Biology subjects

Zhou, X.

Publications and source records attributed to Zhou, X..

At least 757 records · Page 42Linked to original sources

bioRxiv2018

Endoplasmic reticulum stress may activate NLRP3 inflammasomes via TXNIP in preeclampsia

Preeclampsia (PE) development is often associated with placental immune and inflammatory dysregulation, as well as endoplasmic reticulum (ER) stress. However, the mechanisms linking ER stress and inflammatory dysregulation to PE have not been clarified. It has been reported that thioredoxin-interacting protein (TXNIP), which can bind with and activate the NLR family pyrin domain containing 3 (NLRP3) inflammasome, plays a critical role in immune regulation. Recent experimental evidence suggests that activated NLRP3 inflammasomes can activate interleukin-1{beta} (IL-1{beta}) production in the placenta of patients with PE. The objective of the current study was to explore if TXNIP plays a critical signaling role linking ER stress with NLRP3 inflammasome activation in PE. We hypothesised that ER stress would induce TXNIP production, which would bind with NLRP3 inflammasomes to activate IL-1{beta} production. HTR8/SVneo cells were subjected to six hours hypoxia followed by six hours reoxygenation (H/R). These cells showed a higher protein level of NLRP3 and IL-1{beta}, as well as a higher enzymatic activity of caspase-1, indicating enhanced inflammatory dysregulation and ER stress. Cells transfected with TXNIP siRNA showed reduced NLRP3 inflammasome activation. Cells treated with 4-phenylbutyric acid, an inhibitor of ER stress, showed a similar result. In addition, the outgrowth of explant with TXNIP lentivirus in H/R or Tunicamycin (inducers of ER stress) was also measured to verify our hypothesis. These findings demonstrated that TXNIP could influence inflammatory dysregulation by mediating ER stress and NLRP3 inflammasome activation in PE. This novel mechanism may further explain the inflammation observed at the maternal-fetal interface, which leads to placental dysfunction in a patient with PE.

cell biology↗

bioRxiv2018

Modulation of mutant KrasG12D-driven lung tumorigenesis in vivo by gain or loss of PCDH7 function

PROTOCADHERIN 7 (PCDH7), a transmembrane receptor and member of the Cadherin superfamily, is frequently overexpressed in lung adenocarcinoma and is associated with poor clinical outcome. While PCDH7 was recently shown to promote transformation and facilitate brain metastasis in lung and breast cancers, decreased PCDH7 expression has also been documented in colorectal, gastric, and invasive bladder cancers. These data suggest context-dependent functions for PCDH7 in distinct tumor types. Given that PCDH7 is a potentially targetable molecule on the surface of cancer cells, further investigation of its role in tumorigenesis in vivo is needed to evaluate the therapeutic potential of its inhibition. Here we report the analysis of novel PCDH7 gain- and loss-of-function mouse models and provide compelling evidence that this cell-surface protein acts as a potent lung cancer driver. Employing a Cre-inducible transgenic allele, we demonstrated that enforced PCDH7 expression significantly accelerates KrasG12D-driven lung tumorigenesis and potentiates MAPK pathway activation. Furthermore, we performed in vivo somatic genome editing with CRISPR/Cas9 in KrasLSL-G12D; Tp53fl/fl (KP) mice to assess the consequences of PCDH7 loss of function. Inactivation of PCDH7 in KP mice significantly reduced lung tumor development, prolonged survival, and diminished phospho-activation of ERK1/2. Together, these findings establish a critical oncogenic function for PCDH7 in vivo and highlight the therapeutic potential of PCDH7 inhibition for lung cancer. Moreover, given recent reports of elevated or reduced PCDH7 in distinct tumor types, the new inducible transgenic model described here provides a robust experimental system for broadly elucidating the effects of PCDH7 overexpression in vivo.\n\nAUTHOR SUMMARYLung cancer is the leading cause of cancer-associated deaths worldwide. PROTOCADHERIN 7 (PCDH7), cell surface protein and member of the Cadherin superfamily, is frequently overexpressed in lung adenocarcinomas and is associated with poor clinical outcome. Nevertheless, it has yet to be shown in vivo whether PCDH7 plays a role in the initiation and progression of lung cancer, and whether it represents an actionable therapeutic target. Here we demonstrate, using a novel transgenic mouse model, that PCDH7 overexpression accelerates KrasG12D-driven lung tumorigenesis. Furthermore, we validate PCDH7 as a therapeutic target by knocking it out using in vivo somatic genome editing in the KrasLSL-G12D; Tp53fl/fl (KP) model. Our results provide new insight into the mechanisms that drive lung cancer pathogenesis and, because targeting oncogenic cell-surface proteins with antibodies has proven to be a highly effective anti-cancer therapeutic strategy, establish a new target for cancer treatment. Moreover, given recent reports of elevated or reduced PCDH7 in distinct tumor types, the transgenic PCDH7 model described here provides a robust experimental system for elucidating the effects of PCDH7 overexpression in different in vivo settings. This model will also provide an ideal system for future testing of therapeutics directed at PCDH7.

