Statistical extraction of Drosophila cis-regulatory modules using exhaustive assessment of local word frequency

BACKGROUND: Transcription regulatory regions in higher eukaryotes are often represented by cis-regulatory modules (CRM) and are responsible for the formation of specific spatial and temporal gene expression patterns. These extended, ~1 KB, regions are found far from coding sequences and cannot be extracted from genome on the basis of their relative position to the coding regions. RESULTS: To explore the feasibility of CRM extraction from a genome, we generated an original training set, containing annotated sequence data for most of the known developmental CRMs from Drosophila. Based on this set of experimental data, we developed a strategy for statistical extraction of cis-regulatory modules from the genome, using exhaustive analysis of local word frequency (LWF). To assess the performance of our analysis, we measured the correlation between predictions generated by the LWF algorithm and the distribution of conserved non-coding regions in a number of Drosophila developmental genes. CONCLUSIONS: In most of the cases tested, we observed high correlation (up to 0.6–0.8, measured on the entire gene locus) between the two independent techniques. We discuss computational strategies available for extraction of Drosophila CRMs and possible extensions of these methods

The Drosophila Gap Gene Network Is Composed of Two Parallel Toggle Switches

Drosophila “gap” genes provide the first response to maternal gradients in the early fly embryo. Gap genes are expressed in a series of broad bands across the embryo during first hours of development. The gene network controlling the gap gene expression patterns includes inputs from maternal gradients and mutual repression between the gap genes themselves. In this study we propose a modular design for the gap gene network, involving two relatively independent network domains. The core of each network domain includes a toggle switch corresponding to a pair of mutually repressive gap genes, operated in space by maternal inputs. The toggle switches present in the gap network are evocative of the phage lambda switch, but they are operated positionally (in space) by the maternal gradients, so the synthesis rates for the competing components change along the embryo anterior-posterior axis. Dynamic model, constructed based on the proposed principle, with elements of fractional site occupancy, required 5–7 parameters to fit quantitative spatial expression data for gap gradients. The identified model solutions (parameter combinations) reproduced major dynamic features of the gap gradient system and explained gap expression in a variety of segmentation mutants

Time warping of evolutionary distant temporal gene expression data based on noise suppression

<p>Abstract</p> <p>Background</p> <p>Comparative analysis of genome wide temporal gene expression data has a broad potential area of application, including evolutionary biology, developmental biology, and medicine. However, at large evolutionary distances, the construction of global alignments and the consequent comparison of the time-series data are difficult. The main reason is the accumulation of variability in expression profiles of orthologous genes, in the course of evolution.</p> <p>Results</p> <p>We applied Pearson distance matrices, in combination with other noise-suppression techniques and data filtering to improve alignments. This novel framework enhanced the capacity to capture the similarities between the temporal gene expression datasets separated by large evolutionary distances. We aligned and compared the temporal gene expression data in budding (<it>Saccharomyces cerevisiae</it>) and fission (<it>Schizosaccharomyces pombe</it>) yeast, which are separated by more then ~400 myr of evolution. We found that the global alignment (time warping) properly matched the duration of cell cycle phases in these distant organisms, which was measured in prior studies. At the same time, when applied to individual ortholog pairs, this alignment procedure revealed groups of genes with distinct alignments, different from the global alignment.</p> <p>Conclusion</p> <p>Our alignment-based predictions of differences in the cell cycle phases between the two yeast species were in a good agreement with the existing data, thus supporting the computational strategy adopted in this study. We propose that the existence of the alternative alignments, specific to distinct groups of genes, suggests presence of different synchronization modes between the two organisms and possible functional decoupling of particular physiological gene networks in the course of evolution.</p

Homotypic Regulatory Clusters in Drosophila

Cis-regulatory modules (CRMs) are transcription regulatory DNA segments (∼1 Kb range) that control the expression of developmental genes in higher eukaryotes. We analyzed clustering of known binding motifs for transcription factors (TFs) in over 60 known CRMs from 20 Drosophila developmental genes, and we present evidence that each type of recognition motif forms significant clusters within the regulatory regions regulated by the corresponding TF. We demonstrate how a search with a single binding motif can be applied to explore gene regulatory networks and to discover coregulated genes in the genome. We also discuss the potential of the clustering method in interpreting the differential response of genes to various levels of transcriptional regulators

Expression of podocalyxin separates the hematopoietic and vascular potentials of mouse embryonic stem cell-derived mesoderm

In the mouse embryo and differentiating embryonic stem cells, the hematopoietic, endothelial and cardiomyocyte lineages are derived from Flk1+ mesodermal progenitors. Here we report that surface expression of Podocalyxin (Podxl), a member of the CD34 family of sialomucins, can be used to subdivide the Flk1+ cells in differentiating embryoid bodies at day 4.75 into populations that develop into distinct mesodermal lineages. Definitive hematopoietic potential was restricted to the Flk1+Podxl+ population, while the Flk1-negative Podxl+ population displayed only primitive erythroid potential. The Flk1+Podxl-negative population contained endothelial cells and cardiomyocyte potential. Podxl expression distinguishes Flk1+ mesoderm populations in mouse embryos at days 7.5, 8.5 and 9.5 and is a marker of progenitor stage primitive erythroblasts. These findings identify Podxl as a useful tool for separating distinct mesodermal lineages

Memory of Divisional History Directs the Continuous Process of Primitive Hematopoietic Lineage Commitment

Hematopoietic stem cells (HSCs) exist in a dormant state and progressively lose regenerative potency as they undergo successive divisions. Why this functional decline occurs and how this information is encoded is unclear. To better understand how this information is stored, we performed RNA sequencing on HSC populations differing only in their divisional history. Comparative analysis revealed that genes upregulated with divisions are enriched for lineage genes and regulated by cell-cycle-associated transcription factors, suggesting that proliferation itself drives lineage priming. Downregulated genes are, however, associated with an HSC signature and targeted by the Polycomb Repressive Complex 2 (PRC2). The PRC2 catalytic subunits Ezh1 and Ezh2 promote and suppress the HSC state, respectively, and successive divisions cause a switch from Ezh1 to Ezh2 dominance. We propose that cell divisions drive lineage priming and Ezh2 accumulation, which represses HSC signature genes to consolidate information on divisional history into memory.ISSN:2213-671