Biology subjects

Deng, F.

Publications and source records attributed to Deng, F..

At least 19 recordsLinked to original sources

bioRxiv2026

Modular split-trigger based cooperative activation platform for Cas13-12 tandem biosensing system

Achieving precise control of CRISPR/Cas trans-cleavage depends on understanding how nucleic acid activators engage Cas effectors, yet the fundamental principles of split-trigger activation of Cas12a remain unclear. Here, we uncover the mechanistic determinants that enable fragmented nucleic acids to collectively initiate Cas12a activity. We show that split triggers bearing external extensions fully support the R-loop formation, whereas internal extensions which disrupt the spacer complementarity abolish Csa12a activation. We further demonstrate that covalent linkage of split-trigger fragments prevents R-loop propagation, revealing that Cas12as activation strictly requires two physically independent split fragments. Together, these findings establish a synergistic split-trigger activation mechanism in which cooperative hybridization of two individually fragments nucleates and extends the Cas12a R-loop with high efficiency. Conceptually, this mechanism enables a cascade architecture that transforms CRISPR diagnostics from a one-target one-Cas ribonucleoprotein (RNP) paradigm into a highly amplifying process in which a single target molecule activates numerous downstream Cas RNPs. Building on this principle, we show that the cleavage of a rationally designed linear DNA-RNA-DNA mediator by LbuCas13a generates optimally configured split triggers for Cas12a activation, thereby coupling RNA recognition to large-scale Cas12a activation without enzymatic preamplification. The resulting Split Trigger Activated Cas13-Cas12 Cascade System (STACS) achieves amplification-free detection down to 1 copy/{micro}L within 15 minutes and maintains robust performance in complex biological (serum, saliva) and environmental (mud) matrices. This work establishes a generalizable strategy for engineering programmable CRISPR cascades with high Cas RNP activation multiplicity for ultrasensitive molecular diagnostics. Graphic abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=102 SRC="FIGDIR/small/734747v2_ufig1.gif" ALT="Figure 1"> View larger version (18K): org.highwire.dtl.DTLVardef@104a609org.highwire.dtl.DTLVardef@30cebcorg.highwire.dtl.DTLVardef@54b15borg.highwire.dtl.DTLVardef@47f89e_HPS_FORMAT_FIGEXP M_FIG C_FIG Mechanism and detection workflow of the Split Trigger Activated Cas13-12 Cascade System (STACS).

Molecular Biology↗

bioRxiv2026

Anthocyanin-associated cellular programs underlying terroir variation in Cabernet Sauvignon grape berry revealed by SEED-based deconvolution

Plant tissues consist of diverse cell populations that collectively contribute to development, metabolism, environmental responses, and phenotype formation. Although single-cell and single-nucleus RNA sequencing have greatly advanced the study of plant cellular heterogeneity, their application to large sample cohorts remains limited by cost, technical complexity, tissue dissociation constraints, and throughput. In contrast, bulk RNA-seq datasets have accumulated extensively across plant species, tissues, developmental stages, and environmental conditions, yet the celltype-level information embedded in these datasets remains difficult to resolve because plant-oriented deconvolution frameworks are still lacking. Existing deconvolution methods have largely been developed in mammalian systems and have not been systematically optimized for plant transcriptomic features, leaving their applicability under plant-specific constraints unclear. Here, we present SEED, an adaptive deconvolution framework optimized for plant transcriptomic data. SEED integrates candidate reference-template construction with seven deconvolution strategies and automatically identifies an optimal combination for a given dataset. In grapevine simulated benchmarking, SEED showed its clearest advantage under low-replication conditions and remained broadly competitive, rather than uniformly dominant, when larger pseudo-bulk sample sizes were evaluated. SEED further performed robustly in public Arabidopsis thaliana and Nicotiana tabacum datasets. Finally, we applied SEED to bulk RNA-seq data generated in this study from Vitis vinifera cv. Cabernet Sauvignon berries collected from Yinchuan and Yantai, identifying terroir-associated cell subtypes and coordinated celltype interaction patterns. Together, these results establish SEED as a practical framework for plant transcriptome deconvolution and provide a new tool for dissecting cellular heterogeneity associated with environmental adaptation and phenotype formation in plants.

