Inference of biological pathway from gene expression profiles by time delay boolean networks

One great challenge of genomic research is to efficiently and accurately identify complex gene regulatory networks. The development of high-throughput technologies provides numerous experimental data such as DNA sequences, protein sequence, and RNA expression profiles makes it possible to study interactions and regulations among genes or other substance in an organism. However, it is crucial to make inference of genetic regulatory networks from gene expression profiles and protein interaction data for systems biology. This study will develop a new approach to reconstruct time delay Boolean networks as a tool for exploring biological pathways. In the inference strategy, we will compare all pairs of input genes in those basic relationships by their corresponding [Formula: see text]-scores for every output gene. Then, we will combine those consistent relationships to reveal the most probable relationship and reconstruct the genetic network. Specifically, we will prove that [Formula: see text] state transition pairs are sufficient and necessary to reconstruct the time delay Boolean network of [Formula: see text] nodes with high accuracy if the number of input genes to each gene is bounded. We also have implemented this method on simulated and empirical yeast gene expression data sets. The test results show that this proposed method is extensible for realistic networks.     

Cell-cycle-dependent gene expression studied by two-colour fluorescent detection of a mRNA and histone mRNA

We investigated whether a probe specific for histone H3 mRNA could be used as a marker to study cell-cycle dependency of gene expression by double-fluorescent RNA in situ hybridization (FISH). First, we showed that all S-phase cells in cell cultures having incorporated BrdU revealed histone H3 mRNA expression by RNA FISH, indicating that histone H3 expression is a reliable marker for S-phase cells. Second, we analysed whether the expression of human cytomegalovirus immediate early genes in rat 9G cells, which are known to be induced in an S-phase dependent way by cycloheximide, correlated with the expression of histone H3 mRNA. Double-hybridization experiments with a digoxigenin-labelled probe for IE mRNA and a fluoresceinated probe for histone H3 mRNA revealed that cells expressing IE mRNA also expressed histone H3 mRNA. Third, we examined the cell-cycle dependency of luciferase gene expression in X1 cells. Luciferase mRNA is heterogeneously expressed in X1 cell cultures, but cells expressing luciferase did not necessarily express histone H3 mRNA. This indicates that luciferase gene expression in X1 cells is not induced during S-phase. The results of our study show that histone H3 mRNA expression can be successfully used as a marker to establish cell-cycle dependency of gene expression by double-RNA FISH.     

A quantitative method for comparison of expression of alternatively spliced genes using different primer pairs

In this paper we describe a novel two-step method for comparison of expression of alternatively spliced genes by quantitative PCR (QPCR) applying different primer pairs. As a model system we used rat decay accelerating factor (DAF; CD55) mRNA, which comprises three different isoforms: soluble (sDAF), transmembrane (tmDAF) and glycosyl-phosphatidylinositol (GPI) anchored (gpiDAF) forms. The first step was to prepare solid phase specific for each mRNA isoform and purify the three DAF-forms from total RNA. We then assessed amplification efficiency of primer pairs designed to recognise each of the isoforms using equimolar amounts of the three purified DAF mRNAs. The final step in our assay was to compare expression of the three DAF-isoforms in testis by QPCR taking into account the efficiency of their amplification to enable quantification. The RNA capture/QPCR method we described here can be used for quantifying the expression ratios of alternatively spliced mRNAs from a single gene or for direct comparison of expression of different genes.     

RNA sequencing reveals two major classes of gene expression levels in metazoan cells

The expression level of a gene is often used as a proxy for determining whether the protein or RNA product is functional in a cell or tissue. Therefore, it is of fundamental importance to understand the global distribution of gene expression levels, and to be able to interpret it mechanistically and functionally. Here we use RNA sequencing (RNA‐seq) of mouse Th2 cells, coupled with a range of other techniques, to show that all genes can be separated, based on their expression abundance, into two distinct groups: one group comprised of lowly expressed and putatively non‐functional mRNAs, and the other of highly expressed mRNAs with active chromatin marks at their promoters. These observations are confirmed in many other microarray and RNA‐seq data sets of metazoan cell types.     

