Biology subjects

Zhang, L.

Publications and source records attributed to Zhang, L..

At least 955 records · Page 53Linked to original sources

bioRxiv2022

Global genomic analysis reveals the genetic origin and secondary invasion of fall armyworm in the Eastern hemisphere

The major plant pest fall armyworm (FAW), Spodoptera frugiperda, is native to the Americas and has colonized African and Asian countries in the Eastern hemisphere since 2016, causing severe damage to multiple agricultural crop species. However, the genetic origin of these invasive populations require more in-depth exploration. We analyzed genetic variation across FAW genomes of 153 newly sequenced individuals from Eastern hemisphere and 127 individuals mostly originating from the Americas. The global genetic structure of FAW shows that the FAW in American has experienced deep differentiation, largely consistent with the Z-chromosomal Tpi haplotypes commonly used to differentiate "corn-strain" and "rice-strain" populations. Results indicate that the invasive Eastern hemisphere populations are different from the American ones and have relatively homogeneous population structure, consistent with the common origin and recent spreading from Africa to Asia. Our analyses suggest that north-and central American "corn-strain" FAW are the most likely sources of the invasion into the Eastern hemisphere. Furthermore, evidence based on genomic, transcriptomic and mitochondrial haplotype network analysis suggest that there has been an earlier independent introduction of FAW into Africa that introgressed into the recent invasive population.

molecular biology↗

bioRxiv2022

Treatment with anti-inflammatory viral serpin modulates immuno-thrombotic responses and improves outcomes in SARS-CoV-2 infected mice

1.Severe acute respiratory distress syndrome (ARDS) during SARS-CoV-2 (severe acute respiratory syndrome coronavirus-2) infection, manifests as uncontrolled lung inflammation and systemic thrombosis with high mortality. Anti-viral drugs and monoclonal antibodies can reduce COVID-19 severity if administered in the early viremic phase, but treatments for later stage immuno-thrombotic syndrome and long COVID are limited. Serine protease inhibitors (SERPINS) regulate activated proteases during thrombotic, thrombolytic and immune responses. The myxoma poxvirus-derived Serp-1 protein is a secreted immunomodulatory serpin that targets activated coagulation and complement protease pathways as part of a self-defense strategy to combat viral clearance by the innate immune system. When purified and utilized as an anti-immune therapeutic, Serp-1 is effective as an anti-inflammatory drug in multiple animal models of inflammatory lung disease and vasculitis. Here, we describe systemic treatment with purified PEGylated Serp-1 (PEGSerp-1) as a therapy for immuno-thrombotic complications during ARDS. Treatment with PEGSerp-1 in two distinct mouse-adapted SARS-CoV-2 models in C57Bl/6 and BALB/c mice reduced lung and heart inflammation, with improved clinical outcomes. PEGSerp-1 significantly reduced M1 macrophage invasion in the lung and heart by modifying urokinase-type plasminogen activator receptor (uPAR) and complement membrane attack complex (MAC). Sequential changes in urokinase-type plasminogen activator receptor (uPAR) and serpin gene expression were observed in lung and heart with PEGSerp-1 treatment. PEGSerp-1 is a highly effective immune-modulator with therapeutic potential for treatment of severe viral ARDS with additional potential to reduce late SARS-CoV-2 complications related to immune-thrombotic events that persist during long COVID. SignificanceSevere acute respiratory distress syndrome (ARDS) in SARS-CoV-2 infection manifests as uncontrolled tissue inflammation and systemic thrombosis with high mortality. Anti-viral drugs and monoclonal antibodies reduce COVID-19 severity if administered early, but treatments for later stage immuno-thrombosis are limited. Serine protease inhibitors (SERPINS) regulate thrombotic, thrombolytic and complement pathways. We investigate here systemic treatment with purified poxvirus-derived PEGSerp-1 as a therapeutic for immuno-thrombotic complications in viral ARDS. PEGSerp-1 treatment in two mouse-adapted SARS-CoV-2 models (C57Bl/6 and BALB/c) significantly reduced lung and heart inflammation and improved clinical outcomes, with sequential changes in thrombolytic (uPAR) and complement expression. PEGSerp-1 is a highly effective immune-modulator with therapeutic potential for immune-thrombotic complications in severe viral ARDS and has potential benefit for long COVID.

microbiology↗

bioRxiv2022

Exploring high-quality microbial genomes by assembly of linked-reads with high barcode specificity using deep learning

