Biology subjects

wang, y.

Publications and source records attributed to wang, y..

At least 37 records · Page 2Linked to original sources

bioRxiv2024

EnhancerBD identifing sequence feature

Deciphering the non-coding language of DNA is one of the fundamental questions in genomic research. Previous bioinformatics methods often struggled to capture this complexity, especially in cases of limited data availability. Enhancers are short DNA segments that play a crucial role in biological processes, such as enhancing the transcription of target genes. Due to their ability to be located at any position within the genome sequence, accurately identifying enhancers can be challenging. We presented a deep learning method (enhancerBD) for enhancer recognition. We extensively compared the enhancerBD with previous 18 state-of-the-art methods by independent test. Enhancer-BD achieved competitive performances. All detection results on the validation set have achieved remarkable scores for each metric. It is a solid state-of-the-art enhancer recognition software. In this paper, I extended the BERT combined DenseNet121 models by sequentially adding the layers GlobalAveragePooling2D, Dropout, and a ReLU activation function. This modification aims to enhance the convergence of the models loss function and improve its ability to predict sequence features. The improved model is not only applicable for enhancer identification but also for distinguishing enhancer strength. Moreover, it holds the potential for recognizing sequence features such as lncRNA, microRNA, insultor, and silencer.

bioinformatics↗

bioRxiv2024

Dispensable regulation of brain development and myelination by Serpina3n

Serine protease inhibitor clade A member 3n (Serpina3n) or its human orthologue SERPINA3 is a secretory immune-related molecule produced primarily in the liver and brain under homeostatic conditions and upregulated in response to system inflammation. Yet it remains elusive regarding its cellular identity and physiological significance in the development of the postnatal brain. Here, we reported that oligodendroglial lineage cells are the major cell population expressing Serpina3n protein in the postnatal murine CNS. Using loss-of-function genetic tools, we found that Serpina3n conditional knockout (cKO) from Olig2-expressing cells does not significantly affect cognitive and motor functions in mice. Serpina3n depletion does not appear to interfere with oligodendrocyte differentiation and developmental myelination nor affects the population of other glial cells and neurons in vivo. Together, these data suggest that the immune-related molecule Serpina3n plays a minor role, if any, in regulating neural cell development in the postnatal brain under homeostatic conditions. We found that Serpina3n is significantly upregulated in response to oxidative stress, and it potentiates oxidative injury and cell senescence of oligodendrocytes. Our data raise the interest in pursuing its functional significance in the CNS under disease/injury conditions.

neuroscience↗

bioRxiv2024

Multi-Channel smFRET study reveals a Compact conformation of EF-G on the Ribosome

While elongation factor G (EF-G) is crucial for ribosome translocation, the role of its GTP hydrolysis remains ambiguous. EF-Gs indispensability is further exemplified by the phosphorylation of human eukaryotic elongation factor 2 (eEF2) at Thr56, which inhibits protein synthesis globally, but its exact mechanism is not clear. In this study, we developed a multi-channel single-molecule FRET (smFRET) microscopy methodology to examine the conformational changes of E. coli EF-G induced by mutations that closely aligned with eEF2s Thr56 residue. We utilized Alexa 488/594 double-labeled EF-G to catalyze the translocation of fMet-Phe-tRNAPhe-Cy3 inside Cy5-L27 labeled ribosomes, allowing us to probe both processes within the same complex. Our findings indicate that in the presence of either GTP or GDPCP, wild-type EF-G undergoes a conformational extension upon binding to the ribosome to promote normal translocation. On the other hand, T48E and T48V mutations did not affect GTP/GDP binding or GTP hydrolysis, but impeded Poly(Phe) synthesis and caused EF-G to adopt a unique compact conformation, which wasnt observed when the mutants interact solely with the sarcin/ricin loop. This study provides new insights into EF-Gs adaptability and sheds light on the modification mechanism of human eEF2.

biophysics↗

bioRxiv2023

HiCDiff: single-cell Hi-C data denoising with diffusion models

The genome-wide single-cell chromosome conformation capture technique, i.e., single-cell Hi-C (ScHi-C), was recently developed to interrogate the conformation of the genome of individual cells. However, single-cell Hi-C data are much sparser and noisier than bulk Hi-C data of a population of cells, making it difficult to apply and analyze them in biological research. Here, we developed the first generative diffusion models (HiCDiff) to denoise single-cell Hi-C data in the form of chromosomal contact matrices. HiCDiff uses a deep residual network to remove the noise in the reverse process of diffusion and can be trained in both unsupervised and supervised learning modes. Benchmarked on several single-cell Hi-C test datasets, the diffusion models substantially remove the noise in single-cell Hi-C data. The unsupervised HiCDiff outperforms most supervised non-diffusion deep learning methods and achieves the performance comparable to the state-of-the-art supervised deep learning method in terms of multiple metrics, demonstrating that diffusion models are a useful approach to denoising single-cell Hi-C data. Moreover, its good performance holds on denoising bulk Hi-C data.

