BackgroundPigs were domesticated independently in Eastern and Western Eurasia early during the agricultural revolution, and have since been transported and traded across the globe. Here, we present a worldwide survey on 60K genome-wide single nucleotide polymorphism (SNP) data for 2093 pigs, including 1839 domestic pigs representing 122 local and commercial breeds, 215 wild boars, and 39 out-group suids, from Asia, Europe, America, Oceania and Africa. The aim of this study was to infer global patterns in pig domestication and diversity related to demography, migration, and selection.ResultsA deep phylogeographic division reflects the dichotomy between early domestication centers. In the core Eastern and Western domestication regions, Chinese pigs show differentiation between breeds due to geographic isolation, whereas this is less pronounced in European pigs. The inferred European origin of pigs in the Americas, Africa, and Australia reflects European expansion during the sixteenth to nineteenth centuries. Human-mediated introgression, which is due, in particular, to importing Chinese pigs into the UK during the eighteenth and nineteenth centuries, played an important role in the formation of modern pig breeds. Inbreeding levels vary markedly between populations, from almost no runs of homozygosity (ROH) in a number of Asian wild boar populations, to up to 20% of the genome covered by ROH in a number of Southern European breeds. Commercial populations show moderate ROH statistics. For domesticated pigs and wild boars in Asia and Europe, we identified highly differentiated loci that include candidate genes related to muscle and body development, central nervous system, reproduction, and energy balance, which are putatively under artificial selection.ConclusionsKey events related to domestication, dispersal, and mixing of pigs from different regions are reflected in the 60K SNP data, including the globalization that has recently become full circle since Chinese pig breeders in the past decades started selecting Western breeds to improve local Chinese pigs. Furthermore, signatures of ongoing and past selection, acting at different times and on different genetic backgrounds, enhance our insight in the mechanism of domestication and selection. The global diversity statistics presented here highlight concerns for maintaining agrodiversity, but also provide a necessary framework for directing genetic conservation. Electronic supplementary materialThe online version of this article (doi:10.1186/s12711-017-0345-y) contains supplementary material, which is available to authorized users.

The extent of linkage disequilibrium (LD) and effective population size in Finnish Landrace and Finnish Yorkshire pig populations were studied using a whole genome SNP panel (Illumina PorcineSNP60 BeadChip) and pedigree data. Genotypic data included 86 Finnish Landrace and 32 Finnish Yorkshire boars. Pedigree data included 608,138 Finnish Landrace 554,237 and Finnish Yorkshire pigs, and on average 15 ancestral generations were known for the reference animals, born in 2005 to 2009. The breeding animals of the 2 populations have been kept separate in the breeding programs. Based on the pedigree data, the current effective population size for Finnish Landrace is 91 and for Finnish Yorkshire 61. Linkage disequilibrium measures (D' and r(2)) were estimated for over 1.5 million pairs of SNP. Average r(2) for SNP 30 kb apart was 0.47 and 0.49 and for SNP 5 Mb apart 0.09 and 0.12 for Finnish Landrace and Finnish Yorkshire, respectively. Average LD (r(2)) between adjacent SNP in the Illumina PorcineSNP60 BeadChip was 0.43 (57% of the adjacent SNP pairs had r(2) > 0.2) for Finnish Landrace and 0.46 (60% of the adjacent SNP pairs had r(2) > 0.2) for Finnish Yorkshire, and average r(2) > 0.2 extended to 1.0 and 1.5 Mb for Finnish Landrace and Finnish Yorkshire, respectively. Effective population size estimates based on the decay of r(2) with distance were similar to those based on the pedigree data: 80 and 55 for Finnish Landrace and Finnish Yorkshire, respectively. Thus, the results indicate that the effective population size of Finnish Yorkshire is smaller than of Finnish Landrace and has a clear effect on the extent of LD. The current effective population size of both breeds is above the recommended minimum of 50 but may get smaller than that in the near future, if no action is taken to balance the inbreeding rate and selection response. Because a moderate level of LD extends over a long distance, selection based on whole genome SNP markers (genomic selection) is expected to be efficient for both breeds.

Type 2 diabetes (T2D) is a common, polygenic chronic disease with high heritability. The purpose of this whole-genome association study was to discover novel T2D-associated genes. We genotyped 500 familial cases and 497 controls with >300,000 HapMap-derived tagging single-nucleotide-polymorphism (SNP) markers. When a stringent statistical correction for multiple testing was used, the only significant SNP was at TCF7L2, which has already been discovered and confirmed as a T2D-susceptibility gene. For a replication study, we selected 10 SNPs in six chromosomal regions with the strongest association (singly or as part of a haplotype) for retesting in an independent case-control set including 2,573 T2D cases and 2,776 controls. The most significant replicated result was found at the AHI1-LOC441171 gene region.

QTL mapping experiments in plant breeding may involve multiple populations or pedigrees that are related through their ancestors. These known relationships have often been ignored for the sake of statistical analysis, despite their potential increase in power of mapping. We describe here a Bayesian method for QTL mapping in complex plant populations and reported the results from its application to a (previously analysed) potato data set. This Bayesian method was originally developed for human genetics data, and we have proved that it is useful for complex plant populations as well, based on a sensitivity analysis that was performed here. The method accommodates robustness to complex structures in pedigree data, full flexibility in the estimation of the number of QTL across multiple chromosomes, thereby accounting for uncertainties in the transmission of QTL and marker alleles due to incomplete marker information, and the simultaneous inclusion of non-genetic factors affecting the quantitative trait.

Single nucleotide polymorphism (SNP) data enable the estimation of inbreeding at the genome level. In this study, we estimated inbreeding levels for 19,075 Finnish Ayrshire cows genotyped with a low-density SNP panel (8K). The genotypes were imputed to 50K density, and after quality control, 39,144 SNPs remained for the analysis. Inbreeding coefficients were estimated for each animal based on the percentage of homozygous SNPs (F ), runs of homozygosity (F ) and pedigree (F ). Phenotypic records were available for 13,712 animals including non-return rate (NRR), number of inseminations (AIS) and interval from first to last insemination (IFL) for heifers and up to three parities for cows, as well as interval from calving to first insemination (ICF) for cows. Average F was 0.02, F 0.06 and F 0.63. A correlation of 0.71 was found between F and F , 0.66 between F and F and 0.94 between F and F . Pedigree-based inbreeding coefficients did not show inbreeding depression in any of the traits. However, when F or F was used as a covariate, significant inbreeding depression was observed; a 10% increase in F was associated with 5 days longer IFL0 and IFL1, 2 weeks longer IFL3 and 3 days longer ICF2 compared to non-inbred cows.