SOP(3)v2: web-based selection of oligonucleotide primer trios for genotyping of human and mouse polymorphisms

SOP(3)v2 is a database-driven graphical web-based application for facilitating genotyping assay design. SOP(3)v2 accepts data input in numerous forms, including gene names, reference sequence numbers and physical location. For each entry, the application presents a set of recommended forward and reverse PCR primers, along with a sequencing primer, which is optimized for sequence-based genotyping assays. SOP(3)v2-generated oligonucleotide primer trios enable analysis of single nucleotide polymorphisms (SNPs) as well as insertion/deletion polymorphisms found in genomic DNA. The application's database was generated by warehousing information from the National Center for Biotechnology Information (NCBI) dbSNP database, genomic DNA sequences from human and mouse, and LocusLink gene attribute information. Query results can be sorted by their biological relevance, such as nonsynonymous coding changes or physical location. Human polymorphism queries may specify ethnicity, haplotype and validation status. Primers are developed using SOP(3)v2's core algorithm for evaluating primer candidates through stability tests and are suitable for use with sequence-based genotyping methods requiring locus-specific amplification. The method has undergone laboratory validation. Of the SOP(3)v2-designed primer trios that were tested, a majority (>80%) have successfully produced genotyping data. The application may be accessed via the web at

Predicting Transcription Factor Specificity with All-Atom Models

The binding of a transcription factor (TF) to a DNA operator site can initiate or repress the expression of a gene. Computational prediction of sites recognized by a TF has traditionally relied upon knowledge of several cognate sites, rather than an ab initio approach. Here, we examine the possibility of using structure-based energy calculations that require no knowledge of bound sites but rather start with the structure of a protein-DNA complex. We study the PurR E. coli TF, and explore to which extent atomistic models of protein-DNA complexes can be used to distinguish between cognate and non-cognate DNA sites. Particular emphasis is placed on systematic evaluation of this approach by comparing its performance with bioinformatic methods, by testing it against random decoys and sites of homologous TFs. We also examine a set of experimental mutations in both DNA and the protein. Using our explicit estimates of energy, we show that the specificity for PurR is dominated by direct protein-DNA interactions, and weakly influenced by bending of DNA.Comment: 26 pages, 3 figure

Role of carbon dioxide and ion transport in the formation of sub-embryonic fluid by the blastoderm of the Japanese quail

1. The explanted blastoderm of the Japanese quail was used to explore the role of ions and carbon dioxide in determining the rate of sub-embryonic fluid (SEF) production between 54 and 72 h of incubation. 2. Amiloride, an inhibitor of Na+/H+ exchange, at concentrations of 10-3 to 10-6 M substantially decreased the rate of SEF production when added to the albumen culture medium. N-ethylmaleimide, an inhibitor of V type H+ ATPase, also decreased this rate but only to a small extent at the highest dose applied, 10-3 M. Both inhibitors had no effect on SEF production when added to the SEF. 3. The inhibitors of cellular bicarbonate and chloride exchange, 4-acetamido-4-'isothiocyano-2, 2-'disulphonic acid (SITS) and 4,4'diisothiocyanostilbene-2,2-'disulphonic acid (DIDS), had no effect upon SEF production. 4. Ouabain, an inhibitor of Na+/K+ ATPase, decreased SEF production substantially at all concentrations added to the SEF (10-3 to 10-6 M). Three sulphonamide inhibitors of carbonic anhydrase, acetazolamide, ethoxzolamide and benzolamide, decreased SEF production when added to the SEF at concentrations of 10-3 to 10-6 M. Benzolamide was by far the most potent. Neither ouabain nor the sulphonamides altered SEF production when added to the albumen culture medium. 5. Using a cobalt precipitation method, carbonic anhydrase activity was localised to the endodermal cells of the area vasculosa. The carbonic anhydrase activity was primarily associated with the lateral plasma membranes, which together with the potent inhibitory effect of benzolamide, suggests the carbonic anhydrase of these cells is the membrane-associated form, CA IV. 6. The changes in SEF composition produced by inhibitors were consistent with the production of SEF by local osmotic gradients. 7. It is concluded that a Na+/K+ ATPase is located on the basolateral membranes of the endodermal cells of the area vasculosa , and that a sodium ion/hydrogen ion exchanger is located on their apical surfaces. Protons for this exchanger would be provided by the hydration of CO2 catalysed by the membrane-associated carbonic anhydrase. Furthermore, it is proposed that the prime function of the endodermal cells of the area vasculosa is the production of SEF

Recognition models to predict DNA-binding specificities of homeodomain proteins

Motivation: Recognition models for protein-DNA interactions, which allow the prediction of specificity for a DNA-binding domain based only on its sequence or the alteration of specificity through rational design, have long been a goal of computational biology. There has been some progress in constructing useful models, especially for C2H2 zinc finger proteins, but it remains a challenging problem with ample room for improvement. For most families of transcription factors the best available methods utilize k-nearest neighbor (KNN) algorithms to make specificity predictions based on the average of the specificities of the k most similar proteins with defined specificities. Homeodomain (HD) proteins are the second most abundant family of transcription factors, after zinc fingers, in most metazoan genomes, and as a consequence an effective recognition model for this family would facilitate predictive models of many transcriptional regulatory networks within these genomes

