Search Results (3,202)

Climate warming puts new selective pressures on natural populations, but there are few quantitative measurements of selection in natural populations over protracted time periods. Observations made at the beginning and end ofa 47-year cumulative increase of 2.7 °C in the mean September temperature in Northern Minnesota, USA, permit quantitative estimation of selection against a suite of alleles at a single locus determining the expressionof dark color forms in populations of the meadow spittlebug, Philaenus spumarius (L.) (Hemiptera: Cercopoidea: Aphrophoridae). Alternative methods of estimation of the selection coefficient s, a measure of the intensity of selection, produce values of s = 0.0125 and 0.0218, respectively, corresponding to a disadvantage of about one to two percent per year or, since P. spumarius is univoltine, per round of selection. The existence of a locus under selection presents an opportunity for molecular localization and characterization of the genetic locus determining color form. Philaenus spumarius is of particular interest in Europe, as it is the major local vector of the bacterial plant pathogen Xylella fastidiosa. Full article

Autoimmune diseases arise from complex interactions between genetic susceptibility, immune regulation, and tissue-specific inflammatory processes, yet most risk variants identified by genome-wide association studies occur in non-coding regions with poorly defined biological functions. This review addresses the challenge of interpreting non-coding regulatory variants in autoimmunity by synthesizing emerging analytical frameworks that integrate functional genomics, single-cell profiling, spatial transcriptomics, and multi-omics data. We describe stepwise strategies that refine statistical associations through regulatory annotation, immune cell–state resolution, and perturbational evidence, highlighting complementary approaches such as massively parallel reporter assays, transcriptome-wide association studies, and single-cell expression quantitative trait locus mapping. These methods demonstrate that many autoimmune risk variants exert context-dependent effects that emerge only in specific immune cell states, activation trajectories, or tissue microenvironments. Advances in spatial and chromatin-informed technologies further clarify how regulatory variation shapes immune circuits in diseases such as systemic lupus erythematosus and rheumatoid arthritis. Finally, we discuss how machine learning-enabled multi-omics integration supports molecular endotyping and therapeutic inference while emphasizing interpretability and reproducibility. Collectively, this review highlights a shift from static variant annotation toward dynamic, context-aware analytical frameworks that enable mechanism-informed interpretation of genetic risk in autoimmune disease. Full article

Cotton (Gossypium hirsutum) is globally cultivated for its high-quality fiber; yet, its seed, rich in oil and protein, offers untapped potential for various applications, including food, feed, and industry. With cottonseed oil gaining renewed attention as a valuable co-product, efforts to enhance oil content must contend with long-standing breeding priorities focused on lint yield and fiber quality. A central challenge lies in the complex and often antagonistic genetic relationships between oil accumulation and key agronomic traits. Notably, negative correlations between seed oil content and fiber yield, as well as the pleiotropic nature of several regulatory genes and Quantitative Trait Loci (QTLs), present significant barriers to dual-trait improvement. This review synthesizes current knowledge on the genetic and molecular interplay between cottonseed oil content and other agronomic traits. We examine the architecture of oil-related QTLs and pleiotropic loci, co-expression patterns of shared transcriptional regulators, and metabolic trade-offs influencing carbon allocation between seed and fiber. Recent advances in genomics, transcriptomics, and systems biology are explored as tools to disentangle these trait interactions. We highlight strategies such as multi-trait genomic selection, CRISPR-based uncoupling of antagonistic loci, and the use of wild and exotic germplasm to overcome linkage drag. By providing an integrative overview of the constraints and opportunities at the intersection of oil and agronomic trait improvement, this review lays the groundwork for the development of dual-purpose cotton ideotypes. We propose a conceptual framework for breeding programs to simultaneously enhance fiber yield and oil productivity in a sustainable and climate-resilient manner. Full article

