Dynamics of metastasis suppressor gene inactivation

For most cancer cell types, the acquisition of metastatic ability leads to clinically incurable disease. Twelve metastasis suppressor genes (MSGs) have been identified that reduce the metastatic propensity of cancer cells. If these genes are inactivated in both alleles, metastatic ability is promoted. Here, we develop a mathematical model of the dynamics of MSG inactivation and calculate the expected number of metastases formed by a tumor. We analyse the effects of increased mutation rates and different fitness values of cells with one or two inactivated alleles on the ability of a tumor to form metastases. We find that mutations that are negatively selected in the main tumor are unlikely to be responsible for the majority of metastases produced by a tumor. Most metastases-causing mutations will be present in all (or most) cells in the main tumor.     

Dynamics of gene silencing by RNA interference

The large number of candidate genes identified by modern high-throughput technologies require efficient methods for generating knockout phenotypes or gene silencing in order to study gene function. RNA interference (RNAi) is an efficient method that can be used for this purpose. Effective gene silencing by RNAi depends on a number of important parameters, including the dynamics of gene expression and the RNA dose. Using mouse hepatoma cells, we detail some of the principal characteristics of RNAi as a tool for gene silencing, such as the RNA dose level, RNA complex exposure time, and the time of transfection relative to gene induction, in the context of silencing a green fluorescent protein reporter gene. Our experiments demonstrate that different levels of silencing can be attained by modulating the dose level of RNA and the time of transfection and illustrate the importance of a dynamic analysis in designing robust silencing protocols. By quantifying the kinetics of RNAi-based gene silencing, we present a model that may be used to help determine key parameters in more complex silencing experiments and explore alternative gene silencing protocols.     

X chromosome inactivation during Drosophila spermatogenesis

Genes with male- and testis-enriched expression are under-represented on the Drosophila melanogaster X chromosome. There is also an excess of retrotransposed genes, many of which are expressed in testis, that have “escaped” the X chromosome and moved to the autosomes. It has been proposed that inactivation of the X chromosome during spermatogenesis contributes to these patterns: genes with a beneficial function late in spermatogenesis should be selectively favored to be autosomal in order to avoid inactivation. However, conclusive evidence for X inactivation in the male germline has been lacking. To test for such inactivation, we used a transgenic construct in which expression of a lacZ reporter gene was driven by the promoter sequence of the autosomal, testis-specific ocnus gene. Autosomal insertions of this transgene showed the expected pattern of male- and testis-specific expression. X-linked insertions, in contrast, showed only very low levels of reporter gene expression. Thus, we find that X linkage inhibits the activity of a testis-specific promoter. We obtained the same result using a vector in which the transgene was flanked by chromosomal insulator sequences. These results are consistent with global inactivation of the X chromosome in the male germline and support a selective explanation for X chromosome avoidance of genes with beneficial effects late in spermatogenesis.     

Disruption of a conserved region of Xist exon 1 impairs Xist RNA localisation and X-linked gene silencing during random and imprinted X chromosome inactivation

In XX female mammals a single X chromosome is inactivated early in embryonic development, a process that is required to equalise X-linked gene dosage relative to XY males. X inactivation is regulated by a cis-acting master switch, the Xist locus, the product of which is a large non-coding RNA that coats the chromosome from which it is transcribed, triggering recruitment of chromatin modifying factors that establish and maintain gene silencing chromosome wide. Chromosome coating and Xist RNA-mediated silencing remain poorly understood, both at the level of RNA sequence determinants and interacting factors. Here, we describe analysis of a novel targeted mutation, Xist(INV), designed to test the function of a conserved region located in exon 1 of Xist RNA during X inactivation in mouse. We show that Xist(INV) is a strong hypomorphic allele that is appropriately regulated but compromised in its ability to silence X-linked loci in cis. Inheritance of Xist(INV) on the paternal X chromosome results in embryonic lethality due to failure of imprinted X inactivation in extra-embryonic lineages. Female embryos inheriting Xist(INV) on the maternal X chromosome undergo extreme secondary non-random X inactivation, eliminating the majority of cells that express the Xist(INV) allele. Analysis of cells that express Xist(INV) RNA demonstrates reduced association of the mutant RNA to the X chromosome, suggesting that conserved sequences in the inverted region are important for Xist RNA localisation.     

