Sequence-based physical mapping of complex genomes by whole genome profiling

We present whole genome profiling (WGP), a novel next-generation sequencing-based physical mapping technology for construction of bacterial artificial chromosome (BAC) contigs of complex genomes, using Arabidopsis thaliana as an example. WGP leverages short read sequences derived from restriction fragments of two-dimensionally pooled BAC clones to generate sequence tags. These sequence tags are assigned to individual BAC clones, followed by assembly of BAC contigs based on shared regions containing identical sequence tags. Following in silico analysis of WGP sequence tags and simulation of a map of Arabidopsis chromosome 4 and maize, a WGP map of Arabidopsis thaliana ecotype Columbia was constructed de novo using a six-genome equivalent BAC library. Validation of the WGP map using the Columbia reference sequence confirmed that 350 BAC contigs (98%) were assembled correctly, spanning 97% of the 102-Mb calculated genome coverage. We demonstrate that WGP maps can also be generated for more complex plant genomes and will serve as excellent scaffolds to anchor genetic linkage maps and integrate whole genome sequence data.     

Fosmid-based physical mapping of the Histoplasma capsulatum genome

A fosmid library representing 10-fold coverage of the Histoplasma capsulatum G217B genome was used to construct a restriction-based physical map. The data obtained from three restriction endonuclease fingerprints, generated from each clone using BamHI, HindIII, and PstI endonucleases, were combined and used in FPC for automatic and manual contig assembly builds. Concomitantly, a whole-genome shotgun (WGS) sequencing of paired-end reads from plasmids and fosmids were assembled with PCAP, providing a predicted genome size of up to 43.5 Mbp and 17% repetitive DNA. Fosmid paired-end sequences in the WGS assembly provide anchoring information to the physical map and result in joining of existing physical map contigs into 84 clusters containing 9551 fosmid clones. Here, we detail mapping the Histoplasma capsulatum genome comprehensively in fosmids, resulting in an efficient paradigm for de novo sequencing that uses a map-assisted whole genome shotgun approach.     

Improved assembly and variant detection of a haploid human genome using single-molecule,high-fidelity long reads

The sequence and assembly of human genomes using long-read sequencing technologies has revolutionized our understanding of structural variation and genome organization. We compared the accuracy, continuity, and gene annotation of genome assemblies generated from either high-fidelity (HiFi) or continuous long-read (CLR) datasets from the same complete hydatidiform mole human genome. We find that the HiFi sequence data assemble an additional 10% of duplicated regions and more accurately represent the structure of tandem repeats, as validated with orthogonal analyses. As a result, an additional 5 Mbp of pericentromeric sequences are recovered in the HiFi assembly, resulting in a 2.5-fold increase in the NG50 within 1 Mbp of the centromere (HiFi 480.6 kbp, CLR 191.5 kbp). Additionally, the HiFi genome assembly was generated in significantly less time with fewer computational resources than the CLR assembly. Although the HiFi assembly has significantly improved continuity and accuracy in many complex regions of the genome, it still falls short of the assembly of centromeric DNA and the largest regions of segmental duplication using existing assemblers. Despite these shortcomings, our results suggest that HiFi may be the most effective standalone technology for de novo assembly of human genomes.     

Oxford Nanopore sequencing,hybrid error correction,and de novo assembly of a eukaryotic genome

