RESSALVA Atendendo solicitação do(a) autor(a), o texto completo desta tese será disponibilizado somente a partir de 07/08/2022. Campus de Botucatu Instituto de Biociências – Seção Técnica de Pós-Graduação Distrito de Rubião Júnior s.n CEP 18618-000 Botucatu SP Brasil posgraduacao@ibb.unesp.br Aplicabilidade de redes PPI em Biologia de sistemas no contexto da síndrome de Williams-Beuren PRISCILA MEDEIROS BOTUCATU – SP 2021 Campus de Botucatu Instituto de Biociências – Seção Técnica de Pós-Graduação Distrito de Rubião Júnior s.n CEP 18618-000 Botucatu SP Brasil posgraduacao@ibb.unesp.br UNIVERSIDADE ESTADUAL PAULISTA “Júlio de Mesquita Filho” INSTITUTO DE BIOCIÊNCIAS DE BOTUCATU Aplicabilidade de redes PPI em Biologia de sistemas no contexto da síndrome de Williams-Beuren PRISCILA MEDEIROS ORIENTADORA: Profa. Dra. Lucilene Arilho Ribeiro-Bicudo COORIENTADOR: Dr. Bruno Faulin Gamba Tese apresentada ao Instituto de Biociências, Campus Botucatu, UNESP, para obtenção do título de Doutor no Programa de Pós-Graduação em Ciências Biológicas (Genética). BOTUCATU – SP 2021 Palavras-chave: 7q11.23; Genética; PPI; Redes de interação proteína-proteína; Síndrome de Williams-Beuren. Medeiros, Priscila. Aplicabilidade de redes PPI em Biologia de sistemas no contexto da síndrome de Williams-Beuren / Priscila Medeiros. - Botucatu, 2021 Tese (doutorado) - Universidade Estadual Paulista "Júlio de Mesquita Filho", Instituto de Biociências de Botucatu Orientador: Lucilene Arilho Ribeiro-Bicudo Coorientador: Bruno Faulin Gamba Capes: 20200005 1. Genética. 2. Genes. 3. Mapeamento de interação de proteínas. 4. Síndrome de Williams. 5. Williams, Síndrome de. DIVISÃO TÉCNICA DE BIBLIOTECA E DOCUMENTAÇÃO - CÂMPUS DE BOTUCATU - UNESP BIBLIOTECÁRIA RESPONSÁVEL: ROSEMEIRE APARECIDA VICENTE-CRB 8/5651 FICHA CATALOGRÁFICA ELABORADA PELA SEÇÃO TÉC. AQUIS. TRATAMENTO DA INFORM. DEDICATÓRIA Dedico este trabalho à minha família (Eduardo, Ede, Jhonatan e Cleber) que desde sempre apoiaram minhas decisões e, mesmo sem muita compreensão, incentivaram minha jornada. Obrigada pelo imensurável carinho e amor. “Ter família, é ter sempre para onde voltar quando tudo perde sentido...” Dedico também ao meu filho. Você ainda não sabe, mais é o amor da minha vida. “Maternar é tornar-se oceano”. AGRADECIMENTOS À minha orientadora, Prof.ª Dr.ª Lucilene Arilho Ribeiro Bicudo, primeiro pela credibilidade e confiança, mas principalmente por ser a pessoa que é, digna, humana, ímpar. Sou extremamente grata por tudo que fez por mim, sobretudo pela paciência e por não desistir de mim. Meu profundo e eterno agradecimento. Ao meu coorientador, Drª. Bruno Gamba Faulin, por toda paciência, compreensão, aprendizado e amizade. Com certeza se tornou uma pessoa que levarei para sempre comigo. Aos pacientes e familiares da Associação Goiana da Síndrome de Williams (AGSW) que fizeram parte deste estudo, não haveria pesquisa científica sem a contribuição de vocês. Aos companheiros de laboratórios que além de compartilhar ciência, compartilharam momentos inesquecíveis durante a pós-graduação, desde a organização até a participação de eventos científicos, minicursos, palestras: Stéfany Empke, Jakeline Santos Oliveira, Thársis Gabryel, Amanda Tanamachi, Alessandro Vassilievitch, Ana Beatriz Palugan, Peu Macedo, Erica Ramos, Camila Baldin, Paula Freire e ao eterno grupinho “Real Oficial”: Marlene Santos, Fernanda Ramos, Gilvana Vasconcelos, Roberta Curado, Sheila Sestari, Marina Machado. Foi uma honra trabalhar e compartilhar tantos momentos com vocês. Às minhas amigas-irmãs, Luiza Mimura, Luisa Thomazini, Caroline Mitiká, Isabela Lia e seus respectivos, por todo apoio, conselho, amizade e companheirismo. Amigos, a família que o coração escolhe. Eduardo Marreto, agradeço imensamente pela ajuda na bioinformática. Aos amigos que mesmo distante, sempre celebram junto comigo cada conquista alcançada: Marina Sousa, Vinícius Dalri, Nayara Finotti, Pedro Paulo, Matheus Pavan, Lívia Paccagnella, Polyana Tizioto, Nádia Amôr, Mônica Furlan. Às novas amizades que em tão pouco tempo cada um conquistou um espaço especial dentro do meu coração: Lucas Brasa, Bruna Gazeto, Thamara Twan, Fernanda, Alessandra Rossetti. Fazer novas amizades nos recorda que a vida é uma constante surpresa e que algo maravilhoso pode surgir do nada. Aos professores e pesquisadores que contribuíram de alguma forma na minha trajetória na pós- graduação. Por mais árduo que possa ser, todo ensinamento é uma oportunidade de evoluir. Aos Prof.(s) Dr.