Biology subjects

Li, N.

Publications and source records attributed to Li, N..

At least 271 records · Page 15Linked to original sources

bioRxiv2019

Genome-wide association analyses of multiple traits in Duroc pigs using low-coverage whole-genome sequencing strategy

High-density markers discovered in large size samples are essential for mapping complex traits at the gene-level resolution for agricultural livestock and crops. However, the unavailability of large reference panels and array designs for a target population of agricultural species limits the improvement of array-based genotype imputation. Recent studies showed very low coverage sequencing (LCS) of a large number of individuals is a cost-effective approach to discover variations in much greater detail in association studies. Here, we performed cohort-wide whole-genome sequencing at an average depth of 0.73x and identified more than 11.3 M SNPs. We also evaluated the data set and performed genome-wide association analysis (GWAS) in 2885 Duroc boars. We compared two different pipelines and selected a proper method (BaseVar/STITCH) for LCS analyses and determined that sequencing of 1000 individuals with 0.2x depth is enough for identifying SNPs with high accuracy in this population. Of the seven association signals derived from the genome-wide association analysis of the LCS variants, which were associated with four economic traits, we found two QTLs with narrow intervals were possibly responsible for the teat number and back fat thickness traits and identified 7 missense variants in a single sequencing step. This strategy (BaseVar/STITCH) is generally applicable to any populations and any species which have no suitable reference panels. These findings show that the LCS strategy is a proper approach for the construction of new genetic resources to facilitate genome-wide association studies, fine mapping of QTLs, and genomic selection, and implicate that it can be widely used for agricultural animal breeding in the future.

genetics↗

bioRxiv2019

Identification of the Repressive Domain of the Negative Circadian Clock Component CHRONO

Circadian rhythm is an endogenous, self-sustainable oscillation that participates in regulating organisms physiological activities. Key to this oscillation is a negative feedback by main clock components Periods and Cryptochromes that repress transcriptional activity of BMAL1/CLOCK complexes. In addition, a novel repressor, CHRONO, has been identified recently, but details of CHRONOs function during repressing the circadian cycle remain unclear. Here we report that a domain of CHRONO mainly composed of -helixes is critical to repression through the exploitation of protein-protein interactions according to luciferase reporter assays, co-immunoprecipitation, immunofluorescence, genome editing and structural information analysis via circular dichroism spectroscopy. This repression is fulfilled by interactions between CHRONO with a region on the BMAL1 C-terminus where Cryptochrome and CBP bind. Our results indicate that CHRONO and PER differentially function as BMALA/CLOCK-dependent repressors. We further suggest a repression model of how PER, CRY and CHRONO proteins associate with BMAL1, respectively.

molecular biology↗

bioRxiv2019

The loss of ATRX/DAXX complex disturbs rDNA heterochromatinization and promotes development of glioma

BackgroundRibosomal DNA (rDNA) transcription by the RNA polymerase I (Pol I) is a rate-limited step for ribosome synthesis, which is critical for cell growth, cell differentiation, and tumorigenesis. Meanwhile rDNA transcription is modulated by DNA methylation and histone epigenetic modification. Though with great progress in epigenetic research recently, it still remains much uncertain about the relationship of histone variant epigenetic modification and rDNA transcription.\n\nResultsIn this study, epigenetic profiles of silent rDNA in next-generation sequencing datasets were examined. We found that the chaperone of histone variant H3.3, the alpha-thalassemia/mental retardation X-linked syndrome protein (ATRX)/death domain-associated protein (DAXX) complex, and methyltransferase SET domain bifurcated 1 (Setdb1, also known as ESET) help maintain H3.3K9me3 modifications among the promoter and coding regions of silent rDNA. Our experiments further confirmed that DAXX depletion leads to the conversion of silent rDNA into upstream binding factor-bound active rDNA and the release of rDNA transcriptional potency. Support for this model is provided by data from a low-grade glioma in which ATRX is lost and a higher level of ribosomal biosynthesis, nucleolus activity, and proliferation are observed.\n\nConclusionsWe demonstrate a model of epigenetic regulation for rDNA with roles for the ATRX/DAXX complex and H3.3/H3K9me3 modifications identified. Thus, loss of ATRX/DAXX may represent a driving force for tumorigenesis due to its contribution to the release of rDNA transcriptional potency.