cancer biology↗

bioRxiv2018

Corilagin controls post-parasiticide schistosome egg-induced liver fibrosis by inhibiting Stat6 signalling pathway

This study aims to explore the effect of Corilagin (Cor) on post-parasiticide schistosome egg-induced hepatic fibrosis through the Stat6 signalling pathway in vitro and in vivo. Cellular and animal models were established and treated by Corilagin. The inhibitory effect of Corilagin was also confirmed in RAW264.7 cells in which Stat6 was overexpressed based on the GV367-Stat6-EGFP lentiviral vector system and in which Stat6 was knock-downed by gene specific siRNAs. As a result, Corilagin prevented increases in the protein level of Phospho-Stat6 (P-Stat6). Both the mRNA and protein levels of the downstream mediators SOCS1, KLF4, and PPAR{gamma}/{delta} were markedly suppressed after Corilagin treatment. Expression of ARG1 and FIZZ1/Retnla, Ym1, TGF-{beta} and PDGF in serum were also inhibited by Corilagin. The pathological changes, area of granulomas of liver sections, and degree of hepatic fibrosis were significantly alleviated in the Corilagin group. The areas of CD68- and CD206-positive cells stained by immunofluorescence were significantly decreased by Corilagin. In conclusion, Corilagin can suppress post-parasiticide schistosome egg-induced hepatic fibrosis by inhibiting the Stat6 signalling pathway and provide a new therapeutic strategy for schistosomiasis liver fibrosis.

pharmacology and toxicology↗

bioRxiv2018

Pediatric Cancer Variant Pathogenicity Information Exchange (PeCanPIE): A Cloud-based Platform for Curating and Classifying Germline Variants

Variant interpretation in the era of next-generation sequencing (NGS) is challenging. While many resources and guidelines are available to assist with this task, few integrated end-to-end tools exist. Here we present \"PeCanPIE\" - the Pediatric Cancer Variant Pathogenicity Information Exchange, a web- and cloud-based platform for annotation, identification, and classification of variations in known or putative disease genes. Starting from a set of variants in Variant Call Format (VCF), variants are annotated, ranked by putative pathogenicity, and presented for formal classification using a decision-support interface based on published guidelines from the American College of Medical Genetics and Genomics (ACMG). The system can accept files containing millions of variants and handle single-nucleotide variants (SNVs), simple insertions/deletions (indels), multiple-nucleotide variants (MNVs), and complex substitutions. PeCanPIE has been applied to classify variant pathogenicity in cancer predisposition genes in two large-scale investigations involving >4,000 pediatric cancer patients, and serves as a repository for the expert-reviewed results. While PeCanPIEs web-based interface was designed to be accessible to non-bioinformaticians, its back end pipelines may also be run independently on the cloud, facilitating direct integration and broader adoption. PeCanPIE is publicly available and free for research use.

bioinformatics↗

bioRxiv2018

Subset-Based Analysis using Gene-Environment Interactions for Discovery of Genetic Associations across Multiple Studies or Phenotypes

ObjectivesClassical methods for combining summary data from genome-wide association studies (GWAS) only use marginal genetic effects and power can be compromised in the presence of heterogeneity. We aim to enhance the discovery of novel associated loci in the presence of heterogeneity of genetic effects in sub-groups defined by an environmental factor.\n\nMethodsWe present a p-value Assisted Subset Testing for Associations (pASTA) framework that generalizes the previously proposed association analysis based on subsets (ASSET) method by incorporating gene-environment (G-E) interactions into the testing procedure. We conduct simulation studies and provide two data examples.\n\nResultsSimulation studies show that our proposal is more powerful than methods based on marginal associations in the presence of G-E interactions and maintains comparable power even in their absence. Both data examples demonstrate that our method can increase power to detect overall genetic associations and identify novel studies/phenotypes that contribute to the association.\n\nConclusionsOur proposed method can be a useful screening tool to identify candidate single nucleotide polymorphisms (SNPs) that are potentially associated with the trait(s) of interest for further validation. It also allows researchers to determine the most probable subset of traits that exhibit genetic associations in addition to the enhancement of power.

