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, Volume 21, Issue 7, pp 409-418 First online: Mapping of quantitative trait loci for mycoplasma and tetanus antibodies and interferon-gamma in a porcine F2 Duroc × Pietrain resource population
10.1007/s00335-010-9269-3 AbstractThe aim of the present study was to detect quantitative trait loci (QTL) for innate and adaptive immunity in pigs. For this purpose, a Duroc × Pietrain F2 resource population (DUPI) with 319 offspring was used to map QTL for the immune traits blood antibodies and interferon-gamma using 122 microsatellites covering all autosomes. Antibodies response to Mycoplasma hyopneumoniae and tetanus toxoid vaccine and the interferon-gamma (IFNG) serum concentration were measured at three different time points and were used as phenotypes. The differences of antibodies and interferon concentration between different time points were also used for the linkage mapping. Line-cross and imprinting QTL analysis, including two-QTL, were performed using QTL Express. A total of 30 QTL (12, 6, and 12 for mycoplasma, tetanus antibody, and IFNG, respectively) were identified at the 5% chromosome-wide-level significant, of which 28 were detected by line-cross and 2 by imprinting model. In addition, two QTL were identified on chromosome 5 using the two-QTL approach where both loci were in repulsion phase. Most QTL were detected on pig chromosomes 2, 5, 11, and 18. Antibodies were increased over time and immune traits were found to be affected by sex, litter size, parity, and month of birth. The results demonstrated that antibody and IFNG concentration are influenced by multiple chromosomal areas. The flanking markers of the QTL identified for IFNG on SSC5 did incorporate the position of the porcine IFNG gene. The detected QTL will allow further research in these QTL regions for candidate genes and their utilization in selection to improve the immune response and disease resistance in pig. IntroductionThe current release of the Pig QTLdb (May 5, 2010) contains 5732 QTL representing 558 different traits (http://?www.?animalgenome.?org/?QTLdb/?pig.?html), mostly economically important traits like growth, carcass and meat quality, and reproduction. Differences in immune status and variation in immune response depending on the genetic background have been reported (Edfors-Lilja et al. 1994, 1998), and medium-high to high heritabilities (h 2 = 0.3 ? 0.8) have been estimated for several of the immune traits in pigs (Edfors-Lilja et al. 1998). However, little is known about the genetics underlying these traits, especially in swine. Antibody response is one of the first immune competence traits to be examined by QTL analysis (Edfors-Lilja et al. 1998), but a very limited number of QTL analyses have been devoted to health, disease resistance, immune capacity, and immune response traits (Edfors-Lilja et al. 1998; Reiner et al. 2007; Wimmers et al. 2008, 2009). QTL underlying immune response variations have been detected in mouse, chicken, and human (Almasy and Blangero 2009; Biscarini et al. 2010; Hall et al. 2002). Therefore, the aim of the present study was to detect immune-specific QTL for innate (interferon-gamma) and adaptive (tetanus and mycoplasma antibodies) immunity in pig. Measurements of antibodies are immensely important for the evaluation of the health status of animals and herds, especially for the evaluation of vaccination efficiency and herd health programs (Regula et al. 2003). Interferon-gamma (IFNG) is one of the key molecules in the immune system and provides the first line of defense against pathogens. It has immunomodulatory function, possesses antiviral activity, and protects swine from diseases (Scheerlinck and Yen 2005; Yao et al. 2008). While IFNG is a component of the innate immune system, the antibodies belong to the adaptive/humoral immune system. Values of these immune parameters vary according to the individual’s immune status, which can be triggered by vaccine antigens. Therefore, the antibody levels were measured before and after immunological stimulation by vaccines. IFNG was measured at three time points after each vaccination as an innate immune trait, which might not reflect the vaccine’s effect but it is an important immune parameter and can be considered as an indicator of disease resistance (Scheerlinck and Yen 2005; Yao et al. 2008). With regard to the number and magnitude of their impact, QTL for immune traits behave like those for other quantitative traits. Discovery of the chromosomal regions that influence these important immune