and biological pathways underlying quantitative resistance is therefore essential for developing durable resistant varieties. In this study, the Wheat Association Mapping Initiative spring wheat panel (n = 289) was evaluated across two contrasting Indian agroclimatic zones over two seasons. Resistance was quantified using two traits: incubation period (IP) and area under the disease progress curve (AUDPC). Significant genotype, environment, and genotype × environment interaction effects were observed for both traits (p < 0.001). IP and AUDPC were weakly correlated (r = −0.18 to 0.16), indicating that these traits represent partially distinct resistance components. Genome-wide association mapping identified 25 marker–trait associations, 13 for AUDPC and 12 for IP, with most associations showing environment dependence. Putative candidate genes highlighted defense-relevant loci, including an LRR receptor-like kinase and a WRKY transcription factor for IP, and an RGA2-like resistance gene and PHLOEM UNLOADING MODULATOR-like gene for AUDPC. These findings provide the first GWAS-based framework for E. rostratum resistance in wheat, prioritizing loci for validation and marker deployment. Full article

The bacterial proteome is a highly dynamic landscape rather than simply a static reflection of the genome. Recent research has revealed that proteome complexity extends far beyond canonical gene annotation, with N-terminal (Nt-)proteoforms emerging as an important underexplored additional regulatory layer. These molecular variants originate from a single genetic locus through alternative translation initiation at internal or external in-frame start sites, thereby generating N-terminal heterogeneity that can influence protein stability, subcellular localization, interaction networks, and the stoichiometric assembly of multiprotein complexes. While recent advances in riboproteogenomics, N-terminomics, and computational annotation strategies have enabled proteoform mapping at single-amino-acid resolution, rapid high-throughput discovery currently outpaces downstream functional characterization. This review discusses the technological advances driving Nt-proteoform discovery, including emerging ribosome profiling and proteogenomic approaches, and further evaluates strategies for the functional characterization of Nt-proteoforms. Particular emphasis is placed on the transition from conventional plasmid-based heterologous expression systems towards precise genome-engineering approaches that enable selective manipulation of alternative translation initiation events within their native genomic context. Such targeted strategies are essential to bridge the gap between Nt-proteoform identification and functional understanding, ultimately uncovering how individual bacterial genomic loci can encode proteoforms with distinct and potentially divergent functional roles in bacterial physiology and pathogenesis. Ultimately, we hypothesize that alternative translation initiation represents a biologically meaningful post-transcriptional regulatory mechanism that contributes to maximizing prokaryotic coding capacity without expanding genome size, rather than merely constituting stochastic translational noise. Full article

Casimicrobium huifangae SJ-1 is one of the 28 core microbial groups in the activated sludge of municipal wastewater treatment plants. It exhibits strong environmental adaptability and interactions with other microbes. To develop a genetic manipulation system for this strain, we tested several broad-host-range plasmids, and pBBR1MCS-2 was successfully transformed into strain SJ-1. However, only the plasmid extracted from the transformant could be retransformed into strain SJ-1, suggesting strong host defense systems. We investigated the genome-wide DNA methylation and obtained a DNA methylation map and nine methylation-targeting motifs from C. huifangae. A modified pBBR1MCS-2 lacking all targeting motifs achieved transformation efficiency comparable to that of the host-derived plasmid, implicating the restriction modification (R-M) barrier of C. huifangae. REBASE annotation revealed nine R-M systems in the genome, including two of Type I, six of Type II, and one of Type III. Quantitative PCR showed that the restriction endonuclease component of the Type I RM-C system was transcriptionally upregulated in the transformant harboring pBBR1MCS-2. The subunits responsible for the methyltransferase and endonuclease functions of RM-C were expressed in Escherichia coli, purified, and characterized. The targeting motif of RM-C was implicated as 5′-GAGNNNNNNNTGCT-3′ based on in vitro cleavage assays and SMRT methylation calls. These findings reveal the DNA methylation characteristics of C. huifangae SJ-1 and outline the possible methylation-based defense architecture, providing a reference for future genetic manipulation. Full article

