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Homocysteine can be converted to cysteine via the transsulfuration pathway where cystathionine beta-synthase (CBS) is a rate-limiting enzyme. Homocysteine is thought to play a role in bone remodelling and strength. Previous results indicated that some of the difference in bone strength of end-of-lay hens may be associated with CBS expression level. To investigate if differences in the promoter region of the CBS gene might be responsible for observed differences in gene expression between CBS alleles post mortem- and in-vitro expression studies have been undertaken. Transfection of the DF-1 avian cell line with a series of deletion fragments of the 5′ promoter, or constructs containing three CBS allele sequences, with a luciferase reporter revealed that a core region of −155 to +131 bp in the CBS promoter was essential for mRNA expression. We found that a variable number of short tandem repeats (7 nucleotide motif and 6 nucleotide repeats) in the core region of the promoter affecting the transcriptional activity and a strong effect for gene expression. However, methylation of the 6 nucleotide repeats varied between allelic variants and these maybe responsible for differences in promoter activity. Our findings indicated variable short tandem repeats and the differentially methylated sites in the promoter region may be responsible for CBS expression differences in the bone of laying hens. • The region of −155–+131 bp in the CBS promoter was essential for gene transcript. • A VNTR in CBS promoter affects the transcriptional activity. • Methylation of the 6 bp repeats maybe responsible for different promoter activity. [ABSTRACT FROM AUTHOR]

This study aimed to gain insights about the status of the Swedish breeding program through studying key phenotypic traits. In total, 133 and 73 full-sib families were formed during the reproductive seasons of 2016 and 2019, respectively. Growth-related recordings were available from two occasions: ∼ 9 and 24–27 months post-hatch. A preliminary descriptive analysis of the fecundity and early embryo survival identified substantial differences in favor of G0 (year class 2016) which was partly explained by the fact that first-time 3-year-old spawners were used in G1 (year class 2019). Moderate to high heritability values (0.23–0.49) were obtained for body length and weight across both time points and generations. Furthermore, the prediction accuracy of the estimated breeding values was ∼0.65, while the expected genetic gain was 36 g per year. Overall, our results demonstrate the positive performance of the Swedish rainbow trout breeding program. [ABSTRACT FROM AUTHOR]

The article focuses on multi-parent populations (MPP) discussed in the journal Genetics. It is stated that a window into the impact of drift on the genomes has been provided by systematic monitoring of progress with the mouse collaborative cross. It is mentioned that data availability section that is standard for all GSA publications is included in each MPP paper in these issues.

Highlights: [•] Successful implementation of GS for crop breeding cannot be achieved by a ‘copy and paste’ of GS in dairy cattle. [•] The variety of crop breeding schemes presents challenges for implementation of GS. [•] GS will enhance the current phenotypic selection in crop breeding. [•] Current proposals for GS in crops will not reduce the generation interval. [ABSTRACT FROM AUTHOR]

The Collaborative Cross Consortium reports here on the development of a unique genetic resource population. The Collaborative Cross (CC) is a multiparental recombinant inbred panel derived from eight laboratory mouse inbred strains. Breeding of the CC lines was initiated at multiple international sites using mice from The Jackson Laboratory. Currently, this innovative project is breeding independent CC lines at the University of North Carolina (UNC), at Tel Aviv University (TAU), and at Geniad in Western Australia (GND). These institutions aim to make publicly available the completed CC lines and their genotypes and sequence information. We genotyped, and report here, results from 458 extant lines from UNC, TAU, and GND using a custom genotyping array with 7500 SNPs designed to be maximally informative in the CC and used a novel algorithm to infer inherited haplotypes directly from hybridization intensity patterns. We identified lines with breeding errors and cousin lines generated by splitting incipient lines into two or more cousin lines at early generations of inbreeding. We then characterized the genome architecture of 350 genetically independent CC lines. Results showed that founder haplotypes are inherited at the expected frequency, although we also consistently observed highly significant transmission ratio distortion at specific loci across all three populations. On chromosome 2, there is significant overrepresentation of WSB/EiJ alleles, and on chromosome X, there is a large deficit of CC lines with CAST/EiJ alleles. Linkage disequilibrium decays as expected and we saw no evidence of gametic disequilibrium in the CC population as a whole or in random subsets of the population. Gametic equilibrium in the CC population is in marked contrast to the gametic disequilibrium present in a large panel of classical inbred strains. Finally, we discuss access to the CC population and to the associated raw data describing the genetic structure of individual lines. Integration of rich phenotypic and genomic data over time and across a wide variety of fields will be vital to delivering on one of the key attributes of the CC, a common genetic reference platform for identifying causative variants and genetic networks determining traits in mammals. [ABSTRACT FROM AUTHOR]