bioinformatics↗

bioRxiv2026

Reveal Principles of Codon Optimization via Machine Learning

High level of protein expression is usually welcomed in industry and research, and codon optimization is widely used to achieve high expression. Methods of implementing codon optimization can be divided into two branches, one is classical methods which develop cost functions based on empirical law, another is AI methods which learn the codon choice principles from endogenous genes with neural networks. Here we develop two codon optimization tools based on two branches respectively, namely OptimWiz 2.1 and OptimWiz 3.0. Results of fusion protein fluorescence detection indicate that both OptimWiz 2.1 and OptimWiz 3.0 are superior to all the other commercially available codon optimization tools. Principles of codon optimization are revealed in the process of machine learning on both tools.

bioinformatics↗

bioRxiv2026

Photo-downregulation of SIRT4 mitigates aging in mice by enhancing H3K9ac via fatty acid metabolism

As organisms age, mitochondrial metabolic activity declines, and disrupted gene expression regulation mediated by histone acetylation induces the emergence of senescent physiological phenotypes in tissues. In this study, we found that periodic exposure to red light significantly increased histone H3 Lys9 acetylation (H3K9ac) levels in the tissues and organs of aged mice. Following red light exposure, silent information regulation factor 4 (SIRT4) protein levels in keratinocytes were notably reduced, whereas glycolysis, fatty acid metabolism, and the tricarboxylic acid (TCA) cycle were significantly activated in keratinocytes. The reduction in mitochondrial SIRT4 levels enhances the acetylation of mitochondrial metabolic proteins, particularly malonyl-CoA decarboxylase (MCD), a potent inhibitor of the key rate-limiting enzyme carnitine palmitoyltransferase 1A (CPT1A) in fatty acid oxidation. This process promotes mitochondrial fatty acid oxidation and TCA cycle. Additionally, the decrease in SIRT4 activates SIRT1 through feedback mechanisms, thereby alleviating its inhibition on PPAR- in senescent keratinocytes and comprehensively activating the expression of genes related to lipid metabolism. This lipid metabolism activation ultimately facilitates the accumulation of acetyl-CoA within keratinocytes, increases H3K9ac levels, and reshapes the expression patterns of senescence-related genes. Eventually, cellular aging is effectively mitigated by the synergistic regulation of metabolism, inflammation, and gene expression. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=156 SRC="FIGDIR/small/717004v2_ufig1.gif" ALT="Figure 1"> View larger version (82K): org.highwire.dtl.DTLVardef@ba3865org.highwire.dtl.DTLVardef@1cc9a58org.highwire.dtl.DTLVardef@1a90e7borg.highwire.dtl.DTLVardef@1f5e88f_HPS_FORMAT_FIGEXP M_FIG C_FIG Graphical AbstractMechanism of anti-aging action of red light: Red light can reduce SIRT4 signalling in keratinocytes, thereby reactivating lipid metabolism and increasing levels of acetyl-CoA. This promotes histone acetylation, which in turn remodels the expression of age-related inflammatory factors and genes.

cell biology↗

bioRxiv2026

Discovery of metabolites produced by reactions between central carbon metabolites and cysteine that mark inflammatory macrophages

Identifying metabolites and metabolic reactions specific to a cellular state, such as inflammatory state in immune cells, is of great interest, as it can provide important biomarkers and point to compounds and reactions of specific biological functions. However, many cell state-specific metabolites remain in the unannotated part of metabolome. Here we identified a series of sulfur-containing metabolites that are actively produced in macrophages upon classical activation, but not in resting state or alternative activation state. Isotopic tracing, in vitro assays and genetic perturbations further revealed that they are formed from reactions between free cysteine and several important intermediates in glycolysis and TCA cycle. Upon classical activation, macrophages specifically upregulate the import of cystine via Slc7a11, supporting the production of these adducts. Their production dynamically responds to changes in central metabolism, environmental nutrient levels, and is regulated by nitric oxide. Finally, we confirmed these newly identified compounds also present in human samples, and most of them are significantly elevated in inflammatory granuloma annulare lesions. This work elucidated a previously uncharted part of metabolic network that is associated with inflammation and metabolic stress condition, which has important implications and set foundation for many future discoveries.

biochemistry↗

bioRxiv2026

Myristoylation licenses disordered viral VP4 protein to anchor to and perforate the membrane through phase separation