traits, including their production variations, will facilitate the identification of candidate genes for antibodies and interferon production, disease resistance, and immune competence in pigs. Materials and methodsExperimental population and blood samplingThe animal population used for the evaluation of immune traits and the genome scan was based on a Duroc × Pietrain cross. A detailed description of the population structure has been reported earlier (Liu et al. 2007, 2008). In our study, genetic information of three generations, P, F1, and F2, and phenotypes from 319 F2 pigs were used. All pigs were kept at the Frankenforst experimental research farm at the University of Bonn (Germany). The animals were fed an ad libitum diet during the whole test period and were slaughtered when they were at approximately 105 kg live weight. Pigs were vaccinated with Mycoplasma hyopneumoniae (Mh), tetanus toxoid (Tet), and porcine reproductive and respiratory syndrome virus (PRRSV) vaccines at 6, 9, and 15 weeks of age, respectively. Blood samples were taken at six different time points (Supplementary file 1). Antibody titers of Mh were measured in blood samples collected just before vaccination (6 weeks) and 10 and 20 days afterward. The sample for tetanus antibody measurement was collected just before vaccination (9 weeks) and 20 and 40 days after vaccination. The IFNG blood levels were measured from samples collected at 10 days after the Mh and PRRSV vaccinations and 20 days after the tetanus vaccination. Measurement of antibodies and interferon-gammaAntibody response to Mh vaccination was determined by monoclonal blocking ELISA using the HerdChek M. hyo. antibody ELISA kit (IDEXX GmBH, Germany) following the manufacturer’s protocol. Tet antibody was determined by in-house-developed indirect ELISA (Wimmers et al. 2008). The optical density (OD) was read at 650 and 490 nm for Mh and Tet, respectively, by using a microplate reader (ThermoMax, Molecular Devices) and the results of antibodies were determined as S/P ratio. Serum IFNG was measured by sandwich ELISA using Swine INFγ CytoSet and CytoSet Buffer Set (Invitrogen, Carlsbad, CA). Absorbance was measured at 450 nm within 30 min after adding stop solution, and the results were calculated as pg/ml using a four-parameter curve fitted in SoftMaxPro software (Molecular Devices, Sunnyvale, CA). In all cases, two replications of each sample were used for ELISA and the mean value was considered the serum concentration of respective traits. Statistical analysisSingle measurement of the antibodies and interferon at different time points and changes in titer between time points were considered a single trait and analyzed as such in this study. The differences of titer between two time points describe the kinetics of these immune traits in response to vaccine antigen (Edfors-Lilja et al. 1998). The data were analyzed using the SAS software package (version 9.2, SAS Institute, Cary, NC) for a detailed description of the data structure. Generalized linear models (PROC GLM) were used to identify any possible obvious effect of sire, dam, sex, birth weight, average daily weight gain, litter size, parity, and month of birth on the blood level of antibodies and interferon. The phenotypic data followed approximately a normal distribution and were used for linkage analysis. Marker analysisA linkage map with a total length of 2159.3 cM and an average marker interval of 17.7 cM was constructed. P, F1, and F2 animals of the DUPI population were genotyped at 122 markers’ loci covering all porcine autosomes. Marker positions and details of genotyping procedures were given in Liu et al. (2007) and for SSC1 in Grosse-Brinkhaus et al. (2009). Most of the markers were selected from the USDA/MARC map (http://?www.?marc.?usda.?gov). They are also available in Sscrofa5 [NCBI (National Center for Biotechnology Information); http://?www.?ncbi.?nlm.?nih.?gov/?projects/?mapview/?map_?search.?cgi??taxid=?9823] and Sscrofa9 [Ensembl (EMBL-EBI) high-coverage Sscrofa9 (September 2009) assembly; http://?www.?ensembl.?org/?Sus_?scrofa/?Info/?Index]. Genotyping, electrophoresis, and allele determination were done using a LI-COR 4200 automated sequencer (LI-COR Biosciences, Lincoln, NE) which included the OneDScan software (Scanalytics, Fairfax, VA). The CE8000 sequencer (BeckmanCoulter, Brea, CA) was used for genotyping SSC1 and SSC18. Allele and inheritance genotyping errors were checked using Pedcheck software (version 1.1) (O’Connell and Weeks 1998). The relative positions of the markers were assigned using the build, twopoint, and fixed options of the CRIMAP software (version 2.4) (Green et al. 1990). Recombination units were converted to map distances using the Kosambi mapping function. Marker information content and segregation distortion were tested following Knott et al. (1998). QTL analysisQTL interval mapping was performed using the web-based program QTL Express (Seaton et al. 2002) based on a least-square method. Single- and two-QTL analyses were carried out and imprinting (ADI) models were applied. The basic QTL regression model used in the present study was
