Identification and characterisation of de novo germline structural variants in two commercial pig lines using trio-based whole genome sequencing.

BACKGROUND: De novo mutations arising in the germline are a source of genetic variation and their discovery broadens our understanding of genetic disorders and evolutionary patterns. Although the number of de novo single nucleotide variants (dnSNVs) has been studied in a number of species, relatively little is known about the occurrence of de novo structural variants (dnSVs). In this study, we investigated 37 deeply sequenced pig trios from two commercial lines to identify dnSVs present in the offspring. The identified dnSVs were characterised by identifying their parent of origin, their functional annotations and characterizing sequence homology at the breakpoints. RESULTS: We identified four swine germline dnSVs, all located in intronic regions of protein-coding genes. Our conservative, first estimate of the swine germline dnSV rate is 0.108 (95% CI 0.038-0.255) per generation (one dnSV per nine offspring), detected using short-read sequencing. Two detected dnSVs are clusters of mutations. Mutation cluster 1 contains a de novo duplication, a dnSNV and a de novo deletion. Mutation cluster 2 contains a de novo deletion and three de novo duplications, of which one is inverted. Mutation cluster 2 is 25 kb in size, whereas mutation cluster 1 (197 bp) and the other two individual dnSVs (64 and 573 bp) are smaller. Only mutation cluster 2 could be phased and is located on the paternal haplotype. Mutation cluster 2 originates from both micro-homology as well as non-homology mutation mechanisms, where mutation cluster 1 and the other two dnSVs are caused by mutation mechanisms lacking sequence homology. The 64 bp deletion and mutation cluster 1 were validated through PCR. Lastly, the 64 bp deletion and the 573 bp duplication were validated in sequenced offspring of probands with three generations of sequence data. CONCLUSIONS: Our estimate of 0.108 dnSVs per generation in the swine germline is conservative, due to our small sample size and restricted possibilities of dnSV detection from short-read sequencing. The current study highlights the complexity of dnSVs and shows the potential of breeding programs for pigs and livestock species in general, to provide a suitable population structure for identification and characterisation of dnSVs.

Accounting for genetic architecture in single- and multipopulation genomic prediction using weights from genomewide association studies in pigs.

We studied the effect of including GWAS results on the accuracy of single- and multipopulation genomic predictions. Phenotypes (backfat thickness) and genotypes of animals from two sire lines (SL1, n = 1146 and SL3, n = 1264) were used in the analyses. First, GWAS were conducted for each line and for a combined data set (both lines together) to estimate the genetic variance explained by each SNP. These estimates were used to build matrices of weights (D), which was incorporated into a GBLUP method. Single population evaluated with traditional GBLUP had accuracies of 0.30 for SL1 and 0.31 for SL3. When weights were employed in GBLUP, the accuracies for both lines increased (0.32 for SL1 and 0.34 for SL3). When a multipopulation reference set was used in GBLUP, the accuracies were higher (0.36 for SL1 and 0.32 for SL3) than in single-population prediction. In addition, putting together the multipopulation reference set and the weights from the combined GWAS provided even higher accuracies (0.37 for SL1, and 0.34 for SL3). The use of multipopulation predictions and weights estimated from a combined GWAS increased the accuracy of genomic predictions.

Genome-wide association study reveals regions associated with gestation length in two pig populations.

Reproduction traits, such as gestation length (GLE), play an important role in dam line breeding in pigs. The objective of our study was to identify single nucleotide polymorphisms (SNPs) that are associated with GLE in two pig populations. Genotypes and deregressed breeding values were available for 2081 Dutch Landrace-based (DL) and 2301 Large White-based (LW) pigs. We identified two QTL regions for GLE, one in each population. For DL, three associated SNPs were detected in one QTL region spanning 0.52 Mbp on Sus scrofa chromosome (SSC) 2. For LW, four associated SNPs were detected in one region of 0.14 Mbp on SSC5. The region on SSC2 contains the heparin-binding EGF-like growth factor (HBEGF) gene, which promotes embryo implantation and has been described to be involved in embryo survival throughout gestation. The associated SNP can be used for marker-assisted selection in the studied populations, and further studies of the HBEGF gene are warranted to investigate its role in GLE.

Accuracy of genome-enabled prediction exploring purebred and crossbred pig populations.