The VP4 protein of enteroviruses, such as Coxsackievirus B3, is a small, intrinsically disordered protein essential for perforating the host cell membrane during viral entry. A key feature of VP4 is its N-terminal myristoylation, which is required for infectivity in some enteroviruses but dispensable in others, suggesting a complex and context-dependent role that is not fully understood. The precise biophysical mechanisms by which this lipid anchor enables a disordered protein to breach a membrane remain unresolved. Here, using Coxsackievirus B3 VP4 as a model system and integrating multi-scale molecular dynamics simulations with confocal microscopy, we demonstrate that myristoylation is not a simple membrane tether but a multi-functional regulator that orchestrates VP4 activity through distinct, hierarchical roles. First, it provides the necessary hydrophobic anchor to recruit the disordered VP4 to the membrane interface. Second, the myristoyl group acts as a key molecular driver that promotes the liquid-liquid phase separation of VP4, leading to the formation of dynamic condensates on the membrane surface. These condensates actively remodel the membrane, generating substantial curvature that, in turn, lowers the free energy barrier for VP4 penetration. Furthermore, we find evidence that the myristoyl group plays a third role in stabilizing the final transmembrane pore. Our findings establish a novel paradigm where a single lipid modification empowers a disordered viral protein to form a functionally potent condensate that mechanically primes and physically breaches the target membrane, a mechanism that may explain the conditional myristoylation requirement across enteroviruses.

biophysics↗

bioRxiv2025

PKU tags, novel genetically encoded shape tags for cell labeling in light and electron microscopy

Distinguishing among neuronal cell types is crucial for deciphering complex neural networks and brain functions. However, the current repertoire of cell-labeling tools compatible with light microscopy (LM) and/or electron microscopy (EM) is limited compared to the vast number of cell types in the brain. Here, we introduce PKU (polymer king-size unit) tags, genetically encoded "shape tags" that leverage the polymerization of self-assembling proteins, spectrally distinct fluorescent proteins and, optionally, a nuclear targeting sequence to generate a series of multi-shaped (spherical or filamentous), multi-colored (blue, green, red, near-infrared) and multi-localized (cytosolic or nuclear) tags. By co-expressing multiple PKU tags within the same cell, a combinatorial strategy further expands the repertoire, which can theoretically yield hundreds of unique labeling patterns. Expressing PKU tags in vivo provides multi-cell-type labeling and neuronal circuit tracing, without altering the animals behavior or transcriptomic profiles. Moreover, when fused to the peroxidase APEX2, PKU tags maintain their shape-specific features, providing shape "barcoding" using EM. Thus, PKU tags represent a versatile and efficient toolkit for studying connectomics using both LM and EM.

neuroscience↗

bioRxiv2025

Mosaic pattern: lung functional heterogeneity at the alveolus level

Inhaled particles carrying pathogens, pollutants (e.g., microplastics, smoke), therapeutics, and diagnostics are increasingly relevant to public health, yet real-time tracking of aerosol transport in functional alveoli remains challenging. Here, we used the recently developed crystal ribcage to investigate aerosol transport in ex vivo lungs during active ventilation, obtaining the first real-time observations of single aerosol droplet transport and deposition in functional alveoli. We discovered deterministic heterogeneity at both intra- and inter-alveolar levels, with aerosol distribution forming a characteristic "mosaic" pattern in which only specific alveolar clusters received particles. The pattern was consistently formed in vivo during spontaneous breathing and ex vivo using both positive- and negative-pressure ventilation. This pattern was also consistent across a range of aerosols, including small molecules, nanobodies, nanoparticles, microplastics, therapeutics, and pathogens. Additionally, the pattern was observed in murine, porcine, and human lungs, and evolved from birth through aging in mice. The post-deposition stability of the pattern depended on particle type and lung age, lasting from a few minutes for small molecular weight particles to multiple days for cell-binding particles. These alveolar-level heterogeneities may uncover previously unrecognized biological and immunological heterogeneities associated with the mosaic pattern, including its role in postnatal lung development, susceptibility to inhaled airborne hazards such as pollutants and infectious agents, and early pathogenesis and response to inhaled therapeutics in respiratory diseases such as pneumonia, COPD, asthma, and lung cancer.

bioengineering↗

bioRxiv2025

scSTAR2: a multiomics integration algorithm to reveal disease specific cellular signatures by bridging single-cell resolution features and clinical metadata

Single-cell techniques, pivotal in characterizing intricate cell and spatial structures within tissues, face challenges in contextualizing clinical phenotypes. Currently, most investigations of the clinical phenotype related cell/spatial heterogeneities relied on the phenotype information from single-cell data. However, a wealth of underutilized clinical metadata exists within conventional bulk sequencing data. Current methods for correlating clinical information with individual cells or spatial regions remain limited and lack robustness. Here we present scSTAR2, a novel algorithm that transcends existing limitations by reconstructively integrating multiomics data to identify cells associated with clinical phenotypes. Unlike existing methods, scSTAR2 reconstructs single-cell data guided by specific phenotypes, significantly reducing interference from irrelevant noise. By employing scSTAR2 to integrate scRNA-seq, scATAC-seq, and spatial transcriptomics and bulk RNA-seq, we not only confirmed a new heat-shock Treg subtype in tumors but also more sensitively identified TLS (tertiary lymphoid structure) areas than traditional methods. In conclusion, scSTAR2 has proven to significantly enhance single-cell data interpretation across diverse clinical scenarios.

