bioRxiv Science⌕ Search

Biology subjects

Luo, Y.

Publications and source records attributed to Luo, Y..

At least 235 records · Page 13Linked to original sources

Post-Transplant Administration of G-CSF Impedes Engraftment of Gene Edited Human Hematopoietic Stem Cells by Exacerbating the p53-Mediated DNA Damage Response

Granulocyte colony stimulating factor (G-CSF) is commonly used as adjunct treatment to hasten recovery from neutropenia following chemotherapy and autologous transplantation of hematopoietic stem and progenitor cells (HSPCs) for malignant disorders. However, the utility of G-CSF administration after ex vivo gene therapy procedures targeting human HSPCs has not been thoroughly evaluated. Here, we provide evidence that post-transplant administration of G-CSF impedes engraftment of CRISPR-Cas9 gene edited human HSPCs in xenograft models. G-CSF acts by exacerbating the p53-mediated DNA damage response triggered by Cas9- mediated DNA double-stranded breaks. Transient p53 inhibition in culture attenuates the negative impact of G-CSF on gene edited HSPC function. In contrast, post-transplant administration of G-CSF does not impair the repopulating properties of unmanipulated human HSPCs or HSPCs genetically engineered by transduction with lentiviral vectors. The potential for post-transplant G-CSF administration to aggravate HSPC toxicity associated with CRISPR-Cas9 gene editing should be considered in the design of ex vivo autologous HSPC gene editing clinical trials. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=121 SRC="FIGDIR/small/547089v1_ufig1.gif" ALT="Figure 1"> View larger version (38K): org.highwire.dtl.DTLVardef@1dae519org.highwire.dtl.DTLVardef@1f6ddacorg.highwire.dtl.DTLVardef@535cbaorg.highwire.dtl.DTLVardef@ecbeaf_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

Leucine alleviates cytokine storm syndrome by regulating macrophage polarization via the mTORC1/LXRα signaling pathway

Cytokine storms are associated with severe pathological damage and death in some diseases. Excessive activation of M1 macrophages and the subsequent secretion of pro-inflammatory cytokines are a major cause of cytokine storms. Therefore, promoting the polarization of M2 macrophages to restore immune balance is a promising therapeutic strategy for treating cytokine storm syndrome (CSS). This study was aimed at investigating the potential protective effects of leucine on lipopolysaccharide (LPS)-induced CSS in mice and exploring the underlying mechanisms. CSS was induced by LPS administration in mice, which were concurrently administered leucine orally. In vitro, BMDMs were polarized to M1 and M2 phenotypes with LPS and IL-4, respectively, and treated with leucine. Leucine decreased mortality in mice treated with lethal doses of LPS. Specifically, leucine decreased M1 polarization and promoted M2 polarization, thus diminishing pro-inflammatory cytokine levels and ameliorating CSS in mice. Further studies revealed that leucine induced macrophage polarization through the mechanistic target of rapamycin complex 1 (mTORC1)/liver X receptor (LXR) pathway, which synergistically enhanced the expression of the IL-4-induced M2 marker Arg1 and subsequent M2 polarization. In summary, this study revealed that leucine ameliorates CSS in LPS mice by promoting M2 polarization through the mTORC1/LXR/Arg1 signaling pathway. Our findings indicate that a fundamental link between metabolism and immunity contributes to the resolution of inflammation and the repair of damaged tissues.

immunology↗

Reduced Reverse Replay in Anxious Individuals Impairs Reward Prediction

Understanding how we learn about the value and structure of our environment is central to neurocognitive theories of many psychiatric and neurological disorders. Learning processes have been extensively studied during performance of behavioural tasks (online learning) but less so in relation to "resting" (offline) states. A candidate mechanism for such offline learning is "replay," the sequential neural reactivation of past experiences. Notably, value-based learning is especially tied to replay unfolding in reverse order relative to the original experience ("backward replay"). Here, we demonstrate the utility of EEG-based neural decoding for investigating offline learning, and relate it to trait anxiety. Participants were first required to infer sequential relationships among task objects by using a learned rule to reorganise their visual experiences into distinct sequences. Afterwards, they observed that the final object in one of the sequences was associated with a monetary reward and then entered a post-value resting state. During this rest, we found evidence of backward replay for reward-linked object sequences. The strength of such replay was negatively associated with trait anxiety and positively predicted an increased behavioural preference for reward-predictive stimuli. We also found that high-trait-anxiety individuals showed inefficient credit assignment irrespective of reward magnitude, indicating that this effect does not merely reflect reduced reward sensitivity. Together, these findings suggest a potential aberrant replay mechanism during offline learning in individuals with high trait anxiety. More broadly, our approach illustrates the potential of EEG for measuring structured neural representations in vivo, with implications for studying cognition across a range of neuropsychiatric and neurological disorders.

