Biology subjects

Ma, Y.

Publications and source records attributed to Ma, Y..

At least 19 recordsLinked to original sources

bioRxiv2018

High-resolution structural genomics reveals new therapeutic vulnerabilities in glioblastoma

We investigated the role of 3D genome architecture in instructing functional properties of glioblastoma stem cells (GSCs) by generating the highest-resolution 3D genome maps to-date for this cancer. Integration of DNA contact maps with chromatin and transcriptional profiles identified specific mechanisms of gene regulation, including individual physical interactions between regulatory regions and their target genes. Residing in structurally conserved regions in GSCs was CD276, a gene known to play a role in immuno-modulation. We show that, unexpectedly, CD276 is part of a stemness network in GSCs and can be targeted with an antibody-drug conjugate to curb self-renewal, a key stemness property. Our results demonstrate that integrated structural genomics datasets can be employed to rationally identify therapeutic vulnerabilities in self-renewing cells.\n\nSIGNIFICANCEIn adult GBM, GSCs act as therapy-resistant reservoirs to nucleate tumor recurrence. New therapeutic approaches that target these cell populations hold the potential of significantly improving patient care and overall prognosis for this always-lethal cancer. Our work describes new links between 3D genome architecture and stemness properties in GSCs. In particular, through integration of multiple genomics and structural genomics datasets, we found an unexpected connection between immune-related genes and self-renewal programs in GBM. Among these, we show that targeting CD276 with knockdown strategies or specific antibody-drug conjugates achieve suppression of self-renewal. Strategies to target CD276+ cells are currently in clinical trials for solid tumors. Our results indicate that CD276-targeting agents could be deployed in GBM to specifically target GSC populations.\n\nHIGHLIGHTSO_LIWe generated high (sub-5 kb) resolution Hi-C maps for stem-like cells from GBM patients.\nC_LIO_LIIntegration of Hi-C and genomics datasets dissects mechanisms of gene regulation.\nC_LIO_LI3D genomes poise immune-related genes, including CD276, for expression.\nC_LIO_LITargeting CD276 curbs self-renewal properties of GBM cells.\nC_LI

cancer biology↗

bioRxiv2018

Subclonal architecture, evolutionary trajectories and patterns of inheritance of germline variants in pediatric glioblastoma

Pediatric glioblastoma (pGBM) is a lethal cancer with no effective therapies. Intratumoral genetic heterogeneity and mode of tumor evolution have not been systematically addressed for this cancer. Whole-genome sequencing of germline-tumor pairs showed that pGBM is characterized by intratumoral genetic heterogeneity and consequent subclonal architecture. We found that pGBM undergoes extreme evolutionary trajectories, with primary and recurrent tumors having different subclonal compositions. Analysis of variant allele frequencies supported a model of tumor growth involving slow-cycling cancer stem cells that give rise to fast-proliferating progenitor-like cells and to non-dividing cells. pGBM patients germlines had subclonal structural variants, some of which underwent dynamic frequency fluctuations during tumor evolution. By sequencing germlines of mother-father-patient trios, we found that inheritance of deleterious germline variants from healthy parents cooperate with de novo germline and somatic events to the tumorigenic process. Our studies therefore challenge the current notion that pGBM is a relatively homogeneous molecular entity.

cancer biology↗

bioRxiv2018

Resource: Scalable whole genome sequencing of 40,000 single cells identifies stochastic aneuploidies, genome replication states and clonal repertoires

Essential features of cancer tissue cellular heterogeneity such as negatively selected genome topologies, sub-clonal mutation patterns and genome replication states can only effectively be studied by sequencing single-cell genomes at scale and high fidelity. Using an amplification-free single-cell genome sequencing approach implemented on commodity hardware (DLP+) coupled with a cloud-based computational platform, we define a resource of 40,000 single-cell genomes characterized by their genome states, across a wide range of tissue types and conditions. We show that shallow sequencing across thousands of genomes permits reconstruction of clonal genomes to single nucleotide resolution through aggregation analysis of cells sharing higher order genome structure. From large-scale population analysis over thousands of cells, we identify rare cells exhibiting mitotic mis-segregation of whole chromosomes. We observe that tissue derived scWGS libraries exhibit lower rates of whole chromosome anueploidy than cell lines, and loss of p53 results in a shift in event type, but not overall prevalence in breast epithelium. Finally, we demonstrate that the replication states of genomes can be identified, allowing the number and proportion of replicating cells, as well as the chromosomal pattern of replication to be unambiguously identified in single-cell genome sequencing experiments. The combined annotated resource and approach provide a re-implementable large scale platform for studying lineages and tissue heterogeneity.

