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Luo, R.

Publications and source records attributed to Luo, R..

At least 73 records · Page 4Linked to original sources

Symphonizing pileup and full-alignment for deep learning-based long-read variant calling

Deep learning-based variant callers are becoming the standard and have achieved superior SNP calling performance using long reads. In this paper, we present Clair3, which leveraged the best of two major method categories: pile-up calling handles most variant candidates with speed, and full-alignment tackles complicated candidates to maximize precision and recall. Clair3 ran faster than any of the other state-of-the-art variant callers and performed the best, especially at lower coverage.

bioinformatics↗

De novo assembly of 20 chickens reveals the undetectable phenomenon for thousands of core genes on sub-telomeric regions

The gene numbers and evolutionary rates of birds were assumed to be much lower than that of mammals, which in sharp contrast to the huge species number and morphological diversity of birds. It is very necessary to construct a complete avian genome and analyze its evolution.We constructed a chicken pan-genome from 20 de novo genome assemblies with high sequencing depth, newly identified 1,335 protein-coding genes and 3,011 long noncoding RNAs. The majority of these novel genes were detected across most individuals of the examined transcriptomes but were accidentally measured in each of the DNA sequencing data regardless of Illumina or PacBio technology. Furthermore, different from previous pan-genome models, most of these novel genes were overrepresented on chromosomal sub-telomeric regions, surrounded with extremely high proportions of tandem repeats, and strongly blocked DNA sequencing. These hidden genes were proved to be shared by all chicken genomes, included many housekeeping genes, and enriched in immune pathways. Comparative genomics revealed the novel genes had three-fold elevated substitution rates than known ones, updating the evolutionary rates of birds. Our study provides a framework for constructing a better chicken genome, which will contribute towards the understanding of avian evolution and improvement of poultry breeding.

genomics↗

Spatially-resolved transcriptomics analyses of invasive fronts in solid tumors

Solid tumors are complex ecosystems, and heterogeneity is the major challenge for overcoming tumor relapse and metastasis. Uncovering the spatial heterogeneity of cell types and functional states in tumors is essential for developing effective treatment, especially in invasive fronts of tumor, the most active region for tumor cells infiltration and invasion. We firstly used SpaTial Enhanced REsolution Omics-sequencing (Stereo-seq) with a nanoscale resolution to characterize the tumor microenvironment of intrahepatic cholangiocarcinoma (ICC). Enrichment of distinctive immune cells, suppressive immune microenvironment and metabolic reprogramming of tumor cells were identified in the 500{micro}m-wide zone centered bilaterally on the tumor boundary, namely invasive fronts of tumor. Furthermore, we found the damaged states of hepatocytes with overexpression of Serum Amyloid A (SAA) in invasive fronts, recruiting macrophages for facilitating further tumor invasion, and thus resulting in a worse prognosis. We also confirmed these findings in hepatocellular carcinoma and other liver metastatic cancers. Our work highlights the remarkable potential of high-resolution-spatially resolved transcriptomic approaches to provide meaningful biological insights for comprehensively dissecting the tumor ecosystem and guiding the development of novel therapeutic strategies for solid tumors.

cancer biology↗

HKG: An open genetic variant database of 205 Hong Kong Cantonese exomes

HKG is the first fully accessible variant database for Hong Kong Cantonese, constructed from 205 novel whole-exome sequencing data. There has long been a research gap in the understanding of the genetic architecture of southern Chinese subgroups, including Hong Kong Cantonese. HKG detected 196,325 high-quality variants with 5.93% being novel, and 25,472 variants were found to be unique in HKG compared to other Chinese populations (CHN). PCA illustrates the uniqueness of HKG in CHN, and IBD analysis revealed that it is related mostly to southern Chinese with a similar effective population size. An admixture study estimated the ancestral composition of HKG and CHN, with a gradient change from north to south, consistent with their geological distribution. ClinVar, CIViC and PharmGKB annotated 599 clinically significant variants and 360 putative loss-of-function variants, substantiating our understanding of population characteristics for future medical development. Among the novel variants, 96.57% were singleton and 6.85% were of high impact. With a good representation of Hong Kong Cantonese, we demonstrated better variant imputation using reference with the addition of HKG data, thus successfully filling the data gap in southern Chinese to facilitate the regional and global development of population genetics.