Monitoring the progress of DNA molecules through a membrane pore has been postulated as a method for sequencing DNA for several decades. Recently, a nanopore-based sequencing instrument, the Oxford Nanopore MinION, has become available, and we used this for sequencing the Saccharomyces cerevisiae genome. To make use of these data, we developed a novel open-source hybrid error correction algorithm Nanocorr specifically for Oxford Nanopore reads, because existing packages were incapable of assembling the long read lengths (5–50 kbp) at such high error rates (between ∼5% and 40% error). With this new method, we were able to perform a hybrid error correction of the nanopore reads using complementary MiSeq data and produce a de novo assembly that is highly contiguous and accurate: The contig N50 length is more than ten times greater than an Illumina-only assembly (678 kb versus 59.9 kbp) and has >99.88% consensus identity when compared to the reference. Furthermore, the assembly with the long nanopore reads presents a much more complete representation of the features of the genome and correctly assembles gene cassettes, rRNAs, transposable elements, and other genomic features that were almost entirely absent in the Illumina-only assembly.Most DNA sequencing methods are based on either chemical cleavage of DNA molecules (Maxam and Gilbert 1977) or synthesis of new DNA strands (Sanger et al. 1977), which are used in the majority of today''s sequencing routines. In the more common synthesis-based methods, base analogs of one form or another are incorporated into a nascent DNA strand that is labeled either on the primer from which it originates or on the newly incorporated bases. This is the basis of the sequencing method used for most current sequencers, including Illumina, Ion Torrent, and Pacific Biosciences (PacBio) sequencing, and their earlier predecessors (Mardis 2008). Alternatively, it has been observed that individual DNA molecules could be sequenced by monitoring their progress through various types of pores (Kasianowicz et al. 1996; Venkatesan and Bashir 2011) originally envisioned as being pores derived from bacteriophage particles (Sanger et al. 1980). The advantages of this approach include potentially very long and unbiased sequence reads, because neither amplification nor chemical reactions are necessary for sequencing (Yang et al. 2013).Recently we began testing a sequencing device using nanopore technology from Oxford Nanopore Technologies (ONT) through their early access program (Eisenstein 2012). This device, the MinION, is a nanopore-based device in which pores are embedded in a membrane placed over an electrical detection grid. As DNA molecules pass through the pores, they create measureable alterations in the ionic current. The fluctuations are sequence dependent and thus can be used by a base-calling algorithm to infer the sequence of nucleotides in each molecule (Stoddart et al. 2009; Yang et al. 2013). As part of the library preparation protocol, a hairpin adapter is ligated to one end of a double-stranded DNA sample, while a “motor” protein is bound to the other to unwind the DNA and control the rate of nucleotides passing through the pore (Clarke et al. 2009). Under ideal conditions the leading template strand passes through the pore, followed by the hairpin adapter and then the complement strand. In such a run where both strands are sequenced, a consensus sequence of the molecule can be produced; these consensus reads are termed “2D reads” and have generally higher accuracy than reads from only a single pass of the molecule (“1D reads”).The ability to generate very long read lengths from a handheld sequencer opens the potential for many important applications in genomics, including de novo genome assembly of novel genomes, structural variation analysis of healthy or diseased samples, or even isoform resolution when applied to cDNA sequencing. However, both the “1D” and “2D” read types currently have a high error rate that limits their direct application to these problems and necessitates a new suite of algorithms. Here we report our experiences sequencing the Saccharomyces cerevisiae (yeast) genome with the instrument, including an in-depth analysis of the data characteristics and error model. We also describe our new hybrid error correction algorithm, Nanocorr, which leverages high-quality short-read MiSeq sequencing to computationally “polish” the long nanopore reads. After error correction, we then de novo assemble the genome using just the error-corrected long reads to produce a very high-quality assembly of the genome with each chromosome assembled into a small number of contigs at very high sequence identity. We further demonstrate that our error correction is nearly optimal: Our results with the error-corrected real data approach those produced using idealized simulated reads extracted directly from the reference genome itself. Finally, we validate these results by error correcting long Oxford Nanopore reads of the E. coli K12 genome sequenced at a different institution and produce an essentially perfect de novo assembly of the genome. As such, we believe our hybrid error correction and assembly approach will be generally applicable to many other sequencing projects.     

