Biology subjects

Zhao, Y.

Publications and source records attributed to Zhao, Y..

At least 505 records · Page 28Linked to original sources

bioRxiv2024

The segmented flavivirus Alongshan virus reduces mitochondrial mass via degrading STAT2 to suppress innate immune response

Alongshan virus (ALSV) is a newly discovered pathogen of the Flaviviridae family, characterized by a multi-segmented genome distantly related to the canonical flaviviruses. Understanding the pathogenic mechanism of the emerging segmented flavivirus is crucial for the development of intervention strategies. Here we show that ALSV can infect multiple mammalian cells and induces the expression of antiviral genes. Moreover, ALSV is sensitive to IFN-{beta} and possesses the ability to counteract type I IFN response. Mechanistically, ALSVs nonstructural protein NSP1 binds to and degrades human STAT2 through an autophagy pathway in a species-dependent manner, resulting in direct inhibition of the expression of interferon-stimulated genes (ISGs). Specifically, NSP1 methyltransferase domain binds to the key sites of F175/R176 located in coiled-coil domain of STAT2. Moreover, NSP1-mediated degradation of STAT2 results in a reduction in mitochondrial mass by disrupting mitochondrial dynamics to induce mitophagy and inhibiting mitochondrial biogenesis, thereby suppressing the innate immune response. Interestingly, inhibiting mitophagy using 3-Methyladenine and enhancing mitochondrial biogenesis using the PPAR{gamma} agonist pioglitazone can reverse NSP1-mediated inhibition of ISGs, suggesting that promoting mitochondrial mass presents an effective antiviral strategy. Our findings elucidate the intricate regulatory crosstalk between ALSV and the hosts innate immune response, providing valuable insights into the pathogenesis and intervention strategy of emerging segmented flavivirus.

microbiology↗

bioRxiv2024

Probing Phosphorylation-Induced Vibrational Couplings in CFTR by 2D IR Spectra Simulations

Phosphorylation of the regulator (R) domain underlies the basis for gating in the human cystic fibrosis transmembrane conductance regulator (CFTR), malfunction or down regulation of CFTR leads to defective apical chloride transport. The biophysical mechanism that underlies the regulatory effect of R domain is still unclear. Here, we utilize a combination of molecular dynamics simulations and theoretically calculated two-dimensional infrared (2D IR) spectra to probe both the structure and spectral signature of phosphorylated and unphosphorylated CFTR. We uncover an ATP-independent asymptotic movement of nucleotide binding domains (NBDs) driven by phosphorylated R domain. Utilizing non-rephasing cross ground-state bleach infrared (GB IR) spectra simulation, we overcome the interpretation hurdle caused by overlaps of multiple vibrational modes, and find distinct vibrational couplings induced by phosphorylation. By calculating exciton eigenfrequencies, we pinpoint specific vibrational couplings to individual amide I modes (carbonyl stretches), unveiling a critical role of serine residues in modulating the coupling state of neighboring amino acids. Our findings offer a bond-specific perspective on how intramolecular interactions within the R domain translate into its broader regulatory function.