bioinformatics↗

bioRxiv2025

Serotonin shapes the temporal window for associative fear learning

Fear learning is a critical adaptive mechanism that enables the association of an environmental cue (the conditioned stimulus, CS) with a potential threat (the unconditioned stimulus, US), even when these events are temporally discontiguous. When associations are instead formed between unrelated cues and threats, the maladaptive learning process can give rise to neurological disorders. Therefore, maintaining accurate temporal boundaries for forming such associations is crucial for distinguishing real threats from irrelevant stimuli. Despite its importance, the mechanisms defining this precise time window remain poorly understood. Here, we report that serotonin plays a crucial role in modulating the associable interval in trace fear conditioning. Specifically, we show that serotonergic projections from the dorsal raphe nuclei (DRN) to the CA1 region of the ventral hippocampus (vCA1) dynamically regulate the association of discontiguous CS and US. Mechanistically, we demonstrate that sustained serotonin release in the vCA1 maintains the ensemble activity of 5-HT2C receptor-expressing pyramidal neurons, facilitating the association between temporally separated events. In contrast, when the trace interval exceeds the associable window, transient serotonin release fails to drive vCA1 neuronal ensemble activity, thus preventing maladaptive learning. These findings highlight a key role for serotonin in regulating the temporal precision of fear learning and reveal the DRN-vCA1 serotonergic pathway as a potential therapeutic target for related disorders.

neuroscience↗

bioRxiv2025

Concerted actions of distinct serotonin neurons orchestrate female pup care behavior

In many mammalian species, female behavior towards infant conspecifics changes across reproductive stages. Sexually naive females interact minimally or aggressively with infants, whereas the same animals exhibit extensive care behavior, even towards unrelated infants, after parturition1-6. Here, we discovered that two distinct sets of serotonin neurons collectively mediate this dramatic transition in maternal behavior--serotonin neurons projecting to the medial preoptic area (mPOA) promote pup care in mothers, whereas those projecting to the bed nucleus of the stria terminalis (BNST) suppress pup interaction in virgin female mice. Disrupting serotonin synthesis in either of these subpopulations or stimulating either subpopulation is sufficient to toggle pup-directed behavior between that displayed by virgin females and that of lactating mothers. In virgin female mice, the first pup interaction triggers an increase in serotonin release in BNST but a decrease in mPOA. In mothers, serotonin activity becomes greatly elevated in mPOA during pup interactions. Acute interruption of serotonin signaling locally in either mPOA or BNST disrupts the stage-dependent switch in pup care. Together, these results highlight how functionally distinct serotonin subpopulations orchestrate social behaviors appropriate for a given reproductive state, and suggest a circuit logic for how a neuromodulator coordinates adaptive behavioral changes across life stages.

neuroscience↗

bioRxiv2025

From Development to Regeneration: Insights into Flight Muscle Adaptations from Bat Muscle Cell Lines