neuroscience↗

Levy statistics define anxiety and depression in mice subjected to chronic stress

IntroductionAnxiety and depression are recognized as adaptive responses to external stressors in organisms. Current methods for evaluating anxiety and depression in rodents are both burdensome and stressful. The objective of this investigation is to explore a simplified methodology for identifying stress-induced and stress-free states, as well as anxiety and depression levels, by analyzing the movement patterns of rodents. MethodsTo address this issue, we utilized Levy statistics to examine the movement patterns of stressed rodents and compared them to non-stressed controls. We employed the two-dimensional Kolmogorov-Smirnov test to identify significant differences in the {gamma} and parameters derived from Levy flight (LF) between anxiety, depression, and control mice. Additionally, we employed the support vector machine algorithm to optimize the classification of each group. ResultsOur analysis revealed that stressed mice displayed heavy-tailed distributions of movement velocity in open fields, resembling the movement patterns observed in animal predators searching for scarce food sources in nature. In contrast, non-stressed mice exhibited a normal distribution of speed. Notably, the effectiveness of this methodology in the field of drug discovery was confirmed by the response of stressed mice to fluoxetine, a well-established selective serotonin reuptake inhibitor (SSRI). ConclusionThis study unveils a previously unidentified statistical walking pattern in mice experiencing anxiety and depression. These findings offer a novel and accessible approach for distinguishing between anxiety, depression, and healthy mice. This method provides a one-step gentle approach (free walk in an open field) instead of the traditional multi-step stressful tests.

animal behavior and cognition↗

Construction of a multi-tissue cell atlas reveals cell-type-specific regulation of molecular and complex phenotypes in pigs

The systematic characterization of cellular heterogeneity among tissues and cell-type-specific regulation underlying complex phenotypes remains elusive in pigs. Within the Pig Genotype-Tissue Expression (PigGTEx) project, we present a single-cell transcriptome atlas of adult pigs encompassing 229,268 high-quality nuclei from 19 tissues, annotated to 67 major cell types. Besides cellular heterogeneity within and across tissues, we further characterize prominent tissue-specific features and functions of muscle, epithelial, and immune cells. Through deconvoluting 3,921 bulk RNA-seq samples from 17 matching tissues, we dissect thousands of genetic variants with cell-type interaction effects on gene expression (ieQTL). By colocalizing these ieQTL with variants associated with 268 complex traits, we provide new insights into the cellular mechanisms behind these traits. Moreover, we highlight that orthologous genes with cell-type-specific regulation in pigs exhibit significant heritability enrichment for some human complex phenotypes. Altogether, our work provides a valuable resource and highlights novel insights in cellular regulation of complex traits for accelerating pig precision breeding and human biomedical research.

genetics↗

CHPF boosts proliferation and invasion of clear cell renal cell carcinoma

BackgroundClear cell renal cell carcinoma (ccRCC) is a malignant tumor most commonly seen in the urinary system, featuring quick progression, invasive behavior, frequent recrudesce, and bad prognosis, whereas Chondroitin polymerizing factor (CHPF) is an essential glycosyl transferase of biosynthesis involved chondroitin sulphate. But the relationship between the two has not been fully understood so far. The present research will probe into the relationship between CHPF and ccRCC. MethodsExplore the CHPF expression level in renal ccRCC tissues through bioinformatics analysis of The Cancer Genome Atlas (TCGA) and the real-time quantitative polymerase chain reaction detection system (qPCR); acquire relevant clinical data from the TCGA data-base and use Kaplan-Meier survival analysis to verify the relevance of CHPF expression to the clinical prognosis of ccRCC patients; then, effectively silence CHPF in ccRCC 786-O cells by a lentivirus-mediated approach; next, observe the effects of CHPF on tumor cell proliferation, cell cycle progression, and apoptosis. ResultsIn ccRCC tissues, CHPF expression has been significantly upregulated; the higher expression, the shorter survival of ccRCC patients. CHPF downregulation in the 786-O cell can effectively hold back the proliferation, apoptosis and cycle of cancer cells. ConclusionBased on the above results, we arrive at a conclusion that CHPF expression contributes markedly to the development of human ccRCC cells. Therefore, CHPF may act as a potential prognostic marker of ccRCC and provide a new target for ccRCC treatment. Simple SummaryChondroitin polymerizing factor (CHPF) is an important glycosyltransferase involved in the biosynthesis of chondroitin sulfate, which is thought to have some pro-carcinogenic effects. However, the role and mechanism of CHPF in clear cell renal cell carcinoma (ccRCC) have not been reported. The aim of this study was to investigate the relationship between CHPF and ccRCC. In this study, we found that CHPF was highly expressed in ccRCC and knocking out CHPF can greatly inhibit the proliferation and cell cycle progression of ccRCC and accelerate its apoptosis, suggesting that CHPF can predict the prognosis of ccRCC and a potential target for treatment.