genetics↗

bioRxiv2018

Trans-ethnic polygenic analysis supports genetic overlaps of lumbar disc degeneration with height, body mass index, and bone mineral density

Lumbar disc degeneration (LDD) is age-related break-down in the fibrocartilaginous joints between lumbar vertebrae. It is a major cause of low back pain and is conventionally assessed by magnetic resonance imaging (MRI). Like most other complex traits, LDD is likely polygenic and influenced by both genetic and environmental factors. However, genome-wide association studies (GWASs) of LDD have uncovered few susceptibility loci due to the limited sample size. Previous epidemiology studies of LDD also reported multiple heritable risk factors, including height, body mass index (BMI), bone mineral density (BMD), lipid levels, etc. Genetics can help elucidate causality between traits and suggest loci with pleiotropic effects. One such approach is polygenic score (PGS) which summarizes the effect of multiple variants by the summation of alleles weighted by estimated effects from GWAS. To investigate genetic overlaps of LDD and related heritable risk factors, we calculated the PGS of height, BMI, BMD and lipid levels in a Chinese population-based cohort with spine MRI examination and a Japanese case-control cohort of lumbar disc herniation (LDH) requiring surgery. Because most large-scale GWASs were done in European populations, PGS of corresponding traits were created using weights from European GWASs. We calibrated their prediction performance in independent Chinese samples, then tested associations with MRI-derived LDD scores and LDH affection status. The PGS of height, BMI, BMD and lipid levels were strongly associated with respective phenotypes in Chinese, although phenotype variances explained were lower than in Europeans which would reduce the power to detect genetic overlaps. Despite of this, the PGS of BMI and lumbar spine BMD were significantly associated with LDD scores; and the PGS of height was associated with the increased the liability of LDH. Furthermore, linkage disequilibrium score regression suggested that, osteoarthritis, another degenerative disorder that shares common features with LDD, also showed genetic correlations with height, BMI and BMD. The findings suggest a common key contribution of biomechanical stress to the pathogenesis of LDD and will direct the future search for pleiotropic genes.

genetics↗

bioRxiv2018

Bacillus cereus HS24 Suppresses Conidia Germination of Magnaporthe oryzae by Inhibiting the Ca2+ Signaling Pathway

Rice yield is greatly reduced due to rice blast, a worldwide multi-cycle fungal disease caused by the ascomycete Magnaporthe oryzae. Previously, Bacillus cereus HS24 was isolated from rice growing area, which showed a strong bio-control effect on M. oryzae. In order to better exploit it as a bio-control agent, HS24 has been studied for its mechanism of controlling rice blast. Our results showed that conidial germination of M. oryzae was significantly inhibited by HS24 suspension, n and the inhibition rate reached to 97.83% at the concentration of 10 CFU/ml. The transcriptional level of CAMKII, PMC1 and CCH1, which are key genes involved in Ca2+ signaling pathway, were significantly decreased in HS24-treated conidia. The treatment of M. oryzae with Ca2+ signaling pathway inhibitors KN-93, Verapamil, and cyclopiazonic acid (CPA) significantly reduced conidial germination rate and inhibited germ tube elongation. This inhibition effect was found to be concentration-dependent, similar to the HS24 treatment. By quantifying free Ca2+ in M. oryzae conidia, a significant reduction of intracellular free Ca2+ concentration in HS24-treated conidia in comparison to sterile water-treated conidia was found. The addition of exogenous Ca2+ did not abolish the inhibitory effect of HS24 on the reduction of intracellular free Ca2+ concentration and conidial germination. In conclusion, B. cereus HS24 can inhibit conidial germination by suppressing Ca2+ signaling in M. oryzae, and thus offers a great potential as a bio-control agent in rice blast management.\n\nImportanceIn the bio-control of rice blast, most of researches focused on the inhibitory effect of bio-control agents on development of M. oryzae, including inhibition of conidia germination, germ tube deformity, mycelium growth inhibition, etc, while little work has elucidated the molecular mechanisms underlying the various phenotypic change in M. oryzae. In order to better exploit HS24 as a potential bio-control agent, we studied the molecular mechanisms underlying the suppression of B. cereus HS24 on M. oryzae Guy11, and draw the conclusion that HS24 may inhibit conidia germination and germ tube elongation through inhibiting the Ca2+ signaling pathway. In this study, we characterized the morphological and physiological changes of M. oryzae when interacting with B. cereus HS24, and further investgated the responses of M. oryzae Ca2+ signallig pathway to HS24 treatment. Thus we have provided one more piece for the B. cereus / M. oryzae supression puzzle at the molecular level.