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. [Copyright &y& Elsevier]

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 genoniewide 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 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. [ABSTRACT FROM AUTHOR]

Understanding how variation is controlled in complex traits is a major challenge. Combining forward and reverse genetics to study the gene expression signatures of quantitative trait loci and candidate genes has enabled the dissection of complex traits. However, this approach cannot be implemented in vivo in many species. The recent development of a cell-line-based connectivity map demonstrates that gene signatures can be conserved across tissues and species, and that in vitro approaches are relevant to the whole organism. Thus, we propose that the in vitro study of gene expression, using both natural variation and perturbations induced, for example, by RNA interference, might provide a rapid and effective method for complex trait dissection in many species, including humans. [Copyright &y& Elsevier]

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]

Genetical genomics has been proposed to map loci controlling gene-expression differences (eQTLs) that might underlie functional trait variation. We briefly review the studies in model species and conclude that, although they successfully demonstrate the utility of genetical genomics, they are too limited to unlock the full potential of this approach and some results should be interpreted with caution. We subsequently elaborate on two recent studies that use this approach in humans. The many differences between these studies complicate meaningful comparisons between them. A joint analysis of the two experiments offers some scope for more powerful genetical genomics. [Copyright &y& Elsevier]

Abstract: 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. [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]

Examines the quantitative genetic aspects of imprinted genes. Detection of imprinted quantitative trait loci; Analysis of the genome using Mendelian models; Influence of genomic imprinting on the genes and traits of animals.

Reports that the role of imprinting in body composition was investigated in an experimental cross between Chinese Meishan pigs and commercial Dutch pigs. Evidence for five quantitative trait loci affecting body composition revealed by a whole-genome scan.

Most commercial laying hens suffer from sternum (keel) bone damage including deviations and fractures. X-raying hens, followed by segmenting and assessing the keel bone, is a key to automating the monitoring of keel bone condition. The aim of the current work is to train a deep learning model to segment the keel bone out of whole-body x-ray images. We obtained full-body x-ray images of laying hens (n = 1,051) and manually drew the outline of the keel bone on each image. Using the annotated images, a U-net model was then trained to segment the keel bone. The proposed model was evaluated using 5-fold cross validation. We obtained high segmentation accuracy (Dice coefficients of 0.88–0.90) repeatably over several validation folds. In conclusion, automatic segmentation of the keel bone from full-body x-ray images is possible with good accuracy. Segmentation is a requirement for automated measurements of keel geometry and density, which can subsequently be connected to susceptibility to keel deviations and fractures. [ABSTRACT FROM AUTHOR]

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/m2 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. [ABSTRACT FROM AUTHOR]

