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A dataset was simulated and distributed to participants of the QTLMAS XII workshop who were invited to develop genomic selection models. Each contributing group was asked to describe the model development and validation as well as to submit genomic predictions for three generations of individuals, for which they only knew the genotypes. The organisers used these genomic predictions to perform the final validation by comparison to the true breeding values, which were known only to the organisers. Methods used by the 5 groups fell in 3 classes 1) fixed effects models 2) BLUP models, and 3) Bayesian MCMC based models. The Bayesian analyses gave the highest accuracies, followed by the BLUP models, while the fixed effects models generally had low accuracies and large error variance. The best BLUP models as well as the best Bayesian models gave unbiased predictions. The BLUP models are clearly sensitive to the assumed SNP variance, because they do not estimate SNP variance, but take the specified variance as the true variance. The current comparison suggests that Bayesian analyses on haplotypes or SNPs are the most promising approach for Genomic selection although the BLUP models may provide a computationally attractive alternative with little loss of efficiency. On the other hand fixed effect type models are unlikely to provide any gain over traditional pedigree indexes for selection. [ABSTRACT FROM AUTHOR]

Genome scans have identified quantitative trait loci (QTLs) affecting milk yield and composition in dairy cattle. For one QTL on bovine chromosome 6 (BTA6), previously fine-mapped to a 420-Kb region, mutations in two different genes (OPN and ABCG2) have been proposed as the underlying functional mutation. Comparing the arguments for each gene suggests that both mutations are equally probable. However, functional studies and/or additional populations are required to provide a definite answer. [Copyright &y& Elsevier]

A whole-genome scan was conducted to map quantitative trait loci (QTL) for BSE resistance or susceptibility. Cows from four half-sib families were included and 173 microsatellite markers were used to construct a 2835-cM (Kosambi) linkage map covering 29 autosomes and the pseudoautosomal region of the sex chromosome. Interval mapping by linear regression was applied and extended to a multiple-QTL analysis approach that used identified QTL on other chromosomes as cofactors to increase mapping power. In the multiple-QTL analysis, two genome-wide significant QTL (BTA17 and X/Yps) and four genome-wide suggestive QTL (BTA1, 6, 13, and 19) were revealed. The QTL identified here using linkage analysis do not overlap with regions previously identified using TDT analysis. One factor that may explain the disparity between the results is that a more extensive data set was used in the present study. Furthermore, methodological differences between TDT and linkage analyses may affect the power of these approaches. [ABSTRACT FROM AUTHOR]

Skeletal damage is a challenge for laying hens, as the adaptations for egg laying make them susceptible to osteoporosis. We know that activity, growth and puberty influence skeletal quality genetics. However, in this story, we follow the process of resolving a QTL for skeletal quality to a single gene. Providing both a nutritional and a genetic solution and illustrating another level of complexity. Using divergently selected populations in an F2 cross, a QTL for skeletal quality was described. Utilising a series of experiments in the commercial founder line the QTL was fine mapped on chromosome 1 and the differences in physiology of hens that segregated for markers at the locus defined e.g. tibia breaking strength 200.4 vs 218.1 Newton (p< 0.002). Transcriptome profiling of tibia from the high and low bone strength genotype revealed a highly differentially expressed gene co localising to the QTL, the enzyme cystathionine beta synthase (CBS). CBS is a component of one carbon metabolism. Plasma homocysteine, the substrate of CBS had a higher concentration in the genotype associated with poor bone quality. Homocysteine interferes with crosslinking of the collagen matrix, critical to bone formation. Homocysteine can be re-methylated into methionine, a limiting amino acid in laying hens, using betaine as a methyl donor. Testing the hypothesis that reducing plasma homocysteine by feeding betaine, a widely available feed additive, would improve bone quality in laying hens proved successful. This is just one component of a complex trait and its elucidation took us along unexpected routes. However, I am optimistic that with modern tools and an open mind we can progress more quickly. Alongside understanding the factors that determine skeletal quality genetics, the discovery of the mechanisms behind complex traits, although rarely easy, offer the potential for novel interventions to improve animal health and production. [ABSTRACT FROM AUTHOR]

The author comments on the report "Global plan of action for animal genetic resources (AnGR) and the interlaken declaration." AnGR are crucial for global food security and livelihoods. Livestock products have high densities of energy, protein, and other crucial nutrients, which are specifically of benefits for infants and mothers-to-be.

Discusses the abstract of the study 'Molecular genetic mapping of imprinted QTL for gestation length in Bos taurus x Bos indicus cross cattle produced by embryo transfer,' presented at the American Society of Animal Science's Southern Section conference on January 31-February 4, 2003, in Mobile, Alabama.

The mouse Collaborative Cross (CC) is a panel of eight-way recombinant inbred lines: eight diverse parental strains are intermated, followed by repeated sibling mating, many times in parallel, to create a new set of inbred lines whose genomes are random mosaics of the genomes of the original eight strains. Many generations are required to reach inbreeding, and so a number of investigators have sought to make use of phenotype and genotype data on mice from intermediate generations during the formation of the CC lines (so-called pre-CC mice). The development of a hidden Markov model for genotype reconstruction in such pre-CC mice, on the basis of incompletely informative genetic markers (such as single-nucleotide polymorphisms), formally requires the two-locus genotype probabilities at an arbitrary generation along the path to inbreeding. In this article, I describe my efforts to calculate such probabilities. While closed-form solutions for the two-locus genotype probabilities could not be derived, I provide a prescription for calculating such probabilities numerically. In addition, I present a number of useful quantities, including single-locus genotype probabilities, two-locus haplotype probabilities, and the fixation probability and map expansion at each generation along the course to inbreeding. [ABSTRACT FROM AUTHOR]

Imputation is a cost-effective approach to augment marker data for genomic selection and genome-wide association studies. However, most imputation studies have focused on autosomes. Here, we assessed the imputation of markers on the X chromosome in Holstein cattle for nongenotyped animals and animals genotyped with low-density (Illumina BovineLD, Illumina Inc., San Diego, CA) chips, using animals genotyped with medium-density (Illumina BovineSNP50) chips. A total of 26,884 genotyped Holstein individuals genotyped with medium-density chips were used in this study. Imputation was carried out using FImpute V2.2. The following parameters were examined: treating the pseudoautosomal region as autosomal or as X specific, different sizes of reference groups, different male/female proportions in the reference group, and cumulated degree of relationship between the reference group and target group. The imputation accuracy of markers on the X chromosome was improved if the pseudoautosomal region was treated as autosomal. Increasing the proportion of females in the reference group improved the imputation accuracy for the X chromosome. Imputation for nongenotyped animals in general had lower accuracy compared with animals genotyped with the low-density single nucleotide polymorphism array. In addition, higher cumulative pedigree relationships between the reference group and the target animal led to higher imputation accuracy. In the future, better marker coverage of the X chromosome should be developed to facilitate genomic studies involving the X chromosome. [ABSTRACT FROM AUTHOR]

