Please use this identifier to cite or link to this item: http://ahro.austin.org.au/austinjspui/handle/1/18038
Title: Mapping genotype-phenotype associations of nsSNPs in coiled-coil oligomerization domains of the human proteome.
Authors: Mohanasundaram, Kaavya A;Grover, Mani P;Crowley, Tamsyn M;Goscinski, Andrzej;Wouters, Merridee A
Affiliation: School of Medicine, Deakin University, Geelong, Victoria, Australia..
Australian Animal Health Laboratory, CSIRO Biosecurity Flagship, Geelong, Victoria, Australia
School of Information Technology, Faculty of Science Engineering and Built Environment, Deakin University, Geelong, Victoria, Australia
Olivia Newton-John Cancer Research Institute, Heidelberg, Victoria, Australia
School of Cancer Medicine, La Trobe University, Bundoora, Victoria, Australia
Issue Date: Oct-2017
EDate: 2017-06-23
Citation: Human mutation 2017; 38(10): 1378-1393
Abstract: We assessed the impact of disease mutations (DMs) versus polymorphisms (PYs) in coiled-coil (CC) domains in UniProt by modeling the structural and functional impact of variants in silico with the CC prediction program Multicoil. The structural impact of variants was evaluated with respect to three main metrics: the oligomerization score-to determine whether the variant is stabilizing or destabilizing-the oligomerization state, and the register-specific score. The functional impact was queried indirectly in several ways. First, we examined marginally stable CCs that were either stabilized or destabilized by the variant. Second, we looked for variants that altered the register of the wild-type CC near wild-type irregularities of likely functional importance, such as skips and stammers. Third, we searched for variants that altered the oligomerization state of the CC. DMs tended to be more destabilizing than PYs; but interestingly, PYs were more frequently associated with predicted changes in the oligomerization state. The functional impact was also queried by testing the association of CC variants with multiple phenotypes, that is, pleiotropy. Mutations in CC regions of proteins cause 155 different phenotypes and are more frequently associated with pleiotropy than proteins in general. Importantly, the CC region itself often encodes the pleiotropy.
URI: http://ahro.austin.org.au/austinjspui/handle/1/18038
DOI: 10.1002/humu.23252
ORCID: http://orcid.org/0000-0002-2121-912X
PubMed URL: 28489284
Type: Journal Article
Subjects: coiled-coil domain
complex diseases
disease mutations
lamin A
missense mutation
pleiotropy
point mutation
single-nucleotide polymorphisms
Appears in Collections:Journal articles

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