cancer biology↗

bioRxiv2019

Genetic and functional evidence relates a missense variant in B4GALT1 to lower LDL-C and fibrinogen

Increased LDL-cholesterol (LDL-C) and fibrinogen are independent risk factors for cardiovascular disease (CVD). We identified novel associations between an Amish-enriched missense variant (p.Asn352Ser) in a functional domain of beta-1,4-galactosyltransferase 1 (B4GALT1) and 13.5 mg/dl lower LDL-C (p=1.6E-15), and 26 mg/dl lower plasma fibrinogen (p= 9.8E-05). N-linked glycan profiling found p.Asn352Ser to be associated (p-values from 1.4E-06 to 1.0E-17) with decreased glycosylation of glycoproteins including: fibrinogen, ApoB100, immunoglobulin G (IgG), and transferrin. In vitro assays found that the mutant (352Ser) protein had 50% lower galactosyltransferase activity compared to wild type (352Asn) protein. Knockdown of b4galt1 in zebrafish embryos resulted in significantly lower LDL-C compared to control, which was fully rescued by co-expression of 352Asn human B4GALT1 mRNA but only partially rescued by co-expression of 352Ser human B4GALT1 mRNA. Our findings establish B4GALT1 as a novel gene associated with lower LDL-C and fibrinogen and suggest that targeted modulation of protein glycosylation may represent a therapeutic approach to decrease CVD risk.

genetics↗

bioRxiv2019

A Na2CO3-responsive chitinase gene from Chinese wildrye improve pathogen resistance and saline-alkali stress tolerance in transgenic tobacco and maize

Salinity and microbial pathogens are the major limiting factors for crop production. Although the manipulation of many genes could improve plant performance under either of these stresses, few genes have reported that could improve both pathogen resistance and saline-alkali stress tolerance. In this study, we identified a new chitinase gene CHITINASE 2 (LcCHI2) that encodes a class II chitinase from a Chinese wildrye (Leymus Chinensis), which grows naturally on alkaline-sodic soil. Overexpression of LcCHI2 increased chitinase activity in transgenic plants. The transgenic tobacco and maize exhibited improved pathogen resistance and enhanced both neutral salt and alkaline salt stress tolerance. Overexpression of LcCHI2 reduced sodium (Na+) accumulation, malondialdehyde content and relative electrical conductivity in transgenic tobacco under salt stress. In addition, the transgenic tobacco showed diminished lesion against bacterial and fungal pathogen challenge, suggesting an improved disease resistance. Similar improved performance was also observed in LcCHI2-overexpressed maize under both pathogen and salt stresses. It is worth noting that this genetic manipulation does not impair the growth and yield of transgenic tobacco and maize under normal cultivation condition. Apparently, application of LcCHI2 provides a new train of thought for genetically engineering saline-alkali and pathogen resistant crops of both dicots and monocots.

plant biology↗

bioRxiv2019

Recombinase system-dependent copackaging strategy for highly efficient neurocircuit tracing

Mapping the detailed cell-type-specific input networks and neuronal projectomes are essential to understand brain function in normal and pathological states. However, several properties of current tracing systems, including labeling sensitivity, trans-synaptic efficiencies, reproducibility among different individuals and different Cre-driver animals, still remained unsatisfactory. Here, we developed MAP-ENVIVIDERS, a recombinase system-dependent vector mixing-based strategy for highly efficient neurocircuit tracing. MAP-ENVIVIDERS enhanced tracing efficiency of input networks across the whole brain, with over 10-fold improvement in diverse previously poor-labeled input brain regions and particularly, up to 70-fold enhancement in brainstem compared with the current standard rabies-virus-mediated systems. MAP-ENVIVIDERS was over 10-fold more sensitive for cell-type-specific labeling than previous strategies, enabling us to capture individual cell-type-specific neurons with extremely complex axonal branches and presynaptic axonal boutons, both about one order of magnitude than previously reported and considered. MAP-ENVIVIDERS provides powerful tools for deconstructing novel input/output circuitry towards functional studies and disorders-related mechanisms.

