Biology subjects

Zhang, T.

Publications and source records attributed to Zhang, T..

At least 271 records · Page 15Linked to original sources

bioRxiv2024

Peptidergic neurons with extensive branching orchestrate the internal states and energy balance of male Drosophila melanogaster.

Neuropeptide SIFamide (SIFa) neurons in Drosophila melanogaster have been characterized by their exceptionally elaborate arborization patterns, which extend from the brain into the ventral nerve cord (VNC). SIFa neurons are equipped to receive signals that integrate both internal physiological cues and external environmental stimuli. These signals enable the neurons to regulate energy balance, sleep patterns, metabolic status, and circadian timing. These peptidergic neurons are instrumental in orchestrating the animals internal states and refining its behavioral responses, yet the precise molecular underpinnings of this process remain elusive. Here we demonstrate that SIFa neurons coordinate a range of behavioral responses by selectively integrating inputs and outputs in a context-dependent manner. These neurons engage in a feedback loop with sNPF neurons in the ventral nerve cord, modifying behaviors such as long mating duration (LMD) and shorter mating duration (SMD). Furthermore, SIFa neurons receive essential inputs from neuropeptides Dsk, sNPF, and dilp2, which regulate interval timing behaviors. Activating SIFa neurons leads to reduced mating duration and increased food intake, while deactivating them reduces food intake. Overall, these findings demonstrate the importance of SIFa neurons in absorbing inputs and turning them into behavioral outputs, shedding light on animals intricate behavioral orchestration.

neuroscience↗

bioRxiv2024

Long-range neuropeptide relay as a central-peripheral communication mechanism for the context-dependent modulation of interval timing behaviors.

Neuropeptides play crucial roles in regulating context-dependent behaviors, but the underlying mechanisms remain elusive. We investigate the role of the neuropeptide SIFa and its receptor SIFaR in regulating two distinct mating duration behaviors in male Drosophila: Longer-Mating-Duration (LMD) and Shorter-Mating-Duration (SMD). We found that SIFaR expression in specific neurons is required for both LMD and SMD behaviors. Social context and sexual experience lead to synaptic reorganization between SIFa and SIFaR neurons, altering internal states of brain. We revealed that the SIFa-SIFaR/Crz-CrzR neuropeptide relay pathway is essential for generating distinct interval timing behaviors, with Crz neurons being responsive to the activity of SIFa neurons. Additionally, CrzR expression in non-neuronal cells is critical for regulating LMD and SMD behaviors. Our study provides insights into how neuropeptides and their receptors modulate context-dependent behaviors through synaptic plasticity and calcium signaling, with implications for understanding the neural circuitry underlying interval timing and neuropeptidergic system modulation of behavioral adaptations.

neuroscience↗

bioRxiv2024

Discovery of Potent Degraders of the Dengue Virus Envelope Protein

Targeted protein degradation has been widely adopted as a new approach to eliminate both established and previously recalcitrant therapeutic targets. Here we report the development of small molecule degraders of the envelope (E) protein of dengue virus. We developed two classes of bivalent E-degraders, linking two previously reported E-binding small molecules, GNF-2 and CVM-2-12-2, to a glutarimide-based recruiter of the CRL4CRBN ligase to effect proteosome-mediated degradation of the E protein. ZXH-2-107 (based on GNF-2) is an E degrader with ABL inhibition while ZXH-8-004 (based on CVM-2-12-2) is a selective and potent E-degrader. These two compounds provide proof-of-concept that difficult-to-drug targets such as a viral envelope protein can be effectively eliminated using a bivalent degrader and provide starting points for the future development of a new class antiviral drugs.

biochemistry↗

bioRxiv2024

Freeform robotic optical coherence tomography beyond the optical field-of-view limit

