Biology subjects

Du, H.

Publications and source records attributed to Du, H..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

Microcompartments in Hodarchaeales: a bioenergetic engine that could have fuelled eukaryogenesis

Eukaryotic intracellular compartmentalization is a key innovation in the evolution of complex cellular life. While microcompartments enable metabolic specialization in many bacteria, to our knowledge, no analogous systems have been identified in Archaea. Here, we report the discovery of archaeal microcompartments (AMCs) in Hodarchaeales, an order within the phylum Promethearchaeati (Asgard archaea) that includes the closest known archaeal relatives of eukaryotes. Phylogenetic and structural analyses indicate that these catabolic AMCs, which are specialized for sugar-phosphate metabolism, were acquired by horizontal gene transfer from deep-rooted bacteria of the phylum Myxococcota. The shell pentamers of AMCs are fused to lysine/arginine-rich intrinsically disordered regions that capture cytosolic DNA, facilitating nutrient scavenging. Reaction-diffusion modelling predicts that enzyme colocalization and substrate channelling within AMCs can increase the NADH flux approximately 100-fold. Thus, the AMCs substantially boost energy production in the cell and might have primed the archaeal host for eukaryogenesis.

microbiology↗

bioRxiv2025

Association of cytochrome c oxidase dysfunction with amyloidosis in Alzheimer's disease and patient-derived cerebral organoids

Patients with Alzheimers disease (AD) demonstrate brain mitochondrial dysfunction and energy deficiency that are closely associated with cognitive impairment. Cytochrome c oxidase (CCO), also known as mitochondrial complex IV, is the terminal enzyme in mitochondrial electron transport chain (ETC). Consistent with the pivotal role of CCO in mitochondrial bioenergetics and high demand for energy to sustain neuronal function, CCO dysfunction has been linked to neurological disorders including AD. However, it remains unclear whether mitochondrial CCO dysfunction represents an adaptive response to AD-associated toxic molecules versus a bona fide pathology to promote AD development. In this study, by meta-analysis of publicly available proteomics analysis of post-mortem frontal lobe tissues from four large cohorts of patients with AD we identified loss of key CCO subunits including mitochondrial DNA (mtDNA)-encoded COX1 and COX3 as well as nuclear DNA (nDNA)-encoded COX5A, COX6B1, COX7C, COX8A, and NDUFA4 in patients with AD. Further biochemical analysis using post-mortem frontal lobe tissues showed lowered CCO activity of neuronal mitochondria from patients with AD, suggesting CCO vulnerability and its potential association with amyloidosis in AD. Lastly, in addition to the inverse relationship between neuronal CCO activity and brain amyloidosis in the tested AD cohort, pharmacological inhibition of CCO promoted amyloid production and elevated beta-secretase 1 (BACE1) activity in cerebral organoids derived from human induced pluripotent stem cells (hiPSCs) from one nonAD and one AD subject. The simplest interpretation of the results is that CCO dysfunction in the frontal lobe is a phenotypic mitochondrial change accompanying AD, which may contribute to the development of brain amyloidosis.

neuroscience↗

bioRxiv2025

Vaccine Elicitation of HIV-1 Neutralizing Antibodies Against Both V2 Apex and Fusion Peptide in Rhesus Macaques

Broadly neutralizing antibodies targeting multiple sites of HIV-1 Env vulnerability can be induced by infection, but simultaneous elicitation of neutralizing antibodies (NAbs) against multiple epitopes has not yet been achieved by vaccination. In this study, we designed a dual-epitope vaccine targeting both fusion peptide (FP) and V2 apex and evaluated its capacity to induce NAbs against both epitopes in rhesus macaques. This vaccine combined an FP conjugate with a cocktail of engineered Env trimers with enhanced V2 apex recognition and increased antigen retention in lymph nodes. Immunization of macaques with the dual-epitope vaccine elicited >1000-fold higher autologous tier 2-neutralization titers than the wildtype Env trimer and enhanced heterologous NAb breadth. Both FP and V2-apex monoclonal antibodies (mAb) were isolated from immunized macaques and showed heterologous neutralization with genetic and structural signatures that were similar to well-characterized FP and V2 apex bNAbs, although the V2 apex mAbs showed incomplete maturation. These results demonstrate proof-of-concept for simultaneous vaccine elicitation of NAbs against multiple sites of Env vulnerability, which will likely be critical for an effective HIV-1 vaccine. HIGHLIGHTSO_LIDesigned a dual-epitope vaccine targeting both fusion peptide (FP) and V2 apex C_LIO_LIV2-SET Env trimer conferred higher binding of V2 apex bNAbs, longer retention in draining lymph nodes, and >1000-fold higher induction of autologous neutralization titers compared with wildtype Env trimer C_LIO_LIDual-epitope vaccine enhanced serum tier 2 neutralization breadth C_LIO_LIDual-epitope vaccine elicited FP- and V2 apex-specific neutralizing mAbs with genetic signatures similar to well-characterized FP and V2 apex bNAbs C_LI

