Predicting human genes susceptible to genomic instability associated with /-mediated rearrangements.

TitlePredicting human genes susceptible to genomic instability associated with /-mediated rearrangements.
Publication TypeJournal Article
Year of Publication2018
AuthorsSong, X, Beck, CR, Du, R, Campbell, IM, Coban-Akdemir, Z, Gu, S, Breman, AM, Stankiewicz, P, Ira, G, Shaw, CA, Lupski, JR
JournalGenome Res
Date Published2018 08
KeywordsAlu Elements, DNA Copy Number Variations, Gene Duplication, Genome, Human, Genomic Instability, Humans, Sequence Deletion

elements, the short interspersed element numbering more than 1 million copies per human genome, can mediate the formation of copy number variants (CNVs) between substrate pairs. These /-mediated rearrangements (AAMRs) can result in pathogenic variants that cause diseases. To investigate the impact of AAMR on gene variation and human health, we first characterized s that are involved in mediating CNVs (CNV-s) and observed that these s tend to be evolutionarily younger. We then computationally generated, with the assistance of a supercomputer, a test data set consisting of 78 million pairs and predicted ∼18% of them are potentially susceptible to AAMR. We further determined the relative risk of AAMR in 12,074 OMIM genes using the count of predicted CNV- pairs and experimentally validated the predictions with 89 samples selected by correlating predicted hotspots with a database of CNVs identified by clinical chromosomal microarrays (CMAs) on the genomes of approximately 54,000 subjects. We fine-mapped 47 duplications, 40 deletions, and two complex rearrangements and examined a total of 52 breakpoint junctions of simple CNVs. Overall, 94% of the candidate breakpoints were at least partially mediated. We successfully predicted all (100%) of pairs that mediated deletions ( = 21) and achieved an 87% positive predictive value overall when including AAMR-generated deletions and duplications. We provided a tool, AluAluCNVpredictor, for assessing AAMR hotspots and their role in human disease. These results demonstrate the utility of our predictive model and provide insights into the genomic features and molecular mechanisms underlying AAMR.

Alternate JournalGenome Res
PubMed ID29907612
PubMed Central IDPMC6071635
Grant List / HHMI / Howard Hughes Medical Institute / United States
R01 GM080600 / GM / NIGMS NIH HHS / United States
F31 NS083159 / NS / NINDS NIH HHS / United States
UM1 HG006542 / HG / NHGRI NIH HHS / United States
R35 NS105078 / NS / NINDS NIH HHS / United States
R01 GM106373 / GM / NIGMS NIH HHS / United States
R01 NS058529 / NS / NINDS NIH HHS / United States
K99 GM120453 / GM / NIGMS NIH HHS / United States