Imaging complex, non-planar anatomies with optical coherence tomography (OCT) is limited by the optical field of view (FOV) in a single volumetric acquisition. Combining linear mechanical translation with OCT extends the FOV but suffers from inflexibility in imaging non-planar anatomies. We report the freeform robotic OCT to fill this gap. To address challenges in volumetric reconstruction associated with the robotic movement accuracy being two orders of magnitudes worse than OCT imaging resolution, we developed a volumetric registration algorithm based on simultaneous localization and mapping (SLAM) to overcome this limitation. We imaged the entire aqueous humor outflow pathway, whose imaging has the potential to customize glaucoma surgeries but is typically constrained by the FOV, circumferentially in mice as a test. We acquired volumetric OCT data at different robotic poses and reconstructed the entire anterior segment of the eye. The reconstructed volumes showed heterogeneous Schlemms canal (SC) morphology in the reconstructed anterior segment and revealed a segmental nature in the circumferential distribution of collector channels (CC) with spatial features as small as a few micrometers.

bioengineering↗

bioRxiv2024

Unraveling the impact of host genetics and factors on the urinary microbiome in a young population

The significance of the urinary microbiome in maintaining health and contributing to disease development is increasingly recognized. However, a comprehensive understanding of this microbiome and its influencing factors remains elusive. Utilizing whole metagenomic and whole-genome sequencing, along with detailed metadata, we characterized the urinary microbiome and its influencing factors in a cohort of 1579 Chinese individuals. Our findings unveil the distinctiveness of the urinary microbiome from other four body sites, delineating five unique urotypes dominated by Gardnerella vaginalis, Sphingobium fluviale, Lactobacillus iners, Variovorax sp PDC80 and Acinetobacter junii, respectively. We identified 108 host factors significantly influencing the urinary microbiome, collectively explaining 12.92% of the variance in microbial composition. Notably, gender-related factors, including sex hormones, emerged as key determinants in defining urotype groups, microbial composition and pathways, with the urinary microbiome exhibiting strong predictive ability for gender (AUC=0.843). Furthermore, we discovered 43 genome-wide significant associations between host genetic loci and specific urinary bacteria, Acinetobacter in particular, linked to 8 host loci (p < 5x10-8). These associations were also modulated by gender and sex hormone levels. In summary, our study provides novel insights into the impact of host genetics and other factors on the urinary microbiome, shedding light on its implications for host health and disease.

microbiology↗

bioRxiv2024

A versatile bacterial innate immunity protein directly senses two disparate phage proteins

Eukaryotic innate immune systems use pattern recognition receptors (PRRs) to sense infection by detecting pathogen-associated molecular patterns, which then triggers an immune response. Bacteria have similarly evolved immunity proteins that sense certain components of their viral predators known as bacteriophages1-6. Although different immunity proteins can recognize different phage-encoded triggers, individual bacterial immunity proteins have only been found to sense a single trigger during infection, suggesting a one-to-one relationship between bacterial PRRs and their ligands7-11. Here, we demonstrate that the anti-phage defense protein CapRelSJ46 in Escherichia coli can directly bind and sense two completely unrelated and structurally different proteins using the same sensory domain, with overlapping but distinct interfaces. Our results highlight the remarkable versatility of an immune sensory domain, which may be a common property of anti-phage defense systems and enable them to keep pace with their rapidly evolving viral predators. We found that Bas11 phages harbor both trigger proteins that are sensed by CapRelSJ46 during infection, and we demonstrate that such phage can only fully evade CapRelSJ46 defense when both triggers are mutated. Our work reveals how a bacterial immune system that senses more than one trigger can help prevent phages from easily escaping detection, and it may allow detection of a broader range of phages. More generally, our findings illustrate unexpected multifactorial sensing by bacterial defense systems and complex coevolutionary relationships between them and their phage-encoded triggers.

microbiology↗

bioRxiv2024

Augment Single-cell RNA-seq data with Surface Protein Levels using Gene set-based Deep Learning and Transfer Learning Methods

