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At least 19 recordsLinked to original sources
PubMed2026

Chromatin context shapes SPT5 regulation of promoter-proximal Pol II, fine-tuning gene expression changes during Drosophila embryogenesis.

Transcription involves initiation, pausing, elongation, and termination. Suppressor of Ty5 (SPT5) regulates promoter-proximal pausing and elongation, but how it orchestrates both steps during dynamic developmental changes in gene expression remains unclear. Here, using rapid optogenetic depletion in Drosophila embryos, we uncover different consequences of SPT5 removal at different developmental stages. In early embryos, SPT5 depletion causes a shift of RNA polymerase II (Pol II) from the canonical pausing site to the +1 nucleosome, which is strongly positioned. In late embryos, SPT5 depletion similarly reduces pausing at the canonical site, but the transcriptional machinery can overcome the +1 nucleosome-which appears more labile at this time point-moving into the gene body. This results in lethality and both up- and downregulation of expression, depending on the balance between Pol II entering the gene body and defective elongation. This is intensified for genes naturally increasing or decreasing their expression, indicating that SPT5 contributes to fine-tuning dynamic expression changes.

+1 nucleosome↗
PubMed2026

OsMYB8-OsARF12/25 module fine-tunes tiller angle via auxin signaling pathway in rice.

Tiller angle is a critical determinant of rice plant architecture and significantly impacts grain yield by influencing planting density and photosynthetic efficiency. Although auxin signaling is known to affect tiller angle in rice, the detailed regulatory networks remain largely unknown. In this study, we identify OsMYB8, an R2R3-MYB transcription factor, as a positive regulator of rice tiller angle. Functional analyses revealed that loss-of-function mutants of OsMYB8 exhibited reduced tiller angles and a more compact architecture, while overexpression of OsMYB8 resulted in more expanded tiller angles. Further investigations found that OsMYB8 might negatively regulate the shoot gravitropic response by disrupting asymmetric auxin distribution. At the molecular level, OsMYB8 directly binds to the promoters of 2 auxin response factors, OsARF12 and OsARF25, and represses their transcription. Genetic analyses confirmed that OsMYB8 acts upstream of OsARF12 and OsARF25 in regulating rice tiller angle. Our finding elucidates a previously uncharacterized OsMYB8-OsARF12/25 transcriptional module that fine-tunes auxin signaling to regulate tiller angle in rice, and offers valuable genetic targets for the optimization of rice architecture and yield potential.

Oryza↗
PubMed2026

Transfer Learning across Material Properties Using Center-Environment Features: From Energetics to Mechanical Properties in Multicomponent Mo Alloys.

Transfer learning (TL) provides a viable approach to mitigate data scarcity in materials informatics. While conventional TL focuses on predicting identical properties across different systems, this work demonstrates a cross-property extension of TL from energy to mechanical properties via end-to-end model weight pre-training and fine-tuning: knowledge learned from predicting substitution energies is transferred to predict distinctly different mechanical properties, substantially improving computational efficiency given the typically higher cost of acquiring target-domain data. To accelerate computational alloy design, machine learning models using center-environment (CE) features were first developed to predict substitution energies of alloying elements in molybdenum (Mo)-based alloys. The Random Forest models achieved the optimal performance and transferability-R2 = 0.97, 〈MAE〉 = 0.11 eV, and 〈RMSE〉 = 0.16 eV-against the density functional theory (DFT) benchmark. The model dependency of feature selection and importance analysis was discussed. The transferability of the energy models was validated on unknown systems with new elements. Subsequently, the energy models were fine-tuned using limited mechanical property data to construct energy-to-property (E2P) TL models capable of predicting elastic properties, including bulk modulus, Young's modulus, shear modulus, and elastic constants, achieving an improved accuracy over the non-transferred ML by ∼10-30%, with its transferability verified by additional DFT calculations. This cross-property E2P transfer learning framework opens a new avenue for accelerating computational materials discovery and may be extended to other multiproperty predictions governed by similar physical principles.

center-environment feature↗
PubMed2026

Cystathionine γ-Lyase-Dependent S-Sulfhydration of Smad3: A Novel Target to Alleviate Fibrosis in Systemic Sclerosis.

