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

Harendra Guturu, Sandeep Chinchali, Shoa L. Clarke, Gill Bejerano

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

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.
Original languageEnglish (US)
Pages (from-to)e1004711
JournalPLOS COMPUTATIONAL BIOLOGY
Volume12
Issue number2
DOIs
StatePublished - Feb 4 2016
Externally publishedYes

Bibliographical note

KAUST Repository Item: Exported on 2022-05-26
Acknowledgements: HG was supported by a National Science Foundation Fellowship DGE-1147470, SC was supported by a Stanford Graduate Fellowship and a National Science Foundation Fellowship DGE-1147470, SLC was supported by a HHMI Gilliam Fellowship and GB was supported by NIH grants R01HG005058 and R01HD059862, NSF Center for Science of Information (CSoI) grant CCF-0939370 and KAUST. GB is a Packard Fellow and Microsoft Research Fellow.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.

ASJC Scopus subject areas

  • Ecology
  • Cellular and Molecular Neuroscience
  • Ecology, Evolution, Behavior and Systematics
  • Genetics
  • Modeling and Simulation
  • Computational Theory and Mathematics
  • Molecular Biology

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