A pecuária de corte brasileira tem sofrido grande pressão devido às questões ambientais, às exigências dos mercados consumidores por carne de qualidade e rígidos padrões sanitários. Esses fatores aumentam a importância da melhoria da eficiência produtiva da pecuária de corte. A proposta do presente trabalho foi avaliar o efeito da inclusão dos valores genéticos moleculares, de um painel de marcadores genéticos comerciais (Perfil IGENITY® Nelore V3) na seleção de animais da raça Nelore. Foram utilizados dados de 9.749 animais da raça Nelore mensurados para área de olho de lombo, espessura de gordura subcutânea e espessura de gordura na picanha e 39.687 animais na matriz de parentesco. Dois modelos de análise foram utilizados. O modelo de análise uni-característica em que apenas os parâmetros genéticos do fenótipo foram estimados e o modelo bi-característica em que os valores genéticos moleculares de 3.033 animais foram incluídos como característica correlacionada. A inclusão dos valores genéticos moleculares no modelo aumentou as acurácias das estimativas dos valores genéticos preditos dos animais genotipados, principalmente dos machos jovens. As analises dos conflitos de seleção demonstraram maiores divergências nos touros e machos jovens que tiveram seus genótipos definidos. A taxa de ganho genético anual com a inclusão dos valores genéticos moleculares no modelo foi aumentada em 2,4% para área de olho de lombo, 0,9% para espessura de gordura subcutânea e 1,9% para espessura de gordura na picanha. Esses resultados demonstram que a utilização dos valores genéticos moleculares , mesmo quando oriundos de painéis de marcadores de DNA de baixa densidade, pode contribuir na seleção de animais superior mérito genético e, além de promover aumento nos ganhos genéticos dos programas de melhoramento genético da raça Nelore. / The Brazilian beef cattle chain is suffering a huge pressure due to environmental issues, the demand of consumer markets for meat quality and strict sanitary standards of the international market. These factors increase the importance of improving productive efficiency of beef cattle. The proposal of this study was to evaluate the effect of inclusion of the molecular breeding values of a commercial panel of genetic markers (Nellore Profile IGENITY® V3) in the genetic selection of Nellore cattle. Data of 9,749 animals measured for ribeye area, fat thickness and rump fat thickness were used in this study, with a relationship matrix compound of 39,687 animals. Two models of analysis were performed. Single trait model was performed only for each observed phenotypes and two-trait model was performed phenotypes and molecular breeding values of 3,033 animals as a correlated trait. The inclusion of molecular information in genetic evaluation provided increases on the accuracies of predicted breeding values of genotyped animals and, mainly, for replacement young bulls. The divergences of selection for 20% best animals classified by 1-trait breeding values and 2-trait breeding values demonstrated highest divergence for sires and replacement young bulls. The genetic change rate on the 2-trait model increased 2,4% for ribeye area, 0,9 for fat thickness and 1,9% for rump fat thickness. These results demonstrated that the inclusion of molecular breeding values, even when estimated from low density genetic markers panels, on animal breeding evaluations can contribute on the selection of best genetic merit animals and increase of genetic change rate on animal breeding programs for Nellore cattle.