OBJECTIVE: The cystathionine γ-lyase (CSE)/hydrogen sulfide (H2S) axis has emerged as a key regulator in tissue fibrogenesis. This study aimed to explore the role of the CSE/H2S axis in systemic sclerosis (SSc) and to investigate its underlying mechanisms to identify promising therapeutic targets. METHODS: CSE/H2S levels were assessed in serum samples from 25 patients with SSc and 28 healthy controls. Human dermal fibroblasts from patients with SSc and healthy controls were used for functional studies, including propargylglycine (CSE inhibitor) treatment, Gyy4137, a slow-releasing hydrogen sulfide donor, CSE silencing, and CSE overexpression, combined with liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based S-sulfhydration proteomics. Molecular dynamics simulations were performed to study the effects of S-sulfhydration on protein structure, and an Smad3 C121S (cysteine [Cys] 121 mutated to Ser) mutant was generated to verify the function targets of S-sulfhydration. In vivo, bleomycin-induced mouse models of skin and lung fibrosis were constructed to evaluate the effects of CSE overexpression. RESULTS: In human samples, CSE/H2S levels were reduced in SSc. CSE inhibition promoted extracellular matrix deposition. S-sulfhydration proteomics showed that S-sulfhydration levels were globally reduced in SSc compared to controls. CSE overexpression increased S-sulfhydration on Smad3, suppressed transforming growth factor β 1 (TGFβ1)/Smad3 signaling, mitigating skin fibrosis. Notably, Cys121 on Smad3, identified as a pivotal target for S-sulfhydration by proteomics, was shown to fine-tune its MH1 domain, with its mutation impairing the antifibrotic effects. In mice, CSE overexpression attenuated bleomycin-induced skin and lung fibrosis. CONCLUSION: Smad3 S-sulfhydration mediates the antifibrotic effect of CSE in SSc, highlighting it as a critical mechanism and promising therapeutic target.

Humans↗
PubMed2026

Regulatory Evolution and the Genetic Basis of Human Brain Expansion.

The evolution of the human brain is characterized by profound changes in structure and function, despite relatively limited divergence in protein-coding genes compared to other primates. This paradox has led to increasing recognition of gene regulatory elements (GREs) as primary drivers of evolutionary innovation. In this review, we synthesize current knowledge on the role of conserved noncoding elements (CNEs), human accelerated regions (HARs), and transposable element (TE)-derived sequences in shaping gene regulatory networks (GRNs) underlying brain development. Comparative analyses across humans and closely related primates, including the chimpanzee, gorilla, and orangutan, reveal that while core regulatory architectures are highly conserved, subtle changes in regulatory elements drive species-specific gene expression patterns. We highlight how CNEs provide a stable regulatory framework, whereas HARs and TE-derived elements introduce lineage-specific modifications that fine-tune neurodevelopmental processes. Advances in functional genomics, including CRISPR-based perturbations, massively parallel reporter assays, and single-cell multi-omics, have enabled direct interrogation of regulatory function, linking sequence variation to cellular phenotypes. Furthermore, we discuss how regulatory evolution contributes to both cognitive innovation and susceptibility to neurological disorders. Despite significant progress, challenges remain in establishing causal relationships between regulatory variation and phenotypic outcomes. Future integration of multi-omics data and comparative models will be essential for resolving these complexities. Together, this review provides a comprehensive framework for understanding the molecular basis of primate brain evolution through the lens of gene regulation.

Brain evolution↗
PubMed2026

Expansion of the allelic and phenotypic spectrum of MED25-related developmental disorder: novel compound heterozygous variants with structural domain implications.

MED25-related developmental disorder (Basel-Vanagaite-Smirin-Yosef syndrome) is a rare autosomal recessive disorder, defined by severe neurodevelopmental delay, corpus callosum abnormalities, ocular involvement, epilepsy, and marked facial appearance. MED25 pathogenic variants interfere with the functioning of the Mediator complex, which is responsible for RNA polymerase II transcription. We report a 9-year-old girl who presents with significant global developmental delay, agenesis of the corpus callosum, congenital cataracts, epilepsy, hypotonia, musculoskeletal abnormalities, and typical craniofacial features. Trio-based whole-exome sequencing revealed compound heterozygous variants in MED25: a maternally transmitted truncating variant (c.1366 C > T; p.Gln456*) and a paternally inherited missense variant (c.430 C > T; p.Leu144Phe). The new classification of the missense variant as potentially pathogenic is supported by a systematic ACMG re-evaluation supported by segregation analysis, phenotypic specificity, computational prediction, and structural localization in the MED25 Activator Interaction Domain (ACID). Comparative phenotypic analyses show strong agreement with reported cases but add more data to fine-tune clinical spectrum. This article broadens the allelic and phenotypic spectrum of MED25-related developmental disorder and highlights the need for comprehensive evaluation across molecular, structural, and phenotypic pathways to elucidate variant signature in rare genetic disease models correctly.