Despite long-read sequencing enables to generate complete genomes of unculturable microbes, its high cost hinders its widespread application in large cohorts. An alternative method is to assemble short-reads with long-range connectivity, which can be a cost-effective way to generate high-quality microbial genomes. We developed Pangaea to improve metagenome assembly using short-reads with physical or virtual barcodes. It adopts a deep-learning-based binning algorithm to assemble the co-barcoded reads with similar sequence contexts and abundances to improve assemblies of high- and medium-abundance microbes. Pangaea also leverages a multi-thresholding reassembly strategy to refine assembly for low-abundance microbes. We benchmarked Pangaea with linked-reads and a combination of short- and long-reads from mock communities and human gut metagenomes. Pangaea achieved significantly higher contig continuity as well as more near-complete metagenome-assembled genomes (NCMAGs) than the existing assemblers. Pangaea was also observed to generate three complete and circular NCMAGs on the human gut microbiomes.

genomics↗

bioRxiv2022

Reactive astrocyte derived extracellular vesicles promote functional repair post stroke

Reactive astrocytes are both neurotoxic and pro-regenerative. Their reparative roles after injury have been demonstrated, but how they play a contributing role to regeneration remains question. Here, we investigate the use of astrocytic extracellular vesicles from primary astrocytes cultured in reactive conditions in promoting repair after ischemic stroke. Our studies show that extracellular vesicles derived from reactive astrocytes that co-express a significant number of reactive genes (155 upregulated including log2 of 9.61 for Lcn2) and axonal outgrowth genes (59 upregulated including log2 of 3.49 Ntn1) are necessary for improved regenerative outcomes, including axonal infiltration, vascularization, and improved behavioral recovery. Proteomic analysis of the extracellular vesicles show that astrocytes enrich pro-reparative proteins in extracellular vesicles with only 30 proteins relating to inflammatory or complement pathways loaded out of a total of 1073 proteins. Further, we show that the use of a biomaterial scaffold is necessary for the improved regeneration observed from reactive astrocyte extracellular vesicles. These studies show that reactive astrocytes use extracellular vesicles enriched with pro-repair proteins to promote recovery after injury.

neuroscience↗

bioRxiv2022

The injury-induced circular RNA circGLIS3 activates dermal fibroblasts to promote wound healing

Delayed skin wound healing and excessive scarring are consequences of an impaired healing process and represent a major health and economic burden worldwide. Current intervention strategies lack efficacy and suffer from high recurrence rates necessitating the investigation into alternative treatment modalities like circular RNAs (circRNAs). By RNA sequencing, we profiled circRNA expression changes during human skin wound healing as well as in keratinocytes and fibroblasts isolated from donor-matched skin and acute wounds. CircGLIS3 was found to be transiently upregulated in the dermal fibroblasts upon skin injury, which was at least partially due to the activated IL-1 signaling. Similarly, overabundant circGLIS3 expression was detected in human keloid lesions compared to the surrounding healthy skin. We found that circGLIS3 resided mainly in the cytoplasm, where it interacted with and stabilized Procollagen C-endopeptidase enhancer 1 (PCPE-1) protein to enhance TGF-{beta} signaling, fibroblast activation, and production of extracellular matrix - important biological processes required for wound repair. Accordingly, knockdown of circGLIS3 in human ex vivo wounds potently reduced wound contraction and delayed re-epithelialization. Collectively, we have identified a previously uncharacterized circRNA regulator of human skin wound healing that may open an avenue for circRNA-based therapeutics for abnormal scarring or nonhealing wounds. One Sentence SummaryTransient increase of the circular RNA circGLIS3 promotes the wound fibroblast activation and extracellular matrix production to facilitate wound closure.

molecular biology↗

bioRxiv2022

Neuronal C-Reactive Protein Mediates Neuropathic Pain by Activating Nociceptive FcγRI-Coupled Signaling

