Biology subjects

Li, S.

Publications and source records attributed to Li, S..

1,349 records · Page 75Linked to original sources

bioRxiv2017

Structural basis of the Cope rearrangement and C-C bond-forming cascade in hapalindole/fischerindole biogenesis

STRUCTURESThe atomic coordinates and structure factors for:\n\nHpiC1 W73M/K132M SeMet (P212121) -1.7 [A]\n\nHpiC1 native (C2) -1.5 [A]\n\nHpiC1 native (P42) -2.1 [A]\n\nHpiC1 Y101F (C2) -1.4 [A]\n\nHpiC1 Y101S (C2) -1.4 [A]\n\nHpiC1 F138S (P21) -1.7 [A]\n\nHpiC1 Y101F/F138S (P21 -1.65 [A] have been deposited with the Research Collaboratory for Structural Bioinformatics as Protein Data Bank entries 5WPP, 5WPR, 6AL6, 5WPR, 5WPU, 6AL7, and 6AL8 (www.rcsb.org).\n\nGRANTSThis work was supported by: The authors thank the National Science Foundation under the CCI Center for Selective C-H Functionalization (CHE-1205646), the National Institutes of Health (CA70375 to RMW and DHS), R35 GM118101, R01 GM076477 and the Hans W. Vahlteich Professorship (to DHS) for financial support. M.G-B. thanks the Ramon Areces Foundation for a postdoctoral fellowship. J.N.S. acknowledges the support of the National Institute of General Medical Sciences of the National Institutes of Health under Award Number F32GM122218. Computational resources were provided by the UCLA Institute for Digital Research and Education (IDRE) and the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by the NSF (OCI-1053575). The content does not necessarily represent the official views of the National Institutes of Health.\n\nABSTRACTHapalindole alkaloids are a structurally diverse class of cyanobacterial natural products defined by their varied polycyclic ring systems and diverse biological activities. These polycyclic scaffolds are generated from a common biosynthetic intermediate by the Stig cyclases in three mechanistic steps, including a rare Cope-rearrangement, 6-exo-trig cyclization, and electrophilic aromatic substitution. Here we report the structure of HpiC1, a Stig cyclase that catalyzes the formation of 12-epi-hapalindole U in vitro. The 1.5 [A] structure reveals a dimeric assembly with two calcium ions per monomer and the active sites located at the distal ends of the protein dimer. Mutational analysis and computational methods uncovered key residues for an acid catalyzed [3,3]-sigmatropic rearrangement and specific determinants that control the position of terminal electrophilic aromatic substitution leading to a switch from hapalindole to fischerindole alkaloids.

biochemistry↗

bioRxiv2017

Computational proteogenomic identification and functional interpretation of translated fusions and micro structural variations in cancer

MotivationRapid advancement in high throughput genome and transcriptome sequencing (HTS) and mass spectrometry (MS) technologies has enabled the acquisition of the genomic, transcriptomic and proteomic data from the same tissue sample. In this paper we introduce a novel computational framework which can integratively analyze all three types of omics data to obtain a complete molecular profile of a tissue sample, in normal and disease conditions. Our framework includes MiStrVar, an algorithmic method we developed to identify micro structural variants (microSVs) on genomic HTS data. Coupled with deFuse, a popular gene fusion detection method we developed earlier, MiStrVar can provide an accurate profile of structurally aberrant transcripts in cancer samples. Given the breakpoints obtained by MiStrVar and deFuse, our framework can then identify all relevant peptides that span the breakpoint junctions and match them with unique proteomic signatures in the respective proteomics data sets. Our framework's ability to observe structural aberrations at three levels of omics data provides means of validating their presence.\n\nResultsWe have applied our framework to all The Cancer Genome Atlas (TCGA) breast cancer Whole Genome Sequencing (WGS) and/or RNA-Seq data sets, spanning all four major subtypes, for which proteomics data from Clinical Proteomic Tumor Analysis Consortium (CPTAC) have been released. A recent study on this dataset focusing on SNVs has reported many that lead to novel peptides [1]. Complementing and significantly broadening this study, we detected 244 novel peptides from 432 candidate genomic or transcriptomic sequence aberrations. Many of the fusions and microSVs we discovered have not been reported in the literature. Interestingly, the vast majority of these translated aberrations (in particular, fusions) were private, demonstrating the extensive inter-genomic heterogeneity present in breast cancer. Many of these aberrations also have matching out-of-frame downstream peptides, potentially indicating novel protein sequence and structure. Moreover, the most significantly enriched genes involved in translated fusions are cancer-related. Furthermore a number of the somatic, translated microSVs are observed in tumor suppressor genes.\n\nContactcenksahi@indiana.edu