The Arctic charr breeding programme has been a main driving force for developing the aquaculture industry in Sweden. Selection has been performed for almost 40 years using animals from a closed breeding nucleus. The aim of the current study was to evaluate the potential of further improving growth‐related traits taking into account the existence of genotype‐by‐environment interaction. Furthermore, we investigated the magnitude of the genetic component associated with survival to the eyed stage and potential associations with inbreeding coefficients. A preliminary heritability estimate of 0.23 (SE 0.20) was obtained for survival to the eyed stage using records spanning from 2000 to 2017 (n = 230). Moreover, moderate‐to‐high heritability estimates (0.27–0.49) were obtained for growth‐related traits (body weight and length), using animals from the latest generation of selection (year class 2017). Those animals (n = 2,776), originating from 55 full‐sib families, were split into two groups and reared in separate land‐based facilities of commercial fish farms in Sweden. The growth‐related traits were recorded twice in both sites when animals were of >1 and >2 years of age. Existence of sexual growth dimorphism was indicated with the males having on average 6%–8% higher total length and 22%–34% higher body weight. Furthermore, high genetic correlations regarding growth traits were obtained amongst animals reared at the two different sites (0.82–0.95). In addition, we assessed the accuracy of best linear unbiased prediction (BLUP)‐derived estimated breeding values (EBVs) when phenotypes from each rearing site were subsequently masked and used as a validation set. A mean prediction accuracy of 0.60 (length) and 0.64 (weight) were derived for both rearing sites. Overall, our results suggest that further growth improvements should be possible in the subsequent generations of selection. Finally, even though indications for the existence of an underlying genetic component(s) involved in survival to the eyed stage were obtained additional data will be required for elucidating its magnitude. [ABSTRACT FROM AUTHOR]

Rainbow trout is one of the most popular aquaculture species worldwide, with a long history of domestication. However, limited information exists about the genetic diversity of farmed rainbow trout populations globally, with most available reports relying on low‐throughput genotyping technologies. Notably, no information exists about the genetic diversity status of farmed rainbow trout in Sweden. Double‐digest restriction‐site‐associated DNA sequencing was performed on more than 500 broodfish from two leading producers in Sweden and from the country's national breeding program. Following the detection of single nucleotide polymorphisms (SNPs), genetic diversity was studied by using either individual SNPs (n = 8680; one SNP retained per 300 bp sequence reads) or through SNP haplotypes (n = 20 558; all SNPs retained in 300 bp sequence reads). Similar amounts of genetic diversity were found amongst the three populations when individual SNPs were used. Furthermore, principal component analysis and discriminant analysis of principal components suggested two genetic clusters with the two industry populations grouped together. Genetic differentiation based on the FST fixation index was ~0.01 between the industry populations and ~0.05 when those were compared with the breeding program. Preliminary estimates of effective population size (Ne) and inbreeding (based on runs of homozygosity; FROH) were similar amongst the three populations (Ne ≈ 50–80; median FROH ≈ 0.11). Finally, the haplotype‐based analysis suggested that animals from the breeding program had higher shared coancestry levels than those from the other two populations. Overall, our study provides novel insights into the genetic diversity and structure of Sweden's three main farmed rainbow trout populations, which could guide their future management. [ABSTRACT FROM AUTHOR]

The author highlights the value offered by society journals, specifically the "Genes," "Genomes" and "Genetics" from the Genetics Society of America (GSA). Topics covered include the ways in how these journals provide a voice and vehicle for practicing scientists to move science forward, the response of the GSA journals to the increased demands for open access data, and the commitment of the GSA to publishing reproducible science.

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. [ABSTRACT FROM AUTHOR]

The article offers information on the publication of articles in "Genetics" and "G3" periodicals on genomic selection including invitation for readers to participate in scholarly discussion about the topic.

The article discusses the role of society-sponsored journals in collaborative science. It recognizes society-sponsored journals as one of the most exciting resources for research. It cites the case of the journal "Genetics" that provides updates on the field. In addition, the article explains the importance data sharing to collaborations.