The presence of imprinting effects was tested by adding a third effect (i) into the model (Knott et al. 1998) using QTL Express (Seaton et al. 2002). Chromosome- (CW) and experiment-wide (GW) significance thresholds were determined using 1000 permutations (Churchill and Doerge 1994). Chromosome-wide 1 and 5% significance thresholds became genome-wide significance thresholds after Bonferroni correction for 18 autosomes of the haploid porcine genome (de Koning et al. 2001). Methods for mapping a single QTL can be biased by the presence of other QTL (Meuwissen and Goddard 2004; Raadsma et al. 2009). To address this situation, two-QTL models were also fitted for all traits using QTL Express (Seaton et al. 2002). To control for false-positive QTL due to multiple testing, the permutation thresholds obtained in the single-QTL analyses were used to test for the significance of the two- versus one-QTL and two- versus no-QTL. Multiple QTL were declared on a chromosome if they were separated by at least 30 cM and exceeded 5% CW/GW level significance (Kim et al. 2005; Liu et al. 2008). The phenotype variation that was explained by a QTL was calculated using the following equation:
ResultsDistribution of phenotypesIt was found that antibodies for tetanus and mycoplasma increased over time after vaccinations for most animals but that IFNG levels behaved differently (Fig. 1). Overall Mh antibody concentrations were increased significantly at 10 and 20 days after vaccination compared with the concentration prior to vaccination (Fig. 1a). Tetanus antibody was significantly higher at 15 weeks of age compared with that at 9 weeks of age (Fig. 1b). When IFNG concentrations at different time points were compared, the concentration was higher at 7 weeks and lower at 12 weeks of age but no significant difference could be verified (Fig. 1c). Antibodies and interferon were found to be significantly affected by sex, litter size, parity, and month of birth (Supplementary file 2).
Fig. 1
The concentration of antibodies and interferon-gamma at different ages. Mh1, Mh2, and Mh3 indicate mycoplasma antibody level at prior vaccination (at 6 weeks of age), 10 days afterward, and 20 days afterward, respectively; Tet3, Tet4, and Tet5 indicate tetanus antibody level at prior vaccination (at 9 weeks of age), 20 days afterward, and 40 days afterward, respectively; IFN2, IFN4, and IFN6 indicate interferon-gamma level at 52, 83, and 115 days of age, respectively. * p < 0.05; ** p < 0.01 QTL for mycoplasma and tetanus antibodiesA total of 18 QTL were identified for antibodies, of which one was highly significant (experiment-wide, p < 0.05), five were significant (chromosome-wide, p < 0.01), and 12 were suggestive (chromosome-wide, p < 0.05) (Table 1). Two QTL for Mh3 and Mh2-1, respectively, were identified on SSC2. A QTL for Tet3 was detected at 115 cM on SSC4 (CW, p < 0.01) on the marker S0097. Chromosomal regions on SSC7 influencing Mh1 and Mh2 were mapped at 19 and 33 cM, respectively. The QTL for Mh2 (CW, p < 0.01) at 33 cM was located on the marker S0064 (Fig. 2a). QTL for Tet3 (GW, p < 0.05) was identified at 0 cM on SSC8, very close to the marker SW241 which explained 37.50% of the phenotypic variation. QTL (CW, p < 0.05) for Mh1 at 85 cM and for Mh2 at 101 cM were identified in this study close to the marker SW398 on SSC13. In addition, two chromosomal regions (CW, p < 0.05) at 59 and 53 cM on SSC15 were associated with Mh3 and Mh2-1. The QTL for Mh3 (CW, p < 0.05) was very close to the marker SW936. On SSC16 a QTL (CW, p < 0.01) influencing Mh3-2was found at 6 cM, which explained 27% of the phenotypic variation (Fig. 2c). Five QTL regions were identified on SSC18 (Fig. 2d). Among them, QTL (CW, p < 0.05) for Mh3 and Mh3-1 were located at the same position, very close to the marker SY4, and QTL (CW, p < 0.05) for Tet4 and Tet5-4 were located within an 8-cM region around the marker S0062. Moreover, a paternally imprinted QTL was identified for Tet3 (CW, p < 0.05) on SSC2.