microbiology↗

bioRxiv2018

Cell cycle-controlled clearance of the CcrM DNA methyltransferase by Lon is dependent on DNA-facilitated proteolysis and substrate polar sequestration

N6-adenine methylation catalyzed by the DNA methyltransferase CcrM is an essential epigenetic event of the Caulobacter cell cycle. Limiting CcrM to a specific time period during the cell cycle relies on temporal control of ccrM transcription and CcrM proteolysis. We investigated how Lon, a protease from AAA+ superfamily conserved from bacteria to humans, temporally degrades CcrM to maintain differential chromosomal methylation state, thereby regulating transcription factor synthesis and enabling cell cycle progression. We demonstrate that CcrM degradation by Lon requires DNA as an adaptor for robust proteolysis. Lon, a DNA-bound protein, is constitutively active throughout the cell cycle, but allows CcrM mediated DNA methylation only when CcrM is transcribed and translated upon completion of DNA replication. An additional mechanism to limit CcrM activity to a narrow window of the cell cycle is its sequestration to the pole of the progeny stalked cell, which prevents physical contact with DNA-bound Lon. Thus, we have provided evidence for a novel mechanism for substrate selection by the Lon protease, providing robust cell cycle control mediated by DNA methylation.

molecular biology↗

bioRxiv2018

Structure of the receptor-activated human TRPC6 ion channel

TRPC6 is a receptor-activated nonselective cation channel that belongs to the family of canonical transient receptor potential (TRPC) channels. It is activated by diacylglycerol, a lipid second messenger. TRPC6 is involved in many physiological processes and implicated in human genetic diseases. Here we present the structure of human TRPC6 homotetramer in complex with a newly identified high affinity inhibitor BTDM solved by single-particle cryo-electron microscopy to 3.8 [A] resolution. The structure shows a two-layer architecture, in which the bell-shaped cytosolic layer holds the transmembrane layer. Extensive inter-subunit interactions of cytosolic domain, including N terminal ankyrin repeats and C terminal coiled-coil, contribute to the tetramer assembly. The high affinity inhibitor BTDM wedges between S5-S6 pore domain and voltage sensor-like domain to inhibit channel opening. Our structure uncovers the molecular architecture of TRPC channels and provides a structural basis for understanding the mechanism of these channels.

biophysics↗

bioRxiv2018

Pleiotropic Mapping and Annotation Selection in Genome-wide Association Studies with Pe-nalized Gaussian Mixture Models

MotivationGenome-wide association studies (GWASs) have identified many genetic loci associated with complex traits. A substantial fraction of these identified loci are associated with multiple traits - a phenomena known as pleiotropy. Identification of pleiotropic associations can help characterize the genetic relationship among complex traits and can facilitate our understanding of disease etiology. Effective pleiotropic association mapping requires the development of statistical methods that can jointly model multiple traits with genome-wide SNPs together.\n\nResultsWe develop a joint modeling method, which we refer to as the integrative MApping of Pleiotropic association (iMAP). iMAP models summary statistics from GWASs, uses a multivariate Gaussian distribution to account for phenotypic correlation, simultaneously infers genome-wide SNP association pattern using mixture modeling, and has the potential to reveal causal relationship between traits. Importantly, iMAP integrates a large number of SNP functional annotations to substantially improve association mapping power, and, with a sparsity-inducing penalty, is capable of selecting informative annotations from a large, potentially noninformative set. To enable scalable inference of iMAP to association studies with hundreds of thousands of individuals and millions of SNPs, we develop an efficient expectation maximization algorithm based on an approximate penalized regression algorithm. With simulations and comparisons to existing methods, we illustrate the benefits of iMAP both in terms of high association mapping power and in terms of accurate estimation of genome-wide SNP association patterns. Finally, we apply iMAP to perform a joint analysis of 48 traits from 31 GWAS consortia together with 40 tissue-specific SNP annotations generated from the Roadmap Project. iMAP is freely available at www.xzlab.org/software.html.