Atualmente, o Brasil é considerado o maior exportador mundial e terceiro maior produtor mundial de carne de frango. Este destaque é resultado, principalmente, do melhoramento animal baseado na estimação do valor genético a partir da mensuração de fenótipos e informações de pedigree. Entretanto, é comum que a seleção não seja feita para cada característica isoladamente devido à correlação genética entre elas. Esta correlação tem como causas a pleiotropia ou a ligação genética. Com este trabalho objetivou-se detectar associações entre características fenotípicas de interesse para a avicultura e SNPs em uma região do cromossomo 1 (168 - 208 cM e 57 - 71 Mbp), onde possíveis QTL ligados foram previamente mapeados. Utilizou-se o Beadchip de SNPs de 60k para genotipar 14 animais da geração Parental (machos TT e fêmeas CC) e 28 F1 da população TCTC desenvolvida pela Embrapa Suínos e Aves. A linhagem TT apresentou maior variabilidade genotípica que CC, porém, os F1 foram superiores às linhagens Parentais com base no número de heterozigotos e MAF. O polimorfismo com maior ocorrência em ambas as gerações foram as transições com 84,3%. Foram selecionados 144 SNPs mais informativos com base na heterozigosidade dos cinco casais F1 que geraram os 453 F2. Houve redução de heterozigotos e MAF em F2, em função da média de F1, decorrente de certo grau de parentesco e endogamia entre os animais que compuseram esta geração. Os blocos de haplótipos construídos demonstraram que os machos TT apresentaram 25 blocos, fêmeas CC (17), F1 (32) e F2 (23) com tamanho médio de 278, 467, 242 e 160 kpb, respectivamente. Foi evidenciado que 236 (42,7%) correlações fenotípicas foram significativas, das quais o maior número constatado foi entre PB_MS e outras 17 características e, o maior valor estimado foi entre PB_MS e EE_MS (-0,90). Do total esperado de 3.456 testes de associação, 609 (17,6%) foram considerados significativos (p < 0,05), sendo 424 (69,6%) com efeito aditivo e 185 com efeito de dominância (30,4%). PV41 apresentou maior número de associações (123), enquanto DOR não foi associado a nenhum SNP. Proporcionalmente, o maior número de SNPs foi associado próximo ao QTL pleiotrópico 2 para 17 características. Já os maiores níveis de significância (p < 9,59 x 10-8) para o efeito aditivo foram evidenciados para SNPs localizados próximos ao QTL pleiotrópico 1 e associados somente com PV41, a saber: Gga_rs13869715 (A < C), Gga_rs13870613 (T < C), Gga_rs14827719 (A < G), GGaluGA019336 (T < C) e GGaluGA019533 (A < C). Foram detectadas associações ainda não descritas na literatura para GP3541, CA3541, INT, PES, CAB, FIG, COR, MOE, PUL, HEM, COL, TRI, TC, PB_MS, EE_MS, CZ_MS. Finalmente, foram indicados possíveis genes candidatos posicionais e funcionais, tais como, IGF1, MYBPC1, MTPN, SOX-5, FGFR1OP2 e TTLL12 que poderão ser empregados na análise de expressão gênica. / Actually, Brazil is considered the world\'s first- and third-biggest exporter and producer of poultry meat, respectively. These performances are mainly consequence of animal breeding based on the estimation of breeding value combining phenotypes and pedigree information. However, usually the selection is not carried out for each trait separately due to genetic correlation between them. This correlation is caused by pleiotropy or linkage. We aimed to detect associations between phenotypic traits of interest to poultry industry and SNPs on a region of chromosome 1 (168 - 208 cM and 57 - 71 Mbp), where putative linked-QTL were previously mapped. A chicken 60k SNP BeadChip was used to genotype 14 animals from Parental generation (TT males and CC females) and 28 F1 of the TCTC population that was developed by Embrapa Swine and Poultry. The TT line showed greater genotypic variability than CC, however, F1 were higher than Parental generation based on the number of heterozygotes and MAF. The polymorphism more frequent in both generations was the transitions with 84.3%. The 144 most informative SNPs were selected based on heterozygosity of the five F1 couples which generated the 453 F2. There was a reduction of heterozygotes and MAF in F2, based on the F1 mean value, as consequence of some degree of relationship and inbreeding between animals that formed this generation. Haplotype blocks demonstrated that the TT males showed 25 blocks, CC female (17) F1 (32) and F2 (23) with an average size of 278, 467, 242 and 160 kbp, respectively. It was observed that 236 (42.7%) phenotypic correlations were significant. Out of these, the highest number was found between PB_MS and other 17 traits and the highest estimated value was between PB_MS and EE_MS (-0.90). Out of 3,456 expected association tests, 609 (17.6 %) were considered significant (p < 0.05), being 424 (69.6%) with additive effect and 185 with dominance effect (30.4%). PV41 presented the highest number of associations (123), while DOR was not associated to any SNP. Proportionally, the highest number of SNPs was associated close to the pleiotropic QTL 2 with 17 traits. On the other hand, the highest significance levels (p < 9.59 x 10-8) for the additive effect were evidenced for SNPs located close to the pleiotropic QTL 1 and associated only with PV41 (Gga_rs13869715 (A < C), Gga_rs13870613 (T < C), Gga_rs14827719 (A < G), GGaluGA019336 (T < C) and GGaluGA019533 (A < C)). Novel associations were detected for GP3541, CA3541, INT, PES, CAB, FIG, COR, MOE, PUL, HEM, COL, TRI, TC, PB_MS, EE_MS, CZ_MS when we compared our results with literature. Finally, putative positional and functional candidate genes were indicated such as IGF1, MYBPC1, MTPN, SOX-5, FGFR1OP2 and TTLL12, which may be used in gene expression analysis.

