Biology subjects

Bao, Y.

Publications and source records attributed to Bao, Y..

At least 73 records · Page 4Linked to original sources

bioRxiv2023

Pan-genome and Haplotype Map of Cultivars and Their Wild Ancestors Provides Insights into Adaptive Evolution of Cassava (Manihot esculenta Crantz)

Cassava is the most important starch sources, a tropical model crop. We constructed nearly T2T genomes of cultivar AM560, wild ancestors FLA4047 and W14, pan-genome of 24 representatives and a clarified evolutionary tree with 486 accessions. Comparison of SVs and SNVs between the ancestors and cultivated cassavas revealed predominant expansion, contraction of genes and gene families. Significantly selective sweeping occurred in the cassava genomes in 122 footprints with 1,519 candidate domestication genes. We identified selective mutations in MeCSK and MeFNR3 promoting photoreaction associated with MeNADP-ME of C4 assimilation in modern cassava. Co-evolved retardation of floral primordia and initiation of storage roots arose from MeCOL5 mutants with altered bindings to MeFT1, MeFT2 and MeTFL2. MebHLHs evolved to regulate the biosynthesis, transport and endogenous remobilization of cyanogenic glucosides, with new functionalities of MeMATE1, MeGTR in selected sweet cassava. These findings enhanced comprehensive knowledge and database on the evolution and breeding of cassava. HIGHLIGHTSO_LIThree nearly T2T cassava genomes of cultivar AM560 and its wild ancestors FLA4047 and W14. C_LIO_LIA species-level cassava panSV haplotype map across 346,322 structural variations over 31,362 gene families and 96,032,008 SNPs and InDels variations globally and a clarified evolutionary tree with 486 accessions. C_LIO_LISelective mutations in MeCSK and MeFNR3 promoted photoreaction associated with MeNADP-ME of C4 assimilation shaped the C3-C4 intermediate photosynthesis of modern cassava. C_LIO_LICoevolution of floral primordia contrary to initiated storage root is pivotal for the domestication of cassava, and arose from MeCOL5 mutants altered the binding with MeFT1, MeFT2 (SP6A), and MeTFL2. C_LI

systems biology↗

bioRxiv2023

Machine learning detection of SARS-CoV-2 high-risk variants

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has evolved many high-risk variants, resulting in repeated COVID-19 waves of pandemic during the past years. Therefore, accurate early-warning of high-risk variants is vital for epidemic prevention and control. Here we construct a machine learning model to predict high-risk variants of SARS-CoV-2 by LightGBM algorithm based on several important haplotype network features. As demonstrated on a series of different retrospective testing datasets, our model achieves accurate prediction of all variants of concern (VOC) and most variants of interest (AUC=0.96). Prediction based on the latest sequences shows that the newly emerging lineage BA.5 has the highest risk score and spreads rapidly to become a major epidemic lineage in multiple countries, suggesting that BA.5 bears great potential to be a VOC. In sum, our machine learning model is capable to early predict high-risk variants soon after their emergence, thus greatly improving public health preparedness against the evolving virus.

bioinformatics↗

bioRxiv2023

Changes in the urine proteome after massage in healthy people

This study aimed to explore the effect of massage on the urine proteome of healthy people. In this study, participants underwent 1-hour whole body massage. Urine samples were collected at 0, 2, and 24h after the massage and urine proteins were analyzed using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Compared with the control (before massage), 41 differential proteins were identified in the group 2h after the massage, the random mean number of differentially produced proteins was 11 with 73% confidence, and the biological process of protein enrichment was catecholamine biosynthesis, which was related to the promotion of metabolism and the regulation of neural activities. While 29 differential proteins were identified in the group 24h after the massage, the random average number of differential proteins produced was 10, with the confidence of the difference decreased to 65%, and the effective biological process could not be enriched at this time. The results suggested that the difference in urine protein was greater at 2h after the massage and gradually decreased at 24h after the massage. The proteome of urine may reflect changes in the body following minor massage stimuli, providing a potential way to evaluate the effects of massage therapy.

