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Detecção De Copy Number Variation (CNV) E Sua Caracterização Na População Brasileira

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Detecção De Copy Number Variation (CNV) E Sua Caracterização Na População Brasileira Detecção de Copy Number Variation (CNV) e sua caracterização na população brasileira Ana Cláudia Martins Ciconelle Dissertação apresentada ao Instituto de Matemática e Estatística da Universidade de São Paulo para Obtenção do Título de Mestre em Bioinformática Programa: Mestrado em Bionformática Orientadora: Prof. Dra. Júlia Maria Pavan Soler Durante o desenvolvimento deste trabalho a autora recebeu auxílio financeiro do CNPq e CAPES São Paulo, Janeiro de 2018 Detection of Copy Number Variation (CNV) and its characterization in Brazilian population Esta versão da dissertação contém as correções e alterações sugeridas pela Comissão Julgadora durante a defesa da versão original do trabalho, realizada em 06/02/2018. Uma cópia da versão original está disponível no Instituto de Matemática e Estatística da Universidade de São Paulo. Comissão Julgadora: • Prof. Dra. Júlia Maria Pavan Soler - IME-USP • Prof. Dr. Alexandre da Costa Pereira - HCFMUSP • Prof. Dr. Benilton de Sá Carvalho - UNICAMP Agradecimentos Agradeço aos meus pais, Claudio e Marcia, meu irmão Lucas, minhas avós, Dorga e Isabel, e todos os outros familiares que sempre me apoiaram e me fazem acreditar no significado de família. Agradeço especialmente á minha professora, orientadora e amiga, Júlia M. P. Soler, que desde da minha iniciação científica sempre esteve disponível para me ensinar, orientar e aconselhar com muita paciência, carinho e apoio. Agradeço também meus amigos de graduação em Ciências Moleculares, em especial ao Chico, Otto e o Leo, e aos amigos do IME que sempre me ajudaram em todos os sentidos possíveis. Agradeço aos professores do Ciências Moleculares e do IME por me mostrarem o caminho da ciência. Este trabalho não seria possível sem o apoio do INCOR/FMUSP por conceder os dados do Projeto Corações de Baependi e das agências CNPq e CAPES pelo apoio financeiro. i ii Resumo CICONELLE, A. C. M. Detecção de Copy Number Variation (CNV) e sua caracteri- zação na população brasileira. Programa de Bioinformática - Instituto de Matemática e Estatística, Universidade de São Paulo, São Paulo, 2018. Estudos de associação genética (do inglês, Genome-wide association studies - GWAS) são uma ferramenta fundamental para associar marcadores genéticos, genes e regiões genômicas com doenças e fenótipos complexos, permitindo compreender em mais detalhes essa rede de regulação bem como mapear genes e, com isso, desenvolver técnicas de diagnóstico e tratamento. Atualmente, a principal variante genética utilizada nos estudos de associação é o SNP (do inglês, Single Nucleotide Polymorphism), uma variação que afeta apenas uma base do DNA, sendo o tipo de variação mais comum tanto entre os indivíduos como dentro do genoma.. Apesar das diferentes técnicas disponíveis para os estudos de associação, muitas doenças e traços complexos ainda possuem parte de sua herdabilidade inexplicada. Para contribuir com estes estudos, foram criados banco de dados genéticos de referência, como o HapMap e o 1000 Genomes, que possuem representantes das variantes genéticas comuns das populações mundiais (européias, asiáticas e africanas). Nos últimos anos, duas das solucões adotadas para tentar explicar a herdabilidade de doenças e fenótipos complexos correspondem a utilizar diferentes tipos de variantes genéticas e incluir variantes raras e específicas para uma determinada população. O CNV (do inglês, Copy Number Variation) é uma variante estrutural que está ganhando espaço nos estudos de associação nos últimos anos. Essa variante é caracterizada pela deleção ou duplicação de uma região do DNA que pode ser de apenas alguns pares de bases até cromossomos inteiros, como no caso da síndrome de Down. Em parceria com o Instituto do Coração (InCor-FMUSP), este trabalho utiliza os dados do projeto Corações de Baependi para estabelecer uma metodologia para caracterizar os CNVs na população brasileira a partir de dados de SNPs e associá-los com a altura. O projeto inclui dados genéticos e fenótipos de 1,120 indivíduos relacionados (estruturados em famílias). Para a detecção dos CNVs, os recursos do software PennCNV são utilizados e metodolo- gias de processamento, normalização, identificação e análises envolvidas são revisadas. A caracterização dos CNVs obtidos inclui informações de localização, tamanho e frequência na iii iv população e padrões de herança genética em trios. A associação dos CNVs com a altura é realizada a partir de modelos lineares mistos e utilizando informações sobre a estrutura de família. Os resultados obtidos indicaram que a população brasileira contém regiões (únicas) com variação no número de cópias que não estão identificadas na literatura. Características gerais dos CNVs, como