The dissection of complex traits of economic importance to the pig industry requires the availability of a significant number of genetic markers, such as single nucleotide polymorphisms (SNPs). This study was conducted to discover several hundreds of thousands of porcine SNPs using next generation sequencing technologies and use these SNPs, as well as others from different public sources, to design a high-density SNP genotyping assay. A total of 19 reduced representation libraries derived from four swine breeds (Duroc, Landrace, Large White, Pietrain) and a Wild Boar population and three restriction enzymes (AluI, HaeIII and MspI) were sequenced using Illumina's Genome Analyzer (GA). The SNP discovery effort resulted in the de novo identification of over 372K SNPs. More than 549K SNPs were used to design the Illumina Porcine 60K+SNP iSelect Beadchip, now commercially available as the PorcineSNP60. A total of 64,232 SNPs were included on the Beadchip. Results from genotyping the 158 individuals used for sequencing showed a high overall SNP call rate (97.5%). Of the 62,621 loci that could be reliably scored, 58,994 were polymorphic yielding a SNP conversion success rate of 94%. The average minor allele frequency (MAF) for all scorable SNPs was 0.274. Overall, the results of this study indicate the utility of using next generation sequencing technologies to identify large numbers of reliable SNPs. In addition, the validation of the PorcineSNP60 Beadchip demonstrated that the assay is an excellent tool that will likely be used in a variety of future studies in pigs.

Artificial selection has caused rapid evolution in domesticated species. The identification of selection footprints across domesticated genomes can contribute to uncover the genetic basis of phenotypic diversity. Genome wide footprints of pig domestication and selection were identified using massive parallel sequencing of pooled reduced representation libraries (RRL) representing ∼2% of the genome from wild boar and four domestic pig breeds (Large White, Landrace, Duroc and Pietrain) which have been under strong selection for muscle development, growth, behavior and coat color. Using specifically developed statistical methods that account for DNA pooling, low mean sequencing depth, and sequencing errors, we provide genome-wide estimates of nucleotide diversity and genetic differentiation in pig. Widespread signals suggestive of positive and balancing selection were found and the strongest signals were observed in Pietrain, one of the breeds most intensively selected for muscle development. Most signals were population-specific but affected genomic regions which harbored genes for common biological categories including coat color, brain development, muscle development, growth, metabolism, olfaction and immunity. Genetic differentiation in regions harboring genes related to muscle development and growth was higher between breeds than between a given breed and the wild boar. These results, suggest that although domesticated breeds have experienced similar selective pressures, selection has acted upon different genes. This might reflect the multiple domestication events of European breeds or could be the result of subsequent introgression of Asian alleles. Overall, it was estimated that approximately 7% of the porcine genome has been affected by selection events. This study illustrates that the massive parallel sequencing of genomic pools is a cost-effective approach to identify footprints of selection.

Linkage disequilibrium (LD) may reveal much about domestication and breed history. An investigation was conducted, to analyze the extent of LD, haploblock partitioning, and haplotype diversity within haploblocks across several pig breeds from China and Europe and in European wild boar. In total, 371 single-nucleotide-polymorphisms located in three genomic regions were genotyped. The extent of LD differed significantly between European and Chinese breeds, extending up to 2 cM in Europe and up to 0.05 cM in China. In European breeds, LD extended over large haploblocks up to 400 kb, whereas in Chinese breeds the extent of LD was smaller and generally did not exceed 10 kb. The European wild boar showed an intermediate level of LD between Chinese and European breeds. In Europe, the extent of LD also differed according to genomic region. Chinese breeds showed a higher level of haplotype diversity and shared high levels of frequent haplotypes with Large White, Landrace, and Duroc. The extent of LD differs between both centers of pig domestication, being higher in Europe. Two hypotheses can explain these findings. First, the European ancestral stock had a higher level of LD. Second, modern breeding programs increased the extent of LD in Europe and caused differences of LD between genomic regions. Large White, Landrace, and Duroc showed evidence of past introgression from Chinese breeds.

Livestock conservation practice is changing rapidly in light of policy, climate change and market demands. The last decade saw a step change in technological and analytical approaches to define, manage and conserve Farm Animal Genomic Resources (FAnGR). These changes pose challenges for FAnGR conservation in terms of technological continuity, analytical capacity and the methodologies needed to exploit new, multidimensional data. The ESF Genomic Resources program final conference addressed these problems attempting to contribute to the development of the research and policy agenda for the next decade. We broadly identified four areas related to methodological and analytical challenges, data management and conservation. The overall conclusion is that there is a need for the use of current state-of-the-art tools to characterise the state of genomic resources in non-commercial and local breeds. The livestock genomic sector, which has been relatively well-organised in applying such methodologies so far, needs to make a concerted effort in the coming decade to enable to the democratisation of the powerful tools that are now at its disposal, and to ensure that they are applied in the context of breed conservation as well as development.

Although the Illumina 1 G Genome Analyzer generates billions of base pairs of sequence data, challenges arise in sequence selection due to the varying sequence quality. Therefore, in the framework of the International Porcine SNP Chip Consortium, this pilot study aimed to evaluate the impact of the quality level of the sequenced bases on mapping quality and identification of true SNPs on a large scale.