In the last century, advanced breeding methods have increased the rate of genetic gain in cattle but, with a few exceptions, genes and molecular functions underlying phenotypic variation are still largely unknown. In this thesis, the bovine genome was studied with high-throughput technologies using established and innovative procedures to search for genes controlling complex traits and support bovine breeding. In the first part a medium density marker panel was used to detect selection signatures shared by dairy or by beef breeds, identify candidate genes for specific production aptitudes, and genomic regions associated to production traits in dairy cattle. Genome wide association was run using a classic regression and an innovative gene-centric method. Regions and genes significantly associated to milk traits were specific for each breed. In a second part, data from exome sequences and high-density marker panels were combined to identify deleterious mutations in Italian Holstein. Different approaches were combined to filter and prioritize genetic variants. A set of candidate deleterious genes were found, that control basic biological mechanisms such as development and fertility. State of the art bioinformatics tools were used in these investigations and, whenever necessary, new pipelines and approaches were developed.
Nel corso dell’ultimo secolo, i programmi di miglioramento genetico hanno portato a notevoli progressi nelle razze bovine nonostante le conoscenze scarse o assenti relative ai geni coinvolti e alle loro funzioni. In questa tesi il genoma bovino è stato studiato con tecnologie massive, impiegando metodiche d’analisi sia tradizionali sia innovative per identificare i geni che controllano i fenotipi complessi e dare supporto al sistema allevatoriale. Nella prima parte del lavoro pannelli SNP a media densità sono stati utilizzati per l’individuazione di ”selection signature” condivise tra razze bovine da latte o da carne, identificando geni candidati specifici per l’attitudine produttiva, e di regioni associate ai fenotipi produttivi in razze da latte. L’associazione è stata effettuata sia con una regressione classica sia con un approccio “gene-centrico” innovativo. Regioni e geni associati significativamente ai fenotipi legati alla produzione lattea sono risultati essere razza specifici. Nella seconda parte, i dati dal sequenziamento dell’esoma e da pannelli SNP ad alta densità sono stati combinati per identificare mutazioni deleterie nella razza Frisona. Diversi approcci sono stati combinati per filtrare e ordinare le varianti genetiche. Alcuni geni che controllano meccanismi biologici di base, quali la fertilità e lo sviluppo, sono stati identificati come candidati ad essere deleteri. Per queste indagini sono stati utilizzati alcuni strumenti bioinformatici già disponibili e, quando necessario, sono stati sviluppati nuovi approcci e procedure.
MILANESI, MARCO, HIGH-THROUGHPUT SEQUENCING TECHNOLOGIES AND GENOMICS: INSIGHTS INTO THE BOVINE SPECIES, AJMONE MARSAN, PAOLO, BOMBA, LORENZO, NICOLAZZI, EZEQUIEL LUIS, CAPOMACCIO, STEFANO, Università Cattolica del Sacro Cuore Piacenza:Ciclo XXVII [https://hdl.handle.net/10807/286469]
HIGH-THROUGHPUT SEQUENCING TECHNOLOGIES AND GENOMICS: INSIGHTS INTO THE BOVINE SPECIES
Milanesi, Marco
2015
Abstract
In the last century, advanced breeding methods have increased the rate of genetic gain in cattle but, with a few exceptions, genes and molecular functions underlying phenotypic variation are still largely unknown. In this thesis, the bovine genome was studied with high-throughput technologies using established and innovative procedures to search for genes controlling complex traits and support bovine breeding. In the first part a medium density marker panel was used to detect selection signatures shared by dairy or by beef breeds, identify candidate genes for specific production aptitudes, and genomic regions associated to production traits in dairy cattle. Genome wide association was run using a classic regression and an innovative gene-centric method. Regions and genes significantly associated to milk traits were specific for each breed. In a second part, data from exome sequences and high-density marker panels were combined to identify deleterious mutations in Italian Holstein. Different approaches were combined to filter and prioritize genetic variants. A set of candidate deleterious genes were found, that control basic biological mechanisms such as development and fertility. State of the art bioinformatics tools were used in these investigations and, whenever necessary, new pipelines and approaches were developed.File | Dimensione | Formato | |
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