tamanho e frequência no indivíduo, foram semelhantes ao que é apontado na literatura. Também foi observado que a transmissão de CNV pode não seguir as leis mendelianas, uma vez que a frequência de trios com um dos pais com deleção/duplicação e filho normal era superior à frequência dos trios com filho portador da mesma variação. Este trabalho também identificou uma região no cromossomo 9 que pode estar associ- ada com a altura, sendo que portadores de uma duplicação nesta região podem ter uma diminuição esperada de aproximadamente 3cm na altura. Palavras-chave: CNV, herdabilidade, fenótipos complexos, SNPs, dados de família. Abstract CICONELLE, A. C. M. Detection of Copy Number Variation (CNV) and its char- acterization in Brazilian population. 2016. Master in Bioinformatics - Instituto de Matemática e Estatística, Universidade de São Paulo, São Paulo, 2018. Genome-wide association studies (GWAS) are a tool of high importance to associate genetic markers, genes and genomic regions with complex phenotypes and diseases, allowing to understand in details this regulation of gene expression as well as the genes, and then develop new techniques of diagnoses and treatment of diseases. Nowadays, the main genetic marker used in GWAS is the SNP (single nucleotide polymorphism), a variation that affects only one base of the DNA, being the most common type of variation between individuals and inside the genome. Even though there are multiple techniques available for GWAS, several complex traits still have unexplained heritability. To contribute to these studies, reference genetic maps are being created, such as the HapMap and 1000 Genomes, which have common genetic variants from world wide population (including European, Asian and African populations). In the last years, two solutions adopted to solve the missing heritability are to use different types of genetic variants and include the rare and population specific markers. Copy number variation (CNV) is a structural variant which use is increasing in GWAS in the last years. This variant is characterized for the deletion or duplication of a region a DNA and its length can be from few bases pair to the whole chromosome, as in Down syndrome. In collaboration of the Heart Institute (InCor-FMUSP), this work uses the dataset from Baependi Heart Study to establish a methodology to characterized the CNVs in the Brazilian population using SNP array data and associate them with height. This project uses the genetic and phenotype data of 1,120 related samples (family structure). For CNV calling, resources from the software PennCNV are used and methodologies of preprocessing, normalization, identification and other analysis are reviewed. The character- ization of CNVs include information about location, size, frequency in our population and the patterns of inheritance in trios. The association of CNVs and height is made using linear mixed models and with information of family structure. The obtained results indicate that the Brazilian population has regions with variation in the number of copies that are not in the literature. General characteristics, such as length v vi and frequency in samples, are similar to the information found in the literature. In addi- tion, it was observed that the transmission of CNVs could not follow the Mendelian laws, since the frequency of trios which one parent has a deletion/duplication and the offspring is normal is higher than the frequency of trios with one parent and the offspring has a deletion/duplication. This work also identified a region on chromosome 9 that could be associated to height, being that carries of a duplication in this region can have the expected height dropped by approximately 3cm. Keywords: CNV, heritability, complex phenotypes, SNPs, family data. Contents List of Abbreviations ix List of Figures xi List of Tables xiii 1 Introduction1 2 Copy Number Variation (CNV)7 2.1 Biological background..............................7 2.2 Mechanisms for CNVs Generation and CNV Transmission.......... 11 2.3 CNV Calling................................... 14 2.4 Association Studies and CNVs.......................... 16 2.4.1 CNVs and Height............................. 20 3 Materials and Methods 23 3.1 Dataset...................................... 23 3.1.1 SNP array platform............................ 24 3.2 Methodology Overview.............................. 26 3.3 Preprocessing of SNP data............................ 30 3.3.1 Quantile normalization.......................... 31 3.3.2 Median polish............................... 32 3.3.3 SNP Genotype Calling.......................... 33 3.4 Log R Ratio (LRR) and B Allele Frequency (BAF).............. 35 3.4.1 Log R Ratio (LRR)............................ 36 3.4.2 B Allele Frequency (BAF)........................ 36 3.5 Hidden Markov Models (HMM)......................... 38 3.6 Selection of CNV Regions...........................
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