Background/Objectives: Aging is characterized by genomic instability, reduced biological diversity, and clonal dominance across multiple biological systems. While short tandem repeats (STRs) are traditionally considered neutral genetic markers, emerging evidence raises the possibility that variation in these regions may be examined in relation to broader genomic processes associated with aging. Methods: STR profiles from 400 individuals were analyzed, including 275 young participants aged 21–43 years and 125 elderly participants aged ≥65 years. Genetic diversity was assessed using parameters such as expected heterozygosity (He), individual heterozygosity ratio, and allelic dominance. Additionally, STR loci were mapped to the hg38 reference genome (±100 kb), and nearby genes were annotated with KEGG pathway information to provide exploratory biological context for the investigated loci. Results: No statistically significant differences were observed in heterozygosity or allelic dominance between the young and elderly groups. However, a slight trend toward decreased heterozygosity and increased allelic dominance was noted in the elderly population. Genomic mapping indicated that some STR loci are located in proximity to genes annotated in aging-related pathways; however, this finding is based on genomic proximity and should be interpreted as exploratory. Conclusions: The primary analyses did not demonstrate statistically significant differences in STR-based genetic diversity between the young and elderly groups. The observed trends and genomic proximity findings should therefore be considered exploratory and hypothesis-generating. Validation in larger, independent prospective cohorts and integration with functional genomic data are required before any biological significance can be inferred. Full article

Plant diterpenoids are a diverse class of natural products with important ecological roles and wide applications in the pharmaceutical, agricultural, food additive, and chemical industries. Biosynthesis represents a primary strategy for accessing these valuable compounds. However, the identification of downstream tailoring enzymes (hereafter referred to as tailoring enzymes) involved in diterpenoid biosynthetic pathways remains a major bottleneck, particularly in non-model plant species with limited genomic resources. This review summarizes current strategies for discovering plant diterpenoid biosynthetic pathways and recent advances in elucidating their metabolic routes. We further highlight the lineage-biased distribution of diterpene scaffolds across plant taxa. We propose that scaffold enrichment in specific evolutionary lineages, when integrated with enzyme family expansion and functional divergence, may provide a complementary framework for prioritizing candidate tailoring enzymes. Importantly, scaffold enrichment alone cannot establish enzyme function or evolutionary causality; rather, it provides a complementary layer of evidence that can guide future experimental investigation. Future perspectives include predictive substrate–enzyme mapping, computational and generative design of cytochrome P450 enzymes, and the integration of enzyme discovery, structural modeling, and heterologous chassis engineering. Full article

Autophagy–lysosome dysfunction accompanies dermal fibroblast ageing, yet whether remodelling is transcriptional or post-transcriptional in primary human cells remains unresolved. We reanalysed the Genetic and Epigenetic Signatures of Translational Ageing Laboratory Testing(GESTALT) paired RNA sequencing (RNA-seq) and tandem mass tag (TMT) proteome from 82 donors (aged 22–89) using Data Integration Analysis for Biomarker discovery using Latent cOmponents (DIABLO) for supervised multi-omics integration, weighted gene co-expression network analysis (WGCNA), external Genotype-Tissue Expression(GTEx) transcriptomic comparison, network medicine proximity mapping and CDOCKER molecular docking. Three analyses converged on the autophagy–lysosome axis: Kyoto Encyclopaedia of Genes and Genomes (KEGG) Lysosome ranked first in discordant-quadrant analysis; gene set enrichment analysis (GSEA) identified vacuole organisation and macroautophagy as the top age-upregulated Gene Ontology (GO) terms; and WGCNA recovered KEGG Lysosome in the brown module. Module regression localised most proteomic age signals to the lysosomal degradative-capacity module, whereas the proteasome was unaffected. McNemar testing and GTEx comparison supported a protein-side, post-transcriptional origin. TCIRG1, CTSA and ATP6V0D1 were recurrent hubs. Network proximity computationally prioritised hydroxytyrosol as a lysosomal-degradative-capacity-preferential candidate, and CDOCKER on cathepsin A linked its advantage over tyrosol to an ortho-hydroxyl group forming additional hydrogen bonds. These results support protein-layer-dominant autophagy–lysosome remodelling as a feature of dermal fibroblast ageing and suggest a cell-type-resolved computational route from ageing proteomics to testable dietary candidates. Full article