Using targeted genetical genomics, a quantitative trait locus (QTL) affecting the initial postmortem pH value of chicken breast muscle (Pectoralis major) on chromosome 1 (GGA1) recently was fine-mapped. Thirteen genes were present in the QTL region of approximately 1 Mb. In this study, 10 birds that were inferred to be homozygous for either the high (QQ) or low (qq) QTL allele were selected for resequencing. After enrichment for 1 Mb around the QTL region, >500 x coverage for the QTL region in each of the 10 birds was obtained. In total 5056 single-nucleotide polymorphisms (SNPs) were identified for which the genotypes were consistent with one of the QTL genotypes. We used custom tools to identify putative causal mutations in the mapped QTL region from these SNPs. Four nonsynonymous SNPs differentiating the two QTL genotype groups were identified within four local genes (PRDX4, EIF2S3, PCYT1B, and E1BTD2). Although these are likely candidate SNPs to explain the QTL effect, 54 additional consensus SNPs were detected within gene-related regions (untranslated regions, splicing sites CpG island, and promoter regions) for the QQ birds and 71 for the qq birds. These could also play a role explaining the observed QTL effect. The results provide an important step for prioritizing among a large amount of candidate mutations and significantly contribute to the understanding of the genetic mechanisms affecting the initial postmortem pH value of chicken muscle. [ABSTRACT FROM AUTHOR]

The JAX Diversity Outbred population is a new mouse resource derived from partially inbred Collaborative Cross strains and maintained by randomized outcrossing. As such, it segregates the same allelic variants as the Collaborative Cross but embeds these in a distinct population architecture in which each animal has a high degree of heterozygosity and carries a unique combination of alleles. Phenotypic diversity is striking and often divergent from phenotypes seen in the founder strains of the Collaborative Cross. Allele frequencies and recombination density in early generations of Diversity Outbred mice are consistent with expectations based on simulations of the mating design. We describe analytical methods for genetic mapping using this resource and demonstrate the power and high mapping resolution achieved with this population by mapping a serum cholesterol trait to a 2-Mb region on chromosome 3 containing only 11 genes. Analysis of the estimated allele effects in conjunction with complete genome sequence data of the founder strains reduced the pool of candidate polymorphisms to seven SNPs, five of which are located in an intergenic region upstream of the Foxo1 gene. [ABSTRACT FROM AUTHOR]

The classic diallel takes a set of parents and produces offspring from all possible mating pairs. Phenotype values among the offspring can then be related back to their respective parentage. When the parents are diploid, sexed, and inbred, the diallel can characterize aggregate effects of genetic background on a phenotype, revealing effects of strain dosage, heterosis, parent of origin, epistasis, and sex-specific versions thereof. However, its analysis is traditionally intricate, unforgiving of unplanned missing information, and highly sensitive to imbalance, making the diallel unapproachable to many geneticists. Nonetheless, imbalanced and incomplete diallels arise frequently, albeit unintentionally, as by-products of larger-scale experiments that collect F1 data, for example, pilot studies or multiparent breeding efforts such as the Collaborative Cross or the Arabidopsis MAGIC lines. We present a general Bayesian model for analyzing diallel data on dioecious diploid inbred strains that cleanly decomposes the observed patterns of variation into biologically intuitive components, simultaneously models and accommodates outliers, and provides shrinkage estimates of effects that automatically incorporate uncertainty due to imbalance, missing data, and small sample size. We further present a model selection procedure for weighing evidence for or against the inclusion of those components in a predictive model. We evaluate our method through simulation and apply it to incomplete diallel data on the founders and F1's of the Collaborative Cross, robustly characterizing the genetic architecture of 48 phenotypes. [ABSTRACT FROM AUTHOR]

We present full-genome genotype imputations for 100 classical laboratory mouse strains, using a novel method. Using genotypes at 549,683 SNP loci obtained with the Mouse Diversity Array, we partitioned the genome of 100 mouse strains into 40,647 intervals that exhibit no evidence of historical recombination. For each of these intervals we inferred a local phylogenetic tree. We combined these data with 12 million loci with sequence variations recently discovered by whole-genome sequencing in a common subset of 12 classical laboratory strains. For each phylogenetic tree we identified strains sharing a leaf node with one or more of the sequenced strains. We then imputed high- and medium-confidence genotypes for each of 88 nonsequenced genomes. Among inbred strains, we imputed 92% of SNPs genome-wide, with 71% in high-confidence regions. Our method produced 977 million new genotypes with an estimated per-SNP error rate of 0.083% in high-confidence regions and 0.37% genome-wide. Our analysis identified which of the 88 nonsequenced strains would be the most informative for improving full-genome imputation, as well as which additional strain sequences will reveal more new genetic variants. Imputed sequences and quality scores can be downloaded and visualized online. [ABSTRACT FROM AUTHOR]

There has been a great deal of interest in the development of methodologies to map quantitative trait loci (QTL) using experimental crosses in the last 2 decades. Experimental crosses in animal and plant sciences provide important data sources for mapping QTL through linkage analysis. The Collaborative Cross (CC) is a renewable mouse resource that is generated from eight genetically diverse founder strains to mimic the genetic diversity in humans. The recombinant inbred intercrosses (RIX) generated from CC recombinant inbred (RI) lines share similar genetic structures of F2 individuals but with up to eight alleles segregating at any one locus. In contrast to F2 mice, genotypes of RIX can be inferred from the genotypes of their RI parents and can be produced repeatedly. Also, RIX mice typically do not share the same degree of relatedness. This unbalanced genetic relatedness requires careful statistical modeling to avoid false-positive findings. Many quantitative traits are inherently complex with genetic effects varying with other covariates, such as age. For such complex traits, if phenotype data can be collected over a wide range of ages across study subjects, their dynamic genetic patterns can be investigated. Parametric functions, such as sigmoidal or logistic functions, have been used for such purpose. In this article, we propose a flexible nonparametric time-varying coefficient QTL mapping method for RIX data. Our method allows the QTL effects to evolve with time and naturally extends classical parametric QTL mapping methods. We model the varying genetic effects nonparametrically with the B-spline bases. Our model investigates gene-by-time interactions for RIX data in a very flexible nonparametric fashion. Simulation results indicate that the varying coefficient QTL mapping has higher power and mapping precision compared to parametric models when the assumption of constant genetic effects fails. We also apply a modified permutation procedure to control overall significance level. [ABSTRACT FROM AUTHOR]

