ATP-dependent chromatin remodeling complexes regulate nucleosome organizations. In Drosophila, gene Brm encodes the core Brahma complex, the ATPase subunit of SWI/SNF class of chromatin remodelers. Its role in modulating the nucleosome landscape in vivo is unclear. In this study, we knocked down Brm in Drosophila third instar larvae to explore the changes in nucleosome profiles and global gene transcription. The results show that Brm knockdown leads to nucleosome occupancy changes throughout the entire genome with a bias in occupancy decrease. In contrast, the knockdown has limited impacts on nucleosome position shift. The knockdown also alters another important physical property of nucleosome positioning, fuzziness. Nucleosome position shift, gain or loss and fuzziness changes are all enriched in promoter regions. Nucleosome arrays around the 5' ends of genes are reorganized in five patterns as a result of Brm knockdown. Intriguingly, the concomitant changes in the genes adjacent to the Brahma-dependent remodeling regions have important roles in development and morphogenesis. Further analyses reveal abundance of AT-rich motifs for transcription factors in the remodeling regions.
LIF/Stat3 signaling is critical for maintaining the self-renewal and differentiation potential of mouse embryonic stem cells (mES cells). However, the upstream effectors of this pathway have not been clearly defined. Here, we show that periodic tryptophan protein 1 (Pwp1), a WD-40 repeat-containing protein associated with histone H4 modification, is required for the exit of mES cells from the pluripotent state into all lineages. Knockdown of Pwp1 does not affect mES cell proliferation, self-renewal or apoptosis. However, knockdown of Pwp1 impairs the differentiation potential of mES cells both in vitro and in vivo. PWP1 ChIP-seq results revealed that the PWP1-occupied regions were marked with significant levels of H4K20me3. Moreover, Pwp1 binds to sites in the upstream region of Stat3. Knockdown of Pwp1 decreases the level of H4K20me3 in the upstream region of Stat3 gene and upregulates the expression of Stat3. Furthermore, Pwp1 knockdown (KD) mES cells recover their differentiation potential through suppressing the expression of Stat3 or inhibiting the tyrosine phosphorylation of STAT3. Together, our results suggest that Pwp1 plays important roles in the differentiation potential of mES cells. Stem Cells 2014.
Bisphenol A (BPA) is an environmental endocrine disruptor which has been detected in human bodies. Many studies have implied that BPA exposure is harmful to human health. Previous studies mainly focused on BPA effects on estrogen receptor (ER)-positive cells. Genome-wide impacts of BPA on gene expression in ER-negative cells is unclear. In this study, we performed RNA-seq to characterize BPA-induced cellular and molecular impacts on ER-negative HEK293 cells. The microscopic observation showed that low-dose BPA exposure did not affect cell viability and morphology. Gene expression profiling analysis identified a list of differentially expressed genes in response to BPA exposure in HEK293 cells. These genes were involved in variable important biological processes including ion transport, cysteine metabolic process, apoptosis, DNA damage repair, etc. Notably, BPA up-regulated the expression of ERCC5 encoding a DNA endonuclease for nucleotide-excision repair. Further electrochemical experiment showed that BPA induced significant DNA damage in ER-positive MCF-7 cells but not in ER-negative HEK293 cells. Collectively, our study revealed that ER-negative HEK293 cells employed mechanisms in response to BPA exposure different from ER-positive cells.
