eQTL analysis of laying hens divergently selected for feather pecking identifies KLF14 as a potential key regulator for this behavioral disorder.

Feather pecking in chickens is a damaging behavior, seriously impacting animal welfare and leading to economic losses. Feather pecking is a complex trait, which is partly under genetic control. Different hypotheses have been proposed to explain the etiology of feather pecking and notably, several studies have identified similarities between feather pecking and human mental disorders such as obsessive-compulsive disorder and schizophrenia. This study uses transcriptomic and phenotypic data from 167 chickens to map expression quantitative trait loci and to identify regulatory genes with a significant effect on this behavioral disorder using an association weight matrix approach. From 70 of the analyzed differentially expressed genes, 11,790 genome wide significantly associated variants were detected, of which 23 showed multiple associations (≥15). These were located in proximity to a number of genes, which are transcription regulators involved in chromatin binding, nucleic acid metabolism, protein translation and putative regulatory RNAs. The association weight matrix identified 36 genes and the two transcription factors: SP6 (synonym: KLF14) and ENSGALG00000042129 (synonym: CHTOP) as the most significant, with an enrichment of KLF14 binding sites being detectable in 40 differentially expressed genes. This indicates that differential expression between animals showing high and low levels of feather pecking was significantly associated with a genetic variant in proximity to KLF14. This multiallelic variant was located 652 bp downstream of KLF14 and is a deletion of 1-3 bp. We propose that a deletion downstream of the transcription factor KLF14 has a negative impact on the level of T cells in the developing brain of high feather pecking chickens, which leads to developmental and behavioral abnormalities. The lack of CD4 T cells and gamma-Aminobutyric acid (GABA) receptors are important factors for the increased propensity of laying hens to perform feather pecking. As such, KLF14 is a clear candidate regulator for the expression of genes involved in the pathogenic development. By further elucidating the regulatory pathways involved in feather pecking we hope to take significant steps forward in explaining and understanding other mental disorders, not just in chickens.

Composition of the ileum microbiota is a mediator between the host genome and phosphorus utilization and other efficiency traits in Japanese quail (Coturnix japonica).

BACKGROUND: Phosphorus is an essential nutrient in all living organisms and, currently, it is the focus of much attention due to its global scarcity, the environmental impact of phosphorus from excreta, and its low digestibility due to its storage in the form of phytates in plants. In poultry, phosphorus utilization is influenced by composition of the ileum microbiota and host genetics. In our study, we analyzed the impact of host genetics on composition of the ileum microbiota and the relationship of the relative abundance of ileal bacterial genera with phosphorus utilization and related quantitative traits in Japanese quail. An F2 cross of 758 quails was genotyped with 4k genome-wide single nucleotide polymorphisms (SNPs) and composition of the ileum microbiota was characterized using target amplicon sequencing. Heritabilities of the relative abundance of bacterial genera were estimated and quantitative trait locus (QTL) linkage mapping for the host was conducted for the heritable genera. Phenotypic and genetic correlations and recursive relationships between bacterial genera and quantitative traits were estimated using structural equation models. A genomic best linear unbiased prediction (GBLUP) and microbial (M)BLUP hologenomic selection approach was applied to assess the feasibility of breeding for improved phosphorus utilization based on the host genome and the heritable part of composition of the ileum microbiota. RESULTS: Among the 59 bacterial genera examined, 24 showed a significant heritability (nominal p ≤ 0.05), ranging from 0.04 to 0.17. For these genera, six genome-wide significant QTL were mapped. Significant recursive effects were found, which support the indirect host genetic effects on the host's quantitative traits via microbiota composition in the ileum of quail. Cross-validated microbial and genomic prediction accuracies confirmed the strong impact of microbial composition and host genetics on the host's quantitative traits, as the GBLUP accuracies based on the heritable microbiota-mediated components of the traits were similar to the accuracies of conventional GBLUP based on genome-wide SNPs. CONCLUSIONS: Our results revealed a significant effect of host genetics on composition of the ileal microbiota and confirmed that host genetics and composition of the ileum microbiota have an impact on the host's quantitative traits. This offers the possibility to breed for improved phosphorus utilization based on the host genome and the heritable part of composition of the ileum microbiota.