A seleção genômica (Genomic Selection - GS) permite identificar indivíduos superiores com base no seu método genômico e apresenta a possibilidade de incorporação do melhoramento quantitativo à genética molecular. O melhor preditor linear não viesado (Best Linear Unbiased Prediction - BLUP) é um método de predição dos efeitos aleatórios do modelo com base nos componentes de variância obtidos por meio do método máxima verossimilhança restrita (Restricted maximum likelihood - REML). A eficiência do REML\\BLUP pode ser incrementada por meio da incorporação de matrizes de parentesco genômico nos modelos de seleção genômica, uma vez que os efeitos genéticos genômicos aditivos dos indivíduos avaliados constituem os componentes aleatórios dos modelos mistos abordados. Dentre os algoritmos disponíveis para estimá-las, a partir de dados de polimorfismo de nucleotídeo único (Single-nucleotide polymorphism - SNP\'s) há as matrizes de Vanraden (2008) Astle e Balding (2009) e as de Yang et al. (2010) (matriz de parentesco unificado e matriz de parentesco unificado ajustado). Adicionalmente ao método de estimação da matriz de parentesco, a acurácia da GS depende da densidade de marcadores e da extensão e padrão de desequilíbrio de ligação (Linkage desequilibrium - LD) que existe no painel. Com isto, os objetivos foram: i) investigar o efeito da redução nas densidades de marcadores SNP\'s, por meio do LD, na estimativa do parentesco genético dos indivíduos e, consequentemente, na acurácia preditiva da GS; ii) estudar o efeito do uso de diferentes tipos de matrizes de parentesco genômico na acurácia da seleção genômica para linhagens e híbridos de milho tropical. Para isso, foram considerados dois painéis distintos de milho tropical: uma composta por 64 linhagens endogâmicas e a outra, por 452 híbridos. Estas foram avaliadas para o caráter produtividade de grãos, em oito e cinco ambientes, respectivamente. As linhagens e os híbridos foram genotipados com a plataforma Affymetrix&reg; Axiom&reg; Maize Genotyping Array, com cerca de 600 mil marcadores. Foram construídos diferentes cenários de GS quanto ao tipo de painel (linhagens e híbridos), densidade de marcadores (400k, 60k, 9586 e 1304 para linhagens e 50k, 4458 e 495, para híbridos) e tipos de matrizes de parentesco (citadas acima). Em cada um destes cenários foi estimada a herdabilidade, acurácia, capacidade preditiva e a coincidência de seleção. A partir dos resultados conclui-se que: tanto para híbridos como para linhagens, a densidade de marcas pode ser reduzida significativamente por meio do LD existente entre os SNP\'s, sem gerar prejuízos quanto à acurácia da GS, mas reduzindo os custos com genotipagem e a demanda computacional. Para predição genômica das linhagens, a matriz de Vanraden (2008) apresenta o melhor custo benefício, pois tem menor demanda computacional e proporciona resultados satisfatórios quanto à acurácia e coincidência de seleção. Para a predição genômica de híbridos, as matrizes de Yang et al. (2010) são superiores em relação às demais testadas, quanto à acurácia preditiva e coincidência de seleção. / The efficiency of the Best Linear Unbiased Prediction (BLUP), along with the Restricted maximum likelihood (REML) methods, can be increased by incorporating genomic kinship matrices to Genomic Selection models (GS). Among the available algorithms to estimate these matrices from single-nucleotide polymorphism (SNP) data there are Vanraden (2008), Astle e Balding (2009) and Yang et al. (2010) (unified relationship matrix and adjusted unified relationship matrix). In addition to the estimation method of the relationship matrix, the accuracy of GS depends on the density of markers and the extent and pattern of linkage disequilibrium (LD) that there is in the panel. Thus, the aims were: i) assess the effect of marker density reduction, based on LD, on the estimative of the genetic relationship of individuals and, consequently, on the predictive accuracy of GS; ii) study the effects of types of genomic relationship matrices on the accuracy of genomic selection for tropical maize lines and hybrids. In order to achieve there, two distinct panel of tropical maize were used: the first consisting of 64 inbred lines and latter of 452 hybrids. These panels were evaluated in field trials for grain yield in eight and five environments, respectively. The lines and hybrids were genotyped by the Affymetrix&reg; Axiom&reg; Maize Genotyping Array platform with 612 