Table 1
Evidence of QTL for mycoplasma and tetanus antibody levels
a Sus scrofa chromosome bTrait abbreviations: Mh1 Mh antibody level at time point 1; Mh2 Mh antibody level at time point 2; Mh3 Mh antibody level at time point 3; Mh3-1 Mh antibody difference between time points 3 and 1; Mh3-2 Mh antibody difference between time points 3 and 2; Mh2-1 Mh antibody difference between time points 2 and 1; Tet3 tetanus antibody level at time point 3; Tet4 tetanus antibody level at time point 4; Tet5-4: tetanus antibody difference between time points 5 and 4 cChromosomal position in Kosambi cM dSignificance of the QTL: * significant on a chromosome-wide level with p ≤ 0.05; ** significant on a chromosome-wide level with p ≤ 0.01; *** significant on a genome-wide level with p ≤ 0.05 eThe percentage of phenotypic variance explained by the QTL fAdditive effect and standard error. Positive values indicate the Duroc alleles result in higher values than Pietrain alleles; negative values indicate that Duroc alleles result in lower values than Pietrain alleles gDominance effect and standard error hThe closest markers were those markers around the peak, as near as possible (position of markers in cM) #The imprinting effect and standard error was detected for T3 (?0.07 ± 0.01) on SSC2. When both the additive and the imprinting effects are positive or negative, the paternal allele expresses (maternal imprinting); otherwise the maternal allele expresses (paternal imprinting) 
Fig. 2
QTL results for immune traits on SSC7 (a), SSC11 (b), SSC16 (c), and SSC18 (d). Two threshold levels are shown: the dashed line is the suggestive (CW, 5%) and the thick solid line is the chromosome-wide significance (CW, 1%). Genetic distances in Kosambi cM are given on the x axis along with markers and their positions, respectively, and F values are at the y axis QTL for interferon-gammaInterferon-gamma was found in this study to be related to 12 chromosomal regions on 8 different porcine autosomes (Table 2). A chromosomal region was identified for IFN4-2 at 68 cM on SSC4. Three QTL regions influencing IFNG were detected on SSC5. Among them, chromosomal regions at 51 cM (CW, p < 0.05) and 54 cM (CW, p < 0.01), very close to the marker SW2425, were found to influence IFN4 and IFN4-2, respectively. Three suggestive QTL (CW, p < 0.05) were detected for interferon-gamma on SSC11. Among them, QTL for IFN2 and IFN4-2 was mapped at 29 and 23 cM, respectively, close to the marker S0071. The remaining QTL (CW, p > 0.05) affecting IFN6-4 was identified at 7 cM on SSC11 (Fig. 2b). In addition, a QTL exceeding the 1% CW significance threshold was identified on SSC16, which explained 27.80% of the phenotypic variation (Fig. 2c). Moreover, a paternally imprinted QTL (CW, p < 0.05) affecting IFN2 was identified at 16 cM on SSC2.
Table 2
Evidence of QTL for interferon-gamma levels
a, c, d, e f, g, h See footnotes for Table 1 bTrait abbreviations: IFN2 IFNG level at time point 2; IFN4 IFNG level at time point 4; IFN6 IFNG level at time point 6; IFN6-2 IFNG difference between time points 6 and 2; IFN6-4: IFNG difference between time points 6 and 4; IFN4-2 IFNG difference between time points 4 and 2 #The imprinting effect and standard error was detected for IFN2 (3311.43 ± 1081.97) on SSC2. When both the additive and the imprinting effects are positive or negative, the paternal allele expresses (maternal imprinting); otherwise the maternal allele expresses (paternal imprinting) Two-QTL analyses for different traitsThe two-QTL model was used to identify the presence of possibly two QTL regions on the same chromosome. Results for the two-QTL model conducted with QTL Express are presented in Table 3. Significant evidence for an additional QTL under a two-QTL model was found for IFN4-2 on SSC5, with a difference of 66 cM between the two loci. SSC5 was genotyped with 14 microsatellite markers with an average marker distance of 10.78 cM. In this case, several markers (such as S0092, SW0005, and SW1987) were located between the two QTL regions and one of the two chromosomal regions was identified in the single-QTL approach (QTL A). The two loci on SSC5 for IFN4-2 in this study were in repulsion phase. The QTL affecting IFN4-2 at 51 and 117 cM jointly explained 39.63% of the phenotypic variation.