Genetic Analyses and Genome-Wide Association Studies on Pathogen Resistance of Bos taurus and Bos indicus Cattle Breeds in Cameroon.

Autochthonous taurine and later introduced zebu cattle from Cameroon differ considerably in their resistance to endemic pathogens with little to no reports of the underlying genetic make-up. Breed history and habitat variations are reported to contribute significantly to this diversity worldwide, presumably in Cameroon as well, where locations diverge in climate, pasture, and prevalence of infectious agents. In order to investigate the genetic background, the genotypes of 685 individuals of different Cameroonian breeds were analysed by using the BovineSNP50v3 BeadChip. The variance components including heritability were estimated and genome-wide association studies (GWAS) were performed. Phenotypes were obtained by parasitological screening and categorised in Tick-borne pathogens (TBP), gastrointestinal nematodes (GIN), and onchocercosis (ONC). Estimated heritabilities were low for GIN and TBP (0.079 (se = 0.084) and 0.109 (se = 0.103) respectively) and moderate for ONC (0.216 (se = 0.094)). Further than revealing the quantitative nature of the traits, GWAS identified putative trait-associated genomic regions on five chromosomes, including the chromosomes 11 and 18 for GIN, 20 and 24 for TBP, and 12 for ONC. The results imply that breeding for resistant animals in the cattle population from Northern Cameroon might be possible for the studied pathogens; however, further research in this field using larger datasets will be required to improve the resistance towards pathogen infections, propose candidate genes or to infer biological pathways, as well as the genetic structures of African multi-breed populations.

Meta-analyses of genome wide association studies in lines of laying hens divergently selected for feather pecking using imputed sequence level genotypes.

BACKGROUND: Feather pecking (FP) is damaging behavior in laying hens leading to global economic losses in the layer industry and massive impairments of animal welfare. The objective of the study was to discover genetic variants and affected genes that lead to FP behavior. To achieve that we imputed low-density genotypes from two different populations of layers divergently selected for FP to sequence level by performing whole genome sequencing on founder and half-sib individuals. In order to decipher the genetic structure of FP, genome wide association studies and meta-analyses of two resource populations were carried out by focusing on the traits 'feather pecks delivered' (FPD) and the 'posterior probability of a hen to belong to the extreme feather pecking subgroup' (pEFP). RESULTS: In this meta-analysis, we discovered numerous genes that are affected by polymorphisms significantly associated with the trait FPD. Among them SPATS2L, ZEB2, KCHN8, and MRPL13 which have been previously connected to psychiatric disorders with the latter two being responsive to nicotine treatment. Gene set enrichment analysis revealed that phosphatidylinositol signaling is affected by genes identified in the GWAS and that the Golgi apparatus as well as brain structure may be involved in the development of a FP phenotype. Further, we were able to validate a previously discovered QTL for the trait pEFP on GGA1, which contains variants affecting NIPA1, KIAA1211L, AFF3, and TSGA10. CONCLUSIONS: We provide evidence for the involvement of numerous genes in the propensity to exhibit FP behavior that could aid in the selection against this unwanted trait. Furthermore, we identified variants that are involved in phosphatidylinositol signaling, Golgi metabolism and cell structure and therefore propose changes in brain structure to be an influential factor in FP, as already described in human neuropsychiatric disorders.

Analysis of the brain transcriptome in lines of laying hens divergently selected for feather pecking.

BACKGROUND: Feather pecking (FP) in laying hens reduces animal welfare and leads to economic losses for the layer industry. FP is considered a heritable condition that is influenced by dysregulation of neurotransmitter homeostasis, the gut microbiome, and the immune system. To identify genes and biological pathways responsible for FP behavior we compared the brain transcriptomes of 48 hens divergently selected for FP. In addition, we tested if high feather peckers (HFP) and low feather peckers (LFP) respond differently to light since light has been shown to trigger FP behavior. RESULTS: Of approximately 48 million reads/sample an average of 98.4% were mapped to the chicken genome (GRCg6a). We found 13,070 expressed genes in the analyzed brains of which 423 showed differential expression between HFP and LFP. Genes of uncertain function and non-coding RNAs were overrepresented among those transcripts. Functional analyses revealed the involvement of cholinergic signaling, postsynaptic activity, membrane channels, and the immune system. After the light stimulus, 28 genes were found to be differentially expressed. These included an interaction cluster of core components of the circadian clock. However, differences in the response to light between HFP and LFP were not detectable. CONCLUSIONS: Genes involved in cholinergic signaling, channel activity, synaptic transmission, and immune response were found to be involved in FP behavior. We propose a model in which the gut microbiota modulates the immune system, which in turn affects cholinergic signaling. This might have an influence on monoamine signaling with possible involvement of GABA or glutamate signaling.