thousand markers. Distinct scenarios of GS were comprised considering panel type (lines and hybrids), marker density (400k, 60k, 9586 and 1304 for lines and, 50k, 4458 and 495 for hybrids) and, types of kinship matrices cited aboved. In each of these scenarios heritability, accuracy, predictive capacity and the selection coincidence were estimated. From the results it was concluded that: for both, hybrids and lines, marker density can be significantly reduced based on LD between SNP\'s without affecting the accuracy. Furthermore, this reduction also decreases genotyping costs and computational requirements. For genomic prediction of lines, Vanraden (2008) matrix shows the best cost-benefit, because it demands less computer resources and provides satisfactory results in terms of accuracy and selection coincidence. On the other hand, for genomic prediction of hybrids, the matrices of Yang et al. (2010) yielded higher predictive accuracies and selection coincidences.

L'analyse chromosomique sur puce ADN (ACPA) tend à devenir le principal examen diagnostique dans la déficience intellectuelle (DI). Parmi les techniques d'ACPA, les puces SNP ont l'intérêt de pouvoir détecter les pertes d'hétérozygotie, et par conséquent d’identifier les isodisomies uniparentales (iUPD) et les zones d'identité liées à la consanguinité. Nous avons étudié une cohorte de 1 187 patients atteints de DI, dans un cadre diagnostique, sur puces SNP. Nous avons réalisé, par cette étude, 145 diagnostics (12%) dont 2 iUPD et 6 délétions n'incluant qu'un seul gène. De plus, nous avons détecté 639 CNV rares non décrits chez des sujets contrôles et incluant des séquences codantes, ce qui nous a permis d'identifier 11 gènes candidats dans la DI : CAMTA1, SP3, CNTNAP4, NUDT12, STXBP6, DOCK8, DOCK10, SMARCA2, NYAP2, ATAD3A et ATAD3B. Nous avons tenté de valider l'implication de ces gènes par séquençage, mais n'avons trouvé de seconde mutation pour aucun d'entre eux. Toutefois, des réarrangements de CAMTA1 ont été retrouvés dans 2 autres familles avec un phénotype homogène (DI et ataxie congénitale) ce qui nous a permis d’affirmer qu'il s'agit d'un gène de DI. Par ailleurs, l'homozygosity mapping, réalisé avec puces SNP, a identifié, par séquençage whole exome, une mutation non-sens homozygote du gène BUD13 dans une famille de DI syndromique. Enfin, de façon fortuite, nous avons caractérisé en ACPA une translocation familiale entraînant une disruption d'un gène d'ataxie spino-cérébelleuse, ATXN10, ce qui a permis de mieux comprendre la physiopathologie de cette maladie. Au total, notre étude démontre l'intérêt des puces SNP dans la DI, d'une part en diagnostic et d'autre part pour l'identification de nouveaux gènes responsables de DI. / Chromosomal Microarray Analysis (CMA) has become the main diagnostic test in the field of intellectual disability (ID). Among CMA techniques, SNP arrays have the advantage of identifying losses of heterozygosity in addition to Copy Number Variants (CNVs). Therefore they can detect uniparental isodisomies (iUPD) and regions of identity by descent. We screened a cohort of 1,187 patients with ID, in diagnostic setting, by CMA using SNP arrays. Causal abnormalities, including 2 iUPDs and 6 deletions comprising only one gene, were detected in 145 patients (12%). Moreover we found 639 rare CNVs, absent from control individuals, which included coding sequences. Our results allowed us to identify 11 genes possibly involved in or contributing to ID: CAMTA1, SP3, CNTNAP4, NUDT12, STXBP6, DOCK8, DOCK10, SMARCA2, NYAP2, ATAD3A and ATAD3B. We then screened additional patients with similar phenotypes in order to find a second mutation, but no second mutation was identified in any of them. Besides, CAMTA1 rearrangements were also found among two other families with homogeneous phenotypes (ID and congenital ataxia), which confirms that this gene is involved in ID. Furthermore, thanks to homozygosity mapping made possible by SNP arrays combined with exome sequencing, we identified a homozygous nonsense mutation in the BUD13 gene, in a family with syndromic ID. Finally we incidentally characterized a familial translocation resulting in the disruption of ATXN10, a gene responsible for spinocerebellar ataxia. This translocation has helped to better understand the pathophysiology of the disease. Overall, our study shows the importance of SNP arrays for the molecular diagnosis of ID and as a tool to identify genes responsible for ID.