Polybrominated diphenyl ethers (PBDEs) are widely used as flame-retardant additives in consumer and household products and can escape into the environment over time. PBDEs have become a global environmental organic pollutant due to the properties of persistence, toxicity, and bioaccumulation. The well-studied toxic effects of PBDEs mainly include thyroid hormone disruption and neurotoxicity. There is no consistent conclusions on the carcinogenic potential of PBDEs to date. Here, we explored the toxic effects of BDE-209 on human embryonic kidney cells (HEK293T). The comparison of the gene expression profiles of HEK293T cells with BDE-209 treatment and the negative control found that BDE-209 exposure may alter nucleosome organization through significantly changing the expression of histone gene clusters. The remodeled chromatin structure could further disturb systemic lupus erythematosus as one of the toxic effects of BDE-209. Additionally, gene sets of different cancer modules are positively correlated with BDE-209 exposure. This suggests that BDE-209 has carcinogenic potential for a variety of tumors. Collectively, BDE-209 has a broader toxicity not limited to disruption of thyroid hormone-related biological processes. Notably, the toxic effects of BDE-209 dissolved in dimethyl sulfoxide (DMSO) is not the simply additive effects of BDE-209 and DMSO alone.
Previous phylogenetic analyses have led to incongruent evolutionary relationships between tree shrews and other suborders of Euarchontoglires. What caused the incongruence remains elusive. In this study, we identified 6845 orthologous genes between seventeen placental mammals. Tree shrews and Primates were monophyletic in the phylogenetic trees derived from the first or/and second codon positions whereas tree shrews and Glires formed a monophyly in the trees derived from the third or all codon positions. The same topology was obtained in the phylogeny inference using the slowly and fast evolving genes, respectively. This incongruence was likely attributed to the fast substitution rate in tree shrews and Glires. Notably, sequence GC content only was not informative to resolve the controversial phylogenetic relationships between tree shrews, Glires, and Primates. Finally, estimation in the confidence of the tree selection strongly supported the phylogenetic affiliation of tree shrews to Primates as a monophyly.
Trypanosoma brucei is a unicellular flagellated eukaryotic parasite that causes African trypanosomiasis in human and domestic animals with devastating health and economic consequences. Recent studies have revealed the important roles of the single flagellum of T. brucei in many aspects, especially that the flagellar motility is required for the viability of the bloodstream form T. brucei, suggesting that impairment of the flagellar function may provide a promising cure for African sleeping sickness. Knowing the flagellum proteome is crucial to study the molecular mechanism of the flagellar functions. Here we present a novel computational method for identifying flagellar proteins in T. brucei, called trypanosome flagellar protein predictor (TFPP). TFPP was developed based on a list of selected discriminating features derived from protein sequences, and could predict flagellar proteins with ?92% specificity at a ?84% sensitivity rate. Applied to the whole T. brucei proteome, TFPP reveals 811 more flagellar proteins with high confidence, suggesting that the flagellar proteome covers ?10% of the whole proteome. Comparison of the expression profiles of the whole T. brucei proteome at three typical life cycle stages found that ?45% of the flagellar proteins were significantly changed in expression levels between the three life cycle stages, indicating life cycle stage-specific regulation of flagellar functions in T. brucei. Overall, our study demonstrated that TFPP is highly effective in identifying flagellar proteins and could provide opportunities to study the trypanosome flagellar proteome systematically. Furthermore, the web server for TFPP can be freely accessed at http:/wukong.tongji.edu.cn/tfpp.
Protein turnover metabolism plays important roles in cell cycle progression, signal transduction, and differentiation. Those proteins with short half-lives are involved in various regulatory processes. To better understand the regulation of cell process, it is important to study the key sequence-derived factors affecting short-lived protein degradation. Until now, most of protein half-lives are still unknown due to the difficulties of traditional experimental methods in measuring protein half-lives in human cells. To investigate the molecular determinants that affect short-lived proteins, a computational method was proposed in this work to recognize short-lived proteins based on sequence-derived features in human cells. In this study, we have systematically analyzed many features that perhaps correlated with short-lived protein degradation. It is found that a large fraction of proteins with signal peptides and transmembrane regions in human cells are of short half-lives. We have constructed an SVM-based classifier to recognize short-lived proteins, due to the fact that short-lived proteins play pivotal roles in the control of various cellular processes. By employing the SVM model on human dataset, we achieved 80.8% average sensitivity and 79.8% average specificity, respectively, on ten testing dataset (TE1-TE10). We also obtained 89.9%, 99% and 83.9% of average accuracy on an independent validation datasets iTE1, iTE2 and iTE3 respectively. The approach proposed in this paper provides a valuable alternative for recognizing the short-lived proteins in human cells, and is more accurate than the traditional N-end rule. Furthermore, the web server SProtP (http://reprod.njmu.edu.cn/sprotp) has been developed and is freely available for users.