bioinformatics↗

bioRxiv2024

Platinum drug reprogramming of protein phosphorylation

Cisplatin is a DNA-targeting chemotherapeutic. Here we investigate how the cisplatin damaged gene loci are linked to specific protein-driven signalling pathways. Using forward chemical genetics methods, cisplatin damage to specific genes has been mapped in human lung cancer cells, a total of 16216 cisplatin-damaged genes (CDGs) with fold-enrichment > 1.5. Surprisingly, bioinformatics analysis demonstrates that cisplatin targets the majority of human protein kinase and phosphatase genes and involved in 300 core signalling pathways (-log p >4). The most associated key signalling pathways are sperm motility and protein kinase A. The highest related disease is cancer, and tissue toxicities related to CDGs are about hepato- and nephro- toxicities. Notably, cisplatin damaged 85% (440) of human protein kinase genes and 81% (110) of human protein phosphatase genes. This suggests that cisplatin acts as a multi-targeting protein-phosphorylation regulator, confirmed by a significant decrease in expression of a series of key protein kinase genes. These results reveal that cisplatin disrupts protein phosphorylation signalling genome-wide. Key points summarising the key messages of your articleA total of 16216 genes damaged by the clinical drug cisplatin in human lung cancer cells were identified using a forward chemical genetics method. Bioinformatics analysis revealed that cisplatin targets 85% of protein kinase and 81% of phosphatase genes. Cisplatin acts as a multi-targeting protein-phosphorylation regulator, disrupting protein phosphorylation signalling genome-wide. The disturbance of protein phosphorylation by cisplatin can be related to anticancer activity and tissue toxicities of the drug. These findings suggests novel strategies for rational design of next-generation anticancer metallodrugs involving specific targeting of protein phosphorylation.

cancer biology↗

bioRxiv2024

PreMode predicts mode of action of missense variants by deep graph representation learning of protein sequence and structural context

Accurate prediction of the functional impact of missense variants is important for disease gene discovery, clinical genetic diagnostics, therapeutic strategies, and protein engineering. Previous efforts have focused on predicting a binary pathogenicity classification, but the functional impact of missense variants is multi-dimensional. Pathogenic missense variants in the same gene may act through different modes of action (i.e., gain/loss-of-function) by affecting different aspects of protein function. They may result in distinct clinical conditions that require different treatments. We developed a new method, PreMode, to perform gene-specific mode-of-action predictions. PreMode models effects of coding sequence variants using SE(3)-equivariant graph neural networks on protein sequences and structures. Using the largest-to-date set of missense variants with known modes of action, we showed that PreMode reached state-of-the-art performance in multiple types of mode-of-action predictions by efficient transfer-learning. Additionally, PreModes prediction of G/LoF variants in a kinase is consistent with inactive-active conformation transition energy changes. Finally, we show that PreMode enables efficient study design of deep mutational scans and optimization in protein engineering.

bioinformatics↗

bioRxiv2024

CAMKV Kinase Signaling Is a Novel Therapeutic Avenue with Prognostic Relevance in Neuroblastoma

Neuroblastoma (NB) can be a highly aggressive malignancy in children. However, the precise mechanisms driving NB tumorigenesis remain elusive. This study revealed the critical role of CREB phosphorylation in NB cell proliferation. By employing a CRISPR-Cas9 knockout screen targeting calcium/calmodulin-dependent protein kinase (CaMK) family members, we identified the CaM kinase-like vesicle-associated (CAMKV) protein as a kinase that mediates direct phosphorylation of CREB to promote NB cell proliferation. CAMKV was found to be a transcriptional target of MYCN/MYC in NB cells. CAMKV knockout and knockdown effectively suppressed NB cell proliferation and tumor growth both in vitro and in vivo. Bioinformatic analysis revealed that high CAMKV expression is significantly correlated with poor patient survival. High-risk NB frequently had high CAMKV protein levels by Immunohistochemical staining. Integrated transcriptomic and proteomic analyses of CAMKV knockdown cells unveiled downstream targets involved in CAMKV-regulated phosphorylation and signaling pathways, many of which are linked to neural development and cancer progression. We identified small molecule inhibitors targeting CAMKV and further demonstrated the efficacy of one inhibitor in suppressing NB tumor growth and prolonging the survival of mice bearing xenografted tumors. These findings reveal a critical role for CAMKV kinase signaling in NB growth and identified CAMKV kinase as a potential therapeutic target and prognostic marker for patients with NB.