ABySS: A parallel assembler for short read sequence data

Widespread adoption of massively parallel deoxyribonucleic acid (DNA) sequencing instruments has prompted the recent development of de novo short read assembly algorithms. A common shortcoming of the available tools is their inability to efficiently assemble vast amounts of data generated from large-scale sequencing projects, such as the sequencing of individual human genomes to catalog natural genetic variation. To address this limitation, we developed ABySS (Assembly By Short Sequences), a parallelized sequence assembler. As a demonstration of the capability of our software, we assembled 3.5 billion paired-end reads from the genome of an African male publicly released by Illumina, Inc. Approximately 2.76 million contigs ≥100 base pairs (bp) in length were created with an N50 size of 1499 bp, representing 68% of the reference human genome. Analysis of these contigs identified polymorphic and novel sequences not present in the human reference assembly, which were validated by alignment to alternate human assemblies and to other primate genomes.Massively parallel sequencing platforms, such as the Illumina, Inc. Genome Analyzer, Applied Biosystems SOLiD System, and 454 Life Sciences (Roche) GS FLX, have provided an unprecedented increase in DNA sequencing throughput. Currently, these technologies produce high-quality short reads from 25 to 500 bp in length, which is substantially shorter than the capillary-based sequencing technology. However, the total number of base pairs sequenced in a given run is orders of magnitude higher. These two factors introduce a number of new informatics challenges, including the ability to perform de novo assembly of millions or even billions of short reads.The field of short read de novo assembly developed from pioneering work on de Bruijn graphs by Pevzner et al. (Pevzner and Tang 2001; Pevzner et al. 2001). The de Bruijn graph representation is prevalent in current short read assemblers, with Velvet (Zerbino and Birney 2008), ALLPATHS (Butler et al. 2008), and EULER-SR (Chaisson and Pevzner 2008) all following this approach. As an alternative, a prefix tree-based approach was introduced by Warren et al. (2007) with their early work on SSAKE. This paradigm was also followed in the VCAKE algorithm by Jeck et al. (2007), and in the SHARCGS algorithm by Dohm et al. (2007). On a third branch, Edena (Hernandez et al. 2008) was an adaptation of the traditional overlap-layout-consensus model to short reads.These short read de novo assemblers are single-threaded applications designed to run on a single processor. However, computation time and memory constraints limit the practical use of these implementations to genomes on the order of a megabase in size. On the other hand, as the next generation sequencing technologies have matured, and read lengths and throughput increase, the application of these technologies to structural analysis of large, complex genomes has become feasible. Notably, the 1000 Genomes Project (www.1000genomes.org) is undertaking the identification and cataloging of human genetic variation by sequencing the genomes of 1000 individuals from a diverse range of populations using short read platforms. Up to this point however, analysis of short read sequences from mammalian-sized genomes has been limited to alignment-based methods (Korbel et al. 2007; Bentley et al. 2008; Campbell et al. 2008; Wheeler et al. 2008) due to the lack of de novo assembly tools able to handle the vast amount of data generated by these projects.To assemble the very large data sets produced by sequencing individual human genomes, we have developed ABySS (Assembly By Short Sequencing). The primary innovation in ABySS is a distributed representation of a de Bruijn graph, which allows parallel computation of the assembly algorithm across a network of commodity computers. We demonstrate the ability of our assembler to quickly and accurately assemble 3.5 billion short sequence reads generated from whole-genome sequencing of a Yoruban male (NA18507) on the Illumina Genome Analyzer platform.     

