Unveiling combinatorial regulation through the combination of ChIP information and in silico cis-regulatory module detection

Computationally retrieving biologically relevant cis-regulatory modules (CRMs) is not straightforward. Because of the large number of candidates and the imperfection of the screening methods, many spurious CRMs are detected that are as high scoring as the biologically true ones. Using ChIP-information allows not only to reduce the regions in which the binding sites of the assayed transcription factor (TF) should be located, but also allows restricting the valid CRMs to those that contain the assayed TF (here referred to as applying CRM detection in a query-based mode). In this study, we show that exploiting ChIP-information in a query-based way makes in silico CRM detection a much more feasible endeavor. To be able to handle the large datasets, the query-based setting and other specificities proper to CRM detection on ChIP-Seq based data, we developed a novel powerful CRM detection method 'CPModule'. By applying it on a well-studied ChIP-Seq data set involved in self-renewal of mouse embryonic stem cells, we demonstrate how our tool can recover combinatorial regulation of five known TFs that are key in the self-renewal of mouse embryonic stem cells. Additionally, we make a number of new predictions on combinatorial regulation of these five key TFs with other TFs documented in TRANSFAC.status: publishe

Ranked tiling

Tiling is a well-known pattern mining technique. Traditionally, it discovers large areas of ones in binary databases or matrices, where an area is defined by a set of rows and a set of columns. In this paper, we introduce the novel problem of ranked tiling, which is concerned with finding interesting areas in ranked data. In this data, each transaction defines a complete ranking of the columns. Ranked data occurs naturally in applications like sports or other competitions. It is also a useful abstraction when dealing with numeric data in which the rows are incomparable. We introduce a scoring function for ranked tiling, as well as an algorithm using constraint programming and optimization principles. We empirically evaluate the approach on both synthetic and real-life datasets, and demonstrate the applicability of the framework in several case studies. One case study involves a heterogeneous dataset concerning the discovery of biomarkers for different subtypes of breast cancer patients. An analysis of the tiles by a domain expert shows that our approach can lead to the discovery of novel insights.status: publishe

Bi-clustering gene expression data under constraints

This paper presents a constraint-based approach to mining bi-clusters in gene expression data. Instead of designing an algorithm for each specific task, we propose to use constraint programming to turn the mining problem into a constraint satisfaction and/or optimisation problem. We demonstrate this promising approach on two cases. The first is to mine a single constant-row bi-cluster under noise constraints. The second is to mine a set of generic noisy constant-row bi-clusters under structure constraints, which is called a staircase pattern.status: publishe

Ultraviolet-B radiation stimulates downward leaf curling in Arabidopsis thaliana

Plants are very well adapted to growth in ultraviolet-B (UV-B) containing light. In Arabidopsis thaliana, many of these adaptations are mediated by the UV-B receptor UV RESISTANCE LOCUS 8 (UVR8). Using small amounts of supplementary UV-B light, we observed changes in the shape of rosette leaf blades. Wild type plants show more pronounced epinasty of the blade edges, while this is not the case in uvr8 mutant plants. The UVR8 effect thus mimics the effect of phytochrome (phy) B in red light. In addition, a meta-analysis of transcriptome data indicates that the UVR8 and phyB signaling pathways have over 70% of gene regulation in common. Moreover, in low levels of supplementary UV-B light, mutant analysis revealed that phyB signaling is necessary for epinasty of the blade edges. Analysis of auxin levels and the auxin signal reporter DR5::GUS suggest that the epinasty relies on altered auxin distribution, keeping auxin at the leaf blade edges in the presence of UV-B. Together, our results suggest a co-action of phyB and UVR8 signaling, with auxin as a downstream factor.publisher: Elsevier articletitle: Ultraviolet-B radiation stimulates downward leaf curling in Arabidopsis thaliana journaltitle: Plant Physiology and Biochemistry articlelink: http://dx.doi.org/10.1016/j.plaphy.2014.12.012 content_type: article copyright: Copyright © 2014 Elsevier Masson SAS. All rights reserved.status: publishe

