Biology subjects

Kong, X.

Publications and source records attributed to Kong, X..

At least 91 records · Page 5Linked to original sources

bioRxiv2021

Muscle group specific transcriptomic and DNA methylation differences related to developmental patterning in FSHD

Muscle groups throughout the body are specialized in function and are specified during development by position specific gene regulatory networks. In developed tissue, myopathies affect muscle groups differently. Facioscapulohumeral muscular dystrophy, FSHD, affects upper body and tibialis anterior (TA) muscles earlier and more severely than others such as quadriceps. To investigate an epigenetic basis for susceptibility of certain muscle groups to disease, we perform DNA methylation and RNA sequencing on primary patient derived myoblasts from TA and quadricep for both control and FSHD2 as well as RNA-seq for myoblasts from FSHD1 deltoid, bicep and TA over a time course of differentiation. We find that TA and quadricep retain methylation and expression differences in transcription factors that are key to muscle group specification during embryogenesis. FSHD2 patients have differences in DNA methylation and expression related to SMCHD1 mutations and FGF signaling. Genes induced specifically in FSHD are more highly expressed in commonly affected muscle groups. We find a set of genes that distinguish more susceptible muscle groups including development-associated TFs and genes involved in WNT signaling. Adult muscle groups therefore retain transcriptional and DNA methylation differences associated with development, which may contribute to susceptibility in FSHD.

genomics↗

bioRxiv2021

Machine learning prediction of antiviral-HPV protein interactions for anti-HPV pharmacotherapy

Persistent infection with high-risk types Human Papillomavirus could cause diseases including cervical cancers and oropharyngeal cancers. Nonetheless, so far there is no effective pharmacotherapy for treating the infection from high-risk HPV types, and hence it remains to be a severe threat to the health of female. Based on drug repositioning strategy, we trained and benchmarked multiple machine learning models so as to predict potential effective antiviral drugs for HPV infection in this work. Through optimizing models, measuring models predictive performance using 182 pairs of antiviral-target interaction dataset which were all approved by the United States Food and Drug Administration, and benchmarking different models predictive performance, we identified the optimized Support Vector Machine and K-Nearest Neighbor classifier with high precision score were the best two predictors (0.80 and 0.85 respectively) amongst classifiers of Support Vector Machine, Random forest, Adaboost, Naive Bayes, K-Nearest Neighbors, and Logistic regression classifier. We applied these two predictors together and successfully predicted 57 pairs of antiviral-HPV protein interactions from 864 pairs of antiviral-HPV protein associations. Our work provided good drug candidates for anti-HPV drug discovery. So far as we know, we are the first one to conduct such HPV-oriented computational drug repositioning study.

bioinformatics↗

bioRxiv2021

Retron Editing for Precise Genome Editing without Exogenous Donor DNA in Human Cells

CRISPR-Cas9 mediated seamless genome editing can be achieved by incorporating donor DNA into the CRISPR-Cas9 target loci via homology-directed repair (HDR), albeit with relative low efficiency due to the inefficient delivery of exogenous DNA. Retrons are bacterial genetic element composed of a non-coding RNA (ncRNA) and reverse transcriptase (RT). Retrons coupled with CRISPR-Cas9 have been shown to enhance precise genome editing via HDR in yeast through fusing guide RNA (gRNA) to the 3 end of retron ncRNA, producing multicopy single-stranded DNA (msDNA) covalently tethered to gRNA. Here, we further engineered retrons by fusing Cas9 with E.coli RT from different clades and joining gRNA at the 5 end of retron ncRNA, and found that retron editing can achieve precise genome editing efficiently in human cells. By co-expression of Cas9-RT fusions and retron-ncRNA gRNA (rgRNA) in HEK293T cells, we demonstrated the rates of retron editing at endogenous genomic loci was up to 10 %. We expect our retron editing system could aid in advancing the ex vivo and in vivo therapeutic applications of retron.