Common gene mapping approaches mainly include QTL-mapping, BSA-seq (QTL-seq) and GWAS. BSA-seq is designed to facilitate the mapping of quantitative trait loci (QTL) in a cost-effective and high-efficiency manner. In order to accommodate the diverse species-specific traits and population genetic architectures, researchers have developed a series of tailored BSA methodologies. In this study, using six wild rices (Oryza rufipogon) as donors and the elite cultivated rice Youzhan 8 (YZ8) as the recipient, we constructed a BC₄F₈ population through hybridization and backcrossing. These six wild rice introgression lines together constitute a nested association mapping (NAM) population. Upon genotyping 1819 lines of the NAM population for the Sd1 gene, we found that among lines harboring the 383 bp deletion, 98.5–99.3% exhibited a low plant height (LP) phenotype, whereas 0.7–1.5% showed a high plant height (HP) phenotype. Based on this phenotypic segregation, we selected a total of 20 HP lines and 20 LP lines from six BC₄F₈ populations to form the H-bulk and L-bulk, respectively. Using BSA-seq, we identified a total of 33 significantly associated candidate intervals. One candidate interval located on chromosome 1 contains D18, a previously reported gene that regulates plant height. Furthermore, we preliminarily identified two major candidate genomic regions on chromosome 8 (4.60–5.76 Mb and 7.29–7.33 Mb). Integrating RNA-seq data, CAFRI-Rice online functional prediction and RT-qPCR validation, two key candidate genes, LOC_Os08g09900 and LOC_Os08g09000, were selected for subsequent functional characterization. The results of this study indicate that the NAM-BSA technology has great potential to detect QTL associated with complex traits, which can provide a novel technical strategy for the genetic dissection of complex traits in rice. Full article

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) evolution has been marked by the rapid accumulation of mutations, among which cytosine-to-uracil (C-to-U) transitions represent a major proportion of observed genomic changes. These mutations have been proposed to result from the activity of host APOBEC3 cytidine deaminases, innate immune enzymes capable of editing viral RNA. However, the molecular mechanisms underlying APOBEC3 involvement in SARS-CoV-2 biology remain poorly understood. Here, we systematically investigated physical interactions between APOBEC family members and the SARS-CoV-2 proteins using a Gaussia princeps protein complementation assay. Screening of APOBEC family proteins against the viral proteome identified specific interactions between APOBEC3G (A3G) and APOBEC3H (A3H) with the viral nucleocapsid (N) protein. These interactions were validated by co-immunoprecipitation and were found to be conserved across nucleocapsid proteins from all seven human coronaviruses, suggesting conserved structural determinants. Mechanistic analyses revealed that the RNA-binding and oligomerization capacities of A3G and A3H are key for their interaction with the SARS-CoV-2 nucleocapsid. Mapping experiments further showed that the C-terminal domain of N constitutes the minimal interacting region, with stronger binding observed in larger constructs encompassing adjacent regions, indicating cooperative stabilization. Further work will be needed to determine whether A3G and/or A3H can restrict viral replication and whether their interaction with the nucleocapsid allows them to access and mutate the viral genome. Full article