bioinformatics↗

bioRxiv2017

Drosophila Kruppel homolog 1 represses lipolysis through interaction with dFOXO

Transcriptional coordination is a vital process contributing to metabolic homeostasis. As one of the key nodes in the metabolic network, the forkhead transcription factor FOXO has been shown to interact with diverse transcription co-factors and integrate signals from multiple pathways to control metabolism, oxidative stress response, and cell cycle. Recently, insulin/FOXO signaling has been implicated in the regulation of insect development via the interaction with insect hormones, such as ecdysone and juvenile hormone. In this study, we identified an interaction between dFOXO and the zinc finger transcription factor Kruppel homolog 1 (Kr-h1), one of the key players in juvenile hormone signaling in Drosophila. We found that Kr-h1 mutants have reduced triglyceride storage, decreased insulin signaling and delayed larval development. Notably, Kr-h1 physically and genetically interacts with dFOXO in vitro and in vivo to regulate the transcriptional activation of adipose lipase brummer (bmm). The transcriptional co-regulation by Kr-h1 and dFOXO may represent a broad mechanism by which Kruppel-like factors integrate with insulin signaling to maintain metabolic homeostasis and coordinate organism growth.

genetics↗

bioRxiv2017

Spectrin is a mechanoresponsive protein shaping the architecture of intercellular invasion

Spectrin is a membrane skeletal protein best known for its structural role in maintaining cell shape and protecting cells from mechanical damage1-3. Here, we report that spectrin dynamically accumulates and dissolves at the fusogenic synapse, where an attacking fusion partner mechanically invades its receiving partner with actin-propelled protrusions to promote cell-cell fusion4-7. Using genetics, cell biology, biophysics and mathematical modeling, we demonstrate that unlike myosin II that responds to dilation deformation, spectrin exhibits a mechanosensitive accumulation in response to shear deformation, which is highly elevated at the fusogenic synapse. The accumulated spectrin forms an uneven network, which functions as a \"sieve\" to constrict the invasive fingerlike protrusions, thus putting the fusogenic synapse under high mechanical tension to promote cell membrane fusion. Taken together, our study has revealed a previously unrecognized function of spectrin as a dynamic mechanoresponsive protein that shapes the architecture of intercellular invasion. These findings have general implications for understanding spectrin function in other dynamic cellular processes beyond cell-cell fusion.

cell biology↗

bioRxiv2017

GADD45α regulates cell proliferation and DNA repair of BRL-3A cells that treated by FZD/UVC via P38, JNK, CDC2/CCNB1, AKT and MTOR pathways

GADD45 is a stress-induced gene activated by a variety of stress stimuli, including ultraviolet and ionizing radiation, and involved in cell cycle regulation, apoptosis, maintenance, genomic stability, DNA repair and immune response. However, the effects and regulatory mechanism of GADD45 on proliferation, apoptosis and DNA damage repair of hepatocytes in liver regeneration remains unclear. In this study overexpression of GADD45 significantly inhibited the cell viability, proliferation, the number of cells in G1 and S phases, and of furazolidone (FZD) or UVC induced apoptosis of BRL-3A cells and decreased the inhibition of FZD/UVC on the viability, proliferation of BRL-3A cells, while increased the number of cells in G2/M phase of BRL-3A cells and FZD/UVC induced S phase arrest. Downregulated GADD45 induced the viability, proliferation, the number of cells in S and G2/M phases and the inhibition of FZD/UVC on the viability, proliferation of BRL-3A cells increased, while decreased apoptosis, the number of cells in G1 phases of BRL-3A cells and FZD/UVC induced S phase arrest. The results of qRT-PCR and western blot showed that genes/proteins related to P38MAPK, JNK, CDC2/CCNB1, AKT and MTOR signaling pathways were significantly changed in normal BRL-3A cells. The expression profiles of cell cycle, proliferation and apoptosis related genes/proteins in FZD/UVC treated BRL-3A cells were also detected by qRT-PCR and western blot, and the results indicated that the expression of Myc, Bcl-2, Ccnd1, PCNA, P21, Ccnb1, Caspase3, Caspase8, Caspase9 and Bax have significantly changes.

