Review: Long non-coding RNA in livestock.

Less than 2% of mammalian genomes code for proteins, but 'the majority of its bases can be found in primary transcripts' - a phenomenon termed the pervasive transcription, which was first reported in 2007. Even though most of the transcripts do not code for proteins, they play a variety of biological functions, with regulation of gene expression appearing as the most common one. Those transcripts are divided into two groups based on their length: small non-coding RNAs, which are maximally 200 bp long, and long non-coding RNAs (lncRNAs), which are longer than 200 nucleotides. The advances in next-generation sequencing methods provided a new possibility of investigating the full set of RNA molecules in the cell. In this review, we summarized the current state of knowledge on lncRNAs in three major livestock species - Sus scrofa, Bos taurus and Gallus gallus, based on the literature and the content of biological databases. In the NONCODE database, the largest number of identified lncRNA transcripts is available for pigs, but cattle have the largest number of lncRNA genes. Poultry is represented by less than a half of records. Genomic annotation of lncRNAs showed that the majority of them are assigned to introns (pig, poultry) or intergenic (cattle). The comparison with well-annotated human and mouse genomes indicates that such annotation is a result of lack of proper lncRNA annotation data. Since lncRNAs play an important role in genomic studies, their characterization in farm animals' genomes is critical in bridging the gap between genotype and phenotype.

Two-stage genome-wide association study for the identification of causal variants underlying hoof disorders in cattle.

Feet and legs disorders influence dairy cattle breeding by their effect on animal welfare, economic losses due to lower production and fertility, costs of treatment, and problems with herd management. In our study, we estimated heritabilities and performed a 2-step GWAS for 3 traits describing hoof health: hoof health status defined by a veterinarian (HSV), hoof health status defined by a claw trimmer (HSC), and the total number of hoof disorders (NHD), scored in 1,998 Fleckvieh and 979 Braunvieh cows. The individuals were genotyped with a high-density (HD) panel consisting of 76,934 SNP. For significant genomic regions, the SNP information was enhanced by SNP imputed from the whole-genome sequence of Fleckvieh and Braunvieh bulls from the 1000 Bulls Genome project. The heritabilities were estimated to be 0.035 for HSV, 0.249 for HSC, and 0.279 for NHD. Based on the first-stage GWAS with SNP from the HD panel, 7 significant genomic regions on 6 chromosomes were defined: (1) 120 SNP spanning 15,522 bp on BTA1, including the TOPBP1 gene; (2) 4,139 SNP spanning 1,426,046 bp on BTA7, including the RIOK2 and RGMB genes; (3) 167 SNP spanning 167,352 bp on BTA13, including the C13H20orf194 gene; (4) 2 regions on BTA14, one harboring 1,071 SNP spanning 380,024 bp, including RRM2B and NCALD, and the other comprising 632 SNP spanning 385,111 bp, including STK3; (5) 328 SNP on BTA15, spanning 235,567 bp between FAM168A and PLEKHB1; and (6) 1,549 SNP on BTA22, spanning 596,101 bp in the neighborhood of PTPRG. Then, we conducted a second-stage GWAS based on SNP from whole-genome sequences within the significant regions obtained in the first stage of the analysis. For HSV, the highest additive effect was estimated for 23 SNP located within a region on BTA15, close to FAM168A, corresponding to a predicted gene sequence. For HSC, the highest additive effect was attributed to 44 SNP located within a region of BTA22 corresponding to 4 predicted gene sequences, with rs135082893 within a sequence encoding a microRNA. Another potential causal mutation for HSC was rs134142607 on BTA13, within the exon of C13H20orf194. For NHD, 33 SNP with the highest estimated effect were located on BTA7 within a region of a predicted gene positioned between RIOK2 and RGMB. On BTA14, all significant SNP were located in introns of STK3, which is responsible for the "abnormal gait" phenotype in mice.

The genetic background of clinical mastitis in Holstein-Friesian cattle.