Dynamics of the recovery from sRNA-mediated gene silencing

Comment on: Mitarai N, Benjamin JA, Krishna S, Semsey S, Csiszovszki Z, Massé E, et al. Dynamic features of gene expression control by small regulatory RNAs. Proc Natl Acad Sci USA 2009; 106:10655-9.     

Gene silencing：Double－stranded RNA mediated mRNA degradation and gene inactivation

INTRODUCTIONThe genome structure of plants can be alteredby genetic transformation. During the process ofgene transfer, Agrobacterium tumefaCJens integratepart of their genome into the genome of susceptiblespecies. Recently, genetic transfOrmation techniqueshave been used to modify significantly the organi-zation of the genome. Introducing transgenes intop1ants can both modify the number of copies of agiven sequence and affect gene expression. Becausethe expression of a transgene cannot…     

Analysis of methylation of a human X located gene which escapes X inactivation.

The gene MIC2 is located in the pseudoautosomal region at the ends of the short arms of the X and Y chromosomes. In females MIC2 escapes X inactivation. We have analyzed the methylation pattern of MIC2 on the active X, the inactive X chromosomes, and the Y chromosome. The 5' end of the gene contains a GC rich region which is unmethylated on the active X, the inactive X and on the Y. The body of the gene is characterized by variable methylation.     

Enhancement of allele discrimination by introduction of nucleotide mismatches into siRNA in allele-specific gene silencing by RNAi

Allele-specific gene silencing by RNA interference (RNAi) is therapeutically useful for specifically inhibiting the expression of disease-associated alleles without suppressing the expression of corresponding wild-type alleles. To realize such allele-specific RNAi (ASP-RNAi), the design and assessment of small interfering RNA (siRNA) duplexes conferring ASP-RNAi is vital; however, it is also difficult. In a previous study, we developed an assay system to assess ASP-RNAi with mutant and wild-type reporter alleles encoding the Photinus and Renilla luciferase genes. In line with experiments using the system, we realized that it is necessary and important to enhance allele discrimination between mutant and corresponding wild-type alleles. Here, we describe the improvement of ASP-RNAi against mutant alleles carrying single nucleotide variations by introducing base substitutions into siRNA sequences, where original variations are present in the central position. Artificially mismatched siRNAs or short-hairpin RNAs (shRNAs) against mutant alleles of the human Prion Protein (PRNP) gene, which appear to be associated with susceptibility to prion diseases, were examined using this assessment system. The data indicates that introduction of a one-base mismatch into the siRNAs and shRNAs was able to enhance discrimination between the mutant and wild-type alleles. Interestingly, the introduced mismatches that conferred marked improvement in ASP-RNAi, appeared to be largely present in the guide siRNA elements, corresponding to the 'seed region' of microRNAs. Due to the essential role of the 'seed region' of microRNAs in their association with target RNAs, it is conceivable that disruption of the base-pairing interactions in the corresponding seed region, as well as the central position (involved in cleavage of target RNAs), of guide siRNA elements could influence allele discrimination. In addition, we also suggest that nucleotide mismatches at the 3'-ends of sense-strand siRNA elements, which possibly increase the assembly of antisense-strand (guide) siRNAs into RNA-induced silencing complexes (RISCs), may enhance ASP-RNAi in the case of inert siRNA duplexes. Therefore, the data presented here suggest that structural modification of functional portions of an siRNA duplex by base substitution could greatly influence allele discrimination and gene silencing, thereby contributing to enhancement of ASP-RNAi.     

Polycomb group proteins Ring1A/B link ubiquitylation of histone H2A to heritable gene silencing and X inactivation

In many higher organisms, 5%-15% of histone H2A is ubiquitylated at lysine 119 (uH2A). The function of this modification and the factors involved in its establishment, however, are unknown. Here we demonstrate that uH2A occurs on the inactive X chromosome in female mammals and that this correlates with recruitment of Polycomb group (PcG) proteins belonging to Polycomb repressor complex 1 (PRC1). Based on our observations, we tested the role of the PRC1 protein Ring1B and its closely related homolog Ring1A in H2A ubiquitylation. Analysis of Ring1B null embryonic stem (ES) cells revealed extensive depletion of global uH2A levels. On the inactive X chromosome, uH2A was maintained in Ring1A or Ring1B null cells, but not in double knockout cells, demonstrating an overlapping function for these proteins in development. These observations link H2A ubiquitylation, X inactivation, and PRC1 PcG function, suggesting an unanticipated and novel mechanism for chromatin-mediated heritable gene silencing.     

