Chapter 4 Position effects of rearrangements in disease genomes

Preamble

This chapter is published in the American Journal of Human Genetics:

Cinthya J. Zepeda-Mendoza^*, Jonas Ibn-Salem^*, Tammy Kammin, David J. Harris, Debra Rita, Karen W. Gripp, Jennifer J. MacKenzie, Andrea Gropman, Brett Graham, Ranad Shaheen, Fowzan S. Alkuraya, Campbell K. Brasington, Edward J. Spence, Diane Masser-Frye, Lynne M. Bird, Erica Spiegel, Rebecca L. Sparkes, Zehra Ordulu, Michael E. Talkowski, Miguel A. Andrade-Navarro, Peter N. Robinson, Cynthia C. Morton^#. Computational Prediction of Position Effects of Apparently Balanced Human Chromosomal Rearrangements. Am J Hum Genet. 2017;101(2):206-217. doi:10.1016/j.ajhg.2017.06.011.

The publication is available online: https://doi.org/10.1016/j.ajhg.2017.06.011. My contributions to this publication are indicated in Table E.1. The source code of the complete analysis is available at GitHub: https://github.com/ibn-salem/position_effect. Supplementary information is shown in Appendix C.

^*These authors contributed equally to this work
^#corresponding author

Abstract

Interpretation of variants of uncertain significance, especially chromosome rearrangements in non-coding regions of the human genome, remains one of the biggest challenges in modern molecular diagnosis. To improve our understanding and interpretation of such variants, we used high-resolution 3-dimensional chromosome structure data and transcriptional regulatory information to predict position effects and their association with pathogenic phenotypes in 17 subjects with apparently balanced chromosome abnormalities. We find that the rearrangements predict disruption of long-range chromatin interactions between several enhancers and genes whose annotated clinical features are strongly associated with the subjects’ phenotypes. We confirm gene expression changes for a couple of candidate genes to exemplify the utility of our position effect analysis. These results highlight the important interplay between chromosome structure and disease, and demonstrate the need to utilize chromatin conformation data for the prediction of position effects in the clinical interpretation of cases of non-coding chromosome rearrangements.