neuroscience↗

bioRxiv2019

Mechanisms underlying the response of mouse cortical networks to optogenetic manipulation

GABAergic interneurons can be subdivided into three subclasses: parvalbumin positive (PV), somatostatin positive (SOM) and serotonin positive neurons. With principal cells (PCs) they form complex networks. We examine PCs and PV responses in mouse anterior lateral motor cortex (ALM) and barrel cortex (S1) upon PV photostimulation in vivo. In layer 5, the PV response is paradoxical: photoexcitation reduces their activity. This is not the case in ALM layer 2/3. We combine analytical calculations and numerical simulations to investigate how these results constrain the architecture. Two-population models cannot account for the results. Networks with three inhibitory populations and V1-like architecture account for the data in ALM layer 2/3. Our data in layer 5 can be accounted for if SOM neurons receive inputs only from PCs and PV neurons. In both four-population models, the paradoxical effect implies not too strong recurrent excitation. It is not evidence for stabilization by inhibition.

neuroscience↗

bioRxiv2019

Left prefrontal connectivity links subthalamic stimulation with depressive symptoms in Parkinson’s disease

ObjectiveSubthalamic nucleus deep brain stimulation (STN-DBS) in Parkinsons Disease (PD) not only stimulates focal target structures but also affects distributed brain networks. The impact this network modulation has on non-motor DBS effects is not well characterized. By focusing on the affective domain, we systematically investigate the impact of electrode placement and associated structural connectivity on changes in depressive symptoms following STN-DBS which have been reported to improve, worsen or remain unchanged. MethodsDepressive symptoms before and after STN-DBS surgery were documented in 116 PD patients from three DBS centers (Berlin, Queensland, Cologne). Based on individual electrode reconstructions, the volumes of tissue activated (VTA) were estimated and combined with normative connectome data to identify structural connections passing through VTAs. Berlin and Queensland cohorts formed a training and cross-validation dataset used to identify structural connectivity explaining change in depressive symptoms. The Cologne data served as test-set for which depressive symptom change was predicted. ResultsStructural connectivity was linked to depressive symptom change under STN-DBS. An optimal connectivity map trained on the Berlin cohort could predict changes in depressive symptoms in Queensland patients and vice versa. Furthermore, the joint training-set map predicted changes in depressive symptoms in the independent test-set. Worsening of depressive symptoms was associated with left prefrontal connectivity. InterpretationFibers linking the STN electrode with left prefrontal areas predicted worsening of depressive symptoms. Our results suggest that for the left STN-DBS lead, placement impacting fibers to left prefrontal areas should be avoided to maximize improvement of depressive symptoms.

neuroscience↗

bioRxiv2019

Dosage effect of multiple genes accounts for multisystem disorder of myotonic dystrophy type 1

Multisystem manifestations in myotonic dystrophy type 1 (DM1) may be due to dosage reduction in multiple genes induced by aberrant expansion of CTG repeats in DMPK, including Dmpk and its neighboring genes (Six5 or Dmwd) and downstream Mbnl1. However, the direct evidences are lack. Here, we develop a new strategy to generate mice carrying multigene mutations in one step by injection of haploid embryonic stem cells with mutant Dmpk, Six5 and Mbnl1 into oocytes. The triple heterozygous mutant mice exhibit adult-onset DM1 phenotypes. With the additional mutation in Dmwd, quadruple heterozygous mutant mice recapitulate many major manifestations in congenital DM1. Moreover, muscle stem cells in both models display reduced stemness. Our results suggest that the complex symptoms of DM1 result from the reduced gene dosage of multiple genes.