genomics↗

bioRxiv2018

FRMPD2: a novel GluN2A-interacting scaffold protein in synaptic excitatory transmission

The scaffold proteins FRMPD2 is localized at the basolateral membranes of polarized epithelial cells and associated with tight junction formation. But the expression and function of FRMPD2 in vivo remain unknown. Here, we found that postsynaptic FRMPD2 effectively alters the neuronal excitability by regulating NMDARs-component excitatory synaptic transmission in adult hippocampus. FRMPD2 anchors the NMDAR subunit GluN2A at the synapses without changing the total NMDAR expression. By using of Co-IP, Pull Down and SPR, the second PDZ (PDZ2) domain of FRMPD2 direct and binds to the C-terminus of GluN2A. Our study discover that a novel scaffold protein FRMPD2 regulates synaptic excitatory in a PDZ2 domain-dependent manner in adult hippocampus.

neuroscience↗

bioRxiv2018

Oxytocin promotes synchronized out-group attack during intergroup conflict in humans

Intergroup conflict contributes to human discrimination and violence, but persists because individuals make costly contributions to their groups fighting capacity. Yet how groups effectively synchronize their contributions during intergroup conflict remains poorly understood. Here we examine whether the evolutionary ancient neuropeptide oxytocin provides a neurobiological mechanism underlying group synchronization to attack or defend during real-time intergroup conflict. In a double-blind placebo-controlled study with N=480 males in Attacker-Defender intergroup conflicts, we found that oxytocin reduced attackers contributions and over time increased attackers within-group synchronization of contributions. However, rather than becoming peaceful, oxytocin enabled attackers to track rivals defense-history and synchronize their contributions into well-timed (when defenders were weak) and hence more profitable attacks. Combined, results reveal behavioral synchronization and coordinated action as critical components of successful attacks, subscribe to the possibility that oxytocin enables individuals to contribute to in-group efficiency and prosperity, even when such implies outsiders are excluded or harmed.

neuroscience↗

bioRxiv2018

The crossover function of MutSγ is activated via Cdc7-dependent stabilization of Msh4

The MutS{gamma} complex, Msh4-Msh5, binds DNA joint-molecule (JM) intermediates during homologous recombination to promote crossing over and accurate chromosome segregation at the first division of meiosis. MutS{gamma} facilitates the formation and biased resolution of crossover-specific JM intermediates called double Holliday junctions. Here we show that these activities are governed by regulated proteasomal degradation. MutS{gamma} is initially inactive for crossing over due to an N-terminal degron on Msh4 that renders it unstable. Activation of MutS{gamma} requires the Dbf4-dependent kinase, Cdc7 (DDK), which directly phosphorylates and thereby neutralizes the Msh4 degron. Phosphorylated Msh4 is chromatin bound and requires DNA strand exchange and chromosome synapsis, implying that DDK specifically targets MutS{gamma} that has already bound nascent JMs. Our study establishes regulated protein degradation as a fundamental mechanism underlying meiotic crossover control.

genetics↗

bioRxiv2018

Human cytomegalovirus RNA2.7 regulates host cell cycle and facilitates viral DNA replication by inhibiting RNA polymerase II phosphorylation