bioinformatics↗

bioRxiv2018

miRNAs play important roles in aroma weakening during the shelf life of ‘Nanguo’ pear after cold storage

Cold storage is commonly employed to delay senescence in Nanguo pears after harvest. However, this technique also causes fruit aroma weakening. MicroRNAs play important roles in plant development and in eliciting responses to abiotic environmental stressors. In this study, the miRNA transcript profile of the fruit at the first day (C0, LT0) move in and out of cold storage and the optimum tasting period (COTP, LTOTP) during shelf life at room temperature were analyzed, respectively. More than 300 known miRNAs were identified in Nanguo pears; 176 and 135 miRNAs were significantly differentially expressed on the C0 vs. LT0 and on the COTP vs. LTOTP, respectively. After prediction the target genes of these miRNAs, LOX2S, LOX1_5, HPL, and ADH1 were found differentially expressed, which were the key genes during aroma formation. The expression pattern of these target genes and the related miRNAs were identified by RT-PCR. Mdm-miR172a-h, mdm-miR159a/b/c, mdm-miR160a-e, mdm-miR395a-i, mdm/ppe-miR399a, mdm/ppe-miR535a/b, and mdm-miR7120a/b negatively regulated target gene expression. These results indicate that miRNAs play key roles in aroma weakening in refrigerated Nanguo pear and provide valuable information for studying the molecular mechanisms of miRNAs in the aroma weakening of fruits due to cold storage.

molecular biology↗

bioRxiv2018

Spatial gradient in activity within the insula reflects dissociable neural mechanisms underlying context-dependent advantageous and disadvantageous inequity aversion

Humans are capable of integrating social contextual information into decision-making processes to adjust their attitudes towards inequity. This context-dependency emerges both when individual is better off (i.e. advantageous inequity) and worse off (i.e. disadvantageous inequity) than others. It is not clear however, whether the context-dependent processing of advantageous and disadvantageous inequity rely on dissociable or shared neural mechanisms. Here, by combining an interpersonal interactive game that gave rise to interpersonal guilt and different versions of the dictator games that enabled us to characterize individual weights on aversion to advantageous and disadvantageous inequity, we investigated the neural mechanisms underlying the two forms of inequity aversion in the interpersonal guilt context. In each round, participants played a dot-estimation task with an anonymous co-player. The co-players received pain stimulation with 50% probability when anyone responded incorrectly. At the end of each round, participants completed a dictator game, which determined payoffs of him/herself and the co-player. Both computational model-based and model-free analyses demonstrated that when inflicting pain upon co-players (i.e., the guilt context), participants cared more about advantageous inequity and became less sensitive to disadvantageous inequity, compared with other social contexts. The contextual effects on two forms of inequity aversion are uncorrelated with each other at the behavioral level. Neuroimaging results revealed that the context-dependent representation of inequity aversion exhibited a spatial gradient in activity within the insula, with anterior parts predominantly involved in the aversion to advantageous inequity and posterior parts predominantly involved in the aversion to disadvantageous inequity. The dissociable mechanisms underlying the two forms of inequity aversion are further supported by the involvement of right dorsolateral prefrontal cortex and dorsomedial prefrontal cortex in advantageous inequity processing, and the involvement of right amygdala and dorsal anterior cingulate cortex in disadvantageous inequity processing. These results extended our understanding of decision-making processes involving inequity and the social functions of inequity aversion.

neuroscience↗

bioRxiv2018

Identifying and exploiting trait-relevant tissues with multiple functional annotations in genome-wide association studies