Genomewide Mapping of Selection Signatures and Genes for Extreme Feather Pecking in Two Divergently Selected Laying Hen Lines.

Feather pecking (FP) is a longstanding serious problem in commercial flocks of laying hens. It is a highly polygenic trait and the genetic background is still not completely understood. In order to find genomic regions influencing FP, selection signatures between laying hen lines divergently selected for high and low feather pecking were mapped using the intra-population iHS and the inter-population FST approach. In addition, the existence of an extreme subgroup of FP hens (EFP) across both selected lines has been demonstrated by fitting a mixture of negative binomial distributions to the data and calculating the posterior probability of belonging to the extreme subgroup (pEFP) for each hen. A genomewide association study (GWAS) was performed for the traits pEFP and FP delivered (FPD) with a subsequent post GWAS analysis. Mapping of selection signatures revealed no clear regions under selection. GWAS revealed a region on Chromosome 1, where the existence of a QTL influencing FP is likely. The candidate genes found in this region are a part of the GABAergic system, which has already been linked to FP in previous studies. Despite the polygenic nature of FP, selection on these candidate genes may reduce FP.

GWAS for Meat and Carcass Traits Using Imputed Sequence Level Genotypes in Pooled F2-Designs in Pigs.

In order to gain insight into the genetic architecture of economically important traits in pigs and to derive suitable genetic markers to improve these traits in breeding programs, many studies have been conducted to map quantitative trait loci. Shortcomings of these studies were low mapping resolution, large confidence intervals for quantitative trait loci-positions and large linkage disequilibrium blocks. Here, we overcome these shortcomings by pooling four large F2 designs to produce smaller linkage disequilibrium blocks and by resequencing the founder generation at high coverage and the F1 generation at low coverage for subsequent imputation of the F2 generation to whole genome sequencing marker density. This lead to the discovery of more than 32 million variants, 8 million of which have not been previously reported. The pooling of the four F2 designs enabled us to perform a joint genome-wide association study, which lead to the identification of numerous significantly associated variant clusters on chromosomes 1, 2, 4, 7, 17 and 18 for the growth and carcass traits average daily gain, back fat thickness, meat fat ratio, and carcass length. We could not only confirm previously reported, but also discovered new quantitative trait loci. As a result, several new candidate genes are discussed, among them BMP2 (bone morphogenetic protein 2), which we recently discovered in a related study. Variant effect prediction revealed that 15 high impact variants for the traits back fat thickness, meat fat ratio and carcass length were among the statistically significantly associated variants.

Genome-wide association studies and meta-analysis uncovers new candidate genes for growth and carcass traits in pigs.

Genome-wide association studies (GWAS) have been widely used in the genetic dissection of complex traits. As more genomic data is being generated within different commercial or resource pig populations, the challenge which arises is how to collectively investigate the data with the purpose to increase sample size and implicitly the statistical power. This study performs an individual population GWAS, a joint population GWAS and a meta-analysis in three pig F2 populations. D1 is derived from European type breeds (Piétrain, Large White and Landrace), D2 is obtained from an Asian breed (Meishan) and Piétrain, and D3 stems from a European Wild Boar and Piétrain, which is the common founder breed. The traits investigated are average daily gain, backfat thickness, meat to fat ratio and carcass length. The joint and the meta-analysis did not identify additional genomic clusters besides the ones discovered via the individual population GWAS. However, the benefit was an increased mapping resolution which pinpointed to narrower clusters harboring causative variants. The joint analysis identified a higher number of clusters as compared to the meta-analysis; nevertheless, the significance levels and the number of significant variants in the meta-analysis were generally higher. Both types of analysis had similar outputs suggesting that the two strategies can complement each other and that the meta-analysis approach can be a valuable tool whenever access to raw datasets is limited. Overall, a total of 20 genomic clusters that predominantly overlapped at various extents, were identified on chromosomes 2, 7 and 17, many confirming previously identified quantitative trait loci. Several new candidate genes are being proposed and, among them, a strong candidate gene to be taken into account for subsequent analysis is BMP2 (bone morphogenetic protein 2).

