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Phelan-McDermid syndrome (PMS) is a multi-system disorder characterized by significant variability in clinical presentation. The genetic etiology is also variable with differing sizes of deletions in the chromosome 22q13 region and types of genetic abnormalities (e.g., terminal or interstitial deletions, translocations, ring chromosomes, or SHANK3 variants). Position effects have been shown to affect gene expression and function and play a role in the clinical presentation of various genetic conditions. This study employed a topologically associating domain (TAD) analysis approach to investigate position effects of chromosomal rearrangements on selected candidate genes mapped to 22q13 in 81 individuals with PMS. Data collected were correlated with clinical information from these individuals and with expression and metabolic profiles of lymphoblastoid cells from selected cases. The data confirmed TAD predictions for genes encompassed in the deletions and the clinical and molecular data indicated clear differences among individuals with different 22q13 deletion sizes. The results of the study indicate a positive correlation between deletion size and phenotype severity in PMS and provide evidence of the contribution of other genes to the clinical variability in this developmental disorder by reduced gene expression and altered metabolomics., Competing Interests: The authors have declared that no competing interests exist.

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.

Interpretation of variants of uncertain significance, especially chromosomal 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 three-dimensional chromosomal structural data and transcriptional regulatory information to predict position effects and their association with pathogenic phenotypes in 17 subjects with apparently balanced chromosomal abnormalities. We found 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 analysis of position effect. These results highlight the important interplay between chromosomal structure and disease and demonstrate the need to utilize chromatin conformational data for the prediction of position effects in the clinical interpretation of non-coding chromosomal rearrangements., (Copyright © 2017 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)