Le développement de la seconde génération de séquenceurs haut débit a généralisé l'accès à l'étude du transcriptome via le protocole RNAseq. Celui-ci permet d'obtenir à la fois la séquence et l'abondance des transcrits d'un échantillon. De nombreuses méthodes bioinformatiques ont été et sont encore développées pour permettre l'analyse des données issues du RNAseq et en tirer le maximum d'information. Ce type d'analyse est notamment possible sans utiliser de génome de référence, et donc pour les espèces modèles ou non-modèles, grâce à des méthodes d'assemblage. Durant ma thèse, j'ai principalement travaillé à partir de données RNA-seq issues d'espèces non modèles. Je me suis intéressée dans un premier temps à l'impacte de l'hybridation inter spécifique sur la stabilité des génomes chez les hybrides issus des croisements réciproques de D. mojavensis et D. arizonae. Nos résultats ne montrent pas une dérégulation globale, mais plutôt quelques gènes et éléments transposables qui sont spécifiquement dérégulés. La pipeline d'analyse mis en place ici sera réutilisée pour l'étude des niveaux d'expression des transcrits chez les mâles ainsi que pour les croisements issus d'autres lignées de D. mojavensis avec D. arizonae, conduisant à une fertilité variable chez les hybrides.Dans un second temps, j'ai participé à la validation du logiciel KisSplice pour la détection de SNP dans des données RNA-seq sans génome de référence. Celui-ci permet de trouver différents types de variants (épissage, indels) directement dans le graphe de de Bruijn construit à partir des lectures séquencées. J'ai également participé au développement d'outils de post-traitement permettant de prédire l'impact des SNP sur les protéines / Next-generation high throughput sequencing technologies provide efficient, rapid, and low cost access to sequencing. Its application to transcriptomes, called RNA-seq, enables the study of both the sequence and the expression of the transcripts. Many bio-informatics methods are still developed for RNA-seq data processing, trying to get the maximum out of it. Assembly methods allow us to study non-model species (no reference genome available) as well as model species. The work presented here is mostly related to RNA-seq data on non-model species.In the first study, to understand the initiation of hybrid incompatibility, we performed a genome-wide transcriptomic analysis on ovaries from parental lines and on hybrids from reciprocal crosses of \emph{D. mojavensis} and \emph{D. arizonae}. We didn't see a global deregerulation of genes or transposable element. Instead, we show that reciprocal hybrids presented specific gene categories and few transposable element families misexpressed relative to the parental lines. The analytical workflow developed for this project will be used to analyze transcriptomic data from the testis, but also to study the reciprocal crosses from other lines of D. mojavensis with D. arizonae leading to variable levels of sterility in hybrids. A second project tacked here is the identification and quantification of SNPs from RNA-seq data without a reference genome with KisSplice. Kissplice was developed to identified several type of variants (splicing events, indels) directly from the de Bruijn graph, build from the sequenced reads. We also developed other KisSplice-tools, for downstream analyses of the SNPs, including the prediction of their impact on the protein sequence

