Biology subjects

Ren, X.

Publications and source records attributed to Ren, X..

At least 163 records · Page 9Linked to original sources

bioRxiv2019

Direct Comparative Analysis of 10X Genomics Chromium and Smart-seq2

Single cell RNA sequencing (scRNA-seq) is widely used for profiling transcriptomes of individual cells. The droplet-based 10X Genomics Chromium (10X) approach and the plate-based Smart-seq2 full-length method are two frequently-used scRNA-seq platforms, yet there are only a few thorough and systematic comparisons of their advantages and limitations. Here, by directly comparing the scRNA-seq data by the two platforms from the same samples of CD45-cells, we systematically evaluated their features using a wide spectrum of analysis. Smart-seq2 detected more genes in a cell, especially low abundance transcripts as well as alternatively spliced transcripts, but captured higher proportion of mitochondrial genes. The composite of Smart-seq2 data also resembled bulk RNA-seq data better. For 10X-based data, we observed higher noise for mRNA in the low expression level. Despite the poly(A) enrichment, approximately 10-30% of all detected transcripts by both platforms were from non-coding genes, with lncRNA accounting for a higher proportion in 10X. 10X-based data displayed more severe dropout problem, especially for genes with lower expression levels. However, 10X-data can better detect rare cell types given its ability to cover a large number of cells. In addition, each platform detected different sets of differentially expressed genes between cell clusters, indicating the complementary nature of these technologies. Our comprehensive benchmark analysis offers the basis for selecting the optimal scRNA-seq strategy based on the objectives of each study.

bioinformatics↗

bioRxiv2019

Negative Binomial Additive Model for RNA-Seq Data Analysis

High-throughput sequencing experiments followed by differential expression analysis is a widely used approach for detecting genomic biomarkers. A fundamental step in differential expression analysis is to model the association between gene counts and co-variates of interest. Existing models assume linear effect of covariates, which is restrictive and may not be sufficient for some phenotypes. In this paper, we introduce NBAMSeq, a flexible statistical model based on the generalized additive model and allows for information sharing across genes in variance estimation. Specifically, we model the logarithm of mean gene counts as sums of smooth functions with the smoothing parameters and coefficients estimated simultaneously within a nested iterative method. The variance is estimated by the Bayesian shrinkage approach to fully exploit the information across all genes. Based on extensive simulation and case studies of RNA-Seq data, we show that NBAMSeq offers improved performance in detecting nonlinear effect and maintains equivalent performance in detecting linear effect compared to existing methods. Our proposed NBAMSeq is available for download at https://github.com/reese3928/NBAMSeq and in submission to Bioconductor repository.

bioinformatics↗

bioRxiv2018

Genome wide screen reveals a specific interaction between autosome and X that is essential for hybrid male sterility