A new strategy for genome assembly using short sequence reads and reduced representation libraries

We have developed a novel approach for using massively parallel short-read sequencing to generate fast and inexpensive de novo genomic assemblies comparable to those generated by capillary-based methods. The ultrashort (<100 base) sequences generated by this technology pose specific biological and computational challenges for de novo assembly of large genomes. To account for this, we devised a method for experimentally partitioning the genome using reduced representation (RR) libraries prior to assembly. We use two restriction enzymes independently to create a series of overlapping fragment libraries, each containing a tractable subset of the genome. Together, these libraries allow us to reassemble the entire genome without the need of a reference sequence. As proof of concept, we applied this approach to sequence and assembled the majority of the 125-Mb Drosophila melanogaster genome. We subsequently demonstrate the accuracy of our assembly method with meaningful comparisons against the current available D. melanogaster reference genome (dm3). The ease of assembly and accuracy for comparative genomics suggest that our approach will scale to future mammalian genome-sequencing efforts, saving both time and money without sacrificing quality.Genomes are the fundamental unit by which a species can be defined and form the foundation for deciphering how an organism develops, lives, dies, and is affected by disease. In addition, comparisons of genomes from related species have become a powerful method for finding functional sequences (Eddy 2005; Xie et al. 2005, 2007; Pennacchio et al. 2006; The ENCODE Project Consortium 2007). However, the high cost and effort needed to produce draft genomes with capillary-based sequencing technologies have limited genome-based biological exploration and evolutionary sequence comparisons to dozens of species (Margulies et al. 2007; Stark et al. 2007). This limitation is particularly true for mammalian-sized genomes, which are gigabases in size.With the advent of massively parallel short-read sequencing technologies (Bentley et al. 2008), the cost of sequencing DNA has been reduced by orders of magnitude, now making it possible to sequence hundreds or thousands of genomes. However, the reduced length of the sequence reads, compared with capillary-based approaches, poses new challenges in genome assembly. Here, we sought to address those experimental and bioinformatics hurdles by combining classical biochemical methodologies with new algorithms specifically tailored to handle massive quantities of short-read sequences.To date, the whole-genome shotgun (WGS) approach using massively parallel short-read sequencing has shown significant promise in silico (Butler et al. 2008) and has been applied to de novo sequencing and assembly of small genomes that do not contain an overabundance of low-complexity repetitive sequence (Hernandez et al. 2008). This presents a challenge when scaled to larger more complex genomes, where the information contained in a single short read cannot unambiguously place that read in the genome. Additionally, de novo assembly from WGS short-read sequencing currently requires large computational resources, on the order of hundreds of gigabytes of RAM, when scaled to larger genomes. As a compromise, current mammalian genomic analyses utilizing short-read sequencing technology either use alignments of individual reads against a reference genome (Ley et al. 2008; Wang et al. 2008) or require elaborate parallelization schemes across a large compute farm (Simpson et al. 2009) for assembly. Regardless of computational improvements, effectively handling repetitive sequences in a whole-genome assembly still remains a challenge.Our goal was to establish wet-lab and bioinformatics methods to rapidly sequence and assemble mammalian-sized genomes in a de novo fashion. Importantly, we wanted an approach that (1) did not rely on existing reference assemblies, (2) could be accomplished using commodity computational hardware, and (3) would yield functional assemblies useful for comparative sequence analyses at a fraction of the time and cost of existing capillary-based methods. To accomplish this, we propose a generic genome partitioning approach to solve both the biological and computational challenges of short-read assembly.Traditionally, partitioning of genomic libraries was accomplished through the use of clonal libraries of bacterial artificial chromosomes (BACs) (or yeast artificial chromosomes). This method accurately partitions genomes into more manageable subregions for sequencing and assembly. However, the high financial cost and overhead associated with creating and maintaining these libraries make this method unattractive for scaling to hundreds of genomes. In addition, a single BAC clone, which contains ∼200 kb of sequence, is not large enough to leverage the amount of sequence obtained from a single lane of Illumina data (currently ∼2.5 Gb of sequence), requiring the need for various pooling or indexing strategies (Meyer et al. 2007). Furthermore, virtually all BAC libraries exhibit some degree of variable cloning bias, with some regions overrepresented and others not at all. In silico studies have investigated the cost-saving potential of using a randomized BAC clone library with short-read sequencing (Sundquist et al. 2007); however, even with this shortcut, the clonal library concept does not lend itself to fast and cheap whole-genome partitioning.We propose a novel partitioning approach using restriction enzymes to create a series of reduced representation (RR) libraries by size fractionation. This method was originally described for single nucleotide polymorphism (SNP) discovery using Sanger-based sequencing methods on AB377 machines (Altshuler et al. 2000) and was subsequently used with massively parallel short-read sequencing (Van Tassell et al. 2008). Importantly, this method allows for the selection of a smaller reproducible subset of the genome for assembly. We extended this concept to create a series of distinct RR libraries consisting of similarly sized restriction fragments. Individually, these libraries represent a tractable subset of the genome for sequencing and assembly; when taken together, they represent virtually the entire genome. Using two separate restriction enzymes generates overlapping libraries, which allow for assembly of the genome without using a reference sequence.As proof of concept, we present here a de novo Drosophila melanogaster genomic assembly, equivalent in utility to a comparative grade assembly (Blakesley et al. 2004). Two enzymes were used to create a total of eight libraries. Short reads (∼36 bp) from each library were sequenced on the Illumina Genome Analyzer and assembled using the short-read assembler Velvet (Zerbino and Birney 2008). Contigs assembled from each library were merged into a single nonoverlapping meta assembly using the lightweight assembly program Minimus (Sommer et al. 2007). Furthermore, we sequenced genomic paired-end libraries with short and long inserts to order and orient the contigs into larger genomic scaffolds. When compared with a whole-genome shotgun assembly of the same data, we produce a higher quality assembly more rapidly by reducing the biological complexity and computational cost to assemble each library. Finally, we compare this assembly to the dm3 fly reference to highlight the accuracy of our assembly and utility for comparative sequence analyses. Our results demonstrate that this method is a rapid and cost-effective means to generate high-quality de novo assemblies of large genomes.     