Background: Substantial variation in male fertility is regularly observed in farmed Arctic charr. However, detailed investigations of its fluctuation during a reproductive season and across years are lacking. Furthermore, information about the effect of underlying genetic factors influencing sperm quality is scarce. The current study focused on seasonal and age-related factors that may affect sperm quality characteristics in males reared in natural and delayed photoperiods. Animals were sampled three times for two consecutive years, and sperm quality parameters were recorded using a computer-assisted sperm analysis (CASA) system. Thereafter, high-throughput sequencing technologies were applied, aiming to identify genomic regions related to the variation of sperm quality throughout the reproductive season. Results: An across-season variation in the recorded sperm quality parameters was evident. Overall, 29% and 42% of males from the natural and delayed spawning groups had a highly variable total progressive motility. Males at four years of age showed significantly higher sperm motility and velocities during the early October and November recordings compared to the following year when the same animals were five years of age. On the other hand, the opposite was observed regarding sperm concentration during the last sampling. A genome-wide FST scan detected SNP differentiation among males with high and low variability in total progressive motility (PM) on eight chromosomes (FST > 0.17), Genome wide windows with the highest FST contained SNPs in proximity (within 250 kb up- and downstream distance) to 16 genes with sperm quality biological functions in mammalian species. Conclusion: Our findings provide a detailed view of seasonal, age-related, and genetic effects on sperm quality and can be used to guide decisions on broodstock selection and hatchery management. [ABSTRACT FROM AUTHOR]

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.

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. [ABSTRACT FROM AUTHOR]

Background Boar taint is an offensive urine or faecal-like odour, affecting the smell and taste of cooked pork from some mature non-castrated male pigs. Androstenone and skatole in fat are the molecules responsible. In most pig production systems, males, which are not required for breeding, are castrated shortly after birth to reduce the risk of boar taint. There is evidence for genetic variation in the predisposition to boar taint. A genome-wide association study (GWAS) was performed to identify loci with effects on boar taint. Five hundred Danish Landrace boars with high levels of skatole in fat (>0.3 μg/g), were each matched with a litter mate with low levels of skatole and measured for androstenone. DNA from these 1,000 non-castrated boars was genotyped using the Illumina PorcineSNP60 Beadchip. After quality control, tests for SNPs associated with boar taint were performed on 938 phenotyped individuals and 44,648 SNPs. Empirical significance thresholds were set by permutation (100,000). For androstenone, a 'regional heritability approach' combining information from multiple SNPs was used to estimate the genetic variation attributable to individual autosomes. Results A highly significant association was found between variation in skatole levels and SNPs within the CYP2E1 gene on chromosome 14 (SSC14), which encodes an enzyme involved in degradation of skatole. Nominal significance was found for effects on skatole associated with 4 other SNPs including a region of SSC6 reported previously. Genome-wide significance was found for an association between SNPs on SSC5 and androstenone levels and nominal significance for associations with SNPs on SSC13 and SSC17. The regional analyses confirmed large effects on SSC5 for androstenone and suggest that SSC5 explains 23% of the genetic variation in androstenone. The autosomal heritability analyses also suggest that there is a large effect associated with androstenone on SSC2, not detected using GWAS. Conclusions Significant SNP associations were found for skatole on SSC14 and for androstenone on SSC5 in Landrace pigs. The study agrees with evidence that the CYP2E1 gene has effects on skatole breakdown in the liver. Autosomal heritability estimates can uncover clusters of smaller genetic effects that individually do not exceed the threshold for GWAS significance. [ABSTRACT FROM AUTHOR]

Phenotypic variability of a genotype is relevant both in natural and domestic populations. In the past two decades, variability has been studied as a heritable quantitative genetic trait in its own right, often referred to as inherited variability or environmental canalization. So far, studies on inherited variability have only considered genetic effects of the focal individual, that is, direct genetic effects on inherited variability. Observations from aquaculture populations and some plants, however, suggest that an additional source of genetic variation in inherited variability may be generated through competition. Social interactions, such as competition, are often a source of Indirect Genetic Effects (IGE). An IGE is a heritable effect of an individual on the trait value of another individual. IGEs may substantially affect heritable variation underlying the trait, and the direction and magnitude of response to selection. To understand the contribution of IGEs to evolution of environmental canalization in natural populations, and to exploit such inherited variability in animal and plant breeding, we need statistical models to capture this effect. To our knowledge, it is unknown to what extent the current statistical models commonly used for IGE and inherited variability capture the effect of competition on inherited variability. Here, we investigate the potential of current statistical models for inherited variability and trait values, to capture the direct and indirect genetic effects of competition on variability. Our results show that a direct model of inherited variability almost entirely captures the genetic sensitivity of individuals to competition, whereas an indirect model of inherited variability captures the cooperative genetic effects of individuals on their partners. Models for trait levels, however, capture only a small part of the genetic effects of competition. The estimation of direct and indirect genetic effects of competition, therefore, is possible with models for inherited variability but may require a two‐step analysis. [ABSTRACT FROM AUTHOR]