Human cytomegalovirus (HCMV) is a ubiquitous pathogen belongs to the beta herpesvirus family. RNA2.7 is a viral long non-coding RNA accounting for more than 20% of total viral transcripts at early time of infection. By construction of RNA2.7 deleted mutant and genome transcriptomic analysis, RNA2.7 is demonstrated to repress host cellular RNA polymerase II (Pol II)-dependent transcription through inhibiting the phosphorylation of RNA polymerase II (Pol II). Co-immunoprecipitation, RNA immunoprecipitation and RNA electrophoretic mobility shift assay are followed to investigate its mechnism. A 145nt-in-length fragment in RNA2.7 is identified to bind to Pol II and block the interaction between Pol II and phosphorylated cyckin-dependent kinase 9 (phospho-CDK9). By inhibiting Pol II phosphorylation, RNA2.7 decreases the transcription and expression levels of chromatin licensing and DNA replication factor 1 (Cdt1) and cell division cycle gene 6 (Cdc6). Through above way, RNA2.7 prevents the entry of cells into S phase and facilitates viral DNA replication. Our results discover the functions of HCMV RNA2.7 in regulation of Pol II phosphorylation and cell cycle control during infection.\n\nAuthor summaryHuman cytomegalovirus (HCMV) RNA2.7 is a viral lncRNA that is most abundant during infection. Here we show that a 145nt-in-length fragment in RNA2.7 binds to RNA polymerase II (Pol II) and blocks the interaction between Pol II and phosphorylated cyckin-dependent kinase 9 (phospho-CDK9). By inhibiting Pol II phosphorylation, RNA2.7 decreases the transcription and expression levels of chromatin licensing and DNA replication factor 1 (Cdt1) and cell division cycle gene 6 (Cdc6), and blocks host cells entering into S phase. RNA2.7 is confirmed to facilitate viral DNA replication through decreasing Cdt1 and Cdc6. Therefore, our results discover the functions of HCMV RNA2.7 in regulation of Pol II phosphorylation and cell cycle control during infection.

microbiology↗

bioRxiv2018

Evaluation of the antifibrotic potency by knocking down SPARC, CCR2 and SMAD3

The genes of SPARC, CCR2, and SMAD3 are implicated in orchestrating inflammation and fibrosis in scleroderma and other fibrotic disorders. Aim of the studies was to examine synergistic effect of inhibition of these genes in treating fibrosis. The peptide nanoparticles were used to deliver the siRNAs in bleomycin-induced fibrotic mice. Triple combination of siRNAs targeting on Sparc, Ccr2 and Smad3 achieved favorable anti-inflammatory and anti-fibrotic effects. Inhibition of inflammation was evidenced by reduced inflammatory cells and proinflammatory cytokines in the BALF and/or the tissues. Activation of fibroblasts was suppressed in mouse tissues in which -Sma and collagens were significantly reduced. Aberrant expression of the genes in fibroblasts, monocytes/macrophage, endothelial and epithelial cells were reinstalled after the treatment. In addition, transcriptome profiles indicated that some bleomycin-induced alterations of multiple biological pathways were recovered to varying degrees by the treatment. The results indicated that the triple combination of siRNAs systemically reinstated multiple biopathways, probably through controlling on different cell types including fibroblasts, monocytes/macrophages, endothelial cells and others. The multi-target-combined therapeutic approach examined herein may represent a novel and effective therapy for fibrosis.

molecular biology↗

bioRxiv2018

Chicken uric acid elimination via the uric acid transporters BCRP and MRP4 in the liver, kidneys, and intestines

Breast cancer resistance protein (BCRP) and multidrug resistance protein 4 (MRP4) are involved in uric acid excretion in humans and mice. Despite evidence suggesting that chicken renal proximal tubular epithelial cells participate in uric acid secretion, the roles of BCRP and MRP4 in chickens remain unclear. This study evaluated the relationship between chicken BCRP and MRP4 expression and renal function in the liver, kidneys, and intestines. Sixty 20-day-old Isa brown laying hens were randomly divided into four groups: a control group (NC) and groups provided with sulfonamide-treated drinking water (SD), a diet supplemented with fishmeal (FM), and an intraperitoneal injection of uric acid (IU). Serum uric acid, creatinine, and blood urea nitrogen (BUN) levels were significantly higher in the SD and IU groups than in the NC group. BCRP and MRP4 levels in the SD and IU groups were significantly increased in the kidneys and ileum and decreased in the liver. In the FM group, BCRP and MRP4 were significantly increased in the kidneys and slightly increased in the ileum. These results demonstrate that chicken BCRP and MRP4 are involved in renal and intestinal uric acid excretion. When renal function is impaired, serum uric acid increased and BCRP and MRP4 in the liver, kidneys, and ileum exhibit compensatory increases; when renal function is normal, serum uric acid changes have no effect on ileum BCRP and MRP4 expression. Therefore, this study may provide the references to the uric acid regulation in human.