Metabolic dysfunction-associated steatotic liver disease (MASLD) and its consequences represent a growing global health burden that urgently requires physiologically relevant in vitro models beyond conventional 2D culture systems. In this study, we report the successful establishment of 45 patient-derived liver organoid lines. These organoids were generated from healthy, steatotic and cirrhotic tissues collected from 207 liver surgeries at RWTH University Hospital Aachen, with an initiation success rate of 82%. The organoids were propagated for at least six passages using an optimized protocol. Multiplex immunofluorescence analysis revealed highly proliferative structures with approximately 40% Ki-67-positive cells expressing hepatocyte (Albumin and HNF4α) and cholangiocyte (CK19) markers. Intermittent LGR5 staining suggested the presence of liver progenitor cell features. Quantitative PCR results confirmed variable HNF4α expression, indicating inter-patient heterogeneity in differentiation status. Time-lapse imaging combined with mathematical modeling uncovered a biphasic growth dynamic with an initial linear expansion in the first 15 h, followed by exponential growth (doubling time ≈ 20.6 h) between 30 and 72 h. Overall, our workflow produced genetically and phenotypically stable liver organoids that recapitulate essential features of various hepatic conditions. This provides a solid foundation for disease modeling, potential drug testing, and quantitative systems biology. Full article

Background: The Xinjiang Black pig is an excellent breed developed by the Xinjiang Production and Construction Corps in the 1990s; however, it has been endangered by the impact of commercial breeds. Methods: Whole genomes of 224 individuals from the Xinjiang Black pig conservation population were resequenced. Results: Genetic structure and diversity analyses revealed that Xinjiang Black pigs underwent severe inbreeding and were genetically closely linked to Landrace pigs. The genetic diversity of the F₂ generation was well preserved in the existing breeding scheme. A total of 686 significant selection regions and 406 candidate genes were identified using F_ST and θπ complementary methods, with Xinjiang Black pigs, Min pigs, and Laiwu pigs as ancestral populations, and F₂. Based on Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and quantitative trait loci annotations, potential germplasm candidate genes were identified. Among these, SOX5, HMG20A, and NEDD4 are associated with fat deposition; SPRY1, MNS1, DMXL2, and ALB are closely associated with male reproductive ability; ARPP19 and TLN2 are strongly associated with oestrous cycle regulation and oocyte maturation; and SLC4A4 and SLC12A1 are extremely important for osmotic regulation and foetal survival. Conclusions: These findings deepen our understanding of the genetic mechanisms of artificial selection in Xinjiang Black pigs and provide a theoretical basis for subsequent breeding and genetic research on this breed. Full article

Precision oncology has been evolving rapidly, with increasing emphasis on early detection and personalized diagnostic approaches that translate into tailored treatment algorithms. The integration of molecular markers, quantitative imaging approaches and artificial intelligence (AI) in the diagnostic workflow of cutaneous squamous cell carcinoma (cSCC) has increased accuracy and has the potential to improve early detection rates in these cancers. Sun exposure is the primary etiologic factor in the development of cSCC. The primary objective of this review is to evaluate the current state and future directions of modalities and practices in diagnostic techniques for cSCC. Specifically, this review summarizes the key genetic alterations and potential molecular targets in cSCC. High-risk genetic mutations and pathways implicated in the pathogenesis of cSCC include p53, NOTCH, RAS/MAPK, cell-cycle, and adhesion pathways. This review further explores current and emerging modalities in optical imaging techniques and molecular-based diagnostic modalities in cSCC. Further, we discuss the role of radiomics and AI in the diagnostic work-up of cSCC. These techniques have the potential to enable more accurate risk models that refine conventional histopathology and guide personalized interventions. However, there are limitations to the clinical application of several of these modalities, with cost being an important driver. These challenges have been discussed in detail within this review. Nevertheless, ongoing research is focused on improving the workflow and initiating a shift in clinical practice with application of precision diagnostics as a standard of care. Full article

Background/Objectives: Sweetness is a key determinant of the eating quality of sweet corn, primarily governed by the soluble sugar content in kernels. The soluble sugar content decreases rapidly during the postharvest shelf life, which directly affects the flavor and quality. Relatively few studies have been conducted on the shelf life of sweet corn. Methods: An F₆ recombinant inbred line (RIL) population was constructed from two super sweet inbred lines with contrasting soluble sugar degradation rates: D174 (low degradation rate) and D179 (high degradation rate). Extreme phenotype pools were established using soluble sugar content as the target trait. Based on bulked segregant analysis sequencing, we identified chromosomal segments associated with postharvest soluble sugar reduction in sweet corn, annotated the gene information within these segments, and analyzed the functions of the annotated genes using the Gene Ontology and Genomes databases. Results: Results revealed three associated regions located at 44,205,775–45,290,843 bp on chromosome 4, 6,250,656–6,744,665 bp on chromosome 2, and 135,428,709–136,732,132 bp on chromosome 10. This interval contained 195 genes. Integrated analysis of gene expression, gene annotations, and quantitative real-time PCR indicated that Zm00001eb069070, which is highly expressed in kernels with a prolonged shelf life, might be a key candidate gene regulating soluble sugar degradation in sweet corn. Conclusions: This study provides valuable genetic resources for the improvement of favorable agronomic traits and the advancement of molecular breeding strategies for sweet corn. Full article

