Biology subjects

Chang, J.

Publications and source records attributed to Chang, J..

11 recordsLinked to original sources

bioRxiv2018

eQTL network analysis reveals that regulatory genes are evolutionarily older and bearing more types of PTM sites in Coprinopsis cinerea

Understanding the DNA variation in regulation of carbohydrate-active enzymes (CAZymes) is fundamental to the use of wood-decaying basidiomycetes in lignocellulose conversion into renewable energy. Our goal is to identify the regulators of lignocellulolytic enzymes in Coprinopsis cinerea, of which the genome harbors high number of Auxiliary Activities enzymes.\n\nThe DNA sequence of C. cinerea family including 46 single spore isolates (SSIs) from crosses of two homozygous strains are used to develop a panel of SNP markers. Then the RNA sequence were used to characterize the gene expression profiles. The RNA were extracted from cultures grown on softwood-enriched sawdust to induce lignocellulolytic enzymes and CCR de-repression genes. To assess the genetic contribution to enzyme expression variations among the 46 SSIs, associations between SNPs and gene expressions were examined genome-widely. 5148 local eQTLs and 7738 distant eQTLs were obtained. By analyzing these eQTLs, the potential regulatory factors of the CAZymes expression and the de-repression of Carbon Catabolism Repression (CCR) were identified.\n\nThe eQTL network is characterized in terms of hotspots, evolutionary age and post-translational modifications (PTMs). In the eQTL network of C. cinerea, the non-regulatory genes are younger than the regulatory genes. The proteins regulated by combinational multiple types of PTMs are more likely to function as super regulatory hotspots in protein-protein interactions. The evolutionary age analysis and the PTMome analysis could serve as alternative methods to identify master regulators from genomic data.\n\nThis work demonstrates a comprehensive bioinformatics approach to identify regulatory factors with next-generation sequencing data. The results provide candidate genes for bioengineering to increase the enzyme production, which will practically benefit the bioethanol production from lignocellulose.\n\nSignificanceThis eQTL analysis is designed to study the fungal CAZymes and carbon catabolism repression, especially during the mycelium stage.\n\nO_LIIn Coprinopsis cinerea, only the regions near two ends of the chromosomes have high recombination rate, and suitable for family based eQTL analysis.\nC_LIO_LIA sugar transporter is a hotspot controlling many CCR genes.\nC_LIO_LICAZymes are not regulated by a master regulator, but by individual regulators. This indicates that CAZymes are under specific regulatory pathways, so can response to specific conditions.\nC_LIO_LIIn the eQTL network, the rGenes are evolutionarily older, with more types of PTM sites than eGenes.\nC_LIO_LIIn the eQTL network, the proteins with more types of PTM sites are more likely associated with Information Storage and Processing, and act as super-hub in the network.\nC_LI

bioinformatics↗

bioRxiv2018

Non-driver somatic alteration burden confers good prognosis in non-small cell lung cancer

BackgroundGenomic profiling of patient tumors has linked somatic driver mutations to survival outcomes of non-small cell lung cancer (NSCLC) patients, especially for those receiving targeted therapies. However, it remains unclear whether specific non-driver mutations have any prognostic utility.\n\nMethodsWhole exomes and transcriptomes were measured from NSCLC xenograft models of patients with diverse clinical outcomes. Penalised regression analysis was performed to identify a set of 865 genes associated with patient survival. The number of somatic copy number aberrations, point mutations and associated expression changes within the 865 genes were used to stratify independent NSCLC patient populations, filtered for chemotherapy naive and early-stage. In-depth genomic analysis and functional testing was conducted on the genomic alterations to understand their effect on improving survival.\n\nResultsHigh burden of somatic alterations are associated with longer disease-free survival (HR=0.153, P=1.48x10-4) in NSCLC patients. When somatic alterations burden was integrated with gene expression, we were able to predict prognosis in three independent patient datasets. Patients with high alteration burden could be further stratified based on the presence of immunogenic mutations, revealing another subgroup of patients with even better prognosis (85% with >5 years survival), and associated with cytotoxic T-cell expression. In addition, 95% of these 865 genes lack documented activity relevant to cancer, but are in pathways regulating cell proliferation, motility and immune response were implicated.\n\nConclusionOur results demonstrate that non-driver somatic alterations may influence the outcome of cancer patients by increasing beneficial immune response and inhibiting processes associated to tumorigenesis.

