High-quality draft assemblies of mammalian genomes from massively parallel sequence data

• DOI: 10.1073/pnas.1017351108
• Publication Date: 2010-12-28T01:45:14Z
• Authors: Sante Gnerre; Iain MacCallum; Dariusz Przybylski; Filipe J. Ribeiro; Joshua N. Burton; Bruce J. Walker; Ted Sharpe; Giles Hall; Terrance P. Shea; Sean Sykes; Aaron M. Berlin; Daniel Aird; Maura Costello; Riza Daza; Louise Williams; Robert Nicol; Andreas Gnirke; Chad Nusbaum; Eric S. Lander; David B. Jaffe
• Keywords: 0301 basic medicine; Internet; Mice; 0303 health sciences; 03 medical and health sciences; Genome; Animals; Humans; Reproducibility of Results; Genomics; Sequence Analysis, DNA; Algorithms; Software

Massively parallel DNA sequencing technologies are revolutionizing genomics by making it possible to generate billions of relatively short (~100-base) sequence reads at very low cost. Whereas such data can be readily used for a wide range of biomedical applications, it has proven difficult to use them to generate high-quality de novo genome assemblies of large, repeat-rich vertebrate genomes. To date, the genome assemblies generated from such data have fallen far short of those obtained with the older (but much more expensive) capillary-based sequencing approach. Here, we report the development of an algorithm for genome assembly, ALLPATHS-LG, and its application to massively parallel DNA sequence data from the human and mouse genomes, generated on the Illumina platform. The resulting draft genome assemblies have good accuracy, short-range contiguity, long-range connectivity, and coverage of the genome. In particular, the base accuracy is high (≥99.95%) and the scaffold sizes (N50 size = 11.5 Mb for human and 7.2 Mb for mouse) approach those obtained with capillary-based sequencing. The combination of improved sequencing technology and improved computational methods should now make it possible to increase dramatically the de novo sequencing of large genomes. The ALLPATHS-LG program is available at http://www.broadinstitute.org/science/programs/genome-biology/crd .