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Animal breeding programs can be improved by genetic markers associated with production and reproduction traits. Reproduction traits are important for economic success of pig production and therefore development of genetic tools for selection is of high interest to pig breeding. In this study our objective was to identify genomic regions as-sociated with fertility traits in two Finnish pig breeds using large scale SNP genotyping and genome wide association analysis and characterization of copy number variations (CNV). Since CNVs are structural variations of the genome they potentially have a large effect on gene expression and protein function. We analyzed 1265 genotyped boars for nine different reproduction traits and identified 46 CNV regions encompassing 13 genes. 11 of the CNV regions were shared between the breeds, 20 were unique to the Finnish Yorkshire and 15 to the Finnish Landrace. The ge-nome wide association (GWAS) analysis identified zero to five reproduction associated genomic regions per trait. Furthermore, we identified 23 genomic regions with 20 candidate genes associated with fertility traits using GWAS analysis. The identified CNV regions were compared against GWAS regions to detect candidate regions with an ef-fect on reproduction traits. This study reports candidate genes and genomic regions within two Finnish pig breeds for reproduction traits, which can be utilized in breeding programs.

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 A 22 Γ 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 ( A 22 Γ and A 22 Γ MAF ). Average diagonal elements of A 22 Γ and A 22 Γ MAF 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.

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.

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 (F-ROH) were used as covariats 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 F-ROH. We detected significant inbreeding depression on IFL. Based on our results, a 10% increase in F-ROH 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 F-ROH 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.

[Background]: Pigs were domesticated independently in Eastern and Western Eurasia early during the agricultural revolution, and have since been transported and traded across the globe. Here, we present a worldwide survey on 60K genome-wide single nucleotide polymorphism (SNP) data for 2093 pigs, including 1839 domestic pigs representing 122 local and commercial breeds, 215 wild boars, and 39 out-group suids, from Asia, Europe, America, Oceania and Africa. The aim of this study was to infer global patterns in pig domestication and diversity related to demography, migration, and selection., [Results]: A deep phylogeographic division reflects the dichotomy between early domestication centers. In the core Eastern and Western domestication regions, Chinese pigs show differentiation between breeds due to geographic isolation, whereas this is less pronounced in European pigs. The inferred European origin of pigs in the Americas, Africa, and Australia reflects European expansion during the sixteenth to nineteenth centuries. Human-mediated introgression, which is due, in particular, to importing Chinese pigs into the UK during the eighteenth and nineteenth centuries, played an important role in the formation of modern pig breeds. Inbreeding levels vary markedly between populations, from almost no runs of homozygosity (ROH) in a number of Asian wild boar populations, to up to 20% of the genome covered by ROH in a number of Southern European breeds. Commercial populations show moderate ROH statistics. For domesticated pigs and wild boars in Asia and Europe, we identified highly differentiated loci that include candidate genes related to muscle and body development, central nervous system, reproduction, and energy balance, which are putatively under artificial selection., [Conclusions]: Key events related to domestication, dispersal, and mixing of pigs from different regions are reflected in the 60K SNP data, including the globalization that has recently become full circle since Chinese pig breeders in the past decades started selecting Western breeds to improve local Chinese pigs. Furthermore, signatures of ongoing and past selection, acting at different times and on different genetic backgrounds, enhance our insight in the mechanism of domestication and selection. The global diversity statistics presented here highlight concerns for maintaining agrodiversity, but also provide a necessary framework for directing genetic conservation., This study is supported by National Production Technology System for the Pig Industry in China (nycytx-008) and Outstanding Talents and Innovation Team of Agricultural Science (2011-81) to LH, AGL2010-14822 and AGL2013-41834-R (Ministry of Economy and Science, Spain) to MPE. LI received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 656697. HJM received funding from the IMAGE project (Horizon 2020, No. 677353).

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

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.

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.

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.

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.