physiology↗

bioRxiv2018

FunSPU: a versatile and adaptive multiple functional annotation-based association test of whole-genome sequencing data

Despite ongoing large-scale population-based whole-genome sequencing (WGS) projects such as the NIH NHLBI TOPMed program and the NHGRI Genome Sequencing Program, WGS-based association analysis of complex traits remains a tremendous challenge due to the large number of rare variants, many of which are non-trait-associated neutral variants. External biological knowledge, such as functional annotations based on ENCODE, may be helpful in distinguishing causal rare variants from neutral ones; however, each functional annotation can only provide certain aspects of the biological functions. Our knowledge for selecting informative annotations a priori is limited, and incorporating non-informative annotations will introduce noise and lose power. We propose FunSPU, a versatile and adaptive test that incorporates multiple biological annotations and is adaptive at both the annotation and variant levels and thus maintains high power even in the presence of noninformative annotations. In addition to extensive simulations, we illustrate our proposed test using the TWINSUK cohort (n=1,752) of UK10K WGS data based on six functional annotations: CADD, RegulomeDB, FunSeq, Funseq2, GERP++, and GenoSkyline. We identified genome-wide significant genetic loci on chromosome 19 near gene TOMM40 and APOC4-APOC2 associated with low-density lipoprotein (LDL), which are replicated in the UK10K ALSPAC cohort (n=1,497). These replicated LDL-associated loci were missed by existing rare variant association tests that either ignore external biological information or rely on a single source of biological knowledge. We have implemented the proposed test in an R package \"FunSPU\".

genetics↗

bioRxiv2018

A novel amidase signature family amidase from the marine actinomycete Salinispora arenicola CNS-205

We cloned a new gene from the amidase signature (AS) family, designated am, from the marine actinomycete Salinispora arenicola CNS-205. As indicated by bioinformatics analysis and site-directed mutagenesis, the AM protein belonged to the AS family. AM was expressed, purified, and characterised in Escherichia coli BL21 (DE3), and the AM molecular mass was determined to be 51 kDa. The optimal temperature and pH were 40 {degrees}C and pH 8.0, respectively. AM exhibited a wide substrate spectrum and showed amidase, aryl acylamidase, and acyl transferase activities. AM had high activity towards aromatic and aliphatic amides. The AM substrate specificity for anilides was very narrow; only propanil could be used as an effective substrate. The extensive substrate range of AM indicates it may have broad potential applications in biosynthetic processes and biodegradation.

molecular biology↗

bioRxiv2018

Using composite phenotypes to reveal heterogeneity and model SpO2 of altitude acclimatization

Altitude acclimatization is the physiological process of the human body adjusting to the decreased availability of oxygen. Since several physiological processes are involved and the relation among them is complicated, analyses of single-traits is insufficient in revealing the complex mechanism of altitude acclimatization. In this study, we examined whether these physiological responses could be studied as composite phenotypes which are represented by a linear combination of physiological traits. We developed a strategy which combines both spectral clustering and PLSPM to define composite phenotypes. We captured 14 composite phenotypes from 28 physiological traits of altitude acclimatization. Using these composite phenotypes, we applied k-means to reveal hidden physiological heterogeneity in altitude acclimatization. Furthermore, we employed linear regression to systematically model oxygen saturation (SpO2) changes in altitude acclimatization and evaluated the model fitness performance. And composite phenotypes based Model 2 has better fitness than single-traits based Model 1 in all measurement indices. Therefore, this new strategy of defining and applying composite phenotypes can be considered as a general strategy of complex traits.

systems biology↗

bioRxiv2018

Penalized matrix decomposition for denoising, compression, and improved demixing of functional imaging data

