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1.  CisGenome Browser: a flexible tool for genomic data visualization 
Bioinformatics  2010;26(14):1781-1782.
Summary: We present an open source, platform independent tool, called CisGenome Browser, which can work together with any other data analysis program to serve as a flexible component for genomic data visualization. It can also work by itself as a standalone genome browser. By working as a light-weight web server, CisGenome Browser is a convenient tool for data sharing between labs. It has features that are specifically designed for ultra high-throughput sequencing data visualization.
Availability: http://biogibbs.stanford.edu/∼jiangh/browser/
Contact: jiangh@stanford.edu
doi:10.1093/bioinformatics/btq286
PMCID: PMC2894522  PMID: 20513664
2.  Dynamic Distribution of SeqA Protein across the Chromosome of Escherichia coli K-12 
mBio  2010;1(1):e00012-10.
ABSTRACT
The bacterial SeqA protein binds to hemi-methylated GATC sequences that arise in newly synthesized DNA upon passage of the replication machinery. In Escherichia coli K-12, the single replication origin oriC is a well-characterized target for SeqA, which binds to multiple hemi-methylated GATC sequences immediately after replication has initiated. This sequesters oriC, thereby preventing reinitiation of replication. However, the genome-wide DNA binding properties of SeqA are unknown, and hence, here, we describe a study of the binding of SeqA across the entire Escherichia coli K-12 chromosome, using chromatin immunoprecipitation in combination with DNA microarrays. Our data show that SeqA binding correlates with the frequency and spacing of GATC sequences across the entire genome. Less SeqA is found in highly transcribed regions, as well as in the ter macrodomain. Using synchronized cultures, we show that SeqA distribution differs with the cell cycle. SeqA remains bound to some targets after replication has ceased, and these targets locate to genes encoding factors involved in nucleotide metabolism, chromosome replication, and methyl transfer.
IMPORTANCE
DNA replication in bacteria is a highly regulated process. In many bacteria, a protein called SeqA plays a key role by binding to newly replicated DNA. Thus, at the origin of DNA replication, SeqA binding blocks premature reinitiation of replication rounds. Although most investigators have focused on the role of SeqA at replication origins, it has long been suspected that SeqA has a more pervasive role. In this study, we describe how we have been able to identify scores of targets, across the entire Escherichia coli chromosome, to which SeqA binds. Using synchronously growing cells, we show that the distribution of SeqA between these targets alters as replication of the chromosome progresses. This suggests that sequential changes in SeqA distribution orchestrate a program of gene expression that ensures coordinated DNA replication and cell division.
doi:10.1128/mBio.00012-10
PMCID: PMC2912659  PMID: 20689753
3.  Variable structure motifs for transcription factor binding sites 
BMC Genomics  2010;11:30.
Background
Classically, models of DNA-transcription factor binding sites (TFBSs) have been based on relatively few known instances and have treated them as sites of fixed length using position weight matrices (PWMs). Various extensions to this model have been proposed, most of which take account of dependencies between the bases in the binding sites. However, some transcription factors are known to exhibit some flexibility and bind to DNA in more than one possible physical configuration. In some cases this variation is known to affect the function of binding sites. With the increasing volume of ChIP-seq data available it is now possible to investigate models that incorporate this flexibility. Previous work on variable length models has been constrained by: a focus on specific zinc finger proteins in yeast using restrictive models; a reliance on hand-crafted models for just one transcription factor at a time; and a lack of evaluation on realistically sized data sets.
Results
We re-analysed binding sites from the TRANSFAC database and found motivating examples where our new variable length model provides a better fit. We analysed several ChIP-seq data sets with a novel motif search algorithm and compared the results to one of the best standard PWM finders and a recently developed alternative method for finding motifs of variable structure. All the methods performed comparably in held-out cross validation tests. Known motifs of variable structure were recovered for p53, Stat5a and Stat5b. In addition our method recovered a novel generalised version of an existing PWM for Sp1 that allows for variable length binding. This motif improved classification performance.
Conclusions
We have presented a new gapped PWM model for variable length DNA binding sites that is not too restrictive nor over-parameterised. Our comparison with existing tools shows that on average it does not have better predictive accuracy than existing methods. However, it does provide more interpretable models of motifs of variable structure that are suitable for follow-up structural studies. To our knowledge, we are the first to apply variable length motif models to eukaryotic ChIP-seq data sets and consequently the first to show their value in this domain. The results include a novel motif for the ubiquitous transcription factor Sp1.
doi:10.1186/1471-2164-11-30
PMCID: PMC2824720  PMID: 20074339

Results 1-3 (3)