Pig breeding companies keep relatively small populations of pure sire and dam lines that are selected to improve the performance of crossbred animals. This design of the pig breeding industry presents challenges to the implementation of genomic selection, which requires large data sets to obtain highly accurate genomic breeding values. The objective of this study was to evaluate the impact of different reference sets (across population and multipopulation) on the accuracy of genomic breeding values in 3 purebred pig populations and to assess the potential of using crossbreed performance in genomic prediction. Data consisted of phenotypes and genotypes on animals from 3 purebred populations (sire line [SL] 1, = 1,146; SL2, = 682; and SL3, = 1,264) and 3 crossbred pig populations (Terminal cross [TER] 1, = 183; TER2, = 106; and TER3, = 177). Animals were genotyped using the Illumina Porcine SNP60 Beadchip. For each purebred population, within-, across-, and multipopulation predictions were considered. In addition, data from the paternal purebred populations were used as a reference set to predict the performance of crossbred animals. Backfat thickness phenotypes were precorrected for fixed effects and subsequently included in the genomic BLUP model. A genomic relationship matrix that accounted for the differences in allele frequencies between lines was implemented. Accuracies of genomic EBV obtained within the 3 different sire lines varied considerably. For within-population prediction, SL1 showed higher values (0.80) than SL2 (0.61) and SL3 (0.67). Multipopulation predictions had accuracies similar to within-population accuracies for the validation in SL1. For SL2 and SL3, the accuracies of multipopulation prediction were similar to the within-population prediction when the reference set was composed by 900 animals (600 of the target line plus 300 of another line). For across-population predictions, the accuracy was mostly close to zero. The accuracies of predicting crossbreed performance were similar for the 3 different crossbred populations (ranging from 0.25 to 0.29). In summary, the differences in accuracy of the within-population scenarios may be due to line divergences in heritability and genetic architecture of the trait. Within- and multipopulation predictions yield similar accuracies. Across-population prediction accuracy was negligible. The moderate accuracy of prediction of crossbreed performance appears to be a result of the relationship between the crossbreed and its parental lines.

A genome-wide association study reveals a novel candidate gene for sperm motility in pigs.

Sperm motility is one of the most widely used parameters in order to evaluate boar semen quality. However, this trait can only be measured after puberty. Thus, the use of genomic information appears as an appealing alternative to evaluate and improve selection for boar fertility traits earlier in life. With this study we aimed to identify SNPs with significant association with sperm motility in two different commercial pig populations and to identify possible candidate genes within the identified QTL regions. We performed a single-SNP genome-wide association study using genotyped animals from a Landrace-based (L1) and a Large White-based (L2) pig populations. For L1, a total of 602 animals genotyped for 42,551 SNPs were used in the association analysis. For L2, a total of 525 animals genotyped for 40,890 SNPs were available. After the association analysis, a false discovery rate q-value ≤0.05 was used as the threshold for significant association. No SNPs were significantly associated with sperm motility in L1, while six SNPs on Sus scrofa chromosome 1 (position 117.26-119.56Mb) were significant in L2. The mitochondrial methionyl-tRNA formyltransferase (MTFMT) gene, which affects translation efficiency of proteins in sperm cells, was identified as a putative candidate gene. The significant markers identified in this study may be useful to enhance the genetic improvement of sperm motility by selection of boars at an earlier age under a marker assisted selection strategy.

Asian low-androstenone haplotype on pig chromosome 6 does not unfavorably affect production and reproduction traits.

European pigs that carry Asian haplotypes of a 1.94-Mbp region on pig chromosome 6 have lower levels of androstenone, one of the two main compounds causing boar taint. The objective of our study was to examine potential pleiotropic effects of the Asian low-androstenone haplotypes. A single nucleotide polymorphism marker, rs81308021, distinguishes the Asian from European haplotypes and was used to investigate possible associations of androstenone with production and reproduction traits. Eight traits were available from three European commercial breeds. For the two sow lines studied, a favorable effect on number of teats was detected for the low-androstenone haplotype. In one of these sow lines, a favorable effect on number of spermatozoa per ejaculation was detected for the low-androstenone haplotype. No unfavorable pleiotropic effects were found, which suggests that selection for low-androstenone haplotypes within the 1.94 Mbp would not unfavorably affect the other eight relevant traits.

Linkage disequilibrium and haplotype block structure in six commercial pig lines.