BackgroundNeuropathic pain is difficult to treat in clinical practice, and the underlying mechanisms are insufficiently elucidated. Previous studies have demonstrated that Fc{gamma} receptor I (Fc{gamma}RI) is expressed in the neurons of the dorsal root ganglion (DRG) and may be involved in chronic pain. MethodsChronic constriction injury (CCI) was used to induce neuropathic pain in rats. Primary neuron-specific Fcgr1 conditional knockout (CKO) rats were established by crossing rats carrying a Fcgr1loxP+/+ with the PirtCRE+ line. Behavioral and molecular studies were conducted to evaluate the differences between wild-type and CKO rats after CCI. ResultsWe first revealed that CCI activated neuronal Fc{gamma}RI-related signaling in the DRG. CCI-induced neuropathic pain was alleviated in CKO rats. C-reactive protein (CRP) was increased in the DRG after nerve injury. Intraganglionic injection or overexpression of the recombinant CRP protein in the DRG evoked pain accompanied and activated neuronal Fc{gamma}RI. CRP-evoked pain was significantly reduced in CKO rats. Furthermore, microinjection of native IgG into the DRG alleviated neuropathic pain and the activation of neuronal Fc{gamma}RI-related signaling. ConclusionsOur results indicate that the activation of neuronal CRP/Fc{gamma}RI-related signaling plays an important role in the development of pain in CCI. Our findings may provide novel insights into the neuroimmune responses after peripheral nerve injury and might suggest potential therapeutic targets for neuropathic pain.

neuroscience↗

bioRxiv2022

Structural and mechanistic insights into inhibition of the type I-F CRISPR-Cas surveillance complex by AcrIF4

CRISPR-Cas system provides prokaryotes with protection against mobile genetic elements (MGEs) such as phages. In turn, phages deploy anti-CRISPR (Acr) proteins to evade this immunity. AcrIF4, an Acr targeting the type I-F CRISPR-Cas system, has been reported to bind the crRNA-guided surveillance (Csy) complex. However, it remains controversial whether AcrIF4 inhibits target DNA binding to the Csy complex. Here, we present structural and mechanistic studies into AcrIF4, exploring its unique anti-CRISPR mechanism. While the Csy-AcrIF4 complex displays decreased affinity for target DNA, it is still able to bind the DNA. Structural and functional analyses of the Csy-AcrIF4-dsDNA complex revealed that AcrIF4 binding prevents rotation of the helical bundle (HB) of Cas8f induced by dsDNA binding, therefore resulting in failure of Cas2/3 recruitment and DNA cleavage. Overall, our study provides an interesting example of attack on the nuclease recruitment event by an Acr, but not conventional mechanisms of blocking binding of target DNA.

molecular biology↗

bioRxiv2022

Uni-Fold Symmetry: Harnessing Symmetry in Folding Large Protein Complexes

Deep folding models have revolutionized the conventional methods of protein complex prediction. However, applying them to large protein oligomers is not easy. These models generally require copying the sequences of identical subunits to capture the in-between relationships. Accordingly, the scales of target protein complexes are strictly limited due to the cubic complexity of these models. To address this issue, we propose UF-Symmetry (Uni-Fold Symmetry), which is extricated from the need of sequence copying via harnessing the intrinsic symmetry of large protein oligomers. Taking the sequences of the asymmetric unit (AU) and a pre-specified symmetry group, UF-Symmetry learns to fold the AU and to assemble the complex structure in an end-to-end manner. By reducing the input scales from entire assemblies to AUs, UF-Symmetry allows to predict much larger assemblies with significant acceleration: for a complex of 4-fold cyclic symmetry (C4) and AU size of 512, UF-Symmetry achieves approximately 20 times acceleration to current methods. On a benchmark of recently released PDB multimers, UF-Symmetry approximately halves the failure rate of current methods and achieves approaching accuracy on commonly successful cases.

bioinformatics↗

bioRxiv2022

SCsnvcna: Integrating SNVs and CNAs on a phylogenetic tree from single-cell DNA sequencing data

Single-cell DNA sequencing enables the construction of evolutionary trees that can reveal how tumors gain mutations and grow. Different whole genome amplification (WGA) procedures render genomic materials of different characteristics, often suitable for the detection of either single nucleotide variation (SNV) or for copy number aberration (CNA), but not for both, hindering the placement of both SNVs and CNAs on the same phylogenetic tree for the study of interplay of SNVs and CNAs. SCARLET places SNVs on a CNA tree, a tree derived based on the copy number profiles, while considering SNV loss due to copy number losses. However, SCARLET requires that the SNVs and CNAs are detected from the same sets of cells, which is technically challenging due to the sequencing errors or the low sequencing coverage associated with a particular WGA procedure. Here we presented a novel computational tool, SCsnvcna, that aims at placing SNVs on a CNA tree whereas the sets of cells rendering the SNVs and CNAs are independent, thus is more practical in terms of the technical challenge from single cell WGA process. SCsnvcna is a Bayesian probabilistic model that utilizes both the genotype constraints on the tree and the cellular prevalence (CP) to search the solution that has the highest joint probability. Both simulated and real datasets show that SCsnvcna is highly accurate in predicting the placement of SNVs and SNV cells. In addition, SCsnvcna has a precise prediction of SNV losses due to copy number loss.

