SHARCGS, a fast and highly accurate short-read assembly algorithm for de novo genomic sequencing.

By Juliane C. Dohm, Claudio Lottaz, T. Borodina, Heinz Himmelbauer. Genome Research, 2007

318 citations recorded by the source corpus.

The latest revolution in the DNA sequencing field has been brought about by the development of automated sequencers that are capable of generating giga base pair data sets quickly and at low cost. Applications of such technologies seem to be limited to resequencing and transcript discovery, due to the shortness of the generated reads. In order to extend the fields of application to de novo sequencing, we developed the SHARCGS algorithm to assemble short-read (25-40-mer) data with high accuracy and speed. The efficiency of SHARCGS was tested on BAC inserts from three eukaryotic species, on two yeast chromosomes, and on two bacterial genomes (Haemophilus influenzae, Escherichia coli). We show that 30-mer-based BAC assemblies have N50 sizes >20 kbp for Drosophila and Arabidopsis and >4 kbp for human in simulations taking missing reads and wrong base calls into account. We assembled 949,974 contigs with length >50 bp, and only one single contig could not be aligned error-free against the reference sequences. We generated 36-mer reads for the genome of Helicobacter acinonychis on the Illumina 1G sequencing instrument and assembled 937 contigs covering 98% of the genome with an N50 size of 3.7 kbp. With the exception of five contigs that differ in 1-4 positions relative to the reference sequence, all contigs matched the genome error-free. Thus, SHARCGS is a suitable tool for fully exploiting novel sequencing technologies by assembling sequence contigs de novo with high confidence and by outperforming existing assembly algorithms in terms of speed and accuracy.

Subfields: Molecular Biology, Plant Science

View Paper: https://www.semanticscholar.org/paper/fbd59e17f72c3aedb3cd06af2e50a91526ccd81a

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Citations in the corpus

A window into third-generation sequencing. (2010, methodology): “A number of assemblers for de novo assembly have been written for SGS, including overlap graph approaches in which contigs are assembled by looking at sequence overlaps, like Edna (46), VCAKE (47) and SHARCGS (48); those based on the de Bruijn graph data structure (49), like Velvet (50), EULER-SR (5”
Substantial biases in ultra-short read data sets from high-throughput DNA sequencing (2008, methodology): “We previously generated 12 288 791 36mer reads from Helicobacter acinonychis on an Illumina 1G sequencing device (10).”
ALLPATHS: de novo assembly of whole-genome shotgun microreads. (2008, background): “Several recent papers (Dohm et al. 2007; Jeck et al. 2007; Warren et al. 2007) have demonstrated assembly of unpaired microreads (for comparison, see Supplemental material Part j), but the quality of such assemblies is limited by the use of unpaired-read data.”
De novo bacterial genome sequencing: millions of very short reads assembled on a desktop computer. (2008, methodology): “This assembly comparison was performed on the set of reads obtained with Helicobacter acinonychis strain Sheeba and originally presented in the publication describing SHARCGS.”
Ray: Simultaneous Assembly of Reads from a Mix of High-Throughput Sequencing Technologies (2010, background): “Available assemblers are dedicated to specific and proprietary technologies.”
Utilization of next-generation sequencing platforms in plant genomics and genetic variant discovery (2010, methodology): “A variety of tools that are beyond the scope of this paper have been developed for alignment and de novo assembly of short reads (for examples, see Warren et al. 2007; Dohm et al. 2007; Jeck et al. 2007; De Bona et al. 2008; Chaisson and Pevzner 2008; Li et al. 2008a; Smith et al. 2008; Zerbino and ”
De novo assembly of human genomes with massively parallel short read sequencing. (2010, methodology): “Some other short read assemblers have applied the overlap and extension strategy, such as SSAKE (Warren et al. 2007), VCAKE (Jeck et al. 2007) (the follower of SSAKE which can handle sequencing errors), SHARCGS (Dohm et al. 2007), and Edena (Hernandez et al. 2008).”
Genome assembly reborn: recent computational challenges (2009, background): “The reads are considered in decreasing order of their quality, as defined either by depth of coverage (number of reads confirming a section of a given read) [25] or by using a combination of coverage, quality values and the presence of at least one perfect overlap with another read [26].”
Next-generation sequencing: from basic research to diagnostics. (2009, background): “Software for de novo assembly includes Edina (70), EULER-SR (74), SHARCGS ( 75 ), SSAKE (69), Velvet (76), and SOAPdenovo (http://soap.genomics.org.cn/).”
GapFiller: a de novo assembly approach to fill the gap within paired reads (2012, methodology): “Similarly to other seed-and-extend-based tools like SSAKE [14], SHARCGS [15], QSRA [16], and TAIPAN [17], GapFiller selects one read and tries to extend it using reads that overlap for a significant region.”
Velvet: algorithms for de novo short read assembly using de Bruijn graphs. (2008, methodology): “More recently, programs such as SSAKE (Warren et al. 2007), SHARCGS (Dohm et al. 2007), and VCAKE (Jeck et al. 2007) implicitly use this framework, but at a local level.”
De novo fragment assembly with short mate-paired reads: Does the read length matter? (2009, unknown): “2007), SHARCGS (Dohm et al. 2007), VCAKE (Jeck et al.”
IDBA - A Practical Iterative de Bruijn Graph De Novo Assembler (2010, methodology): “SSAKE [3], VCAKE [4] , SHARCGS [5]) uses the”