Biology subjects

Rao, J.

Publications and source records attributed to Rao, J..

53 records · Page 3Linked to original sources

bioRxiv2022

Preclinical evaluation of RQ3013, a broad-spectrum mRNA vaccine against SARS-CoV-2 variants

The global emergence of SARS-CoV-2 variants has led to increasing breakthrough infections in vaccinated populations, calling for an urgent need to develop more effective and broad-spectrum vaccines to combat COVID-19. Here we report the preclinical development of RQ3013, an mRNA vaccine candidate intended to bring broad protection against SARS-CoV-2 variants of concern (VOCs). RQ3013, which contains pseudouridine-modified mRNAs formulated in lipid nanoparticles, encodes the spike(S) protein harboring a combination of mutations responsible for immune evasion of VOCs. Here we characterized the expressed S immunogen and evaluated the immunogenicity, efficacy, and safety of RQ3013 in various animal models. RQ3013 elicited robust immune responses in mice, hamsters, and nonhuman primates (NHP). It can induce high titers of antibodies with broad cross-neutralizing ability against the Wild-type, B.1.1.7, B.1.351, B.1.617.2, and the omicron B.1.1.529 variants. In mice and NHP, two doses of RQ3013 protected the upper and lower respiratory tract against infection by SARS-CoV-2 and its variants. We also proved the safety of RQ3013 in NHP models. Our results provided key support for the evaluation of RQ3013 in clinical trials.

immunology↗

bioRxiv2022

Multi-trait genomic prediction improves selection accuracy for enhancing seed mineral concentrations in pea (Pisum sativum L.)

The superiority of multi-trait genomic selection (MT-GS) over univariate genomic selection (UNI-GS) can be improved by redesigning the phenotyping strategy. In this study, we used about 300 advanced breeding lines from North Dakota State University (NDSU) pulse breeding program and about 200 USDA accessions evaluated for ten nutritional traits to assess the efficiency of sparse testing in MT-GS. Our results showed that sparse phenotyping using MT-GS consistently outperformed UNI-GS when compared to partially balanced phenotyping using MT-GS. This strategy can be further extended to multi-environment multi-trait GS to improve prediction performance and reduce the cost of phenotyping and time-consuming data collection process. Given that MT-GS relies on borrowing information from genetically correlated traits and relatives, consideration should be given to trait combinations in the training and prediction sets to improve model parameters estimate and ultimately prediction performance. Our results point to heritability and genetic correlation between traits as possible parameters to achieve this objective.

genetics↗

bioRxiv2022

STK25 inhibits PKA signaling by phosphorylating PRKAR1A

In the heart, Protein Kinase A (PKA) is critical for activating calcium handling and sarcomeric proteins in response to beta adrenergic stimulation leading to increased myocardial contractility and performance. The catalytic activity of PKA is tightly regulated by regulatory subunits which inhibit the catalytic subunit until released by cAMP binding. Phosphorylation of Type II regulatory subunits promotes PKA activation, however the role of phosphorylation in Type I regulatory subunits remain uncertain. Here we utilized human induced pluripotent stem cell cardiomyocytes (iPSC-CM) to identify STK25 as a kinase of the Type Ia regulatory subunit PRKAR1A. Phosphorylation of PRKAR1A led to inhibition of PKA kinase activity and increased binding to the catalytic subunit in the presence of cAMP. Stk25 knockout in mice diminished Prkar1a phosphorylation, increased Pka activity and augmented contractile response to beta adrenergic stimulation. Together, these data support STK25 as a negative regulator of PKA signaling through phosphorylation of PRKAR1A.