bioinformatics↗

bioRxiv2022

GPR183 targets lung-resident CD301b+ conventional dendritic cells type 2 to a subtissular TSLP-TSLP receptor-mediated survival niche within the adventitial cuff

Conventional dendritic cells (cDCs) are strategically localized throughout non-lymphoid tissues. How such spatially regulated subtissular placement is achieved remains largely elusive. Here, we reveal that GPR183 targets CD301b+ cDC2 to a TSLP-dependent survival niche within the adventital cuff. We identified a close association of CD301b+ cDC2 with PDGFR+ fibroblasts within the adventitial region of the lung. Genetic ablation of GPR183 within the cDC lineage leads to a selective loss of CD301b+ cDC2 in conjunction with the loss of CD301b+ cDC2 : fibroblast colocalization. Next bone marrow chimeric experiments and expression studies suggested adventitial fibroblasts as the main source of 7,25 hydroxycholesterol, the natural ligand of GPR183. Single cell transcriptomic receptor ligand inference and subsequent genetic validation revealed TSLP receptor signalling as a crucial fibroblast derived CD301b+ cDC2 survival factor. These data expose a subtissular localization mechanism for tissue-specific functionalization of CD301b+ cDC2.

immunology↗

bioRxiv2022

A machine learning model for disease risk prediction by integrating genetic and non-genetic factors

Polygenic risk score (PRS) has been widely used to identify the high-risk individuals from the general population, which would be helpful for disease prevention and early treatment. Many methods have been developed to calculate PRS by weighted aggregating the phenotype-associated risk alleles from genome-wide association studies. However, only considering genetic effects may not be sufficient for risk prediction because the disease risk is not only related to genetic factors but also non-genetic factors, e.g., diet, physical exercise et al. But it is still a challenge to integrate these genetic and non-genetic factors into a unified machine learning framework for disease risk prediction. In this paper, we proposed PRSIMD (PRS Integrating Multi-source Data), a machine learning model that applies posterior regularization to integrate genetic and non-genetic factors to improve disease risk prediction. Also, we applied Mendelian Randomization analysis to identify the causal non-genetic risk factors for the selected diseases. We applied PRSIMD to predict type 2 diabetes and coronary artery disease from UK Biobank and observed that PRSIMD was significantly better than the methods to calculate PRS including p-value threshold (P+T), PRSice2, SBLUP, DMSLMM, and LDpred2. In addition, we observed that PRSIMD achieved the better predictive power than the composite risk score.

bioinformatics↗

bioRxiv2022

Structural and functional insights into the type III-E CRISPR-Cas immunity

The type III-E CRISPR-Cas system comprises a Cas effector (gRAMP), a TPR-CHAT and several ancillary proteins. However, both the structural features of gRAMP and the immunity mechanism remain unknown for this system. Here, we report a series of structures of gRAMP-crRNA, either its alone or in complex with target RNA or TPR-CHAT (called Craspase), and Craspase complexed with cognate (CTR) or non-cognate target RNA (NTR). Importantly, the 3 anti-tag region of NTR and CTR bind at two distinct channels in the Craspase, and CTR with a non-complementary 3 anti-tag induces a marked conformational change of the TPR-CHAT, which allosterically activates its protease activity to cleave an ancillary protein Csx30. This cleavage then triggers an abortive infection as the antiviral strategy of the type III-E system. Together, our study provides crucial insights into both the catalytic mechanism of the gRAMP and the immunity mechanism of the type III-E CRISPR-Cas system.

molecular biology↗

bioRxiv2022

Detection of Frog virus 3 via the system integrating RPA-CRISPR/Cas12a-SPM with deep learning