genetics↗

Silk Road Revealed: Mechanism of silk fibre formation in Bombyx mori

The transition of silk fibroin from liquid to solid is fundamental to silk-fibre production and key to the superior materials properties of native silks. Here we discover that the fibroin heavy chain from the silkworm moth Bombyx mori folds into a novel {beta}-solenoid structure, where the N-terminal domain (NTD) promotes higher-order oligomerization driven by pH reduction. These findings elucidate the complex rheological behaviour of silk and the liquid crystalline textures within the silk gland. We also find that NTD undergoes hydrolysis during standard regeneration, explaining differences between native and regenerated silk feedstocks. Overall, this study establishes a fibroin heavy chain fold, which could be relevant for other similar proteins, and explains mechanistically its liquid-to-solid transition, driven by pH reduction and stress. One sentence summaryThis study redefines the molecular structure of fibroin heavy chain and its role in the transition from solution to fibre.

biochemistry↗

Changes in the gut mycobiome are associated with Type 2 diabetes mellitus and metformin treatment across populations

The human gut teems with a diverse ecosystem of microbes, yet non-bacterial portions of that community are overlooked in studies of metabolic diseases firmly linked to gut bacteria. Type 2 diabetes mellitus (T2D) associates with compositional shifts in the gut bacterial microbiome and fungal mycobiome, but whether T2D and/or pharmaceutical treatments underpin the community change is unresolved. To differentiate these effects, we curated a gut mycobiome cohort to-date spanning 1,000 human samples across 5 countries and a murine experimental model. We use Bayesian multinomial logistic normal models to show that metformin and T2D both associate with shifts in the relative abundance of distinct gut fungi. T2D associates with shifts in the Saccharomycetes and Sordariomycetes fungal classes, while the genera Fusarium and Tetrapisipora most consistently associate with metformin treatment. We confirmed the impact of metformin on individual gut fungi by administering metformin to healthy mice. Thus, metformin and T2D account for subtle, but significant and distinct variation in the gut mycobiome across human populations. This work highlights for the first time that oral pharmaceuticals can confound associations of gut fungi with T2D and warrants the need to consider pharmaceutical interventions in investigations of linkages between metabolic diseases and gut microbial inhabitants.

microbiology↗

Discovery of new deaminase functions by structure-based protein clustering

The elucidation of protein function and its exploitation in bioengineering have greatly contributed to the development of the life sciences. Existing protein mining efforts generally rely on amino acid sequences rather than protein structures due to technical difficulties in structural elucidation. We describe here for the use of AlphaFold2 to predict and subsequently cluster an entire protein family based on predicted structure similarities. We selected the deaminase family of proteins to analyze and through this approach identified many previously unknown deaminase properties. We applied these new deaminases to the development of new cytosine base editors with distinct features. Although we found many new double-stranded DNA deaminases from the DddA-like protein clade, we were surprised to find that most of the proteins in this family were not actually double-stranded DNA cytidine deaminases. From this protein clade, we engineered the smallest single-strand specific cytidine deaminase, which facilitates the first efficient cytosine base editor to be packaged into a single AAV vector. Importantly, we also profiled a deaminase from this clade that edits robustly in soybean plants, which previously suffered from poor editing by cytosine base editors. These newly discovered deaminases based on AI-assisted structural predictions greatly expand the utility of base editors for therapeutic and agricultural applications.