Velvet: algorithms for de novo short read assembly using de Bruijn graphs

We have developed a new set of algorithms, collectively called "Velvet," to manipulate de Bruijn graphs for genomic sequence assembly. A de Bruijn graph is a compact representation based on short words (k-mers) that is ideal for high coverage, very short read (25-50 bp) data sets. Applying Velvet to very short reads and paired-ends information only, one can produce contigs of significant length, up to 50-kb N50 length in simulations of prokaryotic data and 3-kb N50 on simulated mammalian BACs. When applied to real Solexa data sets without read pairs, Velvet generated contigs of approximately 8 kb in a prokaryote and 2 kb in a mammalian BAC, in close agreement with our simulated results without read-pair information. Velvet represents a new approach to assembly that can leverage very short reads in combination with read pairs to produce useful assemblies.     

ALLPATHS: de novo assembly of whole-genome shotgun microreads

New DNA sequencing technologies deliver data at dramatically lower costs but demand new analytical methods to take full advantage of the very short reads that they produce. We provide an initial, theoretical solution to the challenge of de novo assembly from whole-genome shotgun "microreads." For 11 genomes of sizes up to 39 Mb, we generated high-quality assemblies from 80x coverage by paired 30-base simulated reads modeled after real Illumina-Solexa reads. The bacterial genomes of Campylobacter jejuni and Escherichia coli assemble optimally, yielding single perfect contigs, and larger genomes yield assemblies that are highly connected and accurate. Assemblies are presented in a graph form that retains intrinsic ambiguities such as those arising from polymorphism, thereby providing information that has been absent from previous genome assemblies. For both C. jejuni and E. coli, this assembly graph is a single edge encompassing the entire genome. Larger genomes produce more complicated graphs, but the vast majority of the bases in their assemblies are present in long edges that are nearly always perfect. We describe a general method for genome assembly that can be applied to all types of DNA sequence data, not only short read data, but also conventional sequence reads.     