biochemistry↗

bioRxiv2022

A Unitary Mechanism Underlies Adaptation to Both Local and Global Environmental Statistics in Time Perception

Our sense of the passage of time flexibly adapts to the statistical properties of the temporal context. Humans and non-human species exhibit a perceptual bias towards the mean of durations previously observed as well as serial dependence, a perceptual bias towards the duration of recently processed events. Here we asked whether those two phenomena arise from a unitary mechanism or reflect the operation of two distinct systems that adapt separately to the global and local statistics of the environment. We employed a set of duration reproduction tasks in which the target duration was sampled from distributions with different variances and means. The central tendency and serial dependence biases were jointly modulated by the range and the variance of the prior. These effects were well-captured by a unitary mechanism model in which temporal expectancies are updated after each trial based on perceptual observations. Alternative models that assume separate mechanisms for global and local contextual effects failed to capture the empirical results. TeaserTime perception of humans is shaped by a common mechanism that is sensitive to short-term and long-term environmental changes.

neuroscience↗

bioRxiv2022

Serial dependence in timing at the perceptual level being modulated by working memory

Recent experiences bias the perception of following stimuli, as has been verified in various kinds of experiments in visual perception. This phenomenon, known as serial dependence, may reflect mechanisms to maintain perceptual stability. In the current study, we examined several key properties of serial dependence in temporal perception. Firstly, we examined the source of serial dependence effect in temporal perception. We found that perception without motor reproduction is sufficient to induce the sequential effect; the motor reproduction caused a stronger effect and it is achieved by biasing the perception of the future target duration rather than directly influences the subsequent movement. Secondly, we ask how the working memory influences serial dependence in the in a temporal reproduction task. By varying the delay time between standard duration and the reproduction, we showed that the strength of serial dependence enhanced as the delay increased. Those features of serial dependence are consistent with what has been observed in the visual perceptual tasks, for example, orientation perception or location perception. The similarities between the visual and the timing tasks may suggest a similar neural coding mechanism of magnitude between the visual stimuli and the duration.

neuroscience↗

bioRxiv2022

Network-based hub biomarker discovery for glaucoma

Glaucoma is an optic neuropathy, and the leading cause of irreversible blindness worldwide. However, the early detection of glaucoma remains challenging as chronic forms of glaucoma remain largely asymptomatic until considerable irreversible visual field deficits have ensued. Thus, biomarkers that facilitate early diagnosis and treatment for patients with a high risk of progression are critical. Network medicine approaches can be useful in identifying key relationships and important biomolecules for complex diseases. In this paper, we identified several hub biomarkers/drug targets for the diagnosis, treatment and prognosis for glaucoma and explored their associations for glaucoma based on human disease-biomarker and disease-target-drug networks. These results were verified by text-mining and genomic/epidemiology data. We also predicted the new application of BMP1 and MMP9 to diagnose glaucoma and confirm the theory of hub biomarkers with multiple clinical applications. Further, relevant pivotal pathways (regulation of the multicellular organismal process, regulation of localisation, and cytoplasmic vesicle for biomarkers; signal transduction and developmental process for targets) for these hub biomolecules were discovered, which may be foundations for future biomarker and drug target prediction for glaucoma. In conclusion, based on complex networks, hub biomolecules, essential pathways, and close diseases were identified for glaucoma in diagnosis, treatment and prognosis.

bioinformatics↗

bioRxiv2022

An ensemble of interconverting conformations of the elemental paused transcription complex creates regulatory options