Osteoporosis and bone fractures are a severe problem for the welfare of laying hens, with genetics and environment, such as housing system, each making substantial contributions to bone strength. In this work, we performed genetic analyses of bone strength, bone mineral density, and bone composition, as well as body weight, in 860 commercial crossbred laying hens from 2 different companies, kept in either furnished cages or floor pens. We compared bone traits between housing systems and crossbreds and performed a genome-wide association study of bone properties and body weight. As expected, the 2 housing systems produced a large difference in bone strength, with layers housed in floor pens having stronger bones. These differences were accompanied by differences in bone geometry, mineralization, and chemical composition. Genome scans either combining or independently analyzing the 2 housing systems revealed no genome-wide significant loci for bone breaking strength. We detected 3 loci for body weight that were shared between the housing systems on chromosomes 4, 6, and 27 (either genome-wide significant or suggestive) and these coincide with associations for bone length. In summary, we found substantial differences in bone strength, content, and composition between hens kept in floor pens and furnished cages that could be attributed to greater physical activity in pen housing. We found little evidence for large-effect loci for bone strength in commercial crossbred hens, consistent with a highly polygenic architecture for bone strength in the production environment. The lack of consistent genetic associations between housing systems in combination with the differences in bone phenotypes could be due to gene-by-environment interactions with housing system or a lack of power to detect shared associations for bone strength., Competing Interests: Conflicts of interest The authors declare no conflict of interest., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Genetics Society of America.)

Routine implementation of genomic information for guiding selection decisions is not yet common in the majority of aquaculture species. Reduced representation sequencing approaches offer a cost-effective solution for obtaining genome-wide information in species with a limited availability of genomic resources. In the current study, we implemented double-digest restriction site-associated DNA sequencing (ddRAD-seq) on an Arctic charr strain with the longest known history of selection (approximately 40 years) aiming to improve selection decisions. In total, 1730 animals reared at four different farms in Sweden and spanning from year classes 2013-2017 were genotyped using ddRAD-seq. Approximately 5000 single nucleotide polymorphisms (SNPs) were identified, genetic diversity-related metrics were estimated, and genome-wide association studies (GWAS) for body length at different time points and age of sexual maturation were conducted. Low genetic differentiation amongst animals from the different farms was observed based on both the results from pairwise F st values and principal component analysis (PCA). The existence of associations was investigated between the mean genome-wide heterozygosity of each full-sib family (year class 2017) and the corresponding inbreeding coefficient or survival to the eyed stage. A moderate correlation (-0.33) was estimated between the mean observed heterozygosity of each full-sib family and the corresponding inbreeding coefficient, while no linear association was obtained with the survival to the eyed stage. GWAS did not detect loci with major effect for any of the studied traits. However, genomic regions explaining more than 1% of the additive genetic variance for either studied traits were suggested across 14 different chromosomes. Overall, key insights valuable for future selection decisions of Arctic charr have been obtained, suggesting ddRAD as an attractive genotyping platform for obtaining genome-wide information in a cost-effective manner., Competing Interests: The authors declare no conflict of interest., (© 2021 The Authors. Evolutionary Applications published by John Wiley & Sons Ltd.)

Background: Meiotic recombination results in the exchange of genetic material between homologous chromosomes. Recombination rate varies between different parts of the genome, between individuals, and is influenced by genetics. In this paper, we assessed the genetic variation in recombination rate along the genome and between individuals in the pig using multilocus iterative peeling on 150,000 individuals across nine genotyped pedigrees. We used these data to estimate the heritability of recombination and perform a genome-wide association study of recombination in the pig., Results: Our results confirmed known features of the recombination landscape of the pig genome, including differences in genetic length of chromosomes and marked sex differences. The recombination landscape was repeatable between lines, but at the same time, there were differences in average autosome-wide recombination rate between lines. The heritability of autosome-wide recombination rate was low but not zero (on average 0.07 for females and 0.05 for males). We found six genomic regions that are associated with recombination rate, among which five harbour known candidate genes involved in recombination: RNF212, SHOC1, SYCP2, MSH4 and HFM1., Conclusions: Our results on the variation in recombination rate in the pig genome agree with those reported for other vertebrates, with a low but nonzero heritability, and the identification of a major quantitative trait locus for recombination rate that is homologous to that detected in several other species. This work also highlights the utility of using large-scale livestock data to understand biological processes.

Five introduced strains of Nile tilapia (Oreochromis niloticus) were tested for growth performance both in fresh- and brackish-water (2 salinity units) environments for 56 days. The BIG NIN, GIFT, Chitralada, "Ruvu Farm" and Silver YY strains with initial mean average weight (± standard error) of 96.4 ± 6.90 g, 104.1 ± 7.19 g, 137.2 ± 7.21 g, 53.2 ± 6.98 g and 95.3 ± 7.11 g, respectively were used. Individuals were tagged and pooled in hapas (12 m × 8.5 m × 2 m each), aligned into different ponds (20 m × 20 m each). Stocking density of 5 fish/m 2 and 350 g/kg crude protein diet were used. Overall, the average weight gain for GIFT strain was 7.5%, 32%, 45% and 86.5% higher than BIG NIN, Chitralada, "Ruvu Farm" and Silver YY strains, respectively, across both environments. All strains performed significantly better (p < 0.05) when reared in brackish-water than their respective counterparts in freshwater, except for the BIG NIN strain. The morphometric correlations for all strains in both environments ranged from moderate (0.50) to strong positive (0.92). The GIFT strain demonstrated superior growth and genotype by environment interaction was weak and not important to be prioritized in breeding programs.