immunology↗

bioRxiv2025

Impact of Partition Models on Phylogenetic Inference and Divergence Times of Lampyridae from Mitochondrial Genomes

Mitochondrial genomes are frequently used for phylogenetic inference due to their availability and cost-efficient sequencing. In most mitogenomic phylogenetic analyses, only the two ribosomal RNA and 13 protein coding genes are used. For such multi-locus datasets it has long been established that appropriate data partition models, e.g., partitioning by gene type and/or codon position, are necessary for robust phylogenetic inference. While most studies focused on the impact of partition models on the tree topology, little is known about the impact on divergence time estimation. Furthermore, although modeling among site rate variation within a partition is common practice, the extent of substitution rate variation among partitions is less explored. Here we study the impact of four partition model strategies: (i) no subdivision of the data (uniform), (ii) partitioning by gene, (iii) partitioning by codon position, and (iv) partitioning by both gene and codon position (combined). We explore the impact of partition models on divergence time estimation in fireflies (Coleoptera: Lampyridae). To this end, we sequenced mitochondrial genomes from 22 firefly species from Europe and Central America and combined these with 82 published mitochondrial genomes. Our results represent the most comprehensive time-calibrated phylogeny of fireflies to day. While the partition models had an impact on the inferred tree topology, the divergence times were almost not affected. Furthermore, we observed up to 3-fold substitution rate variation across genes and additionally more than to 10-fold substitution rate variation across codon positions. Our study gives insights into best practices of performing partitioned-data time-calibrated phylogenetic inference from mitochondrial genomes and multi-locus datasets in general.

evolutionary biology↗

bioRxiv2025

CellOntologyMapper: Consensus mapping of cell type annotation

Single-cell RNA sequencing has revolutionized cellular biology, with atlases now encompassing over 100 million cells. However, researchers employ vastly different naming conventions when annotating cell types, creating a fragmented landscape that severely impedes data integration and comparative analysis. Here, we present CellOntologyMapper, an automated framework that standardizes cell type annotations by intelligently mapping user-defined names to established Cell Ontology and Cell Taxonomy identifiers. Our approach leverages advanced natural language processing, including sentence transformers and large language models, to interpret diverse naming conventions and resolve them to standardized ontological terms. The system handles complex challenges including abbreviated cell names, synonym resolution, and context-dependent interpretation. We built a comprehensive query system based on 19,381 cell type entries from established Cell Ontology and Cell Taxonomy databases, which organize into 24 biologically coherent clusters. Systematic validation across datasets spanning different scales-- from 17-cell-type lung studies to 91-cell-type immune atlases and complex developmental systems--consistently demonstrated robust performance and high accuracy. CellOntologyMapper successfully resolved annotation challenges across conventional tissue studies, rare cell populations, and developmentally intricate datasets rich in abbreviated nomenclature. By providing automated, scalable annotation harmonization, our framework enables researchers to leverage existing single-cell datasets while ensuring compatibility with future atlas efforts. When incorporated into publications, CellOntologyMapper enhances the credibility and reference value of cell type annotations, representing a crucial step toward an integrated single-cell genomics ecosystem.

bioinformatics↗

bioRxiv2025

Cytoprotective roles of "E3 ubiquitin ligases-NF-κB-autophagy" axis in Pacific oysters Crassostrea gigas exposed to phenanthrene