molecular biology↗

A novel bacterial signal transduction system specifically senses and responds to peptidoglycan damage

The peptidoglycan (PG) layer is a mesh-like structure within the cell envelope essential for maintenance of cell shape and resistance to osmotic stress, and therefore is a primary target of many important and widely used antibiotics, such as {beta}-lactams. In Gram-negative bacteria, while signal transduction systems that monitor the state of the inner- and outer-membranes have been extensively studied and well understood, much less is known about how cells sense and respond to PG-targeting stresses. Here we show that a novel bacterial two-component system (PghKR) from Shewanella oneidensis is capable of sensing and responding to PG damage. This system is specifically activated in cells exposed to various PG-targeting antibiotics or carrying a defect in PG synthesis, resulting in induced expression of blaA and relV, which encode a {beta}-lactamase conferring resistance to {beta}-lactams and a small ppGpp synthetase responsible for antibiotic tolerance, respectively. Intriguingly, the PghKR homologs are widespread among several classes of Proteobacteria and the periplasmic domain of sensor kinase PghK contains a family 9 carbohydrate-binding module that is required for signal perception, implying that the signals could be the glycan fragments of PG. Overall, our results provide critical insights into the regulation of PG homeostasis in Gram-negative bacteria.

microbiology↗

Amphiphilic particle-stabilized nanoliter droplet reactors with a multi-modal portable reader for distributive biomarker quantification

Compartmentalization, leveraging microfluidics, enables highly sensitive assays; but the requirement for significant infrastructure for their design, build, and operation limits access. Newer multi-material particle-based technologies thermodynamically stabilize monodisperse droplets as individual reaction compartments with simple liquid handling steps, precluding the need for expensive microfluidic equipment. Here, we further improve the accessibility of this lab on a particle technology to resource-limited settings by combining this assay system with a portable multi-modal reader, thus enabling nanoliter droplet assays in an accessible platform. We show the utility of this platform in measuring N-terminal propeptide B-type natriuretic peptide (NT-proBNP), a heart failure biomarker, in complex medium and patient samples. We report a limit of detection of [~]0.05 ng/ml and a linear response between 0.2 - 2 ng/ml in spiked plasma samples. We also show that, owing to the plurality of measurements per sample, "swarm" sensing acquires better statistical quantitation with a portable reader. Monte Carlo simulations show the increasing capability of this platform to differentiate between negative and positive samples, i.e. below or above the clinical cut-off for acute heart failure ([~]0.1ng/ml), as a function of the number of particles measured. Our platform measurements correlate with gold standard ELISA measurement in cardiac patient samples, and achieve lower variation in measurement across samples compared to the standard well plate-based ELISA. Thus, we show the capabilities of a cost-effective droplet-reader system in accurately measuring biomarkers in nanoliter droplets for diseases that disproportionally affect underserved communities in resource-limited settings.

bioengineering↗

Supervised biological network alignment with graph neural networks

MotivationDespite the advances in sequencing technology, massive proteins with known sequences remain functionally unannotated. Biological network alignment (NA), which aims to find the node correspondence between species protein-protein interaction (PPI) networks, has been a popular strategy to uncover missing annotations by transferring functional knowledge across species. Traditional NA methods assumed that topologically similar proteins in PPIs are functionally similar. However, it was recently reported that functionally unrelated proteins can be as topologically similar as functionally related pairs, and a new data-driven or supervised NA paradigm has been proposed, which uses protein function data to discern which topological features correspond to functional relatedness. ResultsHere, we propose GraNA, a deep learning framework for the supervised NA paradigm for the pairwise network alignment problem. Employing graph neural networks, GraNA utilizes within-network interactions and across-network anchor links for learning protein representations and predicting functional correspondence between across-species proteins. A major strength of GraNA is its flexibility to integrate multi-faceted non-functional relationship data, such as sequence similarity and ortholog relationships, as anchor links to guide the mapping of functionally related proteins across species. Evaluating GraNA on a benchmark dataset composed of several NA tasks between different pairs of species, we observed that GraNA accurately predicted the functional relatedness of proteins and robustly transferred functional annotations across species, outperforming a number of existing NA methods. When applied to a case study on a humanized yeast network, GraNA also successfully discovered functionally replaceable human-yeast protein pairs that were documented in previous studies. AvailabilityThe code of GraNA is available at https://github.com/luo-group/GraNA. Contactyunan@gatech.edu

bioinformatics↗

Preliminary evidence of a relationship between sleep spindles and treatment response in epileptic encephalopathy