Reproduction traits play an important role in economically viable piglet production and are closely related to the quality and length of the produc- tive life of the sow. A increased removal rate of young sows is undesirable not only because of the associ- ated 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 polymor- phisms within these genes are associated with repro- duction traits in American Yorkshire/Large White and Landrace populations. In this study we evaluated the impact of single polymorphisms (n = 7) in 7 candi- date genes on reproductive efficiency in Finnish York- shire (n = 280) and Landrace (n = 271) populations: IGFBP1, IGFBP2, IGFBP3, IGFBP5, CPTIA (carni- tine O-palmitoyltransferase I), COX2 (PG-endoperox- ide synthase 2, also known as cyclooxgenase-2), and SLC22A5 (organic cation/carnitine transporter 2 (sol- ute 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 polymor- phisms 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 popula- tion, 6 markers were polymorphic, and significant ef- fects 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, pari- ties >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, respec- tively. 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.

Association between pre-eclampsia (PEE1) and the dimethylarginine dimethylaminohydrolase (DDAH) 1 and 2 genes, which play a role in the regulation of nitric oxide synthesis and release, was studied. In a case –control study design single nucleotide polymorphisms (SNPs) were determined at eight sites in the DDAH1 gene and at one site (Pro231Pro) in the DDAH2 gene from 132 women with pre-eclampsia and 112 healthy controls. Three SNPs in the DDAH1 gene were associated with preeclampsia, showing complete linkage disequilibrium with each other, but none of the associations in the allele or genotype data reached statistical significance in either of the genes after the correction for multiple testing. Haplotype frequencies were estimated using a population based on a maximum likelihood method (EM algorithm). Four common DDAH1 haplotypes were present and a significant association of haplotypes H2 and H3 with pre-eclampsia (P 5 0.03) was found. The risk of pre-eclampsia was greatest in individuals (odds ratio: 3.93; 95% confidence interval: 1.54 –9.99) who had two copies of the high-risk haplotypes (H2 or H3). The observed haplotypic association provides the first evidence of the importance of DDAH1 polymorphisms in pre-eclampsia susceptibility.

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.

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.

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.

Sensitivity of segregation analysis for data structure and data transformation was studied using data from two trials in which mice were challenged at three months of age with a cloned isolate of Trypanosoma congolense and survival time was recorded. Data included records from three inbred strains (C57BL/6 (tolerant), A/J, and BALB/c (both susceptible)) and their crosses. Data were standardized and normalized using a modified power transformation. Segregation analysis was applied to both untransformed and transformed data to determine the genetic inheritance of trypanotolerance in these mice. Data from the two trials were analysed separately and combined. Four genetic models were compared; a one locus model, a polygenic model, a mixed model with common variance, and a mixed model with different variances for each major genotype. Even though the separate data sets and the combined data set all supported the hypothesis of a major gene (or a tightly linked cluster of genes) with different variances within each genotype, parameter estimates were highly sensitive to data transformation and several sets of parameter estimates gave similar likelihood values because of high dependency between parameters. Based on the results segregation analysis can be very sensitive to data structure in a crossbreeding design and to data transformation. Interpretation of the results can be misleading if the entire parameter space is not studied carefully.

mpaired migration of primordial germ cells during embryonic development causes hereditary gonadal hypoplasia in both sexes of Northern Finncattle and Swedish Mountain cattle. The affected gonads exhibit a lack of or, in rare cases, a reduced number of germ cells. Most affected animals present left-sided gonadal hypoplasia. However, right-sided and bilateral cases are also found. This type of gonadal hypoplasia prevails in animals with white coat colour. Previous studies indicated that gonadal hypoplasia is inherited in an autosomal recessive fashion with incomplete penetrance. In order to identify genetic regions underlying gonadal hypoplasia, a genome-wide association study (GWAS) and a copy number variation (CNV) analysis were performed with 94 animals, including 21 affected animals, using bovine 777,962 SNP arrays. The GWAS and CNV results revealed two significantly associated regions on bovine chromosomes (BTA) 29 and 6, respectively (P=2.19 x 10-13 and P=5.65 x 10-6). Subsequent cytogenetic and PCR analyses demonstrated that homozygosity of a ~500 kb chromosomal segment translocated from BTA6 to BTA29 (Cs29 allele) is the underlying genetic mechanism responsible for gonadal hypoplasia. The duplicated segment includes the KIT gene that is known to regulate the migration of germ cells and precursors of melanocytes. This duplication is also one of the two translocations associated with colour sidedness in various cattle breeds. ISSN:1932-6203