Phenanthrene (PHE), as one of the most frequently found polycyclic aromatic hydrocarbons can induce immunotoxicity, oxidative stress, and endocrine disruption in marine organisms. However, whether autophagy can be induced by PHE and the regulatory mechanism and cytoprotective roles of autophagy under PHE stress condition have not been unveiled. Our data first unveil a "E3 ubiquitin ligases-NF-{kappa}B-autophagy" axis, which play cytoprotective roles in Pacific oysters Crassostrea gigas exposed to PHE. The results of confocal laser scanning microscope, flow cytometry and transmission electron microscope confirmed that PHE could induce autophagy in the haemocytes of Pacific oysters, and the presence of autophagosomes was also confirmed. The proteomics results showed that the expression of the E3 ubiquitin ligase HUWE1, TRIM36, and autophagy-related protein 7 (ATG7) were significantly upregulated. The expression of genes of the "axis" were significantly upregulated, and the expression of genes of autophagy was downregulated after the inhibition of the NF-{kappa}B, indicating that the expression of the "axis"-related genes can be stimulated by PHE, and thus autophagy is activated. The upregulation of the expression of "axis"-related genes in mouse macrophages, further demonstrating the existence of the "axis" proposed by this study and the "axis" can be activated by PHE. Incorporating with changes of cell number, apoptosis rate, phagocytic capacity, and ROS levels of lymphocytes, we demonstrated that autophagy plays a cytoprotective role in cellular defence against PHE. This study proposed a novel pathway and supplied a comprehensive understanding of the protective role of autophagy in Pacific oysters to cope with pollutants.

cell biology↗

bioRxiv2025

The cortical scene processing network emerges in infancy, prior to independent navigation experience

Sighted people rely on vision to recognize and navigate the local environment. By adulthood, human cortex contains at least three regions that respond selectively to visual scene information, but it remains unknown when or how these regions develop. One hypothesis is that scene selectivity emerges gradually in regions that initially prefer certain low-level visual features (e.g., peripheral visual input, high spatial frequencies, rectilinearity), and then exposure to the visual statistics of natural scenes drives the emergence of scene selective responses. However, both aspects of this hypothesis remain to be tested: how early scene selectivity first arises in human development, and whether it is driven by passive exposure to visual statistics. We therefore collected functional magnetic resonance imaging data from awake 2-9-month-old infants while they watched videos of real-world scenes with ego-motion, as well as faces, objects, and scrambled videos. We found stronger responses to scenes than control conditions in the location of all three scene regions. Scene-selective responses could not be explained by low-level visual properties of the stimuli, and were found in infants as young as 2-5 months old, with no evidence of age-related change. We also measured infants experience independently navigating (e.g., crawling), which was not necessary for the development of scene-selectivity. In sum, cortical regions are scene-selective in human infants prior to independent navigation, and after only limited exposure to visual scene statistics. Significance statementDespite extensive work on the functional organization of scene processing in the human adult visual cortex, little is known about the developmental origins of category selectivity for visual scenes. Here we used fMRI in awake human infants to discover that all three regions of the known visual scene processing system are present within the first few months of life - the youngest age yet detected. Scene-selective cortex therefore develops after only a few months of limited visual exposure, and prior to active experience using visual scene information to plan and guide independent navigation (e.g., by crawling). These findings provide a fundamental constraint on theories of how scene selectivity develops in high-level visual cortex.

neuroscience↗

bioRxiv2025

Developing a versatile technology for agroinfiltration in multiple plants

Agrobacterium-mediated transient transformation methods are widely used in plant science and molecular pharming. However, plant immune response and post-transcriptional gene silencing (PTGS) can compromise gene expression, limiting the adaptability of these methods across plant species. The lack of a robust reporter system further hinders advancements in agroinfiltration technology. To address these challenges, we developed a fungal bioluminescence pathway (FBP)-based reporter system that utilizes caffeic acid to generate self-sustained luminescence. By incorporating NahG and P19, our FBP assay enhances transient transformation efficiency in over 20 plant families, including major crops, vegetables, ornamental plants, and trees. Furthermore, we demonstrate its utility for assessing protein localization, interactions, and transcriptional regulation in multiple plant species, thereby broadening our understanding of gene function throughout the plant kingdom.