Le cancer du pancréas est un cancer très agressif et de pronostic très sombre. Il est diagnostiqué tardivement et se montre résistant aux traitements. Dans ce contexte, il est nécessaire de mettre en évidence de nouveaux marqueurs spécifiques de cette pathologie dévastatrice. Le but de notre étude était de rechercher un marqueur « génétique » de ce cancer au sein du gène de la lipase sels biliaires-dépendante (BSDL) localisé en position 9q34.3 et plus particulièrement au niveau de l'exon 11 de ce gène codant pour le domaine C-terminal de la protéine et constitué de séquences répétées (séquences VNTR). L’analyse des électrophérogrammes obtenues après séquençage de Sanger à partir des amplicons de PCR réalisées sur l’ADNg extraits de tissus de patients atteints de cancer du pancréas, a permis d’identifier deux altérations génétiques : (i) la présence d’un SNP (Single Nucleotide Polymorphism) synonyme référencé rs488087, impliquant la transition c.1719C>T ; qui semble être associée au développement d’un cancer du pancréas sporadique et pourrait être un potentiel facteur prédictif de ce cancer permettant de cibler des populations à risque, (ii) la présence d’une insertion d’un nucléotide C induisant l'apparition d'une protéine BSDL tronquée présentant une séquence C-terminale modifiée contre laquelle ont été développé des anticorps polyclonaux. Cette nouvelle séquence pourrait constituer un potentiel marqueur diagnostique et/ou thérapeutique du cancer du pancréas. Ces deux altérations génétiques constituent ainsi de potentiels marqueurs du cancer du pancréas. / Pancreatic cancer is a devastating disease progressing asymptomatically until death within months after diagnosis. In this context, it is necessary to identify new specific markers to develop diagnostic tools and to target an at risk population. The aim of our study was to find a "genetic" marker in the bile salt-dependant lipase gene (BSDL). The human BSDL gene is located on the long arm of chromosome 9 in 9q34.3 with a variable number of tandem repeats (VNTR) in the coding region of exon 11. The electropherograms obtained after Sanger sequencing analysis of gDNA amplified from pancreatic cancer tissue samples allowed us to highlight: (i) the presence of a SNP (Single Nucleotide Polymorphism) involved in c.1719C>T transition which is referenced rs488087. rs488087 seems to be associated with the sporadic pancreatic cancer development and may be a predictive factor of pancreatic cancer for targeting an at risk population, (ii) the presence of a C nucleotide insertion leading to a premature stop codon with truncated protein and to the modification of the C-terminal sequence end. This new C-terminal sequence, alteration could be used as a potential diagnostic and/or therapeutic marker. Finally, these two genetic alterations identified in BSDL gene could constitute potential markers of pancreatic cancer.

Tambaqui (Colossoma macropomum) is the largest native Characiform species from the Amazon and Orinoco river basins of South America. Tambaqui farming is growing rapidly in Brazil, its production reached 139.209 tons in 2014, what corresponds to 57.7% of increase compared with 2013. However, few genetic studies of tambaqui are currently available. The tambaqui genetic studies for cultured and wild populations need a holistic approach for a rational action facing ecological and market challenges in aquaculture. Approaches based on genetic studies have provided important tools to understand population dynamics, local adaptation, and gene function to improve selection strategies to be applied in breeding programs. The next-generation sequencing (NGS) allowed a great advance in genomic and transcriptomic approaches, especially related to non-model species. The genotype-by-sequencing (GBS) is one of this approaches based on genome complexity reduction using restriction enzymes (REs). This thesis presents the application of these approaches to provide advances in the genetic background for tambaqui studies. The GBS approach provided a high-density SNPs panel that allowed us to develop the first linkage map, and association studies with environmental variables, local adaptation, and lack of intermuscular bones, both using tambaqui as a model. This work can give us many theoretical references to be applied in genetic breeding programs for tambaqui, allowing a better understanding of genetic processes related to traits of interest in aquaculture. / O tambaqui (Colossoma macropomum) é a maior espécie nativa de Characiforme da