De novo bacterial genome sequencing: millions of very short reads assembled on a desktop computer

Novel high-throughput DNA sequencing technologies allow researchers to characterize a bacterial genome during a single experiment and at a moderate cost. However, the increase in sequencing throughput that is allowed by using such platforms is obtained at the expense of individual sequence read length, which must be assembled into longer contigs to be exploitable. This study focuses on the Illumina sequencing platform that produces millions of very short sequences that are 35 bases in length. We propose a de novo assembler software that is dedicated to process such data. Based on a classical overlap graph representation and on the detection of potentially spurious reads, our software generates a set of accurate contigs of several kilobases that cover most of the bacterial genome. The assembly results were validated by comparing data sets that were obtained experimentally for Staphylococcus aureus strain MW2 and Helicobacter acinonychis strain Sheeba with that of their published genomes acquired by conventional sequencing of 1.5- to 3.0-kb fragments. We also provide indications that the broad coverage achieved by high-throughput sequencing might allow for the detection of clonal polymorphisms in the set of DNA molecules being sequenced.     

Dynamic building of a BAC clone tiling path for the Rat Genome Sequencing Project

CLONEPICKER is a software pipeline that integrates sequence data with BAC clone fingerprints to dynamically select a minimal overlapping clone set covering the whole genome. In the Rat Genome Sequencing Project (RGSP), a hybrid strategy of "clone by clone" and "whole genome shotgun" approaches was used to maximize the merits of both approaches. Like the "clone by clone" method, one key challenge for this strategy was to select a low-redundancy clone set that covered the whole genome while the sequencing is in progress. The CLONEPICKER pipeline met this challenge using restriction enzyme fingerprint data, BAC end sequence data, and sequences generated from individual BAC clones as well as WGS reads. In the RGSP, an average of 7.5 clones was identified from each side of a seed clone, and the minimal overlapping clones were reliably selected. Combined with the assembled BAC fingerprint map, a set of BAC clones that covered >97% of the genome was identified and used in the RGSP.     

GAGE: A critical evaluation of genome assemblies and assembly algorithms

New sequencing technology has dramatically altered the landscape of whole-genome sequencing, allowing scientists to initiate numerous projects to decode the genomes of previously unsequenced organisms. The lowest-cost technology can generate deep coverage of most species, including mammals, in just a few days. The sequence data generated by one of these projects consist of millions or billions of short DNA sequences (reads) that range from 50 to 150 nt in length. These sequences must then be assembled de novo before most genome analyses can begin. Unfortunately, genome assembly remains a very difficult problem, made more difficult by shorter reads and unreliable long-range linking information. In this study, we evaluated several of the leading de novo assembly algorithms on four different short-read data sets, all generated by Illumina sequencers. Our results describe the relative performance of the different assemblers as well as other significant differences in assembly difficulty that appear to be inherent in the genomes themselves. Three overarching conclusions are apparent: first, that data quality, rather than the assembler itself, has a dramatic effect on the quality of an assembled genome; second, that the degree of contiguity of an assembly varies enormously among different assemblers and different genomes; and third, that the correctness of an assembly also varies widely and is not well correlated with statistics on contiguity. To enable others to replicate our results, all of our data and methods are freely available, as are all assemblers used in this study.     

Integrated and sequence-ordered BAC- and YAC-based physical maps for the rat genome

As part of the effort to sequence the genome of Rattus norvegicus, we constructed a physical map comprised of fingerprinted bacterial artificial chromosome (BAC) clones from the CHORI-230 BAC library. These BAC clones provide ~13-fold redundant coverage of the genome and have been assembled into 376 fingerprint contigs. A yeast artificial chromosome (YAC) map was also constructed and aligned with the BAC map via fingerprinted BAC and P1 artificial chromosome clones (PACs) sharing interspersed repetitive sequence markers with the YAC-based physical map. We have annotated 95% of the fingerprint map clones in contigs with coordinates on the version 3.1 rat genome sequence assembly, using BAC-end sequences and in silico mapping methods. These coordinates have allowed anchoring 358 of the 376 fingerprint map contigs onto the sequence assembly. Of these, 324 contigs are anchored to rat genome sequences localized to chromosomes, and 34 contigs are anchored to unlocalized portions of the rat sequence assembly. The remaining 18 contigs, containing 54 clones, still require placement. The fingerprint map is a high-resolution integrative data resource that provides genome-ordered associations among BAC, YAC, and PAC clones and the assembled sequence of the rat genome.     