As scRNA-seq becomes increasingly accessible, providing a cost-efficient method to augment surface protein levels from gene expression measurements are desirable. We proposed a machine learning approach that includes a novel geneset neural network (GS-NN) that aims to learn robust and biologically meaningful features and a highly efficient transfer learning strategy to address cross-dataset differences. We conducted comprehensive experiments to show the improvements of the proposed methods. Specifically, we demonstrate that GS-NN learns more robust features to achieve better cross-subject performance than other machine learning approaches. Transfer learning further improves that of GS-NN by reducing dataset differences through highly efficient fine-tuning. The unique genesets design of GS-NN also allows identification of functions contributing to the prediction and improvement of the proposed strategy. Overall, this study reports a novel approach to robustly augment. Key PointsO_LIThe article presents a machine learning approach, Geneset Neural Network(GS-NN) to augment surface protein levels from single-cell RNA sequencing(scRNA-seq) gene expression data. C_LIO_LIThe GS-NN aims to learn robust and biologically meaningful features, and the approach includes a highly efficient transfer learning strategy to address cross-dataset differences in scRNA-seq data. C_LIO_LIComprehensive experiments demonstrate that GS-NN learns more robust features using trasfer learning techniques achieving better cross-subject performance compared to other machine learning approaches. C_LIO_LIThe unique geneset-based architecture of GS-NN allows the identification and interpretion of biological functions contributing to the prediction of cell surface protein level. C_LIO_LIGS-NNs architecture is conveniently transferrable across datasets, making it valuable tool for researchers working with diverse scRNA-seq datasets. C_LI

bioinformatics↗

bioRxiv2024

Sacrificing Adaptability for Functionality: The Ivory Tower of Macular Muller Cells

The predilection of many retinal diseases for the macula suggests it may be less resistant to stress than the peripheral retina. Profiling of single-cell level transcriptional changes found that the peripheral retina exhibited more transcriptional changes than the macula in response to stress. One pronounced change was in a subgroup of Muller cells (MCs) that were dominant in the peripheral retina. Genes more abundantly expressed in peripheral MCs were mainly associated with stress responses and were more influenced by light stress. In contrast, genes highly expressed in MCs that predominated in the macula had roles in cellular function and were less influenced by light stress. Metallothionein 1, A Kinase Anchor Protein 12 and MAF BZIP Transcription Factor F were more abundantly expressed in peripheral MCs than in macular MCs. Knockdown of these genes in primary MCs reduced their viability under stress. Our findings indicate that macular MCs are more directed toward maintaining retinal function rather than mounting a stress response when exposed to stress, which may contribute to the maculas vulnerability to degenerative diseases.

neuroscience↗

bioRxiv2024

Targeting oncogenic K-Ras mutants with a small-molecule degrader through Nedd4-1

K-Ras mutations represent a most prevalent oncogenic alteration in human cancers. Despite of tremendous efforts, it remains a big challenge to develop inhibitors that can target the oncogenic K-Ras mutants, especially mutants without specific active or charged side chains such as K-RasG12V. Here, taking advantage of our previous finding that Nedd4-1 is a bona fide E3 ubiquitin ligase for wild-type Ras proteins, we developed a compound XMU-MP-9 that can promote ubiquitination and degradation of various K-Ras mutants including K-RasG12V, and significantly inhibit proliferation and tumor development of K-Ras mutant harboring cells. Mechanistically, XMU-MP-9 acts as a bifunctional compound to bind the C2 domain of Nedd4-1 and an allosteric site of K-Ras to enhance Nedd4-1 and K-Ras interaction, and to induce a conformational change of Nedd4-1/K-Ras complex to allow Nedd4-1 targeting K128 of K-Ras for ubiquitination. Hence, our study presents a robust strategy to develop small-molecule degrader of K-Ras mutants, and also sheds light on the development of small-molecule degraders for H-Ras and N-Ras mutants.

cancer biology↗

bioRxiv2024

Tumor-expressed SPPL3 supports innate anti-tumor immune responses.