Background: The physiological adaptations that have evolved for egg laying make hens susceptible to bone fractures and keel bone damage. In modern laying hen breeds, longer periods of egg laying could result in a greater risk of poor bone quality, and selection for increased egg production has frequently been stated to be a cause. However, the existing literature does not support this hypothesis. To test the hypothesis that egg production is associated with quality, breaking strength and density of bone, genetic correlations between these traits were estimated in White Leghorn and Rhode Island Red breeds. Genetic correlations of cortical and medullary bone material chemical properties with bone quality were also estimated, in order to identify methods to improve bone quality with appropriately targeted measurement of key traits., Results: Estimates of heritability for bone quality traits were moderate (0.19-0.59) for both White Leghorn and Rhode Island Red breeds, except for the keel bone trait, which had a heritability estimate equal to zero. There was no evidence for genetic or phenotypic relationships between post-peak egg production and bone quality. In the White Leghorn breed, the estimate of the genetic correlation between pre-peak production/age at first egg and bone quality was significant and negative (- 0.7 to - 0.4). Estimates of heritability of thermogravimetric measurements of tibial medullary bone mineralisation were significant (0.18-0.41), as were estimates of their genetic correlations with tibia breaking strength and density (0.6-0.9)., Conclusions: The low genetic correlation of post-peak egg production with bone quality suggests that selection for increased persistency of egg production may not adversely affect bone quality. Onset of puberty and mineralisation of the medullary bone, which is a specialised adaptation for egg laying, were identified as important factors associated with the quality of the skeleton later during egg production. These are traits for which genetic, as well as environmental and management factors can positively impact the overall quality of the skeleton of laying hens.

Arctic charr ( Salvelinus alpinus ) is a species of high economic value for the aquaculture industry, and of high ecological value due to its Holarctic distribution in both marine and freshwater environments. Novel genome sequencing approaches enable the study of population and quantitative genetic parameters even on species with limited or no prior genomic resources. Low coverage genotyping by sequencing (GBS) was applied in a selected strain of Arctic charr in Sweden originating from a landlocked freshwater population. For the needs of the current study, animals from year classes 2013 (171 animals, parental population) and 2017 (759 animals; 13 full sib families) were used as a template for identifying genome wide single nucleotide polymorphisms (SNPs). GBS libraries were constructed using the PstI and MspI restriction enzymes. Approximately 14.5K SNPs passed quality control and were used for estimating a genomic relationship matrix. Thereafter a wide range of analyses were conducted in order to gain insights regarding genetic diversity and investigate the efficiency of the genomic information for parentage assignment and breeding value estimation. Heterozygosity estimates for both year classes suggested a slight excess of heterozygotes. Furthermore, F ST estimates among the families of year class 2017 ranged between 0.009 - 0.066. Principal components analysis (PCA) and discriminant analysis of principal components (DAPC) were applied aiming to identify the existence of genetic clusters among the studied population. Results obtained were in accordance with pedigree records allowing the identification of individual families. Additionally, DNA parentage verification was performed, with results in accordance with the pedigree records with the exception of a putative dam where full sib genotypes suggested a potential recording error. Breeding value estimation for juvenile growth through the usage of the estimated genomic relationship matrix clearly outperformed the pedigree equivalent in terms of prediction accuracy (0.51 opposed to 0.31). Overall, low coverage GBS has proven to be a cost-effective genotyping platform that is expected to boost the selection efficiency of the Arctic charr breeding program., (Copyright © 2020 Palaiokostas et al.)

Lepidium campestre (L.) or field cress is a multifaceted oilseed plant, which is not yet domesticated. Moreover, the molecular and genetic mechanisms underlying the domestication traits of field cress remain largely elusive. The overarching goal of this study is to identify quantitative trait loci (QTL) that are fundamental for domestication of field cress. Mapping and dissecting quantitative trait variation may provide important insights into genomic trajectories underlying field cress domestication. We used 7624 single nucleotide polymorphism (SNP) markers for QTL mapping in 428 F 2 interspecific hybrid individuals, while field phenotyping was conducted in F 2:3 segregating families. We applied multiple QTL mapping algorithms to detect and estimate the QTL effects for seven important domestication traits of field cress. Verification of pod shattering across sites revealed that the non-shattering lines declined drastically whereas the shattering lines increased sharply, possibly due to inbreeding followed by selection events. In total, 1461 of the 7624 SNP loci were mapped to eight linkage groups (LGs), spanning 571.9 cM map length. We identified 27 QTL across all LGs of field cress genome, which captured medium to high heritability, implying that genomics-assisted selection could deliver domesticated lines in field cress breeding. The use of high throughput genotyping can accelerate the process of domestication in novel crop species. This is the first QTL mapping analysis in the field cress genome that may lay a foundational framework for positional or functional QTL cloning, introgression as well as genomics-assisted breeding in field cress domestication.

Background: Skeletal damage is a challenge for laying hens because the physiological adaptations required for egg laying make them susceptible to osteoporosis. Previously, we showed that genetic factors explain 40% of the variation in end of lay bone quality and we detected a quantitative trait locus (QTL) of large effect on chicken chromosome 1. The aim of this study was to combine data from the commercial founder White Leghorn population and the F2 mapping population to fine-map this QTL and understand its function in terms of gene expression and physiology., Results: Several single nucleotide polymorphisms on chromosome 1 between 104 and 110 Mb (galGal6) had highly significant associations with tibial breaking strength. The alternative genotypes of markers of large effect that flanked the region had tibial breaking strengths of 200.4 vs. 218.1 Newton (P < 0.002) and, in a subsequent founder generation, the higher breaking strength genotype was again associated with higher breaking strength. In a subsequent generation, cortical bone density and volume were increased in individuals with the better bone genotype but with significantly reduced medullary bone quality. The effects on cortical bone density were confirmed in a further generation and was accompanied by increased mineral maturity of the cortical bone as measured by infrared spectrometry and there was evidence of better collagen cross-linking in the cortical bone. Comparing the transcriptome of the tibia from individuals with good or poor bone quality genotypes indicated four differentially-expressed genes at the locus, one gene, cystathionine beta synthase (CBS), having a nine-fold higher expression in the genotype for low bone quality. The mechanism was cis-acting and although there was an amino-acid difference in the CBS protein between the genotypes, there was no difference in the activity of the enzyme. Plasma homocysteine concentration, the substrate of CBS, was higher in the poor bone quality genotype., Conclusions: Validated markers that predict bone strength have been defined for selective breeding and a gene was identified that may suggest alternative ways to improve bone health in addition to genetic selection. The identification of how genetic variants affect different aspects of bone turnover shows potential for translational medicine.