cell biology↗

bioRxiv2017

Untangling The Gene-Epigenome Networks: Timing Of Epigenetic Regulation Of Gene Expression In Acquired Cetuximab Resistance

BACKGROUNDTargeted therapies specifically act by blocking the activity of proteins that are encoded by genes critical for tumorigenesis. However, most cancers acquire resistance and long-term disease remission is rarely observed. Understanding the time course of molecular changes responsible for the development of acquired resistance could enable optimization of patients treatment options. Clinically, acquired therapeutic resistance can only be studied at a single time point in resistant tumors. To determine the dynamics of these molecular changes, we obtained high throughput omics data weekly during the development of cetuximab resistance in a head and neck cancer in vitro model.\n\nRESULTSAn unsupervised algorithm, CoGAPS, was used to quantify the evolving transcriptional and epigenetic changes. Applying a PatternMarker statistic to the results from CoGAPS enabled novel heatmap-based visualization of the dynamics in these time course omics data. We demonstrate that transcriptional changes result from immediate therapeutic response or resistance, whereas epigenetic alterations only occur with resistance. Integrated analysis demonstrates delayed onset of changes in DNA methylation relative to transcription, suggesting that resistance is stabilized epigenetically.\n\nCONCLUSIONSGenes with epigenetic alterations associated with resistance that have concordant expression changes are hypothesized to stabilize resistance. These genes include FGFR1, which was associated with EGFR inhibitor resistance previously. Thus, integrated omics analysis distinguishes the timing of molecular drivers of resistance. Our findings provide a relevant towards better understanding of the time course progression of changes resulting in acquired resistance to targeted therapies. This is an important contribution to the development of alternative treatment strategies that would introduce new drugs before the resistant phenotype develops.

cancer biology↗

bioRxiv2017

Human brain-derived Aβ oligomers bind to synapses and disrupt synaptic activity in a manner that requires APP

Compelling genetic evidence links the amyloid precursor protein (APP) to Alzheimers disease (AD), and several theories have been advanced to explain the involvement of APP in AD. A leading hypothesis proposes that a small amphipathic fragment of APP, the amyloid {beta}-protein (A{beta}), self-associates to form soluble aggregates which impair synaptic and network activity. Here, we report on the plasticity-disrupting effects of A{beta} isolated from AD brain and the requirement of APP for these effects. We show that A{beta}-containing AD brain extracts block hippocampal long-term potentiation (LTP), augment glutamate release probability and disrupt the excitation/inhibition balance. Notably, these effects are associated with A{beta} localizing to synapses, and genetic ablation of APP prevents both A{beta} binding and A{beta}-mediated synaptic dysfunctions. These findings indicate a role for APP in AD pathogenesis beyond the generation of A{beta} and suggest modulation of APP expression as a therapy for AD.\n\nAcknowledgmentsWe thank Dr. Tiernan T. OMalley for useful discussions and technical advice. This work was supported by grants to DMW from the National Institutes of Health (AG046275), Bright Focus, and the United States-Israel Binational Science Foundation (2013244, DMW and IS); grants to TSJ from Alzheimers Research UK and the Scottish Government (ARUK-SPG2013-1), Wellcome Trust-University of Edinburgh Institutional Strategic Support funds, and the H2020 European Research Council (ALZSYN); and to the Massachusetts Alzheimers Disease Research Center (AG05134).

neuroscience↗

bioRxiv2017

Epigenetic Reprogramming of Tissue-Specific Transcription Promotes Metastasis

Tumor metastasis is the cause of death for 90% of cancer patients, and no currently-available therapies target this multi-step process in which cancer cells spread from the local tissue of a primary tumor to distant organs where they establish secondary tumors1. Although epithelial-to-mesenchymal transition2, tumor-secreted exosomes3, epigenetic regulators as well as other genes4-8 have been implicated in metastasis, little is known about how cells adapt to and colonize new tissue environments. Here, we show that the epigenetics-mediated reprogramming of tissue-specific gene transcription in cancer cells promotes metastasis. Using colorectal cancer (CRC) as a model, we found in both clinical and cell line studies that metastatic CRC cells lose their colon-specific gene transcription program and gain a liver-specific gene transcription program as they metastasize in the liver. Further, we found this transcription reprogramming is driven by a reshaped epigenetic landscape of both typical and super-enhancers. Chemical inhibition of enhancer activity disrupts the ability of cells to execute altered transcription programs and consequently inhibits metastasis. Binding motif analysis of the enhancers in liver metastatic CRC cells identified the liver-specific transcription factor FOXA2 as a key regulator, and knocking down of FOXA2 expression prevents the colonization of metastatic CRC cells in the liver of a mice xenograft model. These results, together with additional observations of similar reprogramming in several cohorts of clinical CRC tumor samples and in multiple other forms of metastatic cancers, indicate that this reprogramming may be a common feature of metastasis in multiple cancers and suggest the targeted disruption of this epigenetic reprogramming as a strategy for the development of therapies to treat metastasis, the leading cause of cancer-related mortality.

