Estimation of social genetic effects on feeding behaviour and production traits in pigs.

Pigs are housed in groups during the test period. Social effects between pen mates may affect average daily gain (ADG), backfat thickness (BF), feed conversion rate (FCR), and the feeding behaviour traits of pigs sharing the same pen. The aim of our study was to estimate the genetic parameters of feeding behaviour and production traits with statistical models that include social genetic effects (SGEs). The data contained 3075 Finnish Yorkshire, 3351 Finnish Landrace, and 968 F1-crossbred pigs. Feeding behaviour traits were measured as the number of visits per day (NVD), time spent in feeding per day (TPD), daily feed intake (DFI), time spent in feeding per visit (TPV), feed intake per visit (FPV), and feed intake rate (FR). The test period was divided into five periods of 20 days. The number of pigs per pen varied from 8 to 12. Two model approaches were tested, i.e. a fixed group size model and a variable group size model. For the fixed group size model, eight random pigs per pen were included in the analysis, while all pigs in a pen were included for the variable group size model. The linear mixed-effects model included sex, breed, and herd*year*season as fixed effects and group (batch*pen), litter, the animal itself (direct genetic effect (DGE)), and pen mates (SGEs) as random effects. For feeding behaviour traits, estimates of the total heritable variation (T2± SE) and classical heritability (h2± SE, values given in brackets) from the variable group size model (e.g. period 1) were 0.34 ± 0.13 (0.30 ± 0.04) for NVD, 0.41 ± 0.10 (0.37 ± 0.04) for TPD, 0.40 ± 0.15 (0.14 ± 0.03) for DFI, 0.53 ± 0.15 (0.28 ± 0.04) for TPV, 0.66 ± 0.17 (0.28 ± 0.04) for FPV, and 0.29 ± 0.13 (0.22 ± 0.03) for FR. The effect of social interaction was minimal for ADG (T2 = 0.29 ± 0.11 and h2 = 0.29 ± 0.04), BF (T2 = 0.48 ± 0.12 and h2 = 0.38 ± 0.07), and FCR (T2 = 0.37 ± 0.12 and h2 = 0.29 ± 0.04) using the variable group size model. In conclusion, the results indicate that social interactions have a considerable indirect genetic effect on the feeding behaviour and FCR of pigs but not on ADG and BF.

Deletion of porcine BOLL is associated with defective acrosomes and subfertility in Yorkshire boars.

A recessive sperm defect of Yorkshire boars was detected more than a decade ago. Affected boars produce ejaculates that contain spermatozoa with defective acrosomes, resulting in low fertility. The acrosome defect was mapped to porcine chromosome 15 but the causal mutation has not been identified. We re-analyzed microarray-derived genotypes of affected boars and confirmed that the acrosome defect maps to a 12.24 Mb segment of porcine chromosome 15. To detect the mutation causing defective acrosomes, we sequenced the genomes of two affected and three unaffected boars to an average coverage of 11-fold. Read depth analysis revealed a 55 kb deletion that is associated with the acrosome defect. The deletion encompasses the BOLL gene encoding the boule homolog, an RNA binding protein which is an evolutionarily conserved member of the DAZ (Deleted in AZoospermia) gene family. Lack of BOLL expression causes spermatogenic arrest and sperm maturation failure in many species. Boars that carry the deletion in the homozygous state produce sperm but their acrosomes are defective, suggesting that lack of porcine BOLL compromises acrosome formation. Our findings warrant further research to investigate the role of BOLL during spermatogenesis and sperm maturation in pigs.

Metafounder approach for single-step genomic evaluations of Red Dairy cattle.

