enoLOGOS: a versatile web tool for energy normalized sequence logos

enoLOGOS is a web-based tool that generates sequence logos from various input sources. Sequence logos have become a popular way to graphically represent DNA and amino acid sequence patterns from a set of aligned sequences. Each position of the alignment is represented by a column of stacked symbols with its total height reflecting the information content in this position. Currently, the available web servers are able to create logo images from a set of aligned sequences, but none of them generates weighted sequence logos directly from energy measurements or other sources. With the advent of high-throughput technologies for estimating the contact energy of different DNA sequences, tools that can create logos directly from binding affinity data are useful to researchers. enoLOGOS generates sequence logos from a variety of input data, including energy measurements, probability matrices, alignment matrices, count matrices and aligned sequences. Furthermore, enoLOGOS can represent the mutual information of different positions of the consensus sequence, a unique feature of this tool. Another web interface for our software, C2H2-enoLOGOS, generates logos for the DNA-binding preferences of the C2H2 zinc-finger transcription factor family members. enoLOGOS and C2H2-enoLOGOS are accessible over the web at

Transcription factor control of growth rate dependent genes in Saccharomyces cerevisiae: A three factor design

<p>Abstract</p> <p>Background</p> <p>Characterization of cellular growth is central to understanding living systems. Here, we applied a three-factor design to study the relationship between specific growth rate and genome-wide gene expression in 36 steady-state chemostat cultures of <it>Saccharomyces cerevisiae</it>. The three factors we considered were specific growth rate, nutrient limitation, and oxygen availability.</p> <p>Results</p> <p>We identified 268 growth rate dependent genes, independent of nutrient limitation and oxygen availability. The transcriptional response was used to identify key areas in metabolism around which mRNA expression changes are significantly associated. Among key metabolic pathways, this analysis revealed <it>de novo </it>synthesis of pyrimidine ribonucleotides and ATP producing and consuming reactions at fast cellular growth. By scoring the significance of overlap between growth rate dependent genes and known transcription factor target sets, transcription factors that coordinate balanced growth were also identified. Our analysis shows that Fhl1, Rap1, and Sfp1, regulating protein biosynthesis, have significantly enriched target sets for genes up-regulated with increasing growth rate. Cell cycle regulators, such as Ace2 and Swi6, and stress response regulators, such as Yap1, were also shown to have significantly enriched target sets.</p> <p>Conclusion</p> <p>Our work, which is the first genome-wide gene expression study to investigate specific growth rate and consider the impact of oxygen availability, provides a more conservative estimate of growth rate dependent genes than previously reported. We also provide a global view of how a small set of transcription factors, 13 in total, contribute to control of cellular growth rate. We anticipate that multi-factorial designs will play an increasing role in elucidating cellular regulation.</p

Meta-analysis derived atopic dermatitis (MADAD) transcriptome defines a robust AD signature highlighting the involvement of atherosclerosis and lipid metabolism pathways

BACKGROUND: Atopic dermatitis (AD) is a common inflammatory skin disease with limited treatment options. Several microarray experiments have been conducted on lesional/LS and non-lesional/NL AD skin to develop a genomic disease phenotype. Although these experiments have shed light on disease pathology, inter-study comparisons reveal large differences in resulting sets of differentially expressed genes (DEGs), limiting the utility of direct comparisons across studies. METHODS: We carried out a meta-analysis combining 4 published AD datasets to define a robust disease profile, termed meta-analysis derived AD (MADAD) transcriptome. RESULTS: This transcriptome enriches key AD pathways more than the individual studies, and associates AD with novel pathways, such as atherosclerosis signaling (IL-37, selectin E/SELE). We identified wide lipid abnormalities and, for the first time in vivo, correlated Th2 immune activation with downregulation of key epidermal lipids (FA2H, FAR2, ELOVL3), emphasizing the role of cytokines on the barrier disruption in AD. Key AD “classifier genes” discriminate lesional from nonlesional skin, and may evaluate therapeutic responses. CONCLUSIONS: Our meta-analysis provides novel and powerful insights into AD disease pathology, and reinforces the concept of AD as a systemic disease. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12920-015-0133-x) contains supplementary material, which is available to authorized users

Equitoxic Doses of 5-Azacytidine and 5-Aza-2′Deoxycytidine Induce Diverse Immediate and Overlapping Heritable Changes in the Transcriptome