Calcium imaging has revolutionized systems neuroscience, providing the ability to image large neural populations with single-cell resolution. The resulting datasets are quite large (with scales of TB/hour in some cases), which has presented a barrier to routine open sharing of this data, slowing progress in reproducible research. State of the art methods for analyzing this data are based on non-negative matrix factorization (NMF); these approaches solve a non-convex optimization problem, and are highly effective when good initializations are available, but can break down e.g. in low-SNR settings where common initialization approaches fail.\n\nHere we introduce an improved approach to compressing and denoising functional imaging data. The method is based on a spatially-localized penalized matrix decomposition (PMD) of the data to separate (low-dimensional) signal from (temporally-uncorrelated) noise. This approach can be applied in parallel on local spatial patches and is therefore highly scalable, does not impose non-negativity constraints or require stringent identifiability assumptions (leading to significantly more robust results compared to NMF), and estimates all parameters directly from the data, so no hand-tuning is required. We have applied the method to a wide range of functional imaging data (including one-photon, two-photon, three-photon, widefield, somatic, axonal, dendritic, calcium, and voltage imaging datasets): in all cases, we observe ~2-4x increases in SNR and compression rates of 20-300x with minimal visible loss of signal, with no adjustment of hyperparameters; this in turn facilitates the process of demixing the observed activity into contributions from individual neurons. We focus on two challenging applications: dendritic calcium imaging data and voltage imaging data in the context of optogenetic stimulation. In both cases, we show that our new approach leads to faster and much more robust extraction of activity from the video data.

neuroscience↗

bioRxiv2018

On the design of treatment schedules that avoid chemotherapeutic resistance

We introduce a method of designing treatment schedules for a model three-component replicator dynamical system that avoids chemotherapeutic resistance by controlling and managing the competitive release of resistant cells in the tumor. We use an evolutionary game theory model with prisoners dilemma payoff matrix that governs the competition among healthy cells, chemo-sensitive cells, and chemo-resistant cells and the goal is to control the evolution of chemo-resistance via the competitive release mechanism. The method is based on nonlinear trajectory design and energy transfer methods first introduced in the orbital mechanics literature for Hamiltonian systems. By using the structure of the trajectories defined by solutions of the replicator system for different constant chemotherapeutic concentrations (which produces a curvilinear coordinate system spanning the full region), we construct periodic (closed) orbits by switching the chemo-dose at carefully chosen times and appropriate levels to design schedules that are superior to both maximum tolerated dose (MTD) schedules and low-dose metronomic (LDM) schedules, both of which ultimately lead to fixation of either sensitive cells or resistant cells. By keeping the three sub-populations of cells in competition with each other, neither the sensitive cell population nor the resitant cell population are able to dominate as we balance the populations indefinitely (closed periodic orbits), thereby avoiding fixation of the cancer cell population and re-growth of a resistant tumor. The schedules we design have the feature that they maintain a higher average population fitness than either the MTD or the LDM schedules.\n\nPACS numbers: 87.23.Kg; 87.55.de; 87.19.Xj; 87.19.lr

cancer biology↗

bioRxiv2018

Quality Control and Integration of Genotypes from Two Calling Pipelines for Whole Genome Sequence Data in the Alzheimer’s Disease Sequencing Project

The Alzheimers Disease Sequencing Project (ADSP) performed whole genome sequencing (WGS) of 584 subjects from 111 multiplex families at three sequencing centers. Genotype calling of single nucleotide variants (SNVs) and insertion-deletion variants (indels) was performed centrally using GATK-HaplotypeCaller and Atlas V2. The ADSP Quality Control (QC) Working Group applied QC protocols to project-level variant call format files (VCFs) from each pipeline, and developed and implemented a novel protocol, termed \"consensus calling,\" to combine genotype calls from both pipelines into a single high-quality set. QC was applied to autosomal bi-allelic SNVs and indels, and included pipeline-recommended QC filters, variant-level QC, and sample-level QC. Low-quality variants or genotypes were excluded, and sample outliers were noted. Quality was assessed by examining Mendelian inconsistencies (MIs) among 67 parent-offspring pairs, and MIs were used to establish additional genotype-specific filters for GATK calls. After QC, 578 subjects remained. Pipeline-specific QC excluded ~12.0% of GATK and 14.5% of Atlas SNVs. Between pipelines, ~91% of SNV genotypes across all QCed variants were concordant; 4.23% and 4.56% of genotypes were exclusive to Atlas or GATK, respectively; the remaining ~0.01% of discordant genotypes were excluded. For indels, variant-level QC excluded ~36.8% of GATK and 35.3% of Atlas indels. Between pipelines, ~55.6% of indel genotypes were concordant; while 10.3% and 28.3% were exclusive to Atlas or GATK, respectively; and ~0.29% of discordant genotypes were. The final WGS consensus dataset contains 27,896,774 SNVs and 3,133,926 indels and is publicly available.\n\nAbbreviationsAD, Alzheimers disease; QC, Quality Control; LSSAC, Large-Scale Sequencing and Analysis Center; Broad, Broad Institute Genomics Service; Baylor, Baylor College of Medicine Human Genome Sequencing Center; WashU, Washington University-St. Louis McDonnell Genome Institute; WGS, whole genome sequencing; WES, whole exome sequencing; indel, insertion-deletion variants; VCF, variant control format; MI, Mendelian inconsistency; MC, Mendelian consistency; GWAS, genome-wide association study; VR, referent allele read depth; DP, overall read depth; MS, mapping score; GQ, genotype quality score; Ti/Tv, Transition/Transversion; CS, concordance code