bioinformatics↗

bioRxiv2023

AutoHiC: a deep-learning method for automatic and accurate chromosome-level genome assembly

An accurate genome at the chromosome level is the key to unraveling the mysteries of gene function and unlocking the mechanisms of disease. Irrespective of the sequencing methodology adopted, Hi-C aided scaffolding serves as a principal avenue for generating genome assemblies at the chromosomal level. However, the results of such scaffolding are often flawed and require extensive manual refinement. In this paper, we introduce AutoHiC, an innovative deep learning-based tool designed to identify and rectify genome assembly errors. Diverging from conventional approaches, AutoHiC harnesses the power of high-dimensional Hi-C data to enhance genome continuity and accuracy through a fully automated workflow and iterative error correction mechanism. AutoHiC was trained on Hi-C data from more than 300 species (approximately five hundred thousand interaction maps) in DNA Zoo and NCBI. Its confusion matrix results show that the average error detection accuracy is over 90%, and the area under the precision-recall curve is close to 1, making it a powerful error detection capability. The benchmarking results demonstrate AutoHiCs ability to substantially enhance genome continuity and significantly reduce error rates, providing a more reliable foundation for genomics research. Furthermore, AutoHiC generates comprehensive result reports, offering users insights into the assembly process and outcomes. In summary, AutoHiC represents a breakthrough in automated error detection and correction for genome assembly, effectively promoting more accurate and comprehensive genome assemblies.

bioinformatics↗

bioRxiv2023

Identification of a recombinant human astrovirus type 5 strain from an acute gastroenteritis outbreak in Beijing, China

Two samples positive for the same strain (2103CP) of human astrovirus (HAstV) were identified during an acute gastroenteritis outbreak in Beijing, China. A full genomic analysis showed that for both samples, open reading frame 1a (ORF1a) clustered with HAstV-1, whereas ORF1b and ORF2 clustered with HAstV-5. The recombination site was detected upstream of the region where ORF1a and ORF1b overlapped. Recombinant HAstV-5 strains were reported previously in China in 2013 and 2021. Our results indicate the need for continuous surveillance of the prevalence and evolution of this recombinant HAstV-5 in China.

evolutionary biology↗

bioRxiv2023

Ribozyme synthesis of both L- and D- amino acid oligos

The ribosome is responsible for assembling proteins using 20 naturally occurring L-handed amino acids. However, incorporating non-natural amino acids into a protein is a challenging process needs improvement. In this study, we report a new possible approach to creating nonnatural peptides using ribozymes inspired by the peptidyl transfer center. These RNA scaffolds, which are approximately 100 nucleotides in length, bind to RNase T1 truncated tRNA-like chimeras and bring them into close proximity to facilitate peptide ligation. We used single-molecule fluorescence resonance energy transfer (smFRET) to show close distances between RNA-RNA, tRNALys-tRNALys, and RNA-tRNALys pairs, which strongly suggests that the mechanism of peptide ligation is due to the proximity of the substrate through dimerization of the enzymes. Mass spectrometry analysis confirmed the detection of oligopeptides from four amino acids, including L-Lysine, D-Lysine, L-Phenylalanine, and D-Phenylalanine. These results indicate that ribozymes have greater flexibility in accommodating nonnatural amino acids. Our findings pave the way for potentially new avenues in the synthesis of nonnatural peptides, beyond the limitations of ribosomal peptide synthesis and other existing methods. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=190 SRC="FIGDIR/small/538729v1_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@121044corg.highwire.dtl.DTLVardef@a11b2eorg.highwire.dtl.DTLVardef@ffa0b9org.highwire.dtl.DTLVardef@90f512_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2023

Efficient transgene-free genome editing in plants in the T0 generation based on a co-editing strategy