Linkage disequilibrium (LD) across the genome is critical information for association studies and genomic selection because it determines the number of SNP that should be used for a successful association analysis and genomic selection. Linkage disequilibrium also influences the accuracy of genomic breeding values. Some studies have demonstrated that SNP in strong LD are organized into discrete blocks of haplotypes, which are separated by possibly hot spots of recombination. To reduce the number of markers needed to be genotyped for association mapping, a set of SNP can be selected that labels all haplotype blocks. We estimated the LD, calculated the average haplotype block size for 6 pig lines, and compared the block size between lines. Six commercial pig lines were genotyped using the Illumina PorcineSNP60 (number of markers M = 62,163) Genotyping BeadChip (Illumina Inc.); on average, a panel of 37,623 SNP with an average minor allelic frequency (MAF) of 0.283 was included in the analysis. The LD declined as a function of distance. All pig lines had an average r(2) above 0.3 for markers 100 to 150 apart. The estimated average block size was 394.885 kb, and blocks between 100 and 400 kb were most prominent (49.96%) in all lines. These results showed that the extent of LD in pigs is much larger than in the cattle population, in accordance with the genetic map length of pigs, which is much shorter than cattle. The evaluated lines have 2,640 to 3,037 blocks, covering 45% of the pig genome, on average. Differences in haplotype block size between lines were observed for some chromosomes (i.e., SSC 3, 5, 7, 13, 14, and 18), which provide a direction for future studies of haplotype block conservation or divergence across lines.

A single nucleotide polymorphism set for paternal identification to reduce the costs of trait recording in commercial pig breeding.

In animal breeding, recording of correct pedigrees is essential to achieve genetic progress. Markers on DNA are useful to verify the on-farm pedigree records (parental verification) but can also be used to assign parents retrospectively (parental identification). This approach could reduce the costs of recording for traits with low incidence, such as those related to diseases or mortality. In this study, SNP were used to assign the true sires of 368 purebred animals from a Duroc-based sire line and 140 crossbred offspring from a commercial pig population. Some of the sires were closely related. There were 3 full sibs and 17 half sibs among the true fathers and 4 full sibs and 35 half sibs among all putative fathers. To define the number of SNP necessary, 5 SNP panels (40, 60, 80, 100, and 120 SNP) were assembled from the Illumina PorcineSNP60 Beadchip (Illumina, San Diego, CA) based on minor allele frequency (>0.3), high genotyping call rate (≥90%), and equal spacing across the genome. For paternal identification considering only the 66 true sires in the data set, 60 SNP resulted in 100% correct assignment of the sire. By including additional putative sires (n = 304), 80 SNP were sufficient for 100% correct assignment of the sire. The following criteria were derived to identify the correct sire for the current data set: the logarithm of odds (LOD) score for assigning the correct sire was ≥5, the number of mismatches was ≤1, and the difference in the LOD score between the first and the second most likely sire was >5. If the correct sire was not present among all putative sires, the mean LOD for the most likely sire was close to zero or negative when using 100 SNP. More SNP would be needed for paternal identification if the number of putative sires increased and the degree of relatedness was greater than in the data set used here. The threshold for the number of mismatches can be adjusted according to the practical situation to account for the trade-off between false negatives and false positives. The latter can be avoided efficiently, ensuring that the correct father is being sampled. Nevertheless, a restriction on the number of putative sires is advisable to reduce the risk of assigning close relatives.

Inter-laboratory comparison of methods to measure androstenone in pork fat.

Today, different analytical methods are used by different laboratories to quantify androstenone in fat tissue. This study shows the comparison of methods used routinely in different laboratories for androstenone quantification: Time-resolved fluoroimmunoassay in Norwegian School of Veterinary Science (NSVS; Norway), gas chromatography coupled to mass spectrometry in Co-operative Central Laboratory (CCL; The Netherlands) and in Institut de Recerca i Tecnologia Agroalimentàries (IRTA; Spain), and high-pressure liquid chromatography in Agroscope Liebefeld-Posieux Research Station (ALP; Switzerland). In a first trial, a set of adipose tissue (AT) samples from 53 entire males was sent to CCL, IRTA and NSVS for determination of androstenone concentration. The average androstenone concentration (s.d.) was 2.47 (2.10) µg/g at NSVS, 1.31 (0.98) µg/g at CCL and 0.62 (0.52) µg/g at IRTA. Despite the large differences in absolute values, inter-laboratory correlations were high, ranging from 0.82 to 0.92. A closer look showed differences in the preparation step. Indeed, different matrices were used for the analysis: pure fat at NSVS, melted fat at CCL and AT at IRTA. A second trial was organised in order to circumvent the differences in sample preparation. Back fat samples from 10 entire males were lyophilised at the ALP labortary in Switzerland and were sent to the other laboratories for androstenone concentration measurement. The average concentration (s.d.) of androstenone in the freeze-dried AT samples was 0.87 (0.52), 1.03 (0.55), 0.84 (0.46) and 0.99 (0.67) µg/g at NSVS, CCL, IRTA and ALP, respectively, and the pairwise correlations between laboratories ranged from 0.92 to 0.97. Thus, this study shows the influence of the different sample preparation protocols, leading to major differences in the results, although still allowing high inter-laboratory correlations. The results further highlight the need for method standardisation and inter-laboratory ring tests for the determination of androstenone. This standardisation is especially relevant when deriving thresholds of consumer acceptance, whereas the ranking of animals for breeding purposes will be less affected due to the high correlations between methods.