genetics↗

bioRxiv2018

In vivo Chemical Reprogramming of Astrocytes into Functional Neurons

Mammals lack robust regenerative abilities. Lost cells in impaired tissue could potentially be compensated by converting nearby cells in situ through in vivo reprogramming. Small molecule-induced reprogramming is a spatiotemporally flexible and non-integrative strategy for altering cell fate, which is, in principle, favorable for the in vivo reprogramming in organs with poor regenerative abilities, such as the brain. Here, we demonstrate that in the adult mouse brain, small molecules can reprogram resident astrocytes into functional neurons. The in situ chemically induced neurons (CiNs) resemble endogenous neurons in terms of neuron-specific marker expression and electrophysiological properties. Importantly, these CiNs can integrate into the mouse brain. Our study, for the first time, demonstrates in vivo chemical reprogramming in the adult brain, which could be a novel path for generating desired cells in situ for regenerative medicine.

cell biology↗

bioRxiv2018

Nonlinear dynamics of chemotherapeutic resistance

We use a three-component replicator dynamical system with healthy cells, sensitive cells, and resistant cells, with a prisoners dilemma payoff matrix from evolutionary game theory to understand the phenomenon of competitive release, which is the main mechanism by which tumors develop chemotherapeutic resistance. By comparing the phase portraits of the system without therapy compared to continuous therapy above a certain threshold, we show that chemotherapeutic resistance develops if there are pre-exisiting resistance cells in the population. We examine the basin boundaries of attraction associated with the chemo-sensitive population and the chemo-resistant population for increasing values of chemo-concentrations and show their spiral intertwined structure. We also examine the fitness landscapes both with and without continuous therapy and show that with therapy, the average fitness as well as the fitness functions of each of the subpopulations initially increases, but eventually decreases monotonically as the resistant subpopulation saturates the tumor.

cancer biology↗

bioRxiv2018

PKD2 influence uric acid levels and gout risk by interacting with ABCG2

BackgroundUric acid is the final product of purine metabolism and elevated serum urate levels can cause gout. Conflicting results were reported for the effect of PKD2 on serum urate levels and gout risk. Therefore, our study attempted to state the important role of PKD2 in influencing the pathogenesis of gout.\n\nMethodSNPs in PKD2 (rs2725215 and rs2728121) and ABCG2 (rs2231137 and rs1481012) were tested in approximately 5,000 Chinese individuals.\n\nResultsTwo epistatic interactions between loci in PKD2 (rs2728121) and ABCG2 (rs1481012 and rs2231137) showed distinct contributions to uric acid levels with P int values of 0.018 and 0.004, respectively, and the associations varies by gender and BMI. The SNP pair of rs2728121 and rs1481012 justly played roles in uric acid in females (P int = 0.006), while the other pair did in males (P int = 0.017). Regarding BMI, the former SNP pair merely contributed in overweigh subjects (P int = 0.022) and the latter one did in both normal and overweigh individuals (P int = 0.013 and 0.047, respectively). Furthermore, the latter SNP pair was also associated with gout pathology (P int = 0.001), especially in males (P int = 0.001). Finally, functional analysis showed potential epistatic interactions in those genes region and PKD2 mRNA expression had a positive correlation with ABCG2s (r = 0.743, P = 5.83e-06).\n\nConclusionOur study for the first time identified that epistatic interactions between PKD2 and ABCG2 influenced serum urate concentrations and gout risk, and PKD2 might affect the pathogenesis from elevated serum urate to hyperuricemia to gout by modifying ABCG2.

genetics↗