Transcriptional pausing underpins regulation of cellular RNA synthesis but its mechanism remains incompletely understood. Sequence-specific interactions of DNA and RNA with the dynamic, multidomain RNA polymerase (RNAP) trigger reversible conformational changes at pause sites that temporarily interrupt the nucleotide addition cycle. These interactions initially rearrange the elongation complex (EC) into an elemental paused EC (ePEC). ePECs can form longer-lived PECs by further rearrangements or interactions of diffusible regulators. For both bacterial and mammalian RNAPs, a half-translocated state in which the next DNA template base fails to load into the active site appears central to the ePEC. Some RNAPs also swivel interconnected modules that may stabilize the ePEC. However, it is unclear if swiveling and half-translocation are requisite features of a single ePEC state or if multiple ePEC states exist. Here we use cryo-EM analysis of ePECs with different RNA-DNA sequences combined with biochemical probes of ePEC structure to define an interconverting ensemble of ePEC states. ePECs occupy either pre- or half-translocated states but do not always swivel, indicating that difficulty in forming the post-translocated state at certain RNA-DNA sequences may be the essence of the ePEC. The existence of multiple ePEC conformations has broad implications for transcriptional regulation. SIGNIFICANCETranscriptional pausing provides a hub for gene regulation. Pausing provides a timing mechanism to coordinate regulatory interactions, co-transcriptional RNA folding and protein synthesis, and stop signals for transcriptional termination. Cellular RNA polymerases (RNAPs) are complex, with multiple mobile modules shifting positions to control its catalytic activity and pause RNAP in response to DNA-encoded pause signals. Understanding how these modules move to enable pausing is crucial for a mechanistic understanding of gene regulation. Our results clarify the picture significantly by defining multiple states among which paused RNAP partitions in response to different pause signals. This work contributes to an emerging theme wherein multiple interconverting states of the RNAP proceed through a pathway (e.g., initiation or pausing), providing multiple opportunities for regulation.

biochemistry↗

bioRxiv2022

McAN: an ultrafast haplotype network construction algorithm

SummaryHaplotype network is becoming popular due to its increasing use in analyzing genealogical relationships of closely related genomes. We newly proposed McAN, a minimum-cost arborescence based haplotype network construction algorithm, by considering mutation spectrum history (mutations in ancestry haplotype should be contained in descendant haplotype), node size (corresponding to sample count for a given node) and sampling time. McAN is two orders of magnitude faster than the state-of-the-art algorithms, making it suitable for analyzation of massive sequences. AvailabilitySource code is written in C/C++ and available at https://github.com/Theory-Lun/McAN and https://ngdc.cncb.ac.cn/biocode/tools/BT007301 under the MIT license. The online web service of McAN is available at https://ngdc.cncb.ac.cn/ncov/online/tool/haplotype. SARS-CoV-2 dataset are available at https://ngdc.cncb.ac.cn/ncov/.

bioinformatics↗

bioRxiv2022

Epigenetic markers of adverse lifestyle identified among night shift workers

BackgroundEpigenetic changes in the form of DNA methylation (DNAm) may act as biological markers of risk factors or adverse health states. We investigated associations between night shift work and established DNAm predictors of lifestyle, and compared them with those observed between night shift work and self-reported or conventionally-measured phenotypes. MethodsIn two cohort studies, Generation Scotland (GS) (n=7,028) and Understanding Society (UKHLS) (n=1,175), we evaluated associations between night shift work and four lifestyle factors (body mass index, smoking, alcohol, education) using both conventionally-measured phenotypes and DNA methylation-based scores proxying the phenotypes. DNA methylation-based measures of biological ageing were also generated using six established "epigenetic clocks". Meta-analysis of GS and UKHLS results was conducted using inverse-variance weighted fixed effects. ResultsNight shift work was associated with higher BMI (0.79; 95%CI 0.02, 1.56; p=0.04) and lower education (-0.18; -0.30, -0.07; p=0.002). There was weak evidence of association between night shift work and DNAm scores for smoking (0.06, -0.03, 0.15; p=0.18) and education (-0.24; -0.49, 0.01; p=0.06) in fully adjusted models. Two of the epigenetic age measures demonstrated higher age acceleration among night shift workers (0.80; 0.42, 1.18; p<0.001 for GrimAge and 0.46; 0.00, 0.92; p=0.05 for PhenoAge). ConclusionsNight shift work is associated with phenotypic and DNAm-based measures of lower education. Night shift work was also related to DNAm predictors of smoking and ageing.