Mastitis is an inflammatory disease of the mammary gland, which has a significant economic impact and is an animal welfare concern. This work examined the association between single nucleotide polymorphisms (SNPs) and copy number variations (CNVs) with the incidence of clinical mastitis (CM). Using information from 16 half-sib pairs of Holstein-Friesian cows (32 animals in total) we searched for genomic regions that differed between a healthy (no incidence of CM) and a mastitis-prone (multiple incidences of CM) half-sib. Three cows with average sequence depth of coverage below 10 were excluded, which left 13 half-sib pairs available for comparisons. In total, 191 CNV regions were identified, which were deleted in a mastitis-prone cow, but present in its healthy half-sib and overlapped in at least nine half-sib pairs. These regions overlapped with exons of 46 genes, among which APP (BTA1), FOXL2 (BTA1), SSFA2 (BTA2), OTUD3 (BTA2), ADORA2A (BTA17), TXNRD2 (BTA17) and NDUFS6 (BTA20) have been reported to influence CM. Moreover, two duplicated CNV regions present in nine healthy individuals and absent in their mastitis-affected half-sibs overlapped with exons of a cholinergic receptor nicotinic α 10 subunit on BTA15 and a novel gene (ENSBTAG00000008519) on BTA27. One CNV region deleted in nine mastitis-affected sibs overlapped with two neighbouring long non-coding RNA sequences located on BTA12. Single nucleotide polymorphisms with differential genotypes between a healthy and a mastitis-affected sib included 17 polymorphisms with alternate alleles in eight affected and healthy half-sib families. Three of these SNPs were located introns of genes: MET (BTA04), RNF122 (BTA27) and WRN (BTA27). In summary, structural polymorphisms in form of CNVs, putatively play a role in susceptibility to CM. Specifically, sequence deletions have a greater effect on reducing resistance against mastitis, than sequence duplications have on increasing resistance against the disease.

Landscape of copy number variations in Bos taurus: individual - and inter-breed variability.

BACKGROUND: The number of studies of Copy Number Variation in cattle has increased in recent years. This has been prompted by the increased availability of data on polymorphisms and their relationship with phenotypes. In addition, livestock species are good models for some human phenotypes. In the present study, we described the landscape of CNV driven genetic variation in a large population of 146 individuals representing 13 cattle breeds, using whole genome DNA sequence. RESULTS: A highly significant variation among all individuals and within each breed was observed in the number of duplications (P < 10-15) and in the number of deletions (P < 10-15). We also observed significant differences between breeds for duplication (P = 0.01932) and deletion (P = 0.01006) counts. The same variation CNV length - inter-individual and inter-breed differences were significant for duplications (P < 10-15) and deletions (P < 10-15). Moreover, breed-specific variants were identified, with the largest proportion of breed-specific duplications (9.57%) found for Fleckvieh and breed-specific deletions found for Brown Swiss (5.00%). Such breed-specific CNVs were predominantly located in intragenic regions, however in Simmental, one deletion present in five individuals was found in the coding sequence of a novel gene ENSBTAG00000000688 on chromosome 18. In Brown Swiss, Norwegian Red and Simmental breed-specific deletions were located within KIT and MC1R genes, which are responsible for a coat colour. The functional annotation of coding regions underlying the breed-specific CNVs showed that in Norwegian Red, Guernsey, and Simmental significantly under- and overrepresented GO terms were related to chemical stimulus involved in sensory perception of smell and the KEGG pathways for olfactory transduction. In addition, specifically for the Norwegian Red breed, the dopaminergic synapse KEGG pathway was significantly enriched within deleted parts of the genome. CONCLUSIONS: The CNV landscape in Bos taurus genome revealed by this study was highly complex, with inter-breed differences, but also a significant variation within breeds. The former, may explain some of the phenotypic differences among analysed breeds, and the latter contributes to within-breed variation available for selection.

Differences between horse selection based on two forms of osteochondrosis in fetlock.