Genome-wide circular RNA (circRNA) and mRNA profiling identify a circMET-miR-410-3p regulatory motif for cell growth in colorectal cancer

Circular RNA (circRNA) is a non-coding RNA molecule that lacks polyadenylated tails and is highly stable, abundant, and conserved in human cells. CircRNAs can serve as a competing endogenous RNA (ceRNA) to sponge microRNAs (miRNA) and block their effects on target mRNA expression. CircRNAs also have possible relevance to cancer and therefore may be considered as ideal biomarkers for monitoring cancer progression. Of the about 300,000 predicted human circRNAs, only a few have validated biological functions related to cancer. To better understand the ceRNA role of circRNAs in colorectal cancer (CRC), we performed genome-wide circRNA-based RNA-sequencing (RNA-Seq) on nine CRC tumor samples and their paired histologically normal adjacent tissue samples. By profiling the mRNA expression in the same patients, we further explored the expression correlation between circRNAs and mRNAs generated from the same parental gene. Focusing on the concordant differential expression between circRNAs and mRNAs, we substantially reduced the regulatory noise. In total, we identified 694 circRNA-mRNA pairs that were consistently up or downregulated between tumor and normal tissues. These 694 circRNA-mRNA pairs are from 182 protein-coding genes associated with hormone responses and chemotaxis. Of these 182 genes, 43 are downstream targets of three highly conserved miRNAs (miR-410-3p, miR-135a, and miR-30a). Interestingly, these 43 genes are highly mutated in another cohort from eight independent CRC studies, which have significant effects on patient survival time. Focusing on miR-410-3p and its target oncogene MET, we experimentally validated the ceRNA regulatory motif of circMET. Notably, circMET is substantially upregulated in CRC cell lines and could promote cell proliferation and growth. By confirming the regulatory relationship between miR-410-3p and circMET, we propose a new mechanism for the observed sustained activation of MET in CRC. In conclusion, our work identifies a novel regulatory role of circMET and provides a potential diagnostic biomarker for CRC.     

Combined DNA-RNA Fluorescent In situ Hybridization (FISH) to Study X Chromosome Inactivation in Differentiated Female Mouse Embryonic Stem Cells

Fluorescent in situ hybridization (FISH) is a molecular technique which enables the detection of nucleic acids in cells. DNA FISH is often used in cytogenetics and cancer diagnostics, and can detect aberrations of the genome, which often has important clinical implications. RNA FISH can be used to detect RNA molecules in cells and has provided important insights in regulation of gene expression. Combining DNA and RNA FISH within the same cell is technically challenging, as conditions suitable for DNA FISH might be too harsh for fragile, single stranded RNA molecules. We here present an easily applicable protocol which enables the combined, simultaneous detection of Xist RNA and DNA encoded by the X chromosomes. This combined DNA-RNA FISH protocol can likely be applied to other systems where both RNA and DNA need to be detected.     

mRNA-targeted fluorescent in situ hybridization (FISH) of Gram-negative bacteria without template amplification or tyramide signal amplification

Technologies are needed to study gene expression at the level of individual cells within a population or microbial community. Fluorescent in situ hybridization (FISH) supplies high-resolution spatial information and has been widely applied to study microbial communities at the rRNA level. While mRNA-targeted FISH has been popular for studying gene expression in eukaryotic cells, very little success has been achieved with prokaryotes. At present, detection of specific mRNAs in individual prokaryotic cells requires the use of in situ RT-PCR or tyramide signal amplification (TSA). In this study we used DNA oligonucleotide probes labeled with a single near-infrared dye in FISH assays to detect multi-copy plasmid-based and endogenous mRNA molecules in Escherichia coli and Shewanella oneidensis MR-1. We took advantage of the fact that there is much less background signal produced by biological materials and support matrices in the near-infrared spectrum and thus long camera exposure times could be used. In addition, we demonstrate that a combination of probes targeting both rRNA and mRNA could be successfully employed within the same FISH assay. These results, as well as ongoing R&D improvements in NIR and infrared dyes, indicate that the FISH approach we demonstrated could be applied in certain environmental settings to monitor gene expression in mixed populations.     

TedSim: temporal dynamics simulation of single-cell RNA sequencing data and cell division history

Recently, lineage tracing technology using CRISPR/Cas9 genome editing has enabled simultaneous readouts of gene expressions and lineage barcodes, which allows for the reconstruction of the cell division tree and makes it possible to reconstruct ancestral cell types and trace the origin of each cell type. Meanwhile, trajectory inference methods are widely used to infer cell trajectories and pseudotime in a dynamic process using gene expression data of present-day cells. Here, we present TedSim (single-cell temporal dynamics simulator), which simulates the cell division events from the root cell to present-day cells, simultaneously generating two data modalities for each single cell: the lineage barcode and gene expression data. TedSim is a framework that connects the two problems: lineage tracing and trajectory inference. Using TedSim, we conducted analysis to show that (i) TedSim generates realistic gene expression and barcode data, as well as realistic relationships between these two data modalities; (ii) trajectory inference methods can recover the underlying cell state transition mechanism with balanced cell type compositions; and (iii) integrating gene expression and barcode data can provide more insights into the temporal dynamics in cell differentiation compared to using only one type of data, but better integration methods need to be developed.