Skeletal muscle regeneration depends on muscle stem cells, which give rise to myoblasts that drive muscle growth, repair, and maintenance. In bats--the only mammals capable of powered flight--these processes must also sustain contractile performance under extreme mechanical and metabolic stress. However, the cellular and molecular mechanisms underlying bat muscle physiology remain largely unknown. To enable mechanistic investigation of these traits (Graphical Abstract), we established the first myoblast cell lines from the pectoralis muscle of Pteronotus mesoamericanus, a highly maneuverable aerial insectivore. Using both spontaneous immortalization and exogenous hTERT/CDK4 overexpression, we generated two stable cell lines that retain proliferative capacity and differentiate into contractile myotubes. These cells exhibit frequent spontaneous contractions, suggesting robust functional integrity at the neuromuscular junction. In parallel, we performed transcriptomic and metabolic profiling of native pectoralis tissue to define molecular programs supporting muscle specialization. Gene expression analyses revealed enriched pathways for muscle metabolism, development, and regeneration, highlighting the supporting roles in tissue maintenance and repair. Consistent with this profile, the flight muscle is triglyceride-rich, which serves as an important fuel source for energetically demanding processes, including muscle contraction and cellular recovery. Integration of transcriptomic and metabolic data identified three key metabolic modules--glucose utilization, lipid handling, and nutrient signaling--that likely coordinate ATP production and support metabolic flexibility. Together, these complementary tools and datasets provide the first in vitro platform for investigating bat muscle research, enabling direct exploration of muscle regeneration, metabolic resilience, and evolutionary physiology. Graphical AbstractEstablishment of bat muscle cell cultures from the Mesoamerican mustached bat (P. mesoamericnus) provides an in vitro platform to investigate muscle regeneration and flight muscle biology. The pectoralis major muscle was isolated to generate primary myoblast cultures, which were expanded and immortalized using hTERT/CDK4. The resulting myoblast lines retain proliferative and differentiation capacity. RNA sequencing of native pectoralis muscle tissue revealed molecular signatures of myogenic regulation, stress resilience, and tissue remodeling, supporting the relevance of these in vitro models for studying muscle maintenance and regenerative mechanisms. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=127 SRC="FIGDIR/small/662643v1_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@490f49org.highwire.dtl.DTLVardef@8ab615org.highwire.dtl.DTLVardef@b840e1org.highwire.dtl.DTLVardef@ab92eb_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2025

Medial Frontal Theta Reduction Impairs Rule Switching via Prediction Error

Cognitive flexibility, the ability to switch behavior in response to changing rules in an uncertain environment, is crucial for adaptive decision making. Prior research has hypothesized a key role of prediction error and theta oscillations in medial frontal cortex in this process. However, the causal link between such processes remains to be established. To address this, we combined neural stimulation, EEG, behavioral measurement, and computational modelling. Specifically, we applied high-definition transcranial direct current stimulation (HD-tDCS) to modulate theta oscillations as measured via EEG followed by a probabilistic reversal learning task. We find that anodal stimulation reduces theta power and rule prediction error, and it increases the number of trials needed to reliably switch between rules. These findings support the role of rule prediction error signaling as a key mechanism linking neural oscillations to behavioral adaptation and highlight the importance of theta power and rule prediction error for cognitive flexibility. Significance statementCognitive flexibility--the ability to adjust behavior when rules change--is critical for adaptive behavior in uncertain environments. Although prediction error signaling and theta oscillations in medial frontal cortex have been proposed as key mechanisms, their causal relationship remains unclear. Here, we combine high-definition transcranial direct current stimulation (HD-tDCS), EEG, behavioral assessment, and computational modeling to establish a mechanistic link. We show that anodal stimulation reduces frontal theta power and rule-level prediction errors, leading to less efficient rule switching. These findings provide causal evidence that supports behavioral flexibility, advancing our understanding of the neural computations underlying adaptive decision making.

neuroscience↗

bioRxiv2025

A genetically encoded fluorescent sensor for monitoring spatiotemporal prostaglandin E2 dynamics in vivo

Prostaglandin E2 (PGE2) is an important lipid signaling molecule that regulates a wide range of physiological and pathological processes. However, its dynamics during these processes are largely unknown due to the lack of tools to directly visualize PGE2 with high spatiotemporal resolution. Here, we developed and characterized a genetically encoded PGE2 sensor, which we call GRABPGE2-1.0 (PGE2-1.0), that has high specificity for PGE2, nanomolar affinity, rapid kinetics, and high spatial resolution when expressed both in vitro and in vivo. Using fiber-photometry recordings, we found that PGE2-1.0 can reliably monitor endogenous PGE2 dynamics in the preoptic area in the brain during acute inflammation. The wide-field in vivo imaging with PGE2-1.0 reveals spatial heterogeneity in cortex-wide PGE2 dynamics during acute inflammation and seizure. Thus, our PGE2-1.0 sensor can be used to detect endogenous PGE2 dynamics with high spatiotemporal resolution, providing a robust tool for studying PGE2 under specific physiological and pathological conditions.

neuroscience↗

bioRxiv2025

Towards machine learning fairness in classifying multicategory causes of deaths in colorectal or lung cancer patients

