Page 186 - Contributed Paper Session (CPS) - Volume 7

CPS2057 Ana C. M. Ciconelle et al.

Variation in copy number on the genome of the
Brazilian population
Ana C. M. Ciconelle , Júlia M. P. Soler , Alexandre C. Pereira 2
1
1
1 Institute of Mathematics and Statistics - University of Sao Paulo – USP, Brazil
2 Heart Institute - University of Sao Paulo – USP, Brazil

Abstract
Copy number variation (CNV) is an alteration in the number of copies of a DNA
segment, unbalancing the diploid state in humans at any given locus on the
genome. The CNV region can include from a single nucleotide polymorphism
(SNP) to several genes, and such variation can be classified in five states: 0
(deletion of two copies), 1 (deletion of one copy), 2 (normal state), 3 (single
copy duplication) and 4 (double copies duplication). Several diseases (such as
uric acid, pancreatitis and nervous system disorders) and phenotypes (such as
height and cholesterol levels) have been associated to this kind of structural
variation, suggesting that inheritance patterns can be involved besides
revealing variability across populations. In this study we propose a pipeline for
CNVs calling from SNP array data. Further, in collaboration with Heart Institute
(USP), this work uses dataset from Baependi Heart Study to characterized the
CNVs in the Brazilian population and associate them with height. Genomic and
phenotype data consisted of 1,120 related individuals sampled according to
family-based design. The results pointed out to CNV regions specific for
Brazilian population, but also for similarities with others populations according
the length and number of CNVs in samples. In addition, based on trios data
(parents and offspring) it was observed that the CNV transmission could not
follow the Mendelian laws. Our work also identified a region in the
chromosome 9 associated to height, where it carries a duplication with an
expected height dropped by approximately 3cm.

Keywords
CNV calling; association studies; height, missing heritability; mixed model

1. Introduction
As described by Lewis (2012), Genome Wide Association Studies (GWAS)
aim to associate genetic markers, candidate genes or genome regions with
complex traits and diseases, which are likely derived from multiple genes and
environment, such as height and diabetes. In addition, discovering the
associations between diseases and genetic factors is an important step to
understand the pathogenesis of the diseases and to facilitate the process of
diagnosis and treatment. The most used genetic variant for GWAS is the single
nucleotide polymorphism (SNP), but other variants, as small
173 | I S I W S C 2 0 1 9