The hypomethylating agent 5-Azacytidine (5-Aza-CR) is the first drug to prolong overall survival in patients with myelodysplastic syndrome (MDS). Surprisingly, the deoxyribonucleoside analog 5-Aza-2′deoxycytidine (5-Aza-CdR) did not have a similar effect on survival in a large clinical trial. Both drugs are thought to exert their effects after incorporation into DNA by covalent binding of DNA methyltransferase (DNMT). While 5-Aza-CdR is incorporated into only DNA, 5-Aza-CR is also incorporated into RNA. Here, we have analyzed whether this difference in nucleic acid incorporation may influence the capacities of these drugs to regulate the expression of mRNA and microRNAs (miRNA), which may potentially affect the activities of the drugs in patients.A hematopoietic (HL-60; acute myeloid leukemia) and a solid (T24; transitional cell carcinoma) cancer cell line were treated with equitoxic doses of 5-Aza-CR and 5-Aza-CdR for 24 hrs, and the immediate (day 2) and lasting (day 8) effects on RNA expression examined. There was considerable overlap between the RNAs heritably upregulated by both drugs on day 8 but more RNAs were stably induced by the deoxy analog. Both drugs strongly induced expression of cancer testis antigens. On day 2 more RNAs were downregulated by 5-Aza-CR, particularly at higher doses. A remarkable downregulation of miRNAs and a significant upregulation of tRNA synthetases and other genes involved in amino acid metabolism was observed in T24 cells.Overall, this suggests that significant differences exist in the immediate action of the two drugs, however the dominant pattern of the lasting, and possible heritable changes, is overlapping

Integrative analysis for finding genes and networks involved in diabetes and other complex diseases

An integrative analysis combining genetic interactions and protein interactions can be used to identify candidate genes/proteins for type 1 diabetes and other complex diseases

Genetic effects on molecular network states explain complex traits

The complexity of many cellular and organismal traits results from the integration of genetic and environmental factors via molecular networks. Network structure and effect propagation are best understood at the level of functional modules, but so far, no concept has been established to include the global network state. Here, we show when and how genetic perturbations lead to molecular changes that are confined to small parts of a network versus when they lead to modulation of network states. Integrating multi-omics profiling of genetically heterogeneous budding and fission yeast strains with an array of cellular traits identified a central state transition of the yeast molecular network that is related to PKA and TOR (PT) signaling. Genetic variants affecting this PT state globally shifted the molecular network along a single-dimensional axis, thereby modulating processes including energy and amino acid metabolism, transcription, translation, cell cycle control, and cellular stress response. We propose that genetic effects can propagate through large parts of molecular networks because of the functional requirement to centrally coordinate the activity of fundamental cellular processes

Familial co-occurrence of congenital heart defects follows distinct patterns

Aims Congenital heart defects (CHD) affect almost 1% of all live born children and the number of adults with CHD is increasing. In families where CHD has occurred previously, estimates of recurrence risk, and the type of recurring malformation are important for counselling and clinical decision-making, but the recurrence patterns in families are poorly understood. We aimed to determine recurrence patterns, by investigating the co-occurrences of CHD in 1163 families with known malformations, comprising 3080 individuals with clinically confirmed diagnosis. Methods and results We calculated rates of concordance and discordance for 41 specific types of malformations, observing a high variability in the rates of concordance and discordance. By calculating odds ratios for each of 1640 pairs of discordant lesions observed between affected family members, we were able to identify 178 pairs of malformations that co-occurred significantly more or less often than expected in families. The data show that distinct groups of cardiac malformations co-occur in families, suggesting influence from underlying developmental mechanisms. Analysis of human and mouse susceptibility genes showed that they were shared in 19% and 20% of pairs of co-occurring discordant malformations, respectively, but none of malformations that rarely co-occur, suggesting that a significant proportion of co-occurring lesions in families is caused by overlapping susceptibility genes. Conclusion Familial CHD follow specific patterns of recurrence, suggesting a strong influence from genetically regulated developmental mechanisms. Co-occurrence of malformations in families is caused by shared susceptibility genes

Protease activity profiling of snake venoms using high-throughput peptide screening

Snake venom metalloproteinases (SVMPs) and snake venom serine proteinases (SVSPs) are among the most abundant enzymes in many snake venoms, particularly among viperids. These proteinases are responsible for some of the clinical manifestations classically seen in viperid envenomings, including hemorrhage, necrosis, and coagulopathies. The objective of this study was to investigate the enzymatic activities of these proteins using a high-throughput peptide library to screen for the proteinase targets of the venoms of five viperid (Echis carinatus, Bothrops asper, Daboia russelii, Bitis arietans, Bitis gabonica) and one elapid (Naja nigricollis) species of high medical importance. The proteinase activities of these venoms were each tested against 360 peptide substrates, yielding 2160 activity profiles. A nonlinear regression model that accurately described the observed enzymatic activities was fitted to the experimental data, allowing for the comparison of cleavage rates across species. In this study, previously unknown protein targets of snake venom proteinases were identified, potentially implicating novel human and animal proteins that may be involved in the pathophysiology of viper envenomings. The functional relevance of these targets was further evaluated and discussed. These new findings may contribute to our understanding of the clinical manifestations and underlying biochemical mechanisms of snakebite envenoming by viperid species