Humans↗
PubMed2026

CRISPGen: A deep generative framework for multi-objective CRISPR/Cas9 guide RNA design via Conditional Latent Diffusion and Dual-Critic Reinforcement Learning.

MOTIVATION: The CRISPR-Cas9 system offers transformative potential for precision genome editing, yet its clinical translation remains constrained by the risk of unintended off-target double-strand breaks. While current discriminative models excel at evaluating pre-specified candidate guides, resolving the fundamental antagonism between on-target cleavage efficiency and off-target specificity within a fixed sequence search space remains a major challenge. RESULTS: We present CRISPGen, a unified deep generative framework that reframes sgRNA design as a multi-objective constrained sequence synthesis problem. It integrates (i) DNABERT-2 genomic-language embeddings, (ii) a conditional latent diffusion generator conditioned on a user-specified on-target efficiency target, and (iii) a dual-critic reinforcement-learning (RL) stage that couples a frozen on-target efficiency critic with a cross-attention off-target discriminator (validation Pearson R=0.8157) trained on a unified corpus of experimental off-target events from six detection platforms. Across 1000 generated sgRNAs, CRISPGen reduces the mean off-target discriminator score by 99.7% relative to the pre-RL baseline and, under an exhaustive whole-genome screen of all 302,631,056 NGG PAM sites in GRCh38, yields zero perfect-match and only 55 one-mismatch genomic hits. We further show, transparently, that the internal on-target critic saturates under RL optimization - an instance of Goodhart's Law - and therefore assess on-target viability using an independent external CRISPRon screen (mean 47.10/100). Repeating the RL fine-tuning stage under three random seeds (with the diffusion generator, DNABERT-2 embeddings, and off-target discriminator held fixed) yields a stable operating point across seeds. Full diversity, per-mismatch, and reproducibility statistics are reported in the Results. AVAILABILITY: Source code is available at https://github.com/malekpouri/CRISPGen; the pre-trained checkpoints and the 3,000,000-sequence library are hosted on Hugging Face (https://huggingface.co/malekpouri/CRISPGen-Checkpoints) and archived on Zenodo under DOI 10.5281/zenodo.21428641.

CRISPR-Cas9↗
PubMed2026

Selective monitoring of trace-level catechin and myricetin in herbal and aqueous matrices using magnetic MIP-DSPME: Optimization via design of experiments.

A novel dispersive solid-phase microextraction approach utilizing a magnetic molecularly imprinted polymer (MMIP) integrated with HPLC-UV detection was developed for the concurrent quantification of catechin and myricetin in herbal extracts and aqueous samples. The sorbent was engineered as a core-shell nanocomposite, consisting of a selective polymer layer deposited onto Fe3O4@SiO2-APTMS magnetic nanoparticles. Dual-template imprinting using catechin and myricetin generated complementary binding cavities within the polymer framework. Experimental variables influencing extraction were systematically screened and subsequently optimized. A Plackett-Burman design was first applied to identify the most influential factors, with pH and sorption time identified as the dominant variables. These parameters were subsequently fine-tuned using a central composite design, and the optimization process was completed in only 30 experimental runs. The sorption characteristics of the imprinted sorbent (MMIP) were compared with those of its non-imprinted counterpart (MNIP). The MMIP demonstrated markedly higher maximum binding capacities (Qmax), reaching 119.3 mg g-1 for myricetin and 112.1 mg g-1 for catechin, whereas the corresponding values for the MNIP were 32.55 and 32.08 mg g-1, respectively. Moreover, the affinity constants (KL = 0.760-0.950 L mg-1) were approximately 2.3-fold higher for the MMIP, confirming its stronger and more selective interactions with the target analytes. The selectivity coefficients for the targeted flavonoids relative to structurally related compounds, including ferulic acid, p-coumaric acid, melatonin, and curcumin, exceeded 3.5 for the MMIP, whereas the corresponding values for the MNIP were close to 1.1, demonstrating the high molecular recognition capability of the imprinted sorbent. Method validation demonstrated limits of detection (LODs) of 0.33-0.59 ng mL-1 and limits of quantification (LOQs) of 1.10-1.96 ng mL-1, and excellent linearity over the concentration range of 5.0-5500 ng mL-1 (R2 > 0.998). The method achieved recoveries of 93.96% to 105.69% with RSDs below 5.5%, while the preconcentration factors ranged from 209 to 229. Furthermore, the sorbent retained more than 95% of its extraction efficiency after four consecutive reuse cycles and more than 80% after six cycles, demonstrating excellent stability and reusability. The proposed method was successfully applied to the analysis of six medicinal plant extracts and water samples, showing negligible matrix interference and superior sensitivity, selectivity, and operational simplicity compared with conventional solid-phase extraction methods.