cancer biology↗

bioRxiv2024

C. elegans LIN-66 mediates EIF-3.G-dependent protein translation via a cold-shock domain

Protein translation initiation is a complex and conserved process involving many proteins acting in concert. The eukaryotic initiation factor 3 (eIF3) complex is essential for the assembly of the pre-initiation complex that scans and positions mRNA at the initiation codon. eIF3 complex consists of 13 subunits. In addition to their essential roles in general translation initiation, emerging studies suggest that individual subunits of eIF3 can provide specialized functions in response to specific stimuli. We have previously reported that a gain-of-function (gf) mutation in the G subunit of C. elegans eIF3 complex, eif-3.g(gf), selectively modulates protein translation in the ventral cord cholinergic motor neurons. Here, through unbiased genetic suppressor screening, we have identified the lin-66 gene that mediates the eif-3.g(gf)-dependent protein translation in the motor neurons. LIN-66 is previously reported to be a nematode-specific protein composed of largely low complexity amino acid sequences with unknown functional domains. We combined bioinformatic analysis with in vivo functional dissection and identified a cold-shock domain in LIN-66 to be critical for its function. In the cholinergic motor neurons, LIN-66 shows somatic cytoplasmic localization and close association with EIF-3.G. The low complexity amino acid sequences of LIN-66 modulate its subcellular pattern. Cold-shock-domains are known to interact with RNA and have broad functions in RNA metabolism and protein translation. We propose that LIN-66 mediates stimuli-dependent protein translation by facilitating the interaction of mRNAs with EIF-3.G.

genetics↗

bioRxiv2024

The GPI sidechain of Toxoplasma gondii prevents parasite pathogenesis

Glycosylphosphatidylinositols (GPIs) are highly conserved anchors for eukaryotic cell surface proteins. The apicomplexan parasite, Toxoplasma gondii, is a widespread intracellular parasite of warm-blooded animals whose plasma membrane is covered with GPI-anchored proteins, and free GPIs called GIPLs. While the glycan portion is conserved, species differ in sidechains added to the triple mannose core. The functional significance of the Glc1,4GalNAc{beta}1-sidechain reported in Toxoplasma gondii has remained largely unknown without an understanding of its biosynthesis. Here we identify and disrupt two glycosyltransferase genes and confirm their respective roles by serology and mass spectrometry. Parasites lacking the sidechain on account of deletion of the first glycosyltransferase, PIGJ, exhibit increased virulence during primary and secondary infections, suggesting it is an important pathogenesis factor. Cytokine responses, antibody recognition of GPI-anchored SAGs, and complement binding to PIGJ mutants are intact. In contrast, the scavenger receptor CD36 shows enhanced binding to PIGJ mutants, potentially explaining a subtle tropism for macrophages detected early in infection. Galectin-3, which bind GIPLs, exhibits a slight enhancement of binding to PIGJ mutants, and the protection of galectin-3 knockout mice from lethality suggests that{Delta} pigj parasite virulence in this context is sidechain dependent. Parasite numbers are not affected by{Delta} pigj early in the infection in wildtype mice, suggesting a breakdown of tolerance. However, increased tissue cysts in the brains of mice infected with{Delta} pigj parasites indicate an advantage over wildtype strains. Thus, the GPI sidechain of T. gondii plays a crucial and diverse role in regulating disease outcome in the infected host. SummaryThe functional significance of sidechain modifications to the GPI anchor is yet to be determined because the glycosyltransferases responsible for these modifications have not been identified. Here we present identification and characterization of both T. gondii GPI sidechain-modifying glycosyltransferases. Removal of the glycosyltransferase that adds the first GalNAc to the sidechain results in parasites without a sidechain on the GPI, and increased parasite virulence. Loss of the second glycosyltransferase results in a sidechain with GalNAc alone, and no glucose added, and has negligible effect on parasite virulence. This indicates GPI sidechains as fundamental to host-parasite interactions.

microbiology↗

bioRxiv2024

Efficient cloning of genes for wheat yield component traits from QTLs via sequencing of the RIL population

