Validation of Gene Predictions Table 4. Distribution of cluster sizes (number of sequences per cluster) for the CD-HIT clustered combined protein dataset. Table 5. Number of all sequence clusters and clusters supported by MS data, EST data, and MS and EST data, respectively. Cluster Size (sequences per cluster) Number of Clusters 1 2 3 4 5 6 7 8 9 10 .10 8,281 2,476 1,850 1,577 430 160 104 42 23 12 28 doi:10.1371/journal.pone.0003899.t004 Clustering by genomic location Clustering proteins by sequence similarity may group together paralogs from different genomic locations that emerged through gene duplication or gene shuffling mechanisms. Therefore, we explored the homogeneity of the sequence clusters in terms of genomic localization. First, individual protein sequences were mapped onto the T. gondii genome. We successfully mapped 27,777 sequences (92% of the combined and redundant dataset) onto the genome (see Methods). The sequences span an average length of 5,879 nucleotides and, on average, approximately 52% of the genomic coding region is exonic. We found 787 sequences (2.6%) only that can be mapped to multiple locations in the genome, which suggests a relatively low level of gene duplication events. Genomic mappings of the protein sequences determined the genomic location of 92% of the 14,983 sequence clusters (see Methods). In approximately 1% of the clusters, a sequence maps to a different genomic location than the rest of the cluster members. Approximately 99% of the clusters are composed of sequences that are transcribed from the same genomic regions. These clusters of predicted protein sequences may also represent possible splice variants of the same gene. There are 3,120 and 2,969 genomic regions that are comprised of either an individual cluster or a co-localized cluster group (see Methods), respectively, and thus, we estimate that there are 6,089 potential protein-coding regions in the T. gondii genome. The genomic protein-coding regions span, on average, 9,924 nucleotides and, since the T. gondii genome is about 65 Mb, approximately 7% of the genomic sequence is intergenic. The estimated percentage of the genome that accounts for coding regions is larger than what has been previously reported for chromosome Ia (56.7%) and Ib (58.1%) [25], which could be a reflection of the increased number of false positive protein sequences that arise from a larger variety of analyzed gene prediction algorithms or possible characteristic differences among the T. gondii chromosomes. High throughput experimental validation of the T. gondii proteome We explored the T. gondii proteome by performing high throughput, tandem mass spectrometry (MS/MS) experiments on T. gondii plasma membrane, cytoskeletal, and cytosolic protein sequence type (# clusters) 7,914 % of Total Clusters sequence type (# clusters) 1,505 % of MS Clusters sequence type (# clusters) 4,954 % of EST Clusters sequence type (# clusters) 1,396 % of both MS and EST Clusters 53% 61% 54% 61% 7,093 47% 1,625 66% 4,851 52% 1,507 66% For each category, the number of clusters with each predicted sequence type is shown along with the corresponding percentage of the clusters in the respective category. preparations and cross referencing the MS-derived peptides with the computationally generated and experimentally derived amino acid sequences of the hypothetical T. gondii proteome. Expressed sequence tag data was used to provide further experimental support for some sequences in the hypothetical T. gondii proteome. The 252 MS/MS experiments provided 7,270 unique proteo- lytic peptides that identified 6,438 sequences (21% of the combined dataset). The average peptide coverage of the MS/ MS supported sequences is 13.5%. The percentages of sequences with an assigned peptide are similar for the TigrScan, TwinScan, Glimmer, and Release4 datasets (17%, 19%, 27%, and 20%, respectively) while the percentage is substantially higher for the NR dataset (49%) (Table 2). The average peptide coverages are also similar for the TigrScan, TwinScan, Glimmer, and Release4 sequences yet significantly higher for the NR sequences (10.7%, 13.4%, 8.6%, 12.5%, respectively, compared to 29.9%) (Table 2). The fact that the NR dataset has a higher percentage of sequences with assigned peptides and a higher average coverage seems intuitive as is a reflection of the fact that these sequences are believed to be more reliable, because, in general, they are experimentally derived. These sequences certainly do not represent a comprehensive or uniform sample of the T. gondii proteome and thus, no assumptions can be made about the quality of the sequences or coverage of the proteome by this dataset with respect to the predicted datasets. The observation that each protein prediction method has a similar degree of experimental validation, along with the disparate nature of the sequences predicted by each method, indicates that each method predicts the proteome with a similar level of accuracy. There are 2,477 clusters (17% of the total clusters) that contain a sequence with an assigned MS/MS peptide. The portions of the MS/MS supported clusters that contain a TigrScan, TwinScan, or Release4 sequence are similar (60.75%, 65.60%, and 67.62%, respectively) while the portion that contains a Glimmer sequence is slightly lower (56.72%) (Table 5). The discrepancy in the accuracy of the protein prediction methods can be explained by the fact that there are fewer Glimmer sequences as compared to the other Predicted Protein Types TigrScan TwinScan Glimmer Release4 NR 14,983 Total Clusters 2,477 MS Clusters 9,242 EST Clusters 2,275 MS AND EST Clusters 4,916 33% 1,405 57% 3,816 41% 1,315 58% 7,389 49% 1,675 68% 5,645 61% 1,562 69% 889 6% 384 16% 748 8% 370 16% PLoS ONE | www.plosone.org 6 December 2008 | Volume 3 | Issue 12 | e3899