Photochemically induced gene silencing using PNA-peptide conjugates

The potential for exploration of peptide nucleic acid (PNA) as an experimental and therapeutic regulator of gene expression has been hampered by a poor delivery and a lack of site-specific targeting. In the present study, we have developed an efficient strategy for nuclear delivery of PNA by combining cationically charged PNA-peptide conjugates and photochemical internalization (PCI) technology. When using the S100A4 gene as a model system, a consistent downregulation to around 10% remaining protein signal was obtained in three selected cell lines. Furthermore, a dose-dependent and time-dependent inhibition of the S100A4 protein was demonstrated. A main benefit of the strategy proposed is the possibility of site-specific targeting.     

Localization of a gene that escapes inactivation to the X chromosome proximal short arm: implications for X inactivation.

The process of mammalian X chromosome inactivation results in the inactivation of most, but not all, genes along one or the other of the two X chromosomes in females. On the human X chromosome, several genes have been described that "escape" inactivation and continue to be expressed from both homologues. All such previously mapped genes are located in the distal third of the short arm of the X chromosome, giving rise to the hypothesis of a region of the chromosome that remains noninactivated during development. The A1S9T gene, an X-linked locus that complements a mouse temperature-sensitive defect in DNA synthesis, escapes inactivation and has now been localized, in human-mouse somatic cell hybrids, to the proximal short arm, in Xp11.1 to Xp11.3. Thus, A1S9T lies in a region of the chromosome that is separate from the other genes known to escape inactivation and is located between other genes known to be subject to X inactivation. This finding both rules out models based on a single chromosomal region that escapes inactivation and suggests that X inactivation proceeds by a mechanism that allows considerable autonomy between different genes or regions on the chromosome.     

Identification of gene signatures from RNA-seq data using Pareto-optimal cluster algorithm

Background

Gene signatures are important to represent the molecular changes in the disease genomes or the cells in specific conditions, and have been often used to separate samples into different groups for better research or clinical treatment. While many methods and applications have been available in literature, there still lack powerful ones that can take account of the complex data and detect the most informative signatures.

Methods

In this article, we present a new framework for identifying gene signatures using Pareto-optimal cluster size identification for RNA-seq data. We first performed pre-filtering steps and normalization, then utilized the empirical Bayes test in Limma package to identify the differentially expressed genes (DEGs). Next, we used a multi-objective optimization technique, “Multi-objective optimization for collecting cluster alternatives” (MOCCA in R package) on these DEGs to find Pareto-optimal cluster size, and then applied k-means clustering to the RNA-seq data based on the optimal cluster size. The best cluster was obtained through computing the average Spearman’s Correlation Score among all the genes in pair-wise manner belonging to the module. The best cluster is treated as the signature for the respective disease or cellular condition.

Results

We applied our framework to a cervical cancer RNA-seq dataset, which included 253 squamous cell carcinoma (SCC) samples and 22 adenocarcinoma (ADENO) samples. We identified a total of 582 DEGs by Limma analysis of SCC versus ADENO samples. Among them, 260 are up-regulated genes and 322 are down-regulated genes. Using MOCCA, we obtained seven Pareto-optimal clusters. The best cluster has a total of 35 DEGs consisting of all-upregulated genes. For validation, we ran PAMR (prediction analysis for microarrays) classifier on the selected best cluster, and assessed the classification performance. Our evaluation, measured by sensitivity, specificity, precision, and accuracy, showed high confidence.

Conclusions

Our framework identified a multi-objective based cluster that is treated as a signature that can classify the disease and control group of samples with higher classification performance (accuracy 0.935) for the corresponding disease. Our method is useful to find signature for any RNA-seq or microarray data.