physiology↗

bioRxiv2021

Tension-driven multi-scale self-organisation in human iPSC-derived muscle fibers

Human muscle is a hierarchically organised tissue with its contractile cells called myofibers packed into large myofiber bundles. Each myofiber contains periodic myofibrils built by hundreds of contractile sarcomeres that generate large mechanical forces. To better understand the mechanisms that coordinate human muscle morphogenesis from tissue to molecular scales, we adopted a simple in vitro system using induced pluripotent stem cell-derived human myogenic precursors. When grown on an unrestricted two-dimensional substrate, developing myofibers spontaneously align and self-organise into higher-order myofiber bundles, which grow and consolidate to stable sizes. Following a transcriptional boost of sarcomeric components, myofibrils assemble into chains of periodic sarcomeres that emerge across the entire myofiber. By directly probing tension we found that tension build-up precedes sarcomere assembly and increases within each assembling myofibril. Furthermore, we found that myofiber ends stably attach to other myofibers using integrin-based attachments and thus myofiber bundling coincides with stable myofiber bundle attachment in vitro. A failure in stable myofiber attachment results in a collapse of the myofibrils. Overall, our results strongly suggest that mechanical tension across sarcomeric components as well as between differentiating myofibers is key to coordinate the multi-scale self-organisation of muscle morphogenesis.

developmental biology↗

bioRxiv2021

Multi-parameter optical imaging of immune cell activity in chimeric antigen receptor T-cell and checkpoint blockade therapies

Longitudinal multimodal imaging presents unique opportunities for noninvasive surveillance and prediction of treatment response to cancer immunotherapy. In this work we first designed a novel granzyme B activated self-assembly small molecule, G-SNAT, for quantitative assessment of cytotoxic T lymphocyte mediated cancer cell killing in vivo. In lymphoma tumor bearing mice, the retention of cyanine 5 labeled G-SNAT-Cy5 was shown to be highly correlated to CAR T-cell mediated granzyme B release and tumor eradication. In colorectal tumor-bearing transgenic mice, expressing firefly luciferase in hematopoietic cells, and which received combination treatment of anti-PD-1 and anti-CTLA-4, longitudinal bioluminescence and fluorescence imaging revealed the dynamics of immune cell expansion, trafficking, tumor infiltration, and cytotoxic activity which predicted therapeutic outcome before tumor shrinkage was evident. These results support further development of G-SNAT for imaging early immune response to checkpoint blockade and CAR T-cell therapy in patients and highlight the utility of multimodality imaging for improved mechanistic insights into cancer immunotherapy.

immunology↗

bioRxiv2021

AlphaFold-aware prediction of protein-DNA binding sites using graph transformer

Protein-DNA interactions play crucial roles in the biological systems, and identifying protein-DNA binding sites is the first step for mechanistic understanding of various biological activities (such as transcription and repair) and designing novel drugs. How to accurately identify DNA-binding residues from only protein sequence remains a challenging task. Currently, most existing sequence-based methods only consider contextual features of the sequential neighbors, which are limited to capture spatial information. Based on the recent breakthrough in protein structure prediction by AlphaFold2, we propose an accurate predictor, GraphSite, for identifying DNA-binding residues based on the structural models predicted by AlphaFold2. Here, we convert the binding site prediction problem into a graph node classification task and employ a transformer-based variant model to take the protein structural information into account. By leveraging predicted protein structures and graph transformer, GraphSite substantially improves over the latest sequence-based and structure-based methods. The algorithm is further confirmed on the independent test set of 181 proteins, where GraphSite surpasses the state-of-the-art structure-based method by 16.4% in AUPR and 11.2% in MCC, respectively. We provide the datasets, the predicted structures, and the source codes along with the pre-trained models of GraphSite at https://github.com/biomed-AI/GraphSite. The GraphSite web server is freely available at https://biomed.nscc-gz.cn/apps/GraphSite.

bioinformatics↗

bioRxiv2021

Single-dose AAV-based vaccine induces a high level of neutralizing antibodies and provides long-term protection against SARS-CoV-2 in rhesus macaques