Horses lose potential opportunities because of health problems. Available breeding strategies are not effective enough, probably also because of the different definition used and its genetic usefulness. The aim of the study was to compare the genetic background estimated by the genome-wide association study (GWAS) for osteochondrosis using two different scaling osteochondrosis (OC)/healthy and osteochondrosis dissecans (OCD)/healthy systems for evaluating the disease status of investigated fetlock joints. Two hundred one Warmblood horses trained for performance tests (87 stallions and 114 mares) were phenotyped and genotyped. Four fetlock x-ray images per horse were collected using the RTG Girth HF 80 and Vet Scan ray 3600. The DNA of each horse was genotyped using the BeadChip 70K. To identify SNPs that significantly affect the probability of osteochondrosis, two different methods were applied: the Cochran-Armitage test based on an additive mode of inheritance and logistic regression. The genetic background for osteochondrosis, expressed in the number of SNPs found with significant associations with osteochondrosis, was higher by evaluation in the scale of OCD/healthy horses (16 SNPs on several chromosomes mainly on the ECA1 and ECA10) than OC/healthy (2 SNPs on the ECA15 and one SNP on the ECA10). Detailed definition of osteochondrosis is needed in breeding and in veterinary practice. The genetic background for osteochondrosis and osteochondrosis dissecans seems not the same. Suggestive SNPs could be the candidate markers for osteochondrosis but should be checked on a larger population before usage.

Analysis of copy number variations in Holstein-Friesian cow genomes based on whole-genome sequence data.

Thirty-two whole genome DNA sequences of cows were analyzed to evaluate inter-individual variability in the distribution and length of copy number variations (CNV) and to functionally annotate CNV breakpoints. The total number of deletions per individual varied between 9,731 and 15,051, whereas the number of duplications was between 1,694 and 5,187. Most of the deletions (81%) and duplications (86%) were unique to a single cow. No relation between the pattern of variant sharing and a family relationship or disease status was found. The animal-averaged length of deletions was from 5,234 to 9,145 bp and the average length of duplications was between 7,254 and 8,843 bp. Highly significant inter-individual variation in length and number of CNV was detected for both deletions and duplications. The majority of deletion and duplication breakpoints were located in intergenic regions and introns, whereas fewer were identified in noncoding transcripts and splice regions. Only 1.35 and 0.79% of the deletion and duplication breakpoints were observed within coding regions. A gene with the highest number of deletion breakpoints codes for protein kinase cGMP-dependent type I, whereas the T-cell receptor α constant gene had the most duplication breakpoints. The functional annotation of genes with the largest incidence of deletion/duplication breakpoints identified 87/112 Kyoto Encyclopedia of Genes and Genomes pathways, but none of the pathways were significantly enriched or depleted with breakpoints. The analysis of Gene Ontology (GO) terms revealed that a cluster with the highest enrichment score among genes with many deletion breakpoints was represented by GO terms related to ion transport, whereas the GO term cluster mostly enriched among the genes with many duplication breakpoints was related to binding of macromolecules. Furthermore, when considering the number of deletion breakpoints per gene functional category, no significant differences were observed between the "housekeeping" and "strong selection" categories, but genes representing the "low selection pressure" group showed a significantly higher number of breakpoints.

Comparison of significant single nucleotide polymorphisms selections in GWAS for complex traits.

The goal of this study was to compare significant SNP selection approaches in the context of complex traits based on SNP estimates obtained by models: a model fitting a single SNP (M1), a model fitting a single SNP and a random polygenic effect (M2), the nonparametric CAR score (M3), a SNP-BLUP model with random effects of all SNPs fitted simultaneously (M4). There were 46,267 SNPs tested in a population of 2601 Holstein Friesian bulls, four traits (milk and fat yields, somatic cell score, non-return rate for heifers) were considered. The numbers of SNPs selected as significant differed among models. M1 selected a very large number of SNPs, except for a NRH in which no SNPs were significant. M2 and M3 both selected similar and low number of SNPs for each trait. M4 selected more SNPs than M2 and M3. Considering linkage disequilibrium between SNPs, for MY M2 and M3 selected SNPs more highly correlated with each other than in the case of M4, while for FY M3 selection contained more correlated SNPs than M2 and M4. In conclusion, if the research interest is to identify SNPs not only with strong, but also with moderate effects on a complex trait a multiple-SNP model is recommended. Such models are capable of accounting for at least a part of linkage disequilibrium between SNPs through the design matrix of SNP effects. Functional annotation of SNPs significant in M4 reveals good correspondence between selected polymorphisms and functional information as well as with QTL mapping results.