cancer biology↗

bioRxiv2017

Effects of mestranol on estrogen receptors expression in zebrafish

The estrogen receptor (ER) genes, which encode a group of important ligand-activated transcriptional factors, can modulate estrogen-target gene activities. Zebrafish (Danio rerio) have three ER receptor genes, esr1, esr2a, and esr2b. In this study, we examined the mRNA expression levels of these ER receptors after treatment with mestranol (EE3ME). Zebrafish larvae were exposed to 0.01, 0.1, 1, and 10 mg/L from 6 hours post-fertilization (hpf) and the mRNA expression levels of the ER genes were determined at 24, 48, 72 and 96 hpf. Treatment with mestranol led to a significant stimulation of esr1 mRNA expression at lower concentration and reached maximum at 72 hpf, however, the esr1 mRNA levels were reduced at higher mestranol concentration during exposure. The gene expression of esr2b was markedly decreased and the esr2a remained unaffected at all concentration in the duration. Altogether, these results suggested mestranol might cause the disruption of endocrine activities in fish by mediating ER genes expression.

pharmacology and toxicology↗

bioRxiv2017

Nanopore detection of bacterial DNA base modifications

The common bacterial base modification N6-methyladenine (m6A) is involved in many pathways related to an organisms ability to survive and interact with its environment. Recent research has shown that nanopore sequencing can detect m5C with per-read accuracy of upwards of 80% but m6A with significantly lower accuracy. Here we use a binary classifier to improve m6A classification by marking adenines as methylated or unmethylated based on differences between measured and expected current values as each adenine travels through the nanopore. We also illustrate the importance of read quality for base modification detection and compare to PacBio methylation calls. With recent demonstrations of nanopore sequencing in Antarctica and onboard the International Space Station, the ability to reliably characterize m6A presents an opportunity to further examine the role of methylation in bacterial adaptation to extreme or very remote environments.

genomics↗

bioRxiv2017

Altered allostatic regulation of wakefulness and slow-wave-sleep spectral quality in mice with hypocretin (orexin) receptor 1 inactivation in noradrenergic cells

Noradrenaline (NA) and hypocretins/orexins (HCRT), and their receptors, dynamically modulate the circuits that configure behavioral states, and their associated oscillatory activities. Salient stimuli activate spiking of locus coeruleus noradrenergic (NALC) cells, inducing NA release and brain-wide noradrenergic signalling, thus resetting network activity, and mediating an orienting response. Hypothalamic HCRT neurons provide one of the densest input to NALC cells. To functionally address the HCRT-to-NA connection, we selectively disrupted the Hcrtr1 gene in NA neurons, and analyzed resulting (Hcrtr1Dbh-CKO) mice, and their control littermates electrocortical response in several contexts of enhanced arousal. Under enforced wakefulness (EW), or after cage change (CC), Hcrtr1Dbh-CKO mice exhibited a weakened ability to lower infra-{theta} frequencies (1-7 Hz), and mount a robust, narrow-bandwidth, high-frequency {theta} rhythm (~8.5 Hz). A fast-{gamma} (55-80 Hz) response, whose dynamics closely parallelled {theta}, also diminished, while {beta}/slow-{gamma} activity (15-45 Hz) increased. Furthermore, EW-associated locomotion was lower. Surprisingly, nestbuilding-associated wakefulness, inversely, featured enhanced {theta} and fast-{gamma} activities. Thus HCRT-to-NA signalling may fine-tune arousal, up in alarming conditions, and down during self-motivated, goal-driven behaviors. Lastly, slow-wave-sleep following EW and CC, but not nestbuilding, was severely deficient in slow-{delta} waves (0.75-2.25 Hz), suggesting that HCRT-to-NA signalling regulates the slow-{delta} rebound characterizing sleep after stress-associated arousal.

neuroscience↗

bioRxiv2017

Aligning single-cell developmental and reprogramming trajectories identifies molecular determinants of reprogramming outcome