bioinformatics↗

DNA methylation affects pre-mRNA transcriptional initiation and processing in Arabidopsis

BackgroundDNA methylation may regulate pre-mRNA transcriptional initiation and processing, thus affecting gene expression. Unlike animal cells, plants, especially Arabidopsis thaliana, have relatively low DNA methylation levels, limiting our ability to observe any correlation between DNA methylation and pre-mRNA processing using typical short-read sequencing. However, with newly developed long-read sequencing technologies, such as Oxford Nanopore Technology Direct RNA sequencing (ONT DRS), combined with whole-genome bisulfite sequencing, we were able to precisely analyze the relationship between DNA methylation and pre-mRNA transcriptional initiation and processing using DNA methylation-related mutants. ResultsUsing ONT DRS, we generated more than 2 million high-quality full-length long reads of native mRNA for each of the wild type Col-0 and mutants defective in DNA methylation, identifying a total of 117,474 isoforms. We found that low DNA methylation levels around splicing sites tended to prevent splicing events from occurring. The lengths of the poly(A) tail of mRNAs were positively correlated with DNA methylation. DNA methylation before transcription start sites or around transcription termination sites tended to result in gene-silencing or read-through events. Furthermore, using ONT DRS, we identified novel transcripts that we could not have otherwise, since transcripts with intron retention and fusion transcripts containing the uncut intergenic sequence tend not to be exported to the cytoplasm. Using the met1-3 mutant with activated constitutive heterochromatin regions, we confirmed the effects of DNA methylation on pre-mRNA processing. ConclusionThe combination of ONT DRS with whole-genome bisulfite sequencing was a powerful tool for studying the effects of DNA methylation on splicing site selection and pre-mRNA processing, and therefore regulation of gene expression.

plant biology↗

Multi-tissue integrative analysis of personal epigenomes

Understanding how genetic variants impact molecular phenotypes is a key goal of functional genomics, currently hindered by reliance on a single haploid reference genome. Here, we present the EN-TEx resource of personal epigenomes, for [~]25 tissues and >10 assays in four donors (>1500 open-access functional genomic and proteomic datasets, in total). Each dataset is mapped to a matched, diploid personal genome, which has long-read phasing and structural variants. The mappings enable us to identify >1 million loci with allele-specific behavior. These loci exhibit coordinated epigenetic activity along haplotypes and less conservation than matched, non-allele-specific loci, in a fashion broadly paralleling tissue-specificity. Surprisingly, they can be accurately modelled just based on local nucleotide-sequence context. Combining EN-TEx with existing genome annotations reveals strong associations between allele-specific and GWAS loci and enables models for transferring known eQTLs to difficult-to-profile tissues. Overall, EN-TEx provides rich data and generalizable models for more accurate personal functional genomics.

genomics↗

SENSV: Detecting Structural Variations with Precise Breakpoints using Low-Depth WGS Data from a Single Oxford Nanopore MinION Flowcell

Structural variation (SV) is a major cause of genetic disorders. In this paper, we show that low-depth (specifically, 4x) whole-genome sequencing using a single Oxford Nanopore MinION flow cell suffices to support sensitive detection of SV, in particular, pathogenic SV for supporting clinical diagnosis. Existing SV calling software, when using 4x ONT WGS data, often fails to detect pathogenic SV especially in the form of long deletion, terminal deletion, duplication, and unbalanced translocation. Our new SV calling software SENSV is able to achieve high sensitivity for all types of SV and a breakpoint precision typically {+/-}100 bp, both features are important for clinical concerns. The improvement achieved by SENSV stems from several new algorithms. We evaluated SENSV and other software using both real and simulated data. The former was based on 24 patient samples, each diagnosed with a genetic disorder. SENSV found the pathogenic SV in 22 out of 24 cases (all heterozygous, size from hundreds of Kbp to a few Mbp), reporting breakpoints within 100 bp of the true answers. No existing software can detect the pathogenic SV in more than 10 out of 24 cases, even when the breakpoint requirement is relaxed to {+/-}2,000 bp.