Hybrid male progeny from interspecies cross are more prone to sterility or inviability than hybrid female progeny, and the male sterility and inviability often demonstrate a parent-of-origin asymmetry. However, the underlying mechanism of asymmetric sterility or inviability remains elusive. We previously established a genome-wide hybrid incompatibility (HI) landscape between Caenorhabditis briggsae and C. nigoni by phenotyping a large collection of C. nigoni strains each carrying a C. briggsae introgression. In this study, we investigate the genetic mechanism of asymmetric sterility and inviability in both hybrid male and female progeny between the two species. Specifically, we performed reciprocal crosses between C. briggsae and different C. nigoni strains that each carries a GFP-labeled C. briggsae genomic fragment referred to as introgression, and scored the HI phenotypes in the F1 progeny. The aggregated introgressions cover 94.6% of the C. briggsae genome, including 100% of the X chromosome. Surprisingly, we observed that two C. briggsae X fragments that produce C. nigoni male sterility as an introgression rescued hybrid F1 sterility in males fathered by C. briggsae, indicating that at least two separate X-autosome interactions are involved in the hybrid male sterility. In addition, we identified another two C. briggsae genomic intervals on the Chromosome II or IV, respectively, which can rescue the inviability, but not the sterility, of hybrid F1 males fathered by C. nigoni, suggesting the involvement of differential epistatic interactions in the asymmetric hybrid male fertility and inviability. Importantly, backcrossing of the rescued sterile males with C. nigoni led to isolation of a 1.1-Mb genomic interval that specifically interacts with an X-linked introgression, which is essential for hybrid male fertility. We further identified three C. briggsae genomic intervals on the Chromosome I, II and III, respectively that produce inviability in all F1 progeny dependent or independent of the parent-of-origin. Taken together, we identified multiple independent interacting loci that are responsible for asymmetric hybrid male and female sterility and inviability, which provides important insights into the asymmetric HI and lays a foundation for their molecular characterization.\n\nAuthor summaryIt is common that closely related species can mate with each other, but their hybrid progeny are often sterile or inviable, especially in the male progeny. The mechanism underlying the asymmetric sterility or inviability remains poorly understood. We previously addressed this question between two nematodes, Caenorhabditis briggsae and C. nigoni, by systematic substitution of various parts of the C. nigoni genome with its C. briggsaes equivalent followed by phenotypic examination. Here we investigate the genetic mechanism of the asymmetric sterility and inviability in the hybrid F1 male and female progeny between the two species. We achieved this through crossing a cohort of C. nigoni strains each carrying a substitution with C. briggsae, which led to differential homozygosity of the C. briggsae substitution in the hybrid progeny. The aggregated substitutions cover 94.6% of the C. briggsae genome, including 100% of the X chromosome. Surprisingly, we identified two C. briggsae X fragments that produced C. nigoni male sterility as a substitution but rescued hybrid F1 sterility in males fathered by C. briggsae, indicating that at least two separate X-autosome interactions are involved in the hybrid male sterility. In addition, we identified multiple genomic intervals on C. briggsae autosomes that can rescue the inviability, but not the sterility, of hybrid F1 males fathered by C. nigoni. Importantly, we isolated a 1.1-Mb genomic interval that specifically interacts with an X-linked introgression, which is essential for hybrid male fertility. We further identified three C. briggsae genomic intervals on the Chromosome I, II and III, respectively that produce inviability in all F1 progeny dependent or independent of the parent-of-origin. The identified interacting loci lays a foundation for their molecular characterization.

evolutionary biology↗

bioRxiv2018

cis-Regulatory Chromatin Contacts in Neural Cells Reveal Contributions of Genetic Variants to Complex Neurological Disorders

Mutations in gene regulatory elements have been associated with a wide range of complex neurological disorders. However, due to their inherent cell type-specificity and difficulties in characterizing their regulatory targets, our ability to identify causal genetic variants has remained limited. To address these constraints, we perform integrative analysis of chromatin interactions using promoter capture Hi-C (pcHi-C), open chromatin regions using ATAC-seq, and transcriptomes using RNA-seq in four functionally distinct neural cell types: iPSC-induced excitatory neurons and lower motor neurons, iPSC-derived hippocampal dentate gyrus (DG)-like neurons, and primary astrocytes. We identify hundreds of thousands of long-range cis interactions between promoters and distal promoter-interacting regions (PIRs), enabling us to link regulatory elements to their target genes and reveal putative pathways that are dysregulated in disease. We validate several novel PIRs using CRISPR techniques in human excitatory neurons, demonstrating that CDK5RAP3, STRAP, and DRD2 are transcriptionally regulated by physically linked enhancers. Finally, we show that physical chromatin interactions mediate genetic interactions in autism spectrum disorder (ASD). Our study illustrates how characterizing the 3D epigenome elucidates novel regulatory relationships in the central nervous system (CNS), shedding light on previously unknown functions for noncoding variants in complex neurological disorders.

genomics↗

bioRxiv2018

Modular, part-based control of gene expression response time using protein degradation tags

A fundamental principle of cellular signal processing is the encoding of information within the temporal dynamics of regulatory circuits. If synthetic circuits are to achieve the versatility and effectiveness of naturally-occurring circuits, it is necessary to develop simple, effective methods for the control of the dynamical properties of genetic circuits. However, current approaches to dynamical control often require extensive rewiring of circuit architecture, which hinders their implementation in a variety of systems. Therefore, it is essential that simple, modular, genetic parts-based frameworks are created to control the dynamical properties of circuits. Here we address this need by implementing a modular, genetic parts-based system which tunes the response time of a genes expression by tuning its degradation rate via the application of protein degradation tags with various affinities to their protease. This system provides a simple, easily- applicable framework for controlling the temporal aspects of genetic circuit behavior.