Genome-wide association studies (GWASs) have identified many disease associated loci, the majority of which have unknown biological functions. Understanding the mechanism underlying trait associations requires identifying trait-relevant tissues and investigating associations in a trait-specific fashion. Here, we extend the widely used linear mixed model to incorporate multiple SNP functional annotations from omics studies with GWAS summary statistics to facilitate the identification of trait-relevant tissues, with which to further construct powerful association tests. Specifically, we rely on a generalized estimating equation based algorithm for parameter inference, a mixture modeling framework for trait-tissue relevance classification, and a weighted sequence kernel association test constructed based on the identified trait-relevant tissues for powerful association analysis. We refer to our analytic procedure as the Scalable Multiple Annotation integration for trait-Relevant Tissue identification and usage (SMART). With extensive simulations, we show how our method can make use of multiple complementary annotations to improve the accuracy for identifying trait-relevant tissues. In addition, our procedure allows us to make use of the inferred trait-relevant tissues, for the first time, to construct more powerful SNP set tests. We apply our method for an in-depth analysis of 43 traits from 28 GWASs using tissue-specific annotations in 105 tissues derived from ENCODE and Roadmap. Our results reveal new trait-tissue relevance, pinpoint important annotations that are informative of trait-tissue relationship, and illustrate how we can use the inferred trait-relevant tissues to construct more powerful association tests in the Wellcome trust case control consortium study.\n\nAuthor SummaryIdentifying trait-relevant tissues is an important step towards understanding disease etiology. Computational methods have been recently developed to integrate SNP functional annotations generated from omics studies to genome-wide association studies (GWASs) to infer trait-relevant tissues. However, two important questions remain to be answered. First, with the increasing number and types of functional annotations nowadays, how do we integrate multiple annotations jointly into GWASs in a trait-specific fashion to take advantage of the complementary information contained in these annotations to optimize the performance of trait-relevant tissue inference? Second, what to do with the inferred trait-relevant tissues? Here, we develop a new statistical method and software to make progress on both fronts. For the first question, we extend the commonly used linear mixed model, with new algorithms and inference strategies, to incorporate multiple annotations in a trait-specific fashion to improve trait-relevant tissue inference accuracy. For the second question, we rely on the close relationship between our proposed method and the widely-used sequence kernel association test, and use the inferred trait-relevant tissues, for the first time, to construct more powerful association tests. We illustrate the benefits of our method through extensive simulations and applications to a wide range of real data sets.

bioinformatics↗

bioRxiv2017

A systems approach to refine disease taxonomy by integrating phenotypic and molecular networks

The International Classification of Diseases (ICD) relies on clinical features and lags behind the current understanding of the molecular specificity of disease pathobiology, necessitating approaches that incorporate growing biomedical data for classifying diseases to meet the needs of precision medicine. Our analysis revealed that the heterogeneous molecular diversity of disease chapters and the blurred boundary between disease categories in ICD should be further investigated. Here, we propose a new classification of diseases (NCD) by developing an algorithm that predicts the additional categories of a disease by integrating multiple networks consisting of disease phenotypes and their molecular profiles. With statistical validations from phenotype-genotype associations and interactome networks, we demonstrate that NCD improves disease specificity owing to its overlapping categories and polyhierarchical structure. Furthermore, NCD captures the molecular diversity of diseases and defines clearer boundaries in terms of both phenotypic similarity and molecular associations, establishing a rational strategy to reform disease taxonomy.

bioinformatics↗

bioRxiv2017

Genetic analysis of de novo variants reveals sex differences in complex and isolated congenital diaphragmatic hernia and indicates MYRF as a candidate gene

Congenital diaphragmatic hernia (CDH) is one of the most common and lethal birth defects. Previous studies using exome sequencing support a significant contribution of coding de novo variants in complex CDH cases with additional anomalies and likely gene-disrupting (LGD) variants in isolated CDH cases. To further investigate the genetic architecture of CDH, we performed exome or genome sequencing in 283 proband-parent trios. Combined with data from previous studies, we analyzed a total of 357 trios, including 148 complex and 209 isolated cases. Complex and isolated cases both have a significant burden of deleterious de novo coding variants (1.7~fold, p= 1.2x10-5 for complex, 1.5~fold, p= 9.0x10-5 for isolated). Strikingly, in isolated CDH, almost all of the burden is carried by female cases (2.1~fold, p=0.004 for likely gene disrupting and 1.8~fold, p= 0.0008 for damaging missense variants); whereas in complex CDH, the burden is similar in females and males. Additionally, de novo LGD variants in complex cases are mostly enriched in genes highly expressed in developing diaphragm, but distributed in genes with a broad range of expression levels in isolated cases. Finally, we identified a new candidate risk gene MYRF (4 de novo variants, p-value=2x10-10), a transcription factor intolerant of mutations. Patients with MYRF mutations have additional anomalies including congenital heart disease and genitourinary defects, likely representing a novel syndrome.