bioengineering↗

bioRxiv2021

Multi-tissue integrative analysis of personal epigenomes

Understanding how genetic variants impact molecular phenotypes is a key goal of functional genomics, currently hindered by reliance on a single haploid reference genome. Here, we present the EN-TEx resource of personal epigenomes, for [~]25 tissues and >10 assays in four donors (>1500 open-access functional genomic and proteomic datasets, in total). Each dataset is mapped to a matched, diploid personal genome, which has long-read phasing and structural variants. The mappings enable us to identify >1 million loci with allele-specific behavior. These loci exhibit coordinated epigenetic activity along haplotypes and less conservation than matched, non-allele-specific loci, in a fashion broadly paralleling tissue-specificity. Surprisingly, they can be accurately modelled just based on local nucleotide-sequence context. Combining EN-TEx with existing genome annotations reveals strong associations between allele-specific and GWAS loci and enables models for transferring known eQTLs to difficult-to-profile tissues. Overall, EN-TEx provides rich data and generalizable models for more accurate personal functional genomics.

genomics↗

bioRxiv2021

Anatomical and Functional Gradients Shape Dynamic Functional Connectivity in the Human Brain

Large-scale biophysical circuit models can provide mechanistic insights into the fundamental micro-scale and macro-scale properties of brain organization that shape complex patterns of spontaneous brain activity. By allowing local synaptic properties to vary across brain regions, recent large-scale circuit models have demonstrated better fit to empirical observations, such as inter-regional synchrony averaged over several minutes, i.e. static functional connectivity (FC). However, most previous models do not capture how inter-regional synchrony patterns vary over timescales of seconds, i.e., time-varying FC dynamics. Here we developed a spatially-heterogeneous large-scale dynamical circuit model that allowed for variation in local circuit properties across the human cortex. We showed that parameterizing local circuit properties with both anatomical and functional gradients was necessary for generating realistic static and dynamical properties of resting-state fMRI activity. Furthermore, empirical and simulated FC dynamics demonstrated remarkably similar sharp transitions in FC patterns, suggesting the existence of multiple attractors. We found that time-varying regional fMRI amplitude tracked multi-stability in FC dynamics. Causal manipulation of the large-scale circuit model suggested that sensory-motor regions were a driver of FC dynamics. Finally, the spatial distribution of sensory-motor drivers matched the principal gradient of gene expression that encompassed certain interneuron classes, suggesting that heterogeneity in excitation-inhibition balance might shape multi-stability in FC dynamics.

neuroscience↗

bioRxiv2021

Auxin-triggered changes in the Arabidopsis root tip (phospho)proteome reveal novel root growth regulators

Auxin plays a dual role in growth regulation and, depending on the tissue and concentration of the hormone, it can either promote or inhibit division and expansion processes in plants. Recent studies revealed that, beyond transcriptional reprogramming, alternative auxin-controlled mechanisms regulate root growth. Here, we explored the impact of different auxin concentrations on the root tip proteome and phosphoproteome, generating a unique resource. From the phosphoproteome data we pinpointed (novel) growth regulators, such as the RALF34-THE1 module. Our results together with previously published studies suggest that auxin, H+-ATPases, cell wall modifications and cell wall sensing receptor-like kinases are tightly embedded in a pathway regulating cell elongation. Furthermore, our study assigned a novel role to MKK2 as a regulator of primary root growth and a (potential) regulator of auxin biosynthesis and signalling, and suggests the importance of the MKK2 Thr31 phosphorylation site for growth regulation in the Arabidopsis root tip. ONE SENTENCE SUMMARYAn auxin-triggered Arabidopsis root tip (phospho)proteome reveals novel root growth regulators

plant biology↗

bioRxiv2020

1RS.1BL molecular resolution provides novel contributions to wheat improvement

Wheat-rye 1RS.1BL translocation has a significant impact on wheat yield and hence food production globally. However, the genomic basis of its contributions to wheat improvement is undetermined. Here, we generated a high-quality assembly of 1RS.1BL translocation comprising 748,715,293 bp with 4,996 predicted protein-coding genes. We found the size of 1RS is larger than 1BS with the active centromere domains shifted to the 1RS side instead of the 1BL side in Aikang58 (AK58). The gene alignment showed excellent synteny with 1BS from wheat and genes from 1RS were expressed well in wheat especially for 1RS where expression was higher than that of 1BS for the grain-20DPA stage associated with greater grain weight and negative flour quality attributes. A formin-like-domain protein FH14 (TraesAK58CH1B01G010700) was important in regulating cell division. Two PPR genes were most likely the genes for the multi fertility restoration locus Rf multi. Our data not only provide the high-resolution structure and gene complement for the 1RS.1BL translocation, but also defined targets for enhancing grain yield, biotic and abiotic stress, and fertility restoration in wheat.

