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PLoS Comput Biol. 2016 Feb 4;12(2):e1004711. doi: 10.1371/journal.pcbi.1004711. eCollection 2016 Feb.

Erosion of Conserved Binding Sites in Personal Genomes Points to Medical Histories.

Author information

1
Department of Electrical Engineering, Stanford University, Stanford, California, United States of America.
2
Department of Pediatrics (Genetics), Stanford University, Stanford, California, United States of America.
3
Department of Computer Science, Stanford University, Stanford, California, United States of America.
4
Department of Genetics, Stanford University, Stanford, California, United States of America.
5
Department of Developmental Biology, Stanford University, Stanford, California, United States of America.

Abstract

Although many human diseases have a genetic component involving many loci, the majority of studies are statistically underpowered to isolate the many contributing variants, raising the question of the existence of alternate processes to identify disease mutations. To address this question, we collect ancestral transcription factor binding sites disrupted by an individual's variants and then look for their most significant congregation next to a group of functionally related genes. Strikingly, when the method is applied to five different full human genomes, the top enriched function for each is invariably reflective of their very different medical histories. For example, our method implicates "abnormal cardiac output" for a patient with a longstanding family history of heart disease, "decreased circulating sodium level" for an individual with hypertension, and other biologically appealing links for medical histories spanning narcolepsy to axonal neuropathy. Our results suggest that erosion of gene regulation by mutation load significantly contributes to observed heritable phenotypes that manifest in the medical history. The test we developed exposes a hitherto hidden layer of personal variants that promise to shed new light on human disease penetrance, expressivity and the sensitivity with which we can detect them.

PMID:
26845687
PMCID:
PMC4742230
DOI:
10.1371/journal.pcbi.1004711
[Indexed for MEDLINE]
Free PMC Article

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