In wheat (Triticum aestivum L.), yield component traits (YCTs) are the most important yield traits. Only several genes for YCTs have been originally cloned. The efficient cloning of genes for YCTs directly from wheat remains a challenge. Here, we proposed a strategy for cloning genes from quantitative trait loci (QTLs) by sequencing of recombinant inbred lines (RILs) (QTL-Seq-RIL). Using the TN18 x LM6 RIL population as an example, we identified 138 candidate unigenes (CUGs) for YCTs from 77 stable QTLs. The average of CUGs per QTL was 1.8, which enabled us to confirm the CUGs directly. We have confirmed seven CUGs, TaIFABPL, TaDdRp, TaRLK, TaTD, TaTFC3, TaKMT and TaSPL17, via the CRISPR/Cas9 system. Of these, six genes were found firstly to regulate YCTs in crops except for TaSPL17. Five CUGs (include TaSPL17) for which orthologous genes have been cloned previously with the same or similar agronomic functions. It is to say, 11 CUGs were preliminarily validated using a single RIL population. QTL-Seq-RIL provides an efficient method for rapid gene cloning using existing RIL populations.

plant biology↗

bioRxiv2024

Nodulation Trio in Medicago truncatula: Unveiling the Overlapping Roles of MtLYK2, MtLYK3, and MtLYK2bis

The perception of rhizobial nodulation factors (NF) by plant NF receptors is crucial for mediating legume nodulation. In Medicago truncatula nodulation, a proposed two-receptor model designates MtLYK3 as an entry receptor, while other LYK proteins, with unidentified functions, may serve as signaling receptors. Here, we generated the single, double, and triple mutants for M. truncatula MtLYK2, MtLYK3, and MtLYK2bis using CRISPR/Cas technology and examined their roles in nodulation. Our findings suggest that all three LYKs possess redundant functions in Medicago nodulation, with their distinct contributions attributed to varying transcription patterns.Our findings also suggest that a one-receptor model with multiple specificities that mediates both signaling and entry responses is more suitable in M. truncatula.

plant biology↗

bioRxiv2024

From Sight to Insight: A Multi-task Approach with the Visual Language Decoding Model

Visual neural decoding aims to unlock the mysteries of how the human brain interprets the visual world. While early studies made some progress in decoding visual activity for singular type of information, they failed to concurrently reveal the multi-level interweaving linguistic information in the brain. Here, we developed a novel Visual Language Decoding Model (VLDM) capable of decoding categories, semantic labels, and textual descriptions from visual perceptual activities simultaneously. We selected the large-scale NSD dataset to ensure the efficiency of the decoding model in joint training and evaluation across multiple tasks. For category decoding, we achieved the effective classification of 12 categories with an accuracy of nearly 70%, significantly surpassing the chance level. For label decoding, we attained the precise prediction of 80 specific semantic labels with a 16-fold improvement over the chance level. For text decoding, the scores of the decoded text surpassed the corresponding baseline levels by remarkable margins on six evaluation metrics. This study contributes significantly to extensive applications in multi-layered brain-computer interfaces, potentially leading to more natural and efficient human-computer interaction experiences.

neuroscience↗

bioRxiv2024

Nasal commensals reduce Staphylococcus aureus proliferation by restricting siderophore availability