Genetic parameter estimates and targeted association analyses of growth, carcass, and meat quality traits in German Merinoland and Merinoland-cross lambs.

In this study, genetic parameters of nine growth, carcass, and meat quality (MQ) traits were estimated, and targeted association studies were conducted using mixed models. Phenotypic information was collected on 1,599 lambs, including both purebred Merinoland (ML) animals and five different F1 crosses. The F1 lambs were produced by mating rams of the meat-type breeds Charollais, Ile de France, German Blackheaded Mutton (Deutsches Schwarzköpfiges Fleischschaf), Suffolk, and Texel with ML ewes. Between four and six sires were used per sire breed. In total, 29 sires and 298 purebred ML sheep were genotyped with the Illumina OvineSNP50 BeadChip. All F1 individuals were genotyped for 289 SNPs located on the chromosomes 1, 2, 3, 18, and 21. These SNPs were used to impute SNPs on five chromosomes of the Illumina Ovine chip in the F1 individuals. Several Bonferroni-corrected significant associations were identified for shoulder width. A number of additional significant associations were found for other traits. Genetic parameters were estimated and single-marker association analyses were performed with breed-specific effects. Moderate heritability estimates were found for average daily gain (0.23), kidney fat weight (0.19), carcass length (0.15), shoulder width (0.33), subcutaneous fat thickness (0.22), and cutlet area (0.36). While heritability for cooking loss was found to be low (0.07), shear force (0.17) and dressing percentage (0.20) showed moderate heritability, and thus might be candidate traits to be included in the selection index in the population. In general, low phenotypic and low or moderate genetic correlations were detected between the traits.

Host Genome Influence on Gut Microbial Composition and Microbial Prediction of Complex Traits in Pigs.

The aim of the present study was to analyze the interplay between gastrointestinal tract (GIT) microbiota, host genetics, and complex traits in pigs using extended quantitative-genetic methods. The study design consisted of 207 pigs that were housed and slaughtered under standardized conditions, and phenotyped for daily gain, feed intake, and feed conversion rate. The pigs were genotyped with a standard 60 K SNP chip. The GIT microbiota composition was analyzed by 16S rRNA gene amplicon sequencing technology. Eight from 49 investigated bacteria genera showed a significant narrow sense host heritability, ranging from 0.32 to 0.57. Microbial mixed linear models were applied to estimate the microbiota variance for each complex trait. The fraction of phenotypic variance explained by the microbial variance was 0.28, 0.21, and 0.16 for daily gain, feed conversion, and feed intake, respectively. The SNP data and the microbiota composition were used to predict the complex traits using genomic best linear unbiased prediction (G-BLUP) and microbial best linear unbiased prediction (M-BLUP) methods, respectively. The prediction accuracies of G-BLUP were 0.35, 0.23, and 0.20 for daily gain, feed conversion, and feed intake, respectively. The corresponding prediction accuracies of M-BLUP were 0.41, 0.33, and 0.33. Thus, in addition to SNP data, microbiota abundances are an informative source of complex trait predictions. Since the pig is a well-suited animal for modeling the human digestive tract, M-BLUP, in addition to G-BLUP, might be beneficial for predicting human predispositions to some diseases, and, consequently, for preventative and personalized medicine.

A genome-wide association study in a large F2-cross of laying hens reveals novel genomic regions associated with feather pecking and aggressive pecking behavior.