genomics↗

bioRxiv2020

Targeting KRAS-mutant stomach/colorectal tumours by disrupting the ERK2-p53 complex

KRAS is widely mutated in human cancers, resulting in nearly unchecked tumour proliferation and metastasis. No therapies have been developed for targeting KRAS-mutant tumours. Herein, we observed that mutant KRAS specifically promoted the formation of ERK2-p53 complex in stomach/colorectal tumour cells. Disruption of this complex by applying MEK1/2 and ERK2 inhibitors elicits strong apoptotic responses in a p53-dependent manner, validated by genome-wide knockout screening. Mechanistically, p53 physically associates with phosphorylated ERK2 through the hydrophobic interaction in the presence of mutant KRAS, which suppresses p53 activation by preventing the recruitment of p300/CBP; trametinib disrupts the ERK2-p53 complex by reducing ERK2 phosphorylation, allowing the acetylation of p53 protein by recruiting p300/CBP; acetylated p53 activates PUMA transcription and thereby kills KRAS-mutant tumours. Our study unveils an important role of the ERK2-p53 complex and provides a potential therapeutic strategy for treating KRAS-mutant cancer via ERK2 inhibition.

cancer biology↗

bioRxiv2020

IP-MS Analysis of ESX-5 and ESX-1 Substrates Enables Mycobacterial Species Identification

Pulmonary disease resulting from non-tuberculous mycobacteria (NTM) infection has emerged as an increasingly prevalent clinical entity in the past two to three decades, but there are no standardized, commercial assays available for the molecular diagnosis of NTM infections from clinical samples. Herein we discuss the development of an assay that employs immunoprecipitation coupled with mass spectrometry (IP-MS) to rapidly and accurately discriminate prevalent slow-growing mycobacterial species (i.e., M. avium and M. intracellulare, M. kansasii, M. gordonae, M. marinum and M. tuberculosis) during early growth in mycobacterial growth indicator tube (MGIT) cultures. This IP-MS assay employs antibodies specific for conserved tryptic peptides of M. tuberculosis EsxN (AQAASLEAEHQAIVR) and CFP-10 (TQIDQVESTAGSLQGQWR) to capture and identify specific mycobacterial species and allows species-specific mycobacterium identification at the first sign of MGIT culture positivity.

microbiology↗

bioRxiv2020

Relationship of DUX4 and target gene expression in FSHD myocytes

Facioscapulohumeral dystrophy (FSHD) is linked to misexpression of the transcription factor, DUX4. Although DUX4 target gene expression is often readily detectable, analysis of DUX4 expression has been limited due to its low expression in patient samples. Recently, single cell/nucleus RNA-sequencing was used to detect the native expression of DUX4 for the first time, but important spatial relationships with its target gene expression was missing. Furthermore, dynamics of DUX4 expression during myoblast differentiation has not been fully explored. In order to study the spatiotemporal relationship of DUX4 and key target genes, we performed RNA FISH on immortalized FSHD2 patient skeletal muscle cells. Using two probe sets, DUX4 transcripts were detected in 1-4% of myotubes after 3-day differentiation in vitro. We found that DUX4 transcripts mainly localize as foci in one or two nuclei in a myotube compared to abundant accumulation of the target gene transcripts in the cytoplasm. Over a 13-day differentiation timecourse, DUX4 expression without target gene expression significantly increased and peaked at day 7. Target gene expression correlates better with DUX4 expression early in differentiation while the expression of target genes without detectable DUX4 transcripts increases later. Consistently, shRNA depletion of DUX4-activated transcription factors, DUXA and LEUTX, specifically repressed a DUX4-target gene, KDM4E, later in differentiation, suggesting that following the initial activation by DUX4, target genes themselves contribute to the maintenance of downstream gene expression. Together, in situ detection of the DUX4 and target gene transcripts provided new insight into dynamics of DUX4 transcriptional network in FSHD patient myocytes. Significance StatementFSHD is the third most common muscular dystrophy and is associated with upregulation of DUX4, a transcription factor, and its target genes. Although target genes are easily detectable in FSHD, low frequency DUX4 upregulation in patient myocytes is difficult to detect, and examining the relationship and dynamics of DUX4 and target gene expression without artificial overexpression of DUX4 has been challenging. Using RNAScope with highly specific probes, we detect the endogenous DUX4 and target gene transcripts in situ in patient skeletal myotubes during differentiation in vitro. Our study reveals a unique DUX4 expression pattern and its relationship to the expression of target genes, and evidence for self-sustainability of the target gene network. The study provides important new insights into the FSHD disease mechanism.