The development of an effective anti-tumor response relies on the synergistic actions of various immune cells that recognize tumor cells via distinct receptors. Tumors, however, often manipulate receptor-ligand interactions to evade recognition by the immune system. Recently, we highlighted the role of neolacto-series glycosphingolipids (nsGSLs), produced by the enzyme {beta}1,3-N-acetylglucosaminyltransferase 5 (B3GNT5), in tumor immune escape. We previously demonstrated that loss of signal peptidase like 3 (SPPL3), an inhibitor of B3GNT5, results in elevated levels of nsGSLs and impairs CD8 T cell activation. The impact of loss of SPPL3 and an elevated nsGSL profile in tumor cells on innate immune recognition remains to be elucidated. This study investigates the anti-tumor efficacy of neutrophils, NK cells, and {gamma}{delta} T cells on tumor cells lacking SPPL3. Our findings demonstrate that SPPL3-deficient target cells are less susceptible to trogocytosis by neutrophils and killing by NK cells and {gamma}{delta} T cells. Mechanistically, SPPL3 influences trogocytosis and {gamma}{delta} T cell instigated killing through modulation of nsGSL expression while SPPL3-mediated reduced killing by NK cells is nsGSL-independent. The nsGSL-dependent SPPL3 sensitivity depends on the proximity of surface receptor domains to the cell membrane and the affinity of receptor-ligand interactions as shown with various sets of defined antibodies. Thus, SPPL3 expression by tumor cells alters crosstalk with immune cells through the receptor-ligand interactome thereby driving escape not only from adaptive but also from innate immunity. These data underline the importance of investigating a potential synergism of GSL synthesis inhibitors with current immune cell activating immunotherapies.

immunology↗

bioRxiv2024

PLM_Sol: predicting protein solubility by benchmarking multiple protein language models with the updated Escherichia coli protein solubility dataset

Protein solubility plays a crucial role in various biotechnological, industrial and biomedical applications. With the reduction in sequencing and gene synthesis costs, the adoption of high-throughput experimental screening coupled with tailored bioinformatic prediction has witnessed a rapidly growing trend for the development of novel functional enzymes of interest (EOI). High protein solubility rates are essential in this process and accurate prediction of solubility is a challenging task. As deep learning technology continues to evolve, attention-based protein language models (PLMs) can extract intrinsic information from protein sequences to a greater extent. Leveraging these models along with the increasing availability of protein solubility data inferred from structural database like the Protein Data Bank (PDB), holds great potential to enhance the prediction of protein solubility. In this study, we curated an Updated Escherichia coli (E.coli) protein Solubility DataSet (UESolDS) and employed a combination of multiple PLMs and classification layers to predict protein solubility. The resulting best-performing model, named Protein Language Model-based protein Solubility prediction model (PLM_Sol), demonstrated significant improvements over previous reported models, achieving a notable 5.7% increase in accuracy, 9% increase in F1_score, and 10.4% increase in MCC score on the independent test set. Moreover, additional evaluation utilizing our in-house synthesized protein resource as test data, encompassing diverse types of enzymes, also showcased the superior performance of PLM_Sol. Overall, PLM_Sol exhibited consistent and promising performance across both independent test set and experimental set, thereby making it well-suited for facilitating large-scale EOI studies. PLM_Sol is available as a standalone program and as an easy-to-use model at https://zenodo.org/doi/10.5281/zenodo.10675340.

bioinformatics↗

bioRxiv2024

Insight into the Impact of Air Flow Rate on Algal-Bacterial Granules: Reactor Performance, Hydrodynamics by Computational Fluid Dynamics (CFD) and Microbial Community Analysis