Table 3
Summary of significant QTL under a two-QTL model on SSC5 using QTL Express
a, c, d, eSee footnotes for Table 1 bSee footnote for Table 2 gThe QTL effect and the standard error (SE) of both QTL positions QTL A and QTL B hSignificant threshold of the F value (sign threshold) determines if the QTL reached the significance level under 2 vs. 0 QTL (2 degrees of freedom) or 2 vs. 1 QTL (1 degree of freedom) * Chromosome-wide p < 0.05; ** chromosome-wide p < 0.01 DiscussionPhenotype distributionA rise in antibodies concentration in response to Mh and Tet vaccine antigen is found over the time points but it did not increase in all animals; this may be due to individual variation. Animals that specifically had higher Mh antibody at 6 weeks of age (T1, before vaccination) had reduced values at T2 (10 days after vaccination) and increased values at T3 (20 days after vaccination). Hodgins et al. (2004) reported that maternally derived antibodies play a major negative role in response to Mh vaccines by neutralizing vaccine antigen. Mh antibody concentration at T1 is found to be affected by sex, but Moreau et al. (2004) did not find there to be an interaction between the effect of vaccine and sex in pigs. In this study, Mh antibody is significantly influenced by the effects of sire and dam. Differences in patterns of colonization of M. hyopneumoniae between pigs sired by different boars were reported by Ruiz et al. (2002). Passive transmission of Mh antibody from dam to piglets through colostrum might be evidence for dam influence. The Mh antibody concentration was significantly influenced by parity in this study, which is supported by the study of Calsamiglia and Pijoan (2000). Age was found to have an effect on Tet antibody in this study. Cook et al. (2001) reported that the tetanus antibody concentration decreased significantly with age in human. Antibody reached the highest concentration 6 weeks after vaccination (T5) in our study, but no such report is found in pigs. However, human peripheral blood mononuclear cells (PBMC) were reported to produce the highest concentration of anti-tetanus antibody at 3 weeks after exposure to tetanus toxoid (Virella and Hyman 1991). IFNG concentration showed a trend of decreasing with age in this study, with the IFNG concentration higher in younger animals (7 week of age) than in older animals (12 and 16 weeks). Davis et al. (2006) reported that PBMCs collected from young pigs produced higher IFNG than PBMCs collected from older pigs. Sire, litter, and sex have effects on IFNG production; this is supported by a previous report on pigs (Mallard et al. 1989). Outteridge (1993) stated that in addition to genetic causes, there are many causes for individual variation and immune responsiveness such as nutritional status, immunological maturation, antigenic competition, and immunological priming. QTL for mycoplasma and tetanus antibody traitsIn the pig, genome-wide significant QTL for cellular and humoral immune traits are shown to segregate on chromosomes 1, 4, 5, and 6 in an experimental cross of wild boar and Yorkshire (Edfors-Lilja et al. 1998, 2000). QTL for the pseudorabies virus resistance/susceptibility have been mapped to chromosomes 9, 5, and 6 (Reiner et al. 2002), and for Sarcocystis miescheriana they are detected on SSC7, 16, and 2 (Reiner et al. 2007) in pigs. QTL for antibodies of PRRS and Aujeszky’s disease virus were mapped on SSC1, 2, and 6 (Wimmers et al. 2009), and those for mycoplasma, tetanus, and PRRS antibodies on SSC3, 6, 16, and 17 (Wimmers et al. 2008). Recently, the NCBI released the draft assembly of the porcine genome Sscrofa5 (NCBI) which included assemblies for chromosomes 1, 4, 5, 7, 11, 13, 14, 15, 17, and X, and ENSEMBL released Sscrofa9 (Ensembl). These databases help the search for the immunologically important genes located on the identified QTL regions. Two QTL that influence Mh antibody production and have additive and dominant effects were detected on SSC2. Very close to this region, a QTL for leukocyte number was reported previously (Edfors-Lilja et al. 2000). In response to M. hyopneumoniae, macrophage (leukocyte) activation and proliferation