plant biology↗

bioRxiv2025

QuickProt: A Fast and Accurate Homology-Based Protein Annotation Tool for Non-Model Organism Genomes

Despite the increasing number of genomes, the annotation of protein-coding genes is still lacking. In some genomes where transcriptome data is not available, various tools have been developed to annotate genes based on homologous proteins, but each tool has its limitations. Here, we propose quickprot, a user-friendly command-line tool that constructs a set of redundancy-free gene models from the target genome based on the homologous protein sequences of a set of closely related species. We tested its applicability in stonefish, and the results showed that it has high accuracy and runs faster than existing tools. This low-cost, high-precision annotation method is expected to become a useful tool for genome annotation, which will contribute to the research of comparative genomics. The software is implemented in Python and licensed under the MIT License. The source code, documentation, and tutorials can be obtained at https://github.com/thecgs/quickprot.

bioinformatics↗

bioRxiv2025

Nicotinamide-loaded Peptoid Nanotubes for Energy Regeneration in Acute Brain Injury

Acute brain injuries such as perinatal asphyxia, stroke, and traumatic brain injury result in ischemia, oxidative stress, excitotoxicity, and inflammation, leading to a depletion of ATP, the brains cellular energy store. Nicotinamide adenine dinucleotide (NAD+), a key regulator of cellular homeostasis, is crucial for energy regeneration and DNA repair in post-injury recovery. However, the therapeutic benefits of NAD+ and its precursors, such as nicotinamide (NAM), are limited by the complexity of their metabolic pathways and challenges in effective cell-specific intracellular delivery. Therefore, cellular delivery strategies are needed to capture the potential of an NAD+-regenerating therapeutic approach. In this study, we introduce a nanopeptoid delivery strategy to replenish cellular redox state and energy production in the acutely injured brain. By self-assembling peptoids into tubular structures, we created biocompatible NAM-conjugated peptoid nanotubes (NAM-PNTs) that vary in tubular length. NAM-PNTs demonstrated significant therapeutic benefits by enhancing cell viability and replenishing intracellular ATP levels within 24 hours of treatment in oxygen-glucose deprived (OGD) BV-2 cells. In organotypic brain slices, NAM-PNT treatment promoted glial proliferation, reduced pro-inflammatory cytokine levels, and increased anti-inflammatory cytokines after OGD, an ex vivo model of hypoxia-ischemia. A single systemic dose of NAM-PNTs also reduced brain tissue loss and improved neuropathology after hypoxia-ischemia in term-equivalent rats. These findings highlight the strong therapeutic potential of NAM-PNTs for cell-specific targeted delivery and energy restoration in the acutely injured neonatal brain. In the neonatal brain injury field, this is the first demonstration of a novel nanoparticle platform development from first principles design and synthesis to in vitro screening and then demonstration of efficacy in vivo.

bioengineering↗

bioRxiv2025

FT-Kernel: An innovative kernel for decoding cellular secrets related time

The cell fate participants characterization based on single-cell RNA sequencing (scRNA-seq) data greatly facilitates the mechanism understandings of cellular differentiation. However, inferring these fate factors dynamics along the pseudotime is challenging. Based on cell-state density and pseudotime regression weights, we present an algorithm TimeFactorKernel (FT-Kernel), to predict the key cell fate factors, not only the minimum lineage transition genes, but also the related genesets/pathways, and cellular interaction dynamics along the pseudotime. By extrapolating the pseudotime-related key genes from spectral data as a pseudotime-kernel, FT-Kernel outperformed previous methods. Beyond time-related genes, FT-Kernel offered a comprehensive analysis of the inferred cellular interactions dynamics and lineage pathways dynamics along the pseudotime, which were limited in other methods. Additionally, it facilitated time-related fate factors prediction across various data modalities. Our work developed an important pseudotime-kernel in predicting the fate factors, and provided insights into the cellular hierarchies during development. SignificanceUnderstanding cellular changes over time is key to deciphering lifes processes from development to disease. Current single-cell methods miss crucial information by overlooking cell-state density dynamics and thus neglecting rare, low-density transitional states vital for cell fate decisions. TimeFactorKernel, a novel computational tool, overcomes this limitation. By prioritizing genes active in these low-density transitional states and employing machine learning for precise gene identification, TimeFactorKernel provides a powerful new approach to decode cell fate. Validated and widely adopted, TimeFactorKernel also uniquely models cell-cell interactions, opening new avenues for understanding complex biological systems in health and disease. KeypointsO_LIFT-Kernel is a novel kernel algorithm designed to predict time-related fate factors dynamics from the cell state density and pseudotime regression weights. C_LIO_LIFT-Kernel can be applied to identify lineage transition key genes, cellular interactions, and the multimodal fate kernel inference of genesets/pathways. C_LIO_LICompared to other temporal-related kernels, FT-Kernel minimizes the skewness of gene distribution and more accurately captures the state of fate transitions. C_LIO_LIFT-Kernel is an extensible multimodal framework facilitating to understand the mechanisms of cell differentiation and is available on GitHub. C_LI