Single-step genomic BLUP (ssGBLUP) is a powerful approach for breeding value prediction in populations with a limited number of genotyped animals. However, conflicting genomic (G) and pedigree (A22) relationship matrices complicate the implementation of ssGBLUP into practice. The metafounder (MF) approach is a recently proposed solution for this problem and has been successfully used on simulated and real multi-breed pig data. Advantages of the method are easily seen across breed evaluations, where pedigrees are traced to several pure breeds, which are thereafter used as MF. Application of the MF method to ruminants is complicated due to multi-breed pedigree structures and the inability to transmit existing unknown parent groups (UPG) to MF. In this study, we apply the MF approach for ssGBLUP evaluation of Finnish Red Dairy cattle treated as a single breed. Relationships among MF were accounted for by a (co)variance matrix (Γ) computed using estimated base population allele frequencies. The attained Γ was used to calculate a relationship matrix A22Γ for the genotyped animals. We tested the influence of SNP selection on the Γ matrix by applying a minor allele frequency (MAF) threshold (ΓMAF) where accepted markers had an MAF ≥0.05. Elements in the ΓMAF matrix were slightly lower than in the Γ matrix. Correlation between diagonal elements of the genomic and pedigree relationship matrices increased from 0.53 (A22) to 0.76 ( A22Γ and [Formula: see text] ). Average diagonal elements of A22Γ and [Formula: see text] matrices increased to the same level as in the G matrix. The ssGBLUP breeding values (GEBV) were solved using either the original 236 or redefined 8 UPG, or 8 MF computed with or without the MAF threshold. For bulls, the GEBV validation test results for the 8 UPG and 8 MF gave the same validation reliability (R2; 0.31) and over-dispersion (0.73, measured by regression coefficient b1). No significant R2 increase was observed in cows. Thus, the MF greatly influenced the pedigree relationship matrices but not the GEBV. Selection of SNP according to MAF had a notable effect on the Γ matrix and made the A22 and G matrices more similar.

Identification of runs of homozygosity affecting female fertility and milk production traits in Finnish Ayrshire cattle.

Inbreeding gives rise to continuous lengths of homozygous genotypes called runs of homozygosity (ROH) that occur when identical haplotypes are inherited from both parents. ROHs are enriched for deleterious recessive alleles and can therefore be linked to inbreeding depression, defined as decreased phenotypic performance of the animals. However, not all ROHs within a region are expected to have harmful effects on the trait of interest. We aimed to identify ROHs that unfavourably affect female fertility and milk production traits in the Finnish Ayrshire population. The estimated effect of ROHs with the highest statistical significance varied between parities from 9 to 17 days longer intervals from calving to first insemination, from 13 to 38 days longer intervals from first to last insemination and from 0.3 to 1.0 more insemination per conception. Similarly, for milk production traits ROHs were associated with a reduction of 208 kg for milk yield, 7 kg for protein yield and 16 kg for fat yield. We also found regions where ROHs displayed unfavourable effects across multiple traits. Our findings can be exploited for more efficient control of inbreeding depression, for example by minimizing the occurrence of unfavourable haplotypes as homozygous state in breeding programmes.

Estimation of intrachromosomal inbreeding depression on female fertility using runs of homozygosity in Finnish Ayrshire cattle.

Inbreeding increases homozygosity, which in turn increases the frequency of harmful recessive alleles, resulting in inbreeding depression. Inbreeding depression on fertility reduces the profitability of dairy farming by decreasing the lifetime milk production of cows and by increasing insemination and veterinary costs. Continuous homozygous segments, called runs of homozygosity (ROH), are currently considered to provide an effective measure of genomic inbreeding. The aim of this study was to estimate the effect of increased intrachromosomal homozygosity for female fertility in the Finnish Ayrshire population using ROH and haplotype analysis. Genotypes were obtained from 13,712 females with the Illumina BovineLD v.2 BeadChip low-density panel (Illumina Inc., San Diego, CA) and imputed to 50K density. After quality control, 40,554 single nucleotide polymorphisms remained for the analysis. Phenotypic data consisted of records for nonreturn rate, intervals from first to last insemination (IFL), and intervals from calving to first insemination. The raw phenotypic values were preadjusted for systematic effects before statistical analyses. The ROH-based inbreeding coefficients (FROH) were used as covariates in the mixed model equation to estimate the association between inbreeding and inbreeding depression on female fertility. First, we estimated the effect of increased chromosomal FROH. We detected significant inbreeding depression on IFL. Based on our results, a 10% increase in FROH on chromosomes 2, 18, and 22 were associated with IFL of heifers lengthening by 1.6, 0.9, and 0.7 d, respectively. Similarly, a 10% increase in FROH on chromosome 15 was associated with IFL of second-parity cows increasing by 2.3 d. Next, we located the regions within the chromosomes showing inbreeding depression. Our analysis revealed regions near the beginning of chromosome 2 and toward the ends of chromosomes 15, 18, and 22 that were associated with inbreeding depression on IFL. Last, we performed a haplotype analysis for the detected regions. The most promising haplotypes of each region were associated with IFL of heifers increasing by 4.4, 3.2, and 4.1 d on chromosomes 2, 18, and 22, respectively. The haplotype on chromosome 15 associated with IFL of second-parity cows increasing by 7.6 d. Overall, the breeding program requires inbreeding control, as increased genomic inbreeding in our study was associated with reduced reproductive ability in Finnish Ayrshire cattle.

