Clustering of Translocation Breakpoints

Abstract

Translocation, a physical movement of genetic material from one chromosome to another, can result in the aberrant linkage of two cellular genes. This type of fusion may disrupt cellular function by producing novel, biologically active fused genes, or by triggering the activation of normally quiescent growth-associated genes. Either of these mechanisms provides a putative oncogenic stimulus, and indeed, several gene fusions from translocations have been identified in leukemias, lymphomas, and sarcomas. Although the oncogenic effects of genes involved in translocations have been under intensive study, little is known regarding the formation of translocation fusions themselves. The locations of these fusions are typically independent of the resultant oncogenic protein because they usually arise within certain bounded noncoding regions of the genes. Thus the resultant proteins can be ignored in studying translocations, and we can focus exclusively on the fusions. A patterned (in particular, clustered) distribution of fusion breakpoints will potentially yield relevant information about the fusion process by identifying regions prone to recombination. Accordingly, the statistical analysis of translocation breakpoints has focused on the extent to which they cluster. Somewhat questionable methods have been used in this regard. After highlighting these shortcomings, we introduce a variety of approaches, including scan statistics, bandwidth tests, and gap statistics, that provide a comprehensive means for appraising clustering. We apply this battery to TEL–AML1 translocations, the most common translocation in childhood acute lymphoblastic leukemia. The results obtained indicate generally weaker evidence for clustering than previously reported, and also highlight differences between the statistical approaches.

KEY WORDS:

• Bandwidth test
• Gap statistic
• Gene fusion
• Scan statistic