title: Intensification: A Resource for Amplifying Population-Genetic Signals with Protein Repeats.
abstract: Large-scale genome sequencing holds great promise for the interpretation of protein structures through the discovery of many, rare functional variants in the human population. However, because protein-coding regions are under high selective constraints, these variants occur at low frequencies, such that there is often insufficient statistics for downstream calculations. To address this problem, we develop the Intensification approach, which uses the modular structure of repeat protein domains to amplify signals of selection from population genetics and traditional interspecies conservation. In particular, we are able to aggregate variants at the codon level to identify important positions in repeat domains that show strong conservation signals. This allows us to compare conservation over different evolutionary timescales. It also enables us to visualize population-genetic measures on protein structures. We make available the Intensification results as an online resource (http://intensification.gersteinlab.org) and illustrate the approach through a case study on the tetratricopeptide repeat.
authors.affiliation: Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA; Integrated Graduate Program in Physical and Engineering Biology, Yale University, New Haven, CT 06520, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA.
authors.forename: Jieming
authors.initials: J
authors.lastname: Chen
authors.affiliation: Department of Chemistry, Yale University, New Haven, CT 06520, USA.
authors.forename: Bo
authors.initials: B
authors.lastname: Wang
authors.affiliation: Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA; Integrated Graduate Program in Physical and Engineering Biology, Yale University, New Haven, CT 06520, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA; Department of Chemistry, Yale University, New Haven, CT 06520, USA.
authors.forename: Lynne
authors.initials: L
authors.lastname: Regan
authors.affiliation: Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA; Integrated Graduate Program in Physical and Engineering Biology, Yale University, New Haven, CT 06520, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA; Department of Computer Science, Yale University, New Haven, CT 06520, USA. Electronic address: mark@gersteinlab.org.
authors.forename: Mark
authors.initials: M
authors.lastname: Gerstein
mesh_terms: D000595:Amino Acid Sequence; D002874:Chromosome Mapping; D003062:Codon; D019295:Computational Biology; D030541:Databases, Genetic; D019143:Evolution, Molecular; D005828:Genetics, Population / Q000379:methods*; D006801:Humans; D020407:Internet; D015394:Molecular Structure; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry / Q000235:genetics*; D012815:Signal Processing, Computer-Assisted; D014965:X-Rays
chemical_list: D003062:Codon; D011506:Proteins
keywords: database; exome sequencing; population genetics; protein repeat domain; protein structure