Algal-bacterial granules have been drawing attention in wastewater treatment due to their rapid settling ability and efficient nutrient removal performance. This study evaluated the impact of air flow rates on nitrogen removal and the formation of algal-bacterial granules in domestic wastewater treatment. The highest nitrogen removal efficiency was achieved by operating with two separate feedings and the addition of an external carbon source. The higher air flow rate resulted in a higher nitrification rate and produced smaller and more compact granules on average. However, increasing the air flow rate did not necessarily increase extracellular polymeric substances (EPS) production. Computational Fluid Dynamics (CFD) simulations revealed that mechanical mixing was the primary source of shear force. Increasing the air flow rate from 0.2 LPM to 0.5 LPM only yielded a 12% increment in the volume-averaged strain rate. Further analysis of microbial communities showed that changes in bioreactor operation, especially sodium acetate addition and aerations, shifted the microbial community composition. The sodium acetate addition led to the increase of microbial diversity and the relative abundance of denitrifiers such as Thauera, while the aeration caused the increasing relative abundances of nitrogen-related genera (such as Nitrospira) and the decreasing relative abundances of cyanobacteria and Chlorella in the long-term operation of the photobioreactors. Moreover, the decrease in total abundance of grazers and pathogens along with the operation, including Chytridiomycetes, Sessilida, and Operculariidae, might result from the shear force and the decrease of prokaryotic species, such as Chlorella spp.. HighlightsO_LIA higher air flow rate resulted in a higher nitrification rate. C_LIO_LIShear stress, microbial composition, and carbon source affected EPS production. C_LIO_LIIncreasing the air flow rate from 0.2 to 0.5 LPM led to only 12% of the increment of shear stress. C_LIO_LIMicrobial community differed with aeration rate and carbon source. C_LI Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=175 SRC="FIGDIR/small/589810v1_ufig1.gif" ALT="Figure 1"> View larger version (47K): org.highwire.dtl.DTLVardef@c6a7e1org.highwire.dtl.DTLVardef@37da84org.highwire.dtl.DTLVardef@eb362dorg.highwire.dtl.DTLVardef@31d122_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2024

MtrAB two-component system is crucial for the intrinsic resistance and virulence of Mycobacterium abscessus

Mycobacterium abscessus (Mab) poses serious therapeutic challenges, principally due to its intrinsic resistance to a wide array of antibiotics. The pressing issue of drug resistance has spurred an urgent need to explore novel targets and develop new therapeutic agents against Mab. The MtrAB two-component system, conserved among Actinobacteria, is pivotal for regulating various metabolic processes. Nevertheless, the role of MtrAB in Mab remains elusive. In this study, we uncovered that Mab strains with disrupted mtrA, mtrB or both exhibited heightened susceptibility to a variety of antibiotics with diverse mechanisms of action, in contrast to the wild-type strain. In a murine model, rifabutin, bedaquiline, and amikacin, which were inactive against the wild-type Mab strain, demonstrated efficacy against all the mtrA, mtrB and mtrAB knockout strains, significantly reducing pulmonary bacterial burdens compared to vehicle controls after ten days of treatment. Notably, the virulence of all the mtrA, mtrB, and mtrAB knockout strains was highly diminished in the murine model, as evidenced by a substantial decrease in bacterial load in the lungs of mice after 16 days. We observed that all three knockout strains exhibited a significantly reduced growth rate compared to the wild-type strain. We discovered that cells lacking mtrA, mtrB or both exhibited an elongated cell length and had multiple septa, suggesting that both MtrA and MtrB regulate cell division of Mab. Subsequently, an ethidium bromide accumulation assay disclosed that the absence of either mtrA or mtrB or both significantly increased cell envelope permeability. In summary, this study suggests that mtrA and mtrB play an important role in the intrinsic resistance and virulence of Mab by affecting cell division and altering cell permeability. Consequently, MtrA and MtrB represent promising targets for the discovery of anti-Mab drugs. HIGHLIGHTSO_LIKnockout of mtrA, mtrB or mtrAB leads to increased sensitivity of M. abscessus in vitro and in vivo. C_LIO_LIThe mtrA, mtrB or mtrAB knockout M. abscessus strains exhibit highly reduced virulence. C_LIO_LIMtrA and MtrB are potential targets for anti-M. abscessus drug discovery. C_LIO_LIKnockout of mtrA, mtrB or mtrAB results in defective cell division in M. abscessus. C_LI

