Scatter plots of GC content and read coverage of real Illumina data.

<p>The data sets are from <i>S. aureus</i> USA300 (A) and <i>S. aureus</i> MRSA252 (B) genomes. Read coverage is normalized to the mean value, which is represented by a horizontal dashed line. A vertical dashed line denotes the mean GC content. The data points are fitted by a straight line and the slope is defined as the degree of GC bias. The two cases represent a negative and positive GC bias, respectively.</p

Correlation between the degree of GC bias obtained using reference sequences and assembled contigs.

<p>The correlation is calculated for thirteen Illumina data sets, including eight data sets by Edena, four data sets by Vevlet and one data set by ABySS. The high R² value (0.88) indicates that estimating the degree of GC bias using the assembled contigs is appropriate.</p

Distributions of coverage depths at all bases and at error bases.

<p>Distributions of coverage depths at error bases (red curves) are compared with those at all bases (blue curves) in the Velvet assemblies of three bacterial genomes: <i>E. coli</i> (A), <i>S. aureus</i> (B), and <i>M. tuberculosis</i> (C), using data simulated at a strong negative (left column), zero (middle column), and strong positive (right column) GC bias.</p

Effects of GC Bias in Next-Generation-Sequencing Data on <i>De Novo</i> Genome Assembly

<div><p>Next-generation-sequencing (NGS) has revolutionized the field of genome assembly because of its much higher data throughput and much lower cost compared with traditional Sanger sequencing. However, NGS poses new computational challenges to <i>de novo</i> genome assembly. Among the challenges, GC bias in NGS data is known to aggravate genome assembly. However, it is not clear to what extent GC bias affects genome assembly in general. In this work, we conduct a systematic analysis on the effects of GC bias on genome assembly. Our analyses reveal that GC bias only lowers assembly completeness when the degree of GC bias is above a threshold. At a strong GC bias, the assembly fragmentation due to GC bias can be explained by the low coverage of reads in the GC-poor or GC-rich regions of a genome. This effect is observed for all the assemblers under study. Increasing the total amount of NGS data thus rescues the assembly fragmentation because of GC bias. However, the amount of data needed for a full rescue depends on the distribution of GC contents. Both low and high coverage depths due to GC bias lower the accuracy of assembly. These pieces of information provide guidance toward a better <i>de novo</i> genome assembly in the presence of GC bias.</p></div

Completeness of the <i>E.coli</i> assemblies using data of various coverage.

<p>Assembly completeness is measured by N50 length of the corrected contigs, which are output by eight assemblers when treating simulated reads of various coverage (50X, 100X, 250X, 500X, 1000X, and 2000X) at a zero (blue line) and a strong positive GC bias (slope 3.6, pink line).</p

Number of “major” errors in the assemblies at a strong negative, zero, and strong positive GC bias by the eight assemblers for the three bacteria.

<p>Number of “major” errors in the assemblies at a strong negative, zero, and strong positive GC bias by the eight assemblers for the three bacteria.</p

Scatter plots of GC content and read coverage of data simulated with various degrees of background fluctuations.

<p>The data are simulated from the <i>E. coli</i> genome at three degrees of background fluctuations: zero (top row), 10 (middle row), and 20 (bottom row). At each degree of background fluctuation, we simulated PE reads at a strong negative (A), zero (B), and a strong positive (C) GC bias, respectively.</p

Ratio of corrected N50 length at a strong GC bias to that at no GC bias.

<p>Ratio of the corrected N50 length at a strong negative GC bias (A) and a strong positive GC bias (B) to that at no GC bias when assembling the data of five species (in different colors) using eight assemblers.</p

Corrected N50 length of assemblies at three background fluctuations.

<p>We show the corrected N50 length in eight assemblies of three bacterial genomes: <i>E. coli</i> (A), <i>S. aureus</i> (B), and <i>M. tuberculosis</i> (C), using simulated data at three degrees of background fluctuations (x-axis), each at three degrees of GC bias: negative (yellow), zero (dark blue), and positive (pink).</p

Correlation between the degree of GC bias and two statistics of GC contents.

<p>No correlation can be observed between the degree of GC bias (y-axis) and either the mean GC content (A) or the standard deviation of GC contents (B).</p