bioinformatics↗

bioRxiv2025

Data retention in awake infant fMRI: Lessons from more than 750 scanning sessions

Functional magnetic resonance imaging (fMRI) in awake infants has the potential to reveal how the early developing brain gives rise to cognition and behavior. However, awake infant fMRI poses significant methodological challenges that have hampered wider adoption. The present work takes stock after the collection of a substantial amount of awake infant fMRI data across multiple studies from two labs at different institutions. These data were leveraged to glean insights on participant recruitment, experimental design, and data acquisition that could be useful to consider for future studies. Across 766 fMRI sessions with awake infants aged 1-36 months, the authors explored the factors that influenced how much usable data were obtained per session. The age of an infant predicted whether they would successfully enter the scanner (younger more likely) and, if they did enter, the number of minutes of functional data collected (linear, younger more) and retained after preprocessing with lab-specific protocols or harmonized motion exclusion thresholds (quadratic, 12-24 months more than younger and older). The amount of functional data retained was also influenced by assigned sex (female more), experimental paradigm (movies better than blocks and events), and stimulus content (social better than abstract). There were many differences in the research approach between labs making head-to-head comparisons difficult, but Yale was more likely to get infants into the scanner, MIT collected more data from infants who entered, and the amount of data retained after preprocessing did not differ statistically between labs (9 minutes). In addition, the authors assessed the value of attempting to collect multiple experiments per session, an approach that yielded more than one usable experiment averaging across all sessions. Although any given scan is unpredictable, these findings support the feasibility of awake infant fMRI and suggest practices to optimize future research.

neuroscience↗

bioRxiv2024

Predicting temozolomide response in low-grade glioma patients with large-scale machine learning

BackgroundTemozolomide is the primary chemotherapeutic agent and first-line treatment for low-grade glioma (LGG). Although LGGs are generally less aggressive than high-grade gliomas (HGGs), they can eventually progress into HGGs, making it crucial to maximise the efficacy of initial LGG treatment. MethodsIn this study, we analysed data from 109 LGG patients in The Cancer Genome Atlas (TCGA) to assess the predictive performance of 12 machine learning (ML) classification algorithms in forecasting temozolomide response, utilising six types of omics data. Cross-validation and bootstrapping bias correction were employed to compare the performance of these models with that of a conventional biomarker-based model using MGMT promoter methylation status. ResultsAmong the models, the miRNA-based approach using the XGBoost algorithm showed the most promising predictive performance, with a Matthews Correlation Coefficient (MCC) of 0.447, outperforming the auto-ML method JADBio (MCC = 0.250) and the MGMT biomarker-based model. Converting the task into a regression framework by encoding cancer response as a continuous variable generally weakened predictive performance, with best model based on methylation profile (MCC = 0.344). Additionally, ML models focusing on biomarker-relevant features demonstrated improved prediction accuracy, though not to the extent of omics-based models, with the support vector machine (SVM) model achieving an MCC of 0.331. Incorporating clinical variables, such as patient age and Karnofsky score, further enhanced predictive power, with the LR-OMC model achieving the highest MCC (0.483). Feature importance analysis identified six significant miRNA factors, including three tumour-related miRNAs (miR-335, let-7f, and miR-7-2) and three potential biomarkers (miR-204, miR-6513, and miR-376). DiscussionOverall, this study systematically demonstrates the potential of large-scale analyses combining machine learning and omics data to predict temozolomide response, offering superior predictive accuracy compared to standard MGMT biomarkers.