ObjectiveEpileptic encephalopathy with spike wave activation in sleep (EE-SWAS) is a challenging neurodevelopmental disease characterized by abundant epileptiform spikes during non-rapid eye movement (NREM) sleep accompanied by cognitive dysfunction. The mechanism of cognitive dysfunction is unknown, but treatment with high-dose diazepam may improve symptoms. Spike rate does not predict treatment response, but spikes may disrupt sleep spindles. We hypothesized that in patients with EE-SWAS: 1) spikes and spindles would be anticorrelated, 2) high-dose diazepam would increase spindles and decrease spikes, and 3) spindle response would be greater in those with cognitive improvement. MethodsConsecutive EE-SWAS patients treated with high-dose diazepam that met criteria were included. Using a validated automated spindle detector, spindle rate, duration, and percentage were computed in pre- and post-treatment NREM sleep. Spikes were quantified using a validated automated spike detector. Cognitive response was determined from chart review. ResultsSpindle rate was anticorrelated with spike rate in the channel with the maximal spike rate (p=0.002) and averaged across all channels (p=0.0005). Spindle rate, duration, and percentage each increased, and spike rate decreased, after high-dose diazepam treatment (p[≤]2e-5, all tests). Spindle rate, duration, and percentage (p[≤]0.004, all tests) were increased in patients with cognitive improvement after treatment, but not those without. Changes in spike rate did not distinguish between groups. InterpretationThese findings confirm thalamocortical disruption in EE-SWAS, identify a mechanism through which benzodiazepines may support cognitive recovery, and introduce sleep spindles as a promising mechanistic biomarker to detect treatment response in severe epileptic encephalopathies.

neuroscience↗

Finding the right tool: a comprehensive evaluation of microglial inducible cre mouse models

The recent proliferation of new Cre and CreER recombinase lines provides researchers with a diverse toolkit to study microglial gene function. To determine how best to apply these lines in studies of microglial gene function, a thorough and detailed comparison of their properties is needed. Here, we examined four different microglial CreER lines (Cx3cr1CreER(Litt), Cx3cr1CreER(Jung), P2ry12CreER, Tmem119CreER), focusing on (1) recombination specificity; (2) leakiness - degree of non-tamoxifen recombination in microglia and other cells; (3) efficiency of tamoxifen-induced recombination; (4) extra-neural recombination -the degree of recombination in cells outside the CNS, particularly myelo/monocyte lineages (5) off-target effects in the context of neonatal brain development. We identify important caveats and strengths for these lines which will provide broad significance for researchers interested in performing conditional gene deletion in microglia. We also provide data emphasizing the potential of these lines for injury models that result in the recruitment of splenic immune cells.

neuroscience↗

Liproxstatin-1 alleviates cartilage degradation by inhibiting chondrocyte ferroptosis in temporomandibular joint

Ferroptosis contribute to temporomandibular joint osteoarthritis (TMJOA) lesion development is still poorly understood. In this study, we used different TMJOA animal models to detect whether ferroptosis is related to onset of TMJOA which modelling by monosodium iodoacetate (MIA), IL-1{beta}, occlusion disorder (OD) and unilateral anterior crossbite (UAC). Immunohistochemical staining and Western blot analysis were used to detect ferroptosis proteins and cartilage degradation related protein expression. Our results revealed that lower level of ferroptosis-related proteins GPX4 in cartilage layer, but the level of ACSL4 and P53 increase in that of condyle. Injection of ferroptosis inhibitor liproxstatin-1 (Lip-1) effectively decrease ACSL4, P53 and TRF expression. In vitro, IL-1{beta} induced the reduction of cartilage extracellular matrix expression in mandibular condylar chondrocytes (MCCs). Lip-1 maintain the morphology and function of mitochondria, and inhibited the aggravation of lipid peroxidation and reactive oxygen species (ROS) production which induced by IL-1{beta}. These results suggested that chondrocytes ferroptosis play an important role in the development and progression of TMJOA. Inhibition of condylar chondrocyte ferroptosis could be a promising therapeutic strategy for TMJOA. SUMMARY STATEMENTFerroptosis contributed the development and progression of Temporomandibular Joint Osteoarthritis cartilage degeneration. Lip-1 can effective improvement the cartilage degradation of condyle.