Estimation of inbreeding depression on female fertility in the Finnish Ayrshire population.

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 (FPH ), runs of homozygosity (FROH ) and pedigree (FPED ). 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 FPED was 0.02, FROH 0.06 and FPH 0.63. A correlation of 0.71 was found between FPED and FROH , 0.66 between FPED and FPH and 0.94 between FROH and FPH . Pedigree-based inbreeding coefficients did not show inbreeding depression in any of the traits. However, when FROH or FPH was used as a covariate, significant inbreeding depression was observed; a 10% increase in FROH was associated with 5 days longer IFL0 and IFL1, 2 weeks longer IFL3 and 3 days longer ICF2 compared to non-inbred cows.

Novel harmful recessive haplotypes for reproductive traits in pigs.

Harmful recessive haplotypes for reproductive and fertility traits have previously been detected in cattle, but so far, no studies have been published for pigs. The aim of this study was to locate chromosomal regions with putative lethal haplotypes and estimate the effects of the identified haplotypes on reproductive traits in the Finnish Yorkshire pig breed. We used marker genotypes of 871 Finnish Yorkshire AI boars, genotyped with Illumina's PorcineSNP60 BeadChip. The analysed traits were number of stillborn piglets in first (NSB1) and later (NSB2) parities, total number of piglets born in first and later parities and piglet mortality between birth and weaning in first and later parities. A haplotype was claimed as a putative lethal if it was common in the population, but no homozygous animals were found. We detected altogether 26 putative lethal haplotypes, but only one haplotype on chromosome 8 (position 107.0-113.3 Mb) was significantly associated with traits NSB1 and NSB2. Three possible candidate genes were found in this chromosomal region: MAD2LI, FGF2 and ANXA5. Further analysis is needed to confirm the role of these genes on pig reproductive performance.

Evidence for three highly significant QTL for meat quality traits in the Finnish Yorkshire pig breed.

Meat quality is important both to consumers and to the meat processing industry. Commonly used measures of porcine meat quality are the pH and color of the meat. The purpose of this study was to identify SNP associated with these meat quality traits in Finnish Yorkshire using the Illumina PorcineSNP60 BeadChip. The association of each SNP with the quality traits was tested with a weighted linear model. The relatedness of samples was accounted for by a random polygenic genetic effect with the accompanying full relationship matrix. The original EBV from single-trait evaluations were deregressed before analysis. The statistical significance of SNP was established using the Bonferroni correction to adjust for multiple testing. Three genomic regions were significant for the meat quality traits. The PRKAG3 region on chromosome 15 was significant for pH measured from loin and ham and for a* (redness) measured from loin. The smallest P-value in the region was obtained for pH measured from loin (ASGA0070634, P-value = 3.8 × 10(-13)). The allele substitution effect (-0.047) of the unfavorable allele A corresponds to 1 SD of the polygenic effect. The second significant region, on chromosome 2 at around 31 megabases (Mb), was associated with pH and L* (lightness) measured from loin. The most significant SNP (ASGA0009814, P-value = 3.89 × 10(-10)) had an allele substitution effect of 0.86, corresponding to 0.7 SD of the polygenic effect of L*. The third region, located on chromosome 6 at around 83 Mb, was significant for a* measured from ham. The P-value of the best SNP (ALGA0035896) was 8.71 × 10(-7) and the allele substitution effect -0.38, corresponding to 0.5 SD of the polygenic effect of a*. The significant association of PRKAG3 with pH was not due to the known AA substitutions. The candidate gene on chromosome 2 associated with color L* is RCN1, which has a high affinity Ca(2+)-binding motif, the EF hand. The significant region on chromosome 6 for color a* contains several genes, so more data are needed to identify the causative gene. Our results indicate that instead of the known AA substitutions of PRKAG3, some yet-unknown AA substitutions are causative for the pH variation in Finnish Yorkshire. Also, a new major QLT for L* was found on chromosome 2. The significant SNP identified in this study can be used in marker-assisted selection.