cancer biology↗

bioRxiv2018

Protection of circadian rhythms by the protein folding chaperone, BiP

ER stress and dysregulation of collagen synthesis are associated with progression of disease in cancer and fibrosis. Collagen synthesis is co-ordinated with the circadian clock, which curiously in cancer cells, is deregulated by ER stress. We hypothesised that interplay exists between circadian rhythm, collagen synthesis and ER stress in normal cells. Here we show that fibroblasts with ER stress do not demonstrate circadian rhythms in gene expression upon clock-synchronizing time cues. Conversely, overexpression of BiP or treatment with chemical chaperones strengthens the oscillation amplitude of circadian rhythms. The significance of these findings was explored in tendon, where we showed that BiP expression is ramped preemptively prior to a surge in collagen synthesis at night, thereby preventing protein misfolding and ER stress. In turn, we propose, this forestalls activation of the unfolded protein response in order for circadian rhythms to be maintained. Thus, targeting ER stress could be used to modulate circadian rhythm and restore collagen homeostasis in disease.

cell biology↗

bioRxiv2018

Collagen assembly and turnover imaged with a CRISPR-Cas9 engineered Dendra2 tag

Electron microscopy has been the \"gold standard\" for studying collagen networks but dynamic information on how cells synthesise the networks has been lacking. Live imaging methods have been unable to distinguish newly-synthesised fibrils from pre-existing fibrils and intracellular collagen. Here, we tagged endogenous collagen-I using CRISPR-Cas9 with photoswitchable Dendra2 and demonstrate live cells synthesising, migrating on, and interacting with, collagen fibrils. This strategy is applicable for other long half-life proteins.

cell biology↗

bioRxiv2018

Circadian Clock Regulation of the Secretory Pathway

Collagen is the most abundant secreted protein in vertebrates that persists throughout life without renewal. The unchanging nature of collagen contrasts with observed continued collagen synthesis throughout adulthood and with conventional transcriptional and translational homeostatic mechanisms that replace damaged proteins with new copies. Here we show circadian clock regulation of procollagen transport from ER-to-Golgi and Golgi-to-plasma membrane by sequential rhythmic expression of SEC61, TANGO1, PDE4D and VPS33B. The result is nocturnal procollagen synthesis and daytime collagen fibril assembly in mice. Rhythmic collagen degradation by CTSK maintains collagen homeostasis. This circadian cycle of collagen synthesis, assembly and degradation affects only a pool of newly-synthesized collagen whilst maintaining the persistent collagen network. Disabling the circadian clock causes collagen accumulation and abnormal fibrils in vivo. In conclusion, our study has identified a circadian clock mechanism of protein homeostasis in which a sacrificial pool of collagen is synthesized and removed to maintain tissue function.

cell biology↗

bioRxiv2018

Intellectual phenotypes in autism strongly correlate with gene dosage changes and exon locations of truncating mutations

Autism spectrum disorders (ASD) are a group of related neurodevelopmental diseases displaying significant genetic and phenotypic heterogeneity1-4. Despite recent progress in understanding ASD genetics, the nature of phenotypic heterogeneity across probands remains unclear5, 6. Notably, likely gene-disrupting (LGD) de novo mutations affecting the same gene often result in substantially different ASD phenotypes. Nevertheless, we find that truncating mutations that affect the same exon frequently lead to strikingly similar intellectual phenotypes in unrelated ASD probands. Analogous patterns are observed for two independent proband cohorts and several other important ASD-associated phenotypes. We find that exons biased towards prenatal and postnatal expression preferentially contribute to ASD cases with lower and higher IQ phenotypes, respectively. These results suggest that exons, rather than genes, often represent a unit of effective phenotypic impact for truncating mutations in autism. The observed phenotypic effects are likely mediated by nonsense-mediated decay (NMD) of splicing isoforms, with autism phenotypes usually triggered by relatively mild (15-30%) decreases in overall gene dosage. We find that each gene with recurrent ASD mutations can be described by a parameter, phenotype dosage sensitivity (PDS), which characterizes the quantitative relationship between changes in a genes dosage and changes in a given disease phenotype. We further demonstrate analogous relationships between LGD mutations and changes in gene expression across human tissues. Therefore, similar phenotypic patterns may be also observed in multiple other systems and genetic disorders.

genetics↗

bioRxiv2018

Programmable single and multiplex base-editing in Bombyx mori using RNA-guided cytidine deaminases

Standard genome editing tools (ZFN, TALEN and CRISPR/Cas9) edited genome depending on DNA double strand breaks (DSBs). A series of new CRISPR tools that convert cytidine to thymine (C to T) without the requirement for DNA double-strand breaks were developed recently, which have changed this status and have been quickly applied in a variety of organisms. Here, we demonstrate that CRISPR/Cas9-dependent base editor (BE3) converts C to T with a high frequency in the invertebrate Bombyx mori silkworm. Using BE3 as a knock-out tool, we inactivated exogenous and endogenous genes through base-editing-induced nonsense mutations with an efficiency of up to 66.2%. Furthermore, genome-scale analysis showed that 96.5% of B. mori genes have one or more targetable sites being knocked out by BE3 with a median of 11 sites per gene. The editing window of BE3 reached up to 13 bases (from C1 to C13 in the range of gRNA) in B. mori. Notably, up to 14 bases were substituted simultaneously in a single DNA molecule, with a low indel frequency of 0.6%, when 32 gRNAs were co-transfected. Collectively, our data show for the first time that RNA-guided cytidine deaminases are capable of programmable single and multiplex base-editing in an invertebrate model.