Cellular reprogramming through manipulation of defined factors holds great promise for large-scale production of cell types needed for use in therapy, as well as for expanding our understanding of the general principles of gene regulation. MYOD-mediated myogenic reprogramming, which converts many cell types into contractile myotubes, remains one of the best characterized model system for direct conversion by defined factors. However, why MYOD can efficiently convert some cell types into myotubes but not others remains poorly understood. Here, we analyze MYOD-mediated reprogramming of human fibroblasts at pseudotemporal resolution using single-cell RNA-Seq. Successfully reprogrammed cells navigate a trajectory with two branches that correspond to two barriers to reprogramming, with cells that select incorrect branches terminating at aberrant or incomplete reprogramming outcomes. Differential analysis of the major branch points alongside alignment of the successful reprogramming path to a primary myoblast trajectory revealed Insulin and BMP signaling as crucial molecular determinants of an individual cells reprogramming outcome, that when appropriately modulated, increased efficiency more than five-fold. Our single-cell analysis reveals that MYOD is sufficient to reprogram cells only when the extracellular milieu is favorable, supporting MYOD with upstream signaling pathways that drive normal myogenesis in development.

genomics↗

bioRxiv2017

Antibiotic resistance genes in agriculture and urban influenced watersheds in southwestern British Columbia

BackgroundThe dissemination of antibiotic resistance genes (ARGs) from anthropogenic activities into the environment poses an emerging public health threat. Water constitutes a major vehicle for transport of both biological material and chemical substances. The present study focused on putative antibiotic resistance and integrase genes present in the microbiome of agricultural, urban influenced and protected watersheds in southwestern British Columbia, Canada. A metagenomics approach and high throughput quantitative PCR (HT qPCR) were used to screen for elements of resistance including ARGs and integron-associated integrase genes (intI). Sequencing of bacterial genomic DNA was used to characterize the resistome of microbial communities present in watersheds over a one-year period.\n\nResultsData mining using CARD and Integrall databases enabled the identification of putative antibiotic resistance genes present in watershed samples. Antibiotic resistance genes presence in samples from various watershed locations was low relative to the microbial population (<1 %). Analysis of the metagenomic sequences detected a total of 78 ARGs and intI1 across all watershed locations. The relative abundance and richness of antibiotic resistance genes was found to be highest in agriculture impacted watersheds compared to protected and urban watersheds. Gene copy numbers (GCNs) from a subset of 21 different elements of antibiotic resistance were further estimated using HT qPCR. Most GCNs of ARGs were found to be variable over time. A downstream transport pattern was observed in the impacted watersheds (urban and agricultural) during dry months. Urban and agriculture impacted sites had a higher GCNs of ARGs compared to protected sites. Similar to other reports, this study found a strong association between intI1 and ARGs (e.g., sul1), an association which may be used as a proxy for anthropogenic activities. Chemical analysis of water samples for three major groups of antibiotics was negative. However, the high richness and GCNs of ARGs in impacted sites suggest effects of effluents on microbial communities are occurring even at low concentrations of antimicrobials in the water column.\n\nConclusionAntibiotic resistance and integrase genes in a year-long metagenomic study showed that ARGs were driven mainly by environmental factors from anthropogenized sites in agriculture and urban watersheds. Environmental factors accounted for almost 40% of the variability observed in watershed locations.

microbiology↗

bioRxiv2017

Structural basis of Mycobacterium tuberculosis transcription and transcription inhibition

One Sentence SummaryStructures of Mycobacterium tuberculosis RNA polymerase reveal taxon-specific properties and binding sites of known and new antituberculosis agents\n\nAbstractMycobacterium tuberculosis (Mtb) is the causative agent of tuberculosis, which kills 1.8 million annually. Mtb RNA polymerase (RNAP) is the target of the first-line antituberculosis drug rifampin (Rif). We report crystal structures of Mtb RNAP, alone and in complex with Rif. The results identify an Mtb-specific structural module of Mtb RNAP and establish that Rif functions by a steric-occlusion mechanism that prevents extension of RNA. We also report novel non-Rif-related compounds-N-aroyl-N-aryl-phenylalaninamides (AAPs)-that potently and selectively inhibit Mtb RNAP and Mtb growth, and we report crystal structures of Mtb RNAP in complex with AAPs. AAPs bind to a different site on Mtb RNAP than Rif, exhibit no cross-resistance with Rif, function additively when co-administered with Rif, and suppress resistance emergence when co-administered with Rif.