bioinformatics↗

ECNano: A Cost-Effective Workflow for Target Enrichment Sequencing and Accurate Variant Calling on 4,800 Clinically Significant Genes Using a Single MinION Flowcell

BackgroundThe application of long-read sequencing using the Oxford Nanopore Technologies (ONT) MinION sequencer is getting more diverse in the medical field. Having a high sequencing error of ONT and limited throughput from a single MinION flowcell, however, limits its applicability for accurate variant detection. Medical exome sequencing (MES) targets clinically significant exon regions, allowing rapid and comprehensive screening of pathogenic variants. By applying MES with MinION sequencing, the technology can achieve a more uniform capture of the target regions, shorter turnaround time, and lower sequencing cost per sample. MethodWe introduced a cost-effective optimized workflow, ECNano, comprising a wet-lab protocol and bioinformatics analysis, for accurate variant detection at 4,800 clinically important genes and regions using a single MinION flowcell. The ECNano wet-lab protocol was optimized to perform long-read target enrichment and ONT library preparation to stably generate high-quality MES data with adequate coverage. The subsequent variant-calling workflow, Clair-ensemble, adopted a fast RNN-based variant caller, Clair, and was optimized for target enrichment data. To evaluate its performance and practicality, ECNano was tested on both reference DNA samples and patient samples. ResultsECNano achieved deep on-target depth of coverage (DoC) at average >100x and >98% uniformity using one MinION flowcell. For accurate ONT variant calling, the generated reads sufficiently covered 98.9% of pathogenic positions listed in ClinVar, with 98.96% having at least 30x DoC. ECNano obtained an average read length of 1,000 bp. The long reads of ECNano also covered the adjacent splice sites well, with 98.5% of positions having [≥] 30x DoC. Clair-ensemble achieved >99% recall and accuracy for SNV calling. The whole workflow from wet-lab protocol to variant detection was completed within three days. ConclusionWe presented ECNano, an out-of-the-box workflow comprising (1) a wet-lab protocol for ONT target enrichment sequencing and (2) a downstream variant detection workflow, Clair-ensemble. The workflow is cost-effective, with a short turnaround time for high accuracy variant calling in 4,800 clinically significant genes and regions using a single MinION flowcell. The long-read exon captured data has potential for further development, promoting the application of long-read sequencing in personalized disease treatment and risk prediction.

bioinformatics↗

RENET2: High-Performance Full-text Gene-Disease Relation Extraction with Iterative Training Data Expansion

BackgroundRelation extraction is a fundamental task for extracting gene-disease associations from biomedical text. Existing tools have limited capacity, as they can extract gene-disease associations only from single sentences or abstract texts. ResultsIn this work, we propose RENET2, a deep learning-based relation extraction method, which implements section filtering and ambiguous relations modeling to extract gene-disease associations from full-text articles. We designed a novel iterative training data expansion strategy to build an annotated full-text dataset to resolve the scarcity of labels on full-text articles. In our experiments, RENET2 achieved an F1-score of 72.13% for extracting gene-disease associations from an annotated full-text dataset, which was 27.22%, 30.30% and 29.24% higher than the best existing tools BeFree, DTMiner and BioBERT, respectively. We applied RENET2 to (1) ~1.89M full-text articles from PMC and found ~3.72M gene-disease associations; and (2) the LitCovid articles set and ranked the top 15 proteins associated with COVID-19, supported by recent articles. ConclusionRENET2 is an efficient and accurate method for full-text gene-disease association extraction. The source-code, manually curated abstract/full-text training data, and results of RENET2 are available at https://github.com/sujunhao/RENET2.