Coronavirus disease 2019 (COVID-19), which is triggered by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, continues to threaten global public health. Developing a vaccine that only requires single immunization but provides long-term protection for the prevention and control of COVID-19 is important. Here, we developed an adeno-associated virus (AAV)-based vaccine expressing a stable receptor-binding domain (SRBD) protein. The vaccine requires only a single shot but provides effective neutralizing antibodies (NAbs) over 598 days in rhesus macaques (Macaca mulatta). Importantly, our results showed that the NAbs were kept in high level and long lasting against authentic wild-type SARS-CoV-2, Beta, Delta and Omicron variants using plaque reduction neutralization test. Of note, although we detected pre-existing AAV2/9 antibodies before immunization, the vaccine still induced high and effective NAbs against COVID-19 in rhesus macaques. AAV-SRBD immune serum also efficiently inhibited the binding of ACE2 with RBD in the SARS-CoV-2 B.1.1.7 (Alpha), B.1.351 (Beta), P.1/P.2 (Gamma), B.1.617.2 (Delta), B.1.617.1/3(Kappa), and C.37 (Lambda) variants. Thus, these data suggest that the vaccine has great potential to prevent the spread of SARS-CoV-2.

immunology↗

bioRxiv2021

Analysis of viral RNA-host protein interactomes enables rapid antiviral drug discovery

RNA viruses including SARS-CoV-2, Ebola virus (EBOV), and Zika virus (ZIKV) constitute a major threat to global public health and society. The interactions between viral genomes and host proteins are essential in the life cycle of RNA viruses and thus provide targets for drug development. However, viral RNA-host protein interactions have remained poorly characterized. Here we applied ChIRP-MS to profile the interactomes of human proteins and the RNA genomes of SARS-CoV-2, EBOV, and ZIKV in infected cells. Integrated interactome analyses revealed interaction patterns that reflect both common and virus-specific host responses, and enabled rapid drug screening to target the vulnerable host factors. We identified Enasidenib as a SARS-CoV-2 specific antiviral agent, and Trifluoperazine and Cepharanthine as broad spectrum antivirals against all three RNA viruses. One Sentence SummaryInteractome analyses of host proteins and the SARS-CoV-2, EBOV, and ZIKV RNA genomes unveil viral biology and drug targets.

microbiology↗

bioRxiv2021

MolRep: A Deep Representation Learning Library for Molecular Property Prediction

SummaryRecently, novel representation learning algorithms have shown potential for predicting molecular properties. However, unified frameworks have not yet emerged for fairly measuring algorithmic progress, and experimental procedures of different representation models often lack rigorousness and are hardly reproducible. Herein, we have developed MolRep by unifying 16 state-of-the-art models across 4 popular molecular representations for application and comparison. Furthermore, we ran more than 12.5 million experiments to optimize hyperparameters for each method on 12 common benchmark data sets. As a result, CMPNN achieves the best results ranked the 1st in 5 out of 12 tasks with an average rank of 1.75. Relatively, ECC has good performance in classification tasks and MAT good for regression (both ranked 1st for 3 tasks) with an average rank of 2.71 and 2.6, respectively. AvailabilityThe source code is available at: https://github.com/biomed-AI/MolRep Supplementary informationSupplementary data are available online.

bioinformatics↗

bioRxiv2020

A new duck genome reveals conserved and convergently evolved chromosome architectures of birds and mammals