L1 insertion within SPEF2 gene is associated with increased litter size in the Finnish Yorkshire population.

Immotile, short-tail sperm defect (ISTS) expanded in the Finnish Yorkshire population in the end of 1990s. The causal mutation for this defect is a recent L1 insertion within the SPEF2 gene in chromosome 16. Even though all homozygous boars are eliminated from the population because of infertility, the amount of affected boars increased rapidly until marker-assisted selection against the defect was established. To elucidate the associated effects of the ISTS defect on production traits, we have investigated the association of the L1 insertion and PRLR haplotype with reproduction traits in the Finnish Yorkshire population. Two data sets including 357 sows and 491 AI-boars were genotyped for the presence of the L1 insertion and analysed for association with reproduction traits. A Proc Mixed procedure (SAS Inc) and a software package for analysing multivariate mixed models (DMU) were used to study the effect of polymorphisms on reproduction traits. The L1-insertion within SPEF2 gene was associated with litter size in the first parity. The SPEF2 gene is located adjacent to a candidate gene for litter size in the pig, PRLR. Haplotypes within PRLR exon 10 were analysed in data set of 93 AI-boars for the association with reproduction traits. However, no associations were detected within the analysed data set indicating that PRLR sequence variants are not the causal cause for the identified effect on litter size.

Extent of linkage disequilibrium and effective population size in Finnish Landrace and Finnish Yorkshire pig breeds.

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.

Effect of polymorphisms in candidate genes on reproduction traits in Finnish pig populations.

Reproduction traits play an important role in economically viable piglet production and are closely related to the quality and length of the productive life of the sow. A increased removal rate of young sows is undesirable not only because of the associated financial penalties incurred, but also because of ethical concerns. Candidate genes and gene pathways have been identified for fertility in model species, and recent studies have provided evidence that polymorphisms within these genes are associated with reproduction traits in American Yorkshire/Large White and Landrace populations. In this study we evaluated the impact of single polymorphisms (n = 7) in 7 candidate genes on reproductive efficiency in Finnish Yorkshire (n = 280) and Landrace (n = 271) populations: IGFBP1, IGFBP2, IGFBP3, IGFBP5, CPTIA (carnitine O-palmitoyltransferase I), COX2 (PG-endoperoxide synthase 2, also known as cyclooxygenase-2), and SLC22A5 [organic cation/carnitine transporter 2 (solute carrier family member I), OCTN2]. In the Finnish Yorkshire population, only 4 of the analyzed markers were polymorphic. Significant effects on farrowing time were detected from the Yorkshire data, with polymorphisms within the genes CPT1A [a (allele substitution effect of allele A) = 2.97 d for age at first farrowing)], IGFBP3 (a = 0.54 d for farrowing interval of parities >1), and IGFBP5 (a = 3.22, 1.27, and 0.85 d for age at first farrowing and farrowing interval in the first and later parities, respectively). For the Landrace population, 6 markers were polymorphic, and significant effects were detected for traits affecting litter size. The polymorphism within the COX2 gene had an additive effect of 0.3 piglets for litter size in parities >1, and the IGFBP1 gene had an additive effect of 0.21, 0.26, and 0.11 piglets for litter size in the first parity, parities >1, and stillborn in parities >1, respectively. The additive effect of the SNP within the IGFBP2 gene was 0.16, 0.09, and 0.09 piglets for litter size in parities >1 and stillborn in the first and later parities, respectively. Finally, the IGFBP5 gene had an additive effect of 0.18, 0.07, and 0.07 piglets for litter size in the first parity, stillborn in parities >1, and mortality between farrowing and weaning in the first parity, respectively. These results support the suitability of the candidate gene approach for identification of markers to improve the reproductive performance of sows and to provide potential markers for marker-assisted selection.

Genetic parameters for bone strength, osteochondrosis and meat percentage in Finnish Landrace and Yorkshire pigs.

