Computational Prediction of Position Effects of Human Chromosome Rearrangements.

ABSTRACT

Balanced and apparently balanced chromosome abnormalities (BCAs) have long been known to generate disease through position effects, either by altering local networks of gene regulation or positioning genes in architecturally different chromosome domains. Despite these observations, identification of distally affected genes by BCAs is oftentimes neglected, especially when predicted gene disruptions are found elsewhere in the genome. In this unit, we provide detailed instructions on how to run a computational pipeline that identifies relevant candidates of non-coding BCA position effects. This methodology facilitates quick identification of genes potentially involved in disease by non-coding BCAs and other types of rearrangements, and expands on the importance of considering the long-range consequences of genomic lesions.