(OTPS) provided by dsCheck software [22], 95.6% of the validated genes had scores of less than 3, whereas the scores of 60.7% of the genes yet to be validated were greater than 2. Thus, the genes with OTPS less than 3 were rescreened by testing whether knockdown of their suspected off-target genes led to glycosylation defects. When knockdown of the suspected off-target genes did not induce any glycosylation defects, the corresponding genes were classified as glycosylation-related genes (rank 2) along with the genes that were validated by secondary dsRNAs (rank 1) (Table S4). To successfully identify additional glycosylation genes, we searched for genes that interacted with our newly identified genes in the yeast two-hybrid database BIOGRID (http://www. thebiogrid.org/) and in the genetic interaction data listed in FlyBase (http://flybase.bio.indiana.edu/). The RNAi fly strains harboring candidate genes that did not already exist in our library were obtained from the Vienna Drosophila RNAi Library Center (VDRC) [23] (Table S3). Among the 186 genes tested, 10 genes showed glycosylation defects. Further validation experiments identified 1 rank-1 and 5 rank-2 glycosylation-related genes among them. In total, 109 genes were eventually isolated and identified as glycosylation-related genes (Table S4). Significantly, although 14 of the 109 identified genes have already been shown to be involved in glycosylation, the remaining 95 genes were newly assigned to this category by our analysis. Clustering of glycosylation genes Glycosylation-related genes were classified based on their domain structures and presumptive functions using the InterPro (http://www.ebi.ac.uk/interpro/), FlyBase (http://flybase.org/), Figure 3. Screening results. (A) Functional classification of the 109 glycosylation-related genes. (B) Functional classification of the 17 a1,3- fucosylation-specific glycosylation-related genes. The number of genes in each category is listed. doi:10.1371/journal.pgen.1001254.g003 Large-Scale Screen for Glycosylation-Related Genes and Panther (http://www.pantherdb.org/) databases. The gene functional groups obtained included glycosylation reactions, transcription, RNA regulation, translation, intracellular traffick- ing, cytoskeletal regulation, signal transduction, protein degrada- tion, mitochondrial function, and other functions (Figure 3A, Table S4). Genes regulating neural-specific glycosylation To identify genes specifically involved in neural-specific glycosylation, we selected genes whose knockdown induced only abnormal anti-HRP binding activity from among the 109 genes listed in Table S4. From this analysis, 17 genes showing a1,3- fucosylation-specific defects were identified belonging to seven functional groups (Figure 3B). In the RNA regulation group, swm (CG10084) [14], Pabp2 (CG2163) [24], and Hel25E (CG7269) are suggested to interact with each other in the Drosophila interaction database STRING (http://string.embl.de/) and literature [25]. Swm and Pabp2 are required for a1,3-fucosylation Since Swm and Pabp2 have been reported to physically interact with each other in BIOGRID, the roles of these genes were further analyzed in the context of glycosylation. To analyze the glycosylation defects induced by the knockdown of these genes in further detail, Chp glycans in the swm and Pabp2 knockdown lines were subjected to mass spectrometric analysis. The ratio of the a1,3-fucosylated form (M3F2Gn2) at N1012 was markedly decreased in both knockdown lines, whereas the other form (M3F2Gn3) was only slightly affected by swm or Pabp2 knockdown (Figure 4A). These results suggest that Swm and Pabp2 are required for a1,3-fucosylation and that the M3F2Gn2 form might be more sensitive than the M3F2Gn3 form to decreases in Swm and Pabp2. Since swm and Pabp2 mutants have been previously isolated [26] (Flybase), glycosylation defects were also examined in the amorphic and hypomorphic alleles of swm, swmF14 and swmF15, respectively, and the hypomorphic allele of Pabp2, Pabp2KG02359. All cells homozygous for swm mutations were generated in whole Drosophila eyes using a modified FLP/FRT system [27]. Chp was isolated from these mutant eyes and detected by immunoblotting with anti-Chp and anti-HRP antibodies to quantify the amount of a1,3-fucose added to Chp. The a1,3-fucose added in swmF14, swmF15, and Pabp2KG02359 cells decreased to 22.7% 6 4.8%, 28.3% 6 7.3%, and 59.5% 6 8.8% of wild-type levels, respectively (Figure 4B). These results are further evidence from knockdown experiments that Swm and Pabp2 are somehow required for a1,3- fucosylation. Although Pabp2 is known to participate in polyA addition, the function of Swm is largely unknown. Thus, we focused on the role of Swm in glycosylation. Modification of a1,3-fucose is widely utilized for Drosophila neural proteins. Thus, we first examined whether swm depletion affects not only Chp but also a wide range of other proteins. Homogenates of adult eyes heterozygous or homozygous for swmF14 and swmF15 were analyzed by immunoblot analysis with an anti-HRP antibody (Figure 5A). Several positive bands were detected, including a high-molecular-weight band corresponding to Chp (,150 kDa). Quantitative comparison between heterozygotes and homozygotes of the same swm alleles revealed that anti-HRP antibody affinity was reduced in most bands in the homozygotes, with the exception of an approximately 30-kDa product (Figure 5A and 5B). The decrease was much larger in swmF14 than in swmF15 mutants, consistent with the severity of these mutations. Taken together, our data indicate that Swm is required for the a1,3-fucosylation of most proteins that are usually modified by a1,3-fucose. PLoS Genetics | www.plosgenetics.org 4 December 2010 | Volume 6 | Issue 12 | e1001254