bioengineering↗

bioRxiv2018

Cooperation Enhances Robustness of Coexistence in Spatially Structured Consortia

Designing synthetic microbial consortia is an emerging area in synthetic biology and a major goal is to realize stable and robust coexistence of multiple species. Co-operation and competition are fundamental intra/interspecies interactions that shape population level behaviors, yet it is not well-understood how these interactions affect the stability and robustness of coexistence. In this paper, we show that communities with cooperative interactions are more robust to population disturbance, e.g., depletion by antibiotics, by forming intermixed spatial patterns. Meanwhile, competition leads to population spatial heterogeneity and more fragile coexistence in communities. Using reaction-diffusion and nonlocal PDE models and simulations of a two-species E. coli consortium, we demonstrate that cooperation is more beneficial than competition in maintaining coexistence in spatially structured consortia, but not in well-mixed environments. This also suggests a trade-off between constructing heterogeneous communities with localized functions and maintaining robust coexistence. The results provide general strategies for engineering spatially structured consortia by designing interspecies interactions and suggest the importance of cooperation for biodiversity in microbial community.

synthetic biology↗

bioRxiv2018

Polycomb Cbx2 Condensates Assemble through Phase Separation

Polycomb group (PcG) proteins are master regulators of development and differentiation. Mutation and dysregulation of PcG genes cause developmental defects and cancer. PcG proteins form condensates in the nucleus of cells and these condensates are the physical sites of PcG-targeted gene silencing. However, the physiochemical principles underlying the PcG condensate formation remain unknown. Here we show that Polycomb repressive complex 1 (PRC1) protein Cbx2, one member of the Cbx family proteins, contains a long stretch of intrinsically disordered region (IDR). Cbx2 undergoes phase separation to form condensates. Cbx2 condensates exhibit liquid-like properties and can concentrate DNA and nucleosomes. We demonstrate that the conserved residues within the IDR promote the condensate formation in vitro and in vivo. We further indicate that H3K27me3 has minimal effects on the Cbx2 condensate formation while depletion of core PRC1 subunits facilitates the condensate formation. Thus, our results reveal that PcG condensates assemble through liquid-liquid phase separation (LLPS) and suggest that PcG-bound chromatin is in part organized through phase-separated condensates.

biochemistry↗

bioRxiv2018

The Mediator CDK8-Cyclin C complex modulates vein patterning in Drosophila by stimulating Mad-dependent transcription

Dysregulations of CDK8 and its regulatory partner CycC, two subunits of the conserved Mediator complex, have been linked to diverse human diseases such as cancer, thus it is essential to understand the regulatory network mobilizing the CDK8-CycC complex in both normal development and tumorigenesis. To identify upstream regulators or downstream effectors of CDK8, we performed a dominant modifier genetic screen in Drosophila based on the defects in vein patterning caused by specific depletion or overexpression of CDK8 or CycC in wing imaginal discs. We identified 26 genomic loci whose haploinsufficiency can modify these CDK8-specific phenotypes. Further analysis of two deficiency lines and mutant alleles led us to identify interactions between CDK8-CycC and the components of the Decapentaplegic (Dpp, the Drosophila homolog of TGF{beta}) signaling pathway. We observed that CDK8-CycC positively regulates transcription activated by Mad (Mothers against dpp), the primary transcription factor downstream of the Dpp/TGF{beta} signaling pathway. CDK8 can directly interact with Mad in vitro through the linker region between the DNA-binding MH1 (Mad homology 1) domain and the carboxy terminal MH2 transactivation domain. Besides CDK8 and CycC, further analyses of other subunits of the Mediator complex have revealed six additional Mediator subunits that are required for Mad-dependent transcription in the wing discs, including Med12, Med13, Med15, Med23, Med24, and Med31. Furthermore, CDK9 and Yorkie also positively regulate Mad-dependent gene expression in vivo. These results suggest that the Mediator complex may coordinate with other transcription cofactors in regulating Mad-dependent transcription during the wing vein patterning in Drosophila.\n\nSignificanceCDK8 is a conserved subunit of the transcription cofactor Mediator complex that bridges transcription factors with RNA Polymerase II in eukaryotes. Here we explore the role of CDK8 in Drosophila by performing a dominant modifier genetic screen based on vein patterning defects caused by alteration of CDK8-specific activities. We show that components of the Dpp/TGF{beta} signaling pathway genetically interact with CDK8; CDK8 positively regulates gene expression activated by Mad, the key transcription factor downstream of Dpp/TGF{beta} signaling, by directly interacting with the linker region of Mad protein. Given the fundamental roles of Dpp/TGF{beta} signaling in regulating development and its misregulation in various diseases, understanding how Mad/Smad interacts the Mediator complex may have broad implications in understanding and treating these diseases.