In silico identification and mapping of microsatellite markers on sus scrofa chromosome 4.

Marker density of a QTL region on pig chromosome 4 was increased. New microsatellites were identified by in silico mining of BAC-end and genomic shotgun sequences. Among 8,784 BAC-end sequences predicted within the region, 148 microsatellites were identified. In addition, 27,450 CA/TG repeats were identified within the genomic shotgun sequences, of which 157 were most likely located on SSC4q. A selection of 61 new microsatellites was mapped, together with previously mapped markers. The results showed that the human-pig comparative map in combination with BAC-end and genomic sequence resources provides an excellent source for a highly efficient and targeted development of markers.

Associations of functional candidate genes derived from gene-expression profiles of prenatal porcine muscle tissue with meat quality and muscle deposition.

Ten genes (ANK1, bR10D1, CA3, EPOR, HMGA2, MYPN, NME1, PDGFRA, ERC1, TTN), whose candidacy for meat-quality and carcass traits arises from their differential expression in prenatal muscle development, were examined for association in 1700 performance-tested fattening pigs of commercial purebred and crossbred herds of Duroc, Pietrain, Pietrain x (Landrace x Large White), Duroc x (Landrace x Large White) as well as in an experimental F(2) population based on a reciprocal cross of Duroc and Pietrain. Comparative sequencing revealed polymorphic sites segregating across commercial breeds. Genetic mapping results corresponded to pre-existing assignments to porcine chromosomes or current human-porcine comparative maps. Nine of these genes showed association with meat-quality and carcass traits at a nominal P-value of < or = 0.05; PDGFRA revealed no association reaching the P < or = 0.05 threshold. In particular, HMGA2, CA3, EPOR, NME1 and TTN were associated with meat colour, pH and conductivity of loin 24 h postmortem; CA3 and MYPN exhibited association with ham weight and lean content (FOM) respectively at P-values of < 0.003 that correspond to false discovery rates of < 0.05. However, none of the genes showed significant associations for a particular trait across all populations. The study revealed statistical-genetic evidence for association of the functional candidate genes with traits related to meat quality and muscle deposition. The polymorphisms detected are not likely causal, but markers were identified that are in linkage disequilibrium with causal genetic variation within particular populations.

Variance component analysis of quantitative trait loci for pork carcass composition and meat quality on SSC4 and SSC11.

In a previous study, QTL for carcass composition and meat quality were identified in a commercial finisher cross. The main objective of the current study was to confirm and fine map the QTL on SSC4 and SSC11 by genotyping an increased number of individuals and markers and to analyze the data using a combined linkage and linkage disequilibrium analysis method. A modified version of the method excludes linkage disequilibrium information from the analysis, enabling the comparison of results based on linkage information only or results based on combined linkage and linkage disequilibrium information. Nine additional paternal half-sib families were genotyped for 18 markers, resulting in a total of 1,855 animals genotyped for 15 and 13 markers on SSC4 and SSC11, respectively. The QTL affecting meat color on SSC4 was confirmed, whereas the QTL affecting LM weight could not be confirmed. The combined linkage and linkage disequilibrium analysis resulted in the identification of new significant effects for 14 traits on the 2 chromosomes. Heritabilities of the QTL effects ranged from 1.8 to 13.2%. The analysis contributed to a more accurate positioning of QTL and further characterized their phenotypic effect. However, results showed that even greater marker densities are required to take full advantage of linkage disequilibrium information and to identify haplotypes associated with favorable QTL alleles.

