Hyten et al. BMC Genomics 2010, 11:38 http://www.biomedcentral.com/1471-2164/11/38 anchored scaffolds contained just one mapped marker, or contained multiple tightly linked markers whose map order was questionable due to insufficient recombina- tion. Thus, proper orientation of those scaffolds was not possible or was questionable. The ideal marker for anchoring and orienting the soy- bean genome is the single nucleotide polymorphism (SNP), primarily because SNPs are the most abundant marker available. Cultivated soybean [Glycine max (L.) Merr.] has nucleotide diversity (θ) of about 0.001 [3,4], which translates into an average SNP frequency of one SNP per 1000 bp of contiguous sequence. The wild ancestor Glycine soja (Sieb and Zucc.) has an estimated nucleotide diversity of θ = 0.00235, which is the equiva- lent of approximately one SNP per 425 bp [5]. Another advantage of SNPs is the wide array of currently avail- able technologies for performing multiplex assays that can range from genotyping a few SNPs at a time to over 1 million SNPs in parallel [6]. One of these technologies is the GoldenGate assay, which can genotype 384 to 1,536 SNPs in 192 DNA samples in just three days. The reliability and rapidity of this assay was recently docu- mented with soybean SNPs [2,7,8]. New high-throughput re-sequencing technologies have recently become available for generating greater amounts of DNA sequence quickly and inexpensively relative to standard Sanger sequencing [9]. Despite this advantage, large genomes still require a method to reduce genome complexity to a level that ensures accu- rate SNP discovery. One method utilizes high-through- put sequencing of the transcriptome through massively parallel pyro-sequencing technology [10]. While this method was successful, SNP discovery using this proce- dure is restricted to the expressed transcriptome and would likely not discover SNPs that could be used to anchor and orient non-coding DNA stretches of the genome. The use of reduced representation libraries (RRLs) was first proposed in humans to efficiently find SNPs using Sanger sequencing [11]. A reduction in genome com- plexity is accomplished via the construction of an RRL with a restriction digestion followed by size selection. The use of fragments from a size-selected digestion per- mits a similar subset of fragments to be obtained from different genotypes that can be deep-sequenced for accurate SNP discovery. A procedure for high-through- put SNP discovery was recently described in cattle, and used an RRL combined with the sequence-by-synthesis (SBS) method on the clonal single molecule array (CSMA) platform manufactured by Illumina, Inc., with which short sequence reads could be compared to a reference genome for SNP discovery [12]. This approach successfully identified 62,042 putative SNPs. A subse- quent analysis of 22,865 of these SNPs revealed a 91% Page 2 of 8 validation rate, demonstrating the robustness of this SNP discovery method [12]. Our objective was to use the RRL approach with the SBS method on the CSMA platform from Illumina, Inc for the discovery of large numbers of soybean SNPs that could be developed into GoldenGate assays to create a new genetic map with higher resolution than Consensus Map 4.0 [2]. This high resolution genetic map would then help address the challenges faced in assembling and orienting the remainder of the soybean genome [1]. Results Genome Analyzer sequence results A total of 8,671,165 sequence reads of 33 bp in length were obtained for the G. soja accession PI 468916, yield- ing a total of more than 286 Mb of sequence (Table 1). More than 2,500 of the 33-mers, after being sequenced 300 or more times, were determined to be either repeti- tive nuclear DNA, or DNA from chloroplast or mito- chondria. These were excluded from further analysis. From the PI 468916 sequence data, 1.96 million unique 33-mers were obtained, of which 1.82 million (92%) occurred five or fewer times. These PI 468916 short sequence reads were then aligned to the soybean, Wil- liams 82, 6.5× scaffold assemblies for SNP discovery. A total of 4.21 million reads were ultimately aligned uniquely to the Williams 82, 6.5× scaffold assembly. The 4.21 million reads covered a total of 28 Mb of soybean sequence (after accounting for regions with multiple coverage). This translates into a 4.88× coverage of the 6.5× genome assembly for the purposes of SNP prediction. SNP Prediction and Validation Multiple methods were initially tested for SNP predic- tion and filtering. We used the GMAP [13] and Maq [14] mapping software. The GMAP software directly compares predicted bases in short-read query and geno- mic reference sequences, while the Maq software addi- tionally uses quality scores in the short-read sequences, and provides additional output information about the consensus quality of SNP calls. We made three valida- tion runs, on a preliminary 4× scaffold assembly; and one “production” run on the preliminary 6.5× scaffold assembly. The validation runs used GMAP with multiple short sequence reads to predict SNPs, and Maq with either multiple or single short sequence reads to predict SNPs. The production run used predominantly multiple short sequence reads to predict SNPs, with single short sequence read predicted SNPs where necessary in areas of particular interest. Because only one of the programs uses quality scores, the parameter sets are not trivially comparable. However, both programs were tunable for these objectives. For each of the tested methods, we