genetics↗

bioRxiv2022

Void volume fraction of granular scaffolds

Void volume fraction (VVF) of granular biomaterials is a global measurement frequently used to characterize void space. There is currently no gold standard for measuring the VVF of granular scaffolds made in lab. To help the biomaterials field, we provide a library of different simulated scaffolds with known VVF for easy look-up. We use our simulated data to explore the relationship between microscope magnification and VVF, and we study the accuracy of approximating VVF using 2-D z-slice images, which is the most common approach for computing VVF of real scaffolds. Lastly, we test four different approaches for computing VVF using microscope images of real granular scaffolds and reveal that VVF may be an unreliable descriptor.

bioengineering↗

bioRxiv2022

Genetic Diversity of Candidatus Liberibacter asiaticus Based on Four Hypervariable Genomic Regions in China

Huanglongbing (HLB; greening disease), caused by Candidatus Liberibacter asiaticus (CLas), is the most damaging citrus disease worldwide. The disease has spread throughout the citrus-producing regions of Guangxi, Guangdong, Fujian, and others in China. A total of 1,789 HLB-like symptomatic or asymptomatic samples were collected from the Guangxi and Fujian provinces of China to decipher the genetic diversity of CLas and its correlation with pathogenicity and host range. The disease was the most severe in orange and the least in pomelo. CLas bacteria associated with the specific geographical and citrus variety infected more than 50% of the HLB-like symptomatic samples. We identified a total of 6,286 minor variations by comparing 35 published CLas genomes and observed a highly heterogeneous variation distribution across the genome. Highly diverse regions, including two prophages, were generally more unstable and prone to lose. In the collected CLas strains, four highly diverse non-prophage segments and three prophage segments in the prophage region were chosen for PCR amplification and genotyping. Four hypervariable regions were used to decipher CLas diversity. A total of 100 strains were divided into four groups, of which 90 strains were clustered into two clades with 15 reported reference genomes, while 10 were grouped in two clades separately from the reported genomes. This study provides insight into the molecular characteristics and genetic variations of different CLas strains in China and might help develop HLB prevention and control strategies. ImportanceThe objective of the present study is to characterize the hypervariable genomic region sequence, decipher the genetic diversity of CLas strains from China, understand how various strains differ, and lay the foundation for developing HLB prevention and control strategies.

microbiology↗

bioRxiv2022

Genome-wide analyses of PAM-relaxed Cas9 genome editors reveal substantial off-target effects by ABE8e in rice

PAM-relaxed Cas9 nucleases, cytosine base editors and adenine base editors are promising tools for precise genome editing in plants. However, their genome-wide off-target effects are largely undetermined. Here, we conduct whole-genome sequencing (WGS) analyses of transgenic plants edited by xCas9, Cas9-NGv1, Cas9-NG, SpRY, nCas9-NG-PmCDA1, nSpRY-PmCDA1 and nSpRY-ABE8e in rice. Our results reveal different guide RNA (gRNA)-dependent off-target effects with different editors. De novo generated new gRNAs by SpRY editors lead to additional but not substantial off-target mutations. Strikingly, ABE8e results in ~500 genome-wide A-to-G off-target mutations at TA motif sites per transgenic plant. The preference of the TA motif by ABE8e is also observed at the target sites. Finally, we investigate the timeline and mechanism of somaclonal variation due to tissue culture, which chiefly contributes to the background mutations. This study provides a comprehensive understanding on the scales and mechanisms of off-target and background mutations during PAM-relaxed genome editing in plants.

genetics↗

bioRxiv2022

Basis of narrow-spectrum activity of fidaxomicin on gut pathogen Clostridioides difficile