BackgroundThe human microbiome is critically associated with human health and disease. One aspect of this is that antibiotic-resistant opportunistic bacterial pathogens such as methicillin-resistant Staphylococcus aureus can reside within the nasal microbiota which increases the risk of infections. Epidemiological studies of the nasal microbiome have revealed positive and negative correlations between non-pathogenic species and S. aureus, but the underlying molecular mechanisms remain poorly understood. The nasal cavity is iron-limited and bacteria are known to produce iron-scavenging siderophores to proliferate in such environments. Siderophores are public goods that can be consumed by all members of a bacterial community. Accordingly, siderophores are known to mediate bacterial competition and collaboration but their role in the nasal microbiome is unknown. ResultsHere we show that siderophore acquisition is crucial for S. aureus nasal colonization in vivo. We screened 94 nasal bacterial strains from seven genera for their capacity to produce siderophores as well as to consume the siderophores produced by S. aureus. We found that 80% of the strains engaged in siderophoremediated interactions with S. aureus. Non-pathogenic corynebacterial species were found to be prominent consumers of S. aureus siderophores. In co-culture experiments, consumption of siderophores by competitors reduced S. aureus growth in an iron-dependent fashion. ConclusionsOur data show a wide network of siderophore mediated interactions between the species of the human nasal microbiome and provide mechanistic evidence for inter-species competition and collaboration impacting pathogen proliferation. This opens avenues for designing nasal probiotics to displace S. aureus from the nasal cavity of humans.

microbiology↗

bioRxiv2024

In vivo validation of an in situ calibration bead as a reference for backscatter coefficient calculation

ObjectivesThe study aims to assess the capability of Quantitative Ul-trasound (QUS) based on the backscatter coefficient (BSC) for classifying disease states, such as breast cancer response to neoadjuvant chemotherapy and quantifying fatty liver disease. We evaluate the effectiveness of an in situ titanium (Ti) bead as a reference target in calibrating the system and mitigating attenuation and transmission loss effects on BSC estimation. MethodsTraditional BSC estimation methods require external references for calibration, which do not account for ultrasound attenuation or transmis-sion losses through tissues. To address this issue, we use an in situ titanium (Ti) bead as a reference target, because it can be used to calibrate the system and mitigate the attenuation and transmission loss effects on estimation of the BSC. The capabilities of the in situ calibration approach were assessed by quantifying consistency of BSC estimates from rabbit mammary tumors (N = 21). Specifically, mammary tumors were grown in rabbits and when a tumor reached 1 cm or greater in size, a 2-mm Ti bead was implanted into the tumor as a radiological marker and a calibration source for ultrasound. Three days later, the tumors were scanned with a L-14/5 38 array transducer connected to a SonixOne scanner with and without a slab of pork belly placed on top of the tumors. The pork belly acted as an additional source of attenu-ation and transmission loss. QUS parameters, specifically effective scatterer diameter (ESD) and effective acoustic concentration (EAC), were calculated using calibration spectra from both an external reference phantom and the Ti bead. ResultsFor ESD estimation, the 95% confidence interval between measure-ments with and without the pork belly layer was (6.0,27.4) using the in situ bead and (114, 135.1) with the external reference phantom. For EAC esti-mation, the 95% confidence interval were (-8.1, 0.5) for the bead and (-41.5, -32.2) for the phantom. These results indicate that the in situ bead method shows reduced bias in QUS estimates due to intervening tissue losses. ConclusionsThe use of an in situ Ti bead as a radiological marker not only serves its traditional role but also effectively acts as a calibration target for QUS methods. This approach accounts for attenuation and transmission losses in tissue, resulting in more accurate QUS estimates and offering a promising method for enhanced disease state classification in clinical settings.