Transgene-free genome editing of plants in the T0 generation is highly desirable but challenging, especially in perennials and vegetatively propagated plants. Here, we investigated the co-editing strategy for generating transgene-free, gene-edited plants via Agrobacterium-mediated transient expression of cytosine base editor (CBE)/gRNA-Cas12a/crRNA-GFP in planta. Specifically, CBE/gRNA was used to base edit the ALS gene to confer resistance to herbicide chlorsulfuron as a selection marker, which has no negative effects on plant phenotypes; Cas12a/crRNA was used for editing genes(s) of interest; GFP was used for selecting transgene-free transformants. Using this approach, transgene-free genome-edited plants were efficiently generated for various genes (either individual or multiplex) in tomato, tobacco, potato, and citrus in the T0 generation. The biallelic/homozygous transgene-free mutation rates for target genes among herbicide-resistant transformants ranged from 8% to 50%. Whole genome sequencing further confirmed transgene-free and absence of off-target mutations in the edited plants. The co-editing strategy is efficient for generating transgene-free, genome-edited plants in the T0 generation, thus being a potent tool for plant genetic improvement.

plant biology↗

bioRxiv2023

Efficient generation of transgene-free canker-resistant Citrus sinensis using Cas12a/crRNA ribonucleoprotein

Citrus is one of the top three tree crops in the world and its production faces many devastating disease challenges such as citrus canker caused by Xanthomonas citri subsp. citri (Xcc). Genetic improvement of citrus via traditional approaches is a lengthy (approximately 20 years) and laborious process. Biotechnological approaches including CRISPR genome editing technologies have shown promise. However, none of the citrus plants generated by biotechnological approaches have been commercialized, which primarily resulted from the transgenic nature of the genetically modified plants. Here, we successfully developed transgene-free canker-resistant Citrus sinensis lines in the T0 generation within 10 months through transformation of embryogenic citrus protoplasts with Cas12a/crRNA ribonucleoprotein (RNP) to edit the canker susceptibility gene CsLOB1. Among the 39 regenerated lines, 38 are biallelic/homozygous mutants based on Sanger sequencing analysis of targeting sites and whole genome sequencing, demonstrating a 97.4% biallelic/homozygous mutation rate. The edited lines do not contain off-target mutations. The CsLOB1 edited C. sinensis lines demonstrate no differences from wild type plants except canker resistance. Importantly, the transgene-free canker-resistant C. sinensis lines have received regulatory approval by USDA APHIS. This study presents an efficient genome editing approach for citrus using Cas12a/crRNA RNP, which has a broad impact on genetic improvement of elite citrus varieties and potentially other tree crops and their genetic study. This study represents a breakthrough by generating the first transgene-free canker-resistant C. sinensis lines that provide a sustainable and efficient solution to control citrus canker.

bioengineering↗

bioRxiv2022

Integrating Network Pharmacology And Experimental Verification To Explore The Mechanism Of Qionggui Power Against Atherosclerosis

Qionggui Power (QP), a classic prescription in Traditional Chinese Medicine (TCM), has shown potential in the treatment of atherosclerosis during the past decades. However, the mechanism that mediates these cardiovascular benefits remains to be fully elucidated. Here, we investigated the effects and mechanisms of QP against atherosclerosis with network pharmacology approaches and in vitro model. The active ingredients and related targets of QP were collected from public databases. The hub targets and signaling pathways of QP against AS were defined by extensive application of bioinformatics approaches, including the protein-protein interaction (PPI) network, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG). The predicted major targets were validated in LPS-stimulated murine macrophages RAW264.7. The anti-inflammatory properties of QP were also evaluated in this model. In silico investigation of QP resulted in the identification of 18 active ingredients and 49 chemical targets intersecting with AS-related genes. And KEGG pathway analysis revealed a high enrichment in the Lipid and Atherosclerosis pathway of these chemical targets. Biochemical analysis showed marked effects of QP on the expression of predicted chemical targets (PPARr, CAT, PTGS2) and LPS-induced inflammatory genes (IL1, IL6, and TNF). And these inhibitory effects were linked to the suppression of the NF-{kappa}B signaling pathway, which was activated by the LPS stimulus. Our findings revealed the therapeutic potential of QP in the prevention and treatment of atherosclerosis. Graphical Abstract O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

pharmacology and toxicology↗

bioRxiv2022

Bayesian linear models with unknown design over finite alphabets

Our topic is the reconstruction of the unknown matrices S and{omega} for the multivariate linear model Y = S{omega} +{varepsilon} under the assumption that the entries of S are drawn from the finite alphabet [A] = 0, 1 and{omega} is a weight matrix. While a frequentist method has recently been proposed for this purpose, a Bayesian approach seems also desirable. We therefore provide a new hierarchical Bayesian method for this inferential task. Our approach provides estimates of the posterior that may be used to quantify uncertainty. Since matching permutations in both S and{omega} lead to the same reconstruction S{omega}, we introduce an order-preserving shrinkage prior to establish identifiability with respect to permutations.