BACKGROUND: Feather pecking and aggressive pecking in laying hens are serious economic and welfare issues. In spite of extensive research on feather pecking during the last decades, the motivation for this behavior is still not clear. A small to moderate heritability has frequently been reported for these traits. Recently, we identified several single-nucleotide polymorphisms (SNPs) associated with feather pecking by mapping selection signatures in two divergent feather pecking lines. Here, we performed a genome-wide association analysis (GWAS) for feather pecking and aggressive pecking behavior, then combined the results with those from the recent selection signature experiment, and linked them to those obtained from a differential gene expression study. METHODS: A large F2 cross of 960 F2 hens was generated using the divergent lines as founders. Hens were phenotyped for feather pecks delivered (FPD), aggressive pecks delivered (APD), and aggressive pecks received (APR). Individuals were genotyped with the Illumina 60K chicken Infinium iSelect chip. After data filtering, 29,376 SNPs remained for analyses. Single-marker GWAS was performed using a Poisson model. The results were combined with those from the selection signature experiment using Fisher's combined probability test. RESULTS: Numerous significant SNPs were identified for all traits but with low false discovery rates. Nearly all significant SNPs were located in clusters that spanned a maximum of 3 Mb and included at least two significant SNPs. For FPD, four clusters were identified, which increased to 13 based on the meta-analysis (FPDmeta). Seven clusters were identified for APD and three for APR. Eight genes (of the 750 investigated genes located in the FPDmeta clusters) were significantly differentially-expressed in the brain of hens from both lines. One gene, SLC12A9, and the positional candidate gene for APD, GNG2, may be linked to the monomanine signaling pathway, which is involved in feather pecking and aggressive behavior. CONCLUSIONS: Combining the results from the GWAS with those of the selection signature experiment substantially increased the statistical power. The behavioral traits were controlled by many genes with small effects and no single SNP had effects large enough to justify its use in marker-assisted selection.

Genetic parameters and signatures of selection in two divergent laying hen lines selected for feather pecking behaviour.

BACKGROUND: Feather pecking (FP) in laying hens is a well-known and multi-factorial behaviour with a genetic background. In a selection experiment, two lines were developed for 11 generations for high (HFP) and low (LFP) feather pecking, respectively. Starting with the second generation of selection, there was a constant difference in mean number of FP bouts between both lines. We used the data from this experiment to perform a quantitative genetic analysis and to map selection signatures. METHODS: Pedigree and phenotypic data were available for the last six generations of both lines. Univariate quantitative genetic analyses were conducted using mixed linear and generalized mixed linear models assuming a Poisson distribution. Selection signatures were mapped using 33,228 single nucleotide polymorphisms (SNPs) genotyped on 41 HFP and 34 LFP individuals of generation 11. For each SNP, we estimated Wright's fixation index (FST). We tested the null hypothesis that FST is driven purely by genetic drift against the alternative hypothesis that it is driven by genetic drift and selection. RESULTS: The mixed linear model failed to analyze the LFP data because of the large number of 0s in the observation vector. The Poisson model fitted the data well and revealed a small but continuous genetic trend in both lines. Most of the 17 genome-wide significant SNPs were located on chromosomes 3 and 4. Thirteen clusters with at least two significant SNPs within an interval of 3 Mb maximum were identified. Two clusters were mapped on chromosomes 3, 4, 8 and 19. Of the 17 genome-wide significant SNPs, 12 were located within the identified clusters. This indicates a non-random distribution of significant SNPs and points to the presence of selection sweeps. CONCLUSIONS: Data on FP should be analysed using generalised linear mixed models assuming a Poisson distribution, especially if the number of FP bouts is small and the distribution is heavily peaked at 0. The FST-based approach was suitable to map selection signatures that need to be confirmed by linkage or association mapping.

Direct determination of flavor relevant and further branched-chain fatty acids from sheep subcutaneous adipose tissue by gas chromatography with mass spectrometry.