Exploring dominance variance and loci contributing to dominance variation is important to understand the genetic architecture behind quantitative traits. The objectives of this study were i) to estimate dominance variances, ii) to detect quantitative trait loci (QTL) with dominant effects, and iii) to evaluate the power and the precision of identifying loci with dominance effect through post-hoc simulations, with applications for female fertility in Danish Holstein cattle. The female fertility records analyzed were number of inseminations (NINS), days from calving to first insemination (ICF), and days from the first to last insemination (IFL), covering both abilities to recycle and to get pregnant in the female reproductive cycle. There were 3,040 heifers and 4,483 cows with both female fertility records and Illumina BovineSNP50 BeadChip genotypes (35,391 single nucleotide polymorphisms (SNP) after quality control). Genomic best linear unbiased prediction (BLUP) models were used to estimate additive and dominance genetic variances. Linear mixed models were used for association analyses. A post-hoc simulation study was performed using genotyped heifers' data. In heifers, estimates of dominance genetic variances for female fertility traits were larger than additive genetic variances, but had large standard errors. The variance components for fertility traits in cows could not be estimated due to non-convergence of the statistical model. In total, five QTL located on chromosomes 9, 11 (2 QTL), 19, and 28 were identified and all of them showed both additive and dominance genetic effects. Among them, the SNP rs29018921 on chromosome 9 is close to a previously identified QTL in Nordic Holstein for interval between first and last insemination. This SNP is located in the 3' untranslated region of gene peptidylprolyl isomerase like 4 (PPIL4), which was shown to be associated with milk production traits in US Holstein cattle but not known for fertility-related functions. Simulations indicated that the current sample size had limited power to detect QTL with dominance effects for female fertility probably due to low QTL variance. More females need to be genotyped to achieve reliable mapping of QTL with dominance effects for female fertility.

Field cress (Lepidium campestre L.), despite its potential as a sustainable alternative oilseed plant, has been underutilized, and no prior attempts to characterize the genome at the genetic or molecular cytogenetic level have been conducted. Genetic maps are the foundation for anchoring and orienting annotated genome assemblies and positional cloning of candidate genes. Our principal goal was to construct a genetic map using integrated approaches of genetic, comparative and cytogenetic map analyses. In total, 503 F 2 interspecific hybrid individuals were genotyped using 7,624 single nucleotide polymorphism markers. Comparative analysis demonstrated that ~57% of the sequenced loci in L. campestre were congruent with Arabidopsis thaliana (L.) genome and suggested a novel karyotype, which predates the ancestral crucifer karyotype. Aceto-orcein chromosome staining and fluorescence in situ hybridization (FISH) analyses confirmed that L. campestre, L. heterophyllum Benth. and their hybrids had a chromosome number of 2n = 2x = 16. Flow cytometric analysis revealed that both species possess 2C roughly 0.4 picogram DNA. Integrating linkage and comparative maps with cytogenetic map analyses assigned two linkage groups to their particular chromosomes. Future work could incorporate FISH utilizing A. thaliana mapped BAC clones to allow the chromosomes of field cress to be identified reliably.

Biotechnology can provide innovative and efficient tools to support sustainable development of aquaculture. It is generally accepted that use of the term 'genetically modified' causes controversy and conflict among consumers, but little is known about how using the term 'biotechnology' as a salient feature on product packaging affects consumer preferences. In an online discrete choice experiment consisting of two treatments, a set of 1005 randomly chosen Swedish consumers were surveyed about use of hormone and triploidization sterilization techniques for salmonids. The information given to the treatment group included an additional sentence stating that the triploidization technique is an application of biotechnology, while the control group received the same text but without reference to biotechnology. Analysis using a hierarchical Bayes approach revealed significant consumer reactions to the term biotechnology. When the term was included in information, variation in consumer willingness-to-pay (WTP) estimates increased significantly. Moreover, some participants were dissuaded towards an option guaranteeing no biotechnological intervention in production of fish. These results have multiple implications for research and for the food industry. For research, they indicate the importance of examining the distribution of variation in WTP estimates for more complete characterization of the effects of information on consumer behavior. For the food industry, they show that associating food with biotechnology creates more variability in demand. Initiatives should be introduced to reduce the confusion associated with the term biotechnology among consumers., Competing Interests: The authors have declared that no competing interests exist.

Background: In this paper, we simulate deleterious load in an animal breeding program, and compare the efficiency of genome editing and selection for decreasing it. Deleterious variants can be identified by bioinformatics screening methods that use sequence conservation and biological prior information about protein function. However, once deleterious variants have been identified, how can they be used in breeding?, Results: We simulated a closed animal breeding population that is subject to both natural selection against deleterious load and artificial selection for a quantitative trait representing the breeding goal. Deleterious load was polygenic and was due to either codominant or recessive variants. We compared strategies for removal of deleterious alleles by genome editing (RAGE) to selection against carriers. When deleterious variants were codominant, the best strategy for prioritizing variants was to prioritize low-frequency variants. When deleterious variants were recessive, the best strategy was to prioritize variants with an intermediate frequency. Selection against carriers was inefficient when variants were codominant, but comparable to editing one variant per sire when variants were recessive., Conclusions: Genome editing of deleterious alleles reduces deleterious load, but requires the simultaneous editing of multiple deleterious variants in the same sire to be effective when deleterious variants are recessive. In the short term, selection against carriers is a possible alternative to genome editing when variants are recessive. Our results suggest that, in the future, there is the potential to use RAGE against deleterious load in animal breeding.

Bone fracture in egg laying hens is a growing welfare and economic concern in the industry. Although environmental conditions and management (especially nutrition) can exacerbate it, the primary cause of bone weakness and the resulting fractures is believed to have a genetic basis. To test this hypothesis, we performed a genome-wide association study to identify the loci associated with bone strength in laying hens. Genotype and phenotype data were obtained from 752 laying hens belonging to the same pure line population. These hens were genotyped for 580,961 SNPs, with 232,021 SNPs remaining after quality control. Each of the SNPs were tested for association with tibial breaking strength using the family-based score test for association. A total of 52 SNPs across chromosomes 1, 3, 8, and 16 were significantly associated with tibial breaking strength with the genome-wide significance threshold set as a corrected P value of 10e-5. Based on the local linkage disequilibrium around the significant SNPs, 5 distinct and novel QTLs were identified on chromosomes 1 (2 QTLs), 3 (1 QTL), 8 (1 QTL) and 16 (1 QTL). The strongest association was detected within the QTL region on chromosome 8, with the most significant SNP having a corrected P value of 4e-7. A number of candidate genes were identified within the QTL regions, including the BRD2 gene that is required for normal bone physiology. Bone-related pathways involving some of the genes were also identified including chloride channel activity, which regulates bone reabsorption, and intermediate filament organization, which plays a role in the regulation of bone mass. Our result supports previous studies that suggest that bone strength is highly regulated by genetics. It is therefore possible to reduce bone fractures in laying hens through genetic selection and ultimately improve hen welfare.