were reported in pig (Rodriguez et al. 2007), which is an evidence for possible QTL affecting Mh antibody. Moreover, leukocytes and monocytes are reported to phagocyte the mycoplasma pathogen (Marshall et al. 1995). A QTL for Tet antibody was mapped on SSC4 close to the marker S0097, where Edfors-Lilja et al. (2000) reported there to be a QTL affecting eosinophil numbers. The QTL on SSC7 for Mh antibody were in a region similar to where a QTL for platelets number was detected earlier (Reiner et al. 2007). Choi et al. (2006) reported that M. hyopneumoniae causes thrombocytopenia by destroying platelets in pig. Moreover, the immunologically important tumor necrosis factor (TNF-α and β), MHC (I and II), C2, and C4 genes are mapped on the same region (Ensembl and NCBI) on SSC7. TNF-α is reported to be highly expressed and responsible for cachexia in pigs experimentally infected with M. hyopneumoniae (Choi et al. 2006). The very important innate immune gene TLR6 (Toll-like receptor 6) is located at the region on SSC8 that affects tetanus antibody production. Toll-like receptors (TLRs) play an essential role in the recognition of microbial components and are reported as critical proteins linking innate and humoral immunity (Takeda and Akira 2004). TLRs are speculated to be used in the design of vaccines, including tetanus toxoid (van Duin et al. 2006). The natural resistance-associated macrophage protein 1 (NRAMP1) is mapped to SSC15q23-26, where two QTL regions (close to SW936 marker) are detected for Mh antibody in this study. NRAMP1 is a potential candidate gene for controlling pig resistance to salmonella infection (Sun et al. 1998). Recent studies using knockout mice indicated that the NRAMP1 gene expressed in macrophages is capable of controlling resistance and susceptibility to Mycobacterium bovis (BCG), Leishmania donovani, and Salmonella typhimurium (Stecher et al. 2006). NRAMP1 might be a good candidate gene for Mh antibody production. A QTL affecting Mh antibody was found on SSC16 close to marker S0111, where a QTL for C3 was reported earlier (Wimmers et al. 2008). Wimmers et al. (2003) stated that C3 is associated with Mh antibody concentration in pigs. Furthermore, two linkage regions related to Mh antibody production were identified close to the marker SY4 on SSC18. T-cell receptor beta variable 19 (TRBV19) is located very close to this region (Ensembl). The T-cell receptors (TCRs) are a complex of integral membrane proteins that participates in the activation of T cells in response to the presentation of antigen, and TRB is reported to be expressed by T cells in response to Mycoplasma sp. stimulation (Friedman et al. 1991). In addition, two QTL that affect Tet antibody were found close the marker S0062, where growth hormone-releasing hormone receptor (GHRHR) and acyloxyacyl hydroxylase (AOAH) are located (Ensembl). Growth hormone can act as a cytokine that can influence lymphocyte proliferation, and its receptors are located on lymphocytes and macrophages (Postel-Vinay et al. 1997). LeRoith et al. (1996) reported that GH administration elicited a marked activation of the immune system in response to tetanus toxoid. AOAH is reported to modulate host inflammatory responses in Gram-negative bacterial invasion (Feulner et al. 2004). QTL for interferon-gamma traitThe cytokine network is complex and demonstrates redundancy and pleiotropism. IFNG is an important cytokine for inducing activation of macrophage killing and has been evaluated as a marker for acute bacterial infection in swine (Yao et al. 2008). The significant QTL for IFNG on SSC4 was assigned close to the position of CD1 and CRP (C-reactive protein). CRP plays an important role via monocytes in upregulating proinflammatory cytokines. One of the most interesting findings for the interferon QTL was the identification of two linkage regions influencing IFNG on SSC5 close to SSC5p11-12, where the IFNG gene is located. This implies that IFNG is influenced by the region of its own location. However, more regions of other chromosomes also affect IFNG production, which is evidence of the multiple-gene effect. Previously reported QTL that affect