bioinformatics↗

ssc-micorRNA-132 suppresses the Clostridium perfringens beta2 toxin induced inflammation and apoptosis of IPEC-J2 cells via targeting DACH1

Clostridium perfringens (C. perfringens) beta2 (CPB2) is the main virulence factor secreted from C. perfringens type C, which caused diarrhea characterized by high mortality in pig, especially newborn piglets. Our previous research found that ssc-miR-132 displayed decreased expression in piglets diarrhea after infected with C. perfringens type C compared with normal piglets. We speculated that ssc-miR-132 may play an important role in the diarrhea. However, the function of ssc-miR-132 in the diarrhea is limited. Thus, we overexpressed and knocked down ssc-miR-132 in intestinal porcine epithelial (IPEC-J2) cells, and then treated the cells with recombinant CPB2 (rCPB2) toxin (20 g/mL). Our results showed that ssc-miR-132 was significantly decreased after treated with rCPB2 toxin. In addition, overexpression of ssc-miR-132 reduced the expression of lactate dehydrogenase (LDH) and tumor necrosis factor (TNF-), interleukin-6 (IL-6) and interleukin-8 (IL-8) caused by rCPB2 toxin. The CCK8, Edu and TUNEL staining showed that overexpression of ssc-miR-132 weakened the inhibition of rCPB2 toxin on cell proliferation and reduced the promotion of cell apoptosis; while inhibition of ssc-miR-132 had opposite results. The dual luciferase experiment showed that dachshund family transcription factor 1 (DACH1) was the target gene of ssc-miR-132. Silencing DACH1 was consistent with the results of overexpression of ssc-miR-132, and reversed the apoptosis and inflammation caused by rCPB2 toxin. Overexpression of DACH1 weakened the role of ssc-miR-132 in rCPB2 toxin -induced inflammation and apoptosis. In summary, ssc-miR-132 inhibited rCPB2 toxin-induced apoptosis and inflammation in IPEC-J2 cells by targeting DACH1.

cell biology↗

Tracking cytosine depletion in SARS-CoV-2

MotivationDanchin et al. have pointed out that cytosine drives the evolution of SARS-CoV-2. A depletion of cytosine might lead to the attenuation of SARS-CoV-2. ResultsWe built a website to track the composition change of mono-, di-, and tri-nucleotide of SARS-CoV-2 over time. The website downloads new strains available from GISAID and updates its results daily. Our analysis suggests that the composition of cytosine in coronaviruses is related to their reported mortality. Using 137,315 SARS-CoV-2 strains collected in ten months, we observed cytosine depletion at a rate of about one cytosine loss per month from the whole genome. AvailabilityThe website is available at http://www.bio8.cs.hku.hk/sarscov2/. Contactrbluo@cs.hku.hk Supplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗

Modeling SARS-CoV-2 infection in vitro with a human intestine-on-chip device

Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus (SARS-CoV-2) has given rise to a global pandemic. The gastrointestinal symptoms of some COVID-19 patients are underestimated. There is an urgent need to develop physiologically relevant model that can accurately reflect human response to viral infection. Here, we report the creation of a biomimetic human intestine infection model on a chip system that allows to recapitulate the intestinal injury and immune response induced by SARS-CoV-2, for the first time. The microengineered intestine-on-chip device contains human intestinal epithelium (co-cultured human intestinal epithelial Caco-2 cells and mucin secreting HT-29 cells) lined in upper channel and vascular endothelium (human umbilical vein endothelial cells, HUVECs) in a parallel lower channel under fluidic flow condition, sandwiched by a porous PDMS membrane coated with extracellular matrix (ECM). At day 3 post-infection of SARS-CoV-2, the intestine epithelium showed high susceptibility to viral infection and obvious morphological changes with destruction of intestinal villus, dispersed distribution of mucus secreting cells and reduced expression of tight junction (E-cadherin), indicating the destruction of mucous layer and the integrity of intestinal barrier caused by virus. Moreover, the endothelium exhibited abnormal cell morphology with disrupted expression of adherent junction protein (VE-cadherin). Transcriptional analysis revealed the abnormal RNA and protein metabolism, as well as activated immune responses in both epithelial and endothelial cells after viral infection (e.g., up-regulated cytokine genes, TNF signaling and NF-kappa B signaling-related genes). This bioengineered in vitro model system can mirror the human relevant pathophysiology and response to viral infection at the organ level, which is not possible in existing in vitro culture systems. It may provide a promising tool to accelerate our understanding of COVID-19 and devising novel therapies.