(s) Adriana Camargo Ferrasi, Patrícia Pintor do Reis e Robson Francisco de Carvalho pelas contribuições e sugestões durante o exame de Qualificação. Aos Prof.(s) Dr.(s) Renata de Oliveira Dias, Narciso Almeida Vieira, Adriana Camargo Ferrasi, Rossano César Bonatto, por aceitarem o convite para composição da banca examinadora. À Seção de Pós-Graduação do Instituto de Biociências de Botucatu (IBB) pelo suporte técnico. Aos professores, alunos e funcionários do Departamento de Genética pelo suporte técnico e acadêmico. Ao Laboratório de Genética Molecular e Citogenética (LGMC) da Universidade Federal de Goiás (UFG) de Goiânia (GO), pelo acolhimento e colaboração dos professores e alunos. À Profa. Dra. Ana Cristina Victorino Krepischi do Laboratório de Genética Humana do Instituto de Biociências da Universidade de São Paulo (IB-USP), pela parceria na realização de análises de array-CGH das amostras do presente trabalho. Ao Laboratório de Biologia de Sistemas e Genômica do Departamento de Bioprocessos e Biotecnologia da Faculdade de Ciências Agronômicas de Botucatu coordenado pelo Prof. Dr. Guilherme Targino Valente pela colaboração no presente trabalho. À Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) pela concessão da bolsa de estudo. Finalmente, retribuo toda contribuição direta ou indireta para a realização deste trabalho às pessoas que estiveram presentes em toda trajetória. EPÍGRAFE “É tão difícil a gente caminhar Quando uma estrada não está mais lá E ter que construir o próprio chão Com as incertezas que tiver Em cada curva pra lá e pra cá Qualquer desvio pode transformar A ponta de um universo em explosão Coisa com o futuro que vier E tudo que foi dor num dia No outro dia será dia de continuar Caminhado sobre o sol Até o amor se reinventar Vida que a gente aprende Tudo o que acontece de ruim é para melhorar!” Tudo o Que Acontece de Ruim É Para Melhorar – PAULINHO MOSKA RESUMO MEDEIROS, P. Aplicabilidade de redes PPI em Biologia de sistemas no contexto da síndrome de Williams-Beuren. 2021, p.15-120. Tese de doutorado – Instituto de Biociências de Botucatu, Universidade Estadual Paulista “Júlio de Mesquita Filho” Uma microdeleção hemizigótica de 1,5Mb a 1,8Mb na região do braço longo do cromossomo 7 (7q11.23) ocasiona uma doença genética rara multigênica. Faces típicas, doenças cardiovasculares, alterações do tecido conjuntivo combinados com déficit de aprendizado e crescimento, personalidade e perfil cognitivo característicos representam o conjunto de sinais clínicos que caracteriza a síndrome de Williams-Beuren (SWB). Embora a técnica da FISH permita o diagnóstico citomolecular da síndrome, a existência de deleções de tamanhos típicos e atípicos, as quais não são evidenciadas pela FISH, acarreta em diferentes genes afetados. Por isso, o objetivo deste estudo foi investigar e caracterizar a microdeleção mediante análise por CMA (do inglês Chromosome Microarray Analysis) e analisar o impacto desta através de uma abordagem in silico utilizando redes de interação entre proteínas (PPI). Dentre os 14 indivíduos recrutados e avaliados no estudo, apenas um apresentou uma FISH negativa. Clinicamente, todos os participantes exibiram características da SWB com escore acima de 3. Uma deleção típica de 1,367,201Kb foi confirmada e caracterizada por CMA em 13 participantes do estudo e o impacto desta foi analisado em duas redes biológicas, uma representando a rede de um indivíduo sem alterações (GN) e outra representando o indivíduo acometido (PN). As proteínas codificadas pelos genes deletados foram extraídos da rede GN para simular a rede PPI do indivíduo com a deleção (PN). Análises topológicas de ambas redes foram analisadas, assim como nas redes no contexto de comunidades. Os resultados não mostraram diferenças significativas entre as redes. Pela análise de enriquecimento com termos ontológicos relacionados a processos biológicos, foi possível identificar as regiões onde houve enriquecimento dentro de cada comunidade, bem como identificar quais proteínas e termos ontológicos são compartilhados. Com isso, foi possível analisar diferenças entre as redes após a deleção e apontar diferentes proteínas até então não correlacionadas à síndrome. Embora a abordagem in silico utilizada neste estudo não tenha apresentando diferenças estatísticas, a utilização de estudos com redes biológicas além de trazer novas descobertas para o estudo da SWB, pode também ser uma ferramenta importante para esclarecer a variabilidade fenotípica e fisiopatologia da doença. Palavras-chaves: genética, síndrome de Williams-Beuren; redes de interação proteína-proteína; região 7q11.23; SWB; PPI. ABSTRACT MEDEIROS, P. Applicability of PPI networks in systems Biology in the context of Williams- Beuren syndrome. 