Review of alignment and SNP calling algorithms for next-generation sequencing data.

Application of the massive parallel sequencing technology has become one of the most important issues in life sciences. Therefore, it was crucial to develop bioinformatics tools for next-generation sequencing (NGS) data processing. Currently, two of the most significant tasks include alignment to a reference genome and detection of single nucleotide polymorphisms (SNPs). In many types of genomic analyses, great numbers of reads need to be mapped to the reference genome; therefore, selection of the aligner is an essential step in NGS pipelines. Two main algorithms-suffix tries and hash tables-have been introduced for this purpose. Suffix array-based aligners are memory-efficient and work faster than hash-based aligners, but they are less accurate. In contrast, hash table algorithms tend to be slower, but more sensitive. SNP and genotype callers may also be divided into two main different approaches: heuristic and probabilistic methods. A variety of software has been subsequently developed over the past several years. In this paper, we briefly review the current development of NGS data processing algorithms and present the available software.

Genome-wide association study for semen production traits in Holstein-Friesian bulls.

Identifying genomic regions, particularly individual genes associated with semen quality traits, may be very important for improving sire fertility via selective breeding. The aim of the study was to estimate (co)variance components and effects of single nucleotide polymorphisms (SNP) from the Illumina BovineSNP50 BeadChip (Illumina, San Diego, CA) on semen production traits and to find candidate genes for these traits. The analyzed data set originates from the Polish Holstein-Friesian dairy cattle population and consists of 1,212 bulls kept at 4 artificial insemination stations. For each bull, 5 semen production traits were collected: sperm concentration, semen volume, number of spermatozoa, motility, and motility score. A multitrait mixed model was used to estimate genetic parameters. The parameters obtained were used to estimate SNP effects for each trait separately by the mixed model, which is used in the Polish direct genomic value project. Additionally, genes located in the vicinity of significant SNP were selected as candidate genes. For motility, 20 genome-wide significant SNP, located on 12 autosomes, were identified. For sperm concentration, we found 7 significant SNP: 3 on chromosome X, and 1 on chromosomes 1, 6, 23, and 24. For semen volume and motility score, 3 and 1 significant SNP were detected, respectively. All these SNP were located on chromosome X. For the number of spermatozoa, 12 significant SNP were observed. Six SNP were located on chromosome X, 3 on chromosome 8, and 1 on chromosomes 2, 7, and 16. This study clearly indicated a key role of the X chromosome in the determination of semen quality and emphasized that including such traits into genetic evaluation should be strongly considered.

Identification of candidate genes and mutations in QTL regions for immune responses in chicken.

There are two categories of immune responses - innate and adaptive immunity - both having polygenic backgrounds and a significant environmental component. In our study, adaptive immunity was represented by the specific antibody response toward keyhole limpet hemocyanin (KLH); innate immunity was represented by natural antibodies toward lipopolysaccharide (LPS) and lipoteichoic acid (LTA). Defining genetic bases of immune responses leads from defining quantitative trait loci (QTL) toward a single mutation responsible for variation in the phenotypic trait. The goal of the reported study was to define candidate genes and mutations for the immune traits of interest in chicken by performing an association study of SNPs located in candidate genes defined in QTL regions. Candidate genes and SNPs in QTL regions were selected in silico. SNP association was based on a custom SNP panel, GoldenGate genotyping assay (Illumina) and two statistical models: random mixed model and CAR score. The most significant SNP for immune response toward KLH was located in the JMJD6 gene located on GGA18. Four SNPs in candidate genes FOXJ1 (GGA18), EPHB1 (GGA9), PTGER4 (GGAZ) and PRKCB (GGA14) showed association with natural antibodies for LPS. A single SNP in ITGB4 (GGA18) was associated with natural antibodies for LTA. All associated SNPs mentioned above showed additive effects.

Modelling effects of candidate genes on complex traits as variables over time.