Large genomic deletions are potential candidate for loss-of-function, which could be lethal as homozygote. Analysing whole genome data of 175 cattle, we report 8,480 large deletions (199 bp-773 KB) with an overall false discovery rate of 8.8%; 82% of which are novel compared with deletions in the dbVar database. Breakpoint sequence analyses revealed that majority (24 of 29 tested) of the deletions contain microhomology/homology at breakpoint, and therefore, most likely generated by microhomology-mediated end joining. We observed higher differentiation among breeds for deletions in some genic-regions, such as ABCA12, TTC1, VWA3B, TSHR, DST/BPAG1, and CD1D. The genes overlapping deletions are on average evolutionarily less conserved compared with known mouse lethal genes (P-value = 2.3 × 10-6). We report 167 natural gene knockouts in cattle that are apparently nonessential as live homozygote individuals are observed. These genes are functionally enriched for immunoglobulin domains, olfactory receptors, and MHC classes (FDR = 2.06 × 10-22, 2.06 × 10-22, 7.01 × 10-6, respectively). We also demonstrate that deletions are enriched for health and fertility related quantitative trait loci (2-and 1.5-fold enrichment, Fisher's P-value = 8.91 × 10-10 and 7.4 × 10-11, respectively). Finally, we identified and confirmed the breakpoint of a ∼525 KB deletion on Chr23:12,291,761-12,817,087 (overlapping BTBD9, GLO1 and DNAH8), causing stillbirth in Nordic Red Cattle., (© The Author 2017. Published by Oxford University Press on behalf of Kazusa DNA Research Institute.)

The number of functional teats is an important selection criterion in pig breeding. Inherited defects of the udder, such as the inverted teat, do have a considerable negative impact on the nursing ability of the sow. To investigate the genetic background of this defect and the number of functional teats in Swedish maternal lines, samples from 230 Yorkshire pigs were selected for genotyping using the PorcineSNP60K BeadChip (Illumina Inc.), each pig with at least one inverted teat was matched with one non-affected pig (fullsib or pairs with matching herd and gender). A genome-wide association study on these 230 pigs was performed using the two-step approach implemented in GenABEL using 46,652 single nucleotide polymorphisms across all autosomes and the X chromosome. A number of significant regions were identified for the inverted teat defect on chromosomes 2, 10, and 18. Many of the regions associated with the number of functional teats were located in the same or close regions, except two associated markers on the X chromosome and one on chromosome 3. We identified some of the regions on chromosomes previously reported in one linkage and one gene expression study. We conclude, despite being able to suggest new candidate genes, that further studies are needed to better understand the biologic background of the teat development. Despite the in-depth comparison of identified regions for the inverted teat defect done here, more studies are required to allow a clear identification of genetic regions relevant for this defect across many pig populations.

Imputation is a cost-effective approach to augment marker data for genomic selection and genome-wide association studies. However, most imputation studies have focused on autosomes. Here, we assessed the imputation of markers on the X chromosome in Holstein cattle for nongenotyped animals and animals genotyped with low-density (Illumina BovineLD, Illumina Inc., San Diego, CA) chips, using animals genotyped with medium-density (Illumina BovineSNP50) chips. A total of 26,884 genotyped Holstein individuals genotyped with medium-density chips were used in this study. Imputation was carried out using FImpute V2.2. The following parameters were examined: treating the pseudoautosomal region as autosomal or as X specific, different sizes of reference groups, different male/female proportions in the reference group, and cumulated degree of relationship between the reference group and target group. The imputation accuracy of markers on the X chromosome was improved if the pseudoautosomal region was treated as autosomal. Increasing the proportion of females in the reference group improved the imputation accuracy for the X chromosome. Imputation for nongenotyped animals in general had lower accuracy compared with animals genotyped with the low-density single nucleotide polymorphism array. In addition, higher cumulative pedigree relationships between the reference group and the target animal led to higher imputation accuracy. In the future, better marker coverage of the X chromosome should be developed to facilitate genomic studies involving the X chromosome., (Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

Non-coagulating (NC) milk, defined as milk not coagulating within 40 min after rennet-addition, can have a negative influence on cheese production. Its prevalence is estimated at 18% in the Swedish Red (SR) cow population. Our study aimed at identifying genomic regions and causal variants associated with NC milk in SR cows, by doing a GWAS using 777k SNP genotypes and using imputed sequences to fine map the most promising genomic region. Phenotypes were available from 382 SR cows belonging to 21 herds in the south of Sweden, from which individual morning milk was sampled. NC milk was treated as a binary trait, receiving a score of one in case of non-coagulation within 40 min. For all 382 SR cows, 777k SNP genotypes were available as well as the combined genotypes of the genetic variants of αs1-β-κ-caseins. In addition, whole-genome sequences from the 1000 Bull Genome Consortium (Run 3) were available for 429 animals of 15 different breeds. From these sequences, 33 sequences belonged to SR and Finish Ayrshire bulls with a large impact in the SR cow population. Single-marker analyses were run in ASReml using an animal model. After fitting the casein loci, 14 associations at -Log10(P-value) > 6 identified a promising region located on BTA18. We imputed sequences to the 382 genotyped SR cows using Beagle 4 for half of BTA18, and ran a region-wide association study with imputed sequences. In a seven mega base-pairs region on BTA18, our strongest association with NC milk explained almost 34% of the genetic variation in NC milk. Since it is possible that multiple QTL are in strong LD in this region, 59 haplotypes were built, genetically differentiated by means of a phylogenetic tree, and tested in phenotype-genotype association studies. Haplotype analyses support the existence of one QTL underlying NC milk in SR cows. A candidate gene of interest is the VPS35 gene, for which one of our strongest association is an intron SNP in this gene. The VPS35 gene belongs to the mammary gene sets of pre-parturient and of lactating cows.

