Ultraspecific probes for high throughput HLA typing
- Equal contributors
1 Department of Computer Science, University of Houston, Houston, TX, USA
2 Department of Computer Science, Loyola University Chicago, Chicago, IL, USA
3 Department of Biology, Loyola University Chicago, Chicago, IL, USA
4 Collaborative Center for Statistics in Science, Yale University, New Haven, CT, USA
5 Genomics USA, Inverness, IL, USA
6 Department of Biology and Biochemistry, University of Houston, Houston, TX, USA
BMC Genomics 2009, 10:85 doi:10.1186/1471-2164-10-85Published: 20 February 2009
The variations within an individual's HLA (Human Leukocyte Antigen) genes have been linked to many immunological events, e.g. susceptibility to disease, response to vaccines, and the success of blood, tissue, and organ transplants. Although the microarray format has the potential to achieve high-resolution typing, this has yet to be attained due to inefficiencies of current probe design strategies.
We present a novel three-step approach for the design of high-throughput microarray assays for HLA typing. This approach first selects sequences containing the SNPs present in all alleles of the locus of interest and next calculates the number of base changes necessary to convert a candidate probe sequences to the closest subsequence within the set of sequences that are likely to be present in the sample including the remainder of the human genome in order to identify those candidate probes which are "ultraspecific" for the allele of interest. Due to the high specificity of these sequences, it is possible that preliminary steps such as PCR amplification are no longer necessary. Lastly, the minimum number of these ultraspecific probes is selected such that the highest resolution typing can be achieved for the minimal cost of production. As an example, an array was designed and in silico results were obtained for typing of the HLA-B locus.
The assay presented here provides a higher resolution than has previously been developed and includes more alleles than previously considered. Based upon the in silico and preliminary experimental results, we believe that the proposed approach can be readily applied to any highly polymorphic gene system.