Flavonoids↗
PubMed2026

A single-nucleus and spatial transcriptomic atlas of poplar leaves reveals the regulation of leaf polarity and cuticle deposition.

Leaf adaxial-abaxial polarity is fundamental for plant morphogenesis and environmental adaptation through asymmetric cell differentiation. Emerging evidence reveals dorsoventral metabolic gradients act downstream of transcriptional networks to fine-tune cellular specialization. While conserved transcription factors (e.g., HD-ZIP III and KANADI) establish initial polarity, the molecular networks driving position-specific cellular differentiation and their integration with metabolic adaptation remain unclear. Leveraging single-nucleus and spatial transcriptomics, we resolve major cell classes (mesophyll, epidermal, and vascular-associated) and their adaxial-abaxial subtypes, revealing dorsoventral polarity in transcriptional profiles and metabolic pathways. Adaxial cells are enriched in phenylpropanoid/flavonoid biosynthesis, while abaxial cells show preferential activation of stress and hormone signaling. Notably, we identify MYC2 as a key regulator of adaxial cuticle biosynthesis, binding to promoters of lipid biosynthetic and transport genes (e.g., CER10 and LTPG1) and promoting cuticle thickening. Our study uncovers how positional identity shapes transcriptional and metabolic polarity in leaves, with MYC2 emerging as a central regulator coordinating organ-specific adaptations. These findings provide insights into the spatial regulation of plant development and stress resilience, offering potential strategies for engineering stress-tolerant woody crops.

Plant Leaves↗
PubMed2026

Neurovascular coupling in the basolateral amygdala modulates negative emotions.

Emotion induces changes in regional cerebral blood flow, a manifestation of neurovascular coupling (NVC). However, whether NVC provides feedback to actively modulate emotion remains unexplored. Here, we demonstrate that NVC actively and bidirectionally modulates stress-induced negative emotions. We established bidirectional manipulations of NVC in freely moving mice by employing integrated pharmacological, genetic, and arteriolar optogenetic approaches. Our results showed that both systemic and region-specific NVC deficiencies in the basolateral amygdala (BLA) heightened emotional responses when mice transitioned from a safe, familiar environment to anxiogenic environments and that local restoration of NVC in the BLA normalized these responses. Mechanistically, NVC dysfunction impaired the capacity of BLA neuronal scaling during state transitions, manifesting as a characteristic biphasic pattern of c-Fos topology. NVC-deficient animals aberrantly adopted high-stress configurations under mild stress but regressed to low-stress templates during high-demand survival threats, thereby compromising defensive sustainability. Notably, the genetic NVC-enhancement model counteracted NVC impairments caused by chronic stress, thereby alleviating stress-driven emotional distress. These findings establish NVC in the BLA as an allostatic program that fine-tunes neural circuit activity during emotional responses, with implications for understanding and treating emotional disorders.

Animals↗
PubMed2026

Utero-placental calcium and magnesium ion channels: A systematic review of obstetric implications of their alterations.

