Once diagnosed with Fanconi anemia (FA), identification of the mutations remains an arduous task at present. The current screening process is a sequential, multi-step approach and successful identification of mutations may be delayed or hindered at any of these steps: establishing cell lines, growing and transducing cells for complementation, and procuring an efficient transducing vector for all FA genes. FA genes are large, with multiple exons, and harbor a wide spectrum of compound heterozygous mutations spread throughout the gene. Multi-exon size genomic deletions of FA genes are also well documented, and therefore, PCR amplification of exons and Sanger sequencing may not yield both the mutations. Therefore, there is a need for an efficient approach that scans the entire length of all the FA genes, and detects wide spectrum of changes. The next-gen sequencing (NGS) allows sequencing large (megabase) regions of the genome rapidly. This enables identification of mutations, directly from DNA, with no prior requirement for establishment of cell lines and determination of the complementation group. We have targeted 13 FA and 11 additional genes that are associated with DNA repair pathways. We employed MIP (Molecular Inversion probe) selection approach for enrichment of the genomic regions of the targeted 24 genes. Essentially, probes were designed to capture 5136 regions, and each test DNA was subjected to the MIP selection. A library of the enriched material was sequenced using a sequencing instrument (Illumina GAII) in a single-end 36 bp configuration. As an initial step, we tested six DNAs, each with one (or both) previously known mutation in a different FA gene. The MIP selection and sequencing helped identify all the known mutations in the DNAs we tested, thus demonstrating that the methodology may be suitable for screening FA gene mutations. Efforts are underway to employ this methodology to test the DNA from FA individuals with no known mutations. Improvements in the selection strategies, as they emerge, will be employed for optimal utilization of the next-gen sequencing technology for screening for mutations in the known FA genes. A small number of individuals diagnosed with FA do not harbor mutations in any of the known 13 FA genes, suggesting that there may be additional gene(s) mutations in which may contribute to FA. We intend to employ the next-gen sequencing technologies for identification of yet unidentified FA genes. Multi-exon size genomic deletions of FA genes are well documented, and such deletions account for more than a quarter of the mutations in the FANCA gene. At present, deletion mutations are often difficult to discern from the next-gen sequencing data. Comparative genomic hybridization (CGH) using high-density oligo arrays allows for efficient identification of genomic deletions and duplications at a high resolution. Unlike the current methods, aCGH analysis is not limited only to the exonic regions, and therefore can identify the precise ends of a deletion. The high-density arrays accommodate the entire genomic regions of all the FA genes (and many other genes of interest as well), and thus can screen for deletions in all the FA genes at once. A CGH array was developed with 135,000 oligonucleotides, representing 37 genes that includes the 13 FA genes, and several others known to participate in a DNA repair pathway. The median spacing of probes is 14nt. DNA from FA patients was processed to incorporate a Cy5 fluorescent tag, and a reference genomic DNA was similarly processed to incorporate the Cy3 tag. Data from CGH analysis has been collected on DNA from 72 FA patients, which included several controls with known deletions. 50 DNAs assigned to the FANCA gene were analyzed and CGH arrays helped identify deletions in 27. Similarly deletions/duplications were identified in one each of the two DNAs tested from the FA-B, FA-C and FA-G groups. Two FANCA DNAs displayed two overlapping deletions, and another showed a homozygous deletion, and the precise breakpoints of both the deletions could be inferred from the data. We found a deletion in the FANCA gene in a sample with no prior assigned complementation group. Deletions/duplications in any of the FA genes can be queried in a single assay using CGH. Availability of the precise breakpoints will allow for identification of the samples with a shared common deletion interval. In addition to FA individuals, a deletion in FANCC and another in FANCD1 gene have been reported in two pancreatic cancer cell lines. We tested and found that our CGH arrays can identify such deletions from the xenograft of the tumor and the tumor cell line. Thus a combination of aCGH and next-gen sequencing technologies can be employed as a comprehensive screening approach for scanning all the FA genes in individuals diagnosed with FA. In addition, this offers an opportunity to explore the role of FA genes in pancreatic and other cancers.
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