genetics↗

bioRxiv2019

Spatiotemporal limits of optogenetic manipulations in cortical circuits

Neuronal inactivation is commonly used to assess the involvement of groups of neurons in specific brain functions. Optogenetic tools allow manipulations of genetically and spatially defined neuronal populations with excellent temporal resolution. However, the targeted neurons are coupled with other neural populations over multiple length scales. As a result, the effects of localized optogenetic manipulations are not limited to the targeted neurons, but produces spatially extended excitation and inhibition with rich dynamics. Here we benchmarked several optogenetic silencers in transgenic mice and with viral gene transduction, with the goal to inactivate excitatory neurons in small regions of neocortex. We analyzed the effects of the perturbations in vivo using electrophysiology. Channelrhodopsin activation of GABAergic neurons produced more effective photoinhibition of pyramidal neurons than direct photoinhibition using light-gated ion pumps. We made transgenic mice expressing the light-dependent chloride channel GtACR under the control of Cre-recombinase. Activation of GtACR produced the most potent photoinhibition. For all methods, localized photostimuli produced photoinhibition that extended substantially beyond the spread of light in tissue, although different methods had slightly different resolution limits (radius of inactivation, 0.5 mm to 1 mm). The spatial profile of photoinhibition was likely shaped by strong coupling between cortical neurons. Over some range of photostimulation, circuits produced the \"paradoxical effect\", where excitation of inhibitory neurons reduced activity in these neurons, together with pyramidal neurons, a signature of inhibition-stabilized neural networks. The offset of optogenetic inactivation was followed by rebound excitation in a light dose-dependent manner, which can be mitigated by slowly varying photostimuli, but at the expense of time resolution. Our data offer guidance for the design of in vivo optogenetics experiments and suggest how these experiments can reveal operating principles of neural circuits.

neuroscience↗

bioRxiv2019

Simulation-based comparison of Biopharmaceutics Classification System and drug structure

BackgroundThe Biopharmaceutics Classification System (BCS), which classifies bioactive molecules based on solubility and permeability, is widely used to guide new drug development and drug formulation, as well as predict pharmacokinetics. Here we performed computer simulations to study correlations between a molecules structure and its BCS classification.\n\nMethodsA total of 411 small molecules were assigned to BCS categories based on published drug data, and their Pybel-FP4 fingerprints were extrapolated. The information gain(IG) of each fingerprint was calculated and its characteristic structure analyzed. IG was calculated using multiple thresholds, and results were verified using support vector machine prediction, while taking into account the dose coefficient(0-0.1, 0.1-1, or>1). Structural functional features common to fingerprints of compounds in each type of BCS class were determined using computer simulations.\n\nResultsBCS classes III and IV appear to share several structural and functional characteristics, including Secondary aliphaticamine, Michael_acceptor, Isothiourea, and Sulfonamide Sulfonic_derivatives.\n\nConclusionWe demonstrate that our approach can correlate characteristic fingerprints of small-molecule drugs with BCS classifications, which may help guide the development and optimization of new drugs.

molecular biology↗

bioRxiv2019

Transcriptome-wide map of m6A circRNAs identified in hypoxic pulmonary hypertension rat model

