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H. V. Gudiseva, N. Smaoui, I. M. MacDonald, S. J. Bowne, X. Wang, L. S. Sullivan, S. P. Daiger, J. F. Hejtmancik, R. Ayyagari; Evaluation of a Resequencing Arrays of 93 Retinal Dystrophy Genes. Invest. Ophthalmol. Vis. Sci. 2010;51(13):1652.
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© ARVO (1962-2015); The Authors (2016-present)
To test and validate the second generation resequencing array (Retina Array) with 93 retinal dystrophy (RD) genes.
Resequencing arrays were designed using the Affymetrix 300kb array platform. A total of 267,550 bps corresponding to 1470 exons and 23bp of flanking intronic sequence from 93 genes was tiled. A total of 15,350,269 bp sequence from 33 patient samples with a diagnosis of RD (adRP, arRP, BBS, STGD1) and known to contain 75 sequence changes was analyzed using the Retina Array. In addition, 37 exons with 35 known sequence changes were analyzed on three arrays. The exons of relevant genes were amplified and pooled for fragmentation and labeling. Hybridization of labeled fragments and scanning were carried out using the Affymetrix fluidics station and scanner, respectively. Cel files with the output sequences were analyzed using GSEQ v4.0 and SeqPilot software.
The base pair call rate using the Retina Array was 87 to 99.8%. Accuracy and reproducibility of the obtained sequence obtained was > 99%. Out of 35 changes tested in triplicate, twenty eight were detected on all three chips, and four were called either on one or two chips but not on all the three. Among the remaining three changes, two were ambiguous calls and one was false negative. Specificity of the chip is determined by screening samples with 75 known changes. Array sequencing detected 68 of these changes. Among the remaining 7, four were ambiguous calls and 3 were false negatives. The call rates were above 90% even when a single gene was hybridized on to the array. The detection rate was null in the case of deletions/ insertions and intronic changes beyond 10 bps from the splice site.
This analysis indicates that the high density Retina Array can be used to sequence one or few genes in addition to analyzing all the genes in one assay. Majority of changes that gave false negative result were located in GC rich regions. The false negative rate was comparable to other methods. The false positive rate was higher for these chips and software thresholds might be a reason for this limitation. Software that can reliably identify sequence changes is necessary to utilize these arrays effectively for mutation screening.
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