Background: Pigs are one of the most important livestock species for providing meat products in the world. Deciphering the genetic architecture of feed efficiency-related traits is beneficial to improve the genetic progress of these traits and save the total cost of pork production. However, the genetic architecture of feed efficiency-related traits remains unclear. Methods: To address this problem, we collected 1301 genotyped Yorkshire pigs with three feed efficiency-related traits, including days at 100 kg (DAYS_100), backfat thickness at 100 kg (BFT_100), and feed conversion ratio from 30 to 100 kg (FCR_30_100), to explore the genetic parameters and genetic basis of these traits. Results: The heritability of DAYS_100, BFT_100, and FCR_30_100 was 0.25 ± 0.04, 0.40 ± 0.05, and 0.23 ± 0.04, respectively. Additionally, BFT_100 and DAYS_100 had a weak negative genetic correlation (−0.01 ± 0.12), while trait FCR_30_100 showed a positive genetic correlation with DAYS_100 (0.51 ± 0.11) and BFT_100 (0.28 ± 0.12). A genome-wide association study identified 7, 5, and 4 SNPs independently associated with BFT_100, DAYS_100, and FCR_30_100, respectively. Further analysis found that the candidate gene ETV4 was significantly associated with DAYS_100 and the candidate gene ENSSSCG00000045751 was associated with FCR_30_100. The functional annotation of candidate genes was enriched in the bile acid metabolic process and protein ubiquitination terms. Conclusions: This study discovered 16 quantitative trait loci associated with feed efficiency-related traits, providing a comprehensive insight for understanding the genetic basis of feed efficiency-related traits in pigs. The candidate genes, such as ETV4 gene in DAYS_100, CAMK1D gene for BFT_100, and ENSSSCG00000045751 gene for FCR_30_100, could be used for further investigation. Full article

The accurate assessment of tailings dam operational status and timely risk warnings are critical for ensuring their safe operation. To address the limitations of existing models in managing complex environments and multidimensional risk factors, this study proposes an early warning model for tailings dam operational status based on a two-dimensional cloud model. First, a comprehensive early warning system is developed to assess the probability and consequences of dam failure, using risk probability and consequences as two-dimensional coordinates, incorporating the randomness and fuzziness of uncertainty described by cloud theory, and transforming qualitative data into quantitative conclusions. Next, a genetic algorithm optimizes the projection pursuit model to determine weights, and weighted numerical features are utilized to enhance the classification of early warning levels. Furthermore, the two-dimensional cloud model is enhanced by introducing a proximity coefficient to replace the membership function, with the resulting cloud map visualized using a forward cloud generator. Finally, the early warning level of the tailings dam’s operational status is determined based on the clustering of cloud droplets and the proximity coefficient. Empirical application to five tailings dams in Hubei Province confirms the model’s effectiveness and practicality. The results demonstrate that the model effectively addresses the complexity and uncertainty of tailings dam operational status, delivers accurate warnings, and provides robust decision support for emergency response. Full article

Atopic dermatitis (AD) is a chronic inflammatory skin disease with a complex and highly polygenic genetic architecture, in which immune-mediated mechanisms play a central role. Here, we integrated single-cell cis-expression quantitative trait loci from 14 immune cell types with AD GWAS summary statistics using a two-sample Mendelian Randomization (MR) framework to resolve cell-specific genetically mediated transcriptional effects. We identified 303 significant cell-specific gene–trait associations with limited overlaps across cell types. A multi-step prioritization strategy refined these findings to 35 genes across all 14 cell types. A comparison with whole blood cis-eQTLs revealed a limited concordance, suggesting an attenuation of cell-specific regulatory effects in bulk transcriptomic approaches. Intersecting single-cell and bulk evidence identified 22 high-confidence genes with a relatively independent mechanism of action. Integrative annotation implicated several immune-relevant and druggable genes, including IL2RA, with distinct cell-specific effects. Our findings demonstrate diverse mechanisms of risk genes for AD at the single-cell level that act across immune cell states and pathways, with implications for therapeutic interventions. Full article