In this study, changes in gene effects for milk production traits were analysed over time. Such changes can be expected by investigating daily milk production yields, which increase during the early phase of lactation and then decrease. Moreover, additive polygenic effects on milk production traits estimated in other studies differed throughout the 305 days of lactation, clearly indicating changes in the genetic determination of milk production throughout this period. Our study focused on particular candidate genes known to affect milk production traits and on the estimation of potential changes in the magnitude of their effects over time. With two independent data sets from Holstein-Friesian and Jersey breeds, we show that the effects of the DGAT1:p.Lys232Ala polymorphism on fat and protein content in milk change during lactation. The other candidate genes considered in this study (leptin receptor, leptin and butyrophilin, subfamily 1, member A1) exhibited effects that vary across time, but these could be observed in only one of the breeds. Longitudinal modelling of SNP effects enables more precise description of the genetic background underlying the variation of complex traits. A gene that changes the magnitude or even the sign of its effect cannot be detected by a time-averaged model. This was particularly evident when analysing the effect of butyrophilin, missed by many previous studies, which considered butyrophilin's effect as constant over time.

Population parameters incorporated into genome-wide tagSNP selection.

Single nucleotide polymorphisms (SNPs) are the most widespread source of variation in genomes. While the very large number of SNPs allows for a very precise description of genetic variation, it impedes data processing and significantly increases analysis time. Many of the SNPs located close to each other frequently carry the same or similar information. This problem can be solved by selecting the most informative SNPs (tagSNPs) using linkage disequilibrium information by identifying a set of tagSNPs representative for a chromosome fragment. The goal of this study is to check whether the genetic structure of a population, expressed by relationship and inbreeding coefficients, affects tagSNP selection. Six subsets of 450 bulls are selected out of the 1228 Polish Holstein-Friesian bulls genotyped by the Illumina BovineSNP50 Bead Chip. TagSNPs are selected for each of the subsets, as well as for the whole data set. The average reduction of the SNP number is 77.2% and is very similar in each sub-population. Differences in tagSNP selection between sub-populations are small. On average, 93.88% of the tagSNPs overlap between subsets. The study showed that differences in the genetic structure of the reference population have little influence on tagSNP selection.

Modelling QTL effect on BTA06 using random regression test day models.

In statistical models, a quantitative trait locus (QTL) effect has been incorporated either as a fixed or as a random term, but, up to now, it has been mainly considered as a time-independent variable. However, for traits recorded repeatedly, it is very interesting to investigate the variation of QTL over time. The major goal of this study was to estimate the position and effect of QTL for milk, fat, protein yields and for somatic cell score based on test day records, while testing whether the effects are constant or variable throughout lactation. The analysed data consisted of 23 paternal half-sib families (716 daughters of 23 sires) of Chinese Holstein-Friesian cattle genotyped at 14 microsatellites located in the area of the casein loci on BTA6. A sequence of three models was used: (i) a lactation model, (ii) a random regression model with a QTL constant in time and (iii) a random regression model with a QTL variable in time. The results showed that, for each production trait, at least one significant QTL exists. For milk and protein yields, the QTL effect was variable in time, while for fat yield, each of the three models resulted in a significant QTL effect. When a QTL is incorporated into a model as a constant over time, its effect is averaged over lactation stages and may, thereby, be difficult or even impossible to be detected. Our results showed that, in such a situation, only a longitudinal model is able to identify loci significantly influencing trait variation.

Statistical modelling of growth using a mixed model with orthogonal polynomials.

In statistical modelling, the effects of single-nucleotide polymorphisms (SNPs) are often regarded as time-independent. However, for traits recorded repeatedly, it is very interesting to investigate the behaviour of gene effects over time. In the analysis, simulated data from the 13th QTL-MAS Workshop (Wageningen, The Netherlands, April 2009) was used and the major goal was the modelling of genetic effects as time-dependent. For this purpose, a mixed model which describes each effect using the third-order Legendre orthogonal polynomials, in order to account for the correlation between consecutive measurements, is fitted. In this model, SNPs are modelled as fixed, while the environment is modelled as random effects. The maximum likelihood estimates of model parameters are obtained by the expectation-maximisation (EM) algorithm and the significance of the additive SNP effects is based on the likelihood ratio test, with p-values corrected for multiple testing. For each significant SNP, the percentage of the total variance contributed by this SNP is calculated. Moreover, by using a model which simultaneously incorporates effects of all of the SNPs, the prediction of future yields is conducted. As a result, 179 from the total of 453 SNPs covering 16 out of 18 true quantitative trait loci (QTL) were selected. The correlation between predicted and true breeding values was 0.73 for the data set with all SNPs and 0.84 for the data set with selected SNPs. In conclusion, we showed that a longitudinal approach allows for estimating changes of the variance contributed by each SNP over time and demonstrated that, for prediction, the pre-selection of SNPs plays an important role.

