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Summary: Bisulfite sequencing allows cytosine methylation, an important epigenetic marker, to be detected via nucleotide substitutions. Since the Applied Biosystems SOLiD System uses a unique di-base encoding that increases confidence in the detection of nucleotide substitutions, it is a potentially advantageous platform for this application. However, the di-base encoding also makes reads with many nucleotide substitutions difficult to align to a reference sequence with existing tools, preventing the platform's potential utility for bisulfite sequencing from being realized. Here, we present SOCS-B, a reference-based, un-gapped alignment algorithm for the SOLiD System that is tolerant of both bisulfite-induced nucleotide substitutions and a parametric number of sequencing errors, facilitating bisulfite sequencing on this platform. An implementation of the algorithm has been integrated with the previously reported SOCS alignment tool, and was used to align CpG methylation-enriched Arabidopsis thaliana bisulfite sequence data, exhibiting a 2-fold increase in sensitivity compared to existing methods for aligning SOLiD bisulfite data.
Availability: Executables, source code, and sample data are available at http://solidsoftwaretools.com/gf/project/socs/
Supplementary information: Supplementary data are available at Bioinformatics online.
Cytosine methylation is a major epigenetic marker in eukaryotes, performing functions such as transcriptional regulation and transposon silencing. It is now possible to create genome-wide maps of this type of DNA modification at single-nucleotide resolution using a technique termed bisulfite sequencing, or BS-Seq. The method utilizes high-throughput sequencing technologies in conjunction with selective nucleotide substitutions. These substitutions are induced by bisulfite, which converts cytosine residues to uracil residues, but occurs at a much slower rate for 5-methylcytosine (the most common type of methylated cytosine). After an appropriate amount of bisulfite treatment and subsequent PCR amplification, 5-methycytosine residues will be represented by cytosine (or guanine on the complementary strand) and cytosine residues by thymine (or adenine on the complementary strand). By sequencing the converted DNA and aligning with a reference sequence, methylation can be inferred from these substitutions (Frommer et al., 1992).
While any sequencing method can be employed for BS-Seq, the Applied Biosystems SOLiD System is attractive for this application because it is designed around the reliable detection of nucleotide substitutions. This reliability arises not from the absence of sequencing errors, but from the ability to discern most of them from true substitutions. The system achieves this by querying overlapping dinucleotides rather than single nucleotides, such that each nucleotide of each read is ultimately queried by two independent ligation events. The caveat is that each dinucleotide is reported as a color that could represent any of the four dinucleotides, and alignment must be performed using these colors (in ‘color-space’) in order for sequencing errors to be distinguished. In color-space, a nucleotide substitution appears as a specific pattern of two adjacent color-space mismatches. This increased divergence is not a major problem for applications in which reads will typically only contain one nucleotide substitution, such as single nucleotide polymorphism (SNP) detection. However, in BS-Seq, bisulfite-induced nucleotide substitutions (BINS) are ubiquitous, causing most reads to contain too many color-space mismatches relative to the reference sequence to be aligned using the standard color-space alignment tools.
There are ways to avoid this issue and align a portion of the reads with standard tools. One is to create reference sequences that represent the original sequence and complete bisulfite conversion of both the Watson and Crick strands of the sequence, as done in previous bisulfite experiments (Lister et al., 2008). Reads can then be aligned using existing SOLiD alignment tools. The problem with this approach is that reads containing both methylated and unmethylated cytosines could contain numerous color-space mismatches against either reference sequence. Since areas such as CpG islands are dense with potential methylation sites, many reads that are of particular interest would not be aligned within realistic error tolerances. The other possible method is to convert SOLiD reads from their di-nucleotide encoding into nucleotide strings. The reads can then be aligned with an existing tool that is tolerant of BINS, such as the one developed by Cokus et al. (2008). The issue here is that the conversion process assumes the absence of sequencing errors, causing the majority of the reads to be converted incorrectly. Both of these methods ignore much of the information contained in SOLiD output, and thus do not realize the potential of this platform for BS-Seq. Ideally, an alignment tool for this application should be tolerant of BINS as well as some sequencing errors.