Hypoxic pulmonary hypertension (HPH) is a lethal disease. CircRNAs and m6A circRNAs have been reported to be associated with cancer progression, but the expression profiling of m6A circRNAs has not been identified in HPH. This study was to investigate the transcriptome-wide map of m6A circRNAs in HPH. In this study, hypoxia-induced PH rat model was established. Total RNA was extracted and purified from lungs of rats, then circRNAs were detected and annotated by RNA-seq analysis. m6A RNA Immunoprecipitation (MeRIP) was performed following rRNA depletion, and RNA-seq library was constructed. CircRNA-miRNA-mRNA co-expression network was also constructed. In vitro, total m6A was measured. m6A circXpo6 and m6A circTmtc3 were detected in pulmonary artery smooth muscle cells (PASMCs) and pulmonary artery endothelial cells (PAECs) exposed to 21% O2 and 1% O2 for 48 h, respectively. m6A abundance in 166 circRNAs was significantly upregulated and m6A abundance in 191 circRNAs was significantly downregulated in lungs of HPH rats. m6A abundance in circRNAs was significantly reduced in hypoxia in vitro. m6A circRNAs were mainly derived from single exons of protein-coding genes. m6A influenced the circRNA-miRNA-mRNA co-expression network in hypoxia. m6A circXpo6 and m6A circTmtc3 were downregulated in hypoxia. In general, our study firstly identified the transcriptome-wide map of m6A circRNAs in HPH. m6A level in circRNAs was decreased in lungs of HPH rats and in PASMCs and PAECs exposed to hypoxia. Downregulated or upregulated m6A level influenced circRNA-miRNA-mRNA co-expression network in HPH. Moreover, we firstly identified two downregulated m6A circRNAs in HPH: circXpo6 and circTmtc3. We suggested that m6A circRNAs may be used as a potential diagnostic marker or therapy target in the future.\n\nAuthor summaryHPH is a disease with great morbidity and mortality. It is often caused by chronic hypoxic lung diseases, such as chronic obstructive pulmonary disease and interstitial lung diseases. It lacks effective therapy methods so far. CircRNAs are a type of non-coding RNAs and can be used as biomarkers because they are differentially enriched in specific cell types or tissues and not easily degraded. m6A is identified as the most universal modification on non-coding RNAs in eukaryotes. CircRNAs can be modified by m6A. m6A circRNAs in HPH is not well understood yet. Here we identify the transcriptome-wide map of m6A circRNAs in HPH. We elucidate that m6A level in circRNAs is decreased in lungs of HPH rats and in PASMCs and PAECs exposed to hypoxia. We find that downregulated or upregulated m6A level influences circRNA- miRNA-mRNA co-expression network in HPH. Moreover, we are the first to identify two downregulated m6A circRNAs in HPH: circXpo6 and circTmtc3. We suggest that m6A circRNAs may be used as a potential diagnostic marker or therapy target in the future.

genetics↗

bioRxiv2019

Toward a unified connectomic target for deep brain stimulation in obsessive-compulsive disorder

Multiple surgical targets have been proposed for treating obsessive-compulsive disorder (OCD) with deep brain stimulation (DBS). However, different targets may modulate the same neural network responsible for clinical improvement. Here we analyzed data from four cohorts of OCD patients (N = 50) that underwent DBS to the anterior limb of the internal capsule (ALIC), the nucleus accumbens (NAcc) or the subthalamic nucleus (STN). Fiber tracts that were predominantly connected to electrodes in good or poor DBS responders were isolated from a normative structural connectome and assigned a predictive value. Strikingly, the same fiber bundle was related to treatment response when independently analyzing two large training cohorts that targeted either ALIC or STN. This discriminative tract is a subsection of the ALIC and connects frontal regions (such as the dorsal anterior cingulate, dACC, and ventral prefrontal, vlPFC, cortices to the STN). When informing the tract solely based on one cohort (e.g. ALIC), clinical improvements in the other (e.g. STN) could be significantly predicted, and vice versa. Finally, clinical improvements of eight patients from a third center with electrodes in the NAcc and six patients from a fourth center in which electrodes had been implanted in both STN and ALIC were significantly predicted based on this novel tract-based DBS target. Results suggest a functional role of a limbic hyperdirect pathway that projects from dACC and vlPFC to anteriomedial STN. Obsessive-compulsive symptoms seem to be tractable by modulating the specific bundle isolated here. Our results show that connectivity-derived improvement models can inform clinical improvement across DBS targets, surgeons and centers. The identified tract is now three-dimensionally defined in stereotactic standard space and will be made openly available.

neuroscience↗

bioRxiv2019

Positive feedback loop of regulating ERK phosphorylation in mESCs mediated by Etv5-Tet2-Fgfr2 axis