Passiflora germplasm represents an important genetic resource for improving fruit yield and quality in breeding programs targeting semi-arid environments. This study aimed to assess the phenotypic diversity, genetic parameters, and breeding potential of Passiflora accessions conserved in the Passion Fruit Active Germplasm Bank of Embrapa Semiárido. A total of 55 accessions, predominantly Passiflora cincinnata Mast., were evaluated using morphoagronomic descriptors related to plant, flower, and fruit traits. Quantitative data were analyzed using mixed linear models (REML/BLUP) to estimate genetic parameters, and multivariate analyses were applied to characterize phenotypic divergence. Substantial phenotypic variability was observed, particularly for fruit-related traits. Fruit weight ranged from 43.25 to 142.88 g, pulp weight ranged from 7.86 to 51.37 g, and pulp yield ranged from 17.06% to 40.27% among accessions. Broad-sense heritability estimates for key fruit traits were moderate to high, reaching 0.50 for fruit weight, 0.49 for pulp weight, and 0.36 for pulp yield, indicating favorable prospects for selection. Principal Component Analysis explained 66.0% of the total variation in the first two components, with fruit size, pulp-related traits, and seed number contributing most strongly to accession differentiation. Multivariate analyses consistently identified accessions 1 and 16 as superior for fruit weight and pulp yield, whereas accession 55 combined high fruit weight with elevated soluble solid content (up to 14.24 °Brix) but lower pulp yield. Overall, the observed variability highlights the relevance of Passiflora germplasm conserved under semi-arid conditions as a valuable resource for breeding programs focused on fruit yield, quality, and adaptation to water-limited environments. Full article

Gibberellins (GAs) play a crucial regulatory role in the growth and development of cotton (Gossypium hirsutum L.). Through bioinformatics analyses, we identified a total of 39 GA2ox genes (encoding gibberellin 2-oxidases) in the cotton genome, designated GhGA2ox1 to GhGA2ox39. Based on phylogenetic analysis, these genes were classified into five groups. We further examined their gene structures, conserved motifs, and chromosomal distributions, revealing that members within the same group shared similar structural and motif organizations. Collinearity and cis-element analyses provided important insights into the evolutionary history and regulatory potential of the GA2ox gene family in cotton. Notably, using nucleotide diversity (π) and population differentiation (F_ST) analyses across the entire family, we screened and identified nine candidate genes that underwent strong artificial selection during cotton domestication and improvement. Further haplotype-phenotype association analysis identified GH_D09G0919 (GhGA2ox31) as a key regulator of Plant Height (PH). To validate their regulatory roles, we analyzed the genotype distribution in accessions with extreme phenotypes. The results revealed divergent selection histories for these two loci: the favorable allele of GH_D01G0720 (GhGA2ox23) was already fixed in the tested population, whereas GH_D09G0919 maintained significant natural variation. Specifically, the Hap2 allele of GH_D09G0919 was significantly enriched in the shortest accessions compared to the tallest ones. Importantly, quantitative real-time polymerase chain reaction (qRT-PCR) analysis confirmed that the Hap2 allele drives significantly higher gene expression in leaves, suggesting that enhanced GA catabolism underlies the compact phenotype. Additionally, transcriptomic profiling revealed the tissue-specific expression patterns of candidate genes, implying their functional roles in development. Furthermore, functional validation using the Arabidopsis mutant of the homologous gene (AtGA2ox8) confirmed its conserved role in regulating plant height, as the mutant exhibited a distinct short-stature phenotype. These results uncover valuable genetic resources for molecular breeding to shape compact cotton architecture. Collectively, this study aims to analyze the evolutionary patterns of the cotton GA2ox gene family and to identify key genes that regulate plant height under artificial selection, providing theoretical support for molecular breeding of compact plant types. Full article