4-Methyloctanoic acid, 4-ethyloctanoic acid and 4-methylnonanoic acid are key-flavor compounds of sheep and goat. Yet, the low amounts of these volatile branched-chain fatty acids (vBCFAs) in the fat of the ruminants hampered their determination on a routine basis. In this work we developed a gas chromatography/mass spectrometry selected ion monitoring (GC/MS-SIM) method for the direct determination of the vBCFAs as methyl esters, which were obtained after transesterification of subcutaneous adipose tissue of sheep. The excellent sensitivity of the GC/MS-SIM method (limit of quantification, LOQ, 3.6-4.8µg/g; limit of detection, LOD, 1.1-1.4µg/g for 4-Me-8:0, 4-Et-8:0 and 4-Me-9:0) enabled us to determine the three vBCFAs without an enrichment step. Subcutaneous adipose sheep tissue of three different breeds contained 23-88µg/g 4-methyloctanoic acid, 13-26µg/g 4-ethyloctanoic acid and ∼2.9-18µg/g 4-methylnonanoic acid. Since all fatty acids were present in the FAME fraction, the samples could be screened for further branched-chain FAMEs. After elimination of unsaturated fatty acids by hydrogenation (the presence of some unsaturated fatty acids could be verified by this measure), additional measurements in SIM and full scan modes of methyl esters and picolinyl esters enabled the determination of further 97 saturated fatty acids in the samples with eight to 20 carbons. The method is suited for routine analysis and may be useful to investigate the reasons for the abundance/absence of 4-methyloctanoic acid, 4-ethyloctanoic acid and 4-methylnonanoic acid and further branched-chain fatty acids in sheep and goat.

Genomic selection using low density marker panels with application to a sire line in pigs.

BACKGROUND: Genomic selection has become a standard tool in dairy cattle breeding. However, for other animal species, implementation of this technology is hindered by the high cost of genotyping. One way to reduce the routine costs is to genotype selection candidates with an SNP (single nucleotide polymorphism) panel of reduced density. This strategy is investigated in the present paper. Methods are proposed for the approximation of SNP positions, for selection of SNPs to be included in the low-density panel, for genotype imputation, and for the estimation of the accuracy of genomic breeding values. The imputation method was developed for a situation in which selection candidates are genotyped with an SNP panel of reduced density but have high-density genotyped sires. The dams of selection candidates are not genotyped. The methods were applied to a sire line pig population with 895 German Piétrain boars genotyped with the PorcineSNP60 BeadChip. RESULTS: Genotype imputation error rates were 0.133 for a 384 marker panel, 0.079 for a 768 marker panel, and 0.022 for a 3000 marker panel. Error rates for markers with approximated positions were slightly larger. Availability of high-density genotypes for close relatives of the selection candidates reduced the imputation error rate. The estimated decrease in the accuracy of genomic breeding values due to imputation errors was 3% for the 384 marker panel and negligible for larger panels, provided that at least one parent of the selection candidates was genotyped at high-density.Genomic breeding values predicted from deregressed breeding values with low reliabilities were more strongly correlated with the estimated BLUP breeding values than with the true breeding values. This was not the case when a shortened pedigree was used to predict BLUP breeding values, in which the parents of the individuals genotyped at high-density were considered unknown. CONCLUSIONS: Genomic selection with imputation from very low- to high-density marker panels is a promising strategy for the implementation of genomic selection at acceptable costs. A panel size of 384 markers can be recommended for selection candidates of a pig breeding program if at least one parent is genotyped at high-density, but this appears to be the lower bound.

Investigating gene expression differences in two chicken groups with variable propensity to feather pecking.

Feather pecking is a major welfare problem in egg production. It may be caused by genetic, physiological and environmental factors. The main aim of this study was to uncover gene expression variability in brain tissue between individuals from high feather pecking and low feather pecking groups using the Chicken Gene Expression Microarray. In total, 313 signals were initially identified as significant (P ≤ 0.05) for the fold change higher than two. A subset of functional candidate genes including downregulated (GLUL, TSPO, MAOA) and upregulated (HTR1B, SIP1, PSEN1) transcripts was subjected to quantitative PCR validation. The significance level and direction of the fold change in gene expression observed by the microarray analysis were confirmed for four genes (HTR1B, SIP1, PSEN1 and GLUL). Newly identified candidate genes play an important role in neurotransmission and psychopathological disorders and can be considered as potential genetic components involved in complex feather pecking behavior. It can be concluded that this study has revealed some interesting differences in gene expression between high and low feather pecking groups and helped to approach elucidation of the genetic foundations of feather pecking.