Fidaxomicin (Fdx) is widely used to treat Clostridioides difficile (Cdiff) infections (CDIs), but the molecular basis of its narrow-spectrum activity in the human gut microbiome remains enigmatic. CDIs are a leading cause of nosocomial deaths. Fdx, which inhibits RNA polymerase (RNAP), targets Cdiff with minimal effects on gut commensals, reducing CDI recurrence. Here, we present the cryo-electron microscopy structure of Cdiff RNAP in complex with Fdx, allowing us to identify a crucial Fdx-binding determinant of Cdiff RNAP that is absent in most gut microbiota like Proteobacteria and Bacteroidetes. By combining structural, biochemical, and bioinformatic analyses, we establish that a single RNAP residue is a sensitizing element for Fdx narrow-spectrum activity. Our results provide a blueprint for targeted drug design against an important human pathogen.

microbiology↗

bioRxiv2022

Genomic perspectives on the emerging SARS-CoV-2 Omicron variant

A new variant of concern for SARS-CoV-2, Omicron (B.1.1.529), was designated by the World Health Organization on November 26, 2021. This study analyzed the viral genome sequencing data of 108 samples collected from patients infected with Omicron. First, we found that the enrichment efficiency of viral nucleic acids was reduced due to mutations in the region where the primers anneal to. Second, the Omicron variant possesses an excessive number of mutations compared to other variants circulating at the same time (62 vs. 45), especially in the Spike gene. Mutations in the Spike gene confer alterations in 32 amino acid residues, which was more than those observed in other SARS-CoV-2 variants. Moreover, a large number of nonsynonymous mutations occur in the codons for the amino acid residues located on the surface of the Spike protein, which could potentially affect the replication, infectivity, and antigenicity of SARS-CoV-2. Third, there are 53 mutations between the Omicron variant and its closest sequences available in public databases. Many of those mutations were rarely observed in the public database and had a low mutation rate. In addition, the linkage disequilibrium between these mutations were low, with a limited number of mutations (6) concurrently observed in the same genome, suggesting that the Omicron variant would be in a different evolutionary branch from the currently prevalent variants. To improve our ability to detect and track the source of new variants rapidly, it is imperative to further strengthen genomic surveillance and data sharing globally in a timely manner.

genomics↗

bioRxiv2021

ZipHiC: a novel Bayesian framework to identify enriched interactions and experimental biases in Hi-C data

Several computational and statistical methods have been developed to analyse data generated through the 3C-based methods, especially the Hi-C. Most of existing methods do not account for dependency in Hi-C data. Here, we present ZipHiC, a novel statistical method to explore Hi-C data focusing on detection of enriched contacts. ZipHiC implements a Bayesian method based on a hidden Markov random field (HMRF) model and the Approximate Bayesian Computation (ABC) to detect interactions in two-dimensional space based on Hi-C contact frequency matrix. ZipHiC uses data on the sources of biases related to contact frequency matrix, allows borrowing information from neighbours using the Potts model and improves computation speed by using the ABC model. In addition to outperforming existing tools on both simulated and real data, our model also provides insights into different sources of biases that affects Hi-C data. We show that some datasets display higher biases from DNA accessibility or Transposable Elements content. Furthermore, approximately half of the detected significant interactions connect promoters with other parts of the genome indicating a functional biological role. Finally, we found that the micro-C datasets display higher biases from DNA accessibility compared to a similar Hi-C experiment, but this can be corrected by ZipHiC.

bioinformatics↗

bioRxiv2021

GMQN: A reference-based method for correcting batch effects as well as probes bias in HumanMethylation BeadChip

Illumina HumanMethylation BeadChip is one of the most cost-effective ways to quantify DNA methylation levels at the single-base level across the human genome, which makes it a routine platform for epigenome-wide association studies. It has accumulated tens of thousands of DNA methylation array samples in public databases, thus provide great support for data integration and further analysis. However, majority of public DNA methylation data are deposited as processed data without background probes which are widely used in data normalization. Here we present Gaussian mixture quantile normalization (GMQN), a reference based method for correcting batch effects as well as probes bias in HumanMethylation BeadChip. Availability and implementation: https://github.com/MengweiLi-project/gmqn.