Frog virus 3 (FV3, genera Ranavirus, family Iridoviridae), a double-stranded DNA virus, results in irreparable damage to biodiversity and significant economic losses to aquaculture. Although the existing FV3 detection methods are of high sensitivity and specificity, the complex procedure and requirement of expensive instruments limit their practical implantation. Herein, we develop a fast, easy-to-implement, highly sensitive, and point-of-care (POC) detection system for FV3. Combining recombinase polymerase amplification (RPA) and CRISPR/Cas12a, we achieve a limit of detection (LoD) of 100 aM (60.2 copies/L) by optimizing RPA primers and CRISPR RNAs (crRNAs). For POC detection, we build a smartphone microscopy (SPM) and achieve an LoD of 10 aM within 40 minutes. Four positive animal-derived samples with a quantitation cycle (Cq) value of quantitative PCR (qPCR) in the range of 13 to 32 are detectable by the proposed system. In addition, we deploy deep learning models for binary classification (positive or negative samples) and multiclass classification (different concentrations of FV3 and negative samples), achieving 100% and 98.75% accuracy, respectively. Without temperature regulation and expensive equipment, RPA-CRISPR/Cas12a combined with a smartphone readout and artificial intelligence (AI) assisted classification shows great potential for FV3 detection. This integrated system holds great promise for POC detection of aquatic DNA pathogens. HighlightsO_LIAn integrated DNA detection system is developed by combining RPA, CRISPR/Cas12a, smartphone microscopy, and deep learning. C_LIO_LIThe LoD of frog virus 3 is 10 aM within 40 min. C_LIO_LIThe detection system shows good performance on animal-derived samples. C_LI

molecular biology↗

bioRxiv2022

Locating cellular contents during cryoFIB milling by cellular secondary-electron imaging

Cryo-electron tomography (cryoET) is a powerful technique that enables the direct study of the molecular structure of tissues and cells. Cryo-focused ion beam (cryoFIB) milling plays an important role in preparation of high-quality thin lamellar samples for cryoET studies, promoting the rapid development of cryoET in recent years. However, locating the regions of interest in a large cell or tissue during cryoFIB milling remains a major challenge limiting cryoET applications on arbitrary biological samples. Here, we report an on-the-fly location method based on cellular secondary electron imaging (CSEI). CSEI is derived from a basic imaging function of the cryoFIB instruments and enables high-contrast imaging of the cellular contents of frozen hydrated biological samples, highlighted by that both fluorescent labels and additional devices are not required. The present work discusses the imaging principles and settings for optimizing CSEI. Tests on several commercially available cryoFIB instruments demonstrated that CSEI was feasible on mainstream instruments to observe all types of cellular contents and was reliable under different milling conditions. Assisted by CSEI, we established a simple milling-location workflow and tested it using the basal body of Chlamydomonas reinhardtii.

biophysics↗

bioRxiv2022

Single-cell Atlas of Human Fetal Cerebellum Decoding Medulloblastoma Origin and Oncogenesis

Medulloblastoma (MB) is the most common malignant childhood brain tumor1,2, yet the origin of the most aggressive subgroup-3 form remains elusive, impeding development of effective targeted treatments. Previous analyses of mouse cerebella3,4 or human counterparts from frozen tissue nuclei5 have not fully defined the compositional heterogeneity of MBs. Here, we undertook an unprecedented single-cell profiling of freshly-isolated human fetal cerebella to establish a reference map delineating hierarchical cellular states in MBs. We identified a unique transitional cerebellar progenitor connecting neural stem cells to neuronal lineages in developing fetal cerebella. Intersectional analysis revealed that the transitional progenitors were enriched in aggressive MB subgroups, including group-3 and metastatic tumors. Single-cell multi-omics revealed underlying regulatory networks in the transitional progenitor populations, including transcriptional determinants HNRNPH1 and SOX11, which are correlated with clinical prognosis in group-3 MBs. Genomic and Hi-C profiling identified de novo long-range chromatin-loops juxtaposing HNRNPH1/SOX11-targeted super-enhancers to cis-regulatory elements of MYC, an oncogenic driver for group-3 MBs. Targeting the transitional progenitor regulators inhibited MYC expression and MYC-driven group-3 MB growth. Our integrated single-cell atlases of human fetal cerebella and MBs reveal potential cell populations predisposed to transformation and regulatory circuitries underlying tumor cell states and oncogenesis, highlighting hitherto unrecognized transitional progenitor intermediates predictive of disease prognosis and potential therapeutic vulnerabilities.

cancer biology↗

bioRxiv2022

The genome of a vestimentiferan tubeworm (Ridgeia piscesae) provides insights into its adaptation to a deep-sea environment