2021, p.15-120. Doctoral Thesis - Instituto de Biociencias de Botucatu, Universidade Estadual Paulista "Julio de Mesquita Filho" A hemizygous deletion of 1.5Mb to 1.8Mb in the long arm region of chromosome 7 (7q11.23) causes a rare multigenic genetic disorder. Typical faces, cardiovascular disease, connective tissue abnormalities combined with learning and growth deficits, a characteristic personality and cognitive profile represent the set of clinical signs that characterize Williams-Beuren syndrome (SWB). Although the FISH technique allows the diagnosis, a correct genotype-phenotype correlation is necessary since, due to the existence of typical or atypical deletions, different genes can be affected. To this end, the aim of this study was to investigate and characterize microdeletion by Chromosome Microarray Analysis (CMA) and analyze its impact through an in silico approach using protein-protein interaction networks (PPI). Among the fourteen recruited and evaluated individuals, only one had a negative FISH. Clinically, all individuals exhibited WBS characteristics with score higher than 3. A typical deletion of 1,367,201Kb in thirteen individuals was confirmed and characterized by CMA and its impact was analyzed in two biological networks, one representing the network of an unchanged individual (GN) and the other representing the affected individual (PN). The proteins encoded by the deleted genes were extracted from the GN network to simulate the PPI network of the individual with the deletion (PN). Topological analyses of both networks were analyzed, as well as networks in the context of communities. The results exhibited no significant differences among the networks. By analyzing enrichment with ontological terms related to biological processes, it was possible to identify the regions where enrichment occurred within each community, as well as to identify which proteins and ontological terms are shared. By doing so, it was possible to analyze differences between the networks after the deletion and to point out different proteins not previously correlated to the syndrome. Although the in silico approach used in this study did not show statistical differences, the use of studies with biological networks, besides bringing new discoveries for the study of WBS, can also be an important tool to clarify the phenotypic variability and pathophysiology of the disease. Keywords: genetics; Williams-Beuren syndrome; protein-protein interaction networks; region 7q11.23; WBS; PPI. LISTA DE ILUSTRAÇÕES Páginas Figura 1 - Representação da região 7q11.23 deletada na síndrome de Williams-Beuren (SWB).............................................................................................................................................20 Figura 2 - Visão geral da região deletada na síndrome de Williams-Beuren de acordo com a sequência de referência humana: GRCh37/hg19 ............................................................................30 Figura 3 - Representação de um grafo G = (V, E) ..........................................................................45 Figura 4 - Grafos do tipo não direcionado (A) e direcionado (B) ...................................................46 Figura 5 - Distribuição percentual das principais características clínicas da síndrome de Williams- Beuren (SWB) presentes nos casos provenientes da AGSW (n=14) ...............................................62 Figura 6 - Visão geral da região deletada de 1,37 Mb do braço longo do cromossomo 7 ...............65 Figura 7 - Isorformas, provenientes de splicing alternativo, dos genes FKBP6 e GTF2I ..............65 Figura 8 - Diagrama de Venn das proteínas vizinhas (n = 1.225) ...................................................68 Figura 9 - Boxplot .........................................................................................................................70 Figura 10 - Grafos representando o aumento de interações da proteína vizinha Q7Z3Z0 ..............71 Figura 11 - Diagrama de dispersão ................................................................................................72 Figura 12 - Clusterização das proteínas vizinhas (n = 1.219) .........................................................73 Figura 13 - Mapas funcionais das comunidades (1-5) provenientes da rede glogal (GN) ..............76 Figura 14 - Mapas funcionais das comunidades (1-4) provenientes da rede glogal (PN) ...............77 LISTA DE TABELAS Páginas Tabela 1 - Principais genes envolvidos na síndrome de Williams-Beuren (SWB) e suas respectivas correlações genótipo-genótipo .......................................................................................................37 Tabela 2 - Resultados da técnica de CMA dos pacientes (n = 6) provenientes da Associação Goiana da Síndrome de Williams (AGSW) por meio do microarranjo SurePrint G3 Unrestricted CGH, 8x60K (AgilentTechnologies®) .....................................................................................................63 Tabela 3 - Composição das redes de interação entre proteínas (PPI) ..............................................66 Tabela 4 - Medidas topológicas das redes de interação entre proteínas (PPI) provenientes da rede global (GN) e rede paciente (PN) ....................................................................................................67 Tabela 5 - Clusterização da rede global (GN) e da rede paciente (PN) em comunidades com a quantidade de proteínas (total de proteínas de cada rede, proteínas deletadas e proteínas vizinhas)......................................................................................................................................... 69 Tabela 6 - Ontologias genéticas (GOs) anotadas pela análise espacial de enriquecimento funcional (SAFE) nas comunidades da GN de oito proteínas afetadas pela deleção em 7q11.23 ....................78 LISTA DE ABREVIATURAS AAP - Academia Americana de Pediatria ADNPM - artraso no desenvolvimento neuropsicomotor AGSW - Associação Goiana da Síndrome de Williams ATR - proteína quinase relacionada com Ataxia Telanxiectasia e Rad3 AVC - acidente vascular cerebral BA – rede do tipo Albert-László Barabási Betweenness - medidas de centralidade CEP - Comitê de Ética em Pesquisa CGD (chronic granulomatous disease) - doença granulomatosa crônica CGH array (comparative genomic hybridization array) - hibridização genômica comparativa de microarranjos CL - cutis laxa CMA (chromosomal microarray analysis) - análise cromossômica por microarranjos CNVs (copy number variation) - variações no número de cópias DECIPHER - Database of Chromosomal Imbalance and Phenotype in Human using Ensembl Resources DI - deficiência intelectual DGV - Database Genomic Variants E - aresta EAo - estenose aórtica EAP - estenose da artéria pulmonar EASV - estenose aórtica supravalvar FISH - hibridação in situ por fluorescência G - grafo GH - hormônio de crescimento GN (global network) - rede global GOs - termos ontológicos hiPSC - células-tronco pluripotentes induzidas humanas ISCN - International System for Human Cytogenetic Nomenclature k (degree) - grau ou conectividade de um nó KEGG - Kyoto Encyclopedia of Genes and Genomes LCR (low copy repeats) - baixo número de cópias lincRNA (long intergenic non-coding RNA) - lncRNA intergênico lncRNA (long non-coding RNA) - ncRNA longo miRNA - microRNAs MLPA (multiplex ligation-dependent probe amplification) - amplificação multiplex de sondas dependentes de ligação NAHR (non allelic homologous recombination) - recombinação entre homólogos não alélicos NCBI - National Center for Biotechnology Information ncRNA (non-coding RNA) - pequenos RNAs não codificantes NGS (next generation sequencing) - sequenciamento de nova geração NHEJ - união de extremidades não homólogas NPC - células progenitoras neurais OMIM - Online Mendelian Inheritance in Man PCR - reação em cadeia da polimerase piRNA (piwi-interacting rna) - RNAs interagindo com proteínas Piwi PN (patient network) - rede do paciente PPI - interação proteína-proteína QI - quociente de inteligência qPCR - PCR em tempo real RCSWB - região crítica da SWB RT (reverse transcriptase) - RT-qPCR SAFE - análise espacial de enriquecimento funcional SD (segmental duplications) - duplicações segmentais SNC - sistema nervoso central snoRNA (small nucleolar RNA) - RNAs nucleolares SVAS - estenose supravalvar da aorta SWB - síndrome de Williams-Beuren TCLE - Termo de Consentimento Livre e Esclarecido TE (transposable elemento) - elementos transponíveis TEA - transtorno do espectro autista UCSC Genome Browser UFG - Universidade Federal de Goiânia UniProt - Universal Protein V - vértices ou nós WEKA - Waikato Environment for Knowledge Analysis WES (Whole Exome Sequencing) - sequenciamento de exoma WGS (Whole Genome Sequencing) - sequenciamento do genoma todo 7dup - duplicação da região 7q11.23 - média de degree ρ - coeficiente de Pearson SUMÁRIO 1. INTRODUÇÃO E REVISÃO DA LITERATURA ........................................................ 