Genome-wide mapping of quantitative trait loci for fatness, fat cell characteristics and fat metabolism in three porcine F2 crosses.

BACKGROUND: QTL affecting fat deposition related performance traits have been considered in several studies and mapped on numerous porcine chromosomes. However, activity of specific enzymes, protein content and cell structure in fat tissue probably depend on a smaller number of genes than traits related to fat content in carcass. Thus, in this work traits related to metabolic and cytological features of back fat tissue and fat related performance traits were investigated in a genome-wide QTL analysis. QTL similarities and differences were examined between three F2 crosses, and between male and female animals. METHODS: A total of 966 F2 animals originating from crosses between Meishan (M), Pietrain (P) and European wild boar (W) were analysed for traits related to fat performance (11), enzymatic activity (9) and number and volume of fat cells (20). Per cross, 216 (MxP), 169 (WxP) and 195 (WxM) genome-wide distributed marker loci were genotyped. QTL mapping was performed separately for each cross in steps of 1 cM and steps were reduced when the distance between loci was shorter. The additive and dominant components of QTL positions were detected stepwise by using a multiple position model. RESULTS: A total of 147 genome-wide significant QTL (76 at P<0.05 and 71 at P<0.01) were detected for the three crosses. Most of the QTL were identified on SSC1 (between 76-78 and 87-90 cM), SSC7 (predominantly in the MHC region) and SSCX (in the vicinity of the gene CAPN6). Additional genome-wide significant QTL were found on SSC8, 12, 13, 14, 16, and 18. In many cases, the QTL are mainly additive and differ between F2 crosses. Many of the QTL profiles possess multiple peaks especially in regions with a high marker density. Sex specific analyses, performed for example on SSC6, SSC7 and SSCX, show that for some traits the positions differ between male and female animals. For the selected traits, the additive and dominant components that were analysed for QTL positions on different chromosomes, explain in combination up to 23% of the total trait variance. CONCLUSIONS: Our results reveal specific and partly new QTL positions across genetically diverse pig crosses. For some of the traits associated with specific enzymes, protein content and cell structure in fat tissue, it is the first time that they are included in a QTL analysis. They provide large-scale information to analyse causative genes and useful data for the pig industry.

Polymorphic microsatellite sites in the PRNP region point to excess of homozygotes in Creutzfeldt-Jakob disease patients.

Polymorphic microsatellite sites within 148 kb of the human prion gene complex, including the genes PRNP, PRND and PRNT, were analysed together with the Codon129 variants regarding 50 CJD (Creutzfeldt-Jakob Disease) patients and 46 non-diseased control persons. Three of the sites (MM03, MM04, Codon129) differed significantly (P<0.05) for their allele frequencies between the two groups--the predominant allele being always more frequent in the CJD group. Deviations from Hardy-Weinberg Equilibrium were mainly obtained in the CJD group--in all cases with a reduction of the observed heterozygosity. The sites MM03, MM04 and Codon129 were also analysed for their haplotypes. The predominant homozygous haplotype combination was more frequently observed in the CJD group (0.875) than in the non-diseased group (0.38). Thus the different polymorphic sites indicate that high CJD disposition is associated with homozygosity in the PRNP gene.

Numerous polymorphic microsatellites in the human prion gene complex (including PRNP, PRND and PRNT).

Microsatellite sites were analysed with DNA screening software by using about 148 kilobases (kb) of the human genomic DNA sequence GenBank accession number (acc. no.) which includes the genes PRNP, PRND and PRNT. Regarding microsatellites (MS) with at least four repeats and base replacements within the repetitive motifs<10%, 127 sites were found. Sixteen of the sites were analysed and nine of them proved to be polymorphic with up to nine alleles per site. Frequencies<0.95 of the predominant allele were observed for all polymorphic sites, and frequencies<0.4 for four sites. Some allelic DNA sequences were not only different in microsatellite repeats but also in flanking regions. Distances between microsatellite sites were in average of 1.2 kb and allow the identification of a number of further informative markers in the prion protein gene complex. The large number of polymorphic sites within a narrow chromosomal interval can be applied to study the origin of alleles as well as the association to the incidence of diseases.