Dynamic equilibrium of extracellular signal-regulated kinase (ERK) activity is regulated elaborately by multiple feedback loops to ensure the normal self-renewal of mouse embryonic stem cells (mESCs). Previous studies on mESCs have demonstrated that the negative feedback loops are engaged to prevent the overactivated ERK phosphorylation (pERK). It is not clear whether there is any positive feedback loop involved to maintain a minimum of pERK in mESCs. Here, we found that blocking fibroblast growth factor (FGF)-ERK pathway by chemical PD0325901 downregulated the transcription of E26 transformation-specific (ETS) family transcription factor Etv5 in mESCs. In turn, knockout (KO) of Etv5 by CRISPR/Cas9 decreased pERK. Moreover, Etv5 KO enhanced the DNA methylation at promoter of fibroblast growth factor receptor 2 (Fgfr2) by downregulating DNA hydroxylase Tet2, which further decreased the expression of Fgfr2 in mESCs. Collectively, a positive feedback loop of regulating pERK was revealed in mESCs, which was mediated by Etv5-Tet2-Fgfr2 axis. Our findings provide a new paradigm for pERK regulation in mESCs and will be useful to understand the cell fate determination during early embryo development.

developmental biology↗

bioRxiv2019

Remodeling gut microbiota by Streptococcus thermophilus 19 attenuates inflammation in septic mice

Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection and is the leading cause of death in burn patients. Streptococcus thermophilus 19 is a highly effective probiotic, with well-studied health benefits, but its role in protecting viscera against injury caused by sepsis and the underlying mechanism is poorly understood. The goal of this study was to evaluate protection potency of S. thermophilus against inflammation in mice and evaluate the influence of sepsis and S. thermophilus on microbial community. We tested the utility of S. thermophilus 19 in attenuating inflammation in vitro and vivo of LPS-induced sepsis mouse model. We also evaluated the influence of sepsis and S. thermophilus on microbial community. In vitro, S. thermophilus 19 decrease the expression of inflammatory factors. Additionally, in a lipopolysaccharide-induced septic mouse model, mice administered the probiotic 19 was highly resistant to Lps and exhibited decreased expression of inflammatory factors compared to Lps-treated control mice. A MiSeq-based sequence analysis revealed that gut microbiota alterations in mice intraperitoneally injected with 1 mg/ml LPS were mitigated by the administration of oral probiotics 19. Together these findings indicate that S. thermophilus 19 may be a new avenue for interventions against inflammation caused by sepsis and other systemic inflammatory diseases. In an analysis of the gut microbiota of the all group mice, we found that sepsis is associated with gut microbiota and probiotics attenuate the inflammation through remodeling gut microbiota. ImportanceSepsis is life-threatening organ dysfunction which is the leading cause of death in burn patients. Although our understanding of sepsis has increased substantially in recent years, its still reported to be the leading cause of death in seriously ill patients. Evidences showed that gut microbiota play an important role in sepsis. Moreover, probiotics have been used to prevent numbers of gut health disorders and alleviate inflammation associated with some human diseases by promoting changes in the gut microbiota composition. Hence, to investigate the mechanism of probiotics in the treatment of sepsis has emerged. The significance of our research is in identifying the role of gut microbiota in sepsis and found an effective probiotic that reduces inflammation, S. thermophilus 19, and investigating the therapeutic effect and mechanism of S. thermophilus 19 on sepsis, which might be a new avenue for interventions against inflammation caused by sepsis and other systemic inflammatory diseases.

microbiology↗

bioRxiv2019

Scalable and Accurate Drug-target Prediction Based on Heterogeneous Bio-linked Network Mining

