Computational Prediction of Position Effects of Apparently Balanced Human Chromosomal Rearrangements

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\u27 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. Am J Hum Genet 2017 Aug 3; 49(8):1427-1439

Intrametropolitan Decentralization: Is Government Structure Capitalized in Residential Property Values?

Government structure, Capitalization, Border matched repeat sales, H1, H21, R50,