title: Systematic prediction and validation of breakpoints associated with copy-number variants in the human genome.
abstract: Copy-number variants (CNVs) are an abundant form of genetic variation in humans. However, approaches for determining exact CNV breakpoint sequences (physical deletion or duplication boundaries) across individuals, crucial for associating genotype to phenotype, have been lacking so far, and the vast majority of CNVs have been reported with approximate genomic coordinates only. Here, we report an approach, called BreakPtr, for fine-mapping CNVs (available from http://breakptr.gersteinlab.org). We statistically integrate both sequence characteristics and data from high-resolution comparative genome hybridization experiments in a discrete-valued, bivariate hidden Markov model. Incorporation of nucleotide-sequence information allows us to take into account the fact that recently duplicated sequences (e.g., segmental duplications) often coincide with breakpoints. In anticipation of an upcoming increase in CNV data, we developed an iterative, "active" approach to initially scoring with a preliminary model, performing targeted validations, retraining the model, and then rescoring, and a flexible parameterization system that intuitively collapses from a full model of 2,503 parameters to a core one of only 10. Using our approach, we accurately mapped >400 breakpoints on chromosome 22 and a region of chromosome 11, refining the boundaries of many previously approximately mapped CNVs. Four predicted breakpoints flanked known disease-associated deletions. We validated an additional four predicted CNV breakpoints by sequencing. Overall, our results suggest a predictive resolution of approximately 300 bp. This level of resolution enables more precise correlations between CNVs and across individuals than previously possible, allowing the study of CNV population frequencies. Further, it enabled us to demonstrate a clear Mendelian pattern of inheritance for one of the CNVs.
authors.affiliation: Departments of Molecular Biophysics and Biochemistry, Yale University School of Medicine, New Haven, CT 06520, USA. jan.korbel@yale.edu
authors.forename: Jan O
authors.initials: JO
authors.lastname: Korbel
authors.forename: Alexander Eckehart
authors.initials: AE
authors.lastname: Urban
authors.forename: Fabian
authors.initials: F
authors.lastname: Grubert
authors.forename: Jiang
authors.initials: J
authors.lastname: Du
authors.forename: Thomas E
authors.initials: TE
authors.lastname: Royce
authors.forename: Peter
authors.initials: P
authors.lastname: Starr
authors.forename: Guoneng
authors.initials: G
authors.lastname: Zhong
authors.forename: Beverly S
authors.initials: BS
authors.lastname: Emanuel
authors.forename: Sherman M
authors.initials: SM
authors.lastname: Weissman
authors.forename: Michael
authors.initials: M
authors.lastname: Snyder
authors.forename: Mark B
authors.initials: MB
authors.lastname: Gerstein
mesh_terms: D000465:Algorithms; D001483:Base Sequence; D019457:Chromosome Breakage; D002880:Chromosomes, Human, Pair 11; D002892:Chromosomes, Human, Pair 22; D018628:Gene Dosage; D014644:Genetic Variation; D015894:Genome, Human; D006801:Humans; D008957:Models, Genetic; D008969:Molecular Sequence Data; D009693:Nucleic Acid Hybridization; D020411:Oligonucleotide Array Sequence Analysis; D020161:Physical Chromosome Mapping; D016133:Polymerase Chain Reaction; D011110:Polymorphism, Genetic; D011237:Predictive Value of Tests; D015203:Reproducibility of Results; D017422:Sequence Analysis, DNA