MotivationDespite the existing classification- and inference-based machine learning methods that show promising results in drug-target prediction, these methods possess inevitable limitations, where: 1) results are often biased as it lacks negative samples in the classification-based methods, and 2) novel drug-target associations with new (or isolated) drugs/targets cannot be explored by inference-based methods. As big data continues to boom, there is a need to study a scalable, robust, and accurate solution that can process large heterogeneous datasets and yield valuable predictions. ResultsWe introduce a drug-target prediction method that improved our previously proposed method from the three aspects: 1) we constructed a heterogeneous network which incorporates 12 repositories and includes 7 types of biomedical entities (#20,119 entities, # 194,296 associations), 2) we enhanced the feature learning method with Node2Vec, a scalable state-of-art feature learning method, 3) we integrate the originally proposed inference-based model with a classification model, which is further fine-tuned by a negative sample selection algorithm. The proposed method shows a better result for drug-target association prediction: 95.3% AUC ROC score compared to the existing methods in the 10-fold cross-validation tests. We studied the biased learning/testing in the network-based pairwise prediction, and conclude a best training strategy. Finally, we conducted a disease specific prediction task based on 20 diseases. New drug-target associations were successfully predicted with AUC ROC in average, 97.2% (validated based on the DrugBank 5.1.0). The experiments showed the reliability of the proposed method in predicting novel drug-target associations for the disease treatment.

bioinformatics↗

bioRxiv2019

Modulating the human functional connectome using deep brain stimulation

Neuroimaging has seen a paradigm shift from a formal description of local activity patterns toward studying distributed brain networks. The recently defined framework of the human connectome allows to globally analyse parts of the brain and their interconnections. Deep brain stimulation (DBS) is an invasive therapy for patients with severe movement disorders aiming to retune abnormal brain network activity by local high frequency stimulation of the basal ganglia. Beyond clinical utility, DBS represents a powerful research platform to study functional connectomics and the modulation of distributed brain networks in the human brain. We acquired resting-state functional MRI in twenty Parkinsons disease (PD) patients with subthalamic DBS switched ON and OFF. An age-matched control cohort of fifteen subjects was acquired from an open data repository. DBS lead placement in the subthalamic nucleus (STN) was localized using a state-of-the art pipeline that involved brain shift correction, multispectral image registration and use of a precise subcortical atlas. Based on a realistic 3D model of the electrode and surrounding anatomy, the amount of local impact of DBS was estimated using a finite element method approach. On a global level, average connectivity increases and decreases throughout the brain were estimated by contrasting ON and OFF DBS scans on a voxel-wise graph comprising eight thousand nodes. Local impact of DBS on the sensorimotor STN explained half the variance in global connectivity increases within the sensorimotor network (R = 0.711, p < 0.001). Moreover, local impact of DBS on the motor STN could explain the degree of how much voxel-wise average brain connectivity normalized toward healthy controls (R = 0.713, p < 0.001). Finally, a network based statistics analysis revealed that DBS attenuated specific couplings that are known to be pathological in PD. Namely, coupling between motor thalamus and sensorimotor cortex was increased and striatal coupling with cerebellum, external pallidum and STN was decreased by DBS. Our results show that rs-fMRI may be acquired in DBS ON and OFF conditions on clinical MRI hardware and that data is useful to gain additional insight into how DBS modulates the functional connectome of the human brain. We demonstrate that effective DBS increases overall connectivity in the motor network, normalizes the network profile toward healthy controls and specifically strengthens thalamo-cortical connectivity while reducing striatal control over basal ganglia and cerebellar structures.

neuroscience↗

bioRxiv2018

CRUP: A comprehensive framework to predict condition-specific regulatory units

We present the software CRUP (Condition-specific Regulatory Units Prediction) to infer from epigenetic marks a list of regulatory units consisting of dynamically changing enhancers with their target genes. The workflow consists of a novel pre-trained enhancer predictor that can be reliably applied across cell lines and species, solely based on histone modification ChIP-seq data. Enhancers are subsequently assigned to different conditions and correlated with gene expression to derive regulatory units. We thoroughly test and then apply CRUP to a rheumatoid arthritis model, identifying enhancer-gene pairs comprising known disease genes as well as new candidate genes.\n\nAvailabilityhttps://github.com/VerenaHeinrich/CRUP

bioinformatics↗