Efficient de novo assembly of large genomes using compressed data structures

De novo genome sequence assembly is important both to generate new sequence assemblies for previously uncharacterized genomes and to identify the genome sequence of individuals in a reference-unbiased way. We present memory efficient data structures and algorithms for assembly using the FM-index derived from the compressed Burrows-Wheeler transform, and a new assembler based on these called SGA (String Graph Assembler). We describe algorithms to error-correct, assemble, and scaffold large sets of sequence data. SGA uses the overlap-based string graph model of assembly, unlike most de novo assemblers that rely on de Bruijn graphs, and is simply parallelizable. We demonstrate the error correction and assembly performance of SGA on 1.2 billion sequence reads from a human genome, which we are able to assemble using 54 GB of memory. The resulting contigs are highly accurate and contiguous, while covering 95% of the reference genome (excluding contigs <200 bp in length). Because of the low memory requirements and parallelization without requiring inter-process communication, SGA provides the first practical assembler to our knowledge for a mammalian-sized genome on a low-end computing cluster.     

SOAPindel: Efficient identification of indels from short paired reads

We present a new approach to indel calling that explicitly exploits that indel differences between a reference and a sequenced sample make the mapping of reads less efficient. We assign all unmapped reads with a mapped partner to their expected genomic positions and then perform extensive de novo assembly on the regions with many unmapped reads to resolve homozygous, heterozygous, and complex indels by exhaustive traversal of the de Bruijn graph. The method is implemented in the software SOAPindel and provides a list of candidate indels with quality scores. We compare SOAPindel to Dindel, Pindel, and GATK on simulated data and find similar or better performance for short indels (<10 bp) and higher sensitivity and specificity for long indels. A validation experiment suggests that SOAPindel has a false-positive rate of ∼10% for long indels (>5 bp), while still providing many more candidate indels than other approaches.Calling indels from the mapping of short paired-end sequences to a reference genome is much more challenging than SNP calling because the indel by itself interferes with accurate mapping and therefore indels up to a few base pairs in size are allowed in the most popular mapping approaches (Li et al. 2008; Li and Durbin 2009; Li et al. 2009). The most powerful indel calling approach would be to perform de novo assembly of each genome and identify indels by alignment of genomes. However, this is computationally daunting and requires very high sequencing coverage. Therefore, local approaches offer more promise. Recent approaches exploit the paired-end information to perform local realignment of poorly mapped pairs, thus allowing for longer indels (Ye et al. 2009; Homer and Nelson 2010; McKenna et al. 2010; Albers et al. 2011). One such approach, Dindel, maps reads to a set of candidate haplotypes obtained from mapping or from external information. It uses a probabilistic framework that naturally integrates various sources of sequencing errors and was found to have high specificity for identification of indels of sizes up to half the read length (Albers et al. 2011). Deletions longer than that can be called using split read approaches such as implemented in Pindel (Ye et al. 2009). Long insertions remain problematic because short reads will not span them and a certain amount of de novo assembly is required.Our approach, implemented in SOAPindel, performs full local de novo assembly of regions where reads appear to map poorly as indicated by an excess of paired-end reads where only one of the mates maps. The idea is to collect all unmapped reads at their expected genomic positions, then perform a local assembly of the regions with a high density of such reads and finally align these assemblies to the reference. A related idea has recently been published by Carnevali et al. (2012), but their approach is designed for a different sequencing method, and software is not available for comparison.While conceptually simple, our approach is sensitive to various sources of errors, e.g., false mate pairs, sequencing errors, nonunique mapping, and repetitive sequences. We deal with these complexities by examining all the paths in an extended de Bruijn graph (Zerbino and Birney 2008) and choose those that anchor at some points on the reference genome sequence. In this way, we can detect heterozygous indels as two different paths in the de Bruijn graph and, in principle, call multiallelic indels in polyploid samples or pools of individuals. Unlike, e.g., Pindel, the approach treats insertions and deletions in the same way and has no constraint on indel length other than that determined by the local assembly.We explore the specificity and the sensitivity of SOAPindel by extensive simulations based on the human genome and by indel calling on one of the high-coverage samples of the 1000 Genomes Project. We estimate a low false-positive rate of the de novo indel calls by direct Sanger resequencing as well as from simulated reads data based on the Venter genome and the chimpanzee genome, mapped against the reference genome. We benchmark SOAPindel against Dindel, Pindel, and GATK, and it shows similar or better specificity and sensitivity for short indels and much higher sensitivity for long indels.     