Early detection of autism spectrum disorder (ASD) in young children is essential for timely referral, developmental monitoring, and access to early intervention. However, conventional screening and diagnostic pathways often depend on parent-report instruments, episodic clinical observation, and specialist-administered assessments, which may delay identification during the first years of life. This scoping review maps the methodological landscape of early ASD detection from traditional clinical screening to multimodal artificial intelligence (AI). A structured literature search was conducted across major biomedical, psychological, and engineering databases for studies published between January 2010 and May 2026. After screening and eligibility assessment, 65 evidence sources were included in the qualitative synthesis, with additional methodological guidelines used to support reporting and appraisal. The reviewed evidence shows that early ASD detection is increasingly shifting from single-session clinical assessment toward multidimensional risk characterization. Clinical and behavioral screening tools remain the foundation of early identification, while eye tracking, video-based motor analysis, acoustic and vocal biomarkers, electroencephalography (EEG), functional near-infrared spectroscopy (fNIRS), and molecular or genomic indicators provide complementary information across different developmental windows. AI-based methods, including machine learning, deep learning, Transformer architectures, multimodal fusion strategies, and foundation-model-based representation learning, may improve the objective quantification of gaze, movement, vocalization, neural activity, and biological risk. Nevertheless, most AI-assisted systems remain limited by small and heterogeneous datasets, insufficient external validation, population bias, privacy concerns, computational burden, and limited interpretability. This review argues that future early ASD detection systems should be developed as clinician-supervised decision-support tools rather than autonomous diagnostic instruments. Clinically meaningful progress will require robust external validation, privacy-preserving deployment, age-appropriate risk stratification, and intrinsically interpretable architectures that align model outputs with developmental and clinical knowledge. Full article

Background: The directional relationship between epigenetic age acceleration (EAA) and musculoskeletal disease remains unresolved. This study integrated bidirectional Mendelian randomization (MR) with multi-layer genomic evidence to evaluate directionality, shared genetic architecture, and robustness to instrument definition. Methods: Four EAA clocks (IEAA, PhenoAA, HannumAA, and GrimAA) and ten musculoskeletal phenotypes were analyzed in a 10 × 4 bidirectional two-sample MR design. EAA instruments underwent GRCh37 functional annotation, genome-wide-significant external-association screening for the index variants and European linkage-disequilibrium proxies, pair-specific Steiger filtering, and conservative Set A/B/C sensitivity analyses. The juvenile-arthritis reverse models underwent instrument-flow reconstruction, strength assessment, liability-scale directionality testing, and minimum-detectable-effect analysis. Additional analyses comprised LD score regression (LDSC), PLACO+ cross-trait locus mapping, Bayesian colocalization, multivariable MR (MVMR) with exact-SNP matched univariable comparators, and integrated evidence synthesis. Results: Forward MR yielded two nominal HannumAA associations. The inverse HannumAA–spondyloarthritis estimate remained directionally consistent across the original, Steiger-filtered, and conservative external-association-filtered sets, whereas the HannumAA–pain-in-thoracic-spine estimate lost nominal significance in the conservative set; no forward result survived correction across 40 tests. GrimAA forward estimates were sensitive to use of the fallback instrument threshold. Reverse MR identified ten nominal associations. For juvenile arthritis, three harmonized instruments had F statistics of 51.25–102.35; liability-scale Steiger comparisons supported the tested direction under all 16 outcome-by-prevalence combinations, although the 788-case discovery GWAS and possible winner’s curse remained important limitations. LDSC identified FDR-significant positive genetic correlations of GrimAA with hip osteoarthritis (r_g = 0.267, p = 8.49 × 10⁻⁵, q = 0.0019) and knee osteoarthritis (r_g = 0.269, p = 9.52 × 10⁻⁵, q = 0.0019). PLACO+ identified 738 genome-wide-significant cross-trait variants and 65 independent loci; six of 37 evaluable loci showed strong colocalization. Of 96 MVMR models, 43 had primary-exposure conditional F ≥ 10, and 32 also had candidate-trait conditional F ≥ 10. After exact-SNP matching, the 43 primary-strength models were operationally classified as 35 partially attenuated and eight independent-signal models, with no fully attenuated model; no adjusted association survived multiplicity correction. Conclusions: The results support a prioritized genomic map with substantial instrument- and model-specific uncertainty. Disease-to-clock signals were richer than clock-to-disease signals, GrimAA shared polygenic architecture with osteoarthritis, and selected loci showed strong shared-variant evidence, while the MR and MVMR findings remained unsuitable for definitive causal or mediation claims. Full article