Genetic diversity analysis using lowly polymorphic dominant markers: the example of AFLP in pigs.

DNA markers are commonly used for large-scale evaluation of genetic diversity in farm animals, as a component of the management of animal genetic resources. AFLP markers are useful for such studies as they can be generated relatively simply; however, challenges in analysis arise from their dominant scoring and the low level of polymorphism of some markers. This paper describes the results obtained with a set of AFLP markers in a study of 59 pig breeds. AFLP fingerprints were generated using four primer combinations (PC), yielding a total of 148 marker loci, and average harmonic mean of breed sample size was 37.3. The average proportion of monomorphic populations was 63% (range across loci: 3%-98%). The moment-based method of Hill and Weir (2004, Mol Ecol 13:895-908) was applied to estimate gene frequencies, gene diversity (F(ST)), and Reynolds genetic distances. A highly significant average F(ST) of 0.11 was estimated, together with highly significant PC effects on gene diversity. The variance of F(ST) across loci also significantly exceeded the variance expected under the hypothesis of AFLP neutrality, strongly suggesting the sensitivity of AFLP to selection or other forces. Moment estimates were compared to estimates derived from the square root estimation of gene frequency, as currently applied for dominant markers, and the biases incurred in the latter method were evaluated. The paper discusses the hypotheses underlying the moment estimations and various issues relating to the biallelic, dominant, and lowly polymorphic nature of this set of AFLP markers and to their use as compared to microsatellites for measuring genetic diversity.

Genetic diversity within and between European pig breeds using microsatellite markers.

An important prerequisite for a conservation programme is a comprehensive description of genetic diversity. The aim of this study was to use anonymous genetic markers to assess the between- and the within-population components of genetic diversity for European pig breeds at the scale of the whole continent using microsatellites. Fifty-eight European pig breeds and lines were analysed including local breeds, national varieties of international breeds and commercial lines. A sample of the Chinese Meishan breed was also included. Eleven additional breeds from a previous project were added for some analyses. Approximately 50 individuals per breed were genotyped for a maximum of 50 microsatellite loci. Substantial within-breed variability was observed, with the average expected heterozygosity and observed number of alleles per locus being 0.56 [range 0.43-0.68] and 4.5 respectively. Genotypic frequencies departed from Hardy-Weinberg expectations (P < 0.01) in 15 European populations, with an excess of homozygotes in 12 of them. The European breeds were on average genetically very distinct, with a Wright F(ST) index value of 0.21. The Neighbour-Joining tree drawn from the Reynolds distances among the breeds showed that the national varieties of major breeds and the commercial lines were mostly clustered around their breeds of reference (Duroc, Hampshire, Landrace, Large White and Piétrain). In contrast, local breeds, with the exception of the Iberian breeds, exhibited a star-like topology. The results are discussed in the light of various forces, which may have driven the recent evolution of European pig breeds. This study has consequences for the interpretation of biodiversity results and will be of importance for future conservation programmes.

Genetic diversity in European pigs utilizing amplified fragment length polymorphism markers.

The use of DNA markers to evaluate genetic diversity is an important component of the management of animal genetic resources. The Food and Agriculture Organisation of the United Nations (FAO) has published a list of recommended microsatellite markers for such studies; however, other markers are potential alternatives. This paper describes results obtained with a set of amplified fragment length polymorphism (AFLP) markers as part of a genetic diversity study of European pig breeds that also utilized microsatellite markers. Data from 148 AFLP markers genotyped across samples from 58 European and one Chinese breed were analysed. The results were compared with previous analyses of data from 50 microsatellite markers genotyped on the same animals. The AFLP markers had an average within-breed heterozygosity of 0.124 but there was wide variation, with individual markers being monomorphic in 3-98% of the populations. The biallelic and dominant nature of AFLP markers creates a challenge for their use in genetic diversity studies as each individual marker contains limited information and AFLPs only provide indirect estimates of the allelic frequencies that are needed to estimate genetic distances. Nonetheless, AFLP marker-based characterization of genetic distances was consistent with expectations based on breed and regional distributions and produced a similar pattern to that obtained with microsatellites. Thus, data from AFLP markers can be combined with microsatellite data for measuring genetic diversity.

Identification of quantitative trait loci for carcass composition and pork quality traits in a commercial finishing cross.