Classification of patient multicategory survival outcomes is important for personalized cancer treatments. Machine Learning (ML) algorithms have increasingly been used to inform healthcare decisions, but these models are vulnerable to biases in data collection and algorithm creation. ML models have previously been shown to exhibit racial bias, but their fairness towards patients from different age and sex groups have yet to be studied. Therefore, we compared the multimetric performances of 5 ML models (random forests, multinomial logistic regression, linear support vector classifier, linear discriminant analysis, and multilayer perceptron) when classifying colorectal cancer patients (n=515) of various age, sex, and racial groups using the TCGA data. All five models exhibited biases for these sociodemographic groups. We then repeated the same process on lung adenocarcinoma (n=589) to validate our findings. Surprisingly, most models tended to perform more poorly overall for the largest sociodemographic groups. Methods to optimize model performance, including testing the model on merged age, sex, or racial groups, and creating a model trained on and used for an individual or merged sociodemographic group, show potential to reduce disparities in model performance for different groups. Notably, these methods may be used to improve ML fairness while avoiding penalizing the model for exhibiting bias and thus sacrificing overall performance.

bioinformatics↗

bioRxiv2024

In vivo multiplex imaging of dynamic neurochemical networks with designed far-red dopamine sensors

Neurochemical signals like dopamine (DA) play a crucial role in a variety of brain functions through intricate interactions with other neuromodulators and intracellular signaling pathways. However, studying these complex networks has been hindered by the challenge of detecting multiple neurochemicals in vivo simultaneously. To overcome this limitation, we developed a single-protein chemigenetic DA sensor, HaloDA1.0, which combines a cpHaloTag-chemical dye approach with the G protein-coupled receptor activation-based (GRAB) strategy, providing high sensitivity for DA, sub-second response kinetics, and an extensive spectral range from far-red to near-infrared. When used together with existing green and red fluorescent neuromodulator sensors, Ca2+ indicators, cAMP sensors, and optogenetic tools, HaloDA1.0 provides high versatility for multiplex imaging in cultured neurons, brain slices, and behaving animals, facilitating in-depth studies of dynamic neurochemical networks.

neuroscience↗

bioRxiv2024

Perinatal serotonin signalling dynamically influences the development of cortical GABAergic circuits with consequences for lifelong sensory encoding

Serotonin plays a prominent role in neurodevelopment, regulating processes from cell division to synaptic connectivity1,2. Clinical studies suggest that alterations in serotonin signalling such as genetic polymorphisms3-5 or antidepressant exposure during pregnancy6,7 are risk factors for neurodevelopmental disorders. However, an understanding of how dysfunctional neuromodulation alters systems level activity over neocortical development is lacking. Here, we use a longitudinal imaging approach to investigate how genetics, pharmacology, and aversive experience disrupt state-dependent serotonin signalling with pathological consequences for sensory processing. We find that all three factors lead to increased neocortical serotonin levels during the initial postnatal period. Genetic deletion of the serotonin transporter or antidepressant dosing results in a switch from hypo- to hyper-cortical activity that arises as a consequence of altered cortical GABAergic microcircuitry. However, the trajectories of these manipulations differ with postnatal exposure to antidepressants having effects on adult sensory encoding. The latter is not seen in the genetic model despite a similar early phenotype, and a distinct influence of maternal genotype on the development of supragranular layers. These results reveal the dynamics and critical nature of serotonin signalling during perinatal life; pharmacological targeting of which can have profound life-long consequences for cognitive development of the offspring.

neuroscience↗

bioRxiv2024

Genomic and evolutionary evidence for drought adaptation of grass allopolyploid Brachypodium hybridum

Climate change increases the frequency and severity of drought worldwide, threatening the environmental resilience of cultivated grasses. However, the genetic diversity in many wild grasses could contribute to the development of climate-adapted varieties. Here, we elucidated the impact of polyploidy on drought response using allotetraploid Brachypodium hybridum (Bh) and its progenitor diploid species B. stacei (Bs). Our findings suggest that progenitor species genomic legacies resulting from hybridization and whole-genome duplications conferred greater ecological adaptive advantages to Bh over Bs. Genes related to stomatal regulation and immune response from S-subgenomes were under positive selection during speciation, underscoring their evolutionary importance in adapting to environmental stresses. Biased expression in polyploid subgenomes [B. stacei-type (Bhs) and B. distachyon-type (Bhd)] significantly influenced differential gene expression, with the dominant subgenome exhibiting more differential expression. B. hybridum adapted a drought escape strategy characterized by higher photosynthetic capacity and lower WUEi than Bs, driven by a highly correlated co-expression network involving genes in the circadian rhythm pathway. In summary, our study showed the influence of polyploidy on ecological and environmental adaptation and resilience in model Brachypodium grasses. These insights hold promise for informing the breeding of climate-resilient cereal crops and pasture grasses.

evolutionary biology↗