bioinformatics↗

bioRxiv2021

Establishment of a Prognostic Prediction and Drug Selection Model for Patients with Clear Cell Renal Cell Carcinoma by Multi-Omics Data Analysis

RationalePatients with clear cell renal cell cancer (ccRCC) may have completely different treatment choices and prognoses due to the wide range of heterogeneity of the disease. However, there is a lack of effective models for risk stratification, treatment decision making and prognostic prediction of renal cancer patients. The aim of the present study was to establish a model to stratify ccRCC patients in terms of prognostic prediction and drug selection based on multi-omics data analysis. MethodsThis study was based on the multi-omics data (including mRNA, lncRNA, miRNA, methylation and WES) of 258 ccRCC patients from TCGA database. Firstly, we screened the feature values that had impact on the prognosis and obtained two subtypes. Then, we used 10 algorithms to achieve multi-omics clustering, and conducted pseudo-timing analysis to further validate the robustness of our clustering method, based on which the two subtypes of ccRCC patients were further subtyped. Meanwhile, the immune infiltration was compared between the two subtypes, and drug sensitivity and potential drugs were analyzed. Furthermore, to analyze the heterogeneity of patients at the multi-omics level, biological functions between two subtypes were compared. Finally, Boruta and PCA methods were used for dimensionality reduction and cluster analysis to construct a renal cancer risk model based on mRNA expression. ResultsA prognosis predicting model of ccRCC was established by dividing patients into high- and low-risk groups. It was found that overall survival (OS) and progression-free interval (PFI) were significantly different between the two groups (p<0.01). The area under the OS time dependent ROC curve for 1, 3, 5 and 10 years in the training set was 0.75, 0.72, 0.71 and 0.68 respectively. ConclusionThe model could precisely predict the prognosis of ccRCC patients and may have implications for drug selection for ccRCC patients.

genomics↗

bioRxiv2021

Establishment of a prognosis prediction model based on pyroptosis-related signatures associated with the immune microenvironment and molecular heterogeneity in clear cell renal carcinoma

BackgroundPytoptosis is essential for tumorigenesis and progression of clear cell renal cell carcinoma (ccRCC). However, the heterogeneity of pyroposis and its relationship with the tumor microenvironment (TME) remain unclear. The aim of the present study was to identify proptosis-related subtypes and construct a prognosis prediction model based on pyroptosis signatures. MethodsFirst, heterogenous pyroptosis subgroups were explored based on 33 pyroptosis-related genes and ccRCC samples from TCGA, and the model establsihed by LASSO regression was verified by ICGC database. Then, the clinical significance, functional status, immune infiltration, cell-cell communication, genomic alteration and drug sensitivity of different subgroups were further analyzed. Finally, the LASSO-Cox algorithm was applied to narrow down the candidate genes to develop a robust and concise prognostic model. ResultsTwo heterogenous pyroptosis subgroups were identified: pyroptosis-low immunity-low C1 subtype, and pyroptosis-high immunity-high C2 subtype. Compared with C1, C2 was associated with a higher clinical stage or grade and a worse prognosis. More immune cell infiltration was observed in C2 than that in C1, while the response rate in C2 subgroup was lower than that in C1 subgroup. Pyroptosis related genes were mainly expressed in myeloid cells, and T cells and epithelial cells might influence other cell clusters via Pyroptosis related pathway. In addition, C1 was characterized by MTOR and ATM mutation, while C2 was characterized by more significant alterations in SPEN and ROS1 mutation. Finally, we constructed and validated a robust and promising signature based on the pyroptosis-related risk score for assessing the prognosis in ccRCC. ConclusionWe identified two heterogeneous pyroptosis subtypes and 5 reliable risk signatures to establish a prognosis prediction model. Our findings may help better understand the role of pyroptosis in ccRCC progression and provide a new perspective in the management of ccRCC patients.

molecular biology↗