Biology subjects

Zheng, D.

Publications and source records attributed to Zheng, D..

6 recordsLinked to original sources

bioRxiv2018

GREB1 amplifies androgen receptor output in prostate cancer and contributes to antiandrogen resistance

Genomic amplification of the androgen receptor (AR) is an established mechanism of antiandrogen resistance in prostate cancer. Here we show that the magnitude of AR signaling output, independent of AR genomic alteration or expression level, also contributes to antiandrogen resistance, through upregulation of the coactivator GREB1. We demonstrate 100-fold heterogeneity in AR output within cell lines and show that cells with high AR output have reduced sensitivity to enzalutamide. Through transcriptomic and shRNA knockdown studies, together with analysis of clinical datasets, we identify GREB1 as a gene responsible for high AR output. We show that GREB1 is an AR target gene that amplifies AR output by enhancing AR DNA binding and promoting p300 recruitment. GREB1 knockdown in high AR output cells restores enzalutamide sensitivity in vivo. Thus, GREB1 is a candidate driver of enzalutamide resistance through a novel feed forward mechanism.

cancer biology↗

bioRxiv2018

Spatiotemporal Gene Coexpression and Regulation in Mouse Cardiomyocytes of Early Cardiac Morphogenesis

Cardiac looping is an early morphogenic process critical for the formation of four-chambered mammalian hearts. To study the roles of signaling pathways, transcription factors (TFs) and genetic networks in the process, we constructed gene co-expression networks and identified gene modules highly activated in individual cardiomyocytes (CMs) at multiple anatomical regions and developmental stages. Function analyses of the module genes uncovered major pathways important for spatiotemporal CM differentiation. Interestingly, about half of the pathways were highly active in cardiomyocytes at outflow tract (OFT) and atrioventricular canal (AVC), including many well-known signaling pathways for cardiac development and several newly identified ones. Most of the OFT-AVC pathways were predicted to be regulated by 6 6 transcription factors (TFs) actively expressed at the OFT-AVC locations, with the prediction supported by motif enrichment analysis of the TF targets, including 10 TFs that have not been previously associated with cardiac development, e.g., Etv5, Rbpms, and Baz2b. Finally, our study showed that the OFT-AVC TF targets were significantly enriched with genes associated with mouse heart developmental abnormalities and human congenital heart defects.

genetics↗

bioRxiv2018

SMARTcleaner: identify and clean off-target signals in SMART ChIP-seq analysis

BackgroundNoises and artifacts may arise in several steps of the next-generation sequencing (NGS) process. Recently, a NGS library preparation method called SMART, or Switching Mechanism At the 5 end of the RNA Transcript, is introduced to prepare ChIP-seq (chromatin immunoprecipitation and deep sequencing) libraries from small amount of DNA material. The protocol adds Ts to the 3 end of DNA templates, which is subsequently recognized and used by SMART poly(dA) primers for reverse transcription and then addition of PCR primers and sequencing adapters. The poly(dA) primers, however, can anneal to poly(T) sequences in a genome and amplify DNA fragments that are not enriched in the immunoprecipitated DNA templates. This off-target amplification results in false signals in the ChIP-seq data.\n\nResultsHere, we show that the off-target ChIP-seq reads derived from false amplification of poly(T/A) genomic sequences have unique and strand-specific features. Accordingly, we develop a tool (called \"SMARTcleaner\") that can exploit the features to remove SMART ChIP-seq artifacts. Application of SMARTcleaner to several SMART ChIP-seq datasets demonstrates that it can remove reads from off-target amplification effectively, leading to improved ChIP-seq peaks and results.\n\nConclusionsSMARTcleaner could identify and clean the false signals in SMART-based ChIP-seq libraries, leading to improvement in peak calling, and downstream data analysis and interpretation.

bioinformatics↗

bioRxiv2018

Computational model of chimeric antigen receptors explains site-specific phosphorylation kinetics

Chimeric antigen receptors (CARs) have recently been approved for the treatment of hematological malignancies, but our lack of understanding of the basic mechanisms that activate these proteins has made it difficult to optimize and control CAR-based therapies. In this study, we use phospho-proteomic mass spectrometry and mechanistic computational modeling to quantify the in vitro kinetics of individual tyrosine phosphorylation on a variety of CARs. We show that each of the ten tyrosine sites on the CD28-CD3{zeta} CAR is phosphorylated by LCK with distinct kinetics. The addition of CD28 at the N-terminal of CD3{zeta} increases the overall rate of CD3{zeta} phosphorylation. Our computational model identifies that LCK phosphorylates CD3{zeta} through a mechanism of competitive inhibition. This model agrees with previously published data in the literature and predicts that phosphatases in this system interact with CD3{zeta} through a similar mechanism of competitive inhibition. This quantitative modeling framework can be used to better understand CAR signaling and T cell activation.

systems biology↗

bioRxiv2017

Enriched expression of genes associated with autism spectrum disorders in human inhibitory neurons

Autism spectrum disorder (ASD) is highly heritable but genetically heterogeneous. The affected neural circuits and cell types remain unclear and may vary at different developmental stages. By analyzing multiple sets of human single cell transcriptome profiles, we found that ASD candidates showed enriched gene expression in neurons, especially in inhibitory neurons. ASD candidates were also more likely to be the hubs of the co-expressed module that is highly expressed in inhibitory neurons, a feature not detected for excitatory neurons. In addition, we found that upregulated genes in multiple ASD cortex samples were also enriched with genes highly expressed in inhibitory neurons, suggesting a potential increase of inhibitory neurons and an imbalance in the ratio between excitatory and inhibitory neurons. Furthermore, the downstream targets of several ASD candidates, such as CHD8, EHMT1 and SATB2, also displayed enriched expression in inhibitory neurons. Taken together, our analysis of single cell transcriptomic data suggest that inhibitory neurons may be the major neuron subtype affected by the disruption of ASD gene networks, providing single cell functional evidence to support the excitatory/inhibitory (E/I) imbalance hypothesis.

genetics↗

bioRxiv2016

Genetic overlap between in-scanner head motion and the default network connectivity

The association between in-scanner head motion and intrinsic functional connectivity (iFC) may confound explanations for individual differences in functional connectomics. However, the etiology of the correlation between head motion and iFC has not been established. This study aimed to investigate genetic and environmental contributions on the association between head motion and iFC using a twin dataset (175 same-sex twin pairs, aged 14-23 years, 48% females). After establishing that both head motion and default network iFC are moderately heritable, we found large genetic correlations (-0.52 to -0.73) between head motion and the default network iFCs. Common genes can explain 48% - 61% of the negative phenotypic correlation between the two phenotypes. These results advance our understanding of the relationship between head motion and iFC, and may have profound implications for interpreting individual differences in default network connectivity in clinical research and brain-behavior association.

neuroscience↗