bioengineering↗

A human disease model of SARS-CoV-2-induced lung injury and immune responses with a microengineered organ chip

Coronavirus disease 2019 (COVID-19) is a global pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that seriously endangers human health. There is an urgent need to build physiological relevant human models for deep understanding the complex organ-level disease processes and facilitating effective therapeutics for COVID-19. Here, we first report the use of microengineered alveolus chip to create a human disease model of lung injury and immune responses induced by native SARS-CoV-2 at organ-level. This biomimetic system is able to reconstitute the key features of human alveolar-capillary barrier by co-culture of alveolar epithelial and microvascular endothelial cells under microfluidic flow. The epithelial cells on chip showed higher susceptibility to SARS-CoV-2 infection than endothelial cells identified by viral spike protein expression. Transcriptional analysis showed distinct responses of two cell types to SARS-CoV-2 infection, including activated type I interferon (IFN-I) signaling pathway in epithelium and activated JAK-STAT signaling pathway in endothelium. Notably, in the presence of circulating immune cells, a series of alveolar pathological changes were observed, including the detachment of endothelial cells, recruitment of immune cells, and increased production of inflammatory cytokines (IL-6, IL-8, IL-1{beta} and TNF-). These new findings revealed a crucial role of immune cells in mediating lung injury and exacerbated inflammation. Treatment with antiviral compound remdesivir could suppress viral copy and alleviate the disruption of alveolar barrier integrity induced by viral infection. This bioengineered human organ chip system can closely mirror human-relevant lung pathogenesis and immune responses to SARS-CoV-2 infection, not possible by other in vitro models, which provides a promising and alternative platform for COVID-19 research and preclinical trials.

bioengineering↗

Pairing two growth-based, high-throughput selections to fine tune conformational dynamics in oxygenase engineering

Cyclohexanone monooxygenases (CHMO) consume molecular oxygen and NADPH to catalyze the valuable oxidation of cyclic ketones. However, CHMO usage is restricted by poor thermostability and stringent specificity for NADPH. Efforts to engineer CHMO have been limited by the sensitivity of the enzyme to perturbations in conformational dynamics and long-range interactions that cannot be predicted. We demonstrate a pair of aerobic, high-throughput growth selection platforms in Escherichia coli for oxygenase evolution, based on NADPH or NADH redox balance. We utilize the NADPH-dependent selection in the directed evolution of thermostable CHMO and discover the variant CHMO GV (A245G-A288V) with a 2.7-fold improvement in residual activity compared to the wild type after 40 {degrees}C incubation. Addition of a previously reported mutation resulted in A245G-A288V-T415C which has further improved thermostability at 45 {degrees}C. We apply the NADH-dependent selection to alter the cofactor specificity of CHMO to accept NADH, a less expensive cofactor than NADPH. We identified the variant CHMO DTNP (S208D-K326T-K349N-L143P) with a 21-fold cofactor specificity switch from NADPH to NADH compared to the wild type. Molecular modeling indicates that CHMO GV experiences more favorable residue packing and backbone torsions, and CHMO DTNP activity is driven by cooperative fine-tuning of cofactor contacts. Our introduced tools for oxygenase evolution enable the rapid engineering of properties critical to industrial scalability.

bioengineering↗

A splicing isoform of GPR56 mediates microglial synaptic refinement via phosphatidylserine binding