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 Fst 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. [ABSTRACT FROM AUTHOR]

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]

As part of the QTLMAS XII workshop, a simulated dataset was distributed and participants were invited to submit analyses of the data based on genome-wide association, fine mapping and genomic selection. We have evaluated the findings from the groups that reported fine mapping and genomewide association (GWA) efforts to map quantitative trait loci (QTL). Generally the power to detect QTL was high and the Type 1 error was low. Estimates of QTL locations were generally very accurate. Some methods were much better than others at estimating QTL effects, and with some the accuracy depended on simulated effect size or minor allele frequency. There were also indications of bias in the effect estimates. No epistasis was simulated, but the two studies that included searches for epistasis reported several interacting loci, indicating a problem with controlling the Type I error rate in these analyses. Although this study is based on a single dataset, it indicates that there is a need to improve fine mapping and GWA methods with respect to estimation of genetic effects, appropriate choice of significance thresholds and analysis of epistasis. [ABSTRACT FROM AUTHOR]

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]

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]

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, FST 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. [ABSTRACT FROM AUTHOR]

Tilapia hatcheries in Tanzania rely heavily on importing germplasm. Nevertheless, the genetic structure of the imported stocks is poorly understood. In the current study, the level of genetic diversity and differentiation of eight populations of Nile tilapia (Oreochromis niloticus) strains imported in Tanzania was investigated. Four of the studied strains originated from Thailand, three from Uganda, and one from the Netherlands. Double-digest restriction site–associated DNA sequencing (ddRAD-seq) was applied to identify and genotype single nucleotide polymorphisms (SNPs). In total, 2214 SNPs passed all the quality control steps and were utilized for downstream analysis. Mean heterozygosity estimates were higher for the Thailand strains (Ho, 0.23) compared with the strains from Uganda (Ho, 0.12). Low genetic distance was observed amongst populations from the same geographic origin (Fst, 0.01–0.04). However, genetic distance between populations from different geographic origins was substantial (Fst, 0.24–0.44). Bayesian model–based clustering (STRUCTURE) and discriminant analysis of principal components (DAPC) grouped the studied animals into three distinct clusters. A cross-validation approach (where 25% of animals from each population were considered of unknown origin) was conducted in order to test the efficiency of the SNP dataset for identifying the population of origin. The cross-validation procedure was repeated 10 times resulting in approximately 97% of the tested animals being allocated to the correct geographic population of origin. The breeding history and hatchery practices used to manage these stocks prior and after import appear to be the main factors for the genetic diversity observed in this study. Our study will help inform hatchery stock management and future breeding program designs in Tanzania. [ABSTRACT FROM AUTHOR]

