LOCAS – A Low Coverage Assembly Tool for Resequencing Projects Juliane D. Klein1*, Stephan Ossowski2, Korbinian Schneeberger3, Detlef Weigel4, Daniel H. Huson1 1 Chair of Algorithms in Bioinformatics, University of Tu¨ bingen, Tu¨ bingen, Germany, 2 Genes and Disease Program, Center for Genomic Regulation and Universitat Pompeu Fabra, Barcelona, Spain, 3 Department of Plant Developmental Biology, Max-Planck-Institute for Plant Breeding Research, Ko¨ ln, Germany, 4 Department of Molecular Biology, Max Planck Institute for Developmental Biology, Tu¨ bingen, Germany Abstract Motivation: Next Generation Sequencing (NGS) is a frequently applied approach to detect sequence variations between highly related genomes. Recent large-scale re-sequencing studies as the Human 1000 Genomes Project utilize NGS data of low coverage to afford sequencing of hundreds of individuals. Here, SNPs and micro-indels can be detected by applying an alignment-consensus approach. However, computational methods capable of discovering other variations such as novel insertions or highly diverged sequence from low coverage NGS data are still lacking. Results: We present LOCAS, a new NGS assembler particularly designed for low coverage assembly of eukaryotic genomes using a mismatch sensitive overlap-layout-consensus approach. LOCAS assembles homologous regions in a homology- guided manner while it performs de novo assemblies of insertions and highly polymorphic target regions subsequently to an alignment-consensus approach. LOCAS has been evaluated in homology-guided assembly scenarios with low sequence coverage of Arabidopsis thaliana strains sequenced as part of the Arabidopsis 1001 Genomes Project. While assembling the same amount of long insertions as state-of-the-art NGS assemblers, LOCAS showed best results regarding contig size, error rate and runtime. Conclusion: LOCAS produces excellent results for homology-guided assembly of eukaryotic genomes with short reads and low sequencing depth, and therefore appears to be the assembly tool of choice for the detection of novel sequence variations in this scenario. Citation: Klein JD, Ossowski S, Schneeberger K, Weigel D, Huson DH (2011) LOCAS – A Low Coverage Assembly Tool for Resequencing Projects. PLoS ONE 6(8): e23455. doi:10.1371/journal.pone.0023455 Editor: Ying Xu, University of Georgia, United States of America Received April 7, 2011; Accepted July 18, 2011; Published August 15, 2011 Copyright: 2011 Klein et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: The study was supported by the BMBF [German Plant Genome Initiative GABI-GNADE]. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: The authors have declared that no competing interests exist. * E-mail: kleinj@informatik.uni-tuebingen.de Introduction Since the introduction of the first Next Generation Sequencing (NGS) technology in 2005, the throughput and cost-efficiency of sequencing has greatly increased and continues to do so. For example, at present, the Illumina HiSeq 2000 yields up to 600 Gb of sequencing data in one paired-end run taking about one week. While the accuracy of new sequencing technologies is similar to that of Sanger sequencing, the achievable read length has decreased from 1 kb to around 150 bases or less for Illumina’s GAIIx or HiSeq and Applied Biosystem’s SOLiD instruments, or to less than 500 bases for the GS FLX Titanium instrument from Roche/454 Life Sciences. NGS technologies have many different applications, including genome sequencing and resequencing, metagenome analysis, transcriptome analysis and chromatin immunoprecipitation (ChIP)-sequencing. To afford genome sequencing of hundreds to thousands of individuals large-scale re-sequencing projects like the Human 1000 Genomes Project utilize low coverage sequencing to a depth of less than 56[1], followed by mapping of reads to a known reference genome from the same species. This alignment-consensus approach, used by e.g. SOAPsnp [2], VAAL [3], MAQ [4], Pyrobayes [5], SHORE [6] or SHRiMP [7], is capable to detect sequence variants like single-nucleotide polymorphisms (SNPs) or small insertions or deletions (micro-indels) [8,9]. However, regions with high divergence will not be discovered with the alignment- consensus approach since the respective reads are mostly unalign- able to the reference genome. Various approaches to estimate copy number variants and other large rearrangements (commonly referred to as structural variants) [4,6,10] from read quantity or mate-pair data have been introduced but these strategies do not reveal additional sequence information. As de novo assembly does not rely on read alignments against a reference genome, it appears to be better suited for studying unknown or highly diverged regions. Unfortunately, de novo assembly of short reads still poses unsolved issues for eukaryotic genomes. Here, the size and complexity of the genomes place high demands on computational power, which cannot be met by standard servers. Typically, such assemblies also suffer from a high number of short contigs. To cope with these problems, several strategies have been proposed, e.g. reduced representation libraries [10], gene-boosted assembly [11], transcriptome assembly [12] or homology-guided assembly [13]. PLoS ONE | www.plosone.org 1 August 2011 | Volume 6 | Issue 8 | e23455