BackgroundDucks have a typical avian karyotype that consists of macro- and microchromosomes, but a pair of much less differentiated ZW sex chromosomes compared to chicken. To elucidate the evolution of chromosome architectures between duck and chicken, and between birds and mammals, we produced a nearly complete chromosomal assembly of a female Pekin duck by combining long-read sequencing and multiplatform scaffolding techniques. ResultsThe major improvement of genome assembly and annotation quality resulted from successful resolution of lineage-specific propagated repeats that fragmented the previous Illumina-based assembly. We found that the duck topologically associated domains (TAD) are demarcated by putative binding sites of the insulator protein CTCF, housekeeping genes, or transitions of active/inactive chromatin compartments, indicating the conserved mechanisms of spatial chromosome folding with mammals. There are extensive overlaps of TAD boundaries between duck and chicken, and also between the TAD boundaries and chromosome inversion breakpoints. This suggests strong natural selection on maintaining regulatory domain integrity, or vulnerability of TAD boundaries to DNA double-strand breaks. The duck W chromosome retains 2.5-fold more genes relative to chicken. Similar to the independently evolved human Y chromosome, the duck W evolved massive dispersed palindromic structures, and a pattern of sequence divergence with the Z chromosome that reflects stepwise suppression of homologous recombination. ConclusionsOur results provide novel insights into the conserved and convergently evolved chromosome features of birds and mammals, and also importantly add to the genomic resources for poultry studies.

genomics↗

bioRxiv2020

Prednisolone rescues Duchenne Muscular Dystrophy phenotypes in human pluripotent stem cells-derived skeletal muscle in vitro

Duchenne Muscular Dystrophy (DMD) is a devastating genetic disease leading to degeneration of skeletal muscles and premature death. How dystrophin absence leads to muscle wasting remains unclear. Here, we describe an optimized protocol to differentiate human induced Pluripotent Stem Cells (iPSC) to a late myogenic stage. This allows to recapitulate classical DMD phenotypes (mislocalization of proteins of the Dystrophin-glycoprotein associated complex (DGC), increased fusion, myofiber branching, force contraction defects and calcium hyperactivation) in isogenic DMD-mutant iPSC lines in vitro. Treatment of the myogenic cultures with prednisolone (the standard of care for DMD) can dramatically rescue force contraction, fusion and branching defects in DMD iPSC lines. This argues that prednisolone acts directly on myofibers, challenging the largely prevalent view that its beneficial effects are due to anti-inflammatory properties. Our work introduces a new human in vitro model to study the onset of DMD pathology and test novel therapeutic approaches.

cell biology↗

bioRxiv2020

Imputing Single-cell RNA-seq data by combining Graph Convolution and Autoencoder Neural Networks

Single-cell RNA sequencing technology promotes the profiling of single-cell transcriptomes at an unprecedented throughput and resolution. However, in scRNA-seq studies, only a low amount of sequenced mRNA in each cell leads to missing detection for a portion of mRNA molecules, i.e. the dropout problem. The dropout event hinders various downstream analysis, such as clustering analysis, differential expression analysis, and inference of gene-to-gene relationships. Therefore, it is necessary to develop robust and effective imputation methods for the increasing scRNA-seq data. In this study, we have developed an imputation method (GraphSCI) to impute the dropout events in scRNA-seq data based on the graph convolution networks. The method takes advantage of low-dimensional representations of similar cells and gene-gene interactions to impute the dropouts. Extensive experiments demonstrated that GraphSCI outperforms other state-of-the-art methods for imputation on both simulated and real scRNA-seq data. Meanwhile, GraphSCI is able to accurately infer gene-to-gene relationships by utilizing the imputed matrix that are concealed by dropout events in raw data.