Testing candidate gene effects on milk production traits in dairy cattle under various parameterizations and modes of inheritance.

The major objectives of this study were 1) to assess the statistical properties of models commonly used for the estimation of single nucleotide polymorphism (SNP) effects under the assumption of various modes of inheritance and various parameterizations of SNP genotypes using simulated data, and 2) to compare effects of the selected polymorphisms located within butyrophilin (BTN1A1), diacylglycerol acyltransferase 1 (DGAT1), leptin (LEP), and leptin receptor (LEPR) candidate genes on milk production traits using data from 2 dairy cattle breeds (190 Jersey cows and 475 Polish Holstein-Friesian cows). Simulation results showed that type I error and power were not dependent on the assumed parameterization, but differences were observed regarding confidence intervals of estimated SNP effects. In the presence of epistasis, correct confidence intervals for all (epistatic and nonepistatic) SNP and all modes of inheritance were provided only by the parameterization proposed by C. H. Kao and Z. B. Zeng in 2002. However, if no dominance effect was included in the model, confidence intervals for SNP effects were correct for all parameterizations. Results based on real data showed that for both breeds the additive effects of polymorphisms were generally similar, except for LEPR, which had a different allele associated with increased fat content in Holstein-Friesians than in Jerseys. In both breeds, DGAT1 had the largest additive effect of the polymorphisms considered, but its effect on most milk traits was more pronounced in Jerseys than in Holstein-Friesians. Evidence of epistasis was found between LEPR and DGAT1, as well as between LEPR and BTN1A1, but only for milk content traits and only in the Holstein-Friesian breed. There was also more evidence for dominance in the Holstein-Friesian breed than in the Jersey breed.

Additive effects of 19 porcine SNPs on growth rate, meat content and selection index.

A total of 306 boars (108 Large White and 198 Landrace) were genotyped for 52 candidate SNPs to determine which of the polymorphisms influence growth rate, meat content and selection index. The effects of SNPs were estimated by a mixed linear model including a random additive polygenic animal effect, fixed effects of SNPs including additive, and pairwise additive-by-additive epistases, year*season of birth, breed and RYR1 genotype. In order to estimate all possible pairwise SNP combinations without overparameterising the model a stochastic approach was adopted. A total of 1 350 replications of the model were generated, each containing five randomly selected SNPs. The final estimates of the fixed effects of the model equaled an average out of the replications. The hypothesis of a nonzero effect of SNP was tested by the Wald test. Among 4 257 estimates calculated, many significant (P<0.01), but mostly minor effects (below 1 phenotypic standard deviation) were recorded. The selected SNPs will be further investigated to determine which may be used in MAS.

Statistical modeling of candidate gene effects on milk production traits in dairy cattle.

A major objective of dairy cattle genomic research is to identify genes underlying the variability of milk production traits that could be useful in breeding programs. The candidate gene approach provides tools for searching for causative polymorphisms affecting quantitative traits. Genes with a possible effect on milk traits in cattle can be involved in different physiological pathways, such as triglyceride synthesis [acyl-CoA:diacylglycerol acyltransferase 1 gene (DGAT1)], fat secretion from the mammary epithelial tissue (butyrophilin), or entire-body energy homeostasis regulation (leptin and leptin receptor). In this study, based on data from 252 Black and White bulls from the active Polish dairy population, effects and potential interactions of 9 single nucleotide polymorphisms in the butyrophilin, DGAT1, leptin, and leptin receptor genes were investigated. Additionally, the effect of the number of additive, dominance, and epistatic genetic effects fitted into the model on the estimates of model parameters and model selection was illustrated. Phenotypic records were daughter yield deviations for milk, fat, and protein yields, obtained from a routine national genetic evaluation. Out of all the analyzed polymorphisms, DGAT1 K232A had a much larger effect on milk traits than the other single nucleotide polymorphisms considered. Estimates of the additive genetic effect of K232A expressed as half of the difference between Lys- and Ala-encoding variants were -107.4 kg of milk, 5.4 kg of fat, and -1.6 kg of protein at first parity, as well as -120 kg of milk and 6.8 kg of fat at second parity. In terms of model selection, it was demonstrated that the modified version of Bayesian information criterion selects models with the parameterization reflecting the genetic background of the analyzed trait, while the Bayesian information criterion chooses models that are too highly parameterized.