genetics↗

bioRxiv2022

CircRNA_33702 promotes renal fibrosis by targeting the miR-29b-3p/WISP1 pathway

Growing evidence suggest that circular RNAs (circRNAs) are critical mediators in renal diseases. However, there have been very few reports about the role of circRNAs in renal fibrosis. In this study, circRNA_33702 was found to be upregulated, both in UUO mice and in TGF-{beta} 1-treated BUMPT cells. Whilst knockdown of circRNA_33702 was shown to relieve the TGF-{beta} 1-induced expression of collagen I, collagen III and fibronectin; overexpression of circRNA_33702 was found to exert an inhibitory effect on the expression of the same genes. Mechanistically, circRNA_33702 was demonstrated to bind directly with miR-29b-3p and inhibit its expression. Moreover, WISP1 was identified as a target of miR-29b-3p and the expression of WISP1 was observed to be repressed by miR-29b-3p. Notably, knockdown of circRNA_33702 was found to attenuate the expression of collagen I, collagen III and fibronectin by inhibiting the expression of WISP1, and the observed inhibitory effect can be reversed by miR-29b-3p inhibitor. Finally, inhibition of circRNA_33702 was shown to attenuate interstitial fibrosis in UUO mice via the miR-29b-3p/WISP1 axis. In general, our data show that circRNA_33702 may promote renal fibrosis via the miR-29b-3p/WISP1 axis, which may potentially be developed as a new therapeutic target.

molecular biology↗

bioRxiv2021

Histone neutralization in a rat model of acute lung injury induced by double-hit lipopolysaccharide

BackgroundAcute respiratory distress syndrome (ARDS) remains a challenge because of its high morbidity and mortality. Circulation histones levels in ARDS patients were correlated to disease severity and mortality. This study examined the impact of histone neutralization in a rat model of acute lung injury (ALI) induced by a lipopolysaccharide (LPS) double-hit. MethodsSixty-eight male Sprague-Dawley rats were randomized to sham (N=8, received saline only) or LPS (N=60). The LPS double-hit consisted of a 0.8 mg/kg intraperitoneal injection followed after 16 hours by 5 mg/kg intra-tracheal nebulized LPS. The LPS group was then randomized into five groups: LPS only (N=12); LPS + 5, 25, or 100 mg/kg intravenous STC3141 every 8 hours (LPS+L, LPS+M, LPS+H, respectively, each N=12); or LPS + intraperitoneal dexamethasone 2.5 mg/kg every 24 hours for 56 hours (LPS+D, N=12) The animals were observed for 72 hours. ResultsLPS animals developed ALI as suggested by lower oxygenation, lung edema formation, and histological changes compared to the sham animals. Compared to the LPS group, LPS+H and +D animals had significantly lower circulating histone levels; only the LPS+D group had significantly lower bronchoalveolar lavage fluid (BALF) histone concentrations. The LPS+L, +M, +H and +D groups had improved oxygenation compared to the LPS group and the LPS+H and +D groups had a lower lung wet-to-dry ratio. All animals survived. ConclusionNeutralization of histone using STC3141, especially at high dose, had similar therapeutic effects to dexamethasone in this LPS double-hit rat ALI model, with significantly decreased circulating histone concentration, improved oxygenation, and decreased lung edema formation.

pharmacology and toxicology↗

bioRxiv2021

Efficient and Rapid generation of neural stem cells by direct conversion Fibroblasts with A Single microRNA

Neural stem cells (NSCs) have great potential in the application of neurodegenerative disease therapy, drug screening and disease modeling. NSC can be generated by reprogramming from terminally differentiated cells with transcription factors or small molecules. However, current methods for producing NSCs involve the danger of integrating foreign genes into the genome and the problem of low efficiency. Here, we report an efficient method to generate NSCs from human skin-derived fibroblasts with microRNA (mir-302a) in 2-3 days. The induced NSCs (iNSCs) have more than 90% of purity. Their morphology is similar to regular NSCs, expressing key markers including Nestin, Pax6 and Sox2, and can be expanded for more than 20 passages in vitro. They can also differentiate into functional neuron progeny, astrocytes and oligodendrocytes as well. Those cells can elicit action potential, can be xeno-transplanted into the brain of immune-deficient mice, and can survive and differentiate in vivo without tumor formation. This study shows that a single part of pluripotency-inducing mir-302 cluster can drive fibroblasts reprogramming, providing a general platform for high-efficiency generation of individual-specific human NSCs for studies of neuron system development and regenerative cell therapy.