Osteochondrosis (OC) is a major factor causing joint problems that affect animal welfare and pork production profitability. Strong bones are also important in the slaughtering process, especially as broken bones can lead to rejections of parts of the carcass. In this study, 326 Finnish Yorkshire and 464 Finnish Landrace test station pigs were examined post mortem for bone strength and osteochondral lesions. The objective was to estimate genetic parameters for OC and bone strength and their genetic and phenotypic correlations with carcass meat percentage. Two formulas were used for lean meat percentage, the first one (Hennessy meat-%) comprising two fat thickness measurements and one muscle depth measurement, and the second one (test station meat-%) also including the weight of lean meat in ham. Finnish Yorkshire had stronger bones than Finnish Landrace on average, but also more OC in the proximal end of the humerus (36%) and the distal end of the femur (51%) than Finnish Landrace (29% and 31% OC in the humerus and femur, respectively). By using the data on both breeds, the OC heritability estimated was 0.05 in the humerus and 0.26 in the femur. The estimated heritability of bone strength was also moderate (0.26). Test station meat-% showed higher heritability (0.40) than meat-% based on the Hennessy formula (0.29). Genetic correlations between meat percentage and the other studied traits were weak and associated with high standard errors. The results show that a mild form of OC is common in both Finnish pig breeds; bone strength and OC in the distal end of the femur are moderately heritable and can be improved through selection; and selection for high meat percentage does not seem to affect bone strength or OC.

Chromosome 19q13 and multiple sclerosis susceptibility in Finland: a linkage and two-stage association study.

Several studies have previously provided some albeit weak evidence for linkage or association between chromosome 19q13 and multiple sclerosis (MS) susceptibility. We performed a two-stage association analysis with 19 markers spanning 7 Mb/5.5 cM of 19q13. In stage 1 analysis (135 MS families) allelic and haplotypic associations were found with markers within or close to the ApoE-ApoC subregion. These observations were taken as a hypothesis, which was tested in stage 2 in 125 families. However, none of the initial associations were replicated suggesting that they were most likely due to chance. Linkage analysis was performed in 27 Finnish multiplex families using 10 microsatellites spanning 23 Mb/24 cM of 19q13. DNA was available from 72 MS patients and 150 unaffected relatives. Parametric and non-parametric linkage analyses did not provide evidence for linkage when all families were tested. After stratifying the families according to HLA-DR15 there was weak evidence for linkage to the 19q13.1 subregion in DR15 negative families (LOD(max)=1.8). Taken together these results do not support a major role of chromosome 19q13.2-q13.3 in MS susceptibility among Finnish MS patients, whereas conclusions on the 19q13.1 subregion are less clear and this region requires further study.

Multiple QTL mapping in related plant populations via a pedigree-analysis approach.

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.

Respiratory distress syndrome: evaluation of genetic susceptibility and protection by transmission disequilibrium test.

Based on epidemiological data and genetic association studies, neonatal respiratory distress syndrome (RDS) is a complex disease with a multigenic background. The genes coding for surfactant proteins (SP) A and B have been assigned as the most likely genes in the etiology of RDS. The major factor predisposing to RDS is prematurity, and thus the phenotype of a very premature newborn infant that does not develop the disease can be regarded as hypernormal. Altogether 107 father-mother-offspring trios were divided into two sets according to the proband's phenotype, to evaluate familial segregation of candidate gene polymorphisms by the transmission disequilibrium test. A set of 76 trios were analyzed for transmission disequilibrium from parents to affected offspring. Another set of 31 trios were studied for allele transmission from parents to hypernormal offspring born very prematurely before the gestational age of 32 weeks. SP-A1-A2 haplotype 6A(2)-1A(0) showed significant excess transmission to affected infants and SP-A1 allele 6A(2) decreased transmission to the hypernormals. The present family study provides strong support for a direct or indirect role of the SP-A alleles as genetic predisposers to RDS in premature infants. The inclusion of parent-hypernormal offspring trios in transmission disequilibrium test is a useful approach to test for genetic protection against a disease.

Bayesian oligogenic analysis of quantitative and qualitative traits in general pedigrees.

A Bayesian method for multipoint oligogenic analysis of quantitative and qualitative traits is presented. This method can be applied to general pedigrees, which do not necessarily have to be "peelable" and can have large numbers of markers. The number of quantitative/qualitative trait loci (QTL), their map positions in the genome, and phenotypic effects (mode of inheritances) are all estimated simultaneously within the same framework. The summaries of the estimated parameters are based on the marginal posterior distributions that are obtained through Markov chain Monte Carlo (MCMC) methods. The method uses founder alleles together with segregation indicators in order to determine the genotypes of the trait loci of all individuals in the pedigree. To improve mixing properties of the sampler, we propose (1) joint sampling of map position and segregation indicators, (2) omitting data augmentation for untyped or uninformative markers (homozygous parent), and (3) updating several markers jointly within a single block. The performance of the method was tested with two replicate GAW10 data sets (considering two levels of available marker information). The results were concordant and similar to those presented earlier with other methods. These analyses clearly illustrate the utility and wide applicability of the method.

