Analysis of the pig genome for the identification of genomic regions affecting production traits

Schiavo, Giuseppina (2015) Analysis of the pig genome for the identification of genomic regions affecting production traits, [Dissertation thesis], Alma Mater Studiorum Università di Bologna. Dottorato di ricerca in Scienze e tecnologie agrarie, ambientali e alimentari, 27 Ciclo. DOI 10.6092/unibo/amsdottorato/6919.
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The aim of this work was to identify markers associated with production traits in the pig genome using different approaches. We focused the attention on Italian Large White pig breed using Genome Wide Association Studies (GWAS) and applying a selective genotyping approach to increase the power of the analyses. Furthermore, we searched the pig genome using Next Generation Sequencing (NSG) Ion Torrent Technology to combine selective genotyping approach and deep sequencing for SNP discovery. Other two studies were carried on with a different approach. Allele frequency changes for SNPs affecting candidate genes and at Genome Wide level were analysed to identify selection signatures driven by selection program during the last 20 years. This approach confirmed that a great number of markers may affect production traits and that they are captured by the classical selection programs. GWAS revealed 123 significant or suggestively significant SNP associated with Back Fat Thickenss and 229 associated with Average Daily Gain. 16 Copy Number Variant Regions resulted more frequent in lean or fat pigs and showed that different copies of those region could have a limited impact on fat. These often appear to be involved in food intake and behavior, beside affecting genes involved in metabolic pathways and their expression. By combining NGS sequencing with selective genotyping approach, new variants where discovered and at least 54 are worth to be analysed in association studies. The study of groups of pigs undergone to stringent selection showed that allele frequency of some loci can drastically change if they are close to traits that are interesting for selection schemes. These approaches could be, in future, integrated in genomic selection plans.

Tipologia del documento
Tesi di dottorato
Schiavo, Giuseppina
Dottorato di ricerca
Scuola di dottorato
Scienze agrarie
Settore disciplinare
Settore concorsuale
Parole chiave
Genome Wide Association Study, Back Fat Thickness, Average Daily Gain, SNP Discovery, Copy Number Variations, Production traits
Data di discussione
16 Aprile 2015

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