bioinformatics↗

bioRxiv2019

The Collaborative Cross Graphical Genome

The mouse reference is one of the most widely used and accurately assembled mammalian genomes, and is the foundation for a wide range of bioinformatics and genetics tools. However, it represents the genomic organization of a single inbred mouse strain. Recently, inexpensive and fast genome sequencing has enabled the assembly of other common mouse strains at a quality approaching that of the reference. However, using these alternative assemblies in standard genomics analysis pipelines presents significant challenges. It has been suggested that a pangenome reference assembly, which incorporates multiple genomes into a single representation, are the path forward, but there are few standards for, or instances of practical pangenome representations suitable for large eukaryotic genomes. We present a pragmatic graph-based pangenome representation as a genomic resource for the widely-used recombinant-inbred mouse genetic reference population known as the Collaborative Cross (CC) and its eight founder genomes. Our pangenome representation leverages existing standards for genomic sequence representations with backward-compatible extensions to describe graph topology and genome-specific annotations along paths. It packs 83 mouse genomes (8 founders + 75 CC strains) into a single graph representation that captures important notions relating genomes such as identity-by-descent and highly variable genomic regions. The introduction of special anchor nodes with sequence content provides a valid coordinate framework that divides large eukaryotic genomes into homologous segments and addresses most of the graph-based position reference issues. Parallel edges between anchors place variants within a context that facilitates orthogonal genome comparison and visualization. Furthermore, our graph structure allows annotations to be placed in multiple genomic contexts and simplifies their maintenance as the assembly improves. The CC reference pangenome provides an open framework for new tool chain development and analysis.

bioinformatics↗

bioRxiv2019

Detection and characterization of copy number variants based on whole-genome sequencing by MGI platforms

BackgroundNext-generation sequence (NGS) has rapidly developed in past years which makes whole-genome sequencing (WGS) becoming a more cost- and time-efficient choice in wide range of biological researches. We usually focus on some variant detection via WGS data, such as detection of single nucleotide polymorphism (SNP), insertion and deletion (Indel) and copy number variant (CNV), which playing an important role in many human diseases. However, the feasibility of CNV detection based on WGS by DNBSEQ platforms was unclear. We systematically analysed the genome-wide CNV detection power of DNBSEQ platforms and Illumina platforms on NA12878 with five commonly used tools, respectively.\n\nResultsDNBSEQ platforms showed stable ability to detect slighter more CNVs on genome-wide (average 1.24-fold than Illumina platforms). Then, CNVs based on DNBSEQ platforms and Illumina platforms were evaluated with two public benchmarks of NA12878, respectively. DNBSEQ and Illumina platforms showed similar sensitivities and precisions on both two benchmarks. Further, the difference between tools for CNV detection was analyzed, and indicated the selection of tool for CNV detection could affected the CNV performance, such as count, distribution, sensitivity and precision.\n\nConclusionThe major contribution of this paper is providing a comprehensive guide for CNV detection based on WGS by DNBSEQ platforms for the first time.

bioinformatics↗

bioRxiv2019

An integrated Asian human SNV and indel benchmark combining multiple sequencing methods

Precision medicine of human requires an accurate and complete reference variant benchmark for different populations. A human standard cell line of NA12878 provides a good reference for part of the human populations, but it is still lack of a fine reference standard sample and variant benchmark for the Asians. Here, we constructed a stabilized cell line of a Chinese Han volunteer. We received about 4.16T clean data of the sample using eight sequencing strategies in different laboratories, including two BGI regular NGS platforms, three Illumina regular NGS platforms, two linked-read libraries, and PacBio CCS model. The sequencing depth and reference coverage of eight sequencing strategies have reached the saturation. We detected small variants of SNPs and Indels using the eight data sets and obtained eight variant sets by performing a series of strictly quality control. Finally, we got 3.35M SNPs and 349K indels supported by all of sequencing data, which could be considered as a high confidence standard small variant sets for the studies. Besides, we also detected 5,913 high quality SNPs located in the high homologous regions supported by both linked-reads and CCS data benefited by their long-range information, while these regions are recalcitrant to regular NGS data due to the limited mappability and read length. We compared the later SNPs against the public databases and 969 sites of them were novel SNPs, indicating these SNPs provide a vital complement for the variant database. Moreover, we also phased more than 99% heterozygous SNPs also supported by linked-reads and CCS data. This work provided an integrated Asians SNV and indel benchmark for the further basic studies and precision medicine.

genomics↗

bioRxiv2019

Accurate Prediction of Genome-wide RNA Secondary Structure Profile Based On Extreme Gradient Boosting