Climate change and the increasing frequency of extreme temperatures pose severe threats to global agricultural productivity, making the breeding of water-efficient crops a critical imperative. Originating from arid regions, foxtail millet serves as an ideal C4 model crop for elucidating plant adaptations to water deficits. Unlike previous reviews that often isolate genomic features from physiological responses, this review constructs an explicit conceptual framework integrating cross-scale defense mechanisms—mechanistically linking molecular signal transduction and post-transcriptional regulation to cellular homeostasis and field-scale yield stability. We first detail the developmental stage-specific physiological penalties of water stress and dissect proactive water-conservation strategies, including stomatal anatomical optimization, root-carbon reallocation, and dynamic rhizosphere remodeling. At the genetic level, we highlight the application of dynamic quantitative trait loci (QTL) mapping, which transcends the static limitations of conventional QTLs by capturing the spatiotemporal evolution of drought-tolerance traits across distinct developmental nodes. To bridge the gap between intrinsic genetic potential and field application, we spotlight the emerging integration of machine learning-assisted breeding and genomic prediction for the efficient evaluation of superior germplasms. Across this framework, several persistent gaps emerge: most drought-responsive genes identified in foxtail millet remain at the level of expression association without functional validation; dynamic QTL analysis remains underutilized relative to its capacity to resolve reproductive-stage drought tolerance; and ML-based genomic prediction, though demonstrated in this species, has not been integrated into operational breeding. Closing these gaps will require connecting high-throughput field phenotyping to genomic selection and deploying functionally validated editing targets in genetic backgrounds relevant to dryland production. Full article

Cathetus yuanjiangensis Huan C. Wang, Feng Yang et Chao Chen (Phyllantheae, Phyllanthaceae), a new species from the dry-hot valleys of Southwest China, is described and illustrated herein. Morphologically, the new species can be easily distinguished from its congeners by the following combination of characters: leaves 1.5–4.5 cm long, 1–2 cm wide; staminate flowers sepals spreading 1.5–2.0 mm long; filaments connate into a 2–3 mm long column; styles 3, ca. 1.6 mm long, connate into a ca. 0.5 mm long column at base; stigmas spreading, slender, oblong, each bifid to 1/2, the lobes linear. Phylogenetic analyses based on two nuclear (ITS and PHYC) and three chloroplast (matK, accD-psaI and trnS-trnG) DNA makers recover C. yuanjiangensis as the sister clade to C. fasciculate among the sampled taxa. Detailed morphological descriptions, photographs, pollen morphology, and complete plastid genome characteristics of the new species are provided, along with a distribution map and a preliminary conservation assessment. Additionally, we propose a new combination, Cathetus beillei (Hutch.) Huan C. Wang et Feng Yang, based on the basionym Phyllanthus beillei Hutch., which was originally published in Flora of Tropical Africa. An updated identification key for all recognized species of C. subgen. Cathetus is provided. Full article