Ranked tiling based approach to discovering patient subtypes

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Obg and membrane depolarization are part of a microbial bet-hedging strategy that leads to antibiotic tolerance

Within bacterial populations, a small fraction of persister cells is transiently capable of surviving exposure to lethal doses of antibiotics. As a bet-hedging strategy, persistence levels are determined both by stochastic induction and by environmental stimuli, called responsive diversification. Little is known on the mechanisms that link the low frequency of persisters to environmental signals. Our results support a central role for the conserved GTPase Obg in determining persistence in Escherichia coli in response to nutrient starvation. Obg-mediated persistence requires the stringent response alarmone (p)ppGpp and proceeds through transcriptional control of the hokB-sokB type I toxin-antitoxin module. In individual cells, increased Obg levels induce HokB expression, which in turn results in a collapse of the membrane potential, leading to dormancy. Obg also controls persistence in Pseudomonas aeruginosa and thus constitutes a conserved regulator of antibiotic tolerance. Combined, our findings signify an important step towards unravelling shared genetic mechanisms underlying persistence.publisher: Elsevier articletitle: Obg and Membrane Depolarization Are Part of a Microbial Bet-Hedging Strategy that Leads to Antibiotic Tolerance journaltitle: Molecular Cell articlelink: http://dx.doi.org/10.1016/j.molcel.2015.05.011 content_type: article copyright: Copyright © 2015 Elsevier Inc. All rights reserved.status: publishe

Brazilian Flora 2020: Leveraging the power of a collaborative scientific network

International audienceThe shortage of reliable primary taxonomic data limits the description of biological taxa and the understanding of biodiversity patterns and processes, complicating biogeographical, ecological, and evolutionary studies. This deficit creates a significant taxonomic impediment to biodiversity research and conservation planning. The taxonomic impediment and the biodiversity crisis are widely recognized, highlighting the urgent need for reliable taxonomic data. Over the past decade, numerous countries worldwide have devoted considerable effort to Target 1 of the Global Strategy for Plant Conservation (GSPC), which called for the preparation of a working list of all known plant species by 2010 and an online world Flora by 2020. Brazil is a megadiverse country, home to more of the world's known plant species than any other country. Despite that, Flora Brasiliensis, concluded in 1906, was the last comprehensive treatment of the Brazilian flora. The lack of accurate estimates of the number of species of algae, fungi, and plants occurring in Brazil contributes to the prevailing taxonomic impediment and delays progress towards the GSPC targets. Over the past 12 years, a legion of taxonomists motivated to meet Target 1 of the GSPC, worked together to gather and integrate knowledge on the algal, plant, and fungal diversity of Brazil. Overall, a team of about 980 taxonomists joined efforts in a highly collaborative project that used cybertaxonomy to prepare an updated Flora of Brazil, showing the power of scientific collaboration to reach ambitious goals. This paper presents an overview of the Brazilian Flora 2020 and provides taxonomic and spatial updates on the algae, fungi, and plants found in one of the world's most biodiverse countries. We further identify collection gaps and summarize future goals that extend beyond 2020. Our results show that Brazil is home to 46,975 native species of algae, fungi, and plants, of which 19,669 are endemic to the country. The data compiled to date suggests that the Atlantic Rainforest might be the most diverse Brazilian domain for all plant groups except gymnosperms, which are most diverse in the Amazon. However, scientific knowledge of Brazilian diversity is still unequally distributed, with the Atlantic Rainforest and the Cerrado being the most intensively sampled and studied biomes in the country. In times of “scientific reductionism”, with botanical and mycological sciences suffering pervasive depreciation in recent decades, the first online Flora of Brazil 2020 significantly enhanced the quality and quantity of taxonomic data available for algae, fungi, and plants from Brazil. This project also made all the information freely available online, providing a firm foundation for future research and for the management, conservation, and sustainable use of the Brazilian funga and flora