genetics↗

bioRxiv2020

The SUMO E3 Ligase SIZ1 Positively Regulates Active DNA Demethylation by Stabilizing ROS1 in Arabidopsis thaliana

The 5-methylcytosine DNA glycosylase/lyase REPRESSOR OF SILENCING 1 (ROS1)-mediated active DNA demethylation is critical for shaping the genomic DNA methylation landscape in Arabidopsis. Whether and how the stability of ROS1 may be regulated by post-translational modifications is unknown. Using a methylation-sensitive PCR (CHOP-PCR)-based forward genetic screen for Arabidopsis DNA hypermethylation mutants, we identified the SUMO E3 ligase SIZ1 as a critical regulator of active DNA demethylation. Dysfunction of SIZ1 leads to hyper-methylation at approximately one thousand genomic regions. SIZ1 physically interacts with ROS1 and mediates the SUMOylation of ROS1. The SUMOylation of ROS1 is reduced in siz1 mutant plants. Compared to that in wild type plants, the protein level of ROS1 is significantly decreased, even though there is an increased level of ROS1 transcripts in siz1 mutant plants. Our results suggest that SIZ1 positively regulates active DNA demethylation by promoting the stability of ROS1 protein through SUMOylation. Short SummaryThe 5-methylcytosine DNA glycosylase/lyase REPRESSOR OF SILENCING 1 (ROS1) is indispensable for proper DNA methylation landscape in Arabidopsis. Whether and how the stability of ROS1 may be regulated by post-translational modifications is unknown. Here, we show that SIZ1-mediated SUMOylation of ROS1 enhances its stability and positively regulates active DNA demethylation.

plant biology↗

bioRxiv2020

DNA damage induced during mitosis undergoes DNA repair synthesis

Understanding the mitotic DNA damage response (DDR) is critical to our comprehension of cancer, premature aging and developmental disorders which are marked by DNA repair deficiencies. In this study we use a micro-focused-laser to induce DNA damage in selected mitotic chromosomes to study the subsequent repair response. Our findings demonstrate that (1) mitotic cells are capable of DNA repair as evidenced by DNA synthesis at damage sites, (2) Repair is attenuated when DNA-PKcs and ATM are simultaneously compromised, (3) Laser damage may permit the observation of previously undetected DDR proteins when damage is elicited by other methods in mitosis, and (4) Twenty five percent of mitotic DNA-damaged cells undergo a subsequent mitosis. Together these findings suggest that mitotic DDR is more complex than previously thought and may involve factors from multiple repair pathways that are better understood in interphase.