Candidate gene regions and genetic heterogeneity in gluten sensitivity.

BACKGROUND: Gluten sensitivity is a common multifactorial disorder, manifested in the small intestine or on the skin as typical coeliac disease or dermatitis herpetiformis, respectively. The only established genetic risk factor is HLA DQ2. AIMS: We tested genetic linkage of previously reported chromosomal loci 5q and 11q in Finnish families with gluten sensitivity. We also tested if genetic linkage to candidate loci on 5q, 11q, 2q33, and HLA DQ differed with respect to clinical manifestations or sex. SUBJECTS: We studied 102 Finnish families with affected sibpairs. For heterogeneity analysis, families were divided into subgroups according to sex and the presence of dermatitis herpetiformis, the skin manifestation of gluten sensitivity. METHODS: Non-parametric linkage between microsatellite markers and disease was tested. Linkage heterogeneity between subgroups was tested using the M test. The transmission/disequilibrium test and association analysis were performed. RESULTS: Evidence of linkage to 11q (MLS 1.37), but not to 5q, was found in the entire dataset of 102 families. Heterogeneity between subgroups was suggested: families with only the intestinal disease showed linkage mainly to 2q33 whereas families with dermatitis herpetiformis showed linkage to 11q and 5q, but not to 2q33. Linkage in all three non-HLA loci was strongest in families with predominantly male patients. HLA DQ2 conferred much stronger susceptibility to females than males. CONCLUSIONS: Independent evidence for the suggested genetic linkage between 11q and gluten sensitivity was obtained. The possible linkage heterogeneity suggests genetic differences between intestinal and skin manifestations, and the gender dependent effect of HLA DQ2.

Bayesian association mapping for quantitative traits in a mixture of two populations.

We introduce a novel Bayesian approach to estimate and account for population structure simultaneously with association mapping of multiple quantitative trait loci. The method is designed for an analysis of unrelated individuals from a mixture of two populations (no admixture), where the individual population memberships are unknown. In our approach, the population structure is estimated and accounted for by using data on additional "grouping" markers which are assumed to be in Hardy-Weinberg equilibrium within the populations but have different allele frequencies between the populations. We use Bayesian hierarchical modeling and Markov chain Monte Carlo estimation, where we allow both population stratification and genetic heterogeneity. In our model the number of quantitative trait loci and their positions are treated as random variables, and we obtain their posterior distributions. Here we select the candidate and the grouping markers based on results from a preliminary SOLAR analysis.

A Bayesian Markov chain Monte Carlo approach to map disease genes in simulated GAW11 data.

A Bayesian method for multipoint mapping of disease genes based on Markov chain Monte Carlo algorithms was applied to the simulated GAW11 data (Study 2). The method is based on repeated Gibbs and more general Metropolis-Hastings steps. For simplicity we assumed a single disease locus model with two alleles. A normal distribution for the underlying latent variable of the qualitative phenotype was assumed. Based on a single replicate of the data no clear evidence of any of the genes underlying the simulated disease was found. However, when three replicates were combined the method was able to locate the locus C correctly on chromosome 3.

The effect of using different culling regimens on genetic response with two-trait, two-stage selection in a nucleus broiler stock.

Stochastic simulation was used to study the effect on genetic response and inbreeding of various two-stage two-trait culling strategies. Four different parameter sets were considered for the two traits, BW and egg number. Selection of replacement animals was based on animal model best linear unbiased prediction (BLUP) to obtain estimated breeding values (EBV) at the second stage. Culling at Stage 1 was based on either animal model BLUP or phenotypes, and information from culled animals was either available or not available for calculation of second stage EBV. Besides founder individuals, six discrete generations were considered. Culling based on BLUP of two traits at Stage 1 produced higher response than culling on phenotypic evaluations. It was found that culling based on phenotypic evaluation and not carrying information to the second stage reduce rates of response by 9 to 17% and produced inbreeding higher than or close to that of BLUP selection. This study clearly shows that a double penalty of less response and higher inbreeding is generally paid for not using all information. Optimum selection schemes will depend on relative costs and benefits of collecting and processing the extra information required for full BLUP selection schemes.