genetics↗

bioRxiv2017

PyBoost: A parallelized Python implementation of 2D boosting with hierarchies

Motivation: Gene expression is controlled by networks of transcription factors that bind specific sequence motifs in regulatory DNA elements such as promoters and enhancers. GeneClass is a boosting-based algorithm that learns gene regulatory networks from complementary paired feature sets such as transcription factor expression levels and binding motifs across conditions. This algorithm can be used to predict functional genomics measures of cell state, such as gene expression and chromatin accessibility, in different cellular conditions. We present a parallelized, Python-based implementation of GeneClass, called PyBoost, along with a novel hierarchical implementation of the algorithm, called HiBoost. HiBoost allows regulatory logic to be constrained to a hierarchical group of conditions or cell types. The software can be used to dissect differentiation cascades, time courses or other perturbation data that naturally form a hierarchy or trajectory. We demonstrate the application of PyBoost and HiBoost to learn regulators of tadpole tail regeneration and hematopoeitic stem cell differentiation and validate learned regulators through an inducible CRISPR system.\n\nAvailability: The implementation is publicly available here: https://github.com/kundajelab/boosting2D/.

bioinformatics↗

bioRxiv2017

Morphological And Transcriptomic Evidence For Ammonium Induction Of Sexual Reproduction In Thalassiosira pseudonana And Other Centric Diatoms

The reproductive strategy of diatoms includes asexual and sexual phases, but in many species, including the model centric diatom Thalassiosira pseudonana, sexual reproduction has never been observed. Furthermore, the environmental factors that trigger sexual reproduction in diatoms are not understood. Although genome sequences of a few diatoms are available, little is known about the molecular basis for sexual reproduction. Here we show that ammonium reliably induces the key sexual morphologies, including oogonia, auxospores, and spermatogonia, in two strains of T. pseudonana, T. weissflogii, and Cyclotella cryptica. RNA sequencing revealed 1,274 genes whose expression patterns changed when T. pseudonana was induced into sexual reproduction by ammonium. Some of the induced genes are linked to meiosis or encode flagellar structures of heterokont and cryptophyte algae. The identification of ammonium as an environmental trigger suggests an unexpected link between diatom bloom dynamics and strategies for enhancing population genetic diversity.

microbiology↗

bioRxiv2017

Inferring intracellular signal transduction circuitry from molecular perturbation experiments

The development of network inference methodologies that accurately predict connectivity in dysregulated pathways may enable the rational selection of patient therapies. Accurately inferring an intracellular network from data remains a very challenging problem in molecular systems biology. Living cells integrate extremely robust circuits that exhibit significant heterogeneity, but still respond to external stimuli in predictable ways. This phenomenon allows us to introduce a network inference methodology that integrates measurements of protein activation from perturbation experiments. The methodology relies on logic-based networks to provide a predictive approximation of the transfer of signals in a network. The approach presented was validated in silico with a set of test networks and applied to investigate the epidermal growth factor receptor signaling of a breast epithelial cell line, MFC10A. In our analysis, we predict the potential signaling circuitry most likely responsible for the experimental readouts of several proteins in the mitogen activated protein kinase and phosphatidylinositol-3 kinase pathways. The approach can also be used to identify additional necessary perturbation experiments to distinguish between a set of possible candidate networks.

systems biology↗

bioRxiv2016

Methods for detecting co-mutated pathways in cancer samples to inform treatment selection

Tumor genomes evolve through a selection of mutations. These mutations may complement each other to promote tumorigenesis. To better understand the functional interactions of different processes in cancer, we studied mutation data of a set of tumors and identified significantly co-mutated pathways. Fishers exact test is a standard approach that can be used to assess the significance of the joint dysregulation of pathways pairs across a patient population. We developed a robust test to identify co-occurrence using DNA mutations, which overcomes deficiencies of the Fishers exact test by taking into account the large variability in overall mutation load and sequencing depth. Applying our method to a study of six common cancer types, we identify enrichment of co-mutated signal transduction pathways such as IP3 synthesis and PI3K and pairs of co-mutated pathways involving other processes such as immunity and development. We observed enrichment of clonal co-mutation of the proteasome and apoptosis pathways in colorectal cancer, which suggests potential mechanisms for immune evasion.

bioinformatics↗