Sodium Transport in Capillaries Isolated from Rat Brain

Brain capillary endothelial cells form a bloodbrain barrier (BBB) that appears to play a role in fluid and ion homeostasis in brain. One important transport system that may be involved in this regulatory function is the Na + ,K + -ATPase that was previously demonstrated to be present in isolated brain capillaries. The goal of the present study was to identify additional Na + transport systems in brain capillaries that might contribute to BBB function. Microvessels were isolated from rat brains and 22 Na + uptake by and efflux from the cells were studied. Total 22 Na + uptake was increased and the rate of 22 Na + efflux was decreased by ouabain, confirming the presence of Na + ,K + -ATPase in capillary cells. After inhibition of Na + ,K + -ATPase activity, another saturable Na + transport mechanism became apparent. Capillary uptake of 22 Na + was stimulated by an elevated concentration of Na + or H + inside the cells and inhibited by extracellular Na + , H + , Li + , and NH 4 + . Amiloride inhibited 22 Na + uptake with a K i between 10 −5 and 10 −6 M but there was no effect of 1 mM furosemide on 22 Na + uptake by the isolated microvessels. These results indicate the presence in brain capillaries of a transport system capable of mediating Na + / Na + and Na + /H + exchange. As a similar transport system does not appear to be present on the luminal membrane of the brain capillary endothelial cell, it is proposed that Na + /H + exchange occurs primarily across the antiluminal membrane.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/66187/1/j.1471-4159.1983.tb09065.x.pd

An intuitionistic approach to scoring DNA sequences against transcription factor binding site motifs

Background: Transcription factors (TFs) control transcription by binding to specific regions of DNA called transcription factor binding sites (TFBSs). The identification of TFBSs is a crucial problem in computational biology and includes the subtask of predicting the location of known TFBS motifs in a given DNA sequence. It has previously been shown that, when scoring matches to known TFBS motifs, interdependencies between positions within a motif should be taken into account. However, this remains a challenging task owing to the fact that sequences similar to those of known TFBSs can occur by chance with a relatively high frequency. Here we present a new method for matching sequences to TFBS motifs based on intuitionistic fuzzy sets (IFS) theory, an approach that has been shown to be particularly appropriate for tackling problems that embody a high degree of uncertainty. Results: We propose SCintuit, a new scoring method for measuring sequence-motif affinity based on IFS theory. Unlike existing methods that consider dependencies between positions, SCintuit is designed to prevent overestimation of less conserved positions of TFBSs. For a given pair of bases, SCintuit is computed not only as a function of their combined probability of occurrence, but also taking into account the individual importance of each single base at its corresponding position. We used SCintuit to identify known TFBSs in DNA sequences. Our method provides excellent results when dealing with both synthetic and real data, outperforming the sensitivity and the specificity of two existing methods in all the experiments we performed. Conclusions: The results show that SCintuit improves the prediction quality for TFs of the existing approaches without compromising sensitivity. In addition, we show how SCintuit can be successfully applied to real research problems. In this study the reliability of the IFS theory for motif discovery tasks is proven

Features of mammalian microRNA promoters emerge from polymerase II chromatin immunoprecipitation data

Background: MicroRNAs (miRNAs) are short, non-coding RNA regulators of protein coding genes. miRNAs play a very important role in diverse biological processes and various diseases. Many algorithms are able to predict miRNA genes and their targets, but their transcription regulation is still under investigation. It is generally believed that intragenic miRNAs (located in introns or exons of protein coding genes) are co-transcribed with their host genes and most intergenic miRNAs transcribed from their own RNA polymerase II (Pol II) promoter. However, the length of the primary transcripts and promoter organization is currently unknown. Methodology: We performed Pol II chromatin immunoprecipitation (ChIP)-chip using a custom array surrounding regions of known miRNA genes. To identify the true core transcription start sites of the miRNA genes we developed a new tool (CPPP). We showed that miRNA genes can be transcribed from promoters located several kilobases away and that their promoters share the same general features as those of protein coding genes. Finally, we found evidence that as many as 26% of the intragenic miRNAs may be transcribed from their own unique promoters. Conclusion: miRNA promoters have similar features to those of protein coding genes, but miRNA transcript organization is more complex. © 2009 Corcoran et al

Markov Chain-based Promoter Structure Modeling for Tissue-specific Expression Pattern Prediction

Transcriptional regulation is the first level of regulation of gene expression and is therefore a major topic in computational biology. Genes with similar expression patterns can be assumed to be co-regulated at the transcriptional level by promoter sequences with a similar structure. Current approaches for modeling shared regulatory features tend to focus mainly on clustering of cis-regulatory sites. Here we introduce a Markov chain-based promoter structure model that uses both shared motifs and shared features from an input set of promoter sequences to predict candidate genes with similar expression. The model uses positional preference, order, and orientation of motifs. The trained model is used to score a genomic set of promoter sequences: high-scoring promoters are assumed to have a structure similar to the input sequences and are thus expected to drive similar expression patterns. We applied our model on two datasets in Caenorhabditis elegans and in Ciona intestinalis. Both computational and experimental verifications indicate that this model is capable of predicting candidate promoters driving similar expression patterns as the input-regulatory sequences. This model can be useful for finding promising candidate genes for wet-lab experiments and for increasing our understanding of transcriptional regulation