genomics↗

bioRxiv2017

Forward-reverse mutation cycles between stages of cancer development

Earlier, prominent occurrences of interstitial loss-of-heterozygosities (LOHs) were found in different cancers as a type of single-nucleotide-variations (SNVs), at rates far exceeding those of the commonly investigated gain-of-heterozygosities (GOHs) type of SNVs. Herein, such co-occurrences of LOHs and GOHs were confirmed in 102 cases of four cancer types analyzed with three different next-generation sequencing platforms, comparing non-tumor, paratumor, and tumor tissues with white-blood-cell controls; and in 246 pan-cancer cases of whole-genome tumor-control pairs. Unexpectedly, large numbers of SNVs enriched with CG>TG GOHs and copy-number-variations (CNVs) proximal to these GOHs were detected in the non-tumor tissues, which were extensively reversed in paratumors showing prominent TG>CG LOHs with proximal CNVs, and less so in tumors to form forward-reverse mutation cycles. Lineage effects in the reversions, likely resulting from directional selection, supported a sequential rather than parallel mode of evolution as described in a Stage Specific Populations model of cancer development.

cancer biology↗

bioRxiv2017

Deep learning of the splicing (epi)genetic code reveals a novel candidate mechanism linking histone modifications to ESC fate decision

Alternative splicing (AS) is a genetically and epigenetically regulated pre-mRNA processing to increase transcriptome and proteome diversity. Comprehensively decoding these regulatory mechanisms holds promise in getting deeper insights into a variety of biological contexts involving in AS, such as development and diseases. We assembled splicing (epi)genetic code, DeepCode, for human embryonic stem cell (hESC) differentiation by integrating heterogeneous features of genomic sequences, 16 histone modifications with a multi-label deep neural network. With the advantages of epigenetic features, DeepCode significantly improves the performance in predicting the splicing patterns and their changes during hESC differentiation. Meanwhile, DeepCode reveals the superiority of epigenomic features and their dominant roles in decoding AS patterns, highlighting the necessity of including the epigenetic properties when assembling a more comprehensive splicing code. Moreover, DeepCode allows the robust predictions across cell lineages and datasets. Especially, we identified a putative H3K36me3-regulated AS event leading to a nonsense-mediated mRNA decay of BARD1. Reduced BARD1 expression results in the attenuation of ATM/ATR signalling activities and further the hESC differentiation. These results suggest a novel candidate mechanism linking histone modifications to hESC fate decision. In addition, when trained in different contexts, DeepCode can be expanded to a variety of biological and biomedical fields.

bioinformatics↗

bioRxiv2017

Integrated transcriptome and epigenome analyses identify alternative splicing as a novel candidate linking histone modifications to embryonic stem cell fate decision

BackgroundUnderstanding the embryonic stem cell (ESC) fate decision between self-renewal and proper differentiation is important for developmental biology and regenerative medicine. Attention has focused on mechanisms involving histone modifications, alternative pre-mRNA splicing, and cell-cycle progression. However, their intricate interrelations and joint contributions to ESC fate decision remain unclear.\n\nResultsWe analyze the transcriptomes and epigenomes of human ESC and five types of differentiated cells. We identify thousands of alternatively spliced exons and reveal their development and lineage-dependent characterizations. Several histone modifications show dynamic changes in alternatively spliced exons and three are strongly associated with 52.8% of alternative splicing events upon hESC differentiation. The histone modification-associated alternatively spliced genes predominantly function in G2/M phases and ATM/ATR-mediated DNA damage response pathway for cell differentiation, whereas other alternatively spliced genes are enriched in the G1 phase and pathways for self-renewal. These results imply a potential epigenetic mechanism by which some histone modifications contribute to ESC fate decision through the regulation of alternative splicing in specific pathways and cell-cycle genes. Supported by experimental validations and extended dataset from Roadmap/ENCODE projects, we exemplify this mechanism by a cell cycle-related transcription factor, PBX1, which regulates the pluripotency regulatory network by binding to NANOG. We suggest that the isoform switch from PBX1a to PBX1b links H3K36me3 to hESC fate determination through the PSIP1/SRSF1 adaptor, which results in the exon skipping of PBX1.\n\nConclusionWe reveal the mechanism by which alternative splicing links histone modifications to stem cell fate decision.

bioinformatics↗