cell biology↗

bioRxiv2019

TopicNet: a framework for measuring transcriptional regulatory network change

Next generation sequencing data highlights comprehensive and dynamic changes in the human gene regulatory network. Moreover, changes in regulatory network connectivity (network "rewiring") manifest different regulatory programs in multiple cellular states. However, due to the dense and noisy nature of the connectivity in regulatory networks, directly comparing the gains and losses of targets of key TFs is not that informative. Thus, here, we seek a abstracted lower-dimensional representation to understand the main features of network change. In particular, we propose a method called TopicNet that applies latent Dirichlet allocation (LDA) to extract meaningful functional topics for a collection of genes regulated by a TF. We then define a rewiring score to quantify the large-scale changes in the regulatory network in terms of topic change for a TF. Using this framework, we can pinpoint particular TFs that change greatly in network connectivity between different cellular states. This is particularly relevant in oncogenesis. Also, incorporating gene-expression data, we define a topic activity score that gives the degree that a topic is active in a particular cellular state. Furthermore, we show how activity differences can highlight differential survival in certain cancers.

bioinformatics↗

bioRxiv2019

Bayesian modelling of high-throughput sequencing assays with malacoda

NGS studies have uncovered an ever-growing catalog of human variation while leaving an enormous gap between observed variation and experimental characterization of variant function. High-throughput screens powered by NGS have greatly increased the rate of variant functionalization, but the development of comprehensive statistical methods to analyze screen data has lagged behind. In the massively parallel reporter assay (MPRA), short barcodes are counted by sequencing DNA libraries transfected into cells and output RNA in order to simultaneously measure the shifts in transcription induced by thousands of genetic variants. These counts present many statistical challenges, including over-dispersion, depth dependence, and uncertain DNA concentrations. So far, the statistical methods used have been rudimentary, employing transformations on count level data and disregarding experimental and technical structure while failing to quantify uncertainty in the statistical model.\n\nWe have developed an extensive framework for the analysis of NGS functionalization screens available as an R package called malacoda (available from github.com/andrewGhazi/malacoda). Our software implements a probabilistic, fully Bayesian model of screen data. The model uses the negative binomial distribution with gamma priors to model sequencing counts while accounting for effects from input library preparation and sequencing depth. The method leverages the high-throughput nature of the assay to estimate the priors empirically. External annotations such as ENCODE data or DeepSea predictions can also be incorporated to obtain more informative priors - a transformative capability for data integration. The package also includes quality control and utility functions, including automated barcode counting and visualization methods.\n\nTo validate our method, we analyzed several datasets datasets using malacoda and alternative MPRA analysis methods. These data include experiments from the literature, simulated assays, and primary MPRA data. We also used luciferase assays to experimentally validate the strongest hits from our primary data, as well as variants for which the various methods disagree and variants detectable only with the aid of external annotations.\n\nAuthor SummaryGenetic sequencing technology has progressed rapidly in the past two decades. Huge genomic characterization studies have resulted in a massive quantity of background information across the entire genome, including catalogs of observed human variation, gene regulation features, and computational predictions of genomic function. Meanwhile, new types of experiments use the same sequencing technology to simultaneously test the impact of thousands of mutations on gene regulation. While the design of experiments has become increasingly complex, the data analysis methods deployed have remained overly simplistic, often relying on summary measures that discard information. Here we present a statistical framework called for the analysis of massively parallel genomic experiments designed to incorporate prior information in an unbiased way. We validate our method by comparing our method to alternatives on simulated and real datasets, by using different types of assays that provide a similar type of information, and by closely inspecting an example experimental result that only our method detected. We also present the methods accompanying software package which provides and end-to-end pipeline that provides a simple interface for data preparation, analysis, and visualization.

bioinformatics↗

bioRxiv2019

Handedness and Other Variables Associated with Human Brain Asymmetrical Skew

The human cerebral hemispheres show a left-right asymmetrical torque pattern, which has been claimed to be absent in chimpanzees. The functional significance and developmental mechanisms are unknown. Here we carried out the largest-ever analysis of global brain shape asymmetry in magnetic resonance imaging data. Three population datasets were used, the UK Biobank (N = 39,678), Human Connectome Project (N = 1,113) and BIL&GIN (N = 453). At the population level, there was an anterior and dorsal skew of the right hemisphere, relative to the left. Both skews were associated independently with handedness, and various regional grey and white matter metrics oppositely in the two hemispheres, as well as other variables related to cognitive functions, sociodemographic factors, and physical and mental health. The two skews showed SNP-based heritabilities of 4-13%, but also substantial polygenicity in causal mixture model analysis, and no individually significant loci were found in GWAS for either skew. There was evidence for a significant genetic correlation (rg=-0.40, p=0.0075) between horizontal brain skew and Autism Spectrum Disorder. These results provide the first large-scale description of population-average brain skews and their inter-individual variations, their replicable associations with handedness, and insights into biological and other factors which associate with human brain asymmetry.