Despite the established roles of calcium (Ca2+) and magnesium (Mg2+) in placental function and uterine contractility, limited information exists on how dysregulation of major ion channels contributes to poor pregnancy outcomes. We synthesized data on the consequences of Ca2+ and Mg2+ channelopathies in uterine and placental functions. Using PubMed, Wiley Online, AJOL, and Web of Science databases for article search, a systematic review of forty-nine papers published between 2000 and March 2026 was carried out and reported in accordance with the PRISMA 2020 guideline. Based on the PICO framework, eligible studies involving human, animal, and in vitro designs were chosen and subjected to narrative analysis. L-type and T-type voltage-gated Ca2+ channels, together with transient receptor potential channels, emerged as principal mediators of placental Ca2+ transport and myometrial contractility. Mechanosensitive Piezo1 channels mediate stretch-activated Ca2+ influx, while store-operated Ca2+ entry pathways involving STIM1-Orai1 sustain intracellular Ca2+ homeostasis. Potassium-Ca2+ coupling channels modulated membrane hyperpolarization and anti-labor effects, and intracellular regulators such as PMCA and RYR1 fine-tuned Ca2+ homeostasis. The Mg2+ transporters are essential for preserving Mg2+ homeostasis and regulating Ca2+-dependent excitability. Dysregulation of these ion channel systems was consistently linked to abnormal uterine contractility, preterm birth, preeclampsia, fetal growth restriction, and adverse pregnancy outcomes. Both Ca2+ and Mg2+ ion channelopathies represent both a potential therapeutic target and a mechanistic factor underlying key obstetric complications.

Female↗
PubMed2026

Usage and impact of global biodata resources.

MOTIVATION: Biodata resources constitute a critical, large-scale, and globally distributed infrastructure underpinning life science research, yet their organic growth has hindered efforts to quantify key indicators needed to justify sustainable support, including usage, impact, and interdependencies. Here, we present an updated Global Biodata Coalition inventory alongside a Total Resource Usage (TRU) dataset that integrates this inventory with two complementary literature-derived sources: data citations and informal resource name mentions extracted from full-text articles using a fine-tuned machine learning model. A unified database schema enables cross-resource comparisons, dependency network analyses, and evaluation of resource name distinctiveness. RESULTS: The combined dataset captures 11.5 million formal and informal references, revealing that most resources are acknowledged informally within article text. Network analysis indicates a densely interconnected ecosystem in which Global Core Biodata Resources function as key providers and integrators, underscoring their foundational role. While full resource names are generally distinctive, widespread use of acronyms limits detectability through text mining. Together, these findings provide robust empirical evidence of a highly utilized and interconnected biodata infrastructure, highlight limitations of single-metric assessments, and underscore the need for multi-dimensional evaluation frameworks and more consistent data citation practices to support informed decision-making and long-term sustainability. AVAILABILITY AND IMPLEMENTATION: The database and analytical code described here are available on https://github.com/globalbiodata.

Journal Article↗
PubMed2026

GraphyloVar: predicting the impact of non-coding variants using a multi-species sequence model.

MOTIVATION: Understanding the functional impact of genetic variants is a key problem for precision medicine. Tools like CADD, PhyloP, and PhastCons are useful, but they often look at each position in the genome in isolation. This means they can miss important information from the evolutionary history that connects different species. In this paper, we extend our previous model, Graphylo, to predict the effects of variants. Our new model, GraphyloVar, is built to directly utilize the phylogenetic tree that relates the species. RESULTS: GraphyloVar is a deep learning model that considers both DNA sequence and evolutionary patterns from many species. It uses two main components: Graph Convolutional Networks (GCNs) to process the phylogenetic tree, and Transformer encoders to extract features from the DNA sequences. Pre-trained to predict population-level allele frequencies on the TOPMed whole-genome sequencing cohort, GraphyloVar achieves an AUROC of 0.6246 zero-shot on &#x223c;149M held-out variants, and an ensemble with CADD reaches 0.6442 (+0.020, P<10-15). Fine-tuned GraphyloVar achieves the highest AUROC across all 13 MPRA benchmark datasets. By integrating deep learning with explicit phylogenetic input, GraphyloVar offers a powerful and complementary approach to variant effect prediction that utilizes the full evolutionary history from many species to better identify and prioritize important non-coding variants. AVAILABILITY AND IMPLEMENTATION: Code and datasets are available at https://github.com/DongjoonLim/GraphyloVar under DOI: 10.5281/zenodo.20616818.

Phylogeny↗
PubMed2026

DeepGeSeq: deep learning library for genomic sequence modeling and analysis.