Scaffolding a Caenorhabditis nematode genome with RNA-seq

Efficient sequencing of animal and plant genomes by next-generation technology should allow many neglected organisms of biological and medical importance to be better understood. As a test case, we have assembled a draft genome of Caenorhabditis sp. 3 PS1010 through a combination of direct sequencing and scaffolding with RNA-seq. We first sequenced genomic DNA and mixed-stage cDNA using paired 75-nt reads from an Illumina GAII. A set of 230 million genomic reads yielded an 80-Mb assembly, with a supercontig N50 of 5.0 kb, covering 90% of 429 kb from previously published genomic contigs. Mixed-stage poly(A)(+) cDNA gave 47.3 million mappable 75-mers (including 5.1 million spliced reads), which separately assembled into 17.8 Mb of cDNA, with an N50 of 1.06 kb. By further scaffolding our genomic supercontigs with cDNA, we increased their N50 to 9.4 kb, nearly double the average gene size in C. elegans. We predicted 22,851 protein-coding genes, and detected expression in 78% of them. Multigenome alignment and data filtering identified 2672 DNA elements conserved between PS1010 and C. elegans that are likely to encode regulatory sequences or previously unknown ncRNAs. Genomic and cDNA sequencing followed by joint assembly is a rapid and useful strategy for biological analysis.     

Sequencing of natural strains of Arabidopsis thaliana with short reads

Whole-genome hybridization studies have suggested that the nuclear genomes of accessions (natural strains) of Arabidopsis thaliana can differ by several percent of their sequence. To examine this variation, and as a first step in the 1001 Genomes Project for this species, we produced 15- to 25-fold coverage in Illumina sequencing-by-synthesis (SBS) reads for the reference accession, Col-0, and two divergent strains, Bur-0 and Tsu-1. We aligned reads to the reference genome sequence to assess data quality metrics and to detect polymorphisms. Alignments revealed 823,325 unique single nucleotide polymorphisms (SNPs) and 79,961 unique 1- to 3-bp indels in the divergent accessions at a specificity of >99%, and over 2000 potential errors in the reference genome sequence. We also identified >3.4 Mb of the Bur-0 and Tsu-1 genomes as being either extremely dissimilar, deleted, or duplicated relative to the reference genome. To obtain sequences for these regions, we incorporated the Velvet assembler into a targeted de novo assembly method. This approach yielded 10,921 high-confidence contigs that were anchored to flanking sequences and harbored indels as large as 641 bp. Our methods are broadly applicable for polymorphism discovery in moderate to large genomes even at highly diverged loci, and we established by subsampling the Illumina SBS coverage depth required to inform a broad range of functional and evolutionary studies. Our pipeline for aligning reads and predicting SNPs and indels, SHORE, is available for download at http://1001genomes.org.