JID: 100965258; OID: NLM: PMC3248578; 2011/09/05 [received]; 2011/12/02 [accepted]; 2011/12/02 [aheadofprint]; epublish M1 - Journal Article ABSTRACT: BACKGROUND: Male infertility is an increasing problem in all domestic species including man. Localization and identification of genes involved in defects causing male infertility provide valuable information of specific events in sperm development. Sperm development is a complex process, where diploid spermatogonia develop into haploid, highly specialized spermatozoa. Correct expression and function of various genes and their protein products are required for production of fertile sperm. We have identified an infertility defect in Finnish Yorkshire boars caused by spermatogenic arrest. The aim of this study was to locate the disease associated region using genome wide screen with the PorcineSNP60 Beadchip and identify the causal mutation by candidate gene approach. RESULTS: In the Finnish Yorkshire pig population the spermatogenic arrest (SA) defect appears to be of genetic origin and causes severe degeneration of germ cells and total absence of spermatozoa. Genome wide scan with the PorcineSNP60 Beadchip localized the SA defect to porcine chromosome 12 in a 2 Mbp region. Sequencing of a candidate gene Tex14 revealed a 51 bp insertion within exon 27, which caused differential splicing of the exon and created a premature translation stop codon. The expression of Tex14 was markedly down regulated in the testis of a SA affected boar compared to control boars and no protein product was identified by Western blotting. The SA insertion sequence was also found within intron 27 in all analyzed animals, thus the insertion appears to be a possible duplication event. CONCLUSION: In this study we report the identification of a causal mutation for infertility caused by spermatogenic arrest at an early meiotic phase. Our results highlight the role of TEX14 specifically in spermatogenesis and the importance of specific genomic remodeling events as causes for inherited defects.

Background Occurrence of blood and meat inclusions is an internal egg quality defect. Mass candling reveals most of the spots, but because brown eggshell hampers selection in brown chicken lines it has not been possible to eliminate the defect by selection. Estimated frequency of blood and meat inclusions in brown layers is about 18% whereas it is 0.5% in white egg layers. Several factors are known to increase the incidence of this fault: genetic background, low level of vitamin A and/or D, stress or infections, for instance. To study the genetic background of the defect, a mapping population of 1599 F2 hens from a cross of White Rock and Rhode Island Red lines was set up. Results Our histopathological analyses show that blood spots consist of mainly erythrocytes and that meat spots are accumulations of necrotic material. Linkage analysis of 27 chromosomes with 162 microsatellite markers revealed one significant quantitative trait locus (QTL) affecting blood spot and meat spot frequency. We sequenced a fragment of a candidate gene within the region, ZO-2, coding for a tight junction protein. Nine polymorphisms were detected and two of them were included in fine-mapping and association analysis. Fine-mapping defined the QTL result. To further verify the QTL, association analyses were carried out in two independent commercial breeding lines with the marker MCW241 and surrounding SNPs. Association was found mainly in a 0.8 Mb-wide chromosomal area on GGAZ. Conclusions There was good agreement between the location of the QTL region on chromosome Z and the association results in the commercial breeds analyzed. Variations found in tight junction protein ZO-2 and microRNA gga-mir-1556 may predispose egg layers to blood and meat spot defects. This paper describes the first results of detailed QTL analyses of the blood and meat spots trait(s) in chickens.