bioengineering↗

bioRxiv2024

Fast and accurate modeling and design of antibody-antigen complex using tFold

Accurate prediction of antibody-antigen complex structures holds significant potential for advancing biomedical research and the design of therapeutic antibodies. Currently, structure prediction for protein monomers has achieved considerable success, and promising progress has been made in extending this achievement to the prediction of protein complexes. However, despite these advancements, fast and accurate prediction of antibody-antigen complex structures remains a challenging and unresolved issue. Existing end-to-end prediction methods, which rely on homology and templates, exhibit sub-optimal accuracy due to the absence of co-evolutionary constraints. Meanwhile, conventional docking-based methods face difficulties in identifying the contact interface between the antigen and antibody and require known structures of individual components as inputs. In this study, we present a fully end-to-end approach for three-dimensional (3D) atomic-level structure predictions of antibodies and antibody-antigen complexes, referred to as tFold-Ab and tFold-Ag, respectively. tFold leverages a large protein language model to extract both intra-chain and inter-chain residue-residue contact information, as well as evolutionary relationships, avoiding the time-consuming multiple sequence alignment (MSA) search. Combined with specially designed modules such as the AI-driven flexible docking module, it achieves superior performance and significantly enhanced speed in predicting both antibody (1.6% RMSD reduction in the CDR-H3 region, thousand times faster) and antibody-antigen complex structures (37% increase in DockQ score, over 10 times faster), compared to AlphaFold-Multimer. Given the performance and speed advantages, we further extend the capability of tFold for structure-based virtual screening of binding antibodies, as well as de novo co-design of both structure and sequence for therapeutic antibodies. The experiment results demonstrate the potential of tFold as a high-throughput tool to enhance processes involved in these tasks. To facilitate public access, we release code and offer a web service for antibody and antigen-antibody complex structure prediction, which is available at https://drug.ai.tencent.com/en.

bioinformatics↗

bioRxiv2024

Screening and assessment of functional variants by regulatory features from epigenomic data in livestock species

BackgroundUnderstanding the functional impact of genetic variants is essential for advancing animal genomics and improving livestock breeding. Variants that disrupt transcription factor (TF) motifs provide a means to assess functional potential, but the lack of TF ChIP-seq data for farm animals presents a challenge. ResultsTo address this, we curated nearly 900 epigenomic datasets from 10 farm animal species and annotated eight regulatory regions to assess how variants affect TF motifs. Over 127 million candidate functional variants were classified into five functional confidence categories across the species. Variants with high confidence were enriched in eQTLs and trait-associated SNPs, showing greater potential to affect gene expression and phenotypes. Incorporating these functional variants into genomic prediction models improved the accuracy of Estimated Breeding Values (EBVs). Active variants also revealed trait-related tissues, and single-cell RNA sequencing (scRNA-seq) identified the cell types most associated with production traits. To facilitate research, we developed the Integrated Functional Mutation (IFmut) platform, enabling users to explore variant functions easily. Our study provides a flexible platform and resource for studying genomic variation in farm animals, setting a new standard for research and breeding strategies. ConclusionThe results indicated that evaluating functional potential by annotating and categorizing variants that interfere with transcription factor motifs can help elucidate changes in gene expression and phenotype. By focusing on high-confidence variants enriched in eQTL and trait-associated SNPs, it improves the accuracy of genomic predictions in research and breeding strategies.

genomics↗

bioRxiv2024

Single-Cell Transcriptomic Profiling Unveils Critical Metabolic Alterations and Signatures in Progression of Atherosclerosis

Metabolic dysregulation is recognized as a fundamental characteristic of cardiovascular diseases (CVDs), therefore mining metabolic patterns in these diseases would help to identify the possible pathogenic mechanisms and potential intervention targets. Atherosclerosis (AS), serving as the foundational pathology in numerous CVDs, represents a paramount global health concern. However, a systematic integrated analysis of the metabolic networks of AS is still lacking. In this study, we investigated and integrated single-cell RNA sequencing datasets from calcified atherosclerotic core (AC) plaques and patient-matched proximal adjacent (PA) portions of carotid artery tissue to generate metabolic flux profiling at single-cell level. Using scFEA and scWGCNA analyses, we discerned common metabolic changes in endothelial cells (ECs), myeloid cells, and smooth muscle cells. These altered metabolic modules were predominantly enriched in glucose-related pathways and were predicted to potentially facilitate metabolic bypass. Of particular interest, we observed an enrichment of metabolites produced from glucose/sialic acid metabolism pathway in both ECs and myeloid cells. This observation may partially account for their positive involvement in plaque formation, as previously discovered. Furthermore, we predicted that metabolic genes such as HK1, ENO1, PFKL, LDHA, PGK1, and NANS may be implicated in the detected metabolic flux disorder during AS progression. Additionally, we uncovered interactions between various cell types at single-cell level using CellChat. We noted heightened interactions between endothelial/SMC as well as myeloid/ECs in AC group, with ITGB2/VCAM and CD44/CD74 receptors potentially participating in these interactions, thereby fostering the development of pro-inflammatory plaque microenvironment. In conclusion, our study unveils metabolic shifts at single-cell level and identifies key gene signatures associated with metabolic disorders and cell-cell communication in atherosclerosis.