microbiology↗

bioRxiv2024

APOBEC shapes tumor evolution and age at onset of lung cancer in smokers

APOBEC enzymes are part of the innate immunity and are responsible for restricting viruses and retroelements by deaminating cytosine residues1,2. Most solid tumors harbor different levels of somatic mutations attributed to the off-target activities of APOBEC3A (A3A) and/or APOBEC3B (A3B)3-6. However, how APOBEC3A/B enzymes shape the tumor evolution in the presence of exogenous mutagenic processes is largely unknown. Here, by combining deep whole-genome sequencing with multi-omics profiling of 309 lung cancers from smokers with detailed tobacco smoking information, we identify two subtypes defined by low (LAS) and high (HAS) APOBEC mutagenesis. LAS are enriched for A3B-like mutagenesis and KRAS mutations, whereas HAS for A3A-like mutagenesis and TP53 mutations. Unlike APOBEC3A, APOBEC3B expression is strongly associated with an upregulation of the base excision repair pathway. Hypermutation by unrepaired A3A and tobacco smoking mutagenesis combined with TP53-induced genomic instability can trigger senescence7, apoptosis8, and cell regeneration9, as indicated by high expression of pulmonary healing signaling pathway, stemness markers and distal cell-of-origin in HAS. The expected association of tobacco smoking variables (e.g., time to first cigarette) with genomic/epigenomic changes are not observed in HAS, a plausible consequence of frequent cell senescence or apoptosis. HAS have more neoantigens, slower clonal expansion, and older age at onset compared to LAS, particularly in heavy smokers, consistent with high proportions of newly generated, unmutated cells and frequent immuno-editing. These findings show how heterogeneity in mutational burden across co-occurring mutational processes and cell types contributes to tumor development, with important clinical implications.

genomics↗

bioRxiv2024

Biologically informed machine learning modeling of immune cells to reveal physiological and pathological aging process

The immune system undergoes progressive functional remodeling from neonatal stages to old age. Therefore, understanding how aging shapes immune cell function is vital for precise treatment of patients at different life stages. Here, we constructed the first transcriptomic atlas of immune cells encompassing human lifespan, ranging from newborns to supercentenarians, and comprehensively examined gene expression signatures involving cell signaling, metabolism, differentiation, and functions in all cell types to investigate immune aging changes. By comparing immune cell composition among different age groups, HLA highly expressing NK cells and CD83 positive B cells were identified with high percentages exclusively in the teenager (Tg) group, whereas CD4_CTL precursors were exclusively enriched in the supercentenarian (Sc) group. Notably, we found that the biological age (BA) of pediatric COVID-19 patients with multisystem inflammatory syndrome accelerated aging according to their chronological age (CA). Besides, we proved that inflammatory shift-myeloid abundance and signature correlate with the progression of complications in Kawasaki disease (KD). Finally, based on those age-related immune cell compositions, we developed a novel BA prediction model, PHARE (https://xiazlab.org/phare/), which applies to both scRNA-seq and bulk RNA-seq data. Overall, our study revealed changes in immune cell proportions and function associated with aging, both in health and disease, and provided a novel tool for successfully capturing features that accelerate or delay aging.