Background Color and pH of meat measured 24 h post mortem are common selection objectives in pig breeding programs. Several amino acid substitutions in PRKAG3 have been associated with various meat quality traits. In our previous study ASGA0070625, a SNP next to PRKAG3, had the most significant association with meat quality traits in the Finnish Yorkshire. However, the known amino acid substitutions, including I199V, did not show any association. The aims of this study were to characterize further variation in PRKAG3 and its promoter region, and to test the association between these variants and the pH and color of pork meat. Results The data comprised of 220 Finnish Landrace and 230 Finnish Yorkshire artificial insemination boars with progeny information. We sequenced the coding and promoter region of PRKAG3 in these and in three additional wild boars. Genotypes from our previous genome-wide scans were also included in the data. Association between SNPs or haplotypes and meat quality traits (deregressed estimates of breeding values from Finnish national breeding value estimation for pH, color lightness and redness measured from loin or ham) was tested using a linear regression model. Sequencing revealed several novel amino acid substitutions in PRKAG3, including K24E, I41V, K131R, and P134L. Linkage disequilibrium was strong among the novel variants, SNPs in the promoter region and ASGA0070625, especially for the Yorkshire. The strongest associations were observed between ASGA0070625 and the SNPs in the promoter region and pH measured from loin in the Yorkshire and between I199V and pH measured from ham in the Landrace. In contrast, ASGA0070625 was not significantly associated with meat quality traits in the Landrace and I199V not in the Yorkshire. Haplotype analysis showed a significant association between a haplotype consisting of 199I and 24E alleles (or g.-157C or g.-58A alleles in the promoter region) and pH measured from loin and ham in both breeds (P-values varied from 1.72 × 10-4 to 1.80 × 10-8). Conclusions We conclude that haplotype g.-157C - g.-58A - 24E - 199I in PRKAG3 has a positive effect on meat quality in pigs. Our results are readily applicable for marker-assisted selection in pigs.

An immotile short tail sperm defect has recently been identified as a hereditary disorder present within the Finnish Yorkshire pig population. The syndrome is inherited as an autosomal recessive disease exclusively expressed in male individuals as shorter sperm tail length and immotile spermatozoa. Based on the assumption of a recent common origin of the disease-causing mutation, a genome-wide search was performed with 228 evenly spaced microsatellites by homozygosity mapping of affected and unaffected DNA pools. One locus, SW2411 on Chr 16, demonstrated a significantly skewed allele distribution between the two pools. Linkage analysis of five markers in this region mapped the disease-causing gene within a 6-cM confidence interval region with a highest LOD score of 7.7 at marker SW419. It appears that three-marker haplotypes can be used for marker-assisted selection within analyzed pedigrees. Furthermore, future fine mapping may reveal a more precise population-wide associated haplotype and facilitate identification of a new gene affecting sperm tail development.

BACKGROUNDGluten 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.AIMSWe 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.SUBJECTSWe 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.METHODSNon-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.RESULTSEvidence 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.CONCLUSIONSIndependent 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.

Statistical methods to map quantitative trait loci (QTL) in outbred populations are reviewed, extensions and applications to human and plant genetic data are indicated, and areas for further research are identified. Simple and computationally inexpensive methods include (multiple) linear regression of phenotype on marker genotypes and regression of squared phenotypic differences among relative pairs on estimated proportions of identity-by-descent at a locus. These methods are less suited for genetic parameter estimation in outbred populations but allow the determination of test statistic distributions via simulation or data permutation; however, further inferences including confidence intervals of QTL location require the use of Monte Carlo or bootstrap sampling techniques. A method which is intermediate in computational requirements is residual maximum likelihood (REML) with a covariance matrix of random QTL effects conditional on information from multiple linked markers. Testing for the number of QTLs on a chromosome is difficult in a classical framework. The computationally most demanding methods are maximum likelihood and Bayesian analysis, which take account of the distribution of multilocus marker-QTL genotypes on a pedigree and permit investigators to fit different models of variation at the QTL. The Bayesian analysis includes the number of QTLS on a chromosome as an unknown.

Puissance et estimation des parametres dans l'analyse de segregation complexe avec un modele a nombre fini de locus. La puissance de l'analyse de segregation et l'estimation des parametres ont ete etudiees sur des familles nucleaires independantes pour un caractere quantitatif determine soit par un nombre fini de locus soit selon un modele d'heredite mixte, impliquant un gene majeur et un residu polygenique infinitesimal. Dans le modele a nombre fini de locus, le nombre de locus suppose etait de dix et leurs effets suivaient une loi de distribution geometrique. En outre, la possibilite de liaison genetique entre un locus majeur et d'autres locus etait envisagee. Deux methodes d'analyse de segregation ont ete comparees, utilisant soit un modele d'heredite mixte, soit un modele d'heredite avec un nombre fini de locus. Les deux methodes statistiques presentaient des puissances similaires pour detecter un gene majeur et estimer les parametres correspondants. A l'exception toutefois d'une situation avec deux locus majeurs ayant le meme effet sur le phenotype. Le modele a heredite mixte avait alors une puissance superieure a celle du modele a nombre fini de locus, mais les estimees des parametres a partir du modele mixte etaient plus biaisees que celles du modele a nombre fini de locus. L'analyse de segregation etait plus puissante pour detecter un gene majeur dans le cas d'un caractere determine par un nombre fini de locus que dans une situation d'heredite mixte. Un gene majeur lie a un autre gene etait plus difficile a detecter qu'en l'absence de liaison genetique. La segregation de deux genes majeurs creait des biais d'estimation. Les biais etaient encore accrus en cas de liaison genetique quand les parents n'etaient pas tires d'une population en equilibre gametique pour les deux locus majeurs.