neuroscience↗

bioRxiv2019

Convergent genomic signatures of high altitude adaptation among domestic mammals

Abundant and diverse domestic mammals living on the Tibetan Plateau provide useful materials for investigating adaptive evolution and genetic convergence. Here, we utilized 327 genomes from horses, sheep, goats, cattle, pigs and dogs living at both high and low altitudes, including 73 genomes generated for this study, to disentangle the genetic mechanisms underlying local adaptation of domestic mammals. Although molecular convergence is comparatively rare at the DNA sequence level, we found convergent signature of positive selection at the gene level, particularly EPAS1 gene in these Tibetan domestic mammals. We also reported a potential function in response to hypoxia for the gene C10orf67, which underwent positive selection in three of the domestic mammals. Our data provides insight into adaptive evolution of high-altitude domestic mammals, and should facilitate the search for additional novel genes involved in the hypoxia response pathway.

evolutionary biology↗

bioRxiv2019

An integrative ENCODE resource for cancer genomics

ENCODE comprises thousands of functional genomics datasets, and the encyclopedia covers hundreds of cell types, providing a universal annotation for genome interpretation. However, for particular applications, it may be advantageous to use a customized annotation. Here, we develop such a custom annotation by leveraging advanced assays, such as eCLIP, Hi-C, and whole-genome STARR-seq on a number of data-rich ENCODE cell types. A key aspect of this annotation is comprehensive and experimentally derived networks of both transcription factors and RNA-binding proteins (TFs and RBPs). Cancer, a disease of system-wide dysregulation, is an ideal application for such a network-based annotation. Specifically, for cancer-associated cell types, we put regulators into hierarchies and measure their network change (rewiring) during oncogenesis. We also extensively survey TF-RBP crosstalk, highlighting how SUB1, a previously uncharacterized RBP, drives aberrant tumor expression and amplifies the effect of MYC, a well-known oncogenic TF. Furthermore, we show how our annotation allows us to place oncogenic transformations in the context of a broad cell space; here, many normal-to-tumor transitions move towards a stem-like state, while oncogene knockdowns show an opposing trend. Finally, we organize the resource into a coherent workflow to prioritize key elements and variants, in addition to regulators. We showcase the application of this prioritization to somatic burdening, cancer differential expression and GWAS. Targeted validations of the prioritized regulators, elements and variants using siRNA knockdowns, CRISPR-based editing, and luciferase assays demonstrate the value of the ENCODE resource.

genomics↗

bioRxiv2019

The cohesin loader NIPBL interacts with pre-ribosomal RNA and treacle to regulate ribosomal RNA synthesis

NIPBL is an essential loader of cohesin to mediate sister chromatid cohesion and chromatin loop organization. NIPBL mutations cause Cornelia de Lange Syndrome. How NIPBLs genomic localization is specified is not fully understood. We found that NIPBL localizes to the nucleolus in an RNA-dependent manner and binds directly to ribosomal RNA (rRNA). We identified two RNA binding domains in NIPBL in vitro, both of which are required for efficient rRNA binding in vivo. NIPBL binds to ribosomal DNA (rDNA) in an RNA-stimulated manner, recruits PAF1 and promotes pre-rRNA transcription. Stress that inhibits rRNA synthesis displaces NIPBL from the nucleolus and rDNA. Interestingly, treacle, mutated in Treacher Collins syndrome, tightly binds to and recruits NIPBL to the nucleolus, nucleolar organizer regions, and the stress-induced nucleolar cap. The results reveal that a subpopulation of NIPBL is recruited to the nucleolus through its interaction with RNA and treacle and regulates pre-rRNA transcription.

molecular biology↗