developmental biology↗

bioRxiv2018

SSCC: a computational framework for rapid and accurate clustering of large-scale single cell RNA-seq data

Clustering is a prevalent analytical means to analyze single cell RNA sequencing data but the rapidly expanding data volume can make this process computational challenging. New methods for both accurate and efficient clustering are of pressing needs. Here we proposed a new clustering framework based on random projection and feature construction for large scale single-cell RNA sequencing data, which greatly improves clustering accuracy, robustness and computational efficacy for various state-of-the-art algorithms benchmarked on multiple real datasets. On a dataset with 68,578 human blood cells, our method reached 20% improvements for clustering accuracy and 50-fold acceleration but only consumed 66% memory usage compared to the widely-used software package SC3. Compared to k-means, the accuracy improvement can reach 3-fold depending on the concrete dataset. An R implementation of the framework is available from https://github.com/Japrin/sscClust.

bioinformatics↗

bioRxiv2018

Development and Validation of a Method for Human Papillomavirus Genotyping Based on Molecular Beacon Probes

We describe a new assay system for the genotyping of human papillomavirus (HPV) based on linear-after-the-exponential-PCR and melting curve analysis. This system can detect and identify the 23 most common HPV strains (types 6, 11, 16, 18, 31, 33, 35, 39,42, 45, 51, 52, 53, 56, 58, 59, 66, 68, 70, 73, 81, 82, and 83) in two sealed reaction tubes within 2 h. The sensitivity and specificity of this new system was validated using cloned HPV DNA and clinical samples. The detection limit was 5-500 copies/reaction depending on the genotype, and no cross-reactivity was observed with any other low-risk HPV or pathogen that was commonly found in the female genital tract. When compared with the HPV GenoArray test kit, the testing of 1104 clinical samples produced a good overall agreement between the two methods of 98.37% (95% CI: 97.44%-98.97%) and a kappa value of 0.954. Thus, this new HPV genotyping assay system represents a simple, rapid, universally applicable, sensitive, and highly specific detection methodology that should be useful for cervical lesion screening and, thus, is potentially of great value in future clinical applications.

molecular biology↗

bioRxiv2018

Discovery of New CDK8 ligands with a Novel Virtual Drug Screening Tool

Selective inhibition of CDK8 could be a promising strategy for reducing mitogenic signals in cancer cells with reduced toxic effects on normal cells. As compared with type I ligands, binding of a type II compound often achieves longer residence time. We developed a novel virtual drug screening package which takes advantage of two energy evaluation methods: Superposition and Single-Point Energy Evaluation, and VM2 free energy calculation, and applied it to the discovery of new CDK8 type II ligands. In this research we analyzed binding thermodynamics of 11 published CDK8 type II ligands, and extracted the key binding information to assist virtual drug screening for new ligands. The free energy and MD calculations on the reference CDK8-ligand complexes revealed the important factors in the binding. The urea moiety was found to be the critical structural contributor of the reference ligands. Starting with the urea moiety we implemented virtual drug screening and singled out three compounds for bio-assay testing. The ranking from the experimental result for the three compounds is completely consistent with the predicted rankings by both energy evaluation methods. A potent drug-like compound was discovered to have a Kd value of 42.5 nM with CDK8, which is comparable to the most potent reference ligands and provided a good starting point to design and synthesize a series of highly selective and potent CDK8 ligands. Therefore, our novel virtual drug screening package is accurate and efficient enough to be used in drug design projects. We believe this work has significant impact to the field of drug discovery.