Background Male infertility is an increasing problem in all domestic species including man. Localization and identification of genes involved in defects causing male infertility provide valuable information of specific events in sperm development. Correct condensation of the sperm head and development of the acrosome are required for fertile sperm. In the Finnish Yorkshire pig population a knobbed acrosome defect (KAD) has been reported which appears to be of genetic origin. In previous studies we have shown that a large number of affected spermatozoa have a cystic swelling anterior to the apical part of the acrosome. Results Characterization of the knobbed acrosome affected sperm revealed that both the acrosomal granules and chromatin are affected. This type of KAD appears to be a previously unknown and serious form of the defect. A genome wide scan with PorcineSNP60 Genotyping BeadChip defined the KAD associated region within 0.7 Mbp on porcine chromosome 15. Two genes, STK17b and HECW2, located within this region were sequenced. The expression of these genes appeared comparable in KA-affected and control boars. The known function of HECW2 in acrosome development highlighted this gene as a good candidate responsible for the KAD. One nonsynonymous SNP was identified within the HECW2 gene. However, as this mutation was found in homozygous state in individuals with normal sperm, this is not likely to be the causal mutation. Conclusions In this study we identified two candidate genes for a severe defect affecting both the sperm acrosome and chromatin that causes infertility. One of these genes, HECW2, plays an important role in ubiquitination, a prerequisite for chromatin remodelling and acrosome formation, highlighting the involvement of this gene in the knobbed acrosome defect and male infertility.

Recent developments in sequencing methods have enabled whole genome sequencing of several species and the available sequence information has allowed the development of high throughput genotyping chips. However, these genotyping methods require high quality DNA. The possibility to genotype samples based on DNA from non-invasive sources would permit retrospective genotyping of previously collected samples and also facilitate the analysis of large populations e.g. for genomic selection. In this study we have developed and evaluated different DNA preparation methods from porcine hair root follicles for high throughput genotyping with the PorcineSNP60 Genotyping BeadChip (Illumina). We describe a method for DNA extraction from porcine hair root samples, which produces results from high throughput genotyping with the same high degree of accuracy as previously reported for DNA extracted from sperm, blood or tissue samples. This method was used for the genotyping of 273 hair follicle samples. When the DNA concentration was > 30 ng/ìl all samples had the same high call rate ( > 99%) as sperm samples confirming the robustness of this DNA extraction method for high throughput genotyping. Our data also establishes the suitability of the PorcineSNP60 BeadChip for genotyping the Finnish Landrace population., Viime aikoina uuden sukupolven sekvensointimenetelmät ovat mahdollistaneet useiden lajien koko genomin sekvensoinnin. Sekvenssitietoon perustuen on kehitetty genotyypityssiruja, joiden käyttö kuitenkin vaatii laadukasta DNA:ta. Perinteisesti DNA:n eristämiseen on käytetty veri-, sperma- tai kudosnäytteitä, joiden kerääminen kuitenkin on kallista, aikaa vievää ja stressaavaa eläimille. Karvanäytteitä on aiemmin käytetty yksittäisten geenimerkkien genotyypitykseen, mutta heikko DNA:n laatu on estänyt luotettavan sirugenotyypityksen karvanäytteistä. Mahdollisuus käyttää karvatupesta eristettyä DNA:ta sirutyypityksiin mahdollistaisi jo olemassa olevien näytteiden ja laajojen aineistojen genotyypityksen sirutekniikalla. Tässä tutkimuksessa olemme kehittäneet ja testanneet eri menetelmiä laadukkaan DNA:n eristämiseksi sikojen karvatupesta ja analysoitavaksi PorcineSNP60 Genotyping BeadChip-genotyypityssirulla (Illumina). Parhaan DNA konsentraation ja puhtauden antanut menetelmä valittiin 273n karvanäytteen analysointiin. Kun DNAn konsentraatio oli yli 30ng/µl, karvatupesta eristetty DNA tuotti sirugenotyypityksessä yhtä luotettavia tuloksia kuin spermasta eristetty DNA (onnistumisprosentti >99%). Tulokset myös todistavat PorcineSNP60-genotyypityssirun sopivuuden suomalaisen maatiaissikapopulaation analysointiin.