cell biology↗

NULISA: a novel proteomic liquid biopsy platform with attomolar sensitivity and high multiplexing

The blood proteome holds great promise for precision medicine but poses substantial challenges due to the low abundance of most plasma proteins and the vast dynamic range across the proteome. We report a novel proteomic technology - NUcleic acid Linked Immuno-Sandwich Assay (NULISA) - that incorporates a dual capture and release mechanism to suppress the assay background and improves the sensitivity of the proximity ligation assay by over 10,000-fold to the attomolar level. It utilizes pairs of antibodies conjugated to DNA oligonucleotides that enable immunocomplex purification and generate reporter DNA containing target- and sample-specific barcodes for a next-generation sequencing-based, highly multiplexed readout. A 200-plex NULISA targeting 124 cytokines and chemokines and 80 other immune response-related proteins demonstrated superior sensitivity for detecting low-abundance proteins and high concordance with other immunoassays. The ultrahigh sensitivity allowed the detection of previously difficult-to-detect, but biologically important, low-abundance biomarkers in patients with autoimmune diseases and COVID-19. Fully automated NULISA addresses longstanding challenges in proteomic analysis of liquid biopsies and makes broad and in-depth proteomic analysis accessible to the general research community and future diagnostic applications.

genomics↗

Global Marine Cold Seep Metagenomes Reveal Diversity of Taxonomy, Metabolic Function, and Natural Products

Cold seeps in the deep sea are closely linked to energy exploration as well as global climate change. The alkane-dominated chemical energy-driven model makes cold seeps an oasis of deep-sea life, showcasing an unparalleled reservoir of microbial genetic diversity. By analyzing 113 metagenomes collected from 14 global sites across 5 cold seep types, we present a comprehensive Cold Seep Microbiomic Database (CSMD) to archive the genomic and functional diversity of cold seep microbiome. The CSMD includes over 49 million non-redundant genes and 3175 metagenome-assembled genomes (MAGs), which represent 1897 species spanning 106 phyla. In addition, beta diversity analysis indicates that both sampling site and cold seep type have substantial impact on the prokaryotic microbiome community composition. Heterotrophic and anaerobic metabolisms are prevalent in microbial communities, accompanied by considerable mixotrophs and facultative anaerobes, indicating the versatile metabolic potential in cold seeps. Furthermore, secondary metabolic gene cluster analysis indicates that at least 98.81% of the sequences encode potentially novel natural products. These natural products are dominated by ribosomal processing peptides, which are widely distributed in archaea and bacteria. Overall, the CSMD represents a valuable resource which would enhance the understanding and utilization of global cold seep microbiomes.

microbiology↗

The ENCODE Uniform Analysis Pipelines

The Encyclopedia of DNA elements (ENCODE) project is a collaborative effort to create a comprehensive catalog of functional elements in the human genome. The current database comprises more than 19000 functional genomics experiments across more than 1000 cell lines and tissues using a wide array of experimental techniques to study the chromatin structure, regulatory and transcriptional landscape of the Homo sapiens and Mus musculus genomes. All experimental data, metadata, and associated computational analyses created by the ENCODE consortium are submitted to the Data Coordination Center (DCC) for validation, tracking, storage, and distribution to community resources and the scientific community. The ENCODE project has engineered and distributed uniform processing pipelines in order to promote data provenance and reproducibility as well as allow interoperability between genomic resources and other consortia. All data files, reference genome versions, software versions, and parameters used by the pipelines are captured and available via the ENCODE Portal. The pipeline code, developed using Docker and Workflow Description Language (WDL; https://openwdl.org/) is publicly available in GitHub, with images available on Dockerhub (https://hub.docker.com), enabling access to a diverse range of biomedical researchers. ENCODE pipelines maintained and used by the DCC can be installed to run on personal computers, local HPC clusters, or in cloud computing environments via Cromwell. Access to the pipelines and data via the cloud allows small labs the ability to use the data or software without access to institutional compute clusters. Standardization of the computational methodologies for analysis and quality control leads to comparable results from different ENCODE collections - a prerequisite for successful integrative analyses. Database URL: https://www.encodeproject.org/

bioinformatics↗