A QTL study for carcass composition and meat quality traits was conducted on finisher pigs of a cross between a synthetic Piétrain/Large White boar line and a commercial sow cross. The mapping population comprised 715 individuals evaluated for a total of 30 traits related to growth and fatness (4 traits), carcass composition (11 traits), and meat quality (15 traits). Offspring of 8 sires (n = 715) were used for linkage analysis and genotyped for 73 microsatellite markers covering 14 chromosomal regions representing approximately 50% of the pig genome. The regions examined were selected based on previous studies suggesting the presence of QTL affecting carcass composition or meat quality traits. Thirty-two QTL exceeding the 5% chromosome-wise significance level were identified. Among these, 5 QTL affecting 5 different traits were significant at the 1% chromosome-wise level. The greatest significance levels were found for a QTL affecting loin weight on SSC11 and a QTL with an effect on the Japanese color scale score of the loin on SSC4. About one-third of the identified QTL were in agreement with QTL previously reported. Results showed that QTL affecting carcass composition and meat quality traits segregated within commercial lines. Use of these results for marker-assisted selection offers opportunities for improving pork quality by within-line selection.

Genome scan reveals new coat color loci in exotic pig cross.

The porcine genome was scanned to identify loci affecting coat color in an experimental cross between the Meishan breed and Dutch commercial lines. Linkage was studied in 1181 F(2) animals for 132 microsatellite markers and seven binary coat color scores: White, Black spotting, Speckle, Gray, Black, and specific color phenotypes for head and legs. The analyses were performed using interval mapping under various models. The study confirmed the existence of coat color loci on chromosome 8 and chromosome 6. One additional locus affecting White was detected on chromosome 5, possibly representing the porcine equivalent of the steel factor. Two new loci affecting Black were detected on chromosome 2. One of these showed exclusive maternal expression and mapped to a region where imprinted genes have been reported. The effect of the binary coding was tested by additional analyses excluding the white animals (>50% of F(2) animals). This showed that Black spotting was strongly influenced by the locus on chromosome 6 and the other color phenotypes were mainly influenced by the locus on chromosome 8. Epistatic effects were found between the loci on chromosomes 6 and 8 for Black spotting. For Black color, all combinations among chromosomes 2, 6, and 8 showed epistatic effects.

Improving the comparative map of SSC2p-q13 by sample sequencing of BAC clones.

To improve the comparative map for pig chromosome 2 and increase the gene density on this chromosome, a porcine bacterial artificial chromosome (BAC) library was screened with 17 microsatellite markers and 18 genes previously assigned to pig chromosome 2. Fifty-one BAC clones located in the region of a maternally imprinted quantitative trait locus for backfat thickness (BFT) were identified. From these BACs 372 kb were sample sequenced. The average read length of a subclone was 442 basepair (bp). Contig assembly analysis showed that every bp was sequenced 1.28 times. Subsequently, sequences were compared with sequences in the nucleotide databases to identify homology with other mammalian sequences. Sequence identity was observed with sequences derived from 35 BACs. The average percentage identity with human sequences was 87.6%, with an average length of 143 bp. In total, sample sequencing of all BACs resulted in sequence identity with 29 human genes, 13 human expressed sequence tags (ESTs), 17 human genomic clones, one rat gene, one porcine gene and nine porcine ESTs. Eighteen genes located on human chromosome 11 and 19, and seven genes from other human locations, one rat gene and one porcine gene were assigned to pig chromosome 2 for the first time. The new genes were added to the radiation hybrid map at the same position as the locus from which the BAC that was sequenced was derived. In total 57 genes were placed on the radiation hybrid map of SSC2p-q13.

A whole-genome scan for quantitative trait loci affecting teat number in pigs.

A whole-genome scan was conducted using 132 microsatellite markers to identify chromosomal regions that have an effect on teat number. For this purpose, an experimental cross between Chinese Meishan pigs and five commercial Dutch pig lines was used. Linkage analyses were performed using interval mapping by regression under line cross models including a test for imprinting effects. The whole-genome scan revealed highly significant evidence for three quantitative trait loci (QTL) affecting teat number, of which two were imprinted. Paternally expressed (i.e., maternally imprinted) QTL were found on chromosomes 2 and 12. A Mendelian expressed QTL was found on chromosome 10. The estimated additive effects showed that, for the QTL on chromosomes 10 and 12, the Meishan allele had a positive effect on teat number, but, for the QTL on chromosome 2, the Meishan allele had a negative effect on teat number. This study shows that imprinting may play an important role in the expression of teat number.