Natural antibodies (NAb) are produced without any antigenic stimulation as a part of the innate immune system and provide a first line of defense against pathogens. Hence, they may be a useful trait when estimating an animal's potential immune competence and in selection for disease resistance. The aim of this study was to identify genomic regions associated with different NAb traits in milk and potentially describe candidate genes. Milk samples from 1,695 first-lactation Holstein Friesian cows with titer measurements for keyhole limpet hemocyanin, lipopolysaccharide, lipoteichoic acid, and peptidoglycan-binding total NAb and isotypes IgG 1 , IgM, and IgA were used. Genome-wide association study analyses were performed using imputed 777K SNP genotypes, accounting for relationships using pedigree information. Functional enrichment analysis was performed on the significantly associated genomic regions to look for candidate genes. For IgM NAb, significant associations (false discovery rate <0.05) were found on Bos taurus autosome (BTA) 17, 18, and 21 with candidate genes related to immunoglobulin structure and early B cell development. For IgG 1 , associations were found on BTA3, and we confirmed a quantitative trait loci on BTA21 previously reported for IgG NAb in serum. Our results provide new insights into the regulation of milk NAb that will help unravel the complex relationship between milk immunoglobulins and disease resistance in dairy cattle. [ABSTRACT FROM AUTHOR]

Non-coagulating milk is a serious problem in the cheese industry, since it decreases cheese yield, resulting in decreased economic output. This study evaluated rennet-induced coagulation properties and composition of milk from individual Swedish Red Dairy Cattle. Milk samples from 679 individual cows were rheologically evaluated, of which 18.1% of the cows produced non-coagulating milk and 18.9% produced poor-coagulating milk. This resulted in 37% of the milk samples being non-optimal in cheese production, which is an alarmingly high figure. A comparison between non-coagulating and coagulating milk showed a significantly lower calcium content and less free Ca2+ in non-coagulating milk. The results provide more information about non- and poor-coagulating milk and will be further used to understand the genetic background of non-coagulating milk and breed against this undesired milk property. [ABSTRACT FROM AUTHOR]

Abstract Background Plant and animal breeding can contribute to promote human health by providing new and healthier food products that farmers can produce in an economically viable way and consumers will choose to buy and eat. However, this can only be achieved if breeding makes full use of knowledge about nutrition, consumer behaviour, farming and agricultural economics. A strategy is needed for breeding for public health. Scope and Approach A multidisciplinary group of researchers has developed a strategy for plant and animal breeding for public health. The group includes experts in plant breeding, animal breeding, food science, nutrition science, clinical nutrition, agricultural economics, consumer research, and ethics. Key Findings and Conclusions An outline is proposed of a strategy for breeding for public health. It aims at improving public health in both low- and high-income countries. To prevent chronic disease, the highest priority should be to develop healthy variants of traditional food items that can be introduced universally, i.e. completely replace the older, less healthy variants. In particular in low-income countries, food products with enhanced micronutrient content are urgently needed. In all countries, crops with improved fatty acid composition can contribute substantially to improved public health. A reasonable second priority is products that may not be suitable for universal introduction but will expectedly be demanded by large groups of consumers. One example could be diminishing the energy density of traditional foodstuffs by reducing their fat, sugar, and starch content and increasing their dietary fibre content. Changes in the current organization of the market for farm products are needed to encourage the production of healthier foodstuffs. Highlights • A strategy is proposed for breeding for public health. • The first priority is healthy products that can be introduced universally. • The second priority is other healthy products with expected consumer demand. • Oils and fats with improved fatty acid composition exemplify the first priority. • Crops with lower energy density and more dietary fibre exemplify the second priority. [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]

