Merging the physical properties of DNA with genomic annotations in Ensembl

On a DNA sequence, we attach information about its features and attributes, and this kind of information is called annotations. Over the past few years there has been a development to gather and group annotations to a central service, so that scientists will be able to compare all kinds of annotations. Comparisons are performed with the aim of identifying related biological features. Ensembl is such an annotation centre, and this thesis addresses the issue of integrating an annotation made by the stitch profile algorithm into Ensembl. This stitch profile algorithm is a novel way of calculating the different conformations corresponding to a DNA melting profile, i.e. modeling of the physical attributes of the DNA double helix, so that it becomes easier to see what state the DNA molecule is in. We then analyze the how accurately the stitch profiles correlate to the annotations in Ensembl

Stitchprofiles.uio.no: analysis of partly melted DNA conformations using stitch profiles

In this study, we describe a web server that performs computations on DNA melting, thus predicting the localized separation of the two strands for sequences provided by the users. The output types are stitch profiles, melting curves, probability profiles, etc. Stitch profile diagrams visualize the ensemble of alternative conformations that DNA can adopt with different probabilities. For example, a stitch profile shows the possible loop openings in terms of their locations, sizes, probabilities and fluctuations at a given temperature. Sequences with lengths up to several tens or hundreds of kilobase pairs can be analysed. The tools are freely available at

The Human Genomic Melting Map

In a living cell, the antiparallel double-stranded helix of DNA is a dynamically changing structure. The structure relates to interactions between and within the DNA strands, and the array of other macromolecules that constitutes functional chromatin. It is only through its changing conformations that DNA can organize and structure a large number of cellular functions. In particular, DNA must locally uncoil, or melt, and become single-stranded for DNA replication, repair, recombination, and transcription to occur. It has previously been shown that this melting occurs cooperatively, whereby several base pairs act in concert to generate melting bubbles, and in this way constitute a domain that behaves as a unit with respect to local DNA single-strandedness. We have applied a melting map calculation to the complete human genome, which provides information about the propensities of forming local bubbles determined from the whole sequence, and present a first report on its basic features, the extent of cooperativity, and correlations to various physical and biological features of the human genome. Globally, the melting map covaries very strongly with GC content. Most importantly, however, cooperativity of DNA denaturation causes this correlation to be weaker at resolutions fewer than 500 bps. This is also the resolution level at which most structural and biological processes occur, signifying the importance of the informational content inherent in the genomic melting map. The human DNA melting map may be further explored at http://meltmap.uio.no

Correlations of Melting Temperature (Tm) with G + C Content

<p>The correlation coefficients between GC content and Tm are plotted as a function of window sizes. For each chromosome, excluding the segments which contain unknown bases (N's), the correlation coefficient was calculated from all pairs of GC content and average Tm over all nonoverlapping segments of a given window size. Across the chromosomes, the average correlation coefficients and SDs were calculated for each window size. The figure shows the average correlations with SDs (error bars) for window sizes from 10 bp to 1 Mbp for the human chromosomes (red) and the randomized chromosomes (blue).</p

Scatter Plot of Melting Temperature versus GC Content of Flat Melting Segments

<p>Using Chromosome 21, the relationship between local GC content and melting temperature was examined for all flat segments of 50 bps. <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.0030093#pcbi-0030093-g004" target="_blank">Figure 4</a> shows the scatter plot of melting temperature versus GC content. Each data point in this figure represents a 50-bp flat segment. The red dots represent those segments that have higher melting temperatures (Tm) in its neighboring regions at both sides (denoted as category I). The blue dots represent those that have lower Tm in its neighbors (denoted as category III). And, the green dots represent those that have lower Tm in one side neighbor and higher Tm in another (denoted as category II).</p

EpiGRAPH-Generated Diagrams Comparing Genomic Regions with Distinct Melting Profiles

<div><p>Displays boxplots comparing two genomic features between regions of high and low melting temperature (A) and <i>flat</i> and <i>nonflat</i> melting segments (B). Standard boxplots are drawn for the region itself and for ten windows surrounding the region, from −20 Kbp to +20 Kbp <i>(x</i>-axis), in order to capture neighborhood effects. The <i>y</i>-axis shows averages and distribution of the analyzed genomic feature. For each window, two boxplots are drawn, one for each class of melting profiles.</p><p>(A) Regions are characterized by the extreme melting temperatures observed throughout the human genome. “Class 0” comprises 20 regions having low melting temperatures (below 50 °C in all cases), while “class 1” comprises 20 cases having high melting temperature (above 90 °C in all cases). Comparison with the average solvent-accessible surface area of the DNA (as predicted for each base pair using sequence trimers for which solvent accessibility has been established experimentally by the hydroxyl radical method [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.0030093#pcbi-0030093-b064" target="_blank">64</a>]) shows that regions of high melting temperature exhibit substantially higher values than regions of low melting temperature. This is true not only for the region itself (center boxplot), but to a lesser extent also for its sequence neighborhood.</p><p>(B) Regions are characterized by a <i>flat</i>/<i>nonflat</i> segmentation algorithm of the melting profile. “Class 0” contains 50 flat segments having an end-to-end step height of ±0.11 °C or less, while “class 1” contains 50 nonflat segments defined as having an end-to-end step height of ±6 °C or more. All segments were taken from Chromosome 21, exhibit an equal melting temperature of 68 °C and a segment length of 19 or 20 bps. Comparison with the average length of Alu repeat overlap per 1,000 base pairs (as identified by RepeatMasker) shows that flat regions are typically free of Alu repeats, while nonflat regions frequently exhibit substantial overlap with Alu repeats.</p></div

Loop Entropy Factor Estimation

<p>The exact loop entropy factor for <i>σ</i> = 3.5 · 10⁻⁵, <i>α</i> = 1.75, and <i>d</i> = 0 is plotted (red) as a function of loop size, together with two Fixman–Freire approximations: a 10-exponentials approximation (blue), which is valid up to loop size about 10⁴, and a 21-exponentials approximation (green), which is valid up to loop size about 10⁸.</p