bioinformatics↗

bioRxiv2024

Substrate Stiffness Dictates Unique Doxorubicin-induced Senescence-associated Secretory Phenotypes and Transcriptomic Signatures in Human Pulmonary Fibroblasts

Cells are subjected to dynamic mechanical environments which impart forces and induce cellular responses. In age-related conditions like pulmonary fibrosis, there is both an increase in tissue stiffness and an accumulation of senescent cells. While senescent cells produce a senescence-associated secretory phenotype (SASP), the impact of physical stimuli on both cellular senescence and the SASP is not well understood. Here, we show that mechanical tension, modeled using cell culture substrate rigidity, influences senescent cell markers like SA-{beta}-gal and secretory phenotypes. Comparing human primary pulmonary fibroblasts (IMR-90) cultured on physiological (2 kPa), fibrotic (50 kPa), and plastic (approximately 3 GPa) substrates, followed by senescence induction using doxorubicin, we identified unique high-stiffness-driven secretory protein profiles using mass spectrometry and transcriptomic signatures, both showing an enrichment in collagen proteins. Consistently, clusters of p21+ cells are seen in fibrotic regions of bleomycin induced pulmonary fibrosis in mice. Computational meta-analysis of single-cell RNA sequencing datasets from human interstitial lung disease confirmed these stiffness SASP genes are highly expressed in disease fibroblasts and strongly correlate with mechanotransduction and senescence-related pathways. Thus, mechanical forces shape cell senescence and their secretory phenotypes.

cell biology↗

bioRxiv2024

VizCNV: An integrated platform for concurrent phased BAF and CNV analysis with trio genome sequencing data

BackgroundCopy number variation (CNV) is a class of genomic Structural Variation (SV) that underlie genomic disorders and can have profound implications for health. Short-read genome sequencing (sr-GS) enables CNV calling for genomic intervals of variable size and across multiple phenotypes. However, unresolved challenges include an overwhelming number of false-positive calls due to systematic biases from non-uniform read coverage and collapsed calls resulting from the abundance of paralogous segments and repetitive elements in the human genome. MethodsTo address these interpretative challenges, we developed VizCNV. The VizCNV computational tool for inspecting CNV calls uses various data signal sources from sr-GS data, including read depth, phased B-allele frequency, as well as benchmarking signals from other SV calling methods. The interactive features and view modes are adept for analyzing both chromosomal abnormalities [e.g., aneuploidy, segmental aneusomy, and chromosome translocations], gene exonic CNV and non-coding gene regulatory regions. In addition, VizCNV includes a built-in filter schema for trio genomes, prioritizing the detection of impactful germline CNVs, such as de novo CNVs. Upon computational optimization by fine-tuning parameters to maximize sensitivity and specificity, VizCNV demonstrated approximately 83.8% recall and 77.2% precision on the 1000 Genome Project data with an average coverage read depth of 30x. ResultsWe applied VizCNV to 39 families with primary immunodeficiency disease without a molecular diagnosis. With implemented build-in filter, we identified two de novo CNVs and 90 inherited CNVs >10 kb per trio. Genotype-phenotype analyses revealed that a compound heterozygous combination of a paternal 12.8 kb deletion of exon 5 and a maternal missense variant allele of DOCK8 are likely the molecular cause of one proband. ConclusionsVizCNV provides a robust platform for genome-wide relevant CNV discovery and visualization of such CNV using sr-GS data.

genomics↗

bioRxiv2024

Universal function of WRI1 involved in integrated regulation of multiple latex metabolism pathways in Natural Rubber