Single nucleotide polymorphisms (SNPs) are widely used for genetic diversity analysis, linkage mapping, genome-wide association studies (GWAS), and molecular marker development in crop plants. Genotyping-by-sequencing (GBS) enables cost-effective SNP discovery; however, achieving sufficient marker density in polyploid crops remains challenging because of complex genome structures, high sequence similarity among homologous chromosomes, and repetitive genomic regions. In this study, we optimized a GBS-based bioinformatics pipeline for polyploid kiwifruit (Actinidia spp.) by evaluating restriction enzyme combinations through in silico digestion analysis and comparing the SNP detection efficiency of three variant-calling tools, namely freebayes, bcftools, and Genome Analysis Tool Kit (GATK). The methylation-sensitive ApeKI/TfiI combination generated the highest proportion of DNA fragments within the target size range (200–500 bp) in the kiwifruit reference genome cv. Hongyang (A. chinensis). Using GATK, 828,257 SNPs were identified, approximately 22-fold higher than those detected using freebayes and bcftools, with a comparable transition/transversion (Ts/Tv) ratio. GATK also identified substantially higher absolute numbers of SNPs in genic regions, while the proportion of genic-region SNPs was similar across all three tools. Notably, only the GATK-derived SNP dataset exceeded the estimated marker density discussed in this study for high-density genomic coverage of the kiwifruit genome. These results demonstrate that the combination of methylation-sensitive restriction enzymes and GATK-based variant calling generated a high-density SNP dataset for mixed-ploidy kiwifruit germplasm. Because independent validation of SNP accuracy was beyond the scope of this study, the observed differences should be interpreted as differences in SNP discovery rather than comparative variant-calling accuracy. Full article

Increasing evidence shows that epistasis, defined as interactive effects between genetic loci, may contribute to the missing heritability of cancer. However, systematic genome-wide epistasis identification in cancer remains challenging. Here, by leveraging genotype and clinical data from 380,983 samples in the UK Biobank, we identified 202,032 candidate epistatic single nucleotide polymorphism (epiSNP) pairs associated with cancer risk across 16 cancer types. Notably, multivariable Cox regression identified 123 epiSNP pairs with significant interaction effects on overall survival, suggesting that interaction-level genetic signals can provide prognostic information beyond individual SNP effects. Through functional analysis of the 202,032 candidate epiSNP pairs, we identified 7152 pairs supported by gene co-expression data and 12,326 pairs with protein–protein interaction (PPI) evidence. By mapping epiSNP pairs to corresponding gene pairs and then linking these gene pairs to drug–target databases, we identified 1040 epistatic gene pairs with FDA-approved drug–target records. Additionally, through KM survival analysis of the candidate epiSNP pairs, we detected 7068 pairs significantly associated with patient overall survival. Finally, we constructed an open-access database, EpiSNPdb, to facilitate cancer epistasis research. Full article

The high commercial value and the increasing demand for caviar make it susceptible to illegal trade and fraudulent activities, while mislabelling can occur both deliberately and unintentionally. Therefore, reliable methods are urgently needed to distinguish even closely related sturgeon species for the authentication of declared species in caviar products. In this study, we explore the effectiveness of ONT sequencing combined with nanopore adaptive sampling (NAS) to recover mitochondrial genomes from genomic DNA extracted from two caviar samples. NAS yielded similar percentages of mitochondrial reads as sequencing experiments without using the NAS option. However, NAS substantially increased the percentage of bases that could be mapped against a mitochondrial reference genome, demonstrating its effectiveness in enriching ONT sequencing data for mitochondrial sequences. The percentage of mapped mitochondrial reads varied between two samples in our sequencing experiments, ranging between 2.37% and 10.46%, which is exceptionally high compared to previous studies focusing on the recovery of mitochondrial genomes from genomic DNA. This increase may be attributed to the extraction of genomic DNA from individual fish eggs. To determine the taxonomic identities of the two caviar samples, a phylogenetic analysis was performed that included all available acipenseriform mitochondrial genomes from GenBank, as well as the newly recovered mitochondrial genomes. During this process, four problematic mitochondrial genomes obtained from GenBank were identified, which were characterized by either suggestively low sequence quality, chimeric sequence information, or potential misidentification. This underscores the need for reviewing sequencing data before database submission to avoid negative impacts on research and DNA-based species authentication. Full article