Developmental synaptic remodeling is important for the formation of precise neural circuitry and its disruption has been linked to neurodevelopmental disorders such as autism and schizophrenia. Microglia prune synapses, but integration of this synapse pruning with overlapping and concurrent neurodevelopmental processes remains elusive. Adhesion G protein-coupled receptor ADGRG1/GPR56 controls multiple aspects of brain development in a cell type-specific manner: in neural progenitor cells, GPR56 regulates cortical lamination, whereas in oligodendrocyte progenitor cells, GPR56 controls developmental myelination and myelin repair. Here, we show that microglial GPR56 maintains appropriate synaptic numbers in several brain regions in a time- and circuit-dependent fashion. Phosphatidylserine (PS) on pre-synaptic elements binds GPR56 in a domain-specific manner, and microglia-specific deletion of Gpr56 leads to increased synapses as a result of reduced microglial engulfment of PS+ pre-synaptic inputs. Remarkably, a particular alternatively spliced isoform of GPR56 is selectively required for microglia-mediated synaptic pruning. Our present data provide a ligand- and isoform-specific mechanism underlying microglial GPR56-mediated synapse pruning in the context of complex neurodevelopmental processes.

neuroscience↗

Acetylation is required for NLRP3 self-aggregation and full activation of the inflammasome

The full activation of NLRP3 inflammasome needs two sequential signals: the fist priming signal and the second assembly signal. Various stimuli including infections and stress signals can provide the assembly signal. However, how NLRP3 detects diverse stimuli and becomes fully activated remain largely unknown. In this study, we found the second signal specially triggers the acetylation of NLRP3, which facilitates the aggregation of NLRP3 and its interaction with ASC and NEK7, thus promoting the assembly of inflammasome. Meanwhile, by employing pharmacological and molecular approaches, we identified KAT5 as a regulator of NLRP3 acetylation and activation. Furthermore, KAT5 specific inhibitor-NU9056 exhibited a robust suppressive effect on NLRP3 inflammasome both in vitro and in vivo. Thus, our study reveals a new mechanism for NLRP3 full activation and suggests targeting NLRP3 acetylation may provide a new approach for treatment of NLRP3 associated diseases.

immunology↗

Clair: Exploring the limit of using a deep neural network on pileup data for germline variant calling

Single-molecule sequencing technologies have emerged in recent years and revolutionized structural variant calling, complex genome assembly, and epigenetic mark detection. However, the lack of a highly accurate small variant caller has limited the new technologies from being more widely used. In this study, we present Clair, the successor to Clairvoyante, a program for fast and accurate germline small variant calling, using single molecule sequencing data. For ONT data, Clair achieves the best precision, recall and speed as compared to several competing programs, including Clairvoyante, Longshot and Medaka. Through studying the missed variants and benchmarking intentionally overfitted models, we found that Clair may be approaching the limit of possible accuracy for germline small variant calling using pileup data and deep neural networks. Clair requires only a conventional CPU for variant calling and is an open source project available at https://github.com/HKU-BAL/Clair.

bioinformatics↗

Oxytocin modulation of self-other distinction is replicable and influenced by oxytocin receptor (OXTR) genotype

Intranasal oxytocin (OXT) has been associated with effects on diverse social-emotional domains in humans, however progress in the field is currently hampered by poor replicability. Limited statistical power and individual differences in biological factors, such as oxytocin receptor (OXTR) genetics, may have contributed to these variable findings. To this end, we present a pharmaco-genetic study aiming at (1) replicating previous findings suggesting that intranasal oxytocin (24 IU) blurs self-other distinction in a large sample of n = 170 male subjects, (2) determining whether variations in common receptor polymorphisms (rs237887, rs2268491, rs2254298, rs53576, rs2268498) influence sensitivity to oxytocins behavioral effects. Employing a validated oxytocin-sensitive trait judgment paradigm, we confirmed that it blurred self-other distinction in terms of decision time and subsequent memory. However, oxytocin only influenced decision time in rs53576 G carriers, whereas effects on memory performance were most pronounced in rs2268498 TT homozygotes. In summary, the current study replicates our previous findings showing that oxytocin blurs self-other distinction and suggests that sensitivity to its effects in this domain are receptor genotype dependent.

neuroscience↗