Type 2 diabetes (T2D) is a common, polygenic chronic disease with high heritability. The purpose of this whole-genome association study was to discover novel T2D-associated genes. We genotyped 500 familial cases and 497 controls with >300,000 HapMap-derived tagging single-nucleotide-polymorphism (SNP) markers. When a stringent statistical correction for multiple testing was used, the only significant SNP was at TCF7L2, which has already been discovered and confirmed as a T2D-susceptibility gene. For a replication study, we selected 10 SNPs in six chromosomal regions with the strongest association (singly or as part of a haplotype) for retesting in an independent case-control set including 2,573 T2D cases and 2,776 controls. The most significant replicated result was found at the AHI1-LOC441171 gene region.

Background: One of the most commonly used quality measurements of pork is pH measured 24 h after slaughter. The most probable mode of inheritance for this trait is oligogenic with several known major genes, such as PRKAG3. In this study, we used whole-genome SNP genotypes of over 700 AI boars; after a quality check, 42,385 SNPs remained for association analysis. All the boars were purebred Finnish Yorkshire. To account for relatedness of the animals, a pedigree-based relationship matrix was used in a mixed linear model to test the effect of SNPs on pH measured from loin. A bioinformatics analysis was performed to identify the most promising genes in the significant regions related to meat quality. Results: Genome-wide association study (GWAS) revealed three significant chromosomal regions: one on chromosome 3 (39.9 Mb-40.1 Mb) and two on chromosome 15 (58.5 Mb-60.5 Mb and 132 Mb-135 Mb including PRKAG3). A conditional analysis with a significant SNP in the PRKAG3 region, MARC0083357, as a covariate in the model retained the significant SNPs on chromosome 3. Even though linkage disequilibrium was relatively high over a long distance between MARC0083357 and other significant SNPs on chromosome 15, some SNPs retained their significance in the conditional analysis, even in the vicinity of PRKAG3. The significant regions harbored several genes, including two genes involved in cyclic AMP (cAMP) signaling: ADCY9 and CREBBP. Based on functional and transcription factor-gene networks, the most promising candidate genes for meat pH are ADCY9, CREBBP, TRAP1, NRG1, PRKAG3, VIL1, TNS1, and IGFBP5, and the key transcription factors related to these genes are HNF4A, PPARG, and Nkx2-5. Conclusions: Based on SNP association, pathway, and transcription factor analysis, we were able to identify several genes with potential to control muscle cell homeostasis and meat quality. The associated SNPs can be used in selection for better pork. We also showed that post-GWAS analysis reveals important information about the genes' potential role on meat quality. The gained information can be used in later functional studies.

A Bayesian method for mapping linked quantitative trait loci (QTL) using multiple linked genetic markers is presented. Parameter estimation and hypothesis testing was implemented via Markov chain Monte Carlo (MCMC) algorithms. Parameters included were allele frequencies and substitution effects for two biallelic QTL, map positions of the QTL and markers, allele frequencies of the markers, and polygenic and residual variances. Missing data were polygenic effects and multi-locus marker-QTL genotypes. Three different MCMC schemes for testing the presence of a single or two linked QTL on the chromosome were compared. The first approach includes a model indicator variable representing two unlinked QTL affecting the trait, one linked and one unlinked QTL, or both QTL linked with the markers. The second approach incorporates an indicator variable for each QTL into the model for phenotype, allowing or not allowing for a substitution effect of a QTL on phenotype, and the third approach is based on model determination by reversible jump MCMC. Methods were evaluated empirically by analyzing simulated granddaughter designs. All methods identified correctly a second, linked QTL and did not reject the one-QTL model when there was only a single QTL and no additional or an unlinked QTL.