bioinformatics↗

bioRxiv2018

The lysine demethylase dKDM2 is non-essential for viability, but regulates circadian rhythms in Drosophila

Post-translational modification of histones, such as histone methylation controlled by specific methyltransferases and demethylases, play critical roles in modulating chromatin dynamics and transcription in eukaryotes. Misregulation of histone methylation can lead to aberrant gene expression, thereby contributing to abnormal development and diseases such as cancer. As such, the mammalian lysine-specific demethylase 2 (KDM2) homologs, KDM2A and KDM2B, are either oncogenic or tumor suppressive, depending on specific pathological contexts. However, the role of KDM2 proteins during development in the whole organisms remains poorly understood. Unlike vertebrates, Drosophila has only one KDM2 homolog (dKDM2), but its functions in vivo remain elusive due to the complexities of the existing mutant alleles. To address this problem, we have generated two dKdm2 null alleles using the CRISPR/Cas9 technique. These dKdm2 homozygous mutants are fully viable and fertile, with no developmental defects observed under laboratory conditions. However, the dKdm2 null mutant adults display defects in circadian rhythms. Most of the dKdm2 mutants become arrhythmic under constant darkness, while the circadian period of the rhythmic mutant flies is approximately one hour shorter than the control. Interestingly, opposite defects are observed when dKDM2 is overexpressed in circadian pacemaker neurons. Taken together, these results demonstrate that dKdm2 is not essential for viability; instead, dKDM2 protein plays important roles in regulating circadian rhythms in Drosophila. Further analyses of the molecular mechanisms of how dKDM2 and its orthologs in vertebrates regulate circadian rhythms will advance our understanding of the epigenetic regulations of circadian clocks.

developmental biology↗

bioRxiv2018

Role of communication network topology in controlling microbial population in consortia

Engineering microbial consortia is an important new frontier for synthetic biology given its efficiency in performing complex tasks and endurance to environmental uncertainty. Most synthetic circuits regulate populational behaviors via cell-to-cell communications, which are affected by spatially heterogenous environments. Therefore, it is important to understand the limits on controlling system dynamics that are determined by interconnections among cell agents and provide a control strategy for engineering consortia. Here, we build a network model for a fractional population control circuit in two-strain consortia, and characterize the cell-to-cell communication network by topological properties, such as symmetry, locality and connectivity. Using linear network control theory, we relate the network topology to system outputs tracking performance. We analytically and numerically demonstrate that the minimum network control energy for accurate tracking depends on locality difference between two cell populations spatial distributions and how strongly the controller node contributes to communication strength. To realize a robust consortia, we can manipulate the communication network topology and construct strongly connected consortia by altering chemicals in environments. Our results ground the expected cell population dynamics in its spatially organized communication network, and inspire directions in cooperative control in microbial consortia.

synthetic biology↗

bioRxiv2018

Establishment of signaling interactions with cellular resolution for every cell cycle of embryogenesis

Intercellular signaling interaction plays a key role in breaking fate symmetry during animal development. Identification of the signaling interaction at cellular resolution is technically challenging, especially in a developing embryo. Here we develop a platform that allows automated inference and validation of signaling interaction for every cell cycle of C. elegans embryogenesis. This is achieved by generation of a systems-level cell contact map that consists of 1,114 highly confident intercellular contacts by modeling analysis and is validated through cell membrane labeling coupled with cell lineage analysis. We apply the map to identify cell pairs between which a Notch signaling interaction takes place. By generating expression patterns for two ligands and two receptors of Notch signaling pathway with cellular resolution using automated expression profiling technique, we are able to refine existing and identify novel Notch interactions during C. elegans embryogenesis. Targeted cell ablation followed by cell lineage analysis demonstrates the roles of signaling interactions over cell division in breaking fate symmetry. We finally develop a website that allows online access to the cell-cell contact map for mapping of other signaling interaction in the community. The platform can be adapted to establish cellular interaction from any other signaling pathways.

cell biology↗

bioRxiv2018

HIV-1 Nefs are cargo-sensitive AP-1 trimerization switches in tetherin and MHC-I downregulation