Using targeted genetical genomics, a quantitative trait locus (QTL) affecting the initial postmortem pH value of chicken breast muscle (Pectoralis major) on chromosome 1 (GGA1) recently was fine-mapped. Thirteen genes were present in the QTL region of approximately 1 Mb. In this study, 10 birds that were inferred to be homozygous for either the high (QQ) or low (qq) QTL allele were selected for resequencing. After enrichment for 1 Mb around the QTL region, >500 × coverage for the QTL region in each of the 10 birds was obtained. In total 5056 single-nucleotide polymorphisms (SNPs) were identified for which the genotypes were consistent with one of the QTL genotypes. We used custom tools to identify putative causal mutations in the mapped QTL region from these SNPs. Four nonsynonymous SNPs differentiating the two QTL genotype groups were identified within four local genes (PRDX4, EIF2S3, PCYT1B, and E1BTD2). Although these are likely candidate SNPs to explain the QTL effect, 54 additional consensus SNPs were detected within gene-related regions (untranslated regions, splicing sites CpG island, and promoter regions) for the QQ birds and 71 for the qq birds. These could also play a role explaining the observed QTL effect. The results provide an important step for prioritizing among a large amount of candidate mutations and significantly contribute to the understanding of the genetic mechanisms affecting the initial postmortem pH value of chicken muscle., (Copyright © 2015 Li et al.)

Genomic selection has been widely implemented in dairy cattle breeding when the aim is to improve performance of purebred animals. In pigs, however, the final product is a crossbred animal. This may affect the efficiency of methods that are currently implemented for dairy cattle. Therefore, the objective of this study was to determine the accuracy of predicted breeding values in crossbred pigs using purebred genomic and phenotypic data. A second objective was to compare the predictive ability of SNPs when training is done in either single or multiple populations for four traits: age at first insemination (AFI); total number of piglets born (TNB); litter birth weight (LBW); and litter variation (LVR). We performed marker-based and pedigree-based predictions. Within-population predictions for the four traits ranged from 0.21 to 0.72. Multi-population prediction yielded accuracies ranging from 0.18 to 0.67. Predictions across purebred populations as well as predicting genetic merit of crossbreds from their purebred parental lines for AFI performed poorly (not significantly different from zero). In contrast, accuracies of across-population predictions and accuracies of purebred to crossbred predictions for LBW and LVR ranged from 0.08 to 0.31 and 0.11 to 0.31, respectively. Accuracy for TNB was zero for across-population prediction, whereas for purebred to crossbred prediction it ranged from 0.08 to 0.22. In general, marker-based outperformed pedigree-based prediction across populations and traits. However, in some cases pedigree-based prediction performed similarly or outperformed marker-based prediction. There was predictive ability when purebred populations were used to predict crossbred genetic merit using an additive model in the populations studied. AFI was the only exception, indicating that predictive ability depends largely on the genetic correlation between PB and CB performance, which was 0.31 for AFI. Multi-population prediction was no better than within-population prediction for the purebred validation set. Accuracy of prediction was very trait-dependent., (Copyright © 2015 Hidalgo et al.)

In animal breeding, the genetic potential of an animal is summarized as its estimated breeding value, which is derived from its own performance as well as the performance of related individuals. Here, we illustrate why estimated breeding values are not suitable as a phenotype for genome-wide association studies. We simulated human-type and pig-type pedigrees with a range of quantitative trait loci (QTL) effects (0.5-3% of phenotypic variance) and heritabilities (0.3-0.8). We analyzed 1000 replicates of each scenario with four models: (a) a full mixed model including a polygenic effect, (b) a regression analysis using the residual of a mixed model as a trait score (so called GRAMMAR approach), (c) a regression analysis using the estimated breeding value as a trait score, and (d) a regression analysis that uses the raw phenotype as a trait score. We show that using breeding values as a trait score gives very high false-positive rates (up 14% in human pedigrees and >60% in pig pedigrees). Simulations based on a real pedigree show that additional generations of pedigree increase the type I error. Including the family relationship as a random effect provides the greatest power to detect QTL while controlling for type I error at the desired level and providing the most accurate estimates of the QTL effect. Both the use of residuals and the use of breeding values result in deflated estimates of the QTL effect. We derive the contributions of QTL effects to the breeding value and residual and show how this affects the estimates.

Background: It has been shown that if genetic relationships among individuals are not taken into account for genome wide association studies, this may lead to false positives. To address this problem, we used Genome-wide Rapid Association using Mixed Model and Regression and principal component stratification analyses. To account for linkage disequilibrium among the significant markers, principal components loadings obtained from top markers can be included as covariates. Estimation of Bayesian networks may also be useful to investigate linkage disequilibrium among SNPs and their relation with environmental variables.For the quantitative trait we first estimated residuals while taking polygenic effects into account. We then used a single SNP approach to detect the most significant SNPs based on the residuals and applied principal component regression to take linkage disequilibrium among these SNPs into account. For the categorical trait we used principal component stratification methodology to account for background effects. For correction of linkage disequilibrium we used principal component logit regression. Bayesian networks were estimated to investigate relationship among SNPs., Results: Using the Genome-wide Rapid Association using Mixed Model and Regression and principal component stratification approach we detected around 100 significant SNPs for the quantitative trait (p<0.05 with 1000 permutations) and 109 significant (p<0.0006 with local FDR correction) SNPs for the categorical trait. With additional principal component regression we reduced the list to 16 and 50 SNPs for the quantitative and categorical trait, respectively., Conclusions: GRAMMAR could efficiently incorporate the information regarding random genetic effects. Principal component stratification should be cautiously used with stringent multiple hypothesis testing correction to correct for ancestral stratification and association analyses for binary traits when there are systematic genetic effects such as half sib family structures. Bayesian networks are useful to investigate relationships among SNPs and environmental variables.

Combining global gene-expression profiling and genetic analysis of natural allelic variation (genetical genomics) has great potential in dissecting the genetic pathways underlying complex phenotypes. Efficient use of microarrays is paramount in experimental design as the cost of conducting this type of study is high. For those organisms where recombinant inbred lines are available for mapping, the "distant pair design" maximizes the number of informative contrasts over all marker loci. Here, we describe an extension of this design, named the "optimal pair design," for use with F2 crosses between outbred lines. The performance of this design is investigated by simulation and compared to several other two-color microarray designs. We show that, for a given number of microarrays, the optimal pair design outperforms all other designs considered for detection of expression quantitative trait loci (eQTL) with additive effects by linkage analysis. We also discuss the suitability of this design for outbred crosses in organisms with large genomes and for detection of dominance.