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.

Quantitative trait loci (QTL) affecting milk production and health of dairy cattle were mapped in a very large Holstein granddaughter design. The analysis included 1794 sons of 14 sires and 206 genetic markers distributed across all 29 autosomes and flanking an estimated 2497 autosomal cM using Kosambi's mapping function. All families were analyzed jointly with least-squares (LS) and variance components (VC) methods. A total of 6 QTL exceeding approximate experiment-wise significance thresholds, 24 QTL exceeding suggestive thresholds, and 34 QTL exceeding chromosome-wise thresholds were identified. Significance thresholds were determined via data permutation (for LS analysis) and chi-square distribution (for VC analysis). The average bootstrap confidence interval for the experiment-wise significant QTL was 48 cM. Some chromosomes harbored QTL affecting several traits, and these were always in coupling phase, defined by consistency with genetic correlations among traits. Chromosome 17 likely harbors 2 QTL affecting milk yield, and some other chromosomes showed some evidence for 2 linked QTL affecting the same trait. In each of these cases, the 2 QTL were in repulsion phase in those families appearing to be heterozygous for both QTL, a finding which supports the build-up of linkage disequilibrium due to selection.

Background Good genetic progress for pig reproduction traits has been achieved using a quantitative genetics-based multi-trait BLUP evaluation system. At present, whole-genome single nucleotide polymorphisms (SNP) panels provide a new tool for pig selection. The purpose of this study was to identify SNP associated with reproduction traits in the Finnish Landrace pig breed using the Illumina PorcineSNP60 BeadChip. Methods Association of each SNP with different traits was tested with a weighted linear model, using SNP genotype as a covariate and animal as a random variable. Deregressed estimated breeding values of the progeny tested boars were used as the dependent variable and weights were based on their reliabilities. Statistical significance of the associations was based on Bonferroni-corrected P-values. Results Deregressed estimated breeding values were available for 328 genotyped boars. Of the 62 163 SNP in the chip, 57 868 SNP had a call rate > 0.9 and 7 632 SNP were monomorphic. Statistically significant results (P-value < 2.0E-06) were obtained for total number of piglets born in first and later parities and piglet mortality between birth and weaning in later parity, and suggestive associations (P-value < 4.0E-06) for piglet mortality between birth and weaning in first parity, number of stillborn piglets in later parity, first farrowing interval and second farrowing interval. Two of the statistically significant regions for total number of piglets born in first and later parities are located on chromosome 9 around 95 and 79 Mb. The estimated SNP effect in these regions was approximately one piglet between the two homozygote classes. By combining the two most significant SNP in these regions, favourable double homozygote animals are expected to have 1.3 piglets (P-value = 1.69E-08) more than unfavourable double homozygote animals. A region on chromosome 9 (66 Mb) was statistically significant for piglet mortality between birth and weaning in later parity (0.44 piglets between homozygotes, P-value = 6.94E-08). Conclusions Three separate regions on chromosome 9 gave significant results for litter size and pig mortality. The frequencies of favourable alleles of the significant SNP are moderate in the Finnish Landrace population and these SNP are thus valuable candidates for possible marker-assisted selection.

Information on multiple linked genetic markers was used in a Bayesian method for the statistical mapping of quantitative trait loci (QTL). Bayesian parameter estimation and hypothesis testing were implemented via Markov chain Monte Carlo algorithms. Variables sampled were the augmented data (marker-QTL genotypes, polygenic effects), an indicator variable for linkage or nonlinkage, and the parameters. The parameter vector included allele frequencies at the markers and the QTL, map distances of the markers and the QTL, QTL substitution effect, and polygenic and residual variances. The criterion for QTL detection was the marginal posterior probability of a QTL being located on the chromosome carrying the markers, The method was evaluated empirically by analyzing simulated granddaughter designs consisting of 2000 sons, 20 related sires, and their ancestors.