There are two main mechanisms of miRNA-mediated gene silencing: either mRNA degradation or translational repression. However, the precise mechanism of target mRNAs regulated by miRNA remains unclear. As a complementary approach to experiment, a computational method was proposed to recognize the mechanism of miRNA-mediated gene silencing in human. We have analyzed extensive features correlated with miRNA-mediated silencing mechanism of mRNA. It is found that, the duplex structure, the number of binding sites and the structural accessibility of target site region are effective factors in determining whether a target mRNA is cleaved or only translationally inhibited. An SVM-based classifier was constructed to predict the regulation mode of miRNA based on these informative features. The results indicated that the approach proposed is effective in distinguishing whether a target mRNA is cleaved or translationally inhibited in human. Furthermore, the web server microDoR (http://reprod.njmu.edu.cn/microdor) has been developed and is freely available for users.
It has long been known that trypanosomes regulate mitochondrial biogenesis during the life cycle of the parasite; however, the mitochondrial protein inventory (MitoCarta) and its regulation remain unknown. We present a novel computational method for genome-wide prediction of mitochondrial proteins using a support vector machine-based classifier with ?90% prediction accuracy. Using this method, we predicted the mitochondrial localization of 468 proteins with high confidence and have experimentally verified the localization of a subset of these proteins. We then applied a recently developed parallel sequencing technology to determine the expression profiles and the splicing patterns of a total of 1065 predicted MitoCarta transcripts during the development of the parasite, and showed that 435 of the transcripts significantly changed their expressions while 630 remain unchanged in any of the three life stages analyzed. Furthermore, we identified 298 alternatively splicing events, a small subset of which could lead to dual localization of the corresponding proteins.
MicroRNAs (miRNAs) are a class of small non-coding RNAs discovered in recent years, which are found to play important regulatory roles in various organisms. As the number of experimentally validated miRNAs is rapidly increasing, systematic analysis on the characteristics of these known miRNAs is necessary and indispensable, especially for computational prediction of new miRNAs. We extensively analyzed precursor sequences for all experimentally validated mature miRNAs in metazoan species, focusing on the characteristics at the level of primary sequences and secondary structures. An observation over the secondary structures of 2729 miRNA precursors (pre-miRNAs) reveals that these hairpin structures can be approximately classified into two types: one with a hairpin loop, and the other with multiple loops. Interestingly, the two types of pre-miRNAs show significant differences in both sequence and structure characteristics, and our study indicates that separate consideration on each type of pre-miRNAs is more reasonable, especially in computational prediction. Besides, we develop a new criterion called mAMFE which shows robust discriminative power in distinguishing pre-miRNAs against other RNAs, thus can potentially serve as a discriminative feature in prediction of new pre-miRNAs.
Computational analysis of microarray data has provided an effective way to identify disease-related genes. Traditional disease gene selection methods from microarray data such as statistical test always focus on differentially expressed genes in different samples by individual gene prioritization. These traditional methods might miss differentially coexpressed (DCE) gene subsets because they ignore the interaction between genes. In this paper, MIClique algorithm is proposed to identify DEC gene subsets based on mutual information and clique analysis. Mutual information is used to measure the coexpression relationship between each pair of genes in two different kinds of samples. Clique analysis is a commonly used method in biological network, which generally represents biological module of similar function. By applying the MIClique algorithm to real gene expression data, some DEC gene subsets which correlated under one experimental condition but uncorrelated under another condition are detected from the graph of colon dataset and leukemia dataset.
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