MotivationMany studies have shown that RNA secondary structure plays a vital role in fundamental cellular processes, such as protein synthesis, mRNA processing, mRNA assembly, ribosome function and eukaryotic spliceosomes. Identification of RNA secondary structure is a key step to understand the common mechanisms underlying the translation process. Recently, a few experimental methods were developed to measure genome-wide RNA secondary structure profile through high-throughput sequencing techniques, and have been successfully applied to genomes including yeast and human. However, these high-throughput methods usually have low precision and are hard to cover all nucleotides on the RNA due to limited sequencing coverage.\n\nResultsIn this study, we developed a new method for the prediction of genome-wide RNA secondary structure profile (TH-GRASP) from RNA sequence based on eXtreme Gradient Boosting (XGBoost). The method achieves an prediction with areas under the receiver operating characteristic curve (AUC) values greater than 0.9 on three different datasets, and AUC of 0.892 by an independent test on the recently released Zika virus RNA dataset. These AUCs represent a consistent increase of >6% than the recently developed method CROSS trained by a shallow neural network. A further analysis on the 1000-Genome Project data showed that our predicted unpaired probability at mutations sites are highly correlated with the minor allele frequencies (MAF) of synonymous, non-synonymous mutations, and mutations in 3 and 5UTR with Pearson Correlation Coefficients all above 0.8. These PCCs are consistently higher than those generated by RNAplfold method. Moreover, an investigation over all human mRNA indicated a periodic distribution of the predicted unpaired probability on codons, and a decrease of paired probability in the boundary with 5 and 3 untranslated regions. These results highlighted TH-GRASP is effective to remove experimental noises and to have ability to make predictions on nucleotides with low or no coverage by fitting high-throughput genomic data for RNA secondary structure profiles, and also suggested that building model on high throughput experimental data might be a future direction to substitute analytical methods.\n\nAvailabilityThe TH-GRASP is available for academic use at https://github.com/sysu-yanglab/TH-GRASP.\n\nSupplementary informationSupplementary data are available online.

bioinformatics↗

bioRxiv2019

Leptin deficient rats develop nonalcoholic steatohepatitis with unique disease progression

Nonalcoholic steatohepatitis (NASH) is an aggressive liver disease threatening public health, however its natural history is poorly understood. Unlike ob/ob mice, Lep{triangleup}I14/{triangleup}I14 rats develop unique NASH phenotype with steatosis, lymphocyte infiltration and ballooning after postnatal week 16. Using Lep{triangleup}I14/{triangleup}I14 rats as NASH model, we studied the natural history of NASH progression by performing an integrated analysis of hepatic transcriptome from postnatal week 4 to 48. Leptin deficiency results in a robust increase in expression of genes encoding 9 rate-limiting enzymes in lipid metabolism such as ACC and FASN. However, genes in positive regulation of inflammatory response are highly expressed at week 16 and then remain the steady elevated expression till week 48. The high expression of cytokines and chemokines including CCL2, TNF, IL6 and IL1{beta} is correlated with the phosphorylation of several key molecules in pathways such as JNK and NF-{kappa}B. Meanwhile, we observed cell infiltration of MPO+ neutrophils, CD8+ T cells, CD68+ hepatic macrophages and CCR2+ inflammatory monocyte-derived macrophages, together with macrophage polarization from M2 to M1. Importantly, Lep{triangleup}I14/{triangleup}I14 rats share more homologous genes with NASH patients than previously established mouse models and crab eating monkeys with spontaneous hepatic steatosis. Transcriptomic analysis showed that many drug targets in clinical trials can be evaluated in Lep{triangleup}I14/{triangleup}I14 rats.\n\nConclusionWe characterize Lep{triangleup}I14/{triangleup}I14 rats as a unique NASH model by performing a long-term (i.e., 4 to 48 postnatal weeks) integrated transcriptomic analysis. This work reveal the temporal dynamics of hepatic gene expression in lipid metabolism and inflammation, and shed light on understanding the natural history of NASH in human beings.

pathology↗