molecular biology↗

bioRxiv2016

Genetic overlap between in-scanner head motion and the default network connectivity

The association between in-scanner head motion and intrinsic functional connectivity (iFC) may confound explanations for individual differences in functional connectomics. However, the etiology of the correlation between head motion and iFC has not been established. This study aimed to investigate genetic and environmental contributions on the association between head motion and iFC using a twin dataset (175 same-sex twin pairs, aged 14-23 years, 48% females). After establishing that both head motion and default network iFC are moderately heritable, we found large genetic correlations (-0.52 to -0.73) between head motion and the default network iFCs. Common genes can explain 48% - 61% of the negative phenotypic correlation between the two phenotypes. These results advance our understanding of the relationship between head motion and iFC, and may have profound implications for interpreting individual differences in default network connectivity in clinical research and brain-behavior association.

neuroscience↗

bioRxiv2016

Combining inferred regulatory and reconstructed metabolic networks enhances phenotype prediction in yeast

Gene regulatory and metabolic network models have been used successfully in many organisms, but inherent differences between them make networks difficult to integrate. Probabilistic Regulation Of Metabolism (PROM) provides a partial solution, but it does not incorporate network inference and underperforms in eukaryotes. We present an Integrated Deduced REgulation And Metabolism (IDREAM) method that combines statistically inferred Environment and Gene Regulatory Influence Network (EGRIN) models with the PROM framework to create enhanced metabolic-regulatory network models. We used IDREAM to predict phenotypes and genetic interactions between transcription factors and genes encoding metabolic activities in the eukaryote, Saccharomyces cerevisiae. IDREAM models contain many fewer interactions than PROM and yet produce significantly more accurate growth predictions. IDREAM consistently outperformed PROM using any of three popular yeast metabolic models and across three experimental growth conditions. Importantly, IDREAMs enhanced accuracy makes it possible to identify subtle synthetic growth defects. With experimental validation, these novel genetic interactions involving the pyruvate dehydrogenase complex suggested a new role for fatty acid-responsive factor Oaf1 in regulating acetyl-CoA production in glucose grown cells.\n\nAuthor SummaryThe integration of gene regulatory and metabolic network models is an important goal in computational biology, in order to develop methods that can identify the underlying mechanistic links in biological networks and advance metabolic engineering techniques. In this paper, we develop a framework called Integrated Deduced REgulation And Metabolism (IDREAM) that can improve our ability to predict phenotypes of microorganisms, and particularly it can address the challenges in evaluating phenotypic consequence of perturbing transcriptional regulation of metabolism in a eukaryotic cell. We compare the predictive performance of an IDREAM S. cerevisiae model with a PROM model using a TRN available from the YEASTRACT database. IDREAM outperforms PROM using any of three popular yeast metabolic models and across three experimental growth conditions, making it possible to identify subtle synthetic growth defects, and a new role for Oaf1 in the regulation of acetyl-CoA biosynthesis.

systems biology↗

bioRxiv2016

A Deep Boosting Based Approach for Capturing the Sequence Binding Preferences of RNA-Binding Proteins from High-Throughput CLIP-Seq Data

Characterizing the binding behaviors of RNA-binding proteins (RBPs) is important for understanding their functional roles in gene expression regulation. However, current high-throughput experimental methods for identifying RBP targets, such as CLIP-seq and RNAcompete, usually suffer from the false positive and false negative issues. Here, we develop a deep boosting based machine learning approach, called DeBooster, to accurately model the binding sequence preferences and identify the corresponding binding targets of RBPs from CLIP-seq data. Comprehensive validation tests have shown that DeBooster can outperform other state-of-the-art approaches in predicting RBP targets and recover false negatives that are common in current CLIP-seq data. In addition, we have demonstrated several new potential applications of DeBooster in understanding the regulatory functions of RBPs, including the binding effects of the RNA helicase MOV10 on mRNA degradation, the influence of different binding behaviors of the ADAR proteins on RNA editing, as well as the antagonizing effect of RBP binding on miRNA repression. Moreover, DeBooster may provide an effective index to investigate the effect of pathogenic mutations in RBP binding sites, especially those related to splicing events. We expect that DeBooster will be widely applied to analyze large-scale CLIP-seq experimental data and can provide a practically useful tool for novel biological discoveries in understanding the regulatory mechanisms of RBPs. The scource code of DeBooster can be downloaded from http://github.com/dongfanghong/deepboost.

bioinformatics↗