América do Sul e é encontrado nas bacias do rio Amazonas e Orinoco. O cultivo do tambaqui está crescendo rapidamente no Brasil, sua produção atingiu 139.209 toneladas em 2014, o que corresponde a 57,7% de aumento em relação a 2013. No entanto, poucos estudos genéticos realizados com o tambaqui estão disponíveis atualmente. Estudos genéticos em tambaqui, tanto em populações cultivadas quanto em populações selvagens, necessitam de uma abordagem holística para uma ação racional frente aos desafios ecológicos e mercadológicos na aquicultura. Abordagens baseadas em estudos genéticos têm fornecido ferramentas importantes para se entender a dinâmica populacional, adaptação local e função gênica visando melhorar as estratégias de seleção a serem aplicadas em programas de melhoramento genético. O sequenciamento de nova geração (NGS) permitiu um grande avanço nas abordagens genômicas e transcriptômicas, especialmente relacionadas a espécies não-modelo. A genotipagem por sequenciamento (GBS) é uma dessas abordagens que utilizam enzimas de restrição (REs) para reduzir a complexidade do genoma. Esta tese apresenta a aplicação desta abordagem objetivando proporcionar avanços significativos nos estudos genéticos de base para tambaqui. A técnica de GBS forneceu um painel de SNPs de alta densidade que nos permitiu desenvolver o primeiro mapa de ligação e estudos de associação com variáveis ambientais, adaptação local e ausência de ossos intermusculares no tambaqui. Este trabalho pode nos dar muitas referências teóricas a serem aplicadas em programas de melhoramento genético do tambaqui, permitindo uma melhor compreensão dos processos genéticos relacionados a traços de interesse na aquicultura.

Dezoito galinhas de uma população experimental utilizada em um cruzamento recíproco entre as linhagens de frangos de corte (TT) e de postura (CC) foram sequenciadas pela tecnologia de nova geração na plataforma Illumina com uma cobertura média de 10X. A descoberta de variantes genéticas foi realizada em uma região de locos de característica quantitativa (Quantitative Trait Locus, QTL), associado anteriormente com peso e percentagem de gordura abdominal no cromossomo 3 da galinha (GGA3), entre os marcadores microssatélites LEI0161 e ADL0371 (33,595,706-42,632,651 pb). O programa SAMtools foi utilizado na identificação de 136.054 SNPs únicos e 15.496 INDELs únicas nos 18 animais sequenciados e após a filtragem das mutações, 92.518 SNPs únicos e 9.298 INDELs únicas foram mantidas. Uma lista de 77 genes foi analisada buscando genes relacionados ao metabolismo de lipídios. Variantes localizadas na região codificante (386 SNPs e 15 INDELs) foram identificadas e associadas com vias metabólicas importantes. Variantes nos genes LOC771163, EGLN1, GNPAT, FAM120B, THBS2 e GGPS1 foram identificadas e podem ser responsáveis pela associação do QTL com a deposição de gordura na carcaça em galinhas. / Eighteen chickens from a parental generation used in a reciprocal cross with broiler and layer lines were sequenced by new generation technology with an average of 10-fold coverage. The DNA sequencing was performed by Illumina next generation platform. The genetic variants discovery was performed in a quantitative trait loci (QTL) region which was previously associated with abdominal fat weight and percentage in chicken chromosome 3 (GGA3) between the microsatellite markers LEI0161 and ADL0371 (33,595,706-42,632,651 bp). SAMtools software was used to detect 136,054 unique SNPs and 15,496 unique INDELs for the 18 chickens, and after quality filtration 92,518 unique SNPs and 9,298 unique INDELs were retained. One list of 77 genes was analised and genes related to lipid metabolism were searched. Variants located in coding region (386 SNPs and 15 INDELs) were identified and associated with important metabolic pathways. Loss of functional variants in the genes LOC771163, EGLN1, GNPAT, FAM120B, THBS2 and GGPS1 may be responsible for the QTL associated with fat deposition in chicken.