The HIV accessory protein Nef counteracts immune defenses by subverting coated vesicle pathways. The 3.7 [A] cryo-EM structure of a closed trimer of the clathrin adaptor AP-1, the small GTPase Arf1, HIV-1 Nef, and the cytosolic tail of the restriction factor tetherin suggested a mechanism for inactivating tetherin by Golgi retention. The 4.3 [A] structure of a mutant Nef-induced dimer of AP-1 showed how the closed trimer is regulated by the dileucine loop of Nef. HDX-MS and mutational analysis were used to show how cargo dynamics leads to alternative Arf1 trimerization, directing Nef targets to be either retained at the trans-Golgi or sorted to lysosomes. Phosphorylation of the NL4-3 M-Nef was shown to regulate AP-1 trimerization, explaining how O-Nefs lacking this phosphosite counteract tetherin but most M-Nefs do not. These observations show how the higher-order organization of a vesicular coat can be allosterically modulated to direct cargoes to distinct fates.

molecular biology↗

bioRxiv2018

ATP-dependent force generation and membrane scission by ESCRT-III and Vps4

The ESCRTs catalyze reverse-topology scission from the inner face of membrane necks in HIV budding, multivesicular endosome biogenesis, cytokinesis, and other pathways. We encapsulated a minimal ESCRT module consisting of ESCRT-III subunits Snf7, Vps24, and Vps2, and the AAA+ ATPase Vps4 such that membrane nanotubes reflecting the correct topology of scission could be pulled from giant vesicles. Upon ATP release by photo-uncaging, this system was capable of generating forces within the nanotubes in a manner dependent upon Vps4 catalytic activity, Vps4 coupling to the ESCRT-III proteins, and membrane insertion by Snf7. At physiological concentrations, single scission events were observed that correlated with forces of ~6 pN, verifying predictions that ESCRTs are capable of exerting forces on membranes. Imaging of scission with subsecond resolution revealed Snf7 puncta at the sites of membrane cutting, directly verifying longstanding predictions for the ESCRT scission mechanism.\n\nOne Sentence SummaryESCRT-III and Vps4 were reconstituted from within the interior of nanotubes pulled from giant vesicles, revealing that this machinery couples ATP-dependent force production for membrane scission.

biophysics↗

bioRxiv2018

Next generation CRISPR/Cas9 transcriptional activation in Drosophila using flySAM

CRISPR/Cas9-based transcriptional activation (CRISPRa) has recently emerged as a powerful and scalable technique for systematic over-expression genetic analysis in Drosophila melanogaster. We present flySAM, a potent new tool for in vivo CRISPRa, which offers a major improvement over existing strategies in terms of effectiveness, scalability, and ease-of-use. flySAM outperforms existing in vivo CRISPRa strategies, and approximates phenotypes obtained using traditional Gal4-UAS over-expression. Further, because flySAM typically only requires a single sgRNA, it dramatically improves scalability. We use flySAM to demonstrate multiplexed CRISPRa, which has not been previously shown in vivo. In addition, we have simplified the experimental usage of flySAM by creating a single vector encoding both the UAS:Cas9-activator and the sgRNA, allowing for inducible CRISPRa in a single genetic cross. flySAM will thus replace previous CRISPRa strategies as the basis of our growing genome-wide transgenic over-expression resource, TRiP-OE.

genetics↗

bioRxiv2018

Cross-type Biomedical Named Entity Recognition with Deep Multi-Task Learning

MotivationState-of-the-art biomedical named entity recognition (BioNER) systems often require handcrafted features specific to each entity type, such as genes, chemicals and diseases. Although recent studies explored using neural network models for BioNER to free experts from manual feature engineering, the performance remains limited by the available training data for each entity type.\n\nResultsWe propose a multi-task learning framework for BioNER to collectively use the training data of different types of entities and improve the performance on each of them. In experiments on 15 benchmark BioNER datasets, our multi-task model achieves substantially better performance compared with state-of-the-art BioNER systems and baseline neural sequence labeling models. Further analysis shows that the large performance gains come from sharing character- and word-level information among relevant biomedical entities across differently labeled corpora.\n\nAvailabilityOur source code is available at https://github.com/yuzhimanhua/lm-lstm-crf.\n\nContactxwang174@illinois.edu, xiangren@usc.edu.

bioinformatics↗