immunology↗

bioRxiv2024

The subcommissural organ regulates brain development via secreted peptides

The subcommissural organ (SCO) is a gland located at the entrance of the aqueduct of Sylvius in the brain. It exists in species as distantly related as amphioxus and humans, but its function is largely unknown. To explore its function, we compared transcriptomes of SCO and non-SCO brain regions and found three genes, Sspo, Car3, and Spdef, that are highly expressed in the SCO. Mouse strains expressing Cre recombinase from endogenous promoter/enhancer elements of these genes were used to genetically ablate SCO cells during embryonic development, resulting in severe hydrocephalus and defects in neuronal migration and development of neuronal axons and dendrites. Unbiased peptidomic analysis revealed enrichment of three SCO-derived peptides, namely thymosin beta 4, thymosin beta 10, and NP24, and their reintroduction into SCO-ablated brain ventricles substantially rescued developmental defects. Together, these data identify a critical role for the SCO in brain development.

neuroscience↗

bioRxiv2024

Enhanced extracellular matrix remodeling due to embedded spheroid fluidization

Tumor spheroids are in vitro three-dimensional, cellular collectives consisting of cancerous cells. Embedding these spheroids in an in vitro fibrous environment, such as a collagen network, to mimic the extracellular matrix (ECM) provides an essential platform to quantitatively investigate the biophysical mechanisms leading to tumor invasion of the ECM. To understand the mechanical interplay between tumor spheroids and the ECM, we computationally construct and study a three-dimensional vertex model for a tumor spheroid that is mechanically coupled to a cross-linked network of fibers. In such a vertex model, cells are represented as deformable polyhedrons that share faces. Some fraction of the boundary faces of the tumor spheroid contain linker springs connecting the center of the boundary face to the nearest node in the fiber network. As these linker springs actively contract, the fiber network remodels. By toggling between fluid-like and solid-like spheroids via changing the dimensionless cell shape index, we find that the spheroid rheology affects the remodeling of the fiber network. More precisely, fluid-like spheroids displace the fiber network more on average near the vicinity of the spheroid than solid-like spheroids. We also find more densification of the fiber network near the spheroid for the fluid-like spheroids. These spheroid rheology-dependent effects are the result of cellular motility due to active cellular rearrangements that emerge over time in the fluid-like spheroids to generate spheroid shape fluctuations. These shape fluctuations lead to emergent feedback between the spheroid and the fiber network to further remodel the fiber network with, for example, lower radial alignment of the higher-tensioned fibers given the breaking of spheroidal radial symmetry, which can then further remodel the spheroid. Our results uncover intricate morphological-mechanical interplay between an embedded spheroid and its surrounding fiber network with both spheroid contractile strength and spheroid shape fluctuations playing important roles in the pre-invasion stages of tumor invasion.

biophysics↗

bioRxiv2024

The origin and evolution of cultivated rice and genomic signatures of heterosis for yield traits in super-hybrid rice

Unraveling evolutionary history and genomic basis of heterosis is fundamental for advancing rice productivity. We developed a genome-scale phylogeny of Oryzeae by coalescing 39,984 gene trees. Our analysis supports parallel, independent origins and nearly synchronous evolutionary trajectories leading to the subsequent domestication of indica and japonica, evidenced by molecular dating and synonymous substitution rates for syntenic and domestication-associated genes. Our survey of 1,383 gene duplications in ancestor of O. sativa uncovers their roles in vital biological processes, highlighting the significance in environmental adaptability. Additionally, we confirm the lack of hybridization event among subspecies ancestors through gene tree topology and D-statistical analyses. We generated 71.67 GB whole-genome sequencing data for five super-hybrid rice varieties and their progenitors, revealing differential positive selection and genetic exchanges between subspecies, essential for heterosis formation. Crucially, our study underscores the role of non-additive gene expression in heterosis, particularly in genes associated with DNA repair and recombination, which may confer resistance traits. Furthermore, eQTL and de novo mutation analyses identify key developmental and stress response genes, offering targets for enhancing heterosis in rice. Overall, our research reveals crucial insights into the genetics of rice domestication and heterosis, offering a genomic resource to improve rices agricultural productivity.

evolutionary biology↗