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Interferon regulatory factor 7 (IRF7), as a key regulator of type I interferon response, plays an important role during innate response against viral infection. Although well conserved across species, the structure of IRF7 and its function during parasite infection are not well documented in farm animals, such as the pig. To bridge this gap, we have determined the porcine IRF7 gene structure and identified two intronic single nucleotide polymorphisms (SNPs), SNP g.748G>C and SNP g.761A>G, in commercial pig breeds. The distribution of SNP g.761A>G in multiple breeds suggested that it was in Hardy-Weinberg equilibrium and allowed us to map it at the top of SSC2. We found that during Sarcocystis miescheriana infection, the G allele was associated with high lymphocyte levels (P G enhances the transactivation activity of IRF7, possibly by improving IRF7 transcript splicing of intron-3. These findings would suggest that IRF7, as a transcriptional regulator, is involved in the defence mechanism against a larger spectrum of pathogens, and in more host species, than initially anticipated.

Clinical-chemical traits are essential parameters to quantify the health status of individuals and herds, but the knowledge about their genetic architecture is sparse, especially in swine. We have recently described three QTL for serum aspartate aminotransferase activity (sAST), and one of these maps to a region on SSC14 where the aspartate aminotransferase coding gene GOT1 is located. This QTL was only apparent under the acute burden of a model disease. The aim of the present study was to characterize GOT1 as a candidate gene and to test the effects of different GOT1 SNPs as potential quantitative trait nucleotides (QTNs) for sAST. Nine SNPs within GOT1 were identified, and SNP c.-793C>G significantly increased the QTL effects and narrowed the confidence interval from 90 to 15 cM. Additionally, we found a significant association of SNP c.-793C>G in a commercial outbred line, but with reversed phase. We conclude that GOT1 is a putative candidate gene for the sAST QTL on SSC14, and that SNP c.-793C>G is close to the responsible QTN.

Summary Behavioural indices in vertebrates are under genetic control at least to some extent. In spite of significant behavioural problems in farm animals, information on the genetic background of behaviour is sparse. The aim of this study was to map QTL for behavioural indices in swine under healthy conditions and after infection with Sarcocystis miescheriana, as behaviour can be significantly influenced by disease. This well-described parasite model subsequently leads to acute (day 14 p.i.), subclinical (day 28 p.i.) and chronic disease (day 42 p.i.), allowing the study and comparison of the behaviour of pigs under four different states of health or disease. The study was based on a well-described Pietrain/Meishan F2 family that has recently allowed the detection of QTL for disease resistance. We have mapped six genome-wide significant and 24 chromosome-wide significant QTL for six behavioural indices in swine. Six of these QTL (i.e. 20% of total QTL) showed effects on behavioural traits of the healthy pigs (day 0). Some of them (QTL on SSC11 and 18) lost influence on behavioural activities during disease, while the effects of others (QTL on SSC5, SSC8) partly remained during the whole experiment, although with different effects on the distinct behavioural indices. The disease model has been of high relevance to detect effects of gene loci on behavioural indices. Considering the importance of segregating alleles and environmental conditions that allow the identification of the phenotype, we conclude that there are indeed QTL with interesting effects on behavioural indices in swine.

Maintaining pH and blood gases in a narrow range is essential to sustain normal biochemical reactions. Decreased oxygenation, poor tissue perfusion, disturbance to CO(2) expiration, and shortage of HCO(3)(-) can lead to metabolic acidosis. This is a common situation in swine, and originates from a broad range of medical conditions. pH and blood gases appear to be under genetic control, and populations with physiological traits closer to the pathological thresholds may be more susceptible to developing pathological conditions. However, little is known about the genetic basis of such traits. We have therefore estimated phenotypic and genetic variability and identified quantitative trait loci (QTL) for pH and blood gases in blood samples from 139 F(2) pigs from the Meishan/Pietrain family. Samples were taken before and after challenge with Sarcocystis miescheriana, a protozoan parasite of muscle. Twenty-seven QTL influencing pH and blood gases were identified on nine chromosomes. Five of the QTL were significant on a genome-wide level; 22 QTL were significant on a chromosome-wide level. QTL for pH-associated traits have been mapped to SSC3, 18 and X. QTL associated with CO(2) have been detected on SSC6, 7, 8 and 9, and QTL associated with O(2) on SSC2 and SSC8. QTL showed specific health/disease patterns that were related to the physiological state of the pigs from day 0, to acute disease (day 14), convalescence (day 28) and chronic disease (day 42). The results demonstrate that pH and blood gases are influenced by multiple chromosomal areas, each with relatively small effects.

Summary Haematological traits are essential diagnostic parameters in veterinary practice but knowledge on the genetic architecture controlling variability of erythroid traits is sparse, especially in swine. To identify QTL for erythroid traits in the pig, haematocrit (HCT), haemoglobin (HB), erythrocyte counts (RBC) and mean corpuscular haemoglobin content (MCHC) were measured in 139 F2 pigs from a Meishan/Pietrain family, before and after challenge with the protozoan pathogen Sarcocystis miescheriana. The pigs passed through three stages representing acute disease, reconvalescence and chronic disease. Forty-three single QTL controlling erythroid traits were identified on 16 chromosomes. Twelve of the QTL were significant at the genome-wide level while 31 were significant at a chromosomewide level. Because erythroid traits varied with health and disease status, QTL influencing the erythroid phenotypes showed specific health/disease patterns. Regions on SSC5, 7, 8, 12 and 13 contained QTL for baseline erythroid traits, while the other QTL regions affected distinct stages of the disease model. Single QTL explained 9‐17% of the phenotypic variance in the F2 animals. Related traits were partly under common genetic influence. Our analysis confirms that erythroid trait variation differs between Meishan and Pietrain breeds and that this variation is associated with multiple chromosomal regions.