155 1.1. Síndrome de Williams-Beuren (SWB) ....................................................................... 15 1.1.1. Características clínicas ................................................................................. 16 1.1.2. Etiologia genética ......................................................................................... 19 1.1.3. Diagnóstico .................................................................................................. 21 1.1.4. Investigações genéticas ................................................................................ 23 1.1.5. Tratamento ................................................................................................... 28 1.1.6. Correlação genótipo-fenótipo ...................................................................... 29 1.2. Redes biológicas ......................................................................................................... 44 2. OBJETIVOS ...................................................................................................................... 51 2.1. Geral ........................................................................................................................... 51 2.2. Específicos .................................................................................................................. 51 3. MATERIAIS E MÉTODOS ............................................................................................ 533 3.1. Aspectos éticos ........................................................................................................... 53 3.2. Casuística .................................................................................................................... 53 3.3. Análises Genéticas ...................................................................................................... 54 3.3.1. Obtenção do DNA genômico ....................................................................... 54 3.3.2. Análise por CMA ......................................................................................... 54 3.3.2.1. CLC Sequence Viewer .................................................................. 55 3.4. Análise de redes biológicas ......................................................................................... 55 3.4.1. Obtenção e padronização da rede PPI .......................................................... 55 3.4.2. Determinação da rede global (GN) e da rede paciente (PN) ........................ 56 3.4.3. Propriedades topológicas das redes .............................................................. 56 3.4.4. Obtenção e avaliação das proteínas vizinhas ............................................... 56 3.4.5. Obtenção das comunidades ou módulos ...................................................... 57 3.4.6. Análise de enriquecimento de ontologias genéticas (GOs) ......................... 57 4. RESULTADOS ................................................................................................................. 60 4.1. Casuística .................................................................................................................... 60 4.2. Análises Genéticas ...................................................................................................... 63 4.2.1. Investigação por CMA ................................................................................. 63 4.2.1.1. CLC Sequence Viewer .................................................................. 64 4.3. Análises de redes biológicas ....................................................................................... 66 4.3.1. Composição das redes de PPI (GN e PN) .................................................... 66 4.3.2. Análise das propriedades topológicas das redes GN e PN ........................... 66 4.3.3. Análise das propriedades topológicas das proteínas vizinhas em ambas redes (GN e PN) .......................................................................................................................... 67 4.3.4. Análise das propriedades topológicas das proteínas vizinhas dentro das comunidades ...................................................................................................................... 69 4.3.5. Análise de enriquecimento de ontologias genéticas (GOs) .......................... 75 4.3.6. Análise das proteínas vizinhas às proteínas codificadas pelos genes FZD9, ELN e GTF2I ..................................................................................................................... 80 5. 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