This paper presents an analysis of the impact of full and partial curfews on water demand and production, as imposed in Kuwait during the meteorological spring (March, April, and May) of 2020, in response to the COVID-19 pandemic. We consider all desalination technologies used in Kuwait: Multi-Stage Flash (MSF), Multi-Effect Thermal Vapor Compression (MED-TVC), and Reverse Osmosis (RO). Historical data and predictive models are combined and analyzed via a statistical genetic algorithm. The environmental and economic implications of the lockdown measures were assessed through quantitative evaluation, comparing actual 2020 water demand and production data with values predicted under normal operating conditions. During the 2020 COVID-19 pandemic, water consumption surged, with maximum daily consumption climbing by 3.6%, and average daily consumption by 5.2%. These values were significant increases relative to 2019, for which the corresponding figures were 2.1% and 1.6%. The study assesses the economic and environmental consequences quantitatively, specifically the increase in CO, CO₂, and NO_x emissions, due to the increase in fuel consumption at desalination and power plants. Water demand and production across the national water network were simulated using mathematical models specifically designed for this purpose, developed from data provided by the Meteorological Department of Civil Aviation and the Ministry of Electricity, Water, and Renewable Energy. Full article

Coastal marine sediments and beach sands receive microbial and genetic inputs from wastewater discharge, urban runoff, aquaculture, wildlife, and recreational activity, yet their role as coupled microbial–genetic interfaces linking environmental processes and human exposure remains incompletely synthesized. This review integrates quantitative evidence from culture-based studies, qPCR surveys, metagenomic analyses, and multi-year monitoring investigations focused on coastal sediments and sands. Reported antibiotic resistance gene (ARG) concentrations in coastal sediments reach 2.2 × 10⁹ copies g⁻¹ (wet weight) for sul1 in wastewater-impacted systems, with total ARG abundances commonly ranging from 1.59 × 10⁷ to 2.88 × 10⁸ copies g⁻¹ in effluent-receiving zones and tetM reported at 1.43 × 10⁷ copies g⁻¹. Beach sands contain measurable resistance markers, including intI1 at 9–3823 copies g⁻¹ and blaTEM up to 14 copies g⁻¹ in wet sand. Viable fecal indicator bacteria and pathogens have been cultured directly from sands, including Staphylococcus aureus at 0–8710 CFU g⁻¹ and methicillin-resistant S. aureus at 0–605 CFU g⁻¹. Collectively, the evidence indicates that coastal sediments and sands function as structured microbial and genetic reservoirs requiring integrated assessment of benthic retention, hydrodynamic redistribution, and exposure-relevant interpretation. Full article

With global warming, high-temperature stress has become a primary abiotic factor limiting maize yield and quality. Exposure to heat stress induces sunscald on maize leaves, which severely impairs photosynthesis and ultimately leads to yield reduction. In this study, we used the heat-tolerant inbred line Zheng58 and the heat-sensitive inbred line HSBN, both of which are cultivated maize (Zea mays L. subsp. mays) inbred lines, as parents to construct F₂ and F_2:3 populations consisting of 257 lines. Phenotyping for sunscald at the flowering stage was performed across three field environments. The F₂ population was genotyped using the Maize 10K SNP array to construct a genetic map containing 1728 single nucleotide polymorphism (SNP) markers. The map spanned 1406.22 cM, with an average marker density of 0.81 cM per marker. Eight quantitative trait loci (QTLs) associated with heat tolerance were identified in the F₂/F_2:3 populations, distributed on chromosomes 1, 4, 5, and 8, collectively explaining 3.43% to 35.44% of the phenotypic variation. Among them, the stable QTL qHT1-2 on chromosome 1 was consistently detected across all three environments, explaining 11.41% to 35.44% of the phenotypic variation. Additionally, a major QTL, qHT1-3, was identified on the same chromosome, accounting for 33.70% of the phenotypic variation. Transcriptome analysis of flowering-stage leaves from both parents revealed 9262 differentially expressed genes (DEGs). Of these, 21 DEGs were co-localized within the eight QTL intervals. The genes Zm00001eb013260, Zm00001eb012720, Zm00001eb013600, and Zm00001eb013100 exhibited highly significant differential expression between the parental lines, these four genes are identified as candidate genes in response to heat stress in maize, and their specific biological functions require further functional validation. Full article