Dominance is an important source of variation in complex traits. Here, we have carried out the first thorough investigation of quantitative trait locus (QTL) detection using variance component (VC) models extended to incorporate both additive and dominant QTL effects. Simulation results showed that the empirical distribution of the test statistic when testing for dominant QTL effects did not behave in accordance with existing theoretical expectations and varied with pedigree structure. Extensive simulations were carried out to assess accuracy of estimates, type 1 error and statistical power in two-generation human-, poultry- and pig-type pedigrees each with 1900 progeny in small-, medium- and large-sized families, respectively. The distribution of the likelihood-ratio test statistic was heavily dependent on family structure, with empirical thresholds lower for human pedigrees. Power to detect QTL was high (0.84-1.0) in pig and poultry scenarios for dominance effects accounting for >7% of phenotypic variance but much lower (0.42) in human-type pedigrees. Maternal or common environment effects can be partially confounded with dominance and must be fitted in the QTL model. Including dominance in the QTL model did not affect power to detect additive QTL effects. Also, detection of spurious dominance QTL effects only occurred when maternal effects were not included in the QTL model. When dominance effects were present in the data but not in the analysis model, this resulted in spurious detection of additive QTL or inflated estimates of additive QTL effects. The study demonstrates that dominance can be included routinely in QTL analysis of general pedigrees; however, optimal power is dependent on selection of the appropriate thresholds for pedigree structure.

Dissecting the genetic control of variation in complex traits, such as disease resistance and agricultural-product quality, remains very challenging. Farm animals are now well placed to bridge the gap between human biology and traditional model species. Livestock species share with model species the benefits of controlled breeding, and their biology is often much closer to that of humans. Genetic research in model species focuses on differences between homogenous lines, whereas genetic research in humans focuses on genetic variation within populations. Livestock genetics has the strengths of both human and model-species genetics because researchers can exploit both the abundant genetic variation between divergent breeds and the variation that is segregating within breeds. Therefore, livestock genomics fills the void where the genetics of model species proves intractable or where model species are not a good proxy for human biology.

For pedigree-based quantitative trait loci (QTL) association analysis, a range of methods utilizing within-family variation such as transmission-disequilibrium test (TDT)-based methods have been developed. In scenarios where stratification is not a concern, methods exploiting between-family variation in addition to within-family variation, such as the measured genotype (MG) approach, have greater power. Application of MG methods can be computationally demanding (especially for large pedigrees), making genomewide scans practically infeasible. Here we suggest a novel approach for genomewide pedigree-based quantitative trait loci (QTL) association analysis: genomewide rapid association using mixed model and regression (GRAMMAR). The method first obtains residuals adjusted for family effects and subsequently analyzes the association between these residuals and genetic polymorphisms using rapid least-squares methods. At the final step, the selected polymorphisms may be followed up with the full measured genotype (MG) analysis. In a simulation study, we compared type 1 error, power, and operational characteristics of the proposed method with those of MG and TDT-based approaches. For moderately heritable (30%) traits in human pedigrees the power of the GRAMMAR and the MG approaches is similar and is much higher than that of TDT-based approaches. When using tabulated thresholds, the proposed method is less powerful than MG for very high heritabilities and pedigrees including large sibships like those observed in livestock pedigrees. However, there is little or no difference in empirical power of MG and the proposed method. In any scenario, GRAMMAR is much faster than MG and enables rapid analysis of hundreds of thousands of markers.

Functional genomics has been applied to the genetic dissection of immune response in different ways: (1) experimental crosses between lines that differ in their (non-) specific immune response have been used to detect quantitative trait loci (QTL) underlying these differences. (2) The measurement of gene expression levels for thousands of genes using microarrays or oligonucleotide chips to identify differential expression with regard to antigen challenge: (a) before and after infection, (b) resistant versus susceptible lines, or (c) combinations of both. Interpretation of QTL results is hampered by the fact that confidence regions of the QTL are large and can contain hundreds of potential candidate genes for the QTL. At the same time, the microarray experiments tend to show large numbers of differentially expressed genes without identifying the relationships between these genes. In the recently proposed 'genetical genomics' framework, members of a segregating population are characterised for genome-wide molecular markers and for gene expression levels. This facilitates the mapping of expression-QTL (eQTL): loci in the genome that control the expression of genes. Initial applications of this approach are critically reviewed and potential applications of this approach with regard to immune response are presented.

We describe a genetic variation map for the chicken genome containing 2.8 million single-nucleotide polymorphisms (SNPs). This map is based on a comparison of the sequences of three domestic chicken breeds (a broiler, a layer and a Chinese silkie) with that of their wild ancestor, red jungle fowl. Subsequent experiments indicate that at least 90% of the variant sites are true SNPs, and at least 70% are common SNPs that segregate in many domestic breeds. Mean nucleotide diversity is about five SNPs per kilobase for almost every possible comparison between red jungle fowl and domestic lines, between two different domestic lines, and within domestic lines--in contrast to the notion that domestic animals are highly inbred relative to their wild ancestors. In fact, most of the SNPs originated before domestication, and there is little evidence of selective sweeps for adaptive alleles on length scales greater than 100 kilobases.

A whole-genome scan was conducted to map quantitative trait loci (QTL) for BSE resistance or susceptibility. Cows from four half-sib families were included and 173 microsatellite markers were used to construct a 2835-cM (Kosambi) linkage map covering 29 autosomes and the pseudoautosomal region of the sex chromosome. Interval mapping by linear regression was applied and extended to a multiple-QTL analysis approach that used identified QTL on other chromosomes as cofactors to increase mapping power. In the multiple-QTL analysis, two genome-wide significant QTL (BTA17 and X/Y(ps)) and four genome-wide suggestive QTL (BTA1, 6, 13, and 19) were revealed. The QTL identified here using linkage analysis do not overlap with regions previously identified using TDT analysis. One factor that may explain the disparity between the results is that a more extensive data set was used in the present study. Furthermore, methodological differences between TDT and linkage analyses may affect the power of these approaches., (Copyright 2004 Genetics Society of America)

In this article, the quantitative genetic aspects of imprinted genes and statistical properties of methods to detect imprinted QTL are studied. Different models to detect imprinted QTL and to distinguish between imprinted and Mendelian QTL were compared in a simulation study. Mendelian and imprinted QTL were simulated in an F2 design and analyzed under Mendelian and imprinting models. Mode of expression was evaluated against the H(0) of a Mendelian QTL as well as the H(0) of an imprinted QTL. It was shown that imprinted QTL might remain undetected when analyzing the genome with Mendelian models only. Compared to testing against a Mendelian QTL, using the H(0) of an imprinted QTL gave a higher proportion of correctly identified imprinted QTL, but also gave a higher proportion of false inference of imprinting for Mendelian QTL. When QTL were segregating in the founder lines, spurious detection of imprinting became more prominent under both tests, especially for designs with a small number of F1 sires.