cell biology↗

bioRxiv2024

Granulosa cell-layer stiffening prevents the granulosa cells from escaping the post-ovulatory follicle

Ovulation is necessary for successful reproduction. After ovulation, cumulus cells and oocytes are released, while granulosa cells (GCs) remain trapped within the post-ovulatory follicle to form the corpus luteum. However, the mechanism underlying GC confinement has long been unclear. Here, we provide in vitro and in vivo evidence demonstrating that the stiffening of GC-layer as an evolutionarily conserved mechanism that hinders GCs from escaping the post-ovulatory follicles. Spatial transcriptome analysis reveals that the assembly of focal adhesions is primarily responsible for this stiffening. Disrupting focal adhesion assembly through RNA interference results in the release of GCs from the post-ovulatory follicle, leading to the formation of an aberrant corpus luteum with reduced cell density and cavities. We also uncover that the LH (hCG) -cAMP-PKA-CREB signaling axis stimulates focal adhesion assembly and induce GC-layer stiffening. Our findings introduce a novel concept of "GC-layer stiffening", which offers valuable insights into the factors that prevent GCs escape from the post-ovulatory follicle.

cell biology↗

bioRxiv2024

GenerRNA: A generative pre-trained language model for de novo RNA design

AO_SCPLOWBSTRACTC_SCPLOWThe design of RNA plays a crucial role in developing RNA vaccines, nucleic acid therapeutics, and innovative biotechnological tools. Nevertheless, existing techniques lack versatility across various tasks and frequently suffer from a deficiency of automated generation. Inspired by the remarkable success of Large Language Models (LLMs) in the realm of protein and molecule design, we present GenerRNA, the first large-scale pre-trained model for RNA generation, aiming to further automate RNA design. Our approach eliminates the need for secondary structure or other prior knowledge and is capable of de novo generation of RNA with stable secondary structures while ensuring its distinctiveness from existing sequences. This widens our exploration of RNA space, thereby enriching our understanding of RNA structures and functions. Moreover, GenerRNA is fine-tunable on smaller, more specialized datasets for particular subtasks. This flexibility and versatility enables the generation of RNAs with desired specific functionalities or properties. Upon fine-tuning GenerRNA, we successfully generated novel RNA sequences exhibiting high affinity for target proteins. GenerRNA is freely available at the following repository: https://github.com/pfnet-research/GenerRNA

bioinformatics↗

bioRxiv2024

A single-cell 3D spatiotemporal multi-omics atlas from Drosophila embryogenesis to metamorphosis

The development of a multicellular organism is a highly intricate process tightly regulated by numerous genes and pathways in both spatial and temporal manners. Here, we present Flysta3D, a comprehensive multi-omics atlas of the model organism Drosophila, spanning its developmental lifespan from embryo to pupa. Our datasets encompass 3D single-cell spatial transcriptomic, single-cell transcriptomic, and single-cell chromatin accessibility information. By integrating these multi-dimensional data, we constructed cell state trajectories that uncover the detailed profiles of tissue development. With a focus on the central nervous system (CNS) and midgut, we dissected the spatiotemporal dynamics of gene regulatory networks, cell type diversity, and morphological changes from a multi-omics perspective. This extensive atlas provides an unprecedentedly rich resource and serves as a systematic platform for studying Drosophila development with integrated single-cell data at an ultra-high spatiotemporal resolution.

developmental biology↗