Hevea brasiliensis and Taraxacum kok-saghyz are sources of nature rubber (NR) and recent research has focused on finding a method to increase NR quality and production. NR consists mainly of cis-1,4-polyisoprene, which is synthesized from sucrose by a series of reactions during carbon metabolism. WRINKLED1 (WRI1) is a transcription factor (TF) that coordinates many genes involved in carbon metabolism and lipid biosynthesis. Here, we isolated and characterized two orthologues of WRI in rubber-producing plants H. brasiliensisa and T. kok-saghyz, which are highly expressed in their latex. Subcellular localization and ectopic expression in Arabidopsis thaliana indicated that the TFs, HbWRI1 and TkWRI1, are involved in lipid accumulation. Overexpression of HbWRI1 and TkWRI1 in T. kok-saghyz substantially enhanced NR quality and production, including dry rubber content, molecular weight, and the diameter of rubber particles in the latex. Conversely, they were decreased in TkWRI1 repression. Furthermore, based on the activated expression in transgenic T. kok-saghyz latex and the existence of AW-box element in the promoter regions, 16 direct downstream genes of HbWRI1 and TkWRI1 were identified by a dual-luciferase reporter assay and yeast one-hybrid assay, and their products were responsible for both NR biosynthesis and lipid metabolism. These results reveal a regulatory module that HbWRI1 and TkWRI1 TFs can positively regulate NR quality and production in T. kok-saghyz latex by synergistically regulating the entire NR biosynthesis. This module is expected to be utilized to develop superior varieties to enhance NR quality and production.

biochemistry↗

bioRxiv2024

Omega-3 fatty acid normalizes postsynaptic density proteins via miRNAs regulation in hippocampus and prevents DEHP-induced impairment of learning and memory in mice

AbstractsDEHP is the most widely used plasticizer in many products. However, growing evidence has indicated that DEHP may induce neurotoxicity. DEHP exposure affects mircoRNAs (miRNAs) expression in brain. A growing body of evidence suggests that nutrients and other bioactive food components prevent neurotoxicity through regulation of miRNA expression. Due to the increasing concern about the risks of DEHP to human health, we explored the neuroprotective effect of Omega-3 fatty acid (Omega-3FA) on subchronic DEHP-induced neurotoxicity in mice, and the potential involved miRNAs and their targets in the protective action of Omega-3FA against DEHP-induced neurotoxicity. Omega-3FA protected against the DEHP-induced impairment of learning and memory and alleviated the thinning of postsynaptic density (PSD) thickness in hippocampal synapses. We observed that there are fourteen up or down regulated miRNAs associated PSD in DEHP exposure which were normalized by Omega-3FA treatment. Protein targets in PSD of these differentially expressed miRNAs were predicted. Furthermore, the expression levels of protein mGluR5, Homer1, and NMDAR2B were carried out via Western blot, for further verifying PSD associated miRNAs targets are involved in neuroprotection of Omega-3FA against DEHP. These findings suggested that Omega-3FA protected DEHP-induced impairment of learning and memory as well as synaptic structure alteration in the hippocampus by regulating the expression of PSD associated miRNAs and their targets. Thus, Omega-3FA should be included in diet to prevent or suppress neurotoxicity caused by continuous exposure to DEHP.

neuroscience↗

bioRxiv2024

Pangenome Reveals Gene Content Variations and Structural Variants Contributing to Pig Characteristics

Pigs are among the most essential sources of high-quality protein in human diets. Structural variants (SVs) are a major source of genetic variants associated with diverse traits and evolutionary events. However, the current linear reference genome of pigs limits the presentation of position information for SVs. In this study, we generated a pangenome of pigs and a genome variation map of 599 deep-sequenced genomes across Eurasia. Moreover, a section-wide gene repertoire was constructed, which indicated that core genes were more evolutionarily conserved than variable genes. Subsequently, we identified 546,137 SVs, their enrichment regions, and relationships with genomic features and found significant divergence across Eurasian pigs. More importantly, the pangenome-detected SVs could complement heritability estimates and genome-wide association studies based only on single nucleotide polymorphisms. Among the SVs shaped by selection, we identified an insertion in the promoter region of the TBX19 gene, which may be related to the development, growth, and timidity traits of Asian pigs and may affect the gene expression. Our constructed pig pangenome and the identified SVs provide rich resources for future functional genomic research on pigs.

genomics↗