MOTIVATION: Deep learning methods have demonstrated significant potential in genomics, enabling broad applications such as sequence activity prediction, regulatory rule identification, and variant effect quantification. However, their widespread adoption is often hindered by the steep computational learning curve required for model construction, training, and downstream biological interpretation. Here, we introduce DeepGeSeq, a user-friendly Deep-learning library tailored for Genomic Sequence modeling and analysis. RESULTS: By integrating state-of-the-art architectural modules, DeepGeSeq streamlines the entire deep learning workflow, requiring minimal user input via a simple configuration file and an intuitive agentic skill. We comprehensively validate the efficacy of DeepGeSeq through diverse case studies, encompassing pipeline verification using synthetic datasets, the reproduction and application of established models, and model fine-tuning coupled with biological interpretation on user-defined data. Furthermore, we demonstrate DeepGeSeq's versatility in domain-specific applications, including single-cell ATAC-seq modeling for cell-type clustering, and MPRA data modeling coupled with in silico saturation mutagenesis to dissect cis-regulatory elements. Ultimately, DeepGeSeq bridges the gap between computational complexity and biological discovery, providing an accessible resource that facilitates the development and broad application of deep learning methods in genomics research. AVAILABILITY AND IMPLEMENTATION: https://github.com/JiaqiLi1024/DeepGeSeq.

Deep Learning↗
PubMed2026

RNA splicing and cardiovascular disease: a guide for cardiologists.

Alternative splicing (AS) is a fundamental RNA processing mechanism, which generates different RNA transcripts and consequently different protein isoforms from a single gene. This increases the diversity of proteins within an organism and can fine-tune biological processes. This review examines how cardiac-enriched RNA-binding proteins establish heart-specific splicing programs governing aspects of cardiac development, function, and disease. Developmentally, coordinated sarcomeric isoform switches underpin the foetal-to-adult transition and further isoform rewiring in ion channel and kinase genes determine electrophysiology and excitation-contraction coupling. AS contributes to the pathogenesis of several cardiomyopathies and emerging datasets suggest that pathological hypertrophy engages distinct splicing signatures compared with physiological hypertrophy. This review summarizes diagnostic and prognostic opportunities arising from bulk, long-read, and single-cell/nucleus transcriptomics, which resolve cell type-specific isoforms and disease-associated switches. Circulating RNA biomarkers (including splice ratios and circularRNAs) may signify myocardial remodelling and arrhythmic risk. Integrative approaches that link AS with proteomics and genomics improve variant interpretation, reveal previously unannotated protein isoforms, and enable tracking of disease progression and therapy response. Finally, an outline of therapeutic strategies to modulate AS in cardiovascular disease (CVD), including antisense oligonucleotides, small molecules, and genome-editing modalities (CRISPR, base, and prime editing), is provided. The major challenges that remain before splice-targeting therapeutics can be targeted to treat cardiovascular disease are highlighted. Lessons from neuromuscular indications establish clinical feasibility of splicing correction and motivate translation to cardiology. Together, mechanistic insight, biomarker development, and therapeutic innovation position RNA splicing as a tractable axis for precision cardiovascular medicine.

Humans↗
PubMed2026

Comparative analysis of olfactory receptor repertoires reveals evolutionary dynamics and high-altitude adaptation in Schizopygopsis younghusbandi based on the chromosome-level genomes.

The olfactory receptor (OR) gene represent a significant multigene family in vertebrates, forming the core molecular basis of olfactory perception and playing a crucial role in the environmental adaptation of species. High-altitude ecosystems represent extreme habitats characterized by specific abiotic stresses, including low oxygen levels, low temperatures, and intense ultraviolet radiation. These environments also exhibit low aquatic biodiversity and a limited variety of odor molecules, factors that have influenced the adaptive evolution of the sensory systems in endemic species. However, the genetic mechanisms underlying olfactory adaptation in high-altitude freshwater fish remained inadequately understood. In this study, we performed comparative genomics analyses to reveal the evolutionary processes underlying the adaptive and functional evolution of OR genes in S. younghusbandi, a cyprinid fish endemic to the Qinghai-Xizang Plateau. The results indicated that, compared to their low-altitude relatives, S. younghusbandi possessed a significantly smaller number of OR genes, with only 98 genes, which revealed the contraction of the gene family. Phylogenetic analysis revealed that the OR genes of cyprinid fish could be categorized into two major lineages: type I and type II. The &#x3b7; and &#x3b4; families, which perceive water-soluble odors, in S. younghusbandi underwent significant and specific expansion, while the &#x3b5; family was completely absent. This pattern reflected adaptive changes in olfactory recognition to accommodate the simplified odor spectrum of high-altitude water bodies. Chromosomal localization analysis demonstrated that OR genes were clustered, and collinearity analysis confirmed the presence of conserved genomic fragments among species. Selection pressure analysis revealed that the Ka/Ks values of all homologous gene pairs were less than 1, indicating that the OR genes of S. younghusbandi underwent strong purifying selection as a group to preserve core olfactory function. A few genes exhibited relaxed selection characteristics, which may have facilitated the fine-tuning of adaptability to high-altitude environments. In conclusion, this study elucidated the evolutionary dynamics and adaptive characteristics of the OR gene in S. younghusbandi, offering a new perspective on the molecular mechanisms underlying olfactory adaptation at high altitudes and enriching the research on sensory evolution in vertebrates.