Here, we present SOCS-B, an alignment algorithm tolerant of both bisulfite-induced nucleotide substitutions and SOLiD sequencing errors, facilitating BS-Seq using the SOLiD system. The algorithm is based on the iterative version of the Rabin–Karp algorithm that is the foundation of SOCS (Karp and Rabin, 1987; Ondov et al., 2008). The first phase of the algorithm is the creation of a hash table to index potential matches, drastically paring the number of alignments to be performed. The second phase is the assessment of these potential matches by comparison of the color-space sequence of the reads to the color-space sequence of the reference. Both phases of SOCS-B are tolerant of both BINS and sequencing errors. Hashes are created by first translating the color-space reads into nucleotide sequences. To account for the translational effects of sequencing errors, four translations are computed, starting from all four nucleotides (rather than just the terminal primer base provided with the read). Then substrings of all four translations are used to generate partial hashes, which are analogous to seeds. This ensures that the partial hashes based on the correct translations are represented in the hash table, regardless of any sequencing errors that occurred earlier in the reads. A reduced representation of the translated nucleotides, which treats cytosine and thymine as the same symbol, is enumerated in ternary to form each partial hash. To assess the quality of each potential alignment discovered in the hash table, BINS must be distinguished from sequencing errors. Since the validity of a color-space mismatch depends on whether neighboring colors have been attributed to BINS, SOCS-B uses a dynamic programming table to compute the most probable methylation state for each cytosine based on the quality scores for each color (Supplementary Fig. S1). The number and positions of errors follow from this information. If the optimal translation has fewer than a user-specified number of color-space mismatches against the reference sequence, the alignment is kept until the algorithm completes or a more probable alignment is found.
SOCS-B was tested on 54 705 478 50-color reads produced with a SOLiD 3 Plus system from bisulfite-converted Arabidopsis thaliana genomic DNA that had been pre-enriched for CpG methylation by methyl-binding domain affinity chromatography and spiked with phage lambda DNA (to measure bisulfite conversion efficiency). As a control, the reads were first aligned using the alignment tool provided by Applied Biosystems (mapreads) against reference sequences representing the fully bisulfite converted Watson and Crick strands and the unconverted Watson strands of A.thaliana and phage lambda. This approach is analogous to that employed by previous BS-Seq studies (Lister et al., 2008). Alignment was then performed against only the unconverted genomes using SOCS-B, which exhibited a 2-fold increase in total sensitivity for reads with three or fewer errors (Table 1). Using reads that uniquely aligned to the lambda genome, the bisulfite conversion rate was estimated to be 99%, indicating that the increase in sensitivity (and thus the abundance of heterogeneously converted reads) was due to complex methylation patterns, rather than incomplete conversion. Furthermore, since the most biologically relevant methylation sites in the genome occur in dense clusters, it seems possible that the additional reads aligned by SOCS-B might be of more biological significance than those aligned with mapreads. Because of the algorithm's inherent lack of bias, SOCS-B also showed increased specificity when aligning simulated reads (Supplementary Table S2).
SOCS-B alignment took 30 h using an Apple Mac Pro (dual 2.93 GHz Quad-Core Intel Xeon with hyper-threading, 32 GB RAM). Since color-space errors are fairly abundant in SOLiD reads, more reads can be aligned by allowing more mismatches, either at the expense of run time (by increasing the sensitivity) or of specificity (by increasing the tolerance). For larger reference genomes or datasets, or for higher error sensitivity, SOCS has features that facilitate distributed processing. Executable versions, source code, sample datasets, and usage instructions are available at http://solidsoftwaretools.com/gf/project/socs/.
We thank Ryan Lister and Joe Ecker of the Salk Research Institute (La Jolla, CA, USA) for providing A. thaliana genomic DNA, Hank Tu of Life Technologies (Foster City, CA, USA) for assisting with distributed computing, and George Marnellos (Invitrogen, Carlsbad, CA) for helpful discussions.
Funding: DHHS contract N266200400059C/N01-AI-40059.
Conflict of Interest: none declared.