Fine mapping of a QTL for intramuscular fat on porcine chromosome 6 using combined linkage and linkage disequilibrium mapping.

In this study data from a commercial Norwegian slaughter pig cross was analysed to confirm a previous reported quantitative trait locus (QTL) affecting intramuscular fat (IMF) on porcine chromosome 6. The data consisted of an old experiment, in which the QTL was previously detected, and new experimental data from the Norwegian slaughter pig cross. The old and new experimental data were analysed separately and together. A previously described method combining linkage and linkage disequilibrium analysis (LDLA) was used for the analysis, but this method assumes that all animals are descendants from a common base population, which is not realistic in a cross between different breeds. An adjusted version of the method, able to distinguish between different breeds in the cross, is presented here. Using the LDLA method, we were not able to confirm the QTL in the old experimental data, because the genetic variance could be explained by the polygenic effect. Analysis from the new experimental data did however detect the QTL, and analysing the data from both experiments together gave highly significant results for a QTL (p < 0.001) between markers SW1355 and SW1823. The main conclusion is therefore that the previously reported QTL for IMF on porcine chromosome 6 was confirmed within a 8.7-cM confidence interval.

Comparison of random regression test-day models for Polish Black and White cattle.

Test-day milk yields of first-lactation Black and White cows were used to select the model for routine genetic evaluation of dairy cattle in Poland. The population of Polish Black and White cows is characterized by small herd size, low level of production, and relatively early peak of lactation. Several random regression models for first-lactation milk yield were initially compared using the "percentage of squared bias" criterion and the correlations between true and predicted breeding values. Models with random herd-test-date effects, fixed age-season and herd-year curves, and random additive genetic and permanent environmental curves (Legendre polynomials of different orders were used for all regressions) were chosen for further studies. Additional comparisons included analyses of the residuals and shapes of variance curves in days in milk. The low production level and early peak of lactation of the breed required the use of Legendre polynomials of order 5 to describe age-season lactation curves. For the other curves, Legendre polynomials of order 3 satisfactorily described daily milk yield variation. Fitting third-order polynomials for the permanent environmental effect made it possible to adequately account for heterogeneous residual variance at different stages of lactation.

Estimation of quantitative trait loci parameters for milk production traits in German Holstein dairy cattle population.

The main objective of this study was to estimate the proportion of total genetic variance attributed to a quantitative trait locus (QTL) on Bos taurus autosome 6 (BTA6) for milk production traits in the German Holstein dairy cattle population. The analyzed chromosomal region on BTA6 spanned approximately 70 cM, and contained 6 microsatellite markers. Milk production data were obtained from routine genetic evaluation for 4500 genotyped German Holstein bulls. Technical aspects related to the estimation of model parameters for a large data set from routine genotype recording were outlined. A fixed QTL model and a random QTL model were introduced to incorporate marker information into parameter estimation and genetic evaluation. Estimated QTL variances, expressed as the ratio of QTL to polygenic variances, were 0.04, 0.03, and 0.07 for milk yield; 0.06, 0.08, and 0.14 for fat yield; and 0.04, 0.04, and 0.11 for protein yield, in the first 3 parities, respectively. The estimated QTL positions, expressed as distances from the leftmost marker DIK82, were 18, 31, and 17 cM for milk yield; 25, 17, and 9 cM for fat yield; and 16, 30, and 17 cM for protein yield in the 3 respective parities. Because the data for the parameter estimation well represented the current population of active German Holstein bulls, the QTL parameter estimates have been used in routine marker-assisted genetic evaluation for German Holsteins.