neuroscience↗

bioRxiv2021

Transcriptional regulation of schizophrenia risk gene TCF4 in inhibitory neurons during neurodevelopment

The pathology underlying schizophrenia (SCZ) involves cell type-specific and developmental stage-specific dysregulation of multiple gene regulatory networks dominated by some key transcription factors, such as SCZ risk gene transcription factor 4 (TCF4). Previous studies on the regulatory mechanism of TCF4 use SY5Y as the cellular model, which could not reflect its cell typespecific role in the real world. Using the transcriptional profile of whole brain during development stages and single-cell transcriptome data in the developing human prefrontal cortex, we found that TCF4 was preferentially expressed in the interneuron. Chromatin immunoprecipitation combined with sequencing (ChIP-Seq) in human embryonic stem cells (hESC)-derived interneurons revealed that TCF4 primarily activate transcription of genes associated with cortex development and telencephalon regionalization in a long-range manner. As expected, the downstream targets of TCF4 were distinct in inhibitory neurons and neural stem cells during early neurodevelopment, justifying the importance of our study. Deeper investigation further revealed that TCF4 regulate genes related to neurotransmission distally in interneuron in a c-FOS dependent manner, while TCF4 and TCF3 synergistically regulate genes associated with cell proliferation associated proximally in neural stem cells. Our findings suggested that defects in development of interneuron, for instance as a result of TCF4 abnormality, may break excitation and inhibition balance and contribute significantly to the risk of SCZ.

genomics↗

bioRxiv2020

A Reference Feature based method for Quantification and Identification of LC-MS based untargeted metabolomics

Batch inconsistency is a major problem when applying LC-MS based untargeted metabolomics in real-time analysis situation such as clinical diagnosis or health monitoring. And inefficiency of collecting MS2 is a major problem for metabolite identification. Here, we developed a reference-feature based quantification and identification strategy (RFQI). In RFQI, samples are individually profiled using a pre-fixed reference feature table. Quantification results show that RFQI improves features overlap rate and reduce variance across batches significantly in real-time-analysis mode, and can find more than 4-fold numbers of features. Besides, RFQI collects MS2 from consecutive increasing samples for metabolite identification of pre-fixed features, thus it can effectively compensate for the poor efficiency of MS2 collection in data-dependent acquisition mode. In summary, RFQI can make full advantage of consecutive increasing samples in real-time analysis situation, both for quantification and identification.

bioinformatics↗

bioRxiv2020

Constructing early diagnosis model of colorectal cancer based on expression profile

purposeIn order to break through the restrictive factors such as the fecal occult blood test (FOBT) in the routine detection of bowel cancer, which is susceptible to diet and drugs, and the high cost and inconvenience of microscopy, Seeking a possible FOBT alternative. MethodsAn error back propagation neural network (BPNN) algorithm was used to construct a CRC diagnosis model based on expression profiles. ResultsThe accuracy of the model on the training and test sets is 0.943 and 0.935, respectively. AUC all reached above 0.95. ConclusionThe CRC molecular detection model based on expression profiles provides a possible alternative to FOBT. It provides a new approach and method for the clinical diagnosis of bowel cancer.

genetics↗

bioRxiv2019

Time-ResNeXt for epilepsy recognition based on EEG signals

ObjectiveTo automatically detect dynamic EEG signals to reduce the time cost of epilepsy diagnosis. In the signal recognition of electroencephalogram (EEG) of epilepsy, traditional machine learning and statistical methods require manual feature labeling engineering in order to show excellent results on a single data set. And the artificially selected features may carry a bias, and cannot guarantee the validity and expansibility in real-world data. In practical applications, deep learning methods can release people from feature engineering to a certain extent. As long as the focus is on the expansion of data quality and quantity, the algorithm model can learn automatically to get better improvements. In addition, the deep learning method can also extract many features that are difficult for humans to perceive, thereby making the algorithm more robust. MethodBased on the design idea of ResNeXt deep neural network, this paper designs a Time-ResNeXt network structure suitable for time series EEG epilepsy detection to identify EEG signals. ResultsThe accuracy rate of Time-ResNeXt in the detection of EEG epilepsy can reach 90.50%. ConclusionThe Time-ResNeXt network structure produces extremely advanced performance on the benchmark dataset (Berne-Barcelona dataset), and has great potential for improving clinical practice.

bioinformatics↗