Schizopygopsis younghusbandi↗
PubMed2026

PAT: An Image Analysis Tool for Automated Scoring of Pollen in Alexander-Stained Anthers.

Quantitative pollen viability analysis is a critical but labor-intensive step in plant reproductive biology. Existing deep-learning Segment Anything Models (SAM) fail to reliably segment viable pollen in Alexander-stained anthers. To address this, we fine-tuned an existing Cellpose-SAM model for pollen segmentation. We integrated it into PAT (Pollen Analysis Tool), a cross-platform desktop application. PAT features instance segmentation with interactive quality control, an in-app model retraining module, and publication-ready statistical outputs. We deployed PAT in an EMS suppressor screen of semi-sterile Arabidopsis smg7-6 mutants, enabling efficient candidate prioritization for whole-genome sequencing and mapping of the candidate mutation. This screen led to the identification of a point mutation in CAP-D2 (capd2-2), a Condensin I subunit, that rescues the smg7-6 meiotic phenotype. Notably, mutation in a Condensin II subunits (CAP-D3 and CAP-H2) does not confer rescue. Further characterization suggests the capd2-2 allele is hypomorphic, showing no defects in vegetative growth, chromocenter compaction, or transposable element silencing. Collectively, we demonstrate that accessible AI tools have the potential to bridge gaps in plant phenotyping and accelerate the pace of biological discovery.

Alexander staining↗
PubMed2026

The R2R3-MYB transcription factor ScMYB20 negatively regulates drought and salt tolerance through a dual-repression of ScCHALCONE SYNTHASE-1 (ScCHS1)-mediated flavonoid biosynthesis in the desert moss Syntrichia caninervis.

The desert moss Syntrichia caninervis is one of the most desiccation-tolerant land plants known and provides a powerful system for dissecting the molecular foundations of extreme stress adaptation in early-diverging land lineages. The MYB transcription factor superfamily orchestrates secondary metabolism and stress signaling across plants, yet its lineage-specific evolution and mechanistic deployment in bryophytes remain poorly understood. Here, we identified 65 ScMYB genes in the S. caninervis genome and showed that the family expanded predominantly through dispersed duplication, with no detectable synteny to vascular-plant MYBs, indicating bryophyte-specific neo-functionalization. Integrating phylogenetic clustering, cis-element architecture and stress-responsive expression profiling, we pinpointed ScMYB20, a nuclear-localized, S13-subgroup R2R3-MYB that is rapidly and strongly induced by dehydration and salinity. Heterologous overexpression in Arabidopsis, together with overexpression and RNAi in S. caninervis, demonstrated that ScMYB20 negatively regulates drought and salt tolerance by suppressing antioxidant capacity, osmotic adjustment and photosynthetic performance, while concomitantly elevating ROS and MDA accumulation. Mechanistically, ScMYB20 directly binds a TAACCA motif in the ScCHS1 promoter to repress its transcription, and simultaneously sequesters the WD40 protein ScTTG1, a positive transcriptional activator of ScCHS1, thereby antagonising ScTTG1-mediated activation. Transient ScCHS1 overexpression restored flavonoid accumulation, antioxidant capacity and stress tolerance. Together, our findings define a dual-repression module (ScMYB20-ScTTG1-ScCHS1) that fine-tunes flavonoid flux under abiotic stress, and provide evolutionary and mechanistic insights into how R2R3-MYB repressors evolved to balance metabolic investment and stress survival in land plants.

Syntrichia caninervis↗