Vestimentifera (Polychaeta, Siboglinidae) is a taxon of deep-sea worm-like animals living in the deep-sea hydrothermal vent and cold seep areas. The morphology and lifespan of Ridgeia piscesae, which is the only vestimentiferan tubeworm species found in the hydrothermal vents on the Juan de Fuca Ridge, vary greatly according to the endemic environments. Recent analyses have revealed the genomic basis of adaptation in three vent- and seep-dwelling vestimentiferan tubeworms. However, the evolutionary history and mechanism of adaptation in R. piscesae, a unique species in the family Siboglinidae, is remained to be investigated. Here we report a high-quality genome of R. piscesae collected at Cathedral vent of the Juan de Fuca Ridge. Comparative genomic analysis revealed that that the high growth rates of vent-dwelling tubeworms might derive from small genome size. The small genome sizes of these tubeworms are attributed to the repeat content but not the number of genes and intron sizes. Additionally, four genes involved in cell proliferation were subject to positive selection in the genome of R. piscesae, suggesting that, besides apoptosis, cell proliferation is important for regulating growth rate in this species.

genomics↗

bioRxiv2022

RBP45d is required for 5' splice site selection via binding to intronic U-rich elements and interaction with PRP39a in Arabidopsis thaliana

A large number of cryptic splice sites in eukaryotic genome are generally dormant unless activated by mutations of authentic splice sites or splicing factors. How cryptic splice sites are used remains unknown in plants. Here, we identified two cryptic splicing regulators, RBP45d and PRP39a that are homologs of yeast U1 auxiliary protein Nam8 and Prp39, respectively, via genetic screening for suppressors of the virescent sot5 mutant, which results from a point mutation at the 5 splice site (5 ss) of intron 7. PCR and DNA sequencing data showed that loss-of-function mutations in RBP45d and PRP39a significantly increase the level of a cryptically spliced mRNA that encodes a mutated but partially functional sot5 protein, rescuing sot5 to the WT phenotype. Yeast two hybrid and bimolecular fluorescence complementation assays demonstrated that RBP45d and PRP39a interact each other and also with the U1C, a core subunit of U1 small nuclear ribonucleoprotein (U1 snRNP). RNA electronic mobility shift assay showed that RBP45d directly binds to the uridine (U)-rich RNA sequence downstream of the cryptic 5 ss. Consistently, our transcriptomic analysis revealed that a set of introns with U-rich sequences are retained in rbp45d. However, we found that other RBP45/47 members do not function redundantly with RBP45d, at least in regulation of cryptic splicing. Collectively, our data suggest that RBP45d is required for 5 ss selection via binding to intronic U-rich elements and PRP39a in plants. One sentence summaryThe Arabidopsis RBP45d interacting with U1C and PRP39a is required for 5 ss selection via binding to intronic U-rich elements.

plant biology↗

bioRxiv2022

LRTK: A unified and versatile toolkit for analyzing linked-read sequencing data

Linked-read sequencing technologies generate high base quality reads that contain extrapolative information on long-range DNA connectedness. These advantages of linked-read technologies are well known and has been demonstrated in many human genomic and metagenomic studies. However, existing linked-read analysis pipelines (e.g., Long Ranger) were primarily developed to process sequencing data from the human genome and are not suited for analyzing metagenomic sequencing data. Moreover, linked-read analysis pipelines are typically limited to one specific sequencing platform. To address these limitations, we present the Linked-Read ToolKit (LRTK), a unified and versatile toolkit for platform agnostic processing of linked-read sequencing data from both human genomes and metagenomes. LRTK provides functions to perform linked-read simulation, barcode error correction, read cloud assembly, barcode-aware read alignment, reconstruction of long DNA fragments, taxonomic classification and quantification, as well as barcode-assisted genomic variant calling and phasing. LRTK has the ability to process multiple samples automatically, and provides the user with the option to generate reproducible reports during processing of raw sequencing data and at multiple checkpoints throughout downstream analysis. We applied LRTK on two benchmarking and three real linked-read data sets from both the human genome and metagenome. We showcase LRTKs ability to generate comparative performance results from the preceding benchmark study and to report these results in publication-ready HTML document plots. LRTK provides comprehensive and flexible modules along with an easy-to-use Python-based workflow for processing linked-read sequencing datasets, thereby filling the current gap in the field caused by platform-centric genome-specific linked-read data analysis tools.

bioinformatics↗