neutrophil proliferation (Reiner et al. 2002) and IgG production (Edfors-Lilja et al. 1998) are also close to our identified QTL for IFNG on SSC5. Unique receptors of IFNG are located on the surface of the T and B lymphocytes, NK cells, and neutrophils. Transforming growth factor β2 (TGFB2) is a potent anti-inflammatory cytokine located on SSC10, close to the marker SW830 (Ensembl), and has an antagonistic effect on IFNG (Ulloa et al. 1999). Kruppel-like factor 5 (KLF5) is mapped close to the marker S0071 (Ensembl and NCBI) on SSC11. Chen et al. (2000) reported that KLF5 is an immediate-early IFNG responsive gene and IFNG induces KLF5 expression. C9 (complement component 9) gene is an important component of the complement system and plays an important role in innate immune response. This gene is located within the flanking markers of the QTL identified for IFNG (CW, p < 0.01) on SSC16 (Ensembl). Imprinted QTLMost imprinted genes are identified in humans and mice (http://?igc.?otago.?ac.?nz/?). Imprinted genes are considered to be one culprit of phenotypic variation in pig (Bischoff et al. 2009), but only a small number of imprinted genes are identified in pigs (Zhang et al. 2007). A number of imprinting QTL are reported in pigs (de Koning et al. 2000; Holl et al. 2004; Nezer et al. 1999; Thomsen et al. 2004), but no imprinting QTL for immune traits have been reported yet. Recently, imprinting QTL for immune response has been reported in chicken (Pinard-van der Laan et al. 2009). The paternally imprinted QTL found in our study have their best position at 16 cM for IFNG and 0 cM for Tet antibody on SSC2. Imprinting QTL on SSC2 are reported to influence lean growth (Nezer et al. 1999), skeletal and cardiac muscle mass (Jeon et al. 1999), backfat (de Koning et al. 2000), teat number and coat colour (Hirooka et al. 2002), and reproduction (Holl et al. 2004). Notable imprinted genes in this region include IGF2 (insulin-like growth factor 2), H19, and Wilms tumor. QTL with imprinting effects are reported to be more appropriate for analyzing F2 data than only the single line-cross model (Holl et al. 2004). However, for most of the QTL showing imprinting effects, biological reasons for the inherited mode are difficult to derive. Evolutionary reasons behind the presence of parent-of-origin effects are also unclear, although several theories exist (Thomsen et al. 2004; Tycko and Morison 2002). ConclusionsThe results of this work shed new light on the genetic background of both innate and adaptive immune responses in pigs. Mycoplasma and tetanus antibodies and interferon-gamma production are influenced by both environmental and genetic factors. This study has identified several new QTL for immune traits on most autosomes. TNFα, NRAMP1, and TCRs might be good candidate genes for mycoplasma and TLR6 for tetanus antibody production. Our results showed that IFNG is influenced by the chromosomal region to which it is mapped, and there might be more regulative genes along with multiple chromosomal regions. This study enforces the hypothesis that genomic imprinting might be important in livestock species. Despite the fact that candidate genes were identified, before an interpretation of QTL results can be made we must remember that confidence regions of the QTL are large and can contain many potential candidate genes for the QTL (de Koning et al. 2005). However, this discovery of the QTL regions will facilitate identifying candidate genes for immune competence and disease resistance, which is the first step in marker-assisted breeding efforts. Furthermore, follow-up research is needed to further characterize these quantitative trait loci in other crosses and identify candidate genes by fine mapping using denser marker sets like large-scale SNP assays. AcknowledgmentsThis project was supported by the Gene Dialog project, FUGATO Plus, BMBF, grant No. 0315130C, Germany. The authors are indebted to Miss Nadine Leyer, Institute of Animal Science, University of Bonn, Germany, for her help during the experiment. Copyright information Springer Science+Business Media, LLC 2010 |
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