The identification of genetic markers for traits of interest for aquaculture, such as growth, is an important step for the establishment of breeding programmes. As more genomic information becomes available the possibility of applying comparative genomics to identify and refine quantitative trait locus (QTLs) and potentially identify candidate genes responsible for the QTL effect may accelerate genetic improvement in established and new aquaculture species. Here we report such an approach on growth related traits in the European sea bass ( Dicentrarchus labrax ), an important species for European aquaculture. A genetic map was generated with markers targeted to previously identified QTL for growth which reduced distance and improved resolution in these regions. A total of 36 significant QTLs were identified when morphometric traits were considered individually in maternal half sibs, paternal half sibs and sib-pair analysis. Twenty seven new markers targeted to the growth QTLs, obtained by comparative mapping, reduced the average distance between markers from 23.4, 9.1, and 5.8 cM in the previous map to 3.4, 2.2, and 5.2 cM, on linkage group (LG) LG4, LG6 and LG15 respectively. Lists of genes embedded in the QTL – 591 genes in LG4, 234 genes in LG6 and 450 genes in LG15 – were obtained from the European sea bass genome. Comparative mapping revealed conserved gene synteny across teleost fishes. Functional protein association network analysis with the gene products of the 3 linkage groups revealed a large global association network including 42 gene products. Strikingly the association network was populated with genes of known biological importance for growth and body weight in terrestrial farm animals, such as elements of the signaling pathways for Jak–STAT, MAPK, adipocytokine and insulin, growth hormone, IGFI and II. This study demonstrates the feasibility of a comparative genomics combined with functional gene annotation to refine the resolution of QTL and the establishment of hypothesis to accelerate discovery of putative responsible genes. Statement of relevance This study demonstrates the feasibility of a comparative genomics approach, combined with functional annotation to refine the resolution of QTL and establishment of hypothesis to accelerate discovery of candidate genes. As production of genomic data is becoming more accessible, the implementation of this strategy will rapidly and efficiently provide the tools required for genetic selection in new candidate aquaculture species. [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]

No abstract available [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Genetical genomics has been suggested as a powerful approach to study the genotype--phenotype gap. However, the relatively low power of these experiments (usually related to the high cost) has hindered fulfillment of its promise, especially for loci (QTL) of moderate effects. One strategy with which to overcome the issue is to use a targeted approach. It has two clear advantages: (i) it reduces the problem to a simple comparison between different genotypic groups at the QTL and (ii) it is a good starting point from which to investigate downstream effects of the QTL. In this study, from 698 F2 birds used for QTL mapping, gene expression profiles of 24 birds with divergent homozygous QTL genotypes were investigated. The targeted QTL was on chromosome 1 and affected initial pH of breast muscle. The biological mechanisms controlling this trait can be similar to those affecting malignant hyperthermia or muscle fatigue in humans. The gene expression study identified 10 strong local signals that were markedly more significant compared to any genes on the rest of the genome. The differentially expressed genes all mapped to a region,1 Mb, suggesting a remarkable reduction of the QTL interval. These results, combined with analysis of downstream effect of the QTL using gene network analysis, suggest that the QTL is controlling pH by governing oxidative stress. The results were reproducible with use of as few as four microarrays on pooled samples (with lower significance level). The results demonstrate that this cost-effective approach is promising for characterization of QTL. [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]

Abstract: The gilthead seabream (Sparus aurata) is an important aquaculture species that has only been subject to an incipient selective breeding programme. This study, which examined the genetic architecture of seabream morphology and stress response to confinement, takes a step toward the use of marker assisted selection in this species. Major loci affecting these traits were mapped, using data from 460 offspring derived from seven paternal and 73 maternal half-sib families. Fish were killed following a four-hour confinement experiment to induce stress, after which 15 morphometric measurements were collected and blood was sampled for DNA extraction and plasma cortisol level determination. Heritabilities for the morphometric traits were moderate to high (0.24–0.58), with genetic and phenotypic correlations between the traits generally very high. However, the heritability of plasma cortisol level was not significantly different from zero. A population-specific genetic linkage map was built for 56 microsatellite markers, comprising 16 linkage groups (LG) and ten unlinked markers. Half-sib and variance components QTL analyses detected a single genome-wide significant QTL (SaimbcF7b), a single unlinked marker explaining 13–23% of the phenotypic variance in the majority of the morphometric traits. Several other putative QTL were identified for morphometric traits (on LG 4a, 7, 9, 18, A, C, F and I), along with two other QTL (LG10 and B) that were suggestive for stress response. Fitting body weight as a covariate for the morphometric traits resulted in three genome-wide significant QTL affecting aspects of body shape independent of overall body size. For stress response we only identified suggestive evidence for QTL. These findings contribute to understanding the genetic regulation of important economic traits in seabream. [Copyright &y& Elsevier]

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. [ABSTRACT FROM AUTHOR]