TY - JOUR
T1 - Erosion of Conserved Binding Sites in Personal Genomes Points to Medical Histories
AU - Guturu, Harendra
AU - Chinchali, Sandeep
AU - Clarke, Shoa L.
AU - Bejerano, Gill
N1 - 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.
PY - 2016/2/4
Y1 - 2016/2/4
N2 - 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.
AB - 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.
UR - http://hdl.handle.net/10754/678260
UR - https://dx.plos.org/10.1371/journal.pcbi.1004711
UR - http://www.scopus.com/inward/record.url?scp=84959473088&partnerID=8YFLogxK
U2 - 10.1371/journal.pcbi.1004711
DO - 10.1371/journal.pcbi.1004711
M3 - Article
C2 - 26845687
SN - 1553-7358
VL - 12
SP - e1004711
JO - PLOS COMPUTATIONAL BIOLOGY
JF - PLOS COMPUTATIONAL BIOLOGY
IS - 2
ER -