Oenococcus oeni est la principale espèce de bactérie lactique d’intérêt oenologique, elle réalise la plupart des fermentations malolactiques. Les souches d’O. oeni ont souvent été étudiées dans le but de sélectionner des levains malolactiques. Ces souches possèdent des caractéristiques génétiques, et phénotypiques variées. Néanmoins, l’utilisation de différentes méthodes de typage n’a pas permis à ce jour d’obtenir une image exhaustive de la diversité oenologique de cette espèce. L’intérêt grandissant des viticulteurs pour mieux maitriser les FML spontanées nécessite de mieux connaitre cette diversité.La population de souches indigènes d’O. oeni présentes dans les FML de différentes régions a été étudiée, pour tenter d’obtenir une image plus complète de la diversité de cette espèce et savoir s’il serait pertinent de sélectionner des souches de régions ou d’exploitations. L’analyse d’un très grand nombre de vins a mis en évidence la présence de souches spécifiques aux régions, appellations, produits et exploitations étudiées. Un génotypage à l’aide de SNP a permis de les classer dans les groupes génétiques déjà connu et a confirmé l’existence de groupes spécifiques à un type de produit. Certaines de ces groupes rassemblent des souches présentant des comportements phénotypiques et des capacités fermentaires similaires. En complément de l’analyse de diversité, des essais ont été menés pour proposer des protocoles de production de souches et d’utilisation de lies pour améliorer la réalisation des FML spontanées. L’ensemble de ces travaux soulignent la grande diversité génétique de l’espèce O. oeni, l’étude des souches spécifiques de type de vin pourrait aider à comprendre son adaptation à cet environnement. / Oenococcus oeni is the main species of lactic acid bacteria of oenological interest, it performs most of malolactic fermentation. O. oeni strains have often been studied to select malolactic starters. These strains have various genetic and phenotypic characteristics. However, the use of different typing methods failed so far to obtain a complete picture of the enological diversity of this species. The growing interest of winegrowers to better control the spontaneous requires a better knowledge of this diversity.The population of indigenous O. oeni strains present during MLF in different regions has been studied in an attempt to obtain a more complete picture of the diversity of the species and to know whether it would be appropriate to select strains of regions or wineries. The analysis of a large number of wines showed the presence of strains specific to wineproducing areas, different kind of wines, and wineries. SNP Genotyping allowed us to classify these strains in the already known genetic groups and confirmed the existence of specific groups to a specific kind of product. Some of these strains belonging to the same specific genetic groups showed similar behavior and technological properties. In addition to the diversity analysis, trials of production of strains and use of lees to ameliorate the MLF have been done to improve the achievement of spontaneous MLF. Taken together, these studies emphasize the high genetic diversity of the species O. oeni, the study of specific strains of type of wine could help understand the adaptation of this species to this environment.

Background: Imputation of partially missing or unobserved genotypes is an indispensable tool for SNP data analyses. However, research and understanding of the impact of initial SNP-data quality control on imputation results is still limited. In this paper, we aim to evaluate the effect of different strategies of pre-imputation quality filtering on the performance of the widely used imputation algorithms MaCH and IMPUTE. Results: We considered three scenarios: imputation of partially missing genotypes with usage of an external reference panel, without usage of an external reference panel, as well as imputation of ompletely un-typed SNPs using an external reference panel. We first created various datasets applying different SNP quality filters and masking certain percentages of randomly selected high-quality SNPs. We imputed these SNPs and compared the results between the different filtering scenarios by using established and newly proposed measures of imputation quality. While the established measures assess certainty of imputation results, our newly proposed measures focus on the agreement with true genotypes. These measures showed that pre-imputation SNP-filtering might be detrimental regarding imputation quality. Moreover, the strongest drivers of imputation quality were in general the burden of missingness and the number of SNPs used for imputation. We also found that using a reference panel always improves imputation quality of partially missing genotypes. MaCH performed slightly better than IMPUTE2 in most of our scenarios. Again, these results were more pronounced when using our newly defined measures of imputation quality. Conclusion: Even a moderate filtering has a detrimental effect on the imputation quality. Therefore little or no SNP filtering prior to imputation appears to be the best strategy